Why Healthcare Workers Delay Care: A Comparison of Clinical and Non-clinical Staff in Ondo State, Nigeria

Why Healthcare Workers Delay Care: A Comparison of Clinical and Non-clinical Staff in Ondo State, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Why Healthcare Workers Delay Care: A Comparison of Clinical and Non-clinical Staff in Ondo State, Nigeria Isaac Ihinmikaye¹, Ayodeji M. Adebayo², Adedeji A. Onayade³, Olufemi O. Ayodeji¹, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8017279/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 18 You are reading this latest preprint version Abstract Background Healthcare workers (HCWs) are essential to health system functioning, yet they often neglect their own health due to workload, long shifts, staff shortages, and occupational risks. These factors may lead to delayed care, self-medication, and missed diagnoses, sometimes resulting in preventable morbidity and sudden deaths. This study assessed differences in health-seeking behaviour and healthcare service utilisation between clinical and non-clinical HCWs in tertiary hospitals in Ondo State, Nigeria, and examined the determinants of their care-seeking patterns. Methods A comparative, facility-based cross-sectional study was conducted among 230 clinical and 230 non-clinical HCWs selected using a two-stage sampling technique. Quantitative data were collected using pretested, semi-structured questionnaires and analysed with descriptive statistics, chi-square tests, and binary logistic regression at a 5% significance level. Qualitative data from Key Informant Interviews were analysed thematically using NVivo 14. Results Clinical HCWs were significantly younger than non-clinical HCWs (56.5% vs. 36.5% <40 years; p < 0.001). Poor health behaviour was more common among clinical than non-clinical HCWs (82.6% vs. 68.7%; p = 0.001). Inappropriate health-seeking behaviour was also higher among clinical HCWs (87.4% vs. 80.0%; p = 0.032). Overall healthcare utilisation was low in both groups (82.2% vs. 83.9% poor utilisation; p = 0.619). Predictors of good utilisation among clinical HCWs included regular medication use (AOR = 5.52), appropriate health-seeking behaviour (AOR = 4.87), and health insurance (AOR = 2.63). Among non-clinical HCWs, prior consultation with a doctor and appropriate health-seeking behaviour were significant predictors. Conclusion Both clinical and non-clinical HCWs exhibited poor health-seeking behaviour and low utilisation of healthcare services, despite good self-perceived health status. Addressing behavioural, organisational, and structural barriers is essential to enhance timely care-seeking among HCWs. Targeted institutional and policy interventions that promote preventive care, routine screening, and supportive work environments are recommended. Health-seeking behaviour Healthcare utilisation Delay in care Clinical staff Non-clinical staff Nigeria Figures Figure 1 Figure 2 INTRODUCTION Health-seeking behaviour refers to actions individuals take to maintain health, prevent disease and seek appropriate care when illness occurs.¹ These actions include preventive practices such as screening, prompt care-seeking for symptoms and strategies to reduce complications of established disease. Multiple personal and social factors influence whether individuals seek care appropriately, including beliefs, household decision-making, social networks, and access to financial and physical resources.² Delayed care has been associated with increased morbidity, unfavourable clinical outcomes and avoidable deaths.³ Health-seeking behaviour therefore affects not only individual well-being but also population-level health outcomes through utilisation patterns.⁴ Healthcare workers (HCWs), both clinical and non-clinical, form the backbone of the health system and are expected to model appropriate health practices.⁵ Clinical HCWs deliver direct patient care, including doctors, nurses, pharmacists, laboratory professionals and therapists. Non-clinical HCWs support care delivery through administrative, financial, technical, and operational roles.⁶ Although their contributions differ, both groups are exposed to occupational risks, heavy workload and stress that can impair personal health.⁷ Ironically, access to medical knowledge does not always translate to healthy behaviour. Evidence shows that HCWs often delay seeking care, rely heavily on self-medication, engage in informal consultations and avoid assuming the “patient role” due to stigma, confidentiality fears and workload pressure.⁸ This behaviour may result in under-diagnosed chronic conditions, late presentation and preventable mortality.⁹ Sudden deaths among HCWs attributed to undetected illness have raised concern in Nigeria.¹⁰ There is also significant health system strain due to workforce shortages and migration, creating additional barriers to timely care-seeking for the remaining staff.¹¹ Studies investigating HCW health-seeking behaviour in Nigeria have focused predominantly on clinical staff, with limited attention to non-clinical workers who may have less health literacy and less autonomy in navigating hospital systems.¹² Understanding differences in health-seeking patterns between clinical and non-clinical HCWs is essential for developing interventions that promote early care, preventive health behaviours and ultimately sustain a productive workforce. This study compares the two groups in tertiary hospitals in Ondo State and identifies factors influencing their healthcare utilisation. Theoretical frameworks surrounding the delay in seeking healthcare: Health Belief Model: In this study, as shown in figure 1 below, the HBM provides a theoretical basis for understanding the health-seeking behaviour of healthcare workers. It suggests that clinical and non-clinical staff are more likely to seek timely care when they perceive themselves at risk , recognise the severity of illness, believe in the benefits of early treatment, and have confidence in their ability to access care despite perceived barriers. It proposes that health behaviour is influenced by perceived susceptibility, perceived severity, perceived benefits of action, perceived barriers, cues to action and self-efficacy.¹³ The model explains why individuals engage in preventive or care-seeking behaviours when faced with health threats as shown in figure 1 below 13 It also illustrates how individuals make decisions about their health by weighing perceived risks and benefits. It proposes that health-related behaviour is primarily influenced by six key constructs: Perceived Susceptibility – an individual’s belief about the likelihood of developing a health condition. Perceived Severity – how serious a person believes the consequences of the condition would be if it occurred. Perceived Benefits – the individual’s assessment of the positive outcomes expected from taking a specific health action. Perceived Barriers – the potential obstacles (e.g., time, cost, stigma, fear) that may prevent an individual from engaging in a health-promoting behaviour. Cues to Action – internal or external triggers (such as symptoms, media messages, or advice from colleagues) that prompt behaviour change. Self-Efficacy – confidence in one’s ability to successfully perform the desired action. Together, these components explain why individuals may or may not engage in preventive health practices or seek care promptly. Furthermore, this Model as shown in Figure 1 above, suggests that people’s beliefs about health problems in terms of their perceived susceptibility, perceived severity, perceived benefits of action, and perceived barriers to action and self-efficacy explain engagement (or lack of engagement) in health-promoting behaviour A conceptual framework is a visual representation that illustrates the pathways through which programmes achieve their objectives, and it constitutes a logical framework for developing an evaluation plan with appropriate indicators. 14 This conceptual framework, as shown in Figure 2 above, illustrates how various factors interact to influence the health-seeking behaviour and healthcare utilisation patterns of clinical and non-clinical healthcare workers. It integrates elements of the Health Belief Model and Andersen’s Behavioural Model of Health Service Use , showing that health behaviour is not determined by a single factor but by a dynamic interplay of personal, behavioural, and systemic variables. The framework identifies independent variables such as socio-demographic characteristics (age, sex, marital status, income, and education), occupational factors (cadre, workload, work schedule), and behavioural influences (knowledge, attitudes, and perceived barriers). These factors shape an individual’s perceptions of susceptibility, severity, and benefits , which in turn determine their health-seeking behaviour —whether timely, delayed, or inappropriate. Health-seeking behaviour acts as an intermediate or mediating variable , linking background factors to actual utilisation of healthcare services —the key dependent variable in this study. Utilisation is reflected in the frequency, type, and quality of services accessed (routine check-ups, screening, treatment, and preventive care) 15 The model also recognises enabling and reinforcing factors such as health insurance coverage, accessibility of facilities, confidentiality, and social support systems, which either facilitate or hinder service utilisation. Ultimately, the interaction of these variables determines whether healthcare workers engage in proactive health practices or delay care 15 In summary, the framework visually demonstrates that improving health-seeking behaviour among healthcare workers requires addressing not only individual attitudes but also structural and institutional determinants—ensuring that behavioural change is supported by an enabling work environment and accessible healthcare systems. STUDY AREA This study was conducted at two Federal tertiary hospitals in Ondo State, Southwest Nigeria: Federal Medical Centre (FMC), Owo and University of Medical Sciences Teaching Hospital Complex (UNIMEDTHC), Akure. Ondo State has a population of approximately 3.4 million people and 18 Local Government Areas. Healthcare services include primary, secondary and tertiary facilities, with these two tertiary hospitals serving as major referral centres offering specialist care, emergency services, surgical and diagnostic capabilities. FMC Owo was established in 1993, while UNIMEDTHC Akure evolved from the former State General Hospital but now functions as the teaching hospital of the University of Medical Sciences. Both institutions employ clinical and non-clinical healthcare workers essential to service delivery 16 STUDY DESIGN A hospital-based, comparative cross-sectional study was conducted among healthcare workers in the two tertiary hospitals to assess their health-seeking behaviour and healthcare utilisation, comparing clinical and non-clinical staff. STUDY POPULATION The target population included adult healthcare workers employed at the selected hospitals. Clinical staff comprised doctors, nurses, pharmacists, laboratory scientists, radiographers, and other allied health professionals. Non-clinical staff included administrative officers, accountants, secretaries, drivers, cleaners, technicians and other personnel not directly involved in patient care. INCLUSION AND EXCLUSION CRITERIA Inclusion • Full-time employees in either clinical or non-clinical roles • Minimum of six months working experience at the facility • Consent to participate Exclusion • Trainee interns and corps members • Staff on leave or unavailable during data collection • HCWs with severe medical or psychiatric conditions impairing participation SAMPLE SIZE DETERMINATION The sample size was calculated using the formula for comparing two proportions. Based on estimated prevalence from prior studies and adjusting for non-response, 460 respondents were targeted: 230 clinical and 230 non-clinical HCWs. SAMPLING TECHNIQUE A two-stage sampling procedure was used: Facility selection : FMC Owo and UNIMEDTH Akure were purposively selected as the major federal tertiary facilities in the state. Proportionate stratified sampling was used to select 230 clinical and 230 non-clinical staff across departments using staff registers as sampling frames, followed by simple random sampling to identify participants. DATA COLLECTION METHODS A pretested, semi-structured, interviewer-administered questionnaire was used to obtain quantitative data on: • Sociodemographic characteristics • Health behaviours • Health-seeking patterns • Utilisation of formal healthcare services • History of screening and preventive care • Access to health insurance and medication adherence The questionnaire used in this study was developed solely for this study. This is as shown in Appendix 1. Qualitative data were collected using Key Informant Interviews (KIIs) with purposively selected leaders and senior professionals to gain deeper insight into determinants of delayed care-seeking. Interview guides ensured consistency, and interviews were recorded with permission. DATA QUALITY ASSURANCE • The questionnaire was adapted from validated instruments and contextualised • Pretesting was conducted among HCWs in a separate hospital in Ondo State • Research assistants were trained in confidentiality and interviewing techniques • Daily checks of completed questionnaires ensured completeness and accuracy DATA ANALYSIS Quantitative data were analysed using IBM SPSS version 25. Descriptive statistics summarised variables using frequencies, percentages, means and standard deviations. Chi-square tests assessed associations between categorical variable. Variables significant at p<0.05 were entered into binary logistic regression to determine predictors of health service utilisation. Adjusted odds ratios (AOR) and 95% confidence intervals were reported Qualitative data were transcribed verbatim and analysed using thematic analysis . NVivo 14 aided coding, theme development and triangulation with quantitative findings. RESULTS A total of 460 healthcare workers participated, comprising 230 clinical and 230 non-clinical staff. Clinical staff were generally younger than non-clinical workers. Most participants were married and held tertiary-level education. Mean work experience was higher among non-clinical HCWs. Table 1 shows the socio-demographic profile of healthcare workers Variables Clinicals N = 230 n (%) Non-clinicals N = 230 n (%) Test statistics P-Value Age (years) < 40 (Young adults) 130 (56.5) 84 (36.5) χ² = 18.489 < 0.001 ≥ 40 (Middle aged) 100 (43.5) 146 (63.5) Age (Mean ± SD) 38.60 ± 8.416 40.96 ± 7.324 t-test= -3.203 0.001 Sex Male 82 (35.7) 105 (45.7) χ²=4.767 0.029 Female 148 (64.3) 125 (54.3) Marital status Single 52 (22.6) 19 (8.3) χ²=18.138 < 0.001 Married 172 (74.8) 204 (88.7) Divorced/separated/widowed 6 (2.6) 7 (3.0) Religion Christianity 217 (94.3) 208 (90.4) χ² = 2.505 0.113 Islam 13 (5.7) 22 (9.6) Ethnicity Yoruba 176 (76.5) 205 (89.1) χ² = 14.021 0.001 Igbo 27 (11.7) 9 (3.9) Others* 27 (11.7) 16 (7.0) Level of education Primary 0 (0.0) 9 (3.9) LR = 42.613 3 180 (78.3) 178 (77.4) Length of practice (Mean ± SD) 10.13 ± 7.285 8.30 ± 6.175 t-test = 2.907 0.004 Monthly income (naira) ≤ 30000 0 (0.0) 6 (2.6) Fisher’s exact= 0.030 > 30000 230 (100.0) 224 (97.4) *Others in ethnicity include Ebira, Edo, Idoma and Igala ethnic groups ** χ² - Chi-square ***LR- Likelihood ratio ****Bolded p-value is statistically significant The sociodemographic profiles of the participants as presented in Table 1 revealed a significant proportion (56.5%) of the clinical healthcare workers being < 40 years compared to 36.5% of the non-clinical healthcare workers (p < 0.001). More (64.3%) of the clinical healthcare workers were females than 54.3% of non-clinical healthcare workers (p = 0.029). Majority (89.1%) of non-clinical healthcare workers belonged to Yoruba tribe compared to 76.5% of the clinical healthcare workers (p = 0.001). All the clinical healthcare workers had more than thirty thousand naira as their monthly income as against 97.4% among the non-clinical healthcare workers (p = 0.030). Table 2 depict the h ealth behaviour of clinical and non-clinical healthcare workers Variables Clinicals N = 230 n (%) Non-clinicals N = 230 n (%) Test statistics P-Value Health behaviour Good health behaviour 40 (17.4) 72 (31.3) χ²= 12.085 0.001 Poor health behaviour 190 (82.6) 158 (68.7) Alcohol intake Yes 30 (13.0) 25 (10.9) χ²= 0.516 0.472 No 200 (87.0) 205 (89.1) Regularity of alcohol intake (N = 55) Everyday 0 (0.0) 5 (20.0) Fisher’s exact= 0.024 Alternate days 11 (36.7) 10 (40.0) Occasionally 19 (63.3) 10 (40.0) Cigarette smoking Yes 6 (2.6) 3 (1.3) Fisher’s exact= 0.503 No 224 (97.4) 227 (98.7) The health behaviours of the healthcare workers as summarized in Table 2 above reported a significant proportion (82.6%) of the clinical healthcare workers having poor health behaviour as against 68.7% among the non-clinical healthcare workers (p = 0.001). About two-third (63.3%) of the clinical healthcare workers drink alcohol occasionally compared to two-fifth (40.0%) among the non-clinical healthcare workers (p = 0.024). Table 3 shows the h ealth seeking behaviour among clinical and non-clinical healthcare workers Variables Clinicals n (%) Non-clinicals n (%) Chi-square P-Value Health seeking behaviour (N = 460) Appropriate 29 (12.6) 46 (20.0) 4.604 0.032 Inappropriate 201 (87.4) 184 (80.0) Sought healthcare services at last time of illness (N = 460) Yes 123 (53.5) 134 (58.3) 1.067 0.302 No 107 (46.5) 96 (41.7) Type of health facility preferred to visit when ill (N = 460) Private 54 (23.5) 21 (9.1) 17.349 < 0.001 Public 176 (76.5) 209 (90.9) Action taken during last illness (N = 257) Visited TBA/faith-based organisation 1 (0.8) 1 (0.7) 0.074 0.964 Consulted pharmacist/patent medicine vendor 9 (7.3) 11 (8.2) Visited a health facility 113 (91.9) 122 (91.0) Actions taken during last illness while not seeking healthcare (N = 203) Nothing 11 (10.3) 8 (8.3) 3.405 0.182 Took over-the-counter self-medications 73 (68.2) 76 (79.2) Others* 23 (21.5) 12 (12.5) Motivation for visiting health facility at last time of illness (N = 235) Fear of the unknown 55 (48.7) 64 (52.5) 9.049 0.011 The severity of illness 42 (37.2) 54 (44.3) Type of health facility visited at last time of illness (N = 235) Private 15 (13.3) 9 (7.4) 2.225 0.136 Public 98 (86.7) 113 (92.6) *Others- self relaxation, counsel from colleagues, herbal concoction The health seeking behaviour of participants as summarized in Table 3 above found that a significant proportion (87.4%) of the clinical healthcare workers had inappropriate health seeking behaviour compared to 80.0% among the non-clinical healthcare workers (p = 0.032). More (90.9%) of non-clinical healthcare workers preferred to visit public health facility than 76.5% of the clinical healthcare workers (0.001). More non-clinical healthcare workers (52.5%) were motivated to visit the health facility as a result of fear of the unknown compared to 48.7% of the clinical healthcare workers (p = 0.011). Table 4 shows the U tilisation of health services among healthcare workers Variables Clinicals n (%) Non-clinicals n (%) Test statistics P-Value Utilisation of health services (N = 460) Good utilisation 41 (17.8) 37 (16.1) χ²= 0.247 0.619 Poor utilisation 189 (82.2) 193 (83.9) Ever accessed health services (N = 460) Yes 112 (48.7) 108 (47.0) χ²= 0.139 0.709 No 118 (51.3) 122 (53.0) Mode of accessing health services (N = 220) Clinic appointment 88 (78.6) 100 (92.6) χ²= 11.872 0.003 Over the phone 8 (7.1) 6 (5.6) Home visit 16 (14.3) 2 (1.9) Complied with doctor’s prescription (N = 202) Yes 98 (100.0) 102 (98.1) Fisher’s exact 0.498 No 0 (0.0) 2 (1.9) Frequency of accessing check-up (N = 124) Monthly 12 (19.4) 23 (37.1) LR = 17.326 0.002 Quarterly 13 (21.0) 24 (38.7) Bi-annually 9 (14.5) 4 (6.5) Yearly 24 (38.7) 8 (12.9) Cannot recall the last time 4 (6.5) 3 (4.8) Based on the comparison of the level of utilization of health services among healthcare workers in Table 4 above; clinic appointment was the mode of consultation among majority (92.6%) of the non-clinical healthcare workers compared to 78.6% of clinical healthcare workers (p = 0.003). A significant proportion (38.7%) of the clinical healthcare workers had routine medical check-up yearly compared to 12.9% of non-clinical healthcare workers (p = 0.002). There was no statistically significant association in the utilisation of health services between clinical and non-clinical healthcare workers, however, more clinical staff (17.8%) had good utilisation of health services than 16.1% of non-clinical staff (p = 0.619) Table 5 Association between sociodemographic profile and utilisation of healthcare services by clinical and non-clinical healthcare workers Variables Healthcare services utilisation Clinical Non-clinical Good N = 41 n (%) Poor N = 189 n (%) Good N = 37 n (%) Poor N = 193 n (%) Age (years) < 40 (Young adults) 20 (15.4) 110 (84.6) 13 (15.5) 71 (84.5) ≥ 40 (Middle aged) 21 (21.0) 79 (79.0) 24 (16.4) 122 (83.6) χ²= 1.217; p = 0.270 χ²= 0.037; p = 0.848 Sex Male 12 (14.6) 70 (85.4) 16 (15.2) 89 (84.8) Female 29 (19.6) 119 (80.4) 21 (16.8) 104 (83.2) χ²= 0.886; p = 0.346 χ²= 0.103; p = 0.748 Marital status Single 8 (15.4) 44 (84.6) 1 (5.3) 18 (94.7) Married 33 (19.2) 139 (80.8) 34 (16.7) 170 (83.3) Divorced/separated/widowed 0 (0.0) 6 (100.0) 2 (28.6) 5 (71.4) LR = 2.789; p = 0.248 LR = 2 .870; p = 0.238 Religion Christianity 38 (17.5) 179 (82.5) 34 (16.3) 174 (83.7) Islam 3 (23.1) 10 (76.9) 3 (13.6) 19 (86.4) Fisher’s exact = 0.707 Fisher’s exact = 1.000 Ethnicity Yoruba 35 (19.9) 141 (80.1) 30 (14.6) 175 (85.4) Igbo 5 (18.5) 22 (81.5) 3 (33.3) 6 (66.7) Others* 1 (3.7) 26 (96.3) 4 (25.0) 12 (75.0) LR = 5.608; p = 0.061 χ²= 2.771; p = 0.250 The association between the sociodemographic profiles and utilization of healthcare services among the clinical and non-clinical healthcare workers was presented in Table 5 above. No socio-demographic profile including age, sex, marital status, religion had statistically significant association with healthcare services utilisation. Table 6 Predictors of good healthcare services utilisation among clinical healthcare workers Variables Adjusted 0dds ratio P-value 95% Confidence Interval (95% CI) Lower Upper Medical condition requiring routine monitoring Yes 1.710 0.375 0.523 5.588 No (Ref) 1 On regular medications Yes 5.519 0.003 1.804 16.885 No (Ref) 1 Health seeking behaviour Appropriate 4.869 0.001 1.944 12.198 Inappropriate (Ref) 1 Availability of health insurance Yes 2.633 0.041 1.042 6.652 No (Ref) 1 From the summary of the predictors of good healthcare services utilization as shown in Table 6 above; the predictors of good healthcare services utilisation among the clinical healthcare workers were being on regular medications, appropriate health seeking behaviour and availability of health insurance. Clinical healthcare workers who were on regular medications are 5.5 times more likely to utilise healthcare services that those who were not on regular medication (AOR = 5.519; 95%CI = 1.804–16.885). Clinical healthcare workers who had appropriate health seeking behaviour are 4.9 times more likely to utilise healthcare services than their counterpart who had inappropriate health seeking behaviour (AOR = 4.869; 95%CI = 1.944–12.198). The clinical healthcare workers who reported availability of health insurance are 2.6 times more likely to utilise healthcare services that those who reported non-availability of health insurance (AOR = 2.633; 95%CI = 1.042–6.652 QUALITATIVE RESULTS Deepened understanding of why HCWs delay seeking care. Four central themes emerged. Theme 1: Perceived Professional Identity and Self-Reliance Healthcare workers felt pressured to appear strong and avoid vulnerability. “As a health worker, falling sick feels like weakness.” (KII — Clinical) “You don’t want colleagues to see you as someone always going to clinic.” (KII — Clinical) This mentality encouraged self-treatment, over-the-counter medication and delay in formal care. Theme 2: Workload and Scheduling Barriers Shift duties and staffing shortages limited staff availability for medical appointments. “We are too few. Taking time off means others suffer.” (KII — Nurse) Clinical staff particularly reported lack of time to undergo proper investigations or check-ups. Theme 3: Confidentiality Concerns and Fear of Stigma Respondents expressed anxiety about becoming “the patient” within their own workplace. “You don’t want someone you work with to see your diagnosis.” (KII — Laboratory Staff) Privacy concerns were common among those with chronic illnesses or conditions considered socially sensitive. Theme 4: Accessibility and System-Level Barriers Facility bureaucracy, delayed appointments and costs were cited. “Even for us, the process is stressful. The queue is the same.” (KII — Non-clinical) Health insurance limitations occasionally forced out-of-pocket care. Summary of Key Qualitative Insights Major Issue Affected Group Contribution to Delay Self-diagnosis and self-medication More common in clinical staff Avoids formal care Staff shortages, shift patterns Both groups Less time to seek care Fear of stigma and visibility Clinical > Non-clinical Confidentiality issues Insurance & cost obstacles Especially non-clinical staff Reduces utilisation Qualitative findings complemented quantitative evidence, highlighting behavioural and institutional roots of delayed care among HCWs. DISCUSSION OF FINDINGS This study compared the health-seeking behaviour and utilisation of healthcare services among clinical and non-clinical healthcare workers (HCWs) in tertiary health facilities in Ondo State, Nigeria. It further examined predictors influencing utilisation patterns Despite their medical knowledge, clinical HCWs demonstrated poorer health-seeking behaviour than their non-clinical counterparts. This paradox may be due to self-diagnosis, workload pressures, confidentiality concerns, and professional identit y , which discourage them from seeking formal medical care. Both groups exhibited low utilisation of healthcare services, consistent with findings from similar studies in Nigeria, Ethiopia, and Israel 18 – 20 Many HCWs sought care only when illness became severe, highlighting delayed care-seeking tendencies. Clinical staff cited long waiting times and busy schedules as barriers, while non-clinical staff pointed to cost, lack of symptoms, and insufficient institutional support. Predictor analysis revealed that appropriate health-seeking behaviour, regular medication use, and health insurance coverage were significant determinants of good healthcare utilisation among clinical workers. Among non-clinical staff, prior medical consultation and appropriate health-seeking practices improved utilisation. Qualitative findings reinforced these quantitative trends, revealing four major themes: professional self-reliance, workload and scheduling barriers, confidentiality fears, and accessibility challenges. These themes underscore the behavioural and institutional roots of delayed care among HCWs. Clinical HCWs perceived themselves as less healthy than non-clinical staff, mirroring quantitative findings that a greater proportion of clinical workers had fallen ill within the past six months. Despite positive beliefs about routine check-ups, both groups demonstrated poor participation in preventive health, consistent with earlier findings among HCWs in South-South Nigeria Although clinical HCWs possessed higher health knowledge, their health-seeking behaviour was poorer than non-clinical workers. Over-familiarity with healthcare systems, confidence in self-diagnosis, and medication accessibility likely contributed to self-treatment and delayed engagement with formal care services For many respondents, healthcare use occurred only when illness severity compelled it. Clinical staff frequently cited long waiting times, while non-clinical workers reported lack of symptoms, cost and inadequate support systems as barriers 17 Logistic regression identified appropriate health-seeking behaviour, health insurance, and regular medication as significant predictors of good utilisation among clinical staff, while previous doctor consultation and appropriate behaviour predicted utilisation among non-clinical staff Qualitative findings reinforced quantitative trends, revealing that professional identity discourages help-seeking, confidentiality fears create avoidance of facility-based care, and workload restricts time to seek medical attention HCWs tasked with protecting population health often delay care for themselves. Limited routine screening exposes them to preventable morbidity and mortality. Conclusion Although healthcare workers demonstrated good awareness of health-seeking principles, both clinical and non-clinical HCWs exhibited poor utilisation of healthcare services, with clinical workers displaying more inappropriate health-seeking practices. Predictors of improved utilisation included appropriate health-seeking behaviour, regular medication and health insurance coverage Recommendations To Government Develop and enforce staff-centred workplace health policies Improve access to universal health insurance and subsidised screenings for HCWs Hospital Management Regular health education campaigns and preventive screening programs Institutional support to reduce waiting times and improve confidentiality of care Promote occupational health clinics offering fast-track services for staff Healthcare Workers Prioritise timely help-seeking and avoid self-medication Adopt preventive lifestyle habits and regular health monitoring Engage proactively with available healthcare and insurance schemes Strengthening these elements will enhance the well-being and productivity of HCWs and contribute to a safer health system. LIMITATIONS Self-reported data may be subject to recall and social desirability bias Cross-sectional design limits inference on causality Findings from tertiary facilities may not generalise to primary or private settings Work schedules may have reduced participation among certain cadres (e.g., shift workers) Abbreviations FMC OWO (Federal Medical Centre Owo), IBM SPSS (International Business Machines Corporation Statistical Package for the Social Sciences), KII (Key Informant Interview), NVIVO (Non-Versioned Information Versatile Outcomes), UNIMEDTH (University of Medical Sciences Teaching Hospital) Declarations Ethical approval and consent to participate: This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (2013 revision) and followed institutional research ethics standards. Ethical approval was obtained from the Research Ethics Review Committee of the Federal Medical Centre, Owo, Ondo State, Nigeria (Reference No: FMC/OW/380/VOLCLXXVIII/91). Administrative permission was also granted by the management of the hospital prior to data collection. The informed consent to participate in the study was obtained from all the participants in the study. Confidentiality and anonymity were ensured throughout data handling and reporting. Serial numbers and codes were used to identify respondents and the research assistants who interviewed them. The questionnaires were kept in a safe place accessible to the principal researcher alone. The respondents were assured that their responses would not be reported individually but as part of an overall study and that they would not face any consequences for the responses provided. Beneficence to participants: The study assessed and compared the health-seeking behaviour and utilisation of health services among clinical and non-clinical healthcare workers in the tertiary hospitals in Ondo state. Respondents were counselled and guided appropriately on questions concerning other aspects of their health not covered in the study. Non-maleficence to participants: The study was not invasive and without any harm to respondents since only questionnaires was used. Freedom to decline or withdraw from study: Participants were informed of their freedom to decline or opt out of the study at any time and were assured that there will not be any consequences for refusing to participate in the study. Consent for publication: The consent for publication has been obtained Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interests Declaration: The authors declare no competing interests. Funding: There was no financial support of any kind, either in terms of grants or equipment, or otherwise. Author’s Contribution: This work was carried in collaboration with all authors. Author I I, designed the study. Authors AMA and AAO supervised the work, Author BCI edited the manuscript, Author OOA co-edited the work. Acknowledgement: I want to express my unquantifiable gratitude for the support of all my consultants and colleagues in the department in making this work a reality. References Poortaghi S, Raiesifar A, Bozorgzad P, Golzari SEJ, Parvizy S, Rafii F. Evolutionary concept analysis of health seeking behavior in nursing: A systematic review. BMC Health Serv Res. 2015;15(1):523. Adewoye KR, Aremu SK, Ipinnimo TM, Salawu IA, Orewole TO, Bakare A. 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Health seeking behaviour and challenges in utilising health facilities in Wakiso district, Uganda. Afr Health Sci. 2014;14(4):1046–55. Sharma S, Anand T, Dey B, Ingle G, Kishore J. Prevalence of modifiable and non-modifiable risk factors and lifestyle disorders among health care professionals. Astrocyte. 2014;1(3):178. Chandra A SP. Role of Non-Clinical Human Resources for COVID-19: Strategic way forward. J Health Manag. 2021;22(4):541–9. Schou-Bredal I, Bonsaksen T, Ekeberg O, Skogstad L GTK. A Comparison between healthcare workers and non-healthcare workers’ anxiety, depression and PSTD during the initial COVID-19 lockdown. Public Heal – Open J. 2022;3(1):1–5. Osei-Yeboah J, Kye-Amoah KK, Owiredu WKBA, Lokpo SY, Esson J, Bella Johnson B, et al. Cardiometabolic risk factors among healthcare workers: A cross-sectional study at the Sefwi-Wiawso Municipal Hospital, Ghana. Biomed Res Int. 2018 Apr 23;18(2):40. Bana S, Yakoob J, Jivany N, Faisal A, Jawed H, Awan S. Understanding Health Seeking Behavior Of Health Care Professionals In Tertiary Care Hospitals In Pakistan. J Ayub Med Coll Abbottabad. 2016;28(3):545–9. Adamu H, Yusuf A, Inalegwu C, Sufi R, Adamu A. Factors influencing health-seeking behavior of health workers in a Tertiary Health Institution in Sokoto, Northwest Nigeria. Sahel Med J. 2018;21(3):162. Obiebi IP, Moeteke NS, Eze GU, Umuago IJ. How mindful of their own health are healthcare professionals? perception and practice of personnel in a tertiary hospital in Nigeria. Ghana Med J. 2020;54(4):215–24. Abuduxike G, Aşut Ö, Vaizoğlu SA, Cali S. Health-seeking behaviors and its determinants: A facility-based cross-sectional study in the Turkish republic of northern Cyprus. Int J Heal Policy Manag. 2020 Jun 1;9(6):240–9. Mohanty A, Kabi A, Mohanty AP. Health problems in healthcare workers: A review. J Fam Med Prim care. 2019 Aug;8(8):2568–72. Orbell S, Schneider H, Esbitt S, Gonzalez JS, Gonzalez JS, Shreck E, et al. Health Care Utilization. Encycl Behav Med. 2013;909–10. Kim HK, Lee M. Factors associated with health services utilization between the years 2010 and 2012 in Korea: Using Andersen’s Behavioral model. Osong Public Heal Res Perspect. 2016 Feb 1;7(1):18–25. Babitsch B, Gohl D, von Lengerke T. Das Verhaltensmodell der Inanspruchnahme gesundheitsbezogener Versorgung von Andersen re-revisited: Ein systematischer Review von Studien zwischen 1998-2011. GMS Psycho-Social-Medicine. 2012 Jan 1;9(6):11. Masiye F, Kaonga O. Determinants of healthcare utilisation and out-of-pocket payments in the context of free public primary healthcare in Zambia. Int J Heal Policy Manag. 2016;5(12):693–703. Clewley D, Rhon D, Flynn T, Koppenhaver S, Cook C. Health seeking behavior as a predictor of healthcare utilization in a population of patients with spinal pain. PLoS One. 2018 Aug 1;13(8):0201348. Additional Declarations No competing interests reported. Supplementary Files StudyQuestionnaire.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 Jan, 2026 Reviews received at journal 29 Dec, 2025 Reviews received at journal 29 Dec, 2025 Reviews received at journal 27 Dec, 2025 Reviewers agreed at journal 22 Dec, 2025 Reviewers agreed at journal 21 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviewers agreed at journal 20 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers invited by journal 12 Dec, 2025 Editor assigned by journal 08 Dec, 2025 Editor invited by journal 10 Nov, 2025 Submission checks completed at journal 10 Nov, 2025 First submitted to journal 10 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":242553,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eabove \u003c/strong\u003eshows the demographic variables and psychological characteristics.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8017279/v1/bb8e43587cfa4887c2afe6f0.png"},{"id":98441198,"identity":"5941f731-6ae7-4148-900c-cf376dedb79f","added_by":"auto","created_at":"2025-12-17 17:05:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":218828,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eabove \u003c/strong\u003eshow the\u003cstrong\u003e \u003c/strong\u003emodified Conceptual Framework of the Health-Seeking Behaviour and Utilisation of Healthcare Services.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8017279/v1/0834a90c8de6fcc6a4b8b3a8.png"},{"id":98623406,"identity":"0e2b81fa-b4cd-4c9f-868f-f77a30321b7a","added_by":"auto","created_at":"2025-12-19 17:06:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2706822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8017279/v1/4d499313-67de-49c1-b538-7ed88d03a841.pdf"},{"id":98402983,"identity":"a2547dd0-19ce-41b5-83e4-c78b94414a39","added_by":"auto","created_at":"2025-12-17 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appropriately, including beliefs, household decision-making, social networks, and access to financial and physical resources.\u0026sup2; Delayed care has been associated with increased morbidity, unfavourable clinical outcomes and avoidable deaths.\u0026sup3; Health-seeking behaviour therefore affects not only individual well-being but also population-level health outcomes through utilisation patterns.⁴\u003c/p\u003e\n\u003cp\u003eHealthcare workers (HCWs), both clinical and non-clinical, form the backbone of the health system and are expected to model appropriate health practices.⁵ Clinical HCWs deliver direct patient care, including doctors, nurses, pharmacists, laboratory professionals and therapists. Non-clinical HCWs support care delivery through administrative, financial, technical, and operational roles.⁶ Although their contributions differ, both groups are exposed to occupational risks, heavy workload and stress that can impair personal health.⁷\u003c/p\u003e\n\u003cp\u003eIronically, access to medical knowledge does not always translate to healthy behaviour. Evidence shows that HCWs often delay seeking care, rely heavily on self-medication, engage in informal consultations and avoid assuming the \u0026ldquo;patient role\u0026rdquo; due to stigma, confidentiality fears and workload pressure.⁸ This behaviour may result in under-diagnosed chronic conditions, late presentation and preventable mortality.⁹ Sudden deaths among HCWs attributed to undetected illness have raised concern in Nigeria.\u0026sup1;⁰\u003c/p\u003e\n\u003cp\u003eThere is also significant health system strain due to workforce shortages and migration, creating additional barriers to timely care-seeking for the remaining staff.\u0026sup1;\u0026sup1; Studies investigating HCW health-seeking behaviour in Nigeria have focused predominantly on clinical staff, with limited attention to non-clinical workers who may have less health literacy and less autonomy in navigating hospital systems.\u0026sup1;\u0026sup2;\u003c/p\u003e\n\u003cp\u003eUnderstanding differences in health-seeking patterns between clinical and non-clinical HCWs is essential for developing interventions that promote early care, preventive health behaviours and ultimately sustain a productive workforce. This study compares the two groups in tertiary hospitals in Ondo State and identifies factors influencing their healthcare utilisation.\u003c/p\u003e\n\u003ch2\u003eTheoretical frameworks surrounding the delay in seeking healthcare:\u0026nbsp;\u003c/h2\u003e\n\u003ch2\u003eHealth Belief Model:\u003c/h2\u003e\n\u003cp\u003eIn this study, as shown in figure 1 below, the HBM provides a theoretical basis for understanding the health-seeking behaviour of healthcare workers. It suggests that clinical and non-clinical staff are more likely to seek timely care when they \u003cstrong\u003eperceive themselves at risk\u003c/strong\u003e, \u003cstrong\u003erecognise the severity\u003c/strong\u003e of illness, \u003cstrong\u003ebelieve in the benefits\u003c/strong\u003e of early treatment, and \u003cstrong\u003ehave confidence\u003c/strong\u003e in their ability to access care despite perceived barriers.\u003c/p\u003e\n\u003cp\u003eIt proposes that health behaviour is influenced by perceived susceptibility, perceived severity, perceived benefits of action, perceived barriers, cues to action and self-efficacy.\u0026sup1;\u0026sup3; The model explains why individuals engage in preventive or care-seeking behaviours when faced with health threats as shown in figure 1 below\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIt also\u0026nbsp;\u003c/strong\u003eillustrates how individuals make decisions about their health by weighing perceived risks and benefits. It proposes that health-related behaviour is primarily influenced by six key constructs:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived Susceptibility\u003c/strong\u003e \u0026ndash; an individual\u0026rsquo;s belief about the likelihood of developing a health condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived Severity\u003c/strong\u003e \u0026ndash; how serious a person believes the consequences of the condition would be if it occurred.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived Benefits\u003c/strong\u003e \u0026ndash; the individual\u0026rsquo;s assessment of the positive outcomes expected from taking a specific health action.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived Barriers\u003c/strong\u003e \u0026ndash; the potential obstacles (e.g., time, cost, stigma, fear) that may prevent an individual from engaging in a health-promoting behaviour.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCues to Action\u003c/strong\u003e \u0026ndash; internal or external triggers (such as symptoms, media messages, or advice from colleagues) that prompt behaviour change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelf-Efficacy\u003c/strong\u003e \u0026ndash; confidence in one\u0026rsquo;s ability to successfully perform the desired action.\u003c/p\u003e\n\u003cp\u003eTogether, these components explain why individuals may or may not engage in preventive health practices or seek care promptly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, this Model as shown in Figure 1 above, suggests that people\u0026rsquo;s beliefs about health problems in terms of their perceived susceptibility, perceived severity, perceived benefits of action, and perceived barriers to action and self-efficacy explain engagement (or lack of engagement) in health-promoting behaviour\u003c/p\u003e\n\u003cp\u003eA conceptual framework is a visual representation that illustrates the pathways through which programmes achieve their objectives, and it constitutes a logical framework for developing an evaluation plan with appropriate indicators.\u003csup\u003e14\u003c/sup\u003e This conceptual framework, as shown in Figure 2 above, illustrates how various factors interact to influence the health-seeking behaviour and healthcare utilisation patterns of clinical and non-clinical healthcare workers. It integrates elements of the \u003cstrong\u003eHealth Belief Model\u003c/strong\u003e and \u003cstrong\u003eAndersen\u0026rsquo;s Behavioural Model of Health Service Use\u003c/strong\u003e, showing that health behaviour is not determined by a single factor but by a dynamic interplay of personal, behavioural, and systemic variables.\u003c/p\u003e\n\u003cp\u003eThe framework identifies \u003cstrong\u003eindependent variables\u003c/strong\u003e such as socio-demographic characteristics (age, sex, marital status, income, and education), occupational factors (cadre, workload, work schedule), and behavioural influences (knowledge, attitudes, and perceived barriers). These factors shape an individual\u0026rsquo;s \u003cstrong\u003eperceptions of susceptibility, severity, and benefits\u003c/strong\u003e, which in turn determine their \u003cstrong\u003ehealth-seeking behaviour\u003c/strong\u003e\u0026mdash;whether timely, delayed, or inappropriate.\u003c/p\u003e\n\u003cp\u003eHealth-seeking behaviour acts as an \u003cstrong\u003eintermediate or mediating variable\u003c/strong\u003e, linking background factors to actual \u003cstrong\u003eutilisation of healthcare services\u003c/strong\u003e\u0026mdash;the key dependent variable in this study. Utilisation is reflected in the frequency, type, and quality of services accessed (routine check-ups, screening, treatment, and preventive care)\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe model also recognises \u003cstrong\u003eenabling and reinforcing factors\u003c/strong\u003e such as health insurance coverage, accessibility of facilities, confidentiality, and social support systems, which either facilitate or hinder service utilisation. Ultimately, the interaction of these variables determines whether healthcare workers engage in proactive health practices or delay care\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn summary, the framework visually demonstrates that improving health-seeking behaviour among healthcare workers requires addressing not only individual attitudes but also structural and institutional determinants\u0026mdash;ensuring that behavioural change is supported by an enabling work environment and accessible healthcare systems.\u003c/p\u003e"},{"header":"STUDY AREA","content":"\u003cp\u003eThis study was conducted at two Federal tertiary hospitals in Ondo State, Southwest Nigeria: Federal Medical Centre (FMC), Owo and University of Medical Sciences Teaching Hospital Complex (UNIMEDTHC), Akure. Ondo State has a population of approximately 3.4 million people and 18 Local Government Areas. Healthcare services include primary, secondary and tertiary facilities, with these two tertiary hospitals serving as major referral centres offering specialist care, emergency services, surgical and diagnostic capabilities.\u003c/p\u003e\n\u003cp\u003eFMC Owo was established in 1993, while UNIMEDTHC Akure evolved from the former State General Hospital but now functions as the teaching hospital of the University of Medical Sciences. Both institutions employ clinical and non-clinical healthcare workers essential to service delivery\u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSTUDY DESIGN\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA hospital-based, comparative cross-sectional study was conducted among healthcare workers in the two tertiary hospitals to assess their health-seeking behaviour and healthcare utilisation, comparing clinical and non-clinical staff.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSTUDY POPULATION\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe target population included adult healthcare workers employed at the selected hospitals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical staff\u003c/strong\u003e comprised doctors, nurses, pharmacists, laboratory scientists, radiographers, and other allied health professionals. \u003cstrong\u003eNon-clinical staff\u003c/strong\u003e included administrative officers, accountants, secretaries, drivers, cleaners, technicians and other personnel not directly involved in patient care.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eINCLUSION AND EXCLUSION CRITERIA\u003c/strong\u003e\u003c/h2\u003e\n\u003ch3\u003eInclusion\u003c/h3\u003e\n\u003cp\u003e\u0026bull; Full-time employees in either clinical or non-clinical roles\u003cbr\u003e\u0026nbsp;\u0026bull; Minimum of six months working experience at the facility\u003cbr\u003e\u0026nbsp;\u0026bull; Consent to participate\u003c/p\u003e\n\u003ch3\u003eExclusion\u003c/h3\u003e\n\u003cp\u003e\u0026bull; Trainee interns and corps members\u003cbr\u003e\u0026nbsp;\u0026bull; Staff on leave or unavailable during data collection\u003cbr\u003e\u0026nbsp;\u0026bull; HCWs with severe medical or psychiatric conditions impairing participation\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSAMPLE SIZE DETERMINATION\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe sample size was calculated using the formula for comparing two proportions. Based on estimated prevalence from prior studies and adjusting for non-response, 460 respondents were targeted: 230 clinical and 230 non-clinical HCWs.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSAMPLING TECHNIQUE\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA two-stage sampling procedure was used:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eFacility selection\u003c/strong\u003e: FMC Owo and UNIMEDTH Akure were purposively selected as the major federal tertiary facilities in the state.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eProportionate stratified sampling\u003c/strong\u003e was used to select 230 clinical and 230 non-clinical staff across departments using staff registers as sampling frames, followed by simple random sampling to identify participants.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2\u003e\u003cstrong\u003eDATA COLLECTION METHODS\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA pretested, semi-structured, interviewer-administered questionnaire was used to obtain quantitative data on:\u003c/p\u003e\n\u003cp\u003e\u0026bull; Sociodemographic characteristics\u003cbr\u003e\u0026nbsp;\u0026bull; Health behaviours\u003cbr\u003e\u0026nbsp;\u0026bull; Health-seeking patterns\u003cbr\u003e\u0026nbsp;\u0026bull; Utilisation of formal healthcare services\u003cbr\u003e\u0026nbsp;\u0026bull; History of screening and preventive care\u003cbr\u003e\u0026nbsp;\u0026bull; Access to health insurance and medication adherence\u003c/p\u003e\n\u003cp\u003eThe questionnaire used in this study was developed solely for this study. This is as shown in Appendix 1.\u003c/p\u003e\n\u003cp\u003eQualitative data were collected using Key Informant Interviews (KIIs) with purposively selected leaders and senior professionals to gain deeper insight into determinants of delayed care-seeking. Interview guides ensured consistency, and interviews were recorded with permission.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDATA QUALITY ASSURANCE\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u0026bull; The questionnaire was adapted from validated instruments and contextualised\u003cbr\u003e\u0026nbsp;\u0026bull; Pretesting was conducted among HCWs in a separate hospital in Ondo State\u003cbr\u003e\u0026nbsp;\u0026bull; Research assistants were trained in confidentiality and interviewing techniques\u003cbr\u003e\u0026nbsp;\u0026bull; Daily checks of completed questionnaires ensured completeness and accuracy\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDATA ANALYSIS\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eQuantitative data were analysed using IBM SPSS version 25.\u003c/p\u003e\n\u003cp\u003eDescriptive statistics summarised variables using frequencies, percentages, means and standard deviations. Chi-square tests assessed associations between categorical variable. Variables significant at p\u0026lt;0.05 were entered into \u003cstrong\u003ebinary logistic regression\u003c/strong\u003e to determine predictors of health service utilisation. Adjusted odds ratios (AOR) and 95% confidence intervals were reported\u003c/p\u003e\n\u003cp\u003eQualitative data were transcribed verbatim and analysed using \u003cstrong\u003ethematic analysis\u003c/strong\u003e. NVivo 14 aided coding, theme development and triangulation with quantitative findings.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 460 healthcare workers participated, comprising 230 clinical and 230 non-clinical staff. Clinical staff were generally younger than non-clinical workers. Most participants were married and held tertiary-level education. Mean work experience was higher among non-clinical HCWs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eshows the socio-demographic profile of healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinicals\u003c/p\u003e \u003cp\u003eN = 230\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-clinicals\u003c/p\u003e \u003cp\u003eN = 230\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest statistics\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 40 (Young adults)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130 (56.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84 (36.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²\u003cb\u003e=\u003c/b\u003e18.489\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≥ 40 (Middle aged)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (43.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146 (63.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (Mean ± SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.60 ± 8.416\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.96 ± 7.324\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-test= -3.203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82 (35.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105 (45.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²=4.767\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148 (64.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125 (54.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (22.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (8.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²=18.138\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172 (74.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e204 (88.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/separated/widowed\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (3.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217 (94.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e208 (90.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²\u003cb\u003e=\u003c/b\u003e2.505\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (5.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (9.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176 (76.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e205 (89.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²\u003cb\u003e=\u003c/b\u003e14.021\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (11.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (3.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (11.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (7.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (3.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLR = 42.613\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (13.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230 (98.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e191 (83.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of practice (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≤ 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (21.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52 (22.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ²\u003cb\u003e=\u003c/b\u003e0.050\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180 (78.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e178 (77.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of practice (Mean ± SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.13 ± 7.285\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.30 ± 6.175\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-test = 2.907\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly income (naira)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≤ 30000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (2.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFisher’s exact=\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.030\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 30000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230 (100.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224 (97.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e*Others in ethnicity include Ebira, Edo, Idoma and Igala ethnic groups **\u003c/em\u003e χ² - \u003cem\u003eChi-square\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e***LR- Likelihood ratio ****Bolded p-value is statistically significant\u003c/h2\u003e \u003cp\u003eThe sociodemographic profiles of the participants as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e revealed a significant proportion (56.5%) of the clinical healthcare workers being \u0026lt; 40 years compared to 36.5% of the non-clinical healthcare workers (p \u0026lt; 0.001). More (64.3%) of the clinical healthcare workers were females than 54.3% of non-clinical healthcare workers (p = 0.029). Majority (89.1%) of non-clinical healthcare workers belonged to Yoruba tribe compared to 76.5% of the clinical healthcare workers (p = 0.001). All the clinical healthcare workers had more than thirty thousand naira as their monthly income as against 97.4% among the non-clinical healthcare workers (p = 0.030).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003edepict the h\u003c/em\u003eealth behaviour of clinical and non-clinical healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinicals\u003c/p\u003e \u003cp\u003eN = 230\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-clinicals\u003c/p\u003e \u003cp\u003eN = 230\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest statistics\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth behaviour\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood health behaviour\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (17.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (31.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e12.085\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor health behaviour\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e190 (82.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158 (68.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (13.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (10.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e0.516\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200 (87.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e205 (89.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegularity of alcohol intake (N = 55)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEveryday\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (20.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFisher’s exact=\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlternate days\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (36.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (40.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (63.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (40.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCigarette smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (1.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFisher’s exact=\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224 (97.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e227 (98.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe health behaviours of the healthcare workers as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e above reported a significant proportion (82.6%) of the clinical healthcare workers having poor health behaviour as against 68.7% among the non-clinical healthcare workers (p = 0.001). About two-third (63.3%) of the clinical healthcare workers drink alcohol occasionally compared to two-fifth (40.0%) among the non-clinical healthcare workers (p = 0.024).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eshows the h\u003c/em\u003eealth seeking behaviour among clinical and non-clinical healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinicals\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-clinicals\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth seeking behaviour (N = 460)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAppropriate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (12.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (20.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.604\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInappropriate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e201 (87.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184 (80.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSought healthcare services at last time of illness (N = 460)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123 (53.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (58.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.067\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107 (46.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (41.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of health facility preferred to visit when ill (N = 460)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (23.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (9.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.349\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176 (76.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e209 (90.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAction taken during last illness (N = 257)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisited TBA/faith-based organisation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsulted pharmacist/patent medicine vendor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (7.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (8.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisited a health facility\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e113 (91.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (91.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActions taken during last illness while not seeking healthcare (N = 203)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNothing\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (10.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (8.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.405\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTook over-the-counter self-medications\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73 (68.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (79.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (21.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (12.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotivation for visiting health facility at last time of illness (N = 235)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of the unknown\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55 (48.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (52.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.049\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe severity of illness\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42 (37.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (44.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of health facility visited at last time of illness (N = 235)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (13.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (7.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.225\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98 (86.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (92.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e*Others- self relaxation, counsel from colleagues, herbal concoction\u003c/h2\u003e \u003cp\u003eThe health seeking behaviour of participants as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e above found that a significant proportion (87.4%) of the clinical healthcare workers had inappropriate health seeking behaviour compared to 80.0% among the non-clinical healthcare workers (p = 0.032). More (90.9%) of non-clinical healthcare workers preferred to visit public health facility than 76.5% of the clinical healthcare workers (0.001). More non-clinical healthcare workers (52.5%) were motivated to visit the health facility as a result of fear of the unknown compared to 48.7% of the clinical healthcare workers (p = 0.011).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eshows the U\u003c/em\u003etilisation of health services among healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinicals\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-clinicals\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest statistics\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUtilisation of health services (N = 460)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood utilisation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41 (17.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (16.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e0.247\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.619\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor utilisation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189 (82.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193 (83.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEver accessed health services (N = 460)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112 (48.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108 (47.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e0.139\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118 (51.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122 (53.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMode of accessing health services (N = 220)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinic appointment\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88 (78.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100 (92.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e11.872\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver the phone\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (7.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (5.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome visit\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (14.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplied with doctor’s prescription (N = 202)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98 (100.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102 (98.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFisher’s exact\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFrequency of accessing check-up (N = 124)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (19.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (37.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLR \u003cb\u003e=\u003c/b\u003e 17.326\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (21.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (38.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBi-annually\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (14.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (6.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYearly\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (38.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (12.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot recall the last time\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (6.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (4.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eBased on the comparison of the level of utilization of health services among healthcare workers in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e above; clinic appointment was the mode of consultation among majority (92.6%) of the non-clinical healthcare workers compared to 78.6% of clinical healthcare workers (p = 0.003). A significant proportion (38.7%) of the clinical healthcare workers had routine medical check-up yearly compared to 12.9% of non-clinical healthcare workers (p = 0.002). There was no statistically significant association in the utilisation of health services between clinical and non-clinical healthcare workers, however, more clinical staff (17.8%) had good utilisation of health services than 16.1% of non-clinical staff (p = 0.619)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between sociodemographic profile and utilisation of healthcare services by clinical and non-clinical healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHealthcare services utilisation\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNon-clinical\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003cp\u003eN = 41\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eN = 189\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003cp\u003eN = 37\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eN = 193\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 40 (Young adults)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (15.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (84.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (15.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71 (84.5)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≥ 40 (Middle aged)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (21.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (79.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (16.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122 (83.6)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e 1.217; \u003cb\u003ep =\u003c/b\u003e 0.270\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e 0.037; \u003cb\u003ep =\u003c/b\u003e 0.848\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (14.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (85.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (15.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89 (84.8)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (19.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (80.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (16.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (83.2)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e 0.886; \u003cb\u003ep =\u003c/b\u003e 0.346\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e 0.103; \u003cb\u003ep =\u003c/b\u003e 0.748\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (15.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (84.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (5.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (94.7)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (19.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (80.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (16.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170 (83.3)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/separated/widowed\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (100.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (28.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (71.4)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLR =\u003c/b\u003e 2.789; \u003cb\u003ep =\u003c/b\u003e 0.248\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLR = 2\u003c/b\u003e.870; \u003cb\u003ep =\u003c/b\u003e 0.238\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (17.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179 (82.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (16.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e174 (83.7)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (23.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (76.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (13.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (86.4)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFisher’s exact =\u003c/b\u003e 0.707\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eFisher’s exact =\u003c/b\u003e 1.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (19.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141 (80.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (14.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e175 (85.4)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (81.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (96.3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLR =\u003c/b\u003e 5.608; \u003cb\u003ep =\u003c/b\u003e 0.061\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eχ²=\u003c/b\u003e 2.771; \u003cb\u003ep =\u003c/b\u003e 0.250\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe association between the sociodemographic profiles and utilization of healthcare services among the clinical and non-clinical healthcare workers was presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e above. No socio-demographic profile including age, sex, marital status, religion had statistically significant association with healthcare services utilisation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of good healthcare services utilisation among clinical healthcare workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdjusted 0dds ratio\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% Confidence Interval (95% CI)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMedical condition requiring routine monitoring\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.710\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.588\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo \u003cb\u003e(Ref)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOn regular medications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.519\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.804\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.885\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo \u003cb\u003e(Ref)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth seeking behaviour\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAppropriate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.869\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.944\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.198\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInappropriate \u003cb\u003e(Ref)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAvailability of health insurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.633\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.042\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.652\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo \u003cb\u003e(Ref)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eFrom the summary of the predictors of good healthcare services utilization as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e above; the predictors of good healthcare services utilisation among the clinical healthcare workers were being on regular medications, appropriate health seeking behaviour and availability of health insurance. Clinical healthcare workers who were on regular medications are 5.5 times more likely to utilise healthcare services that those who were not on regular medication (AOR = 5.519; 95%CI = 1.804–16.885). Clinical healthcare workers who had appropriate health seeking behaviour are 4.9 times more likely to utilise healthcare services than their counterpart who had inappropriate health seeking behaviour (AOR = 4.869; 95%CI = 1.944–12.198). The clinical healthcare workers who reported availability of health insurance are 2.6 times more likely to utilise healthcare services that those who reported non-availability of health insurance (AOR = 2.633; 95%CI = 1.042–6.652\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eQUALITATIVE RESULTS\u003c/h2\u003e \u003cp\u003eDeepened understanding of why HCWs delay seeking care. Four central themes emerged.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTheme 1: Perceived Professional Identity and Self-Reliance\u003c/h2\u003e \u003cp\u003eHealthcare workers felt pressured to appear strong and avoid vulnerability.\u003c/p\u003e \u003cp\u003e“As a health worker, falling sick feels like weakness.” \u003cem\u003e(KII — Clinical)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e“You don’t want colleagues to see you as someone always going to clinic.” \u003cem\u003e(KII — Clinical)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThis mentality encouraged self-treatment, over-the-counter medication and delay in formal care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eTheme 2: Workload and Scheduling Barriers\u003c/h2\u003e \u003cp\u003eShift duties and staffing shortages limited staff availability for medical appointments.\u003c/p\u003e \u003cp\u003e“We are too few. Taking time off means others suffer.” \u003cem\u003e(KII — Nurse)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eClinical staff particularly reported lack of time to undergo proper investigations or check-ups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eTheme 3: Confidentiality Concerns and Fear of Stigma\u003c/h2\u003e \u003cp\u003eRespondents expressed anxiety about becoming “the patient” within their own workplace.\u003c/p\u003e \u003cp\u003e“You don’t want someone you work with to see your diagnosis.” \u003cem\u003e(KII — Laboratory Staff)\u003c/em\u003e\u003c/p\u003e \u003cp\u003ePrivacy concerns were common among those with chronic illnesses or conditions considered socially sensitive.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTheme 4: Accessibility and System-Level Barriers\u003c/h2\u003e \u003cp\u003eFacility bureaucracy, delayed appointments and costs were cited.\u003c/p\u003e \u003cp\u003e“Even for us, the process is stressful. The queue is the same.” \u003cem\u003e(KII — Non-clinical)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eHealth insurance limitations occasionally forced out-of-pocket care.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eSummary of Key Qualitative Insights\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor Issue\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAffected Group\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eContribution to Delay\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-diagnosis and self-medication\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore common in clinical staff\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAvoids formal care\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaff shortages, shift patterns\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth groups\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess time to seek care\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of stigma and visibility\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical \u0026gt; Non-clinical\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConfidentiality issues\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance \u0026amp; cost obstacles\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEspecially non-clinical staff\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReduces utilisation\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eQualitative findings complemented quantitative evidence, highlighting behavioural and institutional roots of delayed care among HCWs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"DISCUSSION OF FINDINGS","content":"\u003cp\u003eThis study compared the health-seeking behaviour and utilisation of healthcare services among clinical and non-clinical healthcare workers (HCWs) in tertiary health facilities in Ondo State, Nigeria. It further examined predictors influencing utilisation patterns Despite their medical knowledge, clinical HCWs demonstrated poorer health-seeking behaviour than their non-clinical counterparts. This paradox may be due to self-diagnosis, workload pressures, confidentiality concerns, and professional identit\u003cb\u003ey\u003c/b\u003e, which discourage them from seeking formal medical care.\u003c/p\u003e\u003cp\u003eBoth groups exhibited low utilisation of healthcare services, consistent with findings from similar studies in Nigeria, Ethiopia, and Israel\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Many HCWs sought care only when illness became severe, highlighting delayed care-seeking tendencies. Clinical staff cited long waiting times and busy schedules as barriers, while non-clinical staff pointed to cost, lack of symptoms, and insufficient institutional support.\u003c/p\u003e\u003cp\u003ePredictor analysis revealed that appropriate health-seeking behaviour, regular medication use, and health insurance coverage were significant determinants of good healthcare utilisation among clinical workers. Among non-clinical staff, prior medical consultation and appropriate health-seeking practices improved utilisation.\u003c/p\u003e\u003cp\u003eQualitative findings reinforced these quantitative trends, revealing four major themes: professional self-reliance, workload and scheduling barriers, confidentiality fears, and accessibility challenges. These themes underscore the behavioural and institutional roots of delayed care among HCWs.\u003c/p\u003e\u003cp\u003eClinical HCWs perceived themselves as less healthy than non-clinical staff, mirroring quantitative findings that a greater proportion of clinical workers had fallen ill within the past six months. Despite positive beliefs about routine check-ups, both groups demonstrated poor participation in preventive health, consistent with earlier findings among HCWs in South-South Nigeria\u003c/p\u003e\u003cp\u003eAlthough clinical HCWs possessed higher health knowledge, their health-seeking behaviour was poorer than non-clinical workers. Over-familiarity with healthcare systems, confidence in self-diagnosis, and medication accessibility likely contributed to self-treatment and delayed engagement with formal care services\u003c/p\u003e\u003cp\u003eFor many respondents, healthcare use occurred only when illness severity compelled it. Clinical staff frequently cited long waiting times, while non-clinical workers reported lack of symptoms, cost and inadequate support systems as barriers\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eLogistic regression identified appropriate health-seeking behaviour, health insurance, and regular medication as significant predictors of good utilisation among clinical staff, while previous doctor consultation and appropriate behaviour predicted utilisation among non-clinical staff\u003c/p\u003e\u003cp\u003eQualitative findings reinforced quantitative trends, revealing that professional identity discourages help-seeking, confidentiality fears create avoidance of facility-based care, and workload restricts time to seek medical attention\u003c/p\u003e\u003cp\u003eHCWs tasked with protecting population health often delay care for themselves. Limited routine screening exposes them to preventable morbidity and mortality.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough healthcare workers demonstrated good awareness of health-seeking principles, both clinical and non-clinical HCWs exhibited poor utilisation of healthcare services, with clinical workers displaying more inappropriate health-seeking practices. Predictors of improved utilisation included appropriate health-seeking behaviour, regular medication and health insurance coverage\u003c/p\u003e\n\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\n \u003ch2\u003eRecommendations\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\n \u003ch2\u003eTo Government\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eDevelop and enforce staff-centred workplace health policies\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eImprove access to universal health insurance and subsidised screenings for HCWs\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\n \u003ch2\u003eHospital Management\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eRegular health education campaigns and preventive screening programs\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eInstitutional support to reduce waiting times and improve confidentiality of care\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePromote occupational health clinics offering fast-track services for staff\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\n \u003ch2\u003eHealthcare Workers\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ePrioritise timely help-seeking and avoid self-medication\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAdopt preventive lifestyle habits and regular health monitoring\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eEngage proactively with available healthcare and insurance schemes\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eStrengthening these elements will enhance the well-being and productivity of HCWs and contribute to a safer health system.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"LIMITATIONS","content":"\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eSelf-reported data may be subject to recall and social desirability bias\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eCross-sectional design limits inference on causality\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eFindings from tertiary facilities may not generalise to primary or private settings\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eWork schedules may have reduced participation among certain cadres (e.g., shift workers)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eFMC OWO\u003c/strong\u003e (Federal Medical Centre Owo),\u0026nbsp;\u003cstrong\u003eIBM SPSS\u003c/strong\u003e (International Business Machines Corporation Statistical Package for the Social Sciences),\u0026nbsp;\u003cstrong\u003eKII\u003c/strong\u003e (Key Informant Interview),\u0026nbsp;\u003cstrong\u003eNVIVO\u003c/strong\u003e (Non-Versioned Information Versatile Outcomes),\u0026nbsp;\u003cstrong\u003eUNIMEDTH\u003c/strong\u003e (University of Medical Sciences Teaching Hospital)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThis study was conducted in accordance with the ethical principles outlined in the \u003cstrong\u003eDeclaration of Helsinki (2013 revision)\u003c/strong\u003e and followed institutional research ethics standards. Ethical approval was obtained from the \u003cstrong\u003eResearch Ethics Review Committee of the Federal Medical Centre, Owo, Ondo State, Nigeria\u003c/strong\u003e (Reference No: FMC/OW/380/VOLCLXXVIII/91). Administrative permission was also granted by the management of the hospital prior to data collection. The informed consent to participate in the study was obtained from all the participants in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfidentiality and anonymity\u003c/strong\u003e were ensured throughout data handling and reporting. Serial numbers and codes were used to identify respondents and the research assistants who interviewed them. The questionnaires were kept in a safe place accessible to the principal researcher alone. The respondents were assured that their responses would not be reported individually but as part of an overall study and that they would not face any consequences for the responses provided.\u003c/p\u003e\n\u003cp id=\"_Toc169954714\"\u003e\u003cstrong\u003eBeneficence to participants: \u003c/strong\u003eThe study assessed and compared the health-seeking behaviour and utilisation of health services among clinical and non-clinical healthcare workers in the tertiary hospitals in Ondo state. Respondents were counselled and guided appropriately on questions concerning other aspects of their health not covered in the study.\u003c/p\u003e\n\u003cp id=\"_Toc169954715\"\u003e\u003cstrong\u003eNon-maleficence to participants: \u003c/strong\u003eThe study was not invasive and without any harm to respondents since only questionnaires was used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFreedom to decline or withdraw from study:\u003c/strong\u003e Participants were informed of their freedom to decline or opt out of the study at any time and were assured that there will not be any consequences for refusing to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eThe consent for publication has been obtained\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Declaration:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThere was no financial support of any kind, either in terms of grants or equipment, or otherwise.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contribution:\u0026nbsp;\u003c/strong\u003eThis work was carried in collaboration with all authors. Author I I, designed the study. Authors AMA and AAO supervised the work, Author BCI edited the manuscript, Author OOA co-edited the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eI want to express my unquantifiable gratitude for the support of all my consultants and colleagues in the department in making this work a reality.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePoortaghi S, Raiesifar A, Bozorgzad P, Golzari SEJ, Parvizy S, Rafii F. Evolutionary concept analysis of health seeking behavior in nursing: A systematic review. BMC Health Serv Res. 2015;15(1):523. \u003c/li\u003e\n\u003cli\u003eAdewoye KR, Aremu SK, Ipinnimo TM, Salawu IA, Orewole TO, Bakare A. Awareness and Practice of Proper Health Seeking Behaviour and Determinant of Self-Medication among Physicians and Nurses in a Tertiary Hospital in Southwest Nigeria. Open J Epidemiol. 2019;09(01):36\u0026ndash;49. \u003c/li\u003e\n\u003cli\u003eEllis AA, Traore S, Doumbia S, Dalglish SL, Winch PJ. Treatment actions and treatment failure: Case studies in the response to severe childhood febrile illness in Mali. BMC Public Health. 2012 Nov 5;12(1):1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAdam V, Aigbokhaode A. Sociodemographic factors associated with the healthcare-seeking behavior of heads of households in a rural community in Southern Nigeria. Sahel Med J. 2018;21(1):31. \u003c/li\u003e\n\u003cli\u003eGuzm\u0026aacute;n IB, Cuesta JG, Trelles M, Jaweed O, Cherestal S, Van Loenhout JAF, et al. Delays in arrival and treatment in emergency departments: Women, children and non-trauma consultations the most at risk in humanitarian settings. PLoS One. 2019 Mar 1;14(3):1\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eMusoke D, Boynton P, Butler C, Musoke MB. Health seeking behaviour and challenges in utilising health facilities in Wakiso district, Uganda. Afr Health Sci. 2014;14(4):1046\u0026ndash;55. \u003c/li\u003e\n\u003cli\u003eSharma S, Anand T, Dey B, Ingle G, Kishore J. Prevalence of modifiable and non-modifiable risk factors and lifestyle disorders among health care professionals. Astrocyte. 2014;1(3):178. \u003c/li\u003e\n\u003cli\u003eChandra A SP. Role of Non-Clinical Human Resources for COVID-19: Strategic way forward. J Health Manag. 2021;22(4):541\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eSchou-Bredal I, Bonsaksen T, Ekeberg O, Skogstad L GTK. A Comparison between healthcare workers and non-healthcare workers\u0026rsquo; anxiety, depression and PSTD during the initial COVID-19 lockdown. Public Heal \u0026ndash; Open J. 2022;3(1):1\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eOsei-Yeboah J, Kye-Amoah KK, Owiredu WKBA, Lokpo SY, Esson J, Bella Johnson B, et al. Cardiometabolic risk factors among healthcare workers: A cross-sectional study at the Sefwi-Wiawso Municipal Hospital, Ghana. Biomed Res Int. 2018 Apr 23;18(2):40. \u003c/li\u003e\n\u003cli\u003eBana S, Yakoob J, Jivany N, Faisal A, Jawed H, Awan S. Understanding Health Seeking Behavior Of Health Care Professionals In Tertiary Care Hospitals In Pakistan. J Ayub Med Coll Abbottabad. 2016;28(3):545\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAdamu H, Yusuf A, Inalegwu C, Sufi R, Adamu A. Factors influencing health-seeking behavior of health workers in a Tertiary Health Institution in Sokoto, Northwest Nigeria. Sahel Med J. 2018;21(3):162. \u003c/li\u003e\n\u003cli\u003eObiebi IP, Moeteke NS, Eze GU, Umuago IJ. How mindful of their own health are healthcare professionals? perception and practice of personnel in a tertiary hospital in Nigeria. Ghana Med J. 2020;54(4):215\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eAbuduxike G, Aşut \u0026Ouml;, Vaizoğlu SA, Cali S. Health-seeking behaviors and its determinants: A facility-based cross-sectional study in the Turkish republic of northern Cyprus. Int J Heal Policy Manag. 2020 Jun 1;9(6):240\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eMohanty A, Kabi A, Mohanty AP. Health problems in healthcare workers: A review. J Fam Med Prim care. 2019 Aug;8(8):2568\u0026ndash;72. \u003c/li\u003e\n\u003cli\u003eOrbell S, Schneider H, Esbitt S, Gonzalez JS, Gonzalez JS, Shreck E, et al. Health Care Utilization. Encycl Behav Med. 2013;909\u0026ndash;10. \u003c/li\u003e\n\u003cli\u003eKim HK, Lee M. Factors associated with health services utilization between the years 2010 and 2012 in Korea: Using Andersen\u0026rsquo;s Behavioral model. Osong Public Heal Res Perspect. 2016 Feb 1;7(1):18\u0026ndash;25. \u003c/li\u003e\n\u003cli\u003eBabitsch B, Gohl D, von Lengerke T. Das Verhaltensmodell der Inanspruchnahme gesundheitsbezogener Versorgung von Andersen re-revisited: Ein systematischer Review von Studien zwischen 1998-2011. GMS Psycho-Social-Medicine. 2012 Jan 1;9(6):11. \u003c/li\u003e\n\u003cli\u003eMasiye F, Kaonga O. Determinants of healthcare utilisation and out-of-pocket payments in the context of free public primary healthcare in Zambia. Int J Heal Policy Manag. 2016;5(12):693\u0026ndash;703. \u003c/li\u003e\n\u003cli\u003eClewley D, Rhon D, Flynn T, Koppenhaver S, Cook C. Health seeking behavior as a predictor of healthcare utilization in a population of patients with spinal pain. PLoS One. 2018 Aug 1;13(8):0201348. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Health-seeking behaviour, Healthcare utilisation, Delay in care, Clinical staff, Non-clinical staff, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-8017279/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8017279/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHealthcare workers (HCWs) are essential to health system functioning, yet they often neglect their own health due to workload, long shifts, staff shortages, and occupational risks. These factors may lead to delayed care, self-medication, and missed diagnoses, sometimes resulting in preventable morbidity and sudden deaths. This study assessed differences in health-seeking behaviour and healthcare service utilisation between clinical and non-clinical HCWs in tertiary hospitals in Ondo State, Nigeria, and examined the determinants of their care-seeking patterns.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA comparative, facility-based cross-sectional study was conducted among 230 clinical and 230 non-clinical HCWs selected using a two-stage sampling technique. Quantitative data were collected using pretested, semi-structured questionnaires and analysed with descriptive statistics, chi-square tests, and binary logistic regression at a 5% significance level. Qualitative data from Key Informant Interviews were analysed thematically using NVivo 14.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eClinical HCWs were significantly younger than non-clinical HCWs (56.5% vs. 36.5% \u0026lt;40 years; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Poor health behaviour was more common among clinical than non-clinical HCWs (82.6% vs. 68.7%; p\u0026thinsp;=\u0026thinsp;0.001). Inappropriate health-seeking behaviour was also higher among clinical HCWs (87.4% vs. 80.0%; p\u0026thinsp;=\u0026thinsp;0.032). Overall healthcare utilisation was low in both groups (82.2% vs. 83.9% poor utilisation; p\u0026thinsp;=\u0026thinsp;0.619). Predictors of good utilisation among clinical HCWs included regular medication use (AOR\u0026thinsp;=\u0026thinsp;5.52), appropriate health-seeking behaviour (AOR\u0026thinsp;=\u0026thinsp;4.87), and health insurance (AOR\u0026thinsp;=\u0026thinsp;2.63). Among non-clinical HCWs, prior consultation with a doctor and appropriate health-seeking behaviour were significant predictors.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBoth clinical and non-clinical HCWs exhibited poor health-seeking behaviour and low utilisation of healthcare services, despite good self-perceived health status. Addressing behavioural, organisational, and structural barriers is essential to enhance timely care-seeking among HCWs. Targeted institutional and policy interventions that promote preventive care, routine screening, and supportive work environments are recommended.\u003c/p\u003e","manuscriptTitle":"Why Healthcare Workers Delay Care: A Comparison of Clinical and Non-clinical Staff in Ondo State, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 12:02:08","doi":"10.21203/rs.3.rs-8017279/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-05T21:05:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-29T23:07:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-29T08:42:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-27T13:25:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38746256289320440469311108435679919586","date":"2025-12-22T08:19:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18387017130991087078669859546618147802","date":"2025-12-21T14:59:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T07:16:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286170468635140967684944300387833001114","date":"2025-12-20T07:03:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269705058571471219769851570894690835795","date":"2025-12-19T21:39:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289596191738817440486816413438896959188","date":"2025-12-19T18:01:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180667545283491799217168830584005795358","date":"2025-12-19T15:09:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80655526878998260464305555328495867692","date":"2025-12-19T13:52:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29647625023789789177310696024452559959","date":"2025-12-12T10:46:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-12T10:32:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T18:32:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-11T03:13:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-10T19:34:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-11-10T19:30:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2fde8e02-3801-4eae-b28a-b222efc390c8","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-17T12:02:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 12:02:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8017279","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8017279","identity":"rs-8017279","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}