thesis on health seeking behaviour

Understanding health seeking behavior

Journal of Family Medicine and Primary Care 5(2):463
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Health-Seeking Behaviors and its Determinants: A Facility-Based Cross-Sectional Study in the Turkish Republic of Northern Cyprus

Affiliation.

1 Medical Faculty, Near East University, Nicosia,TRNC, Turkey.
PMID: 32613792
PMCID: PMC7382910
DOI: 10.15171/ijhpm.2019.106

Background: Understanding health-seeking behaviors and determining factors help governments to adequately allocate and manage existing health resources. The aim of the study was to examine the health-seeking behaviors of people in using public and private health facilities and to assess the factors that influence healthcare utilization in Northern Cyprus.

Methods: A cross-sectional study was conducted in 2 polyclinics among 507 people using a structured intervieweradministered questionnaire. Health-seeking behaviors were measured using four indicators including routine medical check-ups, preferences of healthcare facilities, admission while having health problems, and refusal of health services while ill. Descriptive statistics and multivariable logistic regression analyses were done to explore factors influencing the use of health services.

Results: About 77.3% of the participants reported to have visited health centers while they had any health problems. More than half (51.7%) of them had a routine medical check-up during the previous year, while 12.2% of them had refused to seek healthcare when they felt ill during the last five years. Of all, 39.1% of them reported preferring private health services. Current smokers (adjusted odds ratio [AOR]=1.92, 95% CI: 1.17-3.14), having chronic diseases (AOR=2.05, 95% CI: 1.95-2.16), having poor perceptions on health (AOR=2.33; 95% CI: 1.563.48), and spending less on health during the last three months (AOR=2.08, 95% CI: 1.43- 3.01) had about twice the odds of having routine checkups. Higher education (AOR=1.87, 95% CI: 1.38-2.55) was shown to be a positive predictor for the health-seeking behaviors, whereas having self-care problems (AOR=0.18, 95% CI: 0.08-0.40) and having a moderate-income (AOR=0.68, 95% CI: 0.57-0.81) were inversely associated with seeking healthcare.

Conclusion: The utilization of public and private health sectors revealed evident disparities in the socio-economic characteristics of participants. The health-seeking behaviors were determined by need factors including chronic disease status and having poor health perception and also by enabling factors such as education, income, insurance status and ability to pay by oneself. These findings highlight the need for further nationwide studies and provide evidence for specific strategies to reduce the socioeconomic inequalities in the use of healthcare services.

Keywords: Determinants; Health Seeking Behaviors; Health Utilization; Northern Cyprus; Polyclinics.

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Open Access

Peer-reviewed

Research Article

Health knowledge and care seeking behaviour in resource-limited settings amidst the COVID-19 pandemic: A qualitative study in Ghana

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Epidemiology and Biostatistics, School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana

Roles Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing

Affiliation Department of Population and Behavioural Sciences, School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana

Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing

Affiliations Department of Population and Health, University of Cape Coast, Cape Coast, Ghana, College of Public Health, Medical and Veterinary Services, James Cook University, Townsville, Australia

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

Affiliation International Institute of Rural Health, College of Social Science, University of Lincoln, Lincoln, United Kingdom

Farrukh Ishaque Saah,
Hubert Amu,
Abdul-Aziz Seidu,
Luchuo Engelbert Bain

Published: May 5, 2021
https://doi.org/10.1371/journal.pone.0250940
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The emergence of a pandemic presents challenges and opportunities for healthcare, health promotion interventions, and overall improvement in healthcare seeking behaviour. This study explored the impact of COVID-19 on health knowledge, lifestyle, and healthcare seeking behaviour among residents of a resource-limited setting in Ghana.

This qualitative study adopted an exploratory design to collect data from 20 adult residents in the Cape Coast Metropolis using face-to-face in-depth interviews. Data collected were analysed thematically and statements from participants presented verbatim to illustrate the themes realised.

Health knowledge has improved due to COVID–19 in terms of access to health information and increased understanding of health issues. There were reductions in risky health-related lifestyles (alcohol intake, sharing of personal items, and consumption of junk foods) while improvements were observed in healthy lifestyles such as regular physical exercise and increased consumption of fruits and vegetables. COVID–19 also positively impacted health seeking behaviour through increased health consciousness and regular check-ups. However, reduced healthcare utilization was prevalent.

The COVID–19 pandemic has presented a positive cue to action and helped improved health knowledge, lifestyle, and care seeking behaviour although existing health system constrains and low economic status reduced healthcare utilization. To improve health systems, health-related lifestyles and healthcare seeking behaviour as well as overall health outcomes even after the pandemic wades off, COVID–19 associated conscious and unconscious reforms should be systematically harnessed.

Citation: Saah FI, Amu H, Seidu A-A, Bain LE (2021) Health knowledge and care seeking behaviour in resource-limited settings amidst the COVID-19 pandemic: A qualitative study in Ghana. PLoS ONE 16(5): e0250940. https://doi.org/10.1371/journal.pone.0250940

Editor: Kingston Rajiah, International Medical University, MALAYSIA

Received: February 22, 2021; Accepted: April 18, 2021; Published: May 5, 2021

Copyright: © 2021 Saah et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

SARS-CoV-2, also called COVID–19, emerged as a new strain of Coronaviruses after a cluster of patients were identified with pneumonia suspected to be novel coronavirus pneumonia in December 2019 in Wuhan, China [ 1 , 2 ]. On March 11, 2020, the World Health Organization (WHO) declared COVID-19 as a global pandemic [ 3 ]. As of February, 7, 2021, 106.7 million confirmed cases and over 2.3 million deaths were recorded cumulatively worldwide since the start of the pandemic [ 4 ]. In Ghana, 70,046 confirmed cases and 449 confirmed deaths were recorded [ 4 ].

The increasing burden of COVID-19 has resulted in various international and national level decisions and protocols, shaped largely by initial responses by high-income countries aimed at ending the pandemic [ 5 ]. These protocols include physical/social distancing, wearing of face masks, frequent hand washing with soap, stay-at-home/work-at-home, closure of schools, international travel bans, and economic lockdown of non-essential businesses together with isolation of infected persons and quarantining of exposed individuals [ 5 – 7 ]. With the recent vaccine breakthrough, vaccination is expected to soon become a bigger tool to the fight against COVID-19 [ 8 , 9 ].

The emergence of COVID-19 has deepened the strain on health systems across the globe more especially the already overburdened health systems of resource-limited countries with 90% of countries in five WHO regions experiencing disruptions to their health services [ 10 ]. The greatest difficulties are reported by low- and middle-income countries [ 10 ]. In fact, poor health system capacity in such countries makes them highly vulnerable to COVID-19 [ 11 ]. Many people in sub-Saharan Africa (SSA) for instance, often lack ready access to clean water for regular hand washing, have poor sanitation, limited to no internet connection for home work and schooling, and little or no savings to support loss of income [ 12 ]. Again, in SSA including Ghana, many of the healthcare and public health systems are compromised by inadequate equipment for the care of COVID–19 patients like intensive care unit (ICU) beds, bedside oxygen supply, pulse oximeters, ventilators, and personal protective equipment [ 5 ].

Healthcare seeking behaviour (HSB) of a population serves as one major determinant of the health status of a country and thus, its socio-economic development [ 13 ]. HSB encompasses a people’s inaction, procrastination or action undertaken following recognition by themselves of departing from good health or having a particular health problem to finding appropriate remedy to restore health [ 14 ]. There is predominantly poor healthcare seeking behaviour among populations in SSA countries like many other low-and middle-income countries [ 15 ]. Poor health seeking behaviour is likely to be deepened with the COVID–19 pandemic because delay in seeking care has been identified to contribute to increased morbidity, mortality and worse health outcomes among patients [ 13 , 16 ].

Although the COVID-19 pandemic has placed many challenges on health systems worldwide, it has also presented opportunities to re-direct resources to many health promotion interventions and activities where lacking. For instance, the Ghana Health Service (GHS) has intensified public health education across the country using various media. However, the impact of the pandemic and its accompanying national prevention protocols and health education activities have on the health knowledge, behaviours and care seeking behaviour of the population has not been investigated. We thus, explored the effect of the COVID-19 pandemic and health education intervention on the healthcare seeking behaviour of residents in a peri-urban community in Ghana.

Conceptual framework

We adapted Andersen’s Healthcare Utilization Model (HUM) propounded in 1968 [ 17 ]. The conceptualization of healthcare utilization by this model acts on the assumption that a person’s use of health service is influenced by three key factors, namely, predisposing factors, enabling factors, and the need for care factors [ 17 , 18 ], incorporating both contextual and individual level predictors [ 19 ]. There are three main tenets of the theory. These are predisposing, enabling, and need factors ( Fig 1 ). The tenets adequately explain the various factors influencing health seeking behaviour amidst the COVID-19 pandemic.

PPT PowerPoint slide
PNG larger image
TIFF original image

Source: Adapted from Andersen and Davidson [ 21 ].

https://doi.org/10.1371/journal.pone.0250940.g001

The predisposing factors refer to individual level predictors comprising sociodemographic characteristics such as sex, age [ 20 ], religion, education, ethnicity, attitude towards health, and social relations, health beliefs [ 18 , 19 ] and contextual factors like social and demographic composition of communities, organisational and collective values, political perspectives and cultural norms. Health knowledge is covered in this tenet as a factor to healthcare behaviours as it shapes beliefs, attitudes, and overall understanding of implications of a specific health behaviour.

According to Andersen and Davidson [ 20 ], enabling factors are organisational and financial factors considered to directly affect access to healthcare as well as access to health knowledge and subsequent use of health service [ 20 , 21 ]. In the context of this study, enabling factors at the individual level include wealth and income at the individual’s disposal to cover the cost of assuming positive health-related lifestyles such as good nutrition, physical exercising, wearing face mask and good hand hygiene [ 19 ]. They also include travel time to the health facility, the means of transportation, and waiting time for healthcare [ 21 ]. In addition, health education and outreach programmes and health policies are factors during this COVID-19 pandemic relevant to individual health behaviour and subsequent healthcare seeking attitude [ 20 , 21 ].

Furthermore, the need factors refer to individual and contextual level perceptions of the seriousness of a disease or health condition [ 21 , 22 ]. At the individual level, the model distinguishes between perceived need for health services (how people perceive and experience their own health status (self-rated health), functional state and illness symptoms) and evaluated need (objective measurements of patients’ health status and professional assessments, and need for medical care) [ 20 , 21 ]. Again, contextually, individuals make a differentiation between population health indices such as current COVID-19 infection rate, death rates and overall incidence and prevalence nationally and locally [ 21 ]. More so, overall measurements of community health, including epidemiological indicators of COVID-19 morbidity and mortality [ 22 ] influence healthcare seeking behaviour.

Despite the few flaws of this model such as disregard for sociocultural dimensions and interactions and omission of social construction of need [ 23 ], as well as inadequacy in forestalling service use as predisposing factors might be exogenous and enabling resources are necessary [ 24 ], it was considered relevant to this study. This is because its tenets are in line with the study and has the strength of indicating both the micro (individual) and the macro (community) level factors that influence healthcare seeking behaviour. It thus, fits well with the study’s objective of assessing impact of the COVID-19 pandemic on the health knowledge and behaviours and subsequent care seeking behaviours of individuals.

Materials and methods

Study design.

This was an exploratory study adopting qualitative approach. The design allowed for exploring care seeking behaviour by gathering in-depth information through interviews [ 25 ]. The design was chosen because it helped to gain in-depth insight on care seeking behaviour amidst COVID-19 with little to no earlier studies to rely upon to predict an outcome for later investigations [ 26 , 27 ]. It is also flexible and helps address all types of research questions such as the what, why, and how of a phenomenon [ 25 , 26 ]. The study also used the interpretivist philosophy due to this philosophy’s ability to explain how people create and maintain their own social worlds and understanding through personal interpretations of their worlds [ 28 ]. The Consolidated Criteria for Reporting Qualitative Research (COREQ) guideline was followed in reporting this study [ 29 ].

Study setting

The study was carried out in the Cape Coast Metropolis of Ghana. The metropolis is one of the 23 administrative districts in the Central Region and its capital, Cape Coast is also the regional capital. The metropolis lies between longitude 1°15ˈW and latitude 5°06ˈN with boundaries to the South by the Gulf of Guinea, to the East by Abura Asebu Kwamankese District, to the West by Komenda Edina Eguafo Abrem Municipality, and the North by Twifu Heman Lower Denkyira District. It has a population of 169,894 (7.7% of the region’s total population) with 48.7% being males according to the 2010 population and housing census [ 30 ]. Also, 90% of the population aged 11 years or older are literate with 67.2% capable of writing and reading English and other Ghanaian languages. Again, 69.5% of the population aged 12 years and above use mobile phones with 32% having access to internet service [ 30 ]. The metropolis also has a regional/teaching hospital, and a district hospital among other health facilities including clinics, health centres, and Community Health and Planning Services (CHPS) compounds.

Study population and sampling

Adult residents in the Cape Coast Metropolis were the study population and were selected using a purposive sampling approach. Only residents aged 18 years and above who had lived in the metropolis for at least six months within the period of COVID-19 pandemic in Ghana were included in the study. The six months inclusion criterion was to ensure that the study included only persons who experienced COVID-19 within the period from April to September 2020 when effects of the COVID-19 pandemic were heavily felt within the Cape Coast Metropolis as COVID-19 case count increased abruptly making the Central Region the third highest region in terms of case prevalence in the country.

The purposive sampling approach allowed us to select only participants who have experienced living in a district with significant COVID-19 cases. Recruitment of participants was done progressively until no new issues were emerging from additional interviewees. Data saturation was achieved after interviewing 20 participants (10 males and 10 females).

Data collection instruments and procedures

Data were collected face-to-face using an in-depth interview guide. The instrument was self-developed and sectioned into four. While section A collected socio-demographic information of the participants, section B, C, and D, focused on the impact of COVID-19 pandemic on health knowledge, health behaviours, and care seeking behaviours, respectively. The key questions contained in the guide included effects of COVID-19 pandemic on: access to health information, understanding and knowledge of selected health issues, risky health behaviours, adoption of preventive health behaviours like healthy diet and physical exercise, health consciousness, access and use of healthcare services. The questions were generated from literature review and the conceptual framework.

The interviews were conducted at the participants’ convenience with support from two trained research assistants who were experienced qualitative researchers with a minimum of bachelor’s degree and fluent Fante speakers. Two of the authors who are qualitative research experts, HA and FIS also conducted some of the interviews. The interviews were conducted in Fante, dialect of a major Akan language group predominant in the Cape Coast Metropolis for participants who could not speak or understand English while some were conducted in English. Consequently, the instrument was translated into the Fante language during the two-day training of the research assistants to ensure consistency in translating from English to Fante during interviews. Each interview was between 30–45 minutes and was tape recorded with the consent of the participants. Also, field notes were taken in order to corroborate the transcriptions from the recorded audios.

Ethical issues

The study obtained approval from the Cape Coast Metropolitan Health Directorate. Prior to inclusion in the study, written informed consent was obtained from the study participants after the study purpose and procedures were explained to them. In effort to protect the study participants and interviewers, the COVID-19 prevention measures of wearing face mask, physically/socially distancing, and using hand sanitizers were ensured. Anonymity was ensured by using pseudonyms combing letters and numbers to identify each participant instead of their personal identifying details. Also, the study data has been stored and password-protected on the personal computer of the corresponding author without access to any third parties to ensure confidentiality.

Data analyses

All the audio recordings were transcribed and those in Fante and Twi (local dialects of the Akan language) were translated and transcribed into English. While listening to the tapes and using the field notes taken, the transcripts were read and edited to resolve any omissions and mistakes in the original transcripts. Thematic analysis was carried out using NVivo version 10 by first re-reading the transcripts to help familiarize with the data [ 31 ]. Initial codes were produced by two of the authors (FIS and HA) from list of ideas found to be interesting and relevant in the data which were later organized into meaningful groups [ 32 ]. The generated codes were sorted out and merged to form potential themes [ 31 ] based on the research objectives, namely; impact of COVID-19 pandemic on health knowledge, health behaviours and care seeking behaviour; and on literature review and emergent themes. The initial themes were reviewed and refined into final themes taking into consideration internal homogeneity (ensuring everything in a theme is similar) and external heterogeneity (ensuring different contents in different themes) [ 33 ]. The themes were defined and named and detailed analysis conducted and written based on how they fit into the broader story of the data. The final step involved full write-up of the report ensuring merit and validity of the analysis using extracts from the data which capture the essence of each theme being demonstrated [ 31 ].

Table 1 presents the themes and sub-themes of the results. Two sub-themes were identified for the impact of COVID-19 on health knowledge whiles there were three sub-themes for the impact of COVID-19 on health-related lifestyles and two for healthcare seeking behaviour.

https://doi.org/10.1371/journal.pone.0250940.t001

Impact of COVID-19 pandemic on health knowledge

The study explored impact of COVID-19 pandemic on health knowledge among participants which found two main positive impacts namely; increased access to health information and improved health knowledge related to chronic diseases, nutrition, hygiene, and risky health behaviours. Regarding increased access to health information, the participants explained that due to the pandemic, many health education activities were ongoing on various media platforms including television and radio stations, community information centres and social media. Mass media, that is, radio and television stations and community information centres, are major platforms used in health education and promotion [ 34 , 35 ] due to their availability to majority of Ghana’s population (69% of women and 80% of men are exposed to radio alone) [ 36 ]. This education aimed at not just educating the public on the pandemic but other health issues that were pertinent to transmission of the infection and risk of complications associated with the COVID-19 disease. Also, these education sessions allowed their consumers to participate through text messages and phone calls. For instance, a 36-year-old man said, “ Oh , due to Covid many education activities are ongoing on both tv and radio . … and it is helping with getting information like this . ” Another participant, 28-year-old woman noted, “Now , most of them (television and radio stations) have health education sessions trying to educate the public on the Covid and how to protect ourselves . Even other health issues like hypertension are discussed . ”

Also, a 42-year man stated;

For those of us who don’t know much about internet , we now get almost all health information we need to prevent health conditions from the regular media like tv and radio . We get to call in to ask questions and they answer us . And the good thing is that it’s in Fante .

Concerning improved health knowledge due to the COVID-19 pandemic, the participants argued that increased access to health information during this pandemic has resulted in better understanding of many health issues. Some also explained that they now understand how to prevent some health conditions like diabetes, hypertension and infectious diseases and how to boost the immune system. Chronic conditions like diabetes and hypertension were noted to dominate many health education programmes due to their increased risk of complications and deaths from COVID-19 with their preventive measures such as healthy diet and increased physical exercise highlighted. Explaining improvement in health knowledge due to COVID-19 pandemic, a 38-year-old woman said, “I now understand that I need to be careful of types of food I eat , do physical exercises , and not consume alcohol in order to reduce my chances of getting these conditions . ”

A male participant, 29-years old, also noted, “ Now , I know that too much alcohol consumption will likely lead to hypertension and other conditions for life . Initially , I didn’t understand why people make a fuss about others drinking alcohol . ” Again, a 47-year-old woman further added;

We just eat anything we have at home without regards to whether it improves or destroys our health , we just eat . But now , I know that food is like medicine and when we take lot of fruits and vegetables , we become stronger against diseases .

Impact of COVID-19 pandemic on health-related lifestyles

We explored the impact of COVID-19 on the health-related lifestyles among the participants. Three positive impacts of COVID-19 pandemic on lifestyle choices were observed, namely; stopped/reduced risky behaviours, started physical exercising, and started/increased consumption of fruits and vegetables. It was explained by the participants that their increased knowledge and perceived threat of the COVID-19 pandemic have made them assumed positive health-related lifestyles while others have quit risky behaviours such as alcohol intake, sharing of personal items, and consumption of junk foods. The participants explained that they had initiated or increased their consumption of fruits and vegetables and physical exercises as understanding their importance has dominated ongoing health education programmes. Thus, the perceived need to assume this positive health behaviours had improved leading to their decision to apply these health choices. A 40-year-old woman for instance, said; “Understanding that eating fruits and vegetables helps our body protect against disease in the midst of this Covid , now at least every two days we take banana , oranges and pineapples as part of our dinner .” A 28-year-old man also posited;

Oh , as for now , every weekend I and my ‘boys boys’ go for jogging and sometimes visit the gym to exercise because we understand exercising will keep us healthy and stronger . Our bodies will be strong to fight disease . Previously , aside some community football once a while , I hardly exercised .

Some of the participants also explained that the pandemic has impacted on their quitting risky behaviours such consumption of junk foods and alcohol. They argued they have stopped or reduced these behaviours due to their improved understanding of risks associated these behaviours and subsequent increased likelihood of complications and death should they be infected with the COVID-19 infection. Explaining this, a 25-year-old woman said;

I used not to cook regular meals at home because I mostly buy “indomie” from the fast-food joint in the evening . But I no longer buy that they said such food increases the risk of chronic conditions and subsequent vulnerability to severe complications should I unluckily get Covid . I eat healthier foods now .

Also, a 38-year-old man explained, “We’re all afraid of being in such conditions (severe COVID-19 illness) due to smoking and alcohol consumption . You know the Covid is everywhere . I have actually reduced my intake of alcohol now . ”

Impact of COVID-19 pandemic on healthcare seeking behaviour

COVID-19 pandemic positively impacted health seeking behaviour among some of the study participants. Positive effect on their healthcare seeking behaviour was explained to be due to the fear of contracting the complicated form of the disease and improved health knowledge. Two aspects of care seeking behaviour were identified to have improved, namely health consciousness and regular medical check-up. Some of the participants posited that they are now more conscious of their health due to improved health knowledge during this period and the need to avoid a health condition taking them by surprise. While some argued that anyone can contract the COVID-19 virus with the rising number of cases as such, they would not want to have the severe form of the disease due to some underlying health conditions, others attributed this to their improved knowledge of health conditions such as diabetes and hypertension. The following quotes summarise their views:

As for me , now every small thing (physical symptoms) then I feel I need to go to the clinic to check what is the problem . Who knows it could be Covid or some other condition that can worsen my survival should I contract the Covid . –Female, 39 years I come into contact with many different people while going to work so anything can happen . So , now even small headache or cough then I go to hospital to check what is going on . –Male, 43 years

Regarding assuming regular health check-ups as an impact of the COVID-19 pandemic, some participants explained that they now understand the risks of chronic diseases like diabetes and hypertension and that the conditions can be managed well when detected early. As such, they now go for regular blood pressure and blood glucose level checks to help diagnose or ascertain risk of hypertension and diabetes contrary to before the pandemic where these are done only when they were seriously ill. A 44-year-old woman for example noted, “I have started going for the nurse at the facility to check my BP at least once a month . By that , if I am found to have pressure (hypertension) then they can help me . ”

Also, a 51-year-old man said;

I know I have pressure (hypertension) but normally unless I feel very sick or need to go for new drugs that I go to the hospital–they check me before giving me my monthly drugs . But now , I go to the small clinic here every two weeks to check and even check for diabetes too . –Male, 51 years

Furthermore, a significant number of the study participants had negative experiences leading to poor healthcare seeking behaviour as a result of the impact of COVID-19 in terms of negative reception at the facility and poor access to care. Negative reception is explained to mean health professionals applying high-level infection prevention protocols alerted by patients presenting with symptoms such as cough and flu, symptoms also associated with the COVID-19 infection. This the framework considers as health system-related factor to health behaviour. Some participants explained that for fear of being treated like someone infected with COVID-19, they do not go to the health facility with symptoms like cough, flu and fever. For instance, a 33-year-old woman said;

When I have symptoms like cough or flu , I am unable to go to the hospital because I feel I will be mistakenly treated like someone with the disease (COVID-19) . I would rather get some drugs from the drugstore and stay home .

For others, poor health seeking behaviour is as a result of the fear of coming into contact with COVID-19 infected person or health professional when they visit the health facility. This is due to limited space at the health facilities and sometimes non-adherence to infection prevention protocols such as sanitizing of hands and equipment between patients, increasing risk of direct or indirect contact with the COVID-19 virus. Limited space and risk of nosocomial infection are health system barriers to positive healthcare seeking behaviour as argued in the framework. A 41-year-old man noted;

What if the person sitting by me at the OPD–sometimes it gets very crowded–has the disease (COVID-19) or the nurse has touched someone who have the disease (COVID-19) ? I can get infected so for me unless my condition is serious needing to visit the hospital , I will not go .

Again, inability to adhere to COVID-19 protocol of facemask wearing was cited to have resulted in poor healthcare seeking behaviour. Some participants argued that one may sometimes forget the face mask at home in the quest of rushing to seek care or may not be able to buy the mask but without the mask, they will not be allowed to enter the health facility to seek care. These barriers, negative health attitude and poor socio-economic status, are considered predisposing factors in the framework. Explaining this, a 38-year-old woman stated;

Sometimes the only money you have is what to take a car to the hospital and something small to add up for drugs because you are lucky to have (health) insurance . How do you use same money to buy nose mask ? But without it you will not be allowed to enter the hospital .

Also, a 47-year-old woman noted, “…sometimes due to how you’re feeling because of the sickness , you may be in a rush to go to the clinic . But should you forget the (face) mask , you will be denied entry to the place . ”

Additionally, male partner involvement in antenatal care (ANC) was found to be poor due to the impact of the COVID-19 pandemic. A participant explained that male partner involvement at ANC has reduced because of the COVID-19 pandemic citing restriction of male partners by nurses and midwives due to limited space at the facility. Limited space at ANC is a common constrain to male partner involvement in Ghana [ 37 ] even before the COVID-19 pandemic. He, 37-year-old, said;

Now , they don’t allow us (men) to be with our wives at ANC–we have to wait for them outside or stay in our cars till they are done . The workers say the place is small so due to social distancing , we should stay outside . What then is the use of coming with my partner ? Most of us (men) have stopped going with our wives now . It’s not good .

This qualitative study explored the impact of COVID-19 on health knowledge, health-related lifestyles and health seeking behaviour among adults in the Cape Coast Metropolis. We found that the pandemic has resulted in improved health knowledge and health behaviours. Similarly, healthcare seeking behaviour has improved although many people have been negatively affected especially due to the restrictions put in place to control the spread of the COVID-19 infection.

Our study found that the pandemic has resulted in improved health knowledge among the population. This is consistent with the intensive public health education including preventive behavioural change messages being disseminated through various media (television, radio, print media, and social media) across Ghana [ 38 , 39 ]. This could have resulted from the use of creative arts in translating COVID-19 information in ways that people are able to connect emotionally to create social awareness thereby, strengthening COVID-19 public health communication through improved public understanding [ 40 ]. The measures to controlling the COVID-19 pandemic in Ghana have used health education and literacy to improve access to health information [ 41 ] using mass media to establish local information networks and adapting educational messages to community beliefs and concerns [ 42 ]. In relation to the conceptual framework, health knowledge is argued to be predisposing factor which influences an individual’s health behaviour [ 18 ] while its access is considered an enabling factor to behaviour change [ 23 ]. Hence, the increases access to health knowledge due to numerous health education campaigns during the pandemic has improved individual’s predisposition to positive health behaviour, understanding of health issues.

Regarding the finding that health-related lifestyles had improved among the participants, Brauer [ 43 ] posits that during pandemic including COVID-19, people change their behaviours. Assumption of positive behaviours has been argued to result from increased access to and magnitude of health informational campaigns which leads to effective and fast behavioural modifications [ 44 , 45 ]. Thus, this finding supports the argument that adaptive and protective behaviour change in response to pandemic should be encourage [ 46 ] and agrees with the study by Min et al. [ 39 ] where significant improvement in food safety knowledge was observed in communities with existence of COVID-19 cases. Health education aims to provide health information and knowledge to individuals and populations and equip them with skills to be able to voluntarily adopt healthy behaviours [ 47 ]. Also, the increase in positive health behaviours and ceasing or reduction in negative health-related lifestyles could have resulted from self-preservation, a common psychological response in COVID-19 [ 48 ], resulting from improved health knowledge and risk perception. Again, the framework posits that improved health knowledge which influences attitude and perception increases the chances of individuals adopting appropriate health behaviour [ 18 , 24 ] including physical exercising, healthier diet choices and ceasing of risky behaviours like alcohol consumption and smoking. Thus, the adoption of healthy behaviours and avoiding of risky behaviours is consistent with the improved health knowledge as a result of increased access to health information in this pandemic period.

Again, we observed improved healthcare seeking behaviour among some of the residents which may have resulted from improved perception of risk of exposure and perceived severity of selected health conditions such as chronic diseases, food borne diseases, and COVID-19 as well as perceived efficiency of coping or preventive strategy [ 49 ] resulting from gained information. Hence, the type and amount of information communicated to individuals and the focus on specific health information could have heightened perceived risk [ 50 ]. Their positive health seeking behaviour change, thus, results from improved understanding of health conditions and risky health behaviours. This finding is consistent with the framework that supportive predisposing factors like improved health knowledge, need for care factors such as adequate perception of health risk and severity together with enabling factors like access to health information lead to better health seeking behaviour [ 18 , 22 ].

More so, our finding that some residents experienced poor healthcare seeking behaviour due to COVID-19 restrictions and protocols is in congruence to the position by Balhara et al. [ 51 ] and Yau et al. [ 48 ] that health-seeking behaviour continues to be significantly disrupted by the COVID-19 pandemic. This comes at the backdrop that outpatient and preventive care have changed significantly due to the COVID-19 pandemic with deferring of elective and preventive care visits, patients avoiding visits to reduce risk of exposure from leaving home [ 52 , 53 ]. The pandemic has also resulted in untold economic and social hardship on individuals making it difficult to access health service. This finding also supports the conceptual framework which Andersen and Newman [ 24 ] posit that the presence of negative factors such as limited access to care and health resources, poor understanding of policies and poor socio-economic status hinders the decision to use health service leading to poor care seeking behaviour.

Poor health seeking behaviour has negative implications for achieving the Sustainable Development Goal (SDG) 3 of ensuring health for all at all ages through promotion of health and provision of quality healthcare services [ 54 ]. Should the poor health seeking behaviour persist, the strides made towards achieving this goal would most likely be lost.

Strengths and limitations

The study is a novel inquiry into the significance of management of a pandemic on healthcare seeking behaviour and the general health system. The study relied on verbal reports by the participants which has the potential of resulting in recall bias and overreporting or underreporting of socially acceptable and unacceptable behaviours respectively. However, participants were encouraged to be honest in their reports and guaranteed on their privacy and confidentiality of their responses while probes were used as mechanism to verify participants’ views.

There has been a positive impact of COVID-19 and its associated management and control measures as well as reforms on health knowledge, health-related lifestyles, and healthcare seeking behaviour among adult residents in the resource-limited setting we studied. The implication of this finding is that although increasing cases of COVID-19 will overburden the health system, efforts put in place are likely to improve health outcomes such as chronic diseases, for majority of the population. COVID-19 associated conscious and unconscious reforms could be a window of opportunity to harness, in order to improve health systems, healthcare seeking behaviour and overall health outcomes even after the pandemic wades off. Thus, health promotion and education interventions put in place should be sustained as part of the regular healthcare structure and financing. It is also important to understand the impact of reduced utilization of healthcare services, as persons with chronic diseases might succumb, not only to COVID-19 if they become infected, but also to the development of complications from pre-existing conditions.

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Health-seeking behaviour during times of illness: a study among adults in a resource poor setting in Ghana

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Vincent Z. Kuuire, Elijah Bisung, Andrea Rishworth, Jenna Dixon, Isaac Luginaah, Health-seeking behaviour during times of illness: a study among adults in a resource poor setting in Ghana, Journal of Public Health , Volume 38, Issue 4, December 2016, Pages e545–e553, https://doi.org/10.1093/pubmed/fdv176

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The implementation of the National Health Insurance Scheme (NHIS) in Ghana aims to bridge the gap between the poor and rich in health-care access and utilization. Guided by Andersen's behavioural model of health services utilization, we examine the factors that influence health-care services utilization in a resource poor setting.

Data for the study were obtained through randomly selected respondents in our study location ( n = 1137). Logistic regression models were fitted to the data to examine the impact of enabling, predisposing and need factors on health-care-seeking behaviour during last illness.

Individuals in the poor and poorest wealth quintiles who are enrolled in the NHIS were less likely to seek treatment in a health facility during their last illness compared with individuals in the richest wealth quintile who are enrolled in the NHIS ( β = 0.41, ρ < 0.01 and β = 0.45, ρ < 0.05, respectively).

Although health insurance is supposed to increase the likelihood of utilizing health services, poor people in our study who are enrolled in the NHIS are still less likely to utilize health services, suggesting that the NHIS has not succeeded in bridging inequalities in health services utilization between the poor and rich.

Health insurance has emerged as a key instrument in current health financing reforms of middle- and low-income countries with the aim of achieving universal health coverage while also encouraging the seeking of treatment in health-care facilities during illness. Ghana is only one of two countries in sub-Saharan Africa to successfully operate a national scale health insurance system, the National Health Insurance Scheme (NHIS). Prior to implementation in 2004, patients were required to pay for their health-care needs, which inherently restricted access to health services for large segments of the populations. Fees associated with health services resulted in adverse effects on health-care-seeking behaviours during illness, 1 , 2 contributing to inequalities that led to considerable disadvantages for the poor. 3

As a consequence of the pernicious effects of user fees, one of the primary goals of Ghana's NHIS was to generally increase the affordability and utilization of drugs and health services, particularly among the poor and most vulnerable populations. Revenue for the NHIS comes from four main sources—a value-added tax (VAT), the Social Security and National Insurance Trust (SSNIT—a national pension scheme), investment income and premiums. In 2011, VAT provided over 72% of the scheme's revenue, while SSNIT, investment income and premiums contributed ∼17, 5 and 4%, respectively. 4 The scheme offers premium exemptions for a section of the population (i.e. children under 18, pregnant women, persons over 70 years and the indigents (defined as the extremely poor)) and covers over 95% of the disease burden in Ghana. Premiums differ based on place of residence and range from a minimum of about $2–$13. 5 NHIS holders can access health care free of charge from accredited health centres. By reducing financial barriers associated with health services, health insurance theoretically influences health-care-seeking behaviour by preventing delays, self-treatment and use of alternative forms of care among populations, particularly the poor. 6

Since the inception of the NHIS, numerous studies have focussed on investigating NHIS enrolment dynamics. 7 – 12 Yet very few studies have examined the impact of the scheme on health-care facility utilization behaviour. Further, these studies tend to focus on the impact of NHIS on maternal health services utilization. 13 – 17 Others have also explored NHIS impact on seeking treatment for specific diseases. 18 , 19 More importantly, no study has specifically targeted a resource poor region to understand the influence of insurance on actual health-care service utilization in such locations. This study fills this gap by examining the impact of wealth on health-seeking behaviour during times of sickness or ill health among NHIS enrolled adults in the Upper West Region (UWR). This article seeks to address the following research question: what is the relationship between poverty and health-seeking behaviours in the UWR. We hypothesize that higher wealth status of individuals will have a positive impact on health-seeking behaviour during illness. The study was conducted in UWR—the poorest region in Ghana 7 —where a paradoxical relationship between NHIS enrolment and poverty has been found. 20 Using national level data, Dixon et al. 20 found that poverty acts as a barrier to enrolment in the NHIS. Yet, regardless of UWR's notoriety as the poorest region in the country, it boasts the highest rate of NHIS enrolment relative to other regions based on population proportion with over 55% rate of enrolment in the region—consistently above the rest of the country. 4 In 2011, the region had the lowest number of doctors in total (17) as well as per population, working in six hospitals. 21 The situation is very similar with regards to other health professionals (nurses, midwifes, anaesthetists, etc.). 7 Such grim statistics potentially influences health facility utilization in the region. Further, only 17.5% of the total population in UWR are urbanized compared with the national average of 51%, with peasant agriculture constituting the main economic activity of the region, employing over 72% of the population. 7 , 22

Conceptual framework—based on Andersen's behavioural model of health-care services utilization.

This study used data from a cross-sectional survey conducted with 2119 respondents throughout UWR between May and December 2011. The services of Research Assistants (RAs) who are fluent in English and the local dialects of the region (Dagaare, Waali or Sissali) and knowledgeable about the culture and geography of the region were engaged to conduct survey interviews. A week-long training about questionnaire administration and adherence to ethical standards was conducted with support from researchers from the University for Development Studies – Wa, to ensure consistency in survey administration and avoidance of ethical violations by RAs in the collection of data. Ethical approval for this study was obtained from the Non-medical Research Ethics Board of the University of Western Ontario. All persons 18 years or older were eligible to participate. Probability sampling based on a sampling frame from Ghana's most recent population and housing census was used to select clusters. In each randomly selected household from the clusters, an adult aged 18 or older whose birthday was closest to the study date 9 was sampled to answer a face-to-face survey administered by an RA. The analytical sample in this study was 1137 respondents, comprising only individuals who were enrolled in the NHIS at the time of their last illness. By eliminating persons not enrolled in the NHIS, our analysis is able to capture health-seeking behaviours of the population without enrolment status acting as a confounder.

The study focussed on health-care-seeking behaviours during respondents' last illness. The dependent variable for this study was obtained from the following question: ‘during your last illness where did you seek treatment?’ This question had the following response categories: ‘did not seek treatment’, ‘health centre’, ‘mobile clinic’, ‘hospital’, ‘traditional healer’ and ‘other’. Based on these response categories, the original question was operationalized as whether individuals sought treatment in a health facility or not during their last illness. We categorized the responses into a binary variable by coding respondents who sought treatment from ‘health centre’, ‘mobile clinic’ and ‘hospital’ into one group and coded as ‘Yes = 1’. Individuals who ‘did not seek treatment’, visited a ‘traditional healer’ or indicated ‘other’ were coded as ‘No = 0’, indicating that they did not seek treatment in a health facility.

The selection of independent variables used in this analysis was closely guided by the behavioural model alluded to in Fig. 1 . The focal independent variable of interest was wealth status of respondents. Wealth quintile, constructed using demographic and health survey recommended guidelines, 10 was used as a proxy for wealth status. Wealth quintile is an asset-based measure employed in locations where incomes are difficult to measure. Assets including livestock and birds (goats, sheep, cattle, donkeys, pigs and chicken), utilities (electricity and running water), type of dwelling and other properties such as radio sets were used to construct our wealth quintiles. In addition, we controlled for two groups of enabling factors—(i) family and individual resources (i.e. household structure) and (ii) community resources (i.e. presence of a community health worker, drug kiosk (local dispensaries for out-of-pocket purchasing of medications) and distance to health facility). We also controlled for socio-demographic (predisposing) characteristics of respondents including age, gender, marital status, self-rated health, education and religion.

Data analysis

Descriptive statistics of study participants ( n = 1137)

.	.	.
Enabling factors
Sought treatment in health facility
No	595	52.3
Yes	542	47.7
Wealth quintile
Richest	36	3.2
Richer	132	11.6
Average	144	12.7
Poor	290	25.5
Poorest	535	47.1
House structure
Nuclear	383	33.7
Polygamy	600	52.8
Female centred	76	6.7
Male centred	76	6.7
Community health worker present
Yes	653	57.4
No	484	42.6
Drug kiosk in community
Yes	522	45.9
No	615	54.1
Distance to health facility
<5 km	846	74.4
5 km or more	291	25.6
Socio-demographic (predisposing) factors
Age
18–34 years	672	59.1
35+ years	465	40.9
Gender
Female	619	54.4
Male	518	45.6
Marital status
Never married	305	26.8
Married	752	66.1
Divorced/widowed	80	7.0
Self-rated health
Good	632	55.6
Fair	449	39.5
Poor	56	4.9
Education
Tertiary	198	17.4
Secondary	291	25.6
Primary	310	27.3
No education	338	29.7
Religion
Christian	752	66.1
Muslim	201	17.7
Traditional	184	16.2

.	.	.
Enabling factors
Sought treatment in health facility
No	595	52.3
Yes	542	47.7
Wealth quintile
Richest	36	3.2
Richer	132	11.6
Average	144	12.7
Poor	290	25.5
Poorest	535	47.1
House structure
Nuclear	383	33.7
Polygamy	600	52.8
Female centred	76	6.7
Male centred	76	6.7
Community health worker present
Yes	653	57.4
No	484	42.6
Drug kiosk in community
Yes	522	45.9
No	615	54.1
Distance to health facility
<5 km	846	74.4
5 km or more	291	25.6
Socio-demographic (predisposing) factors
Age
18–34 years	672	59.1
35+ years	465	40.9
Gender
Female	619	54.4
Male	518	45.6
Marital status
Never married	305	26.8
Married	752	66.1
Divorced/widowed	80	7.0
Self-rated health
Good	632	55.6
Fair	449	39.5
Poor	56	4.9
Education
Tertiary	198	17.4
Secondary	291	25.6
Primary	310	27.3
No education	338	29.7
Religion
Christian	752	66.1
Muslim	201	17.7
Traditional	184	16.2

Zero-order logistic regression models of respondents’ health-seeking behaviours during illness ( n = 1137)

.	.
Enabling factors
Wealth quintile (ref.: richest)
Richer	0.85 (0.34)
Average	0.59 (0.23)
Poor	0.39 (0.15)**
Poorest	0.38 (0.14)***
Household structure (ref.: nuclear)
Polygamy	1.30 (0.17)**
Female centre	0.89 (0.23)
Male centre	1.59 (0.40)
Community health worker present (ref.: yes)
No	0.63 (0.08)***
Drug kiosk in community (ref.: yes)
No	0.50 (0.06)***
Distance to health facility (ref.: <5 km)
5 km or more	0.57 (0.08)***
Socio-demographic (predisposing) factors
Age (ref.: 18–34 years)
35+ years	1.73 (0.21)***
Gender (ref.: female)
Male	0.84 (0.10)
Marital status (ref.: never married)
Married	1.47 (0.20)***
Divorced/widowed	1.24 (0.31)
Self-rated health (ref.: good)
Fair	2.67 (0.34)***
Poor	1.54 (0.43)
Education (ref.: tertiary)
Secondary	0.55 (0.10)***
Primary	0.67 (0.12)**
No education	0.83 (0.15)
Religion (ref.: Christian)
Muslim	0.96 (0.15)
Traditional	0.40 (0.07)***

.	.
Enabling factors
Wealth quintile (ref.: richest)
Richer	0.85 (0.34)
Average	0.59 (0.23)
Poor	0.39 (0.15)**
Poorest	0.38 (0.14)***
Household structure (ref.: nuclear)
Polygamy	1.30 (0.17)**
Female centre	0.89 (0.23)
Male centre	1.59 (0.40)
Community health worker present (ref.: yes)
No	0.63 (0.08)***
Drug kiosk in community (ref.: yes)
No	0.50 (0.06)***
Distance to health facility (ref.: <5 km)
5 km or more	0.57 (0.08)***
Socio-demographic (predisposing) factors
Age (ref.: 18–34 years)
35+ years	1.73 (0.21)***
Gender (ref.: female)
Male	0.84 (0.10)
Marital status (ref.: never married)
Married	1.47 (0.20)***
Divorced/widowed	1.24 (0.31)
Self-rated health (ref.: good)
Fair	2.67 (0.34)***
Poor	1.54 (0.43)
Education (ref.: tertiary)
Secondary	0.55 (0.10)***
Primary	0.67 (0.12)**
No education	0.83 (0.15)
Religion (ref.: Christian)
Muslim	0.96 (0.15)
Traditional	0.40 (0.07)***

* P < 0.05.

** P < 0.01.

*** P < 0.001.

Multivariate logistic regression models of respondents’ health-seeking behaviours during illness ( n = 1137)

.	.	.
Enabling factors
Wealth quintile (ref.: richest)
Richer	0.94 (0.39)	0.89 (0.39)
Average	0.67 (0.27)	0.66 (0.29)
Poor	0.50 (0.19)*	0.41 (0.17)**
Poorest	0.54 (0.21)	0.45 (0.19)*
Household structure (ref.: nuclear)
Polygamy	1.33 (0.18)**	1.34 (0.20)**
Female centred	0.89 (0.23)	0.93 (0.27)
Male centred	1.65 (0.41)**	2.26 (0.64)***
Community health worker present (ref.: yes)
No	0.86 (0.12)	0.95 (0.14)
Drug kiosk in community (ref.: yes)
No	0.63 (0.09)***	0.65 (0.09)***
Distance to health facility (ref.: <5 km)
5 km or more	0.73 (0.11)**	0.72 (0.12)**
Socio-demographic (predisposing) factors
Age (ref.: 18–34 years)
35+ years		1.64 (0.25)***
Gender (ref.: female)
Male		0.85 (0.12)
Marital status (ref.: never married)
Married		1.14 (0.19)
Divorced/widowed		0.86 (0.27)
Self-rated health (ref.: good)
Fair		2.67 (0.38)***
Poor		1.46 (0.47)
Education (ref.: tertiary)
Secondary		0.62 (0.13)**
Primary		0.80 (0.18)
No education		1.03 (0.23)
Religion (ref.: Christian)
Muslim		0.84 (0.15)
Traditional		0.41 (0.08)***
Nagelkerke pseudo-	0.07	0.19
Model χ (sig.)	58.06***	152.13***
Sensitivity	49.08	61.07
Specificity	66.72	69.41
Overall percentage correctly classified	58.31	65.44

.	.	.
Enabling factors
Wealth quintile (ref.: richest)
Richer	0.94 (0.39)	0.89 (0.39)
Average	0.67 (0.27)	0.66 (0.29)
Poor	0.50 (0.19)*	0.41 (0.17)**
Poorest	0.54 (0.21)	0.45 (0.19)*
Household structure (ref.: nuclear)
Polygamy	1.33 (0.18)**	1.34 (0.20)**
Female centred	0.89 (0.23)	0.93 (0.27)
Male centred	1.65 (0.41)**	2.26 (0.64)***
Community health worker present (ref.: yes)
No	0.86 (0.12)	0.95 (0.14)
Drug kiosk in community (ref.: yes)
No	0.63 (0.09)***	0.65 (0.09)***
Distance to health facility (ref.: <5 km)
5 km or more	0.73 (0.11)**	0.72 (0.12)**
Socio-demographic (predisposing) factors
Age (ref.: 18–34 years)
35+ years		1.64 (0.25)***
Gender (ref.: female)
Male		0.85 (0.12)
Marital status (ref.: never married)
Married		1.14 (0.19)
Divorced/widowed		0.86 (0.27)
Self-rated health (ref.: good)
Fair		2.67 (0.38)***
Poor		1.46 (0.47)
Education (ref.: tertiary)
Secondary		0.62 (0.13)**
Primary		0.80 (0.18)
No education		1.03 (0.23)
Religion (ref.: Christian)
Muslim		0.84 (0.15)
Traditional		0.41 (0.08)***
Nagelkerke pseudo-	0.07	0.19
Model χ (sig.)	58.06***	152.13***
Sensitivity	49.08	61.07
Specificity	66.72	69.41
Overall percentage correctly classified	58.31	65.44

Around 48% of the study participants sought treatment in a health facility during their last illness. Almost three-quarters of participants belonged to the poor and poorest wealth quintiles with most people belonging to polygamous households (53%). Some 57% of participants indicated a community health worker lived among them, while ∼54% of participants indicated the absence of a drug kiosk/pharmacy in their community. Most participants lived <5 km from a health facility (74.4%). Individuals between the ages of 18 and 34 formed ∼59% of participants and the gender split was ∼54% females and 46% males. Most people in the sample were currently married (66.1%). Around 30% of participants had no formal education and Christians constituted the highest proportion of participants in terms of religion (66.1%) (see Table 1 ).

In Table 2 , we present results of the bivariate relationship between our outcome variable and selected independent variables. Individuals who are enrolled in the NHIS and belonged to the poor and poorest wealth quintiles were less likely to seek treatment in health facility during their last illness relative to their richest counterparts who are also enrolled in the NHIS ( β = 0.39, ρ < 0.01 and β = 0.38, ρ < 0.001). Our bivariate models show statistical significance between seeking treatment in a health facility during last illness and all enabling factors and predisposing factors.

Multivariate

In Table 3 , two models were built to assess the relationship between seeking treatment in a health facility and wealth status within the context of NHIS enrolment status, while controlling for theoretically relevant predictors. In Model 1, we examine the relationship between seeking treatment and wealth status, controlling for enabling factors. After controlling for selected enabling factors in Model 1, poor individuals were less likely to seek treatment in a health facility during their last illness compared with the richest individuals ( β = 0.50, ρ < 0.05). Individuals in polygamous ( β = 1.33, ρ < 0.01) and male-centred ( β = 1.65, ρ < 0.01) households were each more likely to seek treatment in a health facility during their last illness relative to their counterparts in nuclear households. Respondents who indicated there was no drug kiosk in their community were less likely to seek treatment in a health facility during their last illness compared with those with drug kiosks in their community ( β = 0.63, ρ < 0.001). Compared with individuals who live <5 km away from a health facility, those who lived >5 km were less likely to utilize a health facility during their last illness ( β = 0.73, ρ < 0.01).

In Model 2, respondents' socio-demographic factors are added to Model 1. After controlling for selected theoretically relevant predisposing factors in Model 2, wealth status remained significantly associated with seeking treatment in a health facility during last illness. Compared with the individuals in the richest wealth quintile, respondents in the poor and poorest wealth quintiles were 59 and 55% less likely to seek treatment in a health facility during their last illness, respectively. Household structure remained statistically associated with seeking treatment in a health facility during last illness. Respondents in polygamous ( β = 1.34, ρ < 0.01) and male-centred ( β = 2.26, ρ < 0.001) households were each more likely to seek treatment in a health facility during their last illness relative to their counterparts in nuclear households. The presence of a drug kiosk in the community and distance to health facility both remained statistically associated with seeking treatment in health facility during last illness. Relative to individuals who have a drug kiosk in their community, those without a drug kiosk were less likely to seek treatment in a health facility during their last illness ( β = 0.65, ρ < 0.001). Individuals who lived >5 km to a health facility were less likely to seek treatment in a health facility during their last illness compared with those who lived <5 km from a health facility ( β = 0.72, ρ < 0.01).

Four of the selected socio-demographic (predisposing) factors were significantly associated with seeking treatment in a health facility during last illness in this study. Individuals who were 35 years or older were more likely to seek treatment in a health facility during their last illness relative to those between 18 and 34 years ( β = 1.64, ρ < 0.001). Respondents who rated their health status as fair were more likely to seek treatment in a health facility during their last illness relative to their counterparts who rated their health as good ( β = 2.67, ρ < 0.001). Individuals who reported they had secondary education were less likely to seek treatment in a health facility during their last illness compared with their counterparts with tertiary education ( β = 0.62, ρ < 0.01). Compared with Christians, traditionalists had lower odds of seeking treatment in a health facility during their last illness ( β = 0.41, ρ < 0.01).

Main finding of this study

In this study, we examined the health-seeking behaviours of individuals enrolled in the NHIS during their last illness. The most important finding from this study is that individuals in the poor and poorest wealth quintiles were less likely to seek treatment in a health facility even though they were enrolled in the NHIS. This suggests that the NHIS has not succeeded in bridging the gap between the poor and rich in terms of health-care access. This finding is at odds with the tenets of the NHIS that has the objective of providing access to adequate and equitable health services to the entire population, especially the poor and vulnerable. Furthermore, this finding suggests that the high rate of NHIS enrolment in the UWR 20 does not translate to seeking treatment in a health facility during illness. The public health implication of this finding is that poor people in the UWR are less likely to seek treatment in health facilities even when they have health insurance, potentially predisposing people to further health complications with consequences for mortality.

What is already known on this topic?

Andersen's model of health-care utilization has been used to demonstrate the usefulness of enabling, need and predisposing factors in understanding health-seeking behaviours. 11 , 20 , 30 For example, we found that four of the enabling factors in our study emerged as important for understanding health-seeking behaviours among adults in UWR. Previous studies from Ghana suggests that poor people are less likely to enrol in the NHIS. 12 , 20 This is similar to our findings that show the poor are also less likely to seek treatment in a health-care facility during illness. Individuals in polygamous households were more likely to seek treatment than those in nuclear families. This suggests that larger family units may act as an important social capital that influences health-seeking behaviours due to the ability to mobilize the required resources such as financial resources needed to cover transportation cost among others. 13 , 14 Higher proportions of respondents in male-centred homes sort treatment in a health facility and also lived <5 km from a health centre. The literature on the importance of community resources such as local pharmacy/drugstores on health facility utilization are mixed. While some studies have found the presence of pharmaceutical retail points in communities results in decrease health facility utilization, 15 , 16 others have found no association. 17 Our findings show that individuals who did not have drug kiosks in their communities were less likely to seek treatment in a health facility. We posit that this might be because communities in UWR that did not have drug kiosks might also be very remote with transportation cost serving as a barrier to seeking treatment in a health-care facility. Such locations may have low levels of development, likely without elementary schools, electricity and other basic facilities. Indeed, individuals who live 5 km or more from a health facility were less likely to seek treatment during illness. Due to limited economic sustenance, transportation costs are often beyond the financial means of poverty stricken residents of rural localities such as those in UWR, thereby penalizing an individual's ability to use health services. 18 , 19 A cross tabulation between drug kiosk and distance to health facility showed that ∼77% of respondents who live >5 km from a health facility have no drug kiosks in their community. Further investigation showed that ∼63% of people who live >5 km from a health facility indicated they did not seek treatment in a health facility during their last illness. The observations in this study might be due to sheer lack of health-care facilities and practitioners and general underdevelopment of the region. 21 Under such circumstances, providing access to health insurance will not in itself translate into actual utilization of health-care facilities for vulnerable populations as observed in the findings of this study.

The influence of predisposing factors (i.e. age, self-rated health, educational level and religion) on the health-care-seeking behaviours of adults in the UWR is similar to what exists in the literature. For example, several studies have established that older people tend to utilize health facilities more than the young. 35 – 39 Although we found an association between self-rated health and health-care-seeking behaviours, evidence from the literature suggests a mixed relationship. For example, while Bourne et al . 40 found no relationship, other studies have found associations between the two factors. 41 , 42 Both educational attainment 43 , 44 and beliefs systems 45 have also been found to pervade propensity to utilize health services because of their ability to affect an individual's awareness and recognition of illness severity. 24

What this study adds

To the best of our knowledge, this study is the first to investigate the effectiveness of the supposed pro-poor orientation of the NHIS by examining its impact on health-seeking behaviours in a resource poor setting. Our study is also the first to examine the impact of NHIS on health-seeking behaviour with a focus beyond a specific group or disease. Our findings demonstrate lower odds of seeking treatment in health facility among poor people and highlight the need for some form of intervention to improve access to health among the vulnerable.

National level studies are necessary to investigate the impact of NHIS on health-seeking behaviours at that scale. This study offers new insights on the impact of NHIS among vulnerable populations with policy implications. Particularly, preventative health-care services currently offered through Community-Based Health Planning Services (CHPS) centres in rural communities need to be adequately resourced to provide services beyond what is currently being offered; since these centres tend to be proximally located to the poor in rural areas unlike conventional health centres.

Limitations of this study

This study is not without limitations. First, individuals' self-evaluation of illness severity and the associated need to seek treatment may differ vastly. However, we did not control for severity and/or type of illness as information on this variable was not collected. Further studies are necessary for exploring the role of illness severity in understanding health-seeking behaviours among residents of UWR. Additionally, we relied on self-reported health facility utilization at last illness, which is subject to recall bias.

This work was made possible with the support of the International Development Research Centre (106204-99906075-031), Ottawa, Canada; the Africa Initiative, a multi-year, donor supported programme jointly undertaken by The Centre for International Governance Innovation and Makerere University to contribute to the deepening of Africa's capacity and knowledge; an Ontario Graduate Scholarship and a Doctoral Award from Canada's Social Sciences and Humanities Research Council (752-2012-2455).

The authors would like to thank the people of the Upper West Region for their generous participation in this research, the RAs for their hard work and the anonymous reviewers for their constructive feedback.

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Published: 07 June 2024

Health-seeking behaviour during times of illness among urban poor women: a cross-sectional study

Khadijahtul Qubra Amizah Hamzah 1 ,
Nor Afiah Mohd Zulkefli 1 &
Norliza Ahmad 1

BMC Women's Health volume 24 , Article number: 334 ( 2024 ) Cite this article

Metrics details

Urban poor women face dual challenges regarding gender inequalities and urban poverty, which make them more likely to have health problems and affect their health-seeking behaviour. This study aimed to determine the prevalence of health-seeking behaviour during times of illness and predictors of sought care among urban poor women in Kuala Lumpur, Malaysia.

This cross-sectional study was performed among 340 randomly selected women residents from April to May 2023. Data was collected using a validated and reliable self-administered questionnaire and analysed using SPSS version 28.0 software. The dependent variable in this study was health-seeking behaviour during times of illness, while the independent variables were sociodemographic characteristics, socioeconomic characteristics, medical conditions, women’s autonomy in decision-making, social support, perceived stigma, and attitude towards health. Multiple logistic regression was used to identify the predictors of sought care during times of illness.

Study response rate was 100%, where 72.4% sought care during times of illness. Being non-Malay (AOR = 4.33, 95% CI: 1.847, 10.161), having healthcare coverage (AOR = 2.60, 95% CI: 1.466, 4.612), rating their health as good (AOR = 1.87, 95% CI: 1.119, 3.118), and having pre-existing chronic diseases (AOR = 1.92, 95% CI: 1.130, 3.271) were identified as predictors of sought care during times of illness.

The present study showed that health-seeking behaviour during times of illness among the participants was appropriate. Health promotion and education, with a focus on educating and raising awareness about the importance of seeking timely healthcare, are crucial to improving health-seeking behaviour among urban poor women. Collaboration with relevant stakeholders is needed to develop comprehensive strategies to improve access to healthcare facilities for these women.

Peer Review reports

Health and well-being are the basic needs of a human being. The United Nations, through its third Sustainable Development Goal (SDG), targets that everyone has access to the full range of high-quality healthcare services they require, when and where they need them, and without financial hardship [ 1 ]. This target, known as universal health coverage (UHC), encompasses all aspects of healthcare services, from health promotion to prevention, treatment, rehabilitation, and palliative care. The UHC initiative could be significantly impacted by the health-seeking behaviour (HSB) of the population [ 2 ]. HSB is “any action or inaction taken by individuals who perceive themselves to have a health problem or to be ill to find an appropriate remedy” [ 3 ]. HSB, or illness behaviour or sick-term behaviour, is part of the broader term of health behaviour [ 4 ]. Inappropriate HSB can impact population health outcomes [ 5 ], increase the community’s transmission risk, increase the disease burden and cause premature death [ 6 ]. By comprehending the patterns of HSB, public health practitioners and policymakers can improve the healthcare system and health promotion strategies [ 7 ].

Even though past studies showed that women seek health more than men [ 8 , 9 ], women in developing countries use proper healthcare less than men and prefer traditional healing methods and self-medication [ 10 ]. These are considered inappropriate HSB [ 11 ]. According to Harrison and colleagues [ 12 ], the gender socialisation process, which is influenced by socio-cultural factors, has an impact on health-related notions and habits, such as decisions about when and where to seek care. Not only does it impact how symptoms or distress are expressed and treated, but it also often leads to other societal barriers that hinder women from obtaining the medical care they need. Women who lack knowledge about health issues downplay their illnesses or rely on older relatives or men to look after them. This becomes more evident in nations where structural barriers prevent women from seeking medical attention for their illnesses.

Women in urban areas have more opportunities and job options than women in rural areas. However, they live in an unfavourable environment because of gender inequality, high living costs, and vulnerability to violence, making them more likely to have health problems [ 13 , 14 ] particularly those living in poverty [ 15 ]. Urban poverty is complex and multifaceted, extending beyond a lack of income or resources. The urban poor face issues such as inadequate housing, limited access to basic services, low income levels, and health burdens [ 15 ]. The urban poor often lack representation and voice in policy-making processes, contributing to their marginalisation [ 16 ]. The multiple pressures faced by urban poor women increase their health risks. However, women, especially impoverished women, have limited access to formal healthcare services for their health conditions, and sometimes the costs can be prohibitively high [ 14 , 17 ]. Monitoring gender inequality is essential to identify and track disadvantaged populations to provide decision-makers with an evidence base to formulate more equity-oriented policies, programs and practices towards the progressive realisation of UHC.

The prevalence of HSB varies from illness to illness. HSB among women in Malaysia showed an increasing trend from 36.4% in 2011 to 60.1% in 2019 [ 18 ]. However, HSB in Malaysia is still low compared to the goal set under the United Nations UHC strategies, which targets access to quality essential healthcare services for everyone [ 1 ]. In the nationwide survey, HSB in Kuala Lumpur is among the lowest since 2011 (36.4%), 39.0% in 2015, and 49.6% in 2019 [ 18 ]. Kuala Lumpur is the federal city of Malaysia, with a wide distribution of public and private healthcare facilities compared to other states. In Malaysia, the prevalence of diseases among women showed an increasing trend for example diabetes increased from 9.1% (2015) to 9.8% (2019), hypertension from 14.0% (2015) to 17.8% (2019), and hypercholesterolemia from 9.8% (2015) to 15.1% (2019) [ 19 ].

A review of previous studies suggested that HSB among women could be associated with disease patterns, psychosocial factors, women’s autonomy, self-rated health, cultural beliefs, health literacy, and issues related to healthcare services. Urban poor women often seek healthcare services due to chronic diseases, mental health issues, and reproductive care needs [ 20 , 21 ]. Psychosocial factors encompass psychological and social factors also affecting how women seek healthcare [ 5 ]. Psychological barriers such as stereotypes and stigma about certain health conditions or seeking healthcare can lead to negative emotions such as shame, fear, and embarrassment, preventing them from getting necessary healthcare on time [ 22 ]. Urban poor women challenging circumstances and limited resources make social support crucial for their HSB. Managing diseases successfully requires cooperation between patients, families, and healthcare professionals. For this reason, social support alleviates anxiety, reduces stigma, and provides reassurance, resulting in a more positive healthcare experience [ 23 ].

Moreover, women’s autonomy in healthcare decisions significantly impacts maternal and child health outcomes and reflects women’s empowerment. It also facilitates access to material and social resources such as food, income, knowledge, healthcare, and power within the family and community [ 24 ]. Self-rated health is a person’s subjective evaluation of their state of health. Particularly, people who rate their health as poor are more likely to seek medical attention when they experience illness-related symptoms [ 20 , 25 ]. Additionally, cultural beliefs may influence perceptions of illness, treatment preferences, and attitudes towards healthcare providers, which demonstrates the strong influence of sociocultural practices and beliefs on one’s HSB [ 26 , 27 ].

Furthermore, health literacy is a critical determinant of health-seeking behaviour, as those with better health literacy are more likely to participate in preventive health behaviours and effectively use health services [ 28 ]. Low health literacy has been linked to poor utilization of healthcare resources and poor health outcomes, especially among vulnerable populations [ 28 , 29 ]. Above all, the healthcare system can also influence a woman’s HSB. When health services are far away, the likelihood of seeking care decreases, and vice versa [ 30 ]. This means that people who live farther away from healthcare services may need help accessing the care they need, as indirect costs incurred during travel may make services less affordable. Additionally, the availability and accessibility of healthcare services, including the operating hours of public health facilities, are crucial factors limiting women’s ability to obtain the care they need [ 31 ].

Available research in this field focused mainly on pregnancy and maternal health [ 21 ], mental health [ 22 , 32 ] and other disease-related [ 33 , 34 ]. Limited studies suggest that HSB during times of illness may be influenced by age, household income level, education level, and self-rated health [ 7 , 25 ]. However, these studies were conducted in Ghana and Hong Kong and not among the urban poor women population. The findings have their limitations as there are also healthcare system and cultural differences between these countries and Malaysia.

Little is known about the behaviour of seeking healthcare among urban poor women during times of illness in Malaysia although there have been some studies conducted addressing this issue in other ethnicities such as in African women [ 25 , 34 ]. Considering the lack of study on HSB during times of illness, therefore, the present study aimed to investigate the predictors of HSB during times of illness among urban poor women in Kuala Lumpur.

Study design and area

A population-based cross-sectional study was conducted using the STROBE guidelines from April to May 2023 in a people’s housing project in Kuala Lumpur, the federal city of Malaysia [ 35 ]. The city’s population density was estimated to be 8,157 people per square kilometre in 2020, making Kuala Lumpur the most populous city in Malaysia [ 36 ]. Kuala Lumpur recorded 193.7 thousand households with an income of RM9,149 or less, which is categorised as the low-income group [ 37 ]. The people’s housing project was an initiative by the Malaysian government during the 1997 Asian economic crisis to improve the national economy by providing affordable housing for low-income people [ 38 ]. There are about 30 people’s housing projects in Kuala Lumpur and The People’s Housing Project Seri Semarak was chosen due to its location in the city centre with an estimated 2000 women residents.

Study population and sample size determination

All adult women residents aged between 18 and 59 years old with household incomes of RM9,149 and lesser, understood either Malay or English language with self-reported illness for the past three months before data collection were eligible to participate in the study. Women residents who were non-Malaysians, with special needs (mental, visual or hearing disabilities) or pregnant during data collection were excluded from the study. The sample size of this study was determined by using the two population proportions by Lwanga and Lameshow (1991) on the self-rated health variable from a previous study, considering P 1 = 0.56, the proportion of HSB among good self-rated health, and P 2 = 0.40, the proportion of HSB among fair self-rated health, with an alpha value of 0.05 and a power of 80% [ 39 ]. Hence, the computed sample size was 340 women residents after adjusting for a 20% non-response rate.

Sampling techniques

A paper-form questionnaire was distributed to all women residents who agreed to participate in the study during door-to-door sample recruitment. A total of 1580 residential units were surveyed, and 420 women residents agreed to participate in the study. However, only 350 respondents fulfilled the criteria of a history of self-reported illness in the past three months and household income of ≤ RM9149.00; they were included in the sampling frame. Simple random sampling was performed from the sampling frame using an online random number generator accessed via calculatorsoup.com to pick the sampling unit until the targeted sample size reached 340.

Measurements

The research instrument for this study was a printed self-administered questionnaire. Some of the questions were adopted and adapted from previous studies [ 34 , 40 , 41 , 42 ]. The questionnaire was prepared in English, then translated and back-translated into Malay Language using the WHODAS 2.0 Translation Package [ 43 ]. The questionnaire was divided into two sections. Section I consisted of two screening questions aimed at detecting any reported illnesses in the past three months and the respondent’s household income. Section II consisted of six parts: Part A included questions on the sociodemographic and socioeconomic characteristics of the respondents; Part B was questions about the respondents’ health-seeking behaviours; Part C focused on questions regarding medical conditions and women’s autonomy in decision-making; Part D covered social support; Part E explored perceived stigma; and Part F examined attitudes toward health.

Part A (Sociodemographic and Socioeconomic Characteristics). This part had eight questions on sociodemographic and socioeconomic information. Sociodemographic information included age, ethnicity, education level, and marital status. While socioeconomic information encompassed employment status, monthly household income, and healthcare coverage. Sociodemographic and socioeconomic characteristics were measure using adapted questionnaire from the National Health and Morbidity Survey 2019 (NHMS 2019) [ 18 ] Part B (Health-Seeking Behaviour). On health-seeking behaviour, the questions were adapted from the NHMS 2019 [ 18 ] comprising of two items to assess the HSB of the respondents after they had experienced any of the 22 listed health problems in the last three months. Part C (Medical Conditions and Women’s Autonomy in Decision-Making). There were three questions in this part regarding respondents’ pre-existing chronic diseases, self-rated health and women’s autonomy in making decisions on health. Pre-existing chronic diseases and self-rated health were measured using questions adapted from NHMS 2019 [ 18 ] while women’s autonomy in decision-making was measured using a question adapted from Rani and Bonu [ 41 ]. Part D (Social Support). Social support was measured using an adapted questionnaire by Zimet et al. [ 42 ] that evaluated 12 items from three sources of support which were family, friends and special person. Respondents were required to rate a source of social support on a 7-point Likert scale. In this study, social support was classified into three categories which were strong social support (score between 5.1 and 7), moderate social support (score between 3 and 5), and weak social support (scores ranging from 1 to 2.9) [ 42 ]. Part E (Perceived Stigma). Perceived stigma was measured using an adapted questionnaire from the Stigma Scale for Receiving Psychological Help [ 40 ]. Respondents had to rate their agreement or disagreement with each statement on this 5-item scale using a 5 Likert-type scale. For this study, the level of perceived stigma was categorised into high perceived stigma (score ≥ 11) and low perceived stigma (score < 11). Part F (Attitude Toward Health). Attitude towards health was measured using an adapted questionnaire by Onyango et al. [ 34 ]. Respondents’ attitudes were measured using six items where they were required to indicate their views regarding illness treatment duration, treatment effects on marriage and work, community perception of ill patients and how they acquired the illness. The format of the questionnaire was a 5-Likert scale. For this study, attitude towards health was categorised based on mean scale scores which were positive attitude (score ≤ mean) and negative attitude (score > mean).

Operational definition

The outcome of this study was health-seeking behaviour during times of illness. HSB was categorised into sought care and not sought care. Sought care is defined as respondents who had at least one visit to get advice or treatment on the listed illnesses for the past three months from any healthcare provider including a medical officer in a government health clinic, private clinic, and Accident and Emergency services in a public or private hospital.

The independent variables for this study were sociodemographic characteristics (age, education level, marital status, ethnicity), socioeconomic characteristics (employment status, household income, and healthcare coverage), medical conditions (pre-existing chronic diseases and self-rated health), women’s autonomy in decision-making, social support, perceived stigma and attitude toward health.

Data management and analysis

The data of this study were analysed using the Statistical Package for Social Sciences System (SPSS) version 28.0 software. The data were checked and cleaned before analysis was done. Descriptive statistics which were frequencies, percentages, means with standard deviations, and medians with interquartile ranges were calculated to describe the distribution of the variables. All the variables in this study showed high reliability, with Cronbach alpha values of 0.8 and above. On the other hand, Cohen’s Kappa test for self-rated health, pre-existing chronic diseases and women’s autonomy in decision-making showed values of 0.829, 0.841, and 0.761 respectively for this study.

All the numerical data were transformed into categorical data, such as age in years, monthly household income, social support, perceived stigma, and attitude towards health. Subsequently, Chi-square tests and Simple Logistic Regression analysis were conducted to measure the association between HSB during times of illness and independent variables. In this study, a significance level of 0.05 ( p < 0.05) with a confidence interval of 95% was set.

Multiple logistic regression was performed to ascertain the predictors for sought care during times of illness among the respondents. Factors that were found to have a p-value of 0.25 in bivariate analysis were included for further multivariable analysis. Multiple logistic regression was done using three methods which were the “Enter” method, “Backward LR” method and “Forward LR” method. From these variables’ selection methods, the “Backward LR” method was used in the final model as it was the most parsimonious model that fitted the data well. Multiple logistic regression was conducted to determine the predictors of sought care, and the results were expressed as adjusted odds ratios with a 95% confidence interval not including one that was assumed significant.

Characteristics of the participants

A total of 340 women residents participated in this study. The participants’ mean age was 44.51 ± 11.083 years, ranging from 18 to 59 years old. Most of the participants were Malay (81.8%), married (80.3%) and had secondary education (70.9%). The respondents’ mean household income was RM2649.47 ± 1367.185, which ranged from RM120 to RM9000. The majority of the respondents were housewives (50.6%), had an income of more than RM2216 (51.8%), and self-paid for their healthcare coverage (58.8%). Most of the respondents had no pre-existing chronic diseases (59.4%) and rated their health as good (50.3%). The majority of the respondents can make their own health decisions and have higher autonomy in decision-making (78.2%). Regarding social support, the majority of the respondents (66.8%) had strong social support with a mean score of 5.55 ± 0.797. The mean total score for perceived stigma was 10.78 ± 4.242 with most of the respondents (52.6%) having low perceived stigma. The mean score for attitude toward health was 2.65 ± 0.713 with 50.3% or 171 of the respondents had a negative attitude toward health (Table 1 ).

Health-seeking behaviour during times of illness

The prevalence of the respondents who sought care during times of illness was 72.4%, with the majority of the respondents reporting seeking treatment at a government health clinic (36.5%) and that no daily activities were disrupted during their illness episodes (56.2%) (Table 1 ).

Predictors of sought care during times of illness

Based on chi-square analysis, HSB during times of illness was significantly associated with ethnicity (χ 2 = 10.142, df = 1, p = 0.001), household income (χ 2 = 6.690, df = 1, p = 0.011), healthcare coverage (χ 2 = 11.707, df = 1, p < 0.001), pre-existing chronic diseases (χ 2 = 4.053, df = 1, p = 0.044) and self-rated health (χ 2 = 7.479, df = 1, p = 0.006), and women’s autonomy in decision-making (χ 2 = 16.916, df = 2, p < 0.001) (Table 2 ).

Simple logistic regression revealed that ethnicity, marital status, household income, healthcare coverage, pre-existing chronic diseases, self-rated health, women’s autonomy, social support, and attitude toward health were included in the preliminary model of multiple logistic regression at p ≤ 0.25 (Table 3 ).

Ethnicity, healthcare coverage, self-rated health and pre-existing chronic diseases were significantly associated with HSB during times of illness in multiple logistic regression analyses ( p < 0.05). Non-Malay respondents were 4.33 times more likely to seek care during illness than Malay respondents (95% CI: 1.847, 10.161, p < 0.001). Those respondents with healthcare coverage were 2.60 times more likely to seek care than those with no healthcare coverage (95% CI: 1.466, 4.612, p = 0.001). Respondents who rated their health as good were 1.87 times more likely to seek care than those who rated it as fair or poor (95% CI: 1.119, 3.118, p = 0.017). Nevertheless, respondents with pre-existing chronic diseases were recorded to be 1.92 times more likely to seek care during illness than those without pre-existing chronic diseases (95% CI: 1.130, 3.271, p = 0.016).

In this study, most respondents (72.4%) sought care during times of illness. Compared to previous studies, the prevalence of HSB in this study was much higher than reported among women in developed countries such as Korea [ 44 ] and Norway [ 8 ] and other developing countries such as India [ 45 ] and Cambodia [ 46 ]. For local studies, the prevalence of HSB ranged between 23.1 and 85.9% with urban areas showing a higher prevalence of HSB as compared to rural areas [ 47 , 48 ]. This could probably be due to the availability and accessibility of better healthcare facilities in urban areas [ 28 ]. In Malaysia, the average distance of government health clinic coverage was 9.71 km while private clinic coverage was 0.472 km with a ratio of health clinics to population at 1:4228 [ 49 , 50 ]. In urban regions of Malaysia, there is a low density of government health clinics relative to the population, a gap compensated by the clustering of private clinics. Conversely, rural areas exhibit a higher concentration of government health clinics, a strategic response to address challenges related to geographical accessibility [ 54 ]. The healthcare system in Malaysia is characterised by significant subsidisation, with consultation and medication fees set at only RM1 across all public health clinics for citizens, while children under five and the elderly receive these services free of charge. Despite this, numerous private health clinics in urban areas do not effectively address the health issues of urban poor women due to financial constraints. In recognition of this disparity, the Ministry of Health is actively tackling the matter by developing alternative healthcare facilities with a narrower range of services administered only by paramedics. These facilities primarily focus on minor ailments and simple procedures [ 51 ].

The majority of the respondents in the present study sought care from healthcare facilities. In contrast, respondents who did not seek care during illness either self-medicated (10.9%), took no action (12.4%), or sought traditional care (4.4%). These findings are comparable with findings from a population survey done in Malaysia [ 18 ]. With the advancement of technology and widespread internet access, information can be shared just at the tip of the finger, whether the information is legitimate or needs to be pondered. A study done by Fox and Duggan showed that 35% of internet users had used this online platform to find information related to health, post health-related questions or share their experiences related to health [ 52 ]. This “online health seekers” trend influenced many self-medicated practices [ 18 ]. Despite the extensive distribution of conventional medicine, traditional and complementary medicine (T&CM) is still one of the choices for Malaysians to support their health, as they believe the treatment is effective [ 53 ]. TCM is commonly used to treat both communicable and non-communicable diseases, especially chronic diseases including cancer, diabetes, and rheumatoid arthritis [ 54 ]. A large body of research underlines that many consumers perceive T&CM as a safer option to conventional medicine, and the accessibility and perceived effectiveness of natural approaches emerge as major variables affecting the preference for T&CM in promoting health [ 55 ]. Moreover, studies further reveal that those with insufficient health literacy are more prone to use T&CM [ 56 ]. Following the establishment of the National Traditional and Complementary Medicine Division in Malaysia, T&CM is being integrated into certain government hospitals to provide selected T&CM practices such as herbal therapy for adjuvant treatment of cancer and postnatal care, as well as traditional massage and acupuncture for post-stroke management. As a result, the satisfaction gained from combining T&CM with conventional medication reflects the need not to limit the use of conventional medicine [ 54 ].

Similar to findings from a study done among low-income women in California, HSB was significantly associated with ethnicity [ 57 ]. This could contribute to the observed differences in health-seeking behaviour among different ethnicities. Household income and women’s autonomy in decision-making were significantly associated with HSB in our study and are similar to findings from Ethiopia and India [ 24 , 41 ]. A study in Ghana showed healthcare coverage was significantly associated with accessing healthcare [ 58 ] which was similar to the finding of this study. Pre-existing chronic diseases were also identified as a significant factor of HSB in our study, similar to the findings of previous studies done in Ethiopia, Greece and India [ 59 , 60 , 61 ]. A study done in Uganda found that self-rated health was significantly associated with HSB [ 62 ], a similar finding with our study.

In this study, it was found that being non-Malay was a significant predictor of HSB during times of illness. Non-Malays were four times more likely to seek care during illness than Malay respondents. Many studies have been undertaken in Malaysia to establish the relationship between ethnicity and HSB, but no significant association has been identified [ 28 , 47 ]. However, studies reveal that being Malay increases the likelihood of seeking traditional medicine compared to being non-Malay [ 63 , 64 ]. In Malaysia, ethnicity significantly shapes health-seeking behaviour, particularly among marginalised populations such as urban poor women. Socioeconomic and cultural factors and systemic inequities often contribute to differential healthcare utilisation patterns among different ethnic groups and Malay ethnicity was more likely to utilise complementary and alternative medicine as compared to other ethnicity [ 64 ].

Having healthcare coverage such as health insurance, pensioner cards, government employees’ guarantee letters, and government health funding programs made people three times more likely to seek healthcare during times of illness. Studies have consistently shown that women with healthcare coverage are more likely to seek preventive services, timely screenings, and treatment when needed [ 58 , 65 , 66 ]. This increased utilisation of healthcare services is crucial for early detection, prevention, and management of health conditions, leading to improved health outcomes. By increasing the chances of going for a medical check-up and early treatment, health insurance can save costs on curative health [ 65 ]. Financial problems such as poverty, financial dependence, and the high cost of services, identified as the main barriers to accessing healthcare, can be counter-measured by having healthcare coverage [ 67 ].

In this study, urban poor women who rated their health as good were two times more likely to seek care than those who rated it as fair or poor. Self-rated health reflects an individual’s subjective assessment of their overall health status, incorporating physical, mental, and social well-being [ 68 ]. This perception can influence HSB among urban poor women in several ways. Firstly, individuals with positive or good self-rated health tend to engage in preventive health behaviours such as regular check-ups, screenings, and maintaining a healthy lifestyle [ 69 ]. They are more likely to seek healthcare services as a proactive measure to maintain and improve their well-being. They tend to be more health-conscious and motivated to engage in health-promoting behaviours [ 70 , 71 ]. Conversely, those with negative or poor self-rated health may delay seeking care or only seek it when their health deteriorates significantly or when they experience functional limitations [ 72 ], which are associated with unmet healthcare needs [ 62 ].

Lastly, respondents with pre-existing chronic diseases were two times more likely to seek care than those without. People with chronic diseases often require regular medical attention and monitoring to manage their conditions effectively. When they experience illness or an exacerbation of their chronic condition, promptly seeking medical care becomes a priority [ 73 ]. Chronic diseases can make individuals more vulnerable to infections or complications. Consequently, women with pre-existing chronic diseases may perceive themselves at higher risk and seek care more readily when they become ill to avoid long-term impacts on their health and mortality [ 74 ]. Individuals with chronic diseases may interact regularly with healthcare providers to manage their healthcare needs [ 9 ], with various health education activities given on each visit. This ongoing relationship can facilitate access to healthcare and increase their likelihood of seeking care during illness episodes.

Strengths and limitations of the study

The study was carried out in a residential area designated for a low-income population and used a population-based approach, which is thought to be superior to an institutional-based study. The data was collected face-to-face through the distribution of printed questionnaires, and any uncertainties or lack of comprehension about the questions could be addressed by directly consulting the researcher in the field, resulting in a 100% response rate and reducing missing data.

However, this study was a cross-sectional study, therefore, the causal-temporal relationship cannot be determined between HSB during times of illness and independent variables. This study also did not address other factors, such as health service accessibility, or use any theoretical framework as the study background. One of the variables, women’s autonomy in decision-making, used only one question to measure the variable, which may not provide enough information or accurately measure the variable. Besides, recall bias may arise in this study as the respondents must self-report whether they have experienced any of the listed health problems or report their actions during the illness period. In addition, the generalisation of the study findings may be limited because this study was conducted in a people’s housing project within Kuala Lumpur and might not represent the other urban poor women in other populations in Malaysia and other populations with different sociodemographic backgrounds.

Recommendations

Given that 72.4% of the respondents sought care during times of illness, there is still a need to further improve the HSB among urban poor women. Besides, other factors such as health services accessibility associated with HSB in urban poor women should have been studied. Qualitative studies, such as in-depth interviews or focus group discussions, should be conducted to better understand the factors influencing health-seeking behaviour among urban poor women. It can provide insights into the specific barriers and facilitators they face and the cultural and social factors that may influence their decision-making. Thus, other variables should be explored in the future to determine the association with HSB. Expanding the research to include a larger sample size of urban poor populations in Malaysia with different sociodemographic backgrounds should also be considered. Studies could also include urban poor women who do not reside in a people’s housing project housing types and involve multiple districts or states to improve the problems by generalising the study findings.

Conclusions

This study was conducted to determine the predictors of HSB during times of illness among urban poor women and discovered that HSB during times of illness among the participants was appropriate. The study has identified ethnicity, healthcare coverage, self-rated health, and pre-existing chronic diseases as predictors of HSB during times of illness.

Health promotion and targeted health education should be given through an individual or community approach, to those of Malay ethnicity, individuals with fair or poor self-rated health, no healthcare coverage and without pre-existing chronic diseases, focusing on education and raising awareness about the importance of seeking timely healthcare. Collaboration with relevant stakeholders, such as local authorities, non-governmental organisations and community leaders, is needed to develop comprehensive strategies that address the multifaceted challenges faced by urban poor women in accessing and seeking healthcare services.

Data availability

The dataset for the current study is available from the corresponding author upon receipt of a reasonable request.

Abbreviations

Health-seeking behaviour

Universal health coverage

Screening question A

Screening question B

Confidence interval

Standard deviation

Adjusted odds ratio

Guarantee letter

Traditional and complimentary medicine

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The authors would like to express our gratitude to study participants, the women residents of The People’s Housing Project Seri Semarak for their involvement in this study.

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KQAH, NAMZ and NA conceived and designed the study. KQAH were responsible for data collection, management, cleaned the data, and performed the statistical analysis. KQAH and NAMZ drafted the manuscript. KQAH, NAMZ, and NA critically revised the manuscript. All authors read and approved the final manuscript.

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Hamzah, K.Q.A., Mohd Zulkefli, N.A. & Ahmad, N. Health-seeking behaviour during times of illness among urban poor women: a cross-sectional study. BMC Women's Health 24 , 334 (2024). https://doi.org/10.1186/s12905-024-03178-w

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Factors related to help-seeking for cancer medical care among people living in rural areas: a scoping review

Mariko Oshiro 1 ,
Midori Kamizato 1 &
Sayuri Jahana 1

BMC Health Services Research volume 22 , Article number: 836 ( 2022 ) Cite this article

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Despite the importance of timely diagnosis and access to treatment, previous studies have not adequately explored help-seeking behavior in cancer treatment among rural and remote residents. The barriers preventing help-seeking behavior also remain unclear. To address this research gap, this study conducted a scoping review to suggest a framework for eliminating barriers and facilitating help-seeking for cancer treatment among rural and remote residents. To conduct the scoping review, three English medical databases (PubMed, MEDLINE, and CINAHL) were examined for the keywords “rural,” “remote,” “cancer,” and “help-seeking.” The research objectives and study designs, participants, and excerpts describing help-seeking of the selected papers were recorded in a data charting form. Descriptions of help-seeking behavior were organized and summarized according to their meaning and integrated into factors using thematic analysis. All extracted factors related to help-seeking were sorted into four main themes according to the Ecological Model of Health Behavior, the theoretical lens for this scoping review: (1) Intrapersonal; (2) Interpersonal; (3) Groups, culture, and organizations; and (4) Policy/environment. Factors were categorized as barriers and facilitators of help-seeking. A total of 13 papers were analyzed. Intrapersonal factors such as self-reliance, symptom appraisal, and fatalism, were identified as barriers to help-seeking, whereas presentation of abnormal and serious symptoms facilitated help-seeking. Interpersonal factors such as lack of understanding of family members, influence of surrounding people, role obligations, and lack of trust in experts hindered help-seeking, whereas understanding from surrounding people such as family and friends, promoted help-seeking. Groups, cultural, and organizational factors such as prejudice, social stigma, shame, lack of anonymity, and social norms acted as barriers to help-seeking. Policy-related barriers to help-seeking included lack of medical services and physical distance from medical institutions, leading to a time burden. The study discussed the identified factors from a rural context. Future studies should consider the identified barriers and facilitators according to the four main themes in rural areas when formulating interventions to promote help-seeking. Our findings can offer a theoretical foundation to develop actionable policies, preventive strategies, and relevant interventional tools that may facilitate oncological service utilization in rural areas.

Peer Review reports

Previous studies have reported that there are differences between rural and urban areas in terms of timely access to healthcare [ 1 ], cancer survival rates [ 2 ], healthcare-seeking behaviors [ 3 , 4 ], and financial problems [ 5 ]. In Japan, there are 405 designated regional cancer care hospitals to ensure that high-quality cancer treatment is available nationwide [ 6 ]. Despite this, cancer patients in Japan continue to face challenges in obtaining treatment, primarily due to the lack of accessibility and availability of designated cancer care hospitals in their areas of residence [ 7 ]. Healthcare professionals have reported a lack of access, psychological issues, and economic burdens related to help-seeking among cancer patients in rural areas [ 8 ].

The World Health Organization [ 9 ] mentioned that, to improve timely diagnosis and access to treatment, it is necessary to accurately understand current barriers in accessing care. This is necessary to design effective interventions to support early diagnosis and access to treatment [ 9 ]. Therefore, many existing reviews have focused on the help-seeking behavior of cancer patients to develop interventions for better cancer outcomes [ 10 , 11 ]. According to Dobson [ 12 ], the path of help-seeking for cancer treatment among rural and remote residents is unclear. Moreover, studies focusing on help-seeking for cancer medical care among people living in rural areas are not well established. Existing new research agenda in 2020 advocated the need to clarify the help-seeking path of rural patients for cancer treatment and related factors based on their actual experiences to develop meaningful interventions to improve cancer outcomes for them [ 12 ]. Therefore, this study conducted a scoping review to provide a framework to identify ways to eliminate barriers to help-seeking for cancer treatment among rural and remote residents. This review had a specific and focused research question: What factors are associated with help-seeking for cancer treatment among rural residents in the literature? Our results can be used to develop actionable policies, preventive strategies, and relevant interventional tools that may help facilitate the use of oncological services in rural areas.

Study design

Our research objective was addressed using a scoping review, which is a type of knowledge synthesis approach used to map the concepts underpinning a research area and the main sources and types of evidence available [ 13 , 14 , 15 ].

Protocol and registration

Our protocol was undertaken using updated methodological guidance for conducting scoping reviews [ 16 ] and PRISMA -ScR guidelines [ 17 ].

Eligibility criteria

We set the inclusion criteria as follows: (1) published in a journal as an original paper, (2) written in English, (3) the study sample included adults living in rural and remote areas, and (4) focus on help-seeking for cancer treatment.

The term “rural” has been defined conventionally, subjectively, or geographically, and no definitive definition has yet been established; there is no single agreed definition yet [ 18 , 19 , 20 ]. In this study, all definitions of “rural” and “remote” used in the literature were accepted. Self-defined rural settings from any geographical region were included.

Further, based on previous studies of concept analysis for help-seeking behavior, we defined “help-seeking behavior” as a problem-focused, planned behavior for seeking medical help [ 21 , 22 ].

We excluded the following studies: (1) samples with children, (2) evaluated interventions effects of related help-seeking, and (3) discussed special tests, such as genetic testing. The help-seeking for special tests may differ from those with more common help-seeking.

Information sources and search

Three English medical databases (PubMed, MEDLINE, and CINAHL) were searched using the keywords “rural,” “remote,” “cancer,” and “help-seeking.”

The search terms were refined using a four-step strategy. The strategy was developed not only for research teams but also with the advice from an informational researcher and a rural nursing researcher. Their inputs were useful in the refinement of key search terms which were most likely to produce the results sought. First, we considered related concepts such as “access to care,” synonymous words such as “seek help,” “seek,” and medical subject headings (MeSH) such as “neoplasms” (Table 1 ). These terms were extracted from related lectures by specialists, books, and relevant previous literature. Second, we searched (Table 1 ) databases (PubMed, MEDLINE, and CINAHL) using these specific words. Techniques for searching included the use of search tools such as subject headings and Boolean operators to narrow, widen, and combine literature searches (Additional file 1 ). Moreover, we searched for grey literature, including various sites such as Google. Third, we screened the search results, the titles, and abstracts, to assess whether the search terms reflect our research theme or not. Finally, we arrived at the specific search terms. After that, we confirmed whether the search terms used in this research had covered the main papers.

Papers published from 1991 to 2021 were included: 72 from PubMed, 37 from MEDLINE, and 37 from CINAHL. The search was conducted on July 30, 2021. The inclusion criteria were as follows: (1) published in a journal as an original paper, (2) written in English, (3) the study sample included adults living in rural areas, and (4) focus on help-seeking for cancer treatment. The exclusion criteria were as follows: (1) samples with children, (2) evaluated interventions effects of related help-seeking, and (3) discussed special tests, such as genetic testing.

Selection of sources of evidence

A PRISMA flow diagram outlines the search and selection process [ 22 ] (Fig. 1 ). The title and abstract of each study were screened initially according to the inclusion and exclusion criteria. Papers selected at this stage were read in their entirety. Finally, eligible papers including factors associated with help-seeking by rural residents were analyzed in this review. Two reviewers (MO, MK) screened titles and abstracts for inclusion. Two reviewers (MO, MK) subsequently screened the full-text of potentially relevant articles to determine inclusion using similar inclusion and exclusion criteria. Subsequently, all included studies had been abstracted by the reviewers.

PRISMA flow diagram

Data charting process

The research objectives and study designs, participants, and excerpts describing help-seeking behavior, were recorded in a data charting form (Table 2 ). Each included study was abstracted by the first reviewer (MO) and verified by the second reviewer (MK).

We abstracted data on characteristics of the articles (e.g., type of article or study, country of corresponding author), population characteristics (e.g., type of cancer), and outcomes.

Synthesis of results

First, descriptions of help-seeking behaviors were organized and summarized according to their meaning and then integrated into factors using a thematic analysis. Discrepancies in thematic analysis were discussed among the study authors. Second, all extracted factors related to help-seeking from this study were sorted into “Factor of Barriers and Facilitators” (Table 3 ). Third, these Barriers and Facilitators factors were classified under subthemes in the column and mapped into four main themes in the ecological model of health behavior [ 36 , 37 , 38 , 39 ] (Table 3 ).

The model considers rural and remote residents as individuals influenced by an ecosystem including political and other systems. Therefore, the ecological model was used as a theoretical framework in this study. This model conceptualizes the social world in four spheres or levels of influence. These levels of influence are: (1) Intrapersonal (individual characteristics that influence behavior such as knowledge, attitudes, beliefs, and personality traits); (2) Interpersonal [interpersonal processes and primary groups (family, peers, social networks, associations) that provide social identity and role definition]; (3) Groups, culture, and organizations (home environment/community organizations/informal structures such as religious groups, worksites, schools)]; (4) Policy/environment (healthcare policies/incentives/zoning codes/transportation, city planning) [ 36 , 40 ].

A total of 13 papers were analyzed. Table 2 presents an overview of the papers included in this scoping review. All the selected papers were published after 2007. Five were from Australia, three from Africa, three from South Asia, and two from the US. Based on the study design, six were quantitative, six were qualitative, and one was a mixed-methods study. Table 3 shows the integration of factors associated with help-seeking in rural areas.

Intrapersonal

As shown in Table 3 [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ], demographic factors such as age (age > 63 years, or aged < 18 or > 50 years) [ 29 , 34 ], low education levels [ 29 , 30 ], difficult financial conditions [ 23 , 25 , 28 , 32 , 34 , 35 ], and minority status [ 23 , 35 ] influenced help-seeking behavior. The papers from Africa [ 23 , 32 ], US [ 34 , 35 ], and South Asia [ 25 , 28 ] reported that difficult financial conditions made people feel the burden of paying for travel to medical institutions for procedures like screening, diagnosis, and treatment.

An individual’s value such as Fatalism and Self-reliance influenced help-seeking behavior. The papers from South Asian and African countries, proven in the qualitative studies, reported Fatalism as one’s own fate to develop cancer [ 25 , 28 , 32 ]. Regarding Self-reliance , the paper from Africa reported the use of self-medication when they became aware of cancer symptoms [ 23 ]. The papers from Australia and US reported self-reliance such as trying to control cancer by themselves [ 26 , 34 ], control their emotions so as not to let others see them [ 29 ], and stoicism and machismo [ 31 ].

Symptom appraisal such as being dismissive of problems/optimism and symptoms not linked to cancer were seen as barriers to help-seeking [ 26 , 27 , 29 , 31 ]. The result of the quantitative study shows that, compared with those living in regional and metropolitan areas, people in rural areas were significantly more dismissive of problems [ 27 ]. For example, the people did not think the symptoms were those of cancer. Many experienced similar symptoms in the past that were not due to cancer and felt that they were natural and not problematic. They felt being in good health. As the symptoms worsened gradually, they were not linked to cancer [ 26 ].

The general lack of knowledge/awareness of cancer has emerged in several qualitative and quantitative studies as a relevant factor influencing help-seeking behavior [ 28 , 30 , 32 , 33 , 35 ]. The papers from South Asian [ 28 , 33 ] and African [ 30 , 32 ] countries reported inadequate awareness of cancer and its symptoms. For example, rural women believed that cancer was a disease that always had a poor prognosis [ 33 ]. A lack of knowledge regarding cancer was cited as a barrier in help-seeking and was also associated with a low level of education [ 30 ].

One study from every country reported the fear of tests and treatments and financial burden of screenings and treatments acting as barriers in help-seeking [ 28 , 31 , 32 , 34 ].

Health service utilization habits are a barrier to help-seeking. For example, the people who are not accustomed to visiting the hospital because the family had never done so previously, tend to delay help-seeking [ 34 ].

Interpersonal

Lack of understanding of family members , was identified as a barrier to help-seeking in studies from South Asian and African countries [ 23 , 25 , 28 ]. Specifically, the person cannot seek help to receive treatment without family members such as husband’s and partner’s permission [ 23 , 25 , 28 ]. For example, for some women who already had been diagnosed with cancer, their husbands and mothers-in-law remained unsupportive [ 25 ].

In the US, the papers suggest that people were influenced by help-seeking from their close circle such as family members’ belief and experiences [ 34 , 35 ]. For example, the family’s belief influenced hospital visits, as the family had never done so previously [ 34 ]. Another experience where a family member was diagnosed with cancer and could not be saved, despite seeking clinical assistance, could serve as a barrier to help-seeking [ 35 ].

Role obligations in the family, work and other priorities, are barriers to help-seeking in several countries such as Australia, the US, Africa, and South Asia [ 23 , 25 , 26 , 31 , 34 ].

Unreliable experts (e.g., the doctor did not listen carefully or displayed lack of cordiality) also act as barriers to help-seeking [ 28 , 29 , 34 ].

Groups, culture, and organizations

Community prejudice/social stigma against cancer affects help-seeking tendencies in Asian and African countries [ 25 , 28 , 32 ]. Further, help-seeking was affected by the shame of having cancer [ 26 ] and hesitation in discussing a sex organ such as the uterus [ 25 , 35 ] in several countries, such as Australia, the US, and South Asia.

Additionally, the lack of anonymity and confidentiality create a burden on patients’ minds in close-knit populations like rural areas, which affects help-seeking behavior [ 34 ].

Social norms also affect help-seeking behavior. For example, there are villagers’ cultural norms (e.g., not wanting to let women leave the village) in South Asia [ 28 ]. Moreover, machismo (e.g., a man would never seek treatment unless he felt pain and men should not seek medical help frequently) also influenced help-seeking in Australia and the US [ 26 , 30 ].

Policy/environment

The policy-related barriers to help-seeking were identified as lack of medical services. For example, absence of a specialized hospital in the area that can provide treatment [ 26 , 28 , 34 , 35 ], lack of specialists such as doctors, laboratories or pharmacies in their area of residence [ 28 , 34 ], and absence of a place to obtain information on treatment or screenings [ 35 ] contributed to this issue. This indicated that physical distance from medical institutions in rural areas hindered help-seeking. Medical institutions are located far away [ 28 , 34 ], and insufficient means of transportation to the hospital [ 34 ] exacerbate the issue. Therefore, there is a time burden to access the tests required to receive a diagnosis and to seek help or receive test results. Additional factors include dealing with different doctors during every visit, and insufficient means of transportation to reach the hospital with long waiting times [ 26 , 32 , 34 ]. Help-seeking is associated with accessibility and availability of regional healthcare facilities and medical systems.

Facilitators

Presentation of symptoms of abnormal conditions such as pain and other serious symptoms are facilitators of help-seeking [ 26 , 31 , 32 ].

Understanding from surrounding people facilitates help-seeking [ 26 , 32 , 35 ]. Specifically, being told by people that it was cancer [ 26 , 35 ], and receiving support from neighbors, family members, and healthcare professionals encourage help-seeking [ 32 ].

This scoping review explored factors associated with help-seeking for cancer treatment among rural and remote residents worldwide to develop actionable policies, preventive strategies, and relevant interventional tools that may help facilitate the use of oncological services in rural areas. The factors were grouped into four general categories based on the ecological model: intrapersonal, interpersonal, groups/cultures/organizations, and policy/environment. The diverse categories indicate that many varied factors impact help-seeking in rural settings.

Principal findings and directions for future implication in rural areas

Our findings support factors such as age, low educational level, difficult financial conditions, symptom appraisal, lack of knowledge, fear, and habits related to health services, were associated with help-seeking. These intrapersonal factors are consistent with the components of a model depicting factors associated with help-seeking behaviors among patients with cancer [ 41 ]. In particular, the characteristics of help-seeking of cancer are symptoms experienced and so is symptom appraisal [ 42 ]. Symptom appraisal and presentation of symptoms have been reported in a majority of studies as barriers to help-seeking [ 26 , 27 , 29 , 31 ] and facilitators of help-seeking [ 26 , 31 , 32 ]. When a person notices a bodily change or symptom, they perceive it a reason to seek medical help. Therefore, presentation of symptoms such as pain is one of the facilitators of help-seeking. Moreover, our review identified self-reliance (a “grin and bear it” attitude or trying to manage things on one’s own), and fatalistic views (the beliefs that one’s future health is predetermined by fate or destiny [ 43 ]) as barriers to help-seeking. In the rural areas, adversity was viewed as an inevitable part of life, and people were expected to cope with unexpected events as they occurred [ 44 ]. Rural people tend to accept ill-health with high degrees of stoicism and fatalism [ 45 ]. Thus, self-reliance and fatalism are viewed as values of rural people. When considering the directions for future intervention in rural areas, health service providers need to understand such rural characteristics and values when offering services.

In the interpersonal factors, our review revealed that factors such as a lack of understanding of family members, influence of surrounding people, role obligations, and a lack of trust in experts hindered help-seeking. In contrast, understanding one’s close circle, such as family and friends, promotes help-seeking. A nursing study conducted in rural areas reported that residents were closely connected and that family ties played a central role [ 37 ]. We recommend including the need for an array of studies and intervention approaches to advance help-seeking, to not only people in rural areas but also to their families using family-based approaches from these results.

In the group/cultural/organizational factors, our review also identified prejudice/social stigma, shame, lack of anonymity, and social norms as barriers to help-seeking. In rural areas, “small society” is still prevalent; thus, “everybody knows everybody” and the people’s daily lives are highly visible and open [ 44 ]. This scoping review shows that the regional cultural expectations such as lack of privacy and confidentiality in rural areas can constrain help-seeking, compounding a sense of isolation. This kind of rural context presents unique constraints in help-seeking, such as the lack of opportunities to consult feelings and experiences with others with similar personal, social, and cultural experiences. Hence, it is necessary to seek help inside and outside one’s community. According to a previous study that focused on rural areas, stigma has been related to a lack of knowledge, and educational interventions have been proven to be effective in reducing social prejudice and stigma in the community [ 46 ]. Therefore, educational interventions to spread awareness and knowledge about cancer may be effective in improving help-seeking among individuals in rural areas. Additionally, using technology-based communication, such as telehealth services, may enhance help-seeking for people living in rural areas [ 47 ].

Moreover, owing to the lack of medical resources in rural areas, residents often travel long distances to seek medical help. The resulting time burden is a barrier to help-seeking. Although these issues have been previously identified e.g., from policy-based perspectives [ 48 ], there remains a need for research to go beyond the help-seeking behaviors of individuals to investigate healthcare systems at the national level. Recently, evidence has shown that telehealth services can efficiently and effectively improve healthcare access and cost-effectiveness for rural and remote areas [ 47 , 49 ]. We can consider retaining remote consultations alongside face-to face consultations in future routine healthcare services as this could improve access to healthcare in rural and remote areas.

Implications for practice

This study extracted factors related to help-seeking for cancer medical care among people living in rural areas, including intrapersonal, interpersonal, groups/cultural/organizational, and policy/environmental factors. In order to develop actionable policies, preventive strategies, and relevant interventional tools, multi-level educational and health-promoting interventions should be implemented to reduce social stigma and to improve patients’ and their families’ understanding of cancer. Moreover, medical resources such as telemedicine should be set up and promoted.

Limitations of the study

There are several limitations to our scoping review. First, we have used the unstandardized term for “rural” and “remote.” At present, some sections of the study are challenging in terms of establishing standardized terminology and national definitions of rural and urban areas [ 50 ]. Therefore, future studies should employ standardized terminology with “rural and remote” context using international statistics comparisons, such as degree of urbanization from new global agendas [ 50 ]. Second, our search was limited to only three databases and to studies published in English. This search based on the three databases might have led to omitting relevant articles. Thus, our results may not be generalizable. However, this review has highlighted many adequate comprehensive implications of rural and remote people’s help-seeking behavior for cancer medical care. The findings from the present review can be used as a starting point for future evidence-based strategies.

Conclusions

The scoping review provides an overview of literature on the factors associated with help-seeking for cancer treatment among rural residents. This scoping review explored factors associated with help-seeking for cancer treatment among rural and remote residents worldwide to develop actionable policies, preventive strategies, and relevant interventional tools that may help facilitate the use of oncological services in rural areas. Factors related to help-seeking for cancer medical care can be categorized into four themes: intrapersonal, interpersonal, groups/cultures/organizations, and policy/environment using the ecological model. From the 13 selected articles, the barriers and facilitators were identified. These included understanding of people, self-reliance, fatalistic views, lack of anonymity, social norms, and lack of medical resources. Future studies should consider interventions to promote help-seeking, which must involve intrapersonal, interpersonal and rural community groups, culture, and organizations of each rural area.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

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Acknowledgements

We wish to express our heartfelt appreciation to Grant-in-Aid for Scientific Research of the Japan Society for the Promotion of Science for funding.

This research was funded by Grant-in-Aid for Scientific Research of the Japan Society for the Promotion of Science (grant number 20 K19064). We wish to express our heartfelt appreciation.

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Oshiro, M., Kamizato, M. & Jahana, S. Factors related to help-seeking for cancer medical care among people living in rural areas: a scoping review. BMC Health Serv Res 22 , 836 (2022). https://doi.org/10.1186/s12913-022-08205-w

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Knowledge, Attitudes and Health-seeking behaviour among Patients with Tuberculosis: A Cross-sectional Study

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E-mail address of dr. ntombana mc’ deline rala, downloads 11,803.

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Background:

South Africa is hugely overburdened with the cases of Tuberculosis (TB); individual’s lack of knowledge, attitude towards the disease and delays in health-seeking behaviour, are indirectly associated with death. This study assessed the knowledge, attitude and treatment of TB, and further examined the health-seeking behaviour of TB patients.

This cross-sectional study involved 327 conveniently selected participants with TB from three community health centres in Nelson Mandela Bay Health District, Eastern Cape, South Africa. A close-ended questionnaire was used to collect demographic details, knowledge, attitude and health-seeking behaviour variables. Descriptive and multivariate logistic regression analyses were performed. Statistical significance was considered at alpha <0.05 and a confidence interval of 95%.

The majority of these TB patients indicated that cold air (76.5%), a dusty environment (85.9%), TB bacteria in the air (88.4%), and smoking (84.7%) had caused the disease. About 87.2% of the respondents indicated that TB treatment duration took six months or longer. Participants thought that follow-up sputum tests are an important part of TB treatment (70.6%); non-adherence to TB treatment might lead to drug-resistant TB or death (80%); TB disease could turn into HIV if not properly treated (77.4%) and that individuals with TB disease have HIV (59.9%). About 56.9% participants felt that TB treatment is difficult, takes a long time, is unpleasant, interferes with work or marriage, and people who drink and smoke are to blame for its spread (60.6%). The majority of the participants (74.0%) disagreed with TB being an African disease and 53.5% did not associate TB with poverty. The majority of the participants (92%) indicated that follow-ups at clinics were avoided because of stigmatisation. In the multivariate logistic regression analysis, the informal housing scheme was a statistically significant (p<0.05) factor determining the correct knowledge of TB (AOR=0.556; 95% CI: 0.316-0.977). There was a statistically significant association among TB knowledge, attitude and health-seeking behaviour.

Conclusion:

The participants generally had good knowledge about TB; however, there were misconceptions regarding its spread by cold air and dusty environments. The majority of participants did not attend follow-up TB treatment because of fear of stigmatisation. Formal settlements are associated with the correct knowledge of TB. Measures aimed at addressing the misconceptions about TB and its treatment are needed.

1. INTRODUCTION

Tuberculosis (TB) is an airborne, infectious disease caused by organisms of the Mycobacterium tuberculosis complex [ 1 ]. It mostly affects the lungs, and its symptoms include a persistent cough lasting for more than 3 weeks, chills, fever, night sweats, loss of appetite and fatigue. In the worst cases, blood is also found in the sputum, and patients complain of chest pain [ 1 , 2 ]. Tuberculosis is among the top ten causes of death globally [ 3 - 5 ]. Tuberculosis remains a major health problem in South Africa, even though its rate of spread has declined over the years, after reaching a peak in 2009 [ 3 ]. The Directly Observed Treatment Short-course (DOTS) is one of the principle programmes initiated by the World Health Organization (WHO) for the management and treatment of TB [ 6 ]. The DOTS is effective in escalating successful treatment results and lowering drug resistance by treating patients with a conglomerate of drugs for at least six months [ 7 ]. Many countries worldwide have adopted the DOTS programme, including South Africa.

Another strategy initiated by WHO in the fight against TB is the ‘End TB’ with its proposed milestones for 2020 and 2025 plus targets for 2030 and 2035 to reduce TB cases and deaths [ 5 ]. This strategy is focused on integrated person-centred care at all levels, expanded access to preventive treatment, maximal use of limited resources and roll out plus uptake of innovations [ 4 ]. The targets for 2030 are a 90% drop in TB deaths and an 80% decrease in the TB incidence rate (new cases per 100 000 population per year) compared with levels in 2015; 35% reduction in the number of TB deaths and a 20% reduction in the TB incidence rate [ 5 ]. Accordingly, the South African National Department of Health adopted the DOTS programme with strict guidelines and the `End TB’ strategy to combat the TB scourge in the country. In addition to the TB guidelines, the National Strategic Plan for HIV/Sexually transmitted infections /TB initiated measures aimed at addressing the societal norms and behaviours that fuel, amplify and trigger TB and HIV spread in South Africa, especially in the marginalised, poor and informal settlements [ 8 ]. Notwithstanding this, South Africa is among the eight countries accounting for two-thirds of TB prevalence globally [ 5 , 8 - 10 ]. In addition, TB is the leading cause of death in South Africa; the incidence rate for active TB was estimated at 322,000 in 2017, with 60% co-infected with HIV [ 11 ]. Worryingly, the Eastern Cape is one of the highly TB burdened provinces [ 11 ], and Nelson Mandela Bay Health District has one of the highest TB caseloads in the Eastern Cape Province [ 12 ]. The province also ranks third with the TB treatment defaulters and forms part of the ten worst regions in South Africa with TB-related deaths, poor TB cure and treatment success rates [ 13 ].

The high incidence of active TB infection, high proportion of latent infection and Human Immunodeficiency Virus (HIV) comorbidity, poor or high-risk infection control practices or non-adherence to treatment by patients has greatly thwarted effective TB control in South Africa [ 14 ]. Although DOTS is the most effective global TB programme, its effectiveness is related to the patients’ knowledge of TB, their ability to identify symptoms, as well as their attitudes and health-seeking behaviour, and timely accessibility to health services [ 6 , 8 , 15 ]. Moreover, the effectiveness of DOTS depends on the willingness of the patient to accept and comply with its principles [ 10 ]. Studies conducted in the low- and upper-middle-income countries have shown that patients with TB have a significant deficit in the levels of knowledge of causal agents of TB, transmission, poor attitudes and health-seeking behaviour [ 6 , 15 ]. In the Pacific island nation of Vanuatu, TB was attributed to the smoking of cigarettes; the consumption of kava; a mildly intoxicating drink found across the Pacific made from the roots of a certain plant; alcohol consumption; eating of contaminated food; the sharing of eating utensils and witchcraft [ 16 ]. In rural Uganda, smoking, an inherited consumptive tendency, witchcraft, heavy manual work, and sharing of food and eating utensils with a TB patient were factors associated with the cause of TB [ 17 ].

Anecdotal evidence has shown that patients with TB recognise symptoms of TB when they experience them; they find them worrisome, so they feel compelled to seek medical help. Studies conducted in the low- and upper-middle-income countries revealed that all patients with TB have good knowledge of TB symptoms, such as loss of appetite, weight loss, night sweats, fever, tiredness and a productive cough endured for more than a few weeks, where at times it is accompanied by blood in the sputum [ 6 , 15 , 16 , 18 ].

Regarding transmission, patients with TB have misconceptions. In India, people perceive TB to be transmitted through droplets, food sharing utensils and by touching a person with TB [ 15 ]; in Ethiopia, inhaled droplets, exposure to dust and cold and drinking of raw milk are blamed [ 19 ]; and in Brazil, inhaled droplets; wearing the same clothes; sharing eating utensils; having sexual intercourse with the infected person and drinking contaminated water are deemed the common modes of transmission [ 20 ].

Concerning attitudes, few patients with TB disclose their TB status freely to family and friends. Most of them believe that there are many treatments available, and one can stop TB treatment if one feels better [ 17 - 19 ]. The reasons for patients with TB not disclosing freely is the fear of being isolated by the family because of the fear of airborne infection, the fear of being labelled as having HIV and subsequent stigmatization of the whole family [ 17 ]. Lack of knowledge of a causal agent, the transmission of TB and an attitude of unwillingness to disclose TB delay and affect proper health care. In such instances, TB patients would first seek care from a traditional healer with the belief that traditional medicine is the ideal treatment for TB; medical consultation will be the last option when patients are presenting the worst TB symptoms [ 15 , 16 , 18 , 19 ]. The delay in seeking health care by TB patients might negatively impact the management of TB.

Recognising that there are several international studies exploring the Knowledge, Attitudes and Practices (KAP) regarding TB [ 21 - 23 ], and in the socio-economic perspective; and TB awareness has been explored in South Africa, little information exists on community-based context. Whether late uptake of treatment, poor cure rate and treatment success rates are responsible for the prevalence and death rate from TB or not is speculative; our research is responding to the high defaulter and death rates in Nelson Mandela Bay Health, Eastern Cape, South Africa. The study seeks to ascertain whether TB control and management are influenced by 1) a lack of knowledge and an inability to identify symptoms, 2) negative attitudes and unwillingness to accept, disclose, and comply with DOTS principles and 3) a delay in health-seeking behaviour among patients with TB. Such information may be useful for designing health facility interventions for TB control and management in this setting with high TB rates.

2. MATERIALS AND METHODS

2.1. study design.

This cross-sectional study took place from June 2018 to October 2018. It followed a descriptive, non-experimental research design with a quantitative approach to investigate knowledge, attitudes and health behaviour of TB patients in Nelson Mandela Bay Health District, Sub-District C. Nelson Mandela Bay Health district was purposively selected because of high records of TB patient numbers and concurrent poor treatment outcomes. In 2011, Nelson Mandela Health District declared TB a health crisis, and it ranked among the ten worst metros in the country for deaths caused by TB.

2.2. Population and Sample

The target population was TB patients in the three community health centres in Nelson Mandela Bay - Sub District C (PE Central Community Health Centre, West End clinic and Gqebera clinic) as they experience larger volumes of patients compared to other clinics in the sub-district. According to Nelson Mandela Bay Health District, the three clinics combined from July 2016 to January 2017 had received 496 patients with TB (Gqebera clinic 238 patients, West End clinic 157 patients and PE Central Community Health Centre 101 patients).

The sample consisted of 327 conveniently selected TB patients from the Nelson Mandela Bay Health District, Sub-District C clinics. Participants were TB patients over 18 years of age and they had been on treatment for at least one month for both pulmonary or extrapulmonary TB, bearing in mind the economic and relationship impact of tuberculosis therapy. These patients were recruited regardless of how they were diagnosed. The pulmonary TB patients were mostly diagnosed through bacteriological confirmation tests of the sputum like GeneXpert (70% of the patients), smear microscopy and culture. Chest x-rays were done in some patients who could not produce sputum or who had negative GeneXpert results and were HIV positive, and where extrapulmonary TB (such as pleural effusions and pericardial TB) was suspected. The x-ray findings interpretation was made in light of the patients’ history and other clinical findings. Extra-pulmonary TB investigations included ultrasound examination for abdominal or pericardial TB, culture of tissue or fluid from fine needle aspirate or biopsy and histological examination of tissue. Visiting patients not registered in the three community health centres, but collecting treatment from those facilities, were excluded. This was to reduce the chances of receiving information from patients outside the Nelson Mandela Bay Health District, sub-district C catchment area.

2.3. Instrument Design and Measures

The questionnaire was based on previous literature and TB experts’ (TB nurses) input. The questionnaire was divided into four sections. Section A focused on the demographic profiles (age, gender, level of education, marital status, employment and housing). These demographic indicators formed the independent variables. Section B of the questionnaire concentrated on the knowledge of TB patients regarding TB (dependent variable); while section C dwelt on the attitude of TB patients regarding TB (dependent variable). Section D focused on the health-seeking behaviours of TB patients (dependent variable). The format of the questionnaire was a 5-Likert scale ranging from strong agreement to strong disagreement of statements (1 = strongly agree, 2 = agree, 3 = I don’t know, 4 = disagree and 5 = strongly disagree) with a provision for uncertain answers for all the dependent variables. Thirteen items were used to measure patients’ knowledge about TB disease, causes, treatment and importance of adherence. Patients’ attitudes were measured using ten items where they were required to indicate their views regarding treatment duration, treatment effects on marriage and work, community perception of TB patients and how they acquire and spread TB, perceptions of community reaction to their TB status. For health-seeking behaviour, patients were required to indicate their views regarding their perception of their early TB symptoms, use of alternative treatment, treatment follow-up and treatment location. TB stigma was measured by asking the participants how TB patients are being perceived or supported.

Cronbach alpha coefficients, measuring internal reliability for the items, were 0.628 for TB knowledge variables, 0.828 for TB attitude variables and 0.719 for health-seeking behaviour variables. A content validity index (CVI) was compiled by requesting two TB focal persons in two clinics to indicate to what extent they considered every item relevant to the TB policy implemented at their clinic on a 5-point scale. In each case, 1 indicated no relevance and 5 indicated complete relevance. Twenty-nine items scored a CVI of 5, three items scored a CVI of 4.5, and only one item had a CVI of 2.5, so it was discarded. Overall, the instrument had a CVI of 98.6%. The questionnaire was piloted at a primary health care facility outside the study setting for practicality and was modified prior to distribution amongst the targeted patients.

The primary outcome used in this study is the proportion of respondents who had knowledge, attitudes and health-seeking behaviour concerning tuberculosis. The covariates measures were age, gender, level of education, marital status, employment and housing.

2.4. Ethics

The Human Research Ethics Committee of the University of Fort Hare gave approval for the researchers to conduct the study (Reference number: GOO211SONY01). Before administering each questionnaire, the participants were provided with information on the aim and nature of the study. Participation was voluntary and participants were required to sign an informed consent form. Anonymity and confidentiality of the information provided were assured. Participants’ identities were concealed.

2.5. Data Collection Procedure

Data collection took place between June and October 2018. The study involved three research assistants who were community care workers based at each clinic; these assistants were able to speak English, Xhosa and Afrikaans. Three community health care workers were trained on obtaining participants’ consent, administration of questionnaires, handling of data and ensuring quality data. A pilot study was conducted at Central clinic (Rose Street), Nelson Mandela Bay Sub-District C with 10 participants, who did not form part of the main study. The pre-test lessons learned from the pilot study helped to validate and further improve the questionnaire.

2.6. Data Collection Procedure

Data was collected in the TB waiting rooms. The aim and nature of the study were explained to the patients. Willing patients were provided with informed consent forms to sign before administering the questionnaires to them. Assistance was offered by the research assistants to those having difficulty reading or understanding the questionnaire. The questionnaires were completed and collected on the spot.

2.7. Data Analysis

Descriptive statistics, such as frequency counts and percentages, were used to analyse knowledge and attitudes towards TB causes, treatment, adherence to treatment and health-seeking behaviour. Each correct answer on knowledge, attitude and health-seeking behaviour scored one point and an incorrect answer scored zero. The questions included a ‘don’t know’ option, coded as zero, which indicated that a participant did not have the correct knowledge, attitude or health-seeking behaviour. Higher scores for each variable indicated greater knowledge, better health-seeking behaviour and more positive attitudes towards TB treatment and adherence, respectively. Multivariate logistic regression analysis was used to examine the influence of demographic variables on the knowledge, attitude and health-seeking behaviour towards TB. A p-value of 0.05 was set for statistical significance. All statistical analyses were performed using Statistical Package for Social Sciences (SPSS) version 24.0.

3.1. Demographic Characteristics of the Participants

Of the 327 participants, the majority of the patients (191/58.4%) were 35 years and older, 54.1% were males, 63.0% had secondary education, 55.4% were unemployed, 70.9% were single and 53.8% had formal housing (Table 1 ).

3.2. Knowledge of TB Disease, Causes, Treatment and Adherence

Table 2 displays the knowledge of TB disease, causes, treatment and adherence of the patients. The majority of the TB patients indicated that they thought TB is caused by cold air (76.5%), dusty environment (85.9%), TB bacteria in the air (88.4%) and smoking (84.7%). About 87.2% of the respondents indicated that TB treatment duration takes six months or longer. Some 73.1% of the respondents did not agree that people should stop taking TB treatment as soon as they feel better; 74.0% of the patients disagreed that TB treatment makes people sick and should be stopped when sick; 78.6% of the patients disagreed with the statement that it is not necessary to finish TB treatment when one feels better. About 70.6% of the respondents were aware that follow-up sputum tests are an important part of TB treatment. Over 80% were aware that non-adherence to TB treatment may lead to drug-resistant TB or death. About 77.4% of the respondents thought that TB disease can turn into HIV if not properly treated, and more than half of the respondents (59.9%) thought that everybody with TB disease has HIV.


	-	-
<35	136	41.6
≥35	191	58.4
	-	-
Male	177	54.1
Female	150	45.9
	-	-
None	31	9.5
Primary	60	18.3
Secondary	206	63.0
Tertiary	30	9.2
	-	-
Formal employment	65	19.9
Self-employed	27	8.3
Menial jobs	54	16.5
Unemployed	181	55.4
	-	-
Married	61	18.7
Single	232	70.9
Divorced	22	6.7
Widowed	12	3.7
	-	-
Informal	151	46.2
Formal	176	53.8

3.3. Attitude of Patients Towards TB Disease, Treatment and Adherence

As shown in Table 3 , more than half of the respondents felt that TB treatment is difficult, takes a long time, is unpleasant and interferes with work or marriage. However, the majority (74.3%) did not feel that TB treatment made them feel sick. About 60.6% felt that irresponsible people who drink and smoke are to blame for the spread of TB; and 52.9% believed that people who drink and smoke get what they deserve when infected with TB. About 53.8% felt embarrassed to have to take TB treatment and felt that the community does not respect people with TB. The majority of the participants (74.0%) did not agree that TB is an African disease and 53.5% did not associate TB with poverty.

3.4. Health Seeking Behaviour

As shown in Table 4 , 92% of the respondents indicated that people do not go back to the clinics for follow-up out of fear of what people will say about them. The majority of the respondents (85.6%) agreed that people do not go to the clinics in their catchment area for consultation and follow-up out of fear of what people will say about them. In addition, a majority of 89.9% agreed that most people do not go back to the clinic for their TB results. About 76.1% of the respondents went to more than one clinic before they could start treatment. Few (18%) participants preferred buying treatment from the pharmacy before going to the clinic for treatment of TB; and 15.9% preferred going to traditional healers before they went to the clinic for TB treatment. More than half the respondents (55.4%) reported that only people with a severe cough should go to the clinic to test for TB. About 47.7% of the respondents reported that they did not take the TB symptoms seriously in the beginning and hoped the symptoms would go away on their own.

3.5. Multiple Logistic Regression for Knowledge of TB Disease, Causes, Treatment and Adherence

Results from the multivariate logistic regression analysis conducted for knowledge of TB patients, together with biographical information of TB patients, are presented in Table 5 . None of the variables were statistically significant to determine the TB patients’ knowledge of TB disease causes, treatment and adherence. The housing scheme was a statistically significant (p<0.05) factor determining the knowledge of TB causes, treatment and adherence. Compared with the reference group (informal housing scheme), formal housing was a significant predictor of correct TB knowledge (OR=0.556; 95% CI: 0.316-0.977). None of the independent variables were statistically significant in determining the positive attitude of patients towards TB disease, treatment and adherence. Likewise, none of the factors were significant in determining the correct health-seeking behaviour of TB patients.


Tuberculosis is caused by cold air	250(76.5)	77(23.5)
Tuberculosis is caused by the dusty environment	281(85.9)	46(14.1)
Tuberculosis is caused by tuberculosis bacteria in the air	38(11.6)	289(88.4)
Tuberculosis is caused by smoking	50(15.3)	277(84.7)
Tuberculosis treatment duration takes six months or longer	42(12.8)	285(87.2)
People should stop taking TB treatment as soon as they feel better	88(26.9)	239(73.1)
TB treatment makes people sick and should be stopped as soon as you feel sick	85(26.0)	242(74.0)
It is not necessary to finish TB treatment if I feel better after two months	70(21.4)	257(78.6)
It is not necessary to give follow-up sputum if I am on treatment	96(29.4)	231(70.6)
Drug-resistant TB occurs when a person does not finish TB treatment	55(16.8)	272(83.2)
Not taking tuberculosis treatment may lead to death	37(11.3)	290(88.7)
TB can change to HIV if not treated properly	253(77.4)	74(22.6)
All people with TB disease are also infected with HIV	131(40.1)	196(59.9)


TB treatment is difficult and takes a long time	186(56.9)	141(43.1)
TB treatment is unpleasant and difficult	179(54.7)	148(45.3)
TB treatment interferes with life commitments like work and marriage	192(58.7)	135(41.3)
Irresponsible people who drink and smoke are to blame for the spread of TB	198(60.6)	129(39.4)
People who drink and smoke get what they deserve when they are infected with TB	173(52.9)	154(47.1)
It is embarrassing to have to take treatment for TB disease	176(53.8)	151(46.2)
People in the communities do not respect people with TB	176(53.8)	151(46.2)
TB is associated with poverty	152(46.5)	175(53.5)
TB is an African disease	85(26.0)	242(74.0)
All TB treatment makes people sick	84(25.7)	243(74.3)


Only people with a severe cough should go the clinic to test for TB	181(55.4)	146(44.6)
I did not take the TB symptoms seriously; I was hoping the symptoms would disappear with time	156(47.7)	171(52.3)
People do not go back to the clinics for their TB results	294(89.9)	33(10.1)
People do not make TB follow-up visits because of fear of what people will say about them.	301(92.0)	26(8.0)
Reluctance to visit the clinics in their own area for consultation and follow-up because they fear community rejection	280(85.6)	47(14.4)
I am currently attending a clinic that is outside my catchment area	93(28.4)	234(71.6)
Visiting more than one clinic before starting TB treatment	76(23.2)	251(76.8)
Preferred buying treatment from the pharmacy before going to the clinic for TB treatment	59(18.0)	268(82.0)
Preferred going to traditional healers before seeking medical TB treatment	52(15.9)	275(84.1)
I thought the early TB symptoms would go away on their own	82(25.1)	245(74.9)

Variables	B	OR (95% CI)	p-value
	-	-	-
<35	-	1	-
≥35	0.105	1.111 (0.622-1.984)	0.772
	-	-	-
Male	-	1	-
Female	0.102	1.107(0.637-1.925)	0.719
	-	-	-
None	-	1	-
Primary	-.567	0.567 (0.155-2.077)	0.392
Secondary	-.691	0.501 (0.169-1.484)	0.212
Tertiary	-.348	0.706 (0.282-1.771)	0.458
	-	-	-
Formal employment	-	1	-
Self-employed	-.491	0.612(0.292-1.281)	0.192
Menial jobs	0.082	1.085(0.405-2.909)	0.871
Unemployed	-.417	0.659(0.285-1.524)	0.330
	-	-	-
Married	-	1	-
Single	1.076	2.933(0.550-15.637)	0.208
Divorced	0.595	1.813(0.362-9.072)	0.469
Widowed	0.057	1.059(0.145-7.728)	0.955
	-	-	-
Informal	-	1	-
Formal	-.588	0.556(0.316-.977)	0.041

4. DISCUSSION

This present study was designed to assess the knowledge, attitude and treatment of TB, and to further examine the health-seeking behaviour of TB patients attending community health centres in the Eastern Cape, South Africa. The regression analysis exhibited no difference in knowledge, attitude and health-seeking behaviour in relation to age, gender, literacy level, employment status and marital status. This suggests that people in the Nelson Mandela Bay Sub-District C share the same TB knowledge, attitude and health-seeking behaviour. This is similar to a South African study where regression analysis of TB knowledge and attitude toward TB showed no significant difference in age, gender and education [ 24 ]. However, a Nigerian study showed that males have a higher level of TB knowledge than females, and the knowledge of TB was higher among participants who were single, married, aged 16-29 years and had tertiary education [ 25 ].

Tuberculosis knowledge was generally high among TB patients. While most of the participants knew that bacteria causes TB, there was also a high misconception that cold air and dust cause TB. These findings are similar to an Ethiopian study where 79.9% of the respondents knew the source of TB, yet 62.2% still mentioned exposure to cold air as a cause and 65.4% indicated exposure to dust [ 19 ]. In contrast, a study from Vanuatu reported that 96% of the TB patients did not know that TB was caused by bacteria in the air [ 16 ]. A misunderstanding of TB causation and a knowledge barrier can influence patients’ health-seeking behaviour, adherence to a prescribed treatment regimen and treatment outcome [ 16 ]. This calls for concerted efforts to dispel the misconceptions people have on TB causes and treatment; they also need to be enlightened about the wisdom of repositioning their TB health-seeking behaviour. Participants in this present study misrepresented some facts about TB and HIV, respectively: in fact, 77.4% indicated that TB could change into HIV; and HIV infects TB patients. A previous study done in South Africa revealed that 89% of the respondents agreed that only people who are HIV positive have TB and 60% agreed that all people with TB would develop HIV. This notion can be explained by the fact that South Africa has a high prevalence of HIV and TB is the major source of mortality in people who are co-infected with HIV and TB [ 11 , 25 ]. The belief that having TB automatically translates to HIV positive provides a potential explanation of why some TB patients hide symptoms, resulting in a delay to seek medical advice and get a diagnosis of the disease [ 26 ]. In addition, the threat of HIV stigma and fear or denial also affect early diagnosis and treatment of TB [ 27 ]. As such, there is a need to scale up TB programmes focusing on stigma-related perceptions and attitudes, especially regarding patient support and family sensitisation, irrespective of HIV status [ 27 ].

Most (70.6%) of the respondents were aware that follow-up sputum tests are important. This perceived benefit is suggestive of good communication of treatment guidelines between health workers and patients. In contrast, a Zambian study revealed that only 57% of the participants knew the importance of follow-up sputum tests [ 28 ]. The sputum test results are important to determine the level of treatment required in the future and the outcome.

This study revealed negative attitudes towards the TB disease, treatment and adherence measures. More than half of the respondents felt that TB treatment is difficult and takes a long time. A study in Malawi found that the majority of the participants echoed that TB disease treatment is not easy [ 27 ]. The Moroccan study found that 34.1% of the non-adherent TB clients cited that TB treatment took long [ 29 ]. In addition, 58.7% of the respondents indicated that TB treatment interferes with work or marriage. Similar findings were noted in Zambia, where 35% of the TB patients reported dismissal from work and divorce [ 28 ].

The findings of the study indicated that 53.8% of the participants felt embarrassed taking TB treatment, and felt that the community did not respect people with TB. Similar findings were reported in an Indonesian study where 30% of the TB and ex-TB patients kept their illness a secret because of embarrassment and fear of discrimination [ 30 ]. Similarly, 64.2% of participants in a Moroccan study believed that society does not respect patients with TB [ 31 ].

The majority of the respondents (84.7%) concurred that smoking can cause TB. Smoking is a predisposing factor for TB [ 32 ]. This result is suggestive of high awareness of perceived susceptibility to tuberculosis if one is a smoker. In the Moroccan and Vanuatuan studies, only 15.7% and 26% of the respondents respectively, knew that smoking predisposes one to TB [ 16 , 30 ]. More than half of the population (52.9%) of respondents voiced that people who acquire TB through smoking and drinking were getting what they deserved. A similar study in South Africa revealed that 74% of the respondents agreed that people who smoke and get TB deserve their punishment [ 30 ]. This notion can create fear of judgement by the community that can hinder health-seeking TB treatment and compliance. Most of the respondents (60.6%) in this present study acknowledged that reckless people who drink and smoke are to blame for the spread of TB. Similarly, 90% of the study respondents in a South African study agreed that irresponsible drinkers and smokers are to blame for the spread of TB [ 24 ].

Almost half (47.7%) of the respondents in this study did not initially take their symptoms seriously and more than half of the respondents were of the opinion that only people with a severe cough should seek medical attention. This is consistent with a Zambian study where (66%) did not associate their symptoms with TB beforehand [ 28 ]. This implies distorted personal susceptibility and that disease severity is the major cue to seeking health care. Patients waiting until a cough is severe leads to a delayed diagnosis and treatment commencement. This implies that there is a need for community sensitisation programmes to emphasise that any cough could indicate TB infection, not only a severe one.

5. LIMITATION OF THE STUDY

The present study focused only on three community health centres in Nelson Mandela Bay Health District, Sub-District C. Therefore, the results cannot be generalised to the entire province or country. A structured questionnaire was used for data collection; consequently, no in-depth information could be obtained about the TB patients’ lived experiences while suffering from TB in Nelson Mandela Bay Sub-District C. Notwithstanding these limitations, the study provides insights into the knowledge, attitudes and health-seeking behaviour among patients suffering from TB in an understudied region with a high TB prevalence rate. Such information may be useful to inform health policy interventions on TB management.

The patients showed good comprehension of the causes of TB, duration of treatment and importance of treatment completion. Nevertheless, some patients had misconceptions about TB being caused by cold air and dust; untreated TB may convert to HIV and that having TB translates to HIV infection. As for attitudes towards TB, most patients regarded TB treatment as unpleasant, difficult, being a disease that interferes with work/marriage and endures too long. In addition, the patients expressed sentiments of community disrespect. With respect to health-seeking, it was revealed that patients had a low regard for the follow-up of TB test results and treatment. Disease severity was also the main driver for seeking medical assistance. There was no significant influence between socio-demographic variables (except for formal housing) and knowledge, attitude and health-seeking behaviour. These findings prompt the need for primary health care facilities in Nelson Mandela Bay and similar settings to strengthen health education solidarity in fighting stigmatisation; it would be advisable to build strong TB patient support groups in order to address prevailing difficulty experienced by patients while on treatment. Additionally, health education in these facilities should put more focus on tackling prevailing misconceptions about TB and to correct misinformation that might encourage social isolation of TB patients together with promoting health-seeking behaviour.

LIST OF ABBREVIATIONS


	= Adjusted Odds Ratio
	= Confidence Interval
	= Directly Observed Treatment Short course
	= Human Immune Virus
	= Tuberculosis
	= World Health Organization

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

The Human Research Ethics Committee of the University of Fort Hare, South Africa approved the study (Ethics Number: GOO211SONY01).

HUMAN AND ANIMAL RIGHTS

No animals were used in this research. All human research procedures followed were in accordance with the ethical standards of the committee responsible for human experimentation (institutional and national), and with the Helsinki Declaration of 1975, as revised in 2013.

CONSENT FOR PUBLICATION

The nature and purpose of the study was explained to the participants who provided their consent to participate in the study.

AVAILIBILITY OF DATA & MATERIALS

Data supporting the findings of this study are available within the article.

The financial assistance provided by Govan Mbeki Research and Development Centre and the Health and Welfare Sector Education and Training Authority (HWSETA).

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

We acknowledge all the study participants for taking part in this study. In addition, we appreciate the role played by the research assistants in data collection.

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Research article
Open access
Published: 05 February 2022

Health-seeking behavior of COVID-19 cases during the first eight weeks of the outbreak in Singapore: differences between local community and imported cases and having visits to single or multiple healthcare providers

Min Zhi Tay 1 ,
Li Wei Ang 1 ,
Wycliffe Enli Wei 1 ,
Vernon J. M. Lee 2 , 3 ,
Yee-Sin Leo 3 , 4 , 5 , 6 , 7 &
Matthias Paul H. S. Toh 1 , 3

BMC Public Health volume 22 , Article number: 239 ( 2022 ) Cite this article

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COVID-19 is a novel pandemic affecting almost all countries leading to lockdowns worldwide. In Singapore, locally-acquired cases emerged after the first wave of imported cases, and these two groups of cases may have different health-seeking behavior affecting disease transmission. We investigated differences in health-seeking behavior between locally-acquired cases and imported cases, and within the locally-acquired cases, those who saw single versus multiple healthcare providers.

We conducted a retrospective study of 258 patients who were diagnosed with COVID-19 from 23 January to 17 March 2020. Variables related to health-seeking behavior included number of visits prior to hospitalization, timing of the first visit, duration from symptom onset to admission, and places where the cases had at least one visit.

Locally-acquired cases had longer duration from onset of symptoms to hospital admission (median 6 days, interquartile range [IQR] 4–9) than imported cases (median 4 days, IQR 2–7) ( p < 0.001). Singapore residents were more likely to have at least one visit to private clinics and/or government-subsidized public clinics than non-residents (84.0% vs. 58.7%, p < 0.001). Among locally-acquired cases, those who sought care from a single healthcare provider had fewer visits before their hospital admissions compared with those who went to multiple providers (median 2 vs. 3, p = 0.001).

Our study indicates the need to encourage individuals to seek medical attention early on in their patient journey, particularly from the same healthcare provider. This in turn, would facilitate early detection and isolation, hence limiting local transmission and enabling better control of the COVID-19 outbreak.

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Nearly two years have passed since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared by the World Health Organization as a pandemic. An intact and comprehensive surveillance system remains one of the most important public health measures in this prolonged pandemic with over 255 million cases reported worldwide as of 19 November 2021 [ 1 ]. In Singapore, a total of 1,375 cases had been reported as of 7 April 2020 since the start of the outbreak [ 2 ], prior to the implementation of an elevated set of safe distancing measures, as a “circuit breaker” to pre-empt the trend of increasing local transmission of COVID-19. This was one of the measures Singapore swiftly adopted in order to “flatten the epidemic curve” and avoid overwhelming the healthcare system [ 3 ].

A resilient healthcare system is the crux of any emergency preparedness response, with providers building up surge capacity during normal operations in preparation of a high impact occurrence which could escalate healthcare demand and strain existing resources [ 4 , 5 ]. Transmission risks within the community must be minimized, hence, the role of an enhanced surveillance system is crucial to detect and isolate cases promptly. This would ideally encompass stakeholders from various settings. Previous studies conducted in Singapore after the SARS outbreak in 2003 have highlighted the important role of primary health providers, as many cases sought medical attention from their family physicians as the first level of contact [ 6 , 7 ]. Furthermore, capitalizing on primary care providers could potentially augment care capacities of the healthcare system in outbreak situations [ 6 , 7 ]. International studies have also demonstrated the value of primary healthcare providers in sentinel surveillance [ 5 , 8 , 9 , 10 , 11 , 12 ].

In Singapore, government and independent private primary care clinics form the stronghold of the primary care clinics. A significant portion of private clinics have been voluntarily engaged under the Public Health Preparedness Clinics scheme [ 13 ]. These clinics, deployed in times of public health crisis to provide affordable community care and early detection of suspected cases, were activated in February 2020 in response to the COVID-19 situation [ 14 ].

As health-seeking behavior is a critical factor to take into consideration in emergency preparedness models, this study aims to describe the characteristics of laboratory confirmed COVID-19 cases and their health-seeking behavior prior to hospital admission and isolation. The findings provide insights into reviewing and tailoring public health messaging to guide appropriate health-seeking behavior during the period of an infectious disease outbreak.

We included all cases diagnosed with COVID-19 by SARS-CoV-2 real-time polymerase chain reaction in Singapore from 23 January to 17 March 2020, whose data was collected as part of routine epidemiological investigations under the Infectious Diseases Act. We excluded (i) asymptomatic cases as they were unlikely to visit primary healthcare institutions, (ii) dormitory cases as this subpopulation had different health-seeking behavior and diagnosis workflow, and (iii) persons subsequently determined to be false positives. As we collected details on visits prior to hospitalization for cases reported until 17 March 2020, the study period was confined to about 1.8 months from the report of the first diagnosed case of the COVID-19 outbreak.

Primary care was defined as community ambulatory health services, consisting of private general practitioner clinics and government-subsidized public clinics, in addition to emergency department (ED) of hospitals where patients were not admitted. Locally-acquired cases were patients who did not report travelling outside Singapore up to 14 days before symptoms onset. Imported cases were travellers who returned to Singapore within 14 days of symptom onset.

We compared health-seeking behavior in different subgroups of COVID-19 cases: (a) imported vs. locally-acquired, and (b) those who sought care from one primary care provider vs. multiple care providers within the group of locally-acquired cases. Variables of interest included number of primary healthcare visits prior to hospitalization, timing of first visit, duration from symptom onset to admission, and medical touchpoints where cases reported at least one visit.

Numbers and proportions were presented for categorical variables, and median and interquartile range (IQR) for continuous variables. Fisher’s exact test or Chi-square test was used to compare categorical variables, and Mann–Whitney U test to compare continuous variables between any two groups. We used Spearman rank correlation to measure the association between the number of visits prior to hospitalization and duration from symptom onset to hospital admission. All statistical tests were two-sided, and statistical significance was taken as p < 0.05. Statistical analyses were performed using IBM SPSS Statistics for Windows, V.24.0 and figures were generated using R version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria).

We included 258 cases in our analysis, after excluding 5 asymptomatic cases, 2 dormitory cases, and 2 who were later determined to be false positives from the initial 267 cases reported from 23 January to 17 March 2020.

Comparison of locally-acquired and imported cases

Locally-acquired cases were older (median 50 years, IQR 35–61) than imported cases (median 40 years, IQR 31–53) (Table 1 ). Males constituted a higher proportion of imported cases than locally-acquired cases (64.9% vs 51.6%, p = 0.039). A higher percentage of locally-acquired cases were Singapore residents compared with imported cases (85.7% vs 43.3%, p < 0.001).

213 cases (82.6%) had at least one visit prior to hospitalization, and among these, 60.1% first sought medical attention at primary care clinics or hospital ED prior to admission within two days of symptom onset with no statistical difference detected between locally-acquired and imported cases (62.5% vs 56.5%, p = 0.395). Majority (89.8%) of locally-acquired cases attended primary care clinics at least once in their patient journey compared with 56.5% of the imported cases ( p < 0.001).

Among cases with at least one visit to care providers prior to hospital admission, the proportion with at least one visit to private general practitioner clinics and/or government-subsidized public clinics was higher among Singapore residents than non-residents (84.0% vs. 58.7%, p < 0.001). About 10.2% of locally-acquired cases attended ED without having any clinic visits, compared with 43.5% of imported cases ( p < 0.001).

Approximately 21.7% of locally-acquired cases had three or more visits to primary care clinics and/or ED compared with 6.2% of imported cases ( p < 0.001). Locally-acquired cases had longer duration from symptom onset to hospital admission (median 6 days, IQR 4–9) than imported cases (median 4 days, IQR 2–7) ( p < 0.001). This duration decreased as the epidemic progressed (Fig. 1 ).

Scatterplot with locally estimated scatterplot smoothing curve of duration from symptom onset to hospital admission and date of symptom onset among COVID-19 cases

The number of primary care visits and duration from symptom onset to hospital admission exhibited a more widespread distribution among locally-acquired cases (Fig. 2 ). There was a positive correlation between the number of visits prior to hospitalization and duration from symptom onset to hospital admission (Spearman’s rho = 0.461, p < 0.001).

Scatterplot of duration from symptom onset to hospital admission and number of primary care visits before admission among COVID-19 cases

Comparison of locally-acquired cases who had at least two primary care visits to single care provider and multiple care providers

Among locally-acquired cases with two or more visits, there was no significant difference between those who sought care from single and multiple care providers in their demographics: age (median 53 vs 48 years, p = 0.446), gender (62.1% vs 65.9% were males, p = 0.805) and nationality (86.2% vs 93.2% Singapore residents, p = 0.425) (Table 2 ). There were also no differences in timing of first visit, duration from symptom onset to admission and length of hospital stay. Cases who sought care from the same provider had fewer visits compared with those with different care providers (median 2 vs. 3, p = 0.001). A higher proportion of cases who saw multiple providers (61.4%) had at least three visits compared with those who saw a single provider (27.6%) ( p = 0.008). In addition, 72.4% of the latter group had two visits prior to their hospital admission (Fig. 3 ). In contrast, those with multiple care providers had up to six visits.

Scatterplot of duration of symptoms and number of primary care visits prior to hospital admission among locally-acquired COVID-19 cases who had two or more visits

Our study revealed differences in health-seeking behavior among subgroups of the initial COVID-19 cases in Singapore. Locally-acquired cases had significantly longer duration from symptom onset to hospital admission than imported cases (median 6 days vs. 4 days). Among those with at least one visit prior to admission, a higher percentage of locally-acquired cases had sought medical attention at the primary care level than imported cases (89.8% vs. 56.5%).

Imported cases were more likely to attend ED, bypassing primary care clinics completely (43.5% of imported cases vs 10.2% of locally-acquired cases attended ED directly without any clinic visits, p < 0.001), and those who attended clinics had fewer visits before being referred for further testing at the national screening centre or other EDs (6.2% of imported cases had at least three primary care visits prior to admission compared with 21.3% of locally-acquired cases) (Table 1 ). This observation could be due to two reasons: first, imported cases consisted mostly of Singapore international undergraduate students and foreigners working in Singapore, who were less likely to have a regular physician and with a raised perception of their infection risk, would attend ED directly or earlier in their patient journey; second, the heightened vigilance of primary care physicians towards this group. As the pandemic unfolded and more was known about the virus, Singapore Ministry of Health issued travel advisories and revised circulars circulated to doctors on suspect case definitions. Hence, the attitude of doctors would evolve accordingly with a lower threshold on testing patients deemed to be at increased risk of infection, which resulted in fewer visits by imported cases.

In contrast, doctors’ perception of lower community transmission risk at that time resulted in locally-acquired cases being referred only after lack of clinical improvement despite repeated visits. Equally crucial is the patient’s personal cognizance and health literacy [ 15 , 16 , 17 ]. Locally-acquired cases might have attributed their symptoms to a common cold or gastroenteritis, resulting in delays lasting up to a month in seeking medical attention. While seemingly innocuous under normal circumstances, this could have devastating consequences in an outbreak situation.

Overall, Singapore residents were more likely to attend primary care clinics than non-residents (84.0% vs 58.7%). Fever, cough, sore throat and diarrhoea were common presenting symptoms of COVID-19 cases [ 18 ], routinely managed within the community by family physicians.

Among the subgroup of locally-acquired cases with at least two primary care visits who saw the same care provider (median of 2 visits), a smaller proportion (27.6%) had three or more visits before being referred and admitted, compared with 61.4% of those who saw different providers (median of 3 visits). Having no basis for comparison from previous visits, a different healthcare provider lacks pertinent information when formulating management plan for the patient, which typically leads to later diagnosis, isolation and treatment, and consequently increases transmission risk. Our results thus highlight the risk of seeking care from multiple care providers or “doctor shopping” within the same episode of illness [ 19 , 20 , 21 ].

Doctor shopping could be attributed to various factors. One factor is healthcare accessibility; with high concentrations of primary care clinics island-wide, the convenience of attending clinics near one’s workplace and home outweighs care continuity concerns [ 19 , 22 , 23 , 24 ]. Another factor is unmet expectations; patients might have misconceptions of partaking less efficacious medications as symptoms persist, or feel unsatisfied with previous consultations [ 19 , 22 , 23 , 24 ]. Hence, appropriate public health communication to the public is crucial even during peacetime.

We acknowledged several limitations in our study. The observational design of our study precluded causal inference. This study was limited to the initial COVID-19 period where cases were predominantly imported. As the epidemic progressed, health-seeking behavior would evolve and as such, an in-depth study would be useful to ascertain attitudes and responses of the Singapore population at each phase of the outbreak. Our study was confined to cases diagnosed and managed in Singapore, and the findings may not be generalized to health-seeking behavior of COVID-19 cases in other countries with different health systems and financing mechanisms. As some information related to primary healthcare visits prior to hospitalization was ascertained based on self-reporting, the data collected was subjected to recall bias. Nevertheless, there were standard operating procedures in place to ensure the accuracy and consistency of information documented, such as having trained public health officers to interview the cases, and verifying movements reported by the cases from other sources.

Our findings demonstrated high attendance rates of cases within primary care settings, especially for Singapore residents, underscoring the significance of these care providers as trusted sources for patients. Thus, policy makers could consider creating a comprehensive sentinel surveillance network comprising private and public primary care clinics, which would enable early detection of suspected cases within the community.

Among the locally-acquired cases, our results favour the proposition of every resident seeking early medical attention from a single care provider, which would facilitate early detection and isolation, hence limiting local transmission and enabling better control of the pandemic. This demonstrates the importance of population health literacy especially during an outbreak, where there is a need for individuals to adopt appropriate healthcare seeking behavior (i.e. recognize when they should seek medical advice and visit the same care provider) and for the authorities to communicate public health messages simply and promptly via trusted channels [ 16 , 17 ].

Our study did not delve into population healthcare literacy and specific reasons for health-seeking behavior, which could constitute future considerations to inform and enhance public health prevention strategies.

Availability of data and materials

The data that support the findings of this study are available from the Ministry of Health, Singapore but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. However, if requested, Dr Matthias Paul HS Toh can assess the reasonableness and seek the approval of the Ministry of Health for approval to release the data.

Abbreviations

Emergency department

Interquartile range

Severe acute respiratory syndrome coronavirus 2

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We acknowledge the efforts of contact tracers and activity mappers, and offer our warmest gratitude to all frontline personnel for their hard work in Singapore's fight against COVID-19.

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The study was designed by MPHST and MZT, while MZT did the literature review. LWA analyzed the data and prepared the tables and figures. MZT drafted the manuscript. LWA, WEW, VJML, YSL and MPHST critically reviewed the manuscript. All authors approved the final version of the manuscript.

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Tay, M.Z., Ang, L.W., Wei, W.E. et al. Health-seeking behavior of COVID-19 cases during the first eight weeks of the outbreak in Singapore: differences between local community and imported cases and having visits to single or multiple healthcare providers. BMC Public Health 22 , 239 (2022). https://doi.org/10.1186/s12889-022-12637-8

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The Importance of Seeking Help for Mental Health Issues

1. introduction.

Unwillingness to seek professional help has been related to the stigma against mental illness and to the belief that nothing can be done about it. Despite the prevalence rates of mental health problems, few people seek professional help, and those who do often do so after several years when their problems are very severe. Previous investigations have shown that untreated mental health problems may hinder academic achievement, occupational success, and interpersonal competences. In addition, untreated mental health problems might have adverse effects on the quality of the individual's life. Vignette studies have the methodological advantage of manipulating the content of the vignettes and other characteristics. This feature allows the study of the meaning of differences in the contents of the vignettes and the relationship between these contents and characteristics of the respondent. These studies have explored the factors related to the willingness to seek help in several populations.

1.1. Background and Significance

Mental health has become a leading concern in the context of public health. Recent research estimates that one in five individuals will experience a mental health disorder. The negative impacts of untreated mental health are evident in various areas of life including employment, social connectedness, and overall health status. Mental health continues to be stigmatized by society, and as a result, many individuals choose not to seek help. These individuals often allow their condition to go untreated. In order to minimize the negative impacts, it is crucial that people seek help for their condition. In the context of mental health, help-seeking has been defined as an individual's understanding of a need for services, together with actually reaching out to receive and use these services. It was previously thought that a simple lack of knowledge or access to mental health professionals was the reason why many struggling with mental health were not seeking help. However, recent studies indicate that the decision to seek help is much more complex. There are many factors present including shame, hopelessness, and personal values, among others. Additionally, support from friends and family can also have a major influence on an individual's decision to seek help for an existing mental health issue. The response that an individual receives following disclosure of their condition can be a key factor and has been shown to impact a person's desire to actually seek help for the issue.

2. Barriers to Seeking Help

There are several barriers which may prevent some people from seeking help for mental health issues. Here are just a few: Time: People live busy lives and, as a result, they may feel that they simply don't have the time to seek help. This can be particularly the case when initially seeking help, as people may be reluctant to take time off work to seek treatment. Cost: Psychiatric treatment remains a service that isn't usually covered by state insurance programs. In other words, some people may not seek help because they simply can't afford it. Fortunately, aid is often available from freelance therapists or state-affiliated sources for individuals who can prove insufficient means. Denial: People who have psychiatric symptoms (in themselves or others) may be unaware that these symptoms reflect a treatable psychiatric condition. Denial of one's own psychiatric problems may lead to setbacks in the treatment process. Stigma: By now, it's been well-established that the mentally ill are stigmatized by other people. Some mentally ill people may not seek help because they are afraid of the stigma.

2.1. Stigma and Misconceptions

Despite advances in the diagnosis and treatment of mental health issues, numerous obstacles still prevent patients from receiving help. One particular barrier, which has been the subject of numerous psychological and sociological studies, is the stigma that continues to be attached to mental illness. This can be particularly strong when the individual affected is forced into involuntary treatment and can have a damaging effect on self-esteem. Some people also develop negative attitudes towards those who choose to seek voluntary help, believing them to be weak, inferior, or disfigured. In extreme cases, this prejudice can result in social exclusion, which exacerbates the mental health problem. Misconceptions are also a barrier to seeking help. These include the belief that if a person has a mental disorder, it will always be there, the "once mad, always mad" myth, and that treatment will be both too extreme and ineffective. In some cases, the experience of friends or relatives who have been treated for mental illness can result in a lack of trust in professional help. Age and gender also influence misconceptions, with men, for example, being more likely to be stigmatized and less likely to agree to treatment. Those who hold prejudiced views are themselves less well-informed about mental health, resulting in a self-perpetuating situation.

3. Benefits of Seeking Help

There are many reasons why people often don't ask for the help they need. This is especially true when it involves their mental health. Some reasons people give for not seeking help are "I don't want to appear weak," "It would make me feel embarrassed or ashamed," "It would go on my record and impact me in the future," "What would people or family members think of me if they knew I was seeing a therapist?" This list could go on and on, but the reasons are excuses we give ourselves for not seeking help. However, the rationale behind the thought process is flawed because the inability to take care of yourself with the tried and true treatment methods makes you weak. In reality, not taking advantage of the resources known to alleviate the negative self-medicating behavior is a sign of your inability to exercise healthy alternatives. The more knowledge you have about a situation, the better able you are to address and remedy its effect. Why wouldn't it be the same for a continual ringing of the alarm in your brain, especially if you could see its end? Achieving mental health doesn't have to be a death sentence. It wouldn't be if you had the first signs of any other physical issue looming in your body, so why take it as such for something so natural to the human condition? Seeking help is the most important factor in getting well, but how will this be accomplished if you don't know the person with whom you will be meeting? This is a hard stigma to get over, especially when your age group wasn't brought up in a generation of complete openness and understanding towards mental health as adults in today's society have seemingly implemented. Rest assured that if you reach out to someone for help, that professional can probably help you. They are trained to do so, no matter what their degree or specialty. And regardless of the specialty to what they have devoted their life to develop, mental health specialists do, in fact, provide real advice. Even if you think you are past the point of no return, why not seek someone who can bring you back to your carefree years? Someone who can relate to you, someone who is there to help - those are both the resources and the professionals available to you to become a better person. After all, why take a gun to war if you can use the power of words to end a situation peacefully? Talk first.

3.1. Professional Guidance and Support

People with serious mental health problems often require several types of assistance and benefit from a variety of services. This may include medication, therapy, social services interventions, active monitoring for problems, and practical help in solving them. Families and friends of someone with serious mental health problems may need help and guidance in getting that person into care, getting their own needs addressed, and helping their family member or friend in his or her recovery; and in preventing crisis situations. As the people with mental health problems improve, their needs for many types of services may change. Some people get better and, for a time, do not need assistance. Then they may get worse again. Some people do not get well but have periods of improvement. It can be difficult for families and friends to know what is needed at different times. The system of care for individuals with serious mental health problems is often difficult to understand and navigate. There are many programs, but they are sometimes hard to locate and may be filled up or unavailable when needed. Some programs require people to agree to things they may not want to or may not feel able to do. It takes time to learn how to access resources and to use them effectively. Families often need help learning the regulations and the system, and in advocating for the needs of the person with mental health problems. They may need information on their and the patient's legal rights, have questions about these rights answered, or need assistance in obtaining legal representation. They may need help in understanding treatment options or developing strategies for encouraging the person with the problem into treatment and predicting and preventing problem developments. Family therapy can help families in building coping and communication skills, understanding the ill person better, and dealing with the stresses and strains of caregiving, which are considerable.

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EFFECTS OF ABSTINENCE IN EARLY ADDICTION RECOVERY ON FUNCTIONAL BRAIN NETWORKS AND BEHAVIORS

Alcohol use disorder (AUD) poses negative health and social consequences, and is costly to affected individuals, loved ones, and society (Whiteford et al., 2013). It is a chronic neuropsychiatric disorder, associated with impaired decision making and altered functional connectivity patterns in the brain. Many studies have shown changes in the brain and behaviors after sustained abstinence using within-participant design or between-participant design comparing participants in recovery versus healthy controls (Muller & Meyerhoff, 2021; Wilcox et al., 2019). The purpose of this study was to investigate brain differences between participants in recovery and participants who are actively drinking. Specifically, this study evaluated within- and between-network resting-state functional connectivity (rsFC) strengths in the context of the triple network model, which focuses on three key networks for complex perceptual, emotional and behavior processing as well as introspection, theory of mind and self-awareness; the salience network (SN), the central executive network (CEN), and the default mode network (DMN) (Menon, 2019). Moreover, this study assessed the relationship between impulsive choices in temporal decision-making and changes in resting-state functional connectivity patterns in these networks.

This study included two groups: the Recovery Group and the Drinking Group. The Recovery Group included participants who were starting recovery (within one year), met AUD diagnosis criteria or showed lifetime heavy drinking behaviors during a 12-month period, received treatment for substance use disorder for alcohol and/or illicit drugs, and showed ongoing intentions and efforts to maintain recovery (n=18, 6 females, mean age=32.4±7.4, 17 White, mean years of education=14.5±3.1, average days of abstinence prior to interview days=78.2±45.7). The Drinking Group included participants who were currently drinking that met diagnosis criteria for AUD or showed heavy drinking behaviors (n=49, 24 females, mean age=31.7±6.4, 29 White, mean years of education=13.6±2.3). Participants underwent an initial screen day where structured interviews were conducted to evaluate the number of lifetime AUD criteria and prior drinking patterns. On the study day, participants completed computer tasks and questionnaires prior to their functional Magnetic Resonance Imaging (fMRI) sessions. Participants in the Recovery Group received a virtual reality (VR) intervention targeting future self-continuity where they interacted with avatars that are versions of themselves (present self and future selves in recovery and relapsed) prior to MRI sessions. All participants completed baseline Delay Discounting (DD) to measure intertemporal choice preferences prior to the fMRI sessions and prior to the VR intervention for the Recovery Group.

This study did not find any significant differences in within- and between-network rsFC strength of regions of interest of this study within the triple networks between participants in recovery and those who were actively drinking. The study found that participants in recovery showed a greater preference for delayed rewards (measured by DD task) compared to participants who are actively drinking. Additionally, measures of self-reported impulsivity and impulsive decision-making were associated with resting state functional connectivity (rsFC) strength between regions within the Salience Network (SN), and between the SN and Central Executive Network (CEN). Specifically, baseline delayed reward preference was positively associated with the rsFC between two SN hubs: left dorsal anterior insula (dAIC) and dorsal anterior cingulate cortex (dACC). The rsFC between the left dACC (SN) and dorsolateral prefrontal cortex (dlPFC; CEN) negatively associated with subscales (including negative urgency, lack of perseverance, and lack of premeditation) of self-reported impulsivity measured by the Urgency-Premeditation-Perseverance-Sensation Seeking-Positive Urgency (UPPS-P) impulsive behavior scale. Together, these results suggested that there was an emerging pattern where enhanced the rsFC strength in these regions associated with higher impulsive tendencies. The exploratory analysis showed that the rsFC strength between the right precuneus and ventromedial prefrontal cortex (vmPFC) was related to abstinence length in participants in recovery.

Conclusions

These findings indicated that participants in recovery exhibited higher delayed reward preference compared to participants who were actively drinking, alongside a significant relationship between measures of impulsivity and the rsFC within the SN and between the SN and CEN. These results highlighted the importance of the SN and its dynamic interaction with the CEN in self-reported impulsivity and impulsive decision making in addiction. Additionally, this study found that within-network functional connectivity strength in the DMN was related to abstinence length, suggesting that repairment in the rsFC strength within DMN might be integral to the process of addiction recovery.

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Health Seeking Behaviour and Healthcare Utilization in a Rural Cohort of North India

Rajaram yadav.

1 Indian Council of Medical Research—Regional Medical Research Centre Gorakhpur (ICMR-RMRC Gorakhpur), Gorakhpur 273013, India; [email protected] (R.Y.); moc.liamg@178aarhsim (A.M.); moc.liamg@cmbardneham (M.M.R.); [email protected] (P.Y.); moc.liamg@wsmuhbkihsuak (K.K.)

Kamran Zaman

Ayush mishra, mahendra m. reddy, prem shankar.

2 Department of Community Medicine, All India Institute of Medical Sciences (AIIMS Gorakhpur), Gorakhpur 273013, India; [email protected]

Priyanka Yadav

Kaushik kumar, associated data.

The datasets used and/or analysed during the present study are available from the corresponding author on reasonable request.

Background: The healthcare infrastructure of a country determines the health-seeking behaviour of the population. In developing countries such as India, there is a great disparity in the distribution of healthcare institutions across urban and rural areas with disadvantages for people living in rural areas. Objectives: Our objectives were to study the health-seeking behavior and factors associated with the use of formal healthcare among the Gorakhpur Health and Demographic Surveillance System (GHDSS) cohort of North India. Methods: The study was conducted in 28 villages from two rural blocks in the Gorakhpur district of eastern Uttar Pradesh, North India. Structured questionnaires were used to collect the data with regard to demographics, health-seeking behaviour and healthcare utilization. An adjusted odds ratio with 95% confidence interval was used to report the factors associated with the utilization of healthcare. Results: Out of 120,306 individuals surveyed, 19,240 (16%) individuals reported having any health problem in the last 15 days. Of them, 90% sought healthcare for their health needs. The formal healthcare utilization was 79%. The use of public health facilities was very low (37%) with most of the people seeking treatment from private healthcare (63%). Females, people with a higher level of education (graduate and above), and those belonging to rich and middle tercile were more likely to use formal healthcare services. Among different ailments, respiratory problems, gastrointestinal problems, and musculoskeletal problems were associated with decreased use of formal healthcare. Conclusion: About four in five individuals surveyed who had health problems sought treatments from formal healthcare with three in five preferring private institutions to public healthcare facilities due to a perceived higher level of treatment quality and nearby availability. There is an urgent need to re-establish community trust among public healthcare facilities with a focus on delivering on-site health care and enhancing the quality of services offered by public healthcare institutions.

1. Introduction

When a person becomes unwell, health-seeking behaviour entails going to a healthcare centre or using a home remedy [ 1 ]. The individual’s choice covers all existing healthcare options such as public or private, traditional or modern health care facilities, self-medication, or to not use any health services [ 2 ]. Many factors are associated with health-seeking behaviour, namely the type of sickness, degree of illness, gender, surrounding social environment, cost of care, social beliefs about the cause of illness, quality of care, education and economic background [ 3 , 4 ]. A systematic review that analysed health-seeking behaviour concluded that health-seeking behaviour is a multi-dimensional concept and depends on the context and time an individual is facing [ 5 ].

The healthcare infrastructure of a country determines the health-seeking behaviour of that country’s population [ 3 , 6 ]. People in most developed countries are covered by universal health coverage (UHC) which is funded by the government. However, in developing countries such as India, UHC is still a distant objective, with out-of-pocket spending accounting for the majority of healthcare costs. Despite significant government investment, convenient access to healthcare remains a major issue. The urban-rural differentials in terms of health infrastructure distribution are very much skewed in India with about 80% of health infrastructure catering to urban India. Rural India, wherein two-thirds of India’s population comes from, is left with very less availability of medical manpower forcing them to utilize the services of traditional healers or go for home remedies or self-medication at large [ 7 , 8 , 9 ].

Similar to health-seeking behaviour, healthcare utilization is influenced by a multitude of factors and is a dynamic concept that is again dependent on time. In general factors such as accessibility, comprehensiveness of care, and continuum of care decides the utilization of healthcare facilities [ 10 ]. The utilisation of healthcare facilities in India varies greatly between socioeconomic categories [ 11 ]. People in developing countries, such as India, prefer to use private healthcare facilities because they are easier to access and provide more personalised care, whereas public facilities are perceived to be of low quality, located in remote areas, and having long waiting times and insufficient facilities [ 12 , 13 ]. Due to financial constraints, some poor people chose self-treatment or no therapy [ 14 ].

While there have been studies looking into the health-seeking behaviour of communities in India and other countries, the majority of them have significant limitations. Most of the studies used a smaller sample size and targeted one or more specific strata of populations, such as the elderly, women, and so on [ 6 , 7 , 9 , 15 ]. As a result, there is a scarcity of a comprehensive study on this topic with an adequate sample size covering all strata of the population rather than looking at them in sections. Tejas Shah et al. studied the health-seeking behaviour of urban and rural communities in Gujarat’s Ahmedabad district and discovered that healthcare utilisation was significantly lower in the rural area than in the urban area. Although this study provided useful information, it only included 500 households [ 9 ]. Similarly, a cross-sectional study of rural women in Telangana discovered that formal healthcare utilisation was lower among rural women. However, the study was limited to three villages and with a sample size of 200 women, limiting the generalizability of the findings. Furthermore, the study only included women and provided no information or comparison of healthcare utilisation by other social groups [ 15 ].

Our study attempts to overcome these limitations by including a large sample size (~120,000) and including all sections of society. This will enable us to obtain a comprehensive view of the community’s health-care seeking behaviour. Furthermore, because we have already established the Health and Demographic Surveillance System (HDSS), the community’s health care seeking behaviour can be studied over time, unlike previous studies which were limited to a single point of time. Due to all of these factors, our study’s findings may be more relatable to existing times wherein government interventions are targeted to improve universal health coverage. The present study was carried out to investigate the factors associated with health-seeking behaviour and healthcare utilization in the cohort of the Gorakhpur Health and Demographic Surveillance System (GHDSS).

2. Material and Methods

This study was conducted in the rural cohort of the GHDSS site, which includes 28 villages from 2 blocks (Chargawa and Bhathat) in the Gorakhpur district, Uttar Pradesh. The site includes a total of 20,965 households with a population of about 120,306 people. The baseline data were collected from November 2019 to February 2021. The enumeration survey included all individuals in the study area except those who declined to participate or whose doors were locked. If a door was found to be locked during the initial visit, the household was revisited, and if two additional attempts failed, the house was reported as locked.

Before beginning the interview, informed verbal consent was obtained from the head of the family and, if he/she was unavailable, from the available elder member of the household. Preferably, the head of the household (HoH) was questioned, but if the HoH was not present, any member of the household over the age of 18 was interviewed for pretested open data kit (ODK) based questionnaires to collect data on the household’s health and demography. Field investigators were supervised and overseen by field supervisors and project scientists while they collected the data.

The wealth tercile was determined in STATA using principal component analysis based on the existence or absence of specific assets in the household. After dividing the population into five quintiles, the first and second quintiles were merged to form the poor tercile, the fourth and fifth wealth quintiles were merged to form the rich tercile, and the third quintile was designated as the middle tercile.

The utilization of the healthcare facilities was operationally categorized into either ‘formal’ or ‘informal’ healthcare. Formal healthcare included receiving treatment from both public and private health care providers and Informal healthcare included receiving treatment from traditional healers and by self-medication. Public health facilities included health care facilities of the government (state/central) which provided health care facilities free of cost or a nominal/subsidised rate and the private health facility included health care facilities other than those provided by the government and includes private hospitals and private clinics.

In this study, data from only those persons who had any health problem in the last 15 days preceding the survey were analysed, allowing healthcare used to be estimated among the population in need of care. First, the data were descriptively analysed based on selected household and individual variables. For regression analysis, using formal healthcare (yes/no) was taken as the dependent variable and all categorical variables including household size category, gender, relation to household head, education, marital status, occupation, religion, wealth tercile, age groups, caste and ailments (infection, cancer, blood disease, endocrine metabolic and nutrition, psychiatric and neurological, eye disease, ear disease, cardiovascular disease, respiratory infection, ad gastrointestinal disease, musculoskeletal, obstetric, and injuries) were used as independent variables. Binary logistic regression was carried out to determine the factors associated with the utilization of formal healthcare. All factors were included in the final multivariable logistic regression model and the association was reported using adjusted odds ratio (OR) along with a 95% confidence interval (CI). The model significance was reported using Nagelkerke’s pseudo R 2 and model p -value [ 16 ]. A p -value of less than 0.05 was considered to be a statistically significant association. All analyses were carried out using STATA-14 software (StataCorp LP, College Station, TX, USA).

Of the total 120,306 population surveyed, males accounted for 51.9% of the population in the study, and 7.9% of the population were 60 years or older. The literacy rate in the study area was 73.7%, with around 7.1% of the population having an education level of graduation and above. Approximately 38.1% of the population was in the rich tercile and 29.2% in the poor tercile. Table 1 presents the complete demographic details of the study population.

Socio-demographic profile of the population in the study area ( n = 120,306).

Background Characteristics	Percentage Distribution

Male	51.9
Female	48.0
Transgender	0.1

0–14	30.0
15–29	31.7
30–59	30.4
60+	7.9
	49.3

Illiterate	26.3
Literate without schooling	2.6
Below primary	11.6
Primary	13.4
Middle	17.1
Secondary	10.9
Higher secondary	10.8
Graduation and above	7.1

Never married	22.0
Currently married	71.1
Divorced/separated	0.3
Widowed	6.6

Self-employed in agriculture	0.8	14.5
Self-employed in non-agriculture	0.2	7.9
Regular wage/salary earning	0.6	5.5
Casual labor	1.0	49.9
Housewife	59.1	-
Student	34.4	15.8
Others	3.9	6.4

Hindu	94.7
Minority	5.3

Poor	29.2
Middle	32.7
Rich	38.1

A total of 19,240 (16%) people reported some form of illness/disease in the last 15 days prior to the survey. Of them, any healthcare facility was used by 89.7%, while 10.3% did not seek treatment at all. The use of public healthcare facilities was noted to be low (36.8%) when compared to private healthcare facilities (63.2%). Among them, 20.8% of individuals seeking informal healthcare, traditional healers were approached the maximum (99.3%) followed by self-medication in 0.7% of individuals ( Figure 1 ).

An external file that holds a picture, illustration, etc.
Object name is healthcare-10-00757-g001.jpg

Flow diagram depicting health-seeking behaviour and healthcare utilization among people of GHDSS cohort ( n = 120,306). * PHC, primary health centre; # CHC, community health centre.

The most often reported reasons for not seeking treatment by study participants were that of ailment being ‘not considered to be serious’ (48%) followed by ‘financial constraints’ (36%) ( Figure 2 ).

An external file that holds a picture, illustration, etc.
Object name is healthcare-10-00757-g002.jpg

Reasons for non-utilization of healthcare services among people who reported any ailment in the GHDSS cohort ( n = 1974).

Among the various diseases, obstetric problems had the lowest rate of medical treatment utilisation, with only 76% of the respondents receiving medical treatment, while cardiovascular diseases and endocrine and metabolic diseases had the highest rate, with 98% receiving medical treatment ( Table 2 ).

Health-seeking behaviour across various diseases and their sub-analysis in formal and informal healthcare.

Type of Disease ( )	Sought Healthcare (%)	Formal Healthcare (%)	Informal Healthcare (%)
Infection (1659)	1567 (94.4)	991 (63.2)	576 (36.8)
Cancers (313)	275 (87.9)	255 (92.7)	20 (7.3)
Blood disease (37)	33 (89.2)	32 (97.0)	1 (3.0)
Endocrine, metabolic and nutrition (1670)	1632 (97.7)	1547 (94.8)	85 (5.2)
Psychiatric and neurological (1821)	1602 (88)	1474 (92.0)	128 (8.0)
Eye (729)	596 (81.8)	538 (90.3)	58 (9.7)
Ear (638)	546 (85.6)	465 (85.2)	81 (14.8)
Cardio vascular diseases (1688)	1648 (97.6)	1499 (90.1)	149 (9.0)
Respiratory (2000)	1835 (91.7)	1325 (72.2)	510 (27.8)
Gastro intestinal (1319)	1205 (91.4)	902 (74.9)	303 (25.1)
Skin (969)	894 (92.3)	689 (77.1)	205 (22.9)
Musculoskeletal (3619)	3313 (91.5)	2321 (70.1)	992 (29.9)
Genitourinary (1563)	1399 (89.5)	1189 (85.0)	210 (15.0)
Obstetric (338)	258 (76.3)	251 (97.3)	7 (2.7)
Injuries (4283)	3710 (86.6)	2935 (79.1)	775 (20.9)

Among those who sought treatment, 21.4% (3711) reported changing in medical consultation after the first visit. Most of them (around 90%) reported no relief as a reason for doing so and 4.9% reported financial problems as the reason for changing medical consultation. No significant difference between private (48.4%) and public healthcare (51.6%) was observed in terms of change of the first consultation due to no relief.

Table 3 shows the variation in usage of formal healthcare and informal healthcare in relation to demographic characteristics. People living with a family size of six or more were 1.10 times higher odds of utilizing formal healthcare services for their treatment than those with a family size of five or less. In terms of gender, males had 1.21 times higher odds than females to use formal healthcare. When it comes to intra-household relationships; children (1.34 times), the spouse of children (1.47 times), and grandchildren (1.46 times) are more likely, while parents (0.80 times) are less likely to use formal healthcare compared to the head of the household.

Socio-demographic factors associated with usage of formal healthcare among people living in the GHDSS cohort ( n = 17,266).

Characteristics	= 17,266	Usage of Formal Healthcare, (%)	Unadjusted OR with 95% CI		Adjusted OR with 95% CI

1–5	7125	5500 (77)	1		1
6 and above	10,141	8175 (81)	1.23 ***	[1.14, 1.32]	1.10 *	[1.00, 1.21]

Female	9519	7378 (78)	1		1
Male	7733	6286 (81)	0.79 ***	[0.74, 0.86]	1.21 *	[1.05, 1.41]
Transgender	14	11 (79)	0.84	[0.23, 3.03]	0.94	[0.25, 3.56]

Self	5106	4091 (80)	1		1
Spouse	4930	3837 (78)	0.87 **	[0.79, 0.96]	1.00	[0.84, 1.0]
Child (Son/daughter)	4107	3271 (80)	0.97	[0.88, 1.08]	1.34 **	[1.08, 1.66]
Spouse of child	916	780 (85)	1.42 ***	[1.17, 1.73]	1.47 **	[1.13, 1.91]
Grand child	835	636 (76)	0.79 **	[0.67, 0.94]	1.46 *	[1.04, 2.03]
Father/Mother	1054	790 (75)	0.74 ***	[0.64, 0.87]	0.80 *	[0.66, 0.96]
Brother/Sister	191	153 (80)	1.00	[0.70, 1.43]	0.77	[0.51, 1.16]
Other relative	122	113 (93)	3.12 **	[1.57, 6.16]	3.98 ***	[1.88, 8.45]
Not relative	5	4 (80)	0.99	[0.11, 8.89]	1.70	[0.16, 18.31]

Illiterate	7451	5682 (76)	1		1
Up to higher secondary	8300	6763 (81)	1.37 ***	[1.27, 1.48]	1.19 **	[1.07, 1.32]
Graduation and above	830	759 (91)	3.33 ***	[2.59, 4.27]	1.79 ***	[1.35, 2.36]

Never married	3538	2806 (79)	1		1
Currently married	11,056	8883 (80)	1.07	[0.97, 1.17]	0.81	[0.63, 1.04]
Divorced/separated	61	54 (88)	2.01	[0.91, 4.44]	1.19	[0.51, 2.77]
Widowed	1926	1456 (76)	0.82 **	[0.72, 0.94]	0.76 *	[0.57, 1.01]

Self-employed in agriculture	1699	1383 (81)	1		1
Self-employed in non-agriculture	573	483 (84)	1.23	[0.95, 1.58]	0.87	[0.66, 1.14]
Regular wage/salary	459	431 (94)	3.52 ***	[2.35, 5.25]	2.08 ***	[1.37, 3.16]
Casual labour	2791	2196 (79)	0.84 *	[0.72, 0.98]	0.93	[0.79, 1.10]
Housewife	7158	5594 (78)	0.82 **	[0.71, 0.93]	1.04	[0.84, 1.29]
Student	2369	1821 (77)	0.76 ***	[0.65, 0.89]	0.82	[0.63, 1.07]
Others	1532	1296 (85)	1.25 *	[1.04, 1.51]	1.35 **	[1.09, 1.68]

Hindu	16,189	12,800 (79)	1		1
Muslim	1033	839 (81)	1.15	[0.98, 1.34]	1.05	[0.88, 1.27]
Others	3	3 (100)	1.00	[1.00, 1.00]	1.00	[1.00, 1.00]

Poor	5321	3744 (70)	1		1
Middle	5545	4383 (79)	1.59 ***	[1.46, 1.73]	1.51 ***	[1.37, 1.66]
Rich	6359	5515 (87)	2.75 ***	[2.51, 3.02]	2.19 ***	[1.96, 2.44]

0–14	2173	1575 (72)	1		1
15–29	3291	2669 (81)	1.63 ***	[1.43, 1.85]	1.35 **	[1.11, 1.64]
30–59	7867	6356 (81)	1.60 ***	[1.43, 1.78]	1.90 ***	[1.48, 2.44]
60+	3935	3075 (78)	1.36 ***	[1.20, 1.53]	1.81 ***	[1.38, 2.37]

Scheduled Caste/Scheduled Tribe	5080	3869 (76)	1		1
Other Backward Class	11,232	8975 (80)	1.24 ***	[1.15, 1.35]	1.07	[0.98, 1.17]
Others	913	798 (87)	2.17 ***	[1.77, 2.67]	1.20	[0.95, 1.51]


No	15,704	12,700 (81)	1		1
Yes	1562	975 (62)	0.39 ***	[0.35, 0.43]	0.46 ***	[0.39, 0.53]

No	16,991	13,420 (79)	1		1
Yes	275	255 (93)	3.39 ***	[2.15, 5.36]	3.18 ***	[1.98, 5.09]

No	17,233	13,643 (79)	1		1
Yes	33	32 (97)	8.42 *	[1.15, 61.64]	8.46 *	[1.14, 62.99]

No	15,640	12,134 (78)	1		1
Yes	1626	1541 (95)	5.24 ***	[4.20, 6.54]	3.53 ***	[2.78, 4.49]

No	15,670	12,206 (78)	1		1
Yes	1596	1469 (92)	3.28 ***	[2.73, 3.95]	2.76 ***	[2.23, 3.41]

No	16,671	13,138 (79)	1		1
Yes	595	537 (90)	2.49 ***	[1.89, 3.27]	2.61 ***	[1.96, 3.48]

No	16,724	13,214 (79)	1		1
Yes	542	461 (85)	1.51 ***	[1.19, 1.92]	1.68 ***	[1.28, 2.20]

No	15,623	12,183 (79)	1		1
Yes	1643	1492 (91)	2.79 ***	[2.35, 3.31]	2.07 ***	[1.71, 2.50]

No	15,444	12,364 (80)	1		1
Yes	1822	1311 (72)	0.64 ***	[0.57, 0.71]	0.74 ***	[0.63, 0.86]

No	16,064	12,776 (80)	1		1
Yes	1202	899 (75)	0.76 ***	[0.67, 0.87]	0.72 ***	[0.61, 0.85]

No	16,379	12,995 (79)	1		1
Yes	887	680 (77)	0.85	[0.73, 1.00]	0.88	[0.72, 1.07]

No	13,981	11,388 (81)	1		1
Yes	3285	2287 (70)	0.52 ***	[0.47, 0.57]	0.57 ***	[0.50, 0.66]

No	15,878	12,498 (79)	1		1
Yes	1388	1177 (85)	1.51 ***	[1.30, 1.76]	1.37 ***	[1.14, 1.64]

No	17,009	13,425 (79)	1		1
Yes	257	250 (97)	9.53 ***	[4.50, 20.22]	7.96 ***	[3.70, 17.12]

No	13,569	10,757 (79)	1		1
Yes	3697	2918 (79)	1.49 ***	[1.45, 1.53]	1.02	[0.89, 1.17]

* p < 0.05, ** p < 0.01, *** p < 0.001, @ Unadjusted Odds Ratio, # Adjusted Odds Ratio and model significance: pseudo R 2 = 0.0984, p value < 0.001 ( n = 16,541).

People having education level up to higher secondary (1.19 times) and people having education level of graduation and above (1.76 times) are more likely to use formal healthcare as compared to those who are illiterate. People with regular wage/salary are around 2.3 times ( p < 0.001) more likely to use formal healthcare as compared to people self-employed in agriculture. When compared to the poor, the middle group is 1.51 times ( p < 0.001) and the rich are 2.19 times ( p < 0.001) more likely to use formal healthcare. People in the age groups 15–29, 30–59, and 60 years and above have a, respectively, 1.35 times, 1.90 times, and 1.81 times higher odds of using formal healthcare as compared to people in the age group 0–14 years.

With respect to ailments, after adjusting to all variables except for injuries and skin ailments all other ailments had significant association with usage of formal healthcare. Among infections, respiratory problems, gastrointestinal problems, and musculoskeletal problems were associated with decreased use of formal healthcare (see Table 3 ).

4. Discussion

The under-utilization of a public healthcare facility is common in all developing countries whereas the use of private healthcare is growing in developing and under-developed countries [ 2 ]. It is found in our study that most of the population prefers to use private healthcare facilities viz. private hospitals, private doctors, or private clinics. A similar finding was observed in a previous study which was carried out in Bangladesh [ 17 ]. Private facilities are preferred since they are available nearby and are believed to have a better quality of care [ 2 ]. People have a prevalent belief that private healthcare institutions give superior care to public healthcare facilities [ 18 ].

We found in our study that there is a significant gender difference in the utilization of formal healthcare, wherein it was found that utilization of formal healthcare services was higher among males as compared to females, which is contradictory to the finding of another study previously carried out in India [ 11 ]. The differences could be due to the higher prevalence of the patriarchal system in this part of the country compared to the study from northeast India. We did not find any significant association between religion and the utilization of formal healthcare in this study. This may be due to the low distribution of other religions apart from Hindus in our study population.

It was also observed in our study that people having higher education (higher secondary and graduate and above) are more likely to use formal healthcare since they are more aware of their health. In the case of the relationship between marital status and formal healthcare utilization, it is found in this study that widows are significantly less likely to use formal healthcare for their treatment as compared to those who never married. This is also supported by other previous studies [ 19 , 20 ].

We also found that people who belong to rich or middle-class families are significantly more likely to seek treatment from formal healthcare as compared to the poor, which is also evident from the study carried out in Bangladesh [ 17 ]. The reasons for non-utilization could be due to their disadvantaged status in the community making them have poor awareness, access, and beliefs in the healthcare system.

People with higher age categories (above 14 years) used the formal healthcare system more compared to those in the 0–14 years category. This may be due to the fact that the decision-making process in this age group is in the hands of caregivers who may be influenced by social beliefs.

We found in our study that people seek the help of traditional healers or informal healthcare for diseases such as musculoskeletal diseases, fever of unknown origin (18%), and upper respiratory tract diseases. The major cause of this trend is that people do not consider these diseases as serious. In addition, traditional therapy is considered to be harmless. Similar findings were seen in previously conducted studies in Sierra Leone and Indonesia [ 21 , 22 ]. In our study, we have not captured the severity of disease, which may be one of the important factors to decide in seeking for healthcare.

Further, we found that household size was independently associated with the usage of formal healthcare. Larger household sizes (six and above) compared to lesser household sizes (five and below) have higher odds of using formal healthcare. The reason for this needs to be further explored. In our study, we also found that the relationship with the head of the household also determines the usage of formal healthcare. Children of the head, spouse of the children, and grandchildren use formal healthcare more compared to the head of the household. Also, compared to the head of the household, parents of the head are using formal healthcare significantly lesser. This may be due to the beliefs and also the perceived status of the head of the household, who generally decides the usage of healthcare (especially in rural areas). This could also be attributed by the changing healthcare seeking behaviour across generations with younger generation making informed decisions based on better awareness compared to elderly.

The study findings may be generalizable to similar settings across India and also other lower-middle-income countries. The study has few implications. The study calls for more focus on health infrastructure in rural India and also increased awareness to improve health-seeking behaviours and healthcare utilization across rural India. The study also calls for health insurance coverage for people living in rural India which may bring about a change in health-seeking behaviours and health care utilization by reducing out-of-pocket health expenditures. Furthermore, ailments such as respiratory diseases are having lesser usage of formal healthcare which could have huge consequences in terms of morbidity and mortality especially in paediatric age groups. This calls for increased awareness in rural areas through existing maternal and child health programmes in seeking for formal healthcare in case of ailments such as respiratory infections which may have a huge bearing on outcome if there is a delay in seeking formal healthcare systems. Also, with respect to neglect of seeking healthcare among adults, respiratory infections may derail in achieving the goal of ending tuberculosis (TB) by 2025 in India. There is also a need to increase the formal healthcare system (especially the public health care system) so that it is more accessible and also reduce the health expenditures in rural India. With the advent of Ayushman Bharat and Health and wellness centres in India, the solution for removing the skewness in health coverage across rural and urban India may well be on cards [ 23 ]. Health-seeking behaviour and healthcare utilization must be one of the prominent indicators, especially in rural India to assess the implementation of such schemes in future.

5. Strengths and Limitations of the Study

The study’s strength is that it is based on complete enumeration. Therefore, there is no sampling bias in the study. The study is a part of large cohort with ~120,000 population which makes the findings to be more generalizable. By limiting the morbidity reference period to 15 days before the survey, the utmost effort was taken to reduce recall bias. We have adjusted the analysis so that the independent factors associated with formal healthcare use are determined more accurately. One significant drawback of the study is that morbidity and health-seeking behaviour are quantified based on reported sickness and treatment received rather than being observed or diagnosed. As a result, there is a chance of under-reporting of diseases for which formal care was not sought. Further, as mentioned earlier we have not captured the severity of disease which could be an important factor in seeking for healthcare. Also, the availability of formal healthcare is another factor in deciding the usage of formal healthcare. A variable such as the nearest distance from a particular household to the formal healthcare facility (private/public) would have bought more insights in health-seeking behaviours.

6. Conclusions

This study provides rich information about the local community’s health-seeking behaviour. Although 80% seek formal healthcare for their ailments, three in five persons who sought care preferred private institutions to public healthcare facilities due to a perceived higher level of treatment quality and nearby availability. In our study we found that formal healthcare utilization was significantly higher among males, people having better socioeconomic status and higher age groups (14 years and above). Among different ailments infections, respiratory problems, gastrointestinal problems and musculoskeletal problems were associated with decreased use of formal healthcare. These findings give critical feedback for the development and implementation of healthcare policies. Public healthcare facilities should be extended to underserved areas, with a focus on delivering on-site health care through wellness centres with the assistance of an accredited social health activist (ASHA) and auxiliary nurse midwife (ANM). In order to re-establish community trust in public healthcare facilities, and emphasis should be placed on enhancing the quality of services offered by public healthcare institutions.

Acknowledgments

The authors thank Dr Manoj Murhekar, Dr Nivedita Gupta and Dr Avinash Deoshatwar for their support in the Gorakhpur HDSS establishment. The authors thank Gorakhpur local district administration (Gram Pradhans, Block development Officer) and local health department authorities for their support and help in the study. The authors thank all of the participants and their families involved in the study. The authors also acknowledge the field staff of the Gorakhpur HDSS team (Dinesh Chauhan, Amrendra Kumar, Vipul Kumar, Zeeshan Akhtar, Dhananjay Kumar, Ranjeet Singh, Sunil Kumar Yadav, Mamta Patel, Kuldeep Tripathi, Sanjay Chaurashiya, Rameez Ahmad Khan, Gyanendra Kumar Yadav, Ashutosh Pandey, Ravi Kumar Singh, Ishwar Chand Yadav, Vachaspati Mishra, Hemant Kumar Yadav, Shivbrat Yadav, Neha Yadav, Peeysuh Srivastava, Sunil Kumar Yadav, Sanjay Prajapati, Ashok Samrat, Vikash Kumar, Vinay Kumar Yadav, Shashi Gupta, Pradeep Kumar Yadav, Laxman Kumar, Vinay Singh, Shashi Chand, Ravindra Paswan, Tejaswi Prajapati, Amrit Kumar, Rajan Kumar) for their assistance and support in data collection.

Author Contributions

Conceptualization, R.Y., K.Z., P.S., P.Y., K.K. and R.K.; data curation, R.Y., K.Z., A.M., M.M.R., P.S., P.Y. and K.K.; formal analysis, R.Y., K.Z., A.M., M.M.R. and P.S.; funding acquisition, K.Z. and R.K.; methodology, R.Y., K.Z., M.M.R., P.S., P.Y. and K.K.; project administration, K.Z. and R.K.; supervision, K.Z.; validation, R.Y. and K.Z.; writing—original draft, R.Y., K.Z., A.M., M.M.R., P.Y. and K.K.; writing—review and editing, A.M., M.M.R., P.S. and R.K. All authors have read and agreed to the published version of the manuscript.

Financial support was provided by an intramural grant from the ICMR—Regional Medical Research Centre, Gorakhpur (RMRCGKP/SAC2020-21/P5).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by ICMR-RMRC Gorakhpur Institutional Ethics Committee for Human studies (IEC/June/2019/D-7 dated 24 June 2019).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Health knowledge and care seeking behaviour in resource-limited settings amidst the COVID-19 pandemic: A qualitative study in Ghana

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Impact of COVID-19 pandemic on health knowledge

Impact of COVID-19 pandemic on health-related lifestyles

Impact of COVID-19 pandemic on healthcare seeking behaviour

Strengths and limitations

Article Contents

Health-seeking behaviour during times of illness: a study among adults in a resource poor setting in Ghana

Data analysis

Multivariate

Main finding of this study

What is already known on this topic?

What this study adds

Limitations of this study

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Health-seeking behaviour during times of illness among urban poor women: a cross-sectional study

Study design and area

Study population and sample size determination

Sampling techniques

Measurements

Operational definition

Data management and analysis

Characteristics of the participants

Health-seeking behaviour during times of illness

Predictors of sought care during times of illness

Strengths and limitations of the study

Recommendations

Conclusions

Data availability

Abbreviations

Acknowledgements

Author information

Contributions

Corresponding author

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Consent for publication

Competing interests

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Factors related to help-seeking for cancer medical care among people living in rural areas: a scoping review

Study design

Protocol and registration

Eligibility criteria

Information sources and search

Selection of sources of evidence

Data charting process

Synthesis of results

Intrapersonal

Interpersonal

Groups, culture, and organizations

Policy/environment

Principal findings and directions for future implication in rural areas

Implications for practice

Limitations of the study

Conclusions

Availability of data and materials

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Consent for publication

Additional information