Health Belief Model-based determinants of women’s participation in cervical cancer screening: A case-control study from southeastern Turkey

Health Belief Model-based determinants of women’s participation in cervical cancer screening: A case-control study from southeastern Turkey | 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 Health Belief Model-based determinants of women’s participation in cervical cancer screening: A case-control study from southeastern Turkey Ufuk ACAR, Feyyaz BARLAS, Burcu BEYAZGUL, Ibrahim KORUK This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7723261/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background In line with the World Health Organization’s elimination targets, HPV‑DNA-based cervical cancer screening is the standard; however, screening uptake remains suboptimal in many settings. To assess, in a centre implementing Türkiye’s national cancer screening standards, the relationship between women’s screening status and a Health Belief Model (HBM)-based, 19‑item attitude scale; and to provide clear, practice‑oriented findings on screening behaviour. Methods In a case-control design, women aged 30–65 years were studied (November-December 2024). A total of 210 participants (1:1 screened vs not screened) were included. The HBM‑based scale and sociodemographic variables were administered. Chi‑square tests were used for categorical variables and Mann-Whitney U tests for continuous variables. Scale scores were dichotomised at the median (low/high) and odds ratios (ORs) were calculated from 2×2 tables (two‑sided p < 0.05). Results Scale scores were significantly higher among women who had undergone screening [median (IQR)]: perceived severity 22(4) (p < 0.001, r = 0.339), perceived susceptibility 12(7) (p < 0.001, r = 0.314), perceived barriers/self-efficacy 17(3) (p < 0.001, r = 0.355), perceived benefits 19(4) (p = 0.03, r = 0.176), and total score 71(9) (p < 0.001, r = 0.483).Women with low scores had higher odds of not being screened: severity OR = 3.04, susceptibility OR = 3.33, barriers/self‑efficacy OR = 2.86, total score OR = 4.41 (all p < 0.001); benefits OR = 1.17 (not significant, p = 0.68). Conclusion The HBM‑based attitude scale indicates that perceived threat (severity, susceptibility) and barriers/self‑efficacy are strongly associated with women’s screening behaviour; the total belief score discriminates better than individual subscales. Findings support culturally sensitive communication and service arrangements focused on reducing barriers and enhancing self‑efficacy to improve screening participation. Cervical screening Screening uptake Papanicolaou (Pap) test Health Belief Model Women’s health Figures Figure 1 Background Cervical cancer is the fourth most common cancer among women worldwide; in 2022 approximately 660,000 new cases and 350,000 deaths were reported (the vast majority in low‑ and middle‑income countries) [ 1 ]. This burden reflects marked global inequities in access to vaccination, screening and effective treatment. In response, the World Health Organization (WHO) has adopted the elimination targets 90-70-90: 90% of girls fully vaccinated against HPV by age 15; 70% of women screened with a high‑performance test at ages 35 and 45; and 90% of women with pre‑cancer or cancer receiving appropriate treatment [ 2 , 3 ]. WHO’s 2021 guideline recommends HPV‑DNA testing as the preferred screening method over visual inspection with acetic acid (VIA) or cytology (Pap smear); 5–10‑year intervals are advised for HPV‑negative women, with more frequent intervals for women living with HIV [ 4 ]. Türkiye’s national cancer screening programme recommends HPV‑DNA testing every 5 years for women aged 30–65, with appropriate triage (cytology/colposcopy) for positive results [ 5 ]. At the country level, approximately 2,532 new cervical cancer cases and 1,245 deaths are estimated annually, underscoring the need to achieve elimination targets [ 6 ]. Within the Eastern Mediterranean Region (EMR), cervical cancer ranks sixth among women; in 2022 there were about 16,000 new cases and > 10,000 deaths. Substantial gaps remain in scaling up screening and vaccination across countries in the region. Participation in screening is shaped by individual‑ and system‑level factors including sociocultural norms, privacy/embarrassment, fear of pain, structural barriers to access and health literacy [ 7 ]. The Health Belief Model (HBM) is frequently used to explain the psychosocial determinants of screening behaviour. Multiple syntheses indicate that perceived benefits and perceived barriers are among the strongest correlates of behaviour, with perceived susceptibility and perceived severity also playing important roles [ 8 , 9 ]. Testing this theoretical framework-aligned with an HPV‑DNA‑based national screening strategy-within a neighbouring sociocultural context can inform the design of behavioural interventions and the integration of primary and secondary prevention [ 2 – 5 , 7 ]. This study aims to examine, among women aged 30–65 years, the association between having undergone cervical cancer screening (within a national programme prioritising HPV‑DNA with cytology triage where appropriate) and HBM components-perceived susceptibility, perceived severity, perceived benefits and perceived barriers/self‑efficacy; to assess discriminative performance; and to identify which perceptual domains should be prioritised to enhance screening participation. Using a case-control design, we seek to add practice‑oriented findings with high policy transferability to the limited research from our region. Methods Study design and reporting This research is an observational epidemiological case-control study. Reporting follows the STROBE checklist for case-control studies [ 10 ]. Research area: Structure of KETEM The study was conducted at the Cancer Early Diagnosis, Screening and Education Centre (KETEM) affiliated with the XXXX XXXX District Health Directorate. KETEMs provide community‑based cancer screening, counselling and education; they increase access to screening through annual population‑based plans and primary‑care referrals. Breast, cervical and colorectal screening are implemented according to national standards; HPV‑DNA primary cervical screening algorithms and triage processes (cytology/colposcopy) are standardized in routine practice. KETEM thus enables access to women who have and have not undergone screening within the same service pathway, supporting a comparative sample and reducing misclassification through standardized workflows. In Türkiye’s national programme, women aged 30–65 years are offered HPV‑DNA testing every 5 years with triage for positives; KETEMs are the front‑line implementers of this programme [ 11 , 12 ]. Study population, sample and participant selection The target population comprised women aged 30–65 years presenting to KETEM. Between November and December 2024, consecutive attendees who met eligibility criteria were invited. The case group included women who had not previously undergone cervical cancer screening; the control group comprised women who had a cervical smear at the centre. (Note: while the national programme is HPV‑DNA‑based, during fieldwork the operational indicator of screening behaviour was “having a smear taken”.) A 1:1 sampling ratio was achieved, yielding 210 participants (105 cases, 105 controls) for analysis. Eligibility criteria; Inclusion age 30–65 years; provision of informed consent; ability to understand and respond in Turkish. Exclusion prior hysterectomy or a diagnosis of cervical cancer; cognitive/communication limitations precluding questionnaire completion; repeat attendance during the study period (duplicate record). Sample size and power Following a pilot, G*Power 3.1 was used to estimate the required sample size for two independent groups assuming a small effect size (0.20), α = 0.05 and power = 0.95; a minimum of 105 participants per group was targeted and achieved [ 13 ]. Variables and measurements Dependent variable “Having undergone cervical cancer screening”, operationalized as having a cervical smear at KETEM (yes/no). Independent variables total and subscale scores of the Health Belief Model (HBM)-based Sexually Transmitted Infections Attitude Scale (19 items; perceived susceptibility, perceived severity, perceived benefits, perceived barriers/self‑efficacy) and sociodemographic/sexual‑reproductive characteristics (age, education, marital status, perceived income, sexual activity, family‑planning method use). On the barriers/self‑efficacy subscale, higher scores indicate fewer barriers/greater self‑efficacy. The scale was developed in Turkish; the original study reported Cronbach’s α = 0.74; internal consistency (total and subscales) was re‑evaluated in the present study [ 14 ]. Data collection Trained researchers administered a face‑to‑face questionnaire at KETEM (approximately 10–12 minutes). Screening status was cross‑checked with centre records wherever feasible and duplicates were prevented. Data confidentiality was ensured using anonymized identifiers. Ethical approval and administrative permissions Ethical approval was obtained from the Harran University Faculty of Medicine Clinical Research Ethics Committee (session 02.12.2024, decision HRU/24.19.34). Institutional permission was granted by the Sanlıurfa Provincial Health Directorate (16.10.2024, decision 380284). Written informed consent was obtained from all participants. All procedures complied with the Declaration of Helsinki and institutional standards. Statistical analysis Analyses were performed using IBM SPSS Statistics, Version 26.0 (IBM Corp., Armonk, NY, USA). Normality of continuous variables was assessed using the Kolmogorov-Smirnov test, distributional plots, and skewness/kurtosis. Categorical variables were summarized as n (%); continuous variables as mean ± SD and median (IQR) as appropriate. Chi‑square tests were used for categorical comparisons and Mann-Whitney U tests for continuous variables (effect sizes were reported as rank-biserial correlation (r) for Mann-Whitney U test). To examine associations between scale scores and screening status, scores were dichotomized at the median (low/high) and odds ratios (ORs) were calculated. Receiver Operating Characteristic (ROC) analysis was used to evaluate the discriminative performance of the total score (area under the curve, AUC) and to identify an optimal cut‑off. Statistical significance was set at two‑sided p < 0.05. Results A total of 210 women were included; 105 had undergone cervical cancer screening and 105 had not. The median age was 45.0 years (30.0–63.0) among those who had been screened and 42.0 years (30.0–65.0) among those not screened, with no difference by age (p = 0.21). Groups were also similar by education (p = 0.26), gainful employment (p = 0.64), marital status (p = 0.07) and perceived income (p = 0.30) (Table 1 ). Table 1 Sociodemographic characteristics of participants by cervical cancer screening status Variable Screened n (%) Not screened n (%) χ² p Education level No formal education 28 (58.3) 20 (41.7) 6.46 0.26 Literate, no schooling 7 (30.4) 16 (69.6) Primary education 32 (52.5) 29 (47.5) Secondary education 18 (56.3) 14 (43.7) High school 12 (46.2) 14 (53.8) University or higher 8 (40.0) 12 (60.0) Employment Employed 9 (42.9) 12 (57.1) 0.21 0.64 Unemployed 96 (50.8) 93 (49.2) Marital status Single/Divorced/Separated/Widowed 6 (28.6) 15 (71.4) 3.39 0.07 Married 99 (52.4) 90 (47.6) Perceived income High 33 (57.9) 24 (42.1) 2.73 0.30 Moderate 42 (49.4) 43 (50.6) Low 30 (44.1) 38 (55.9) Screened = had undergone cervical cancer screening; Not screened = had not undergone cervical cancer screening. Values are presented as n (%). Chi-square test was used . Screening uptake did not differ by sexual activity (active: 50.0% vs inactive: 50.0%; p = 1.00) or by use of any family‑planning method (yes: 50.0% vs no: 50.0%; p = 1.00). There was a difference across method types (p = 0.04), driven by the condom and tubal ligation groups (Table 2 ). Table 2 Sexual activity and family-planning use in relation to cervical screening status Variable Screened n (%) Not screened n (%) χ² p Sexual activity Active 79 (50.0) 79 (50.0) 0.00 1.00 Inactive 26 (50.0) 26 (50.0) Use of any family-planning method Yes 43 (50.0) 43 (50.0) 0.00 1.00 No 62 (50.0) 62 (50.0) Type of family-planning method † Oral contraceptive pill 6 (75.0) 2 (25.0) 10.10 0.04 Condom 6 (28.6) 15 (71.4) Intrauterine device 17 (45.9) 20 (54.1) Withdrawal 6 (60.0) 4 (40.0) Tubal ligation 8 (80.0) 2 (20.0) † Fisher’s exact test recommended due to small expected counts; the overall difference was mainly contributed by the condom and tubal-ligation groups. Screened = had undergone cervical cancer screening; Not screened = had not undergone cervical cancer screening. Scores on the HBM‑based Sexually Transmitted Infections Attitude Scale (subscales and total) were significantly higher in women who had undergone screening than in those who had not [median (IQR); mean ± SD]: For perceived severity, 22 (4); 21.8 ± 2.7 vs 20 (3); 20.2 ± 2.8 among those not screened (p < 0.001, r = 0.339). For perceived susceptibility, 12 (7); 12.2 ± 4.4 vs 10 (5); 9.8 ± 4.0 (p < 0.001, r = 0.314); for barriers/self-efficacy, 17 (3); 16.8 ± 2.7 vs 16 (3); 15.3 ± 2.6 (p < 0.001, r = 0.355); for benefits, 19 (4); 19.1 ± 3.3 vs 19 (4); 17.8 ± 3.3 (p = 0.03, r = 0.176). The total score was 71 (9); 69.9 ± 7.8 among screened vs 64 (11); 63.0 ± 7.9 among non-screened (p < 0.001, r = 0.483) (Table 3 ). Table 3 Attitude scale scores by cervical screening status Subscale Screened median (IQR) Not screened median (IQR) U statistic p rank-biserial r Perceived severity 22 (4) 20 (3) 3646.00 < 0.001 0.339 Perceived susceptibility 12 (7) 10 (5) 3781.00 < 0.001 0.314 Perceived barriers/self-efficacy † 17 (3) 16 (3) 3555.00 < 0.001 0.355 Perceived benefits 19 (4) 19 (4) 4541.00 0.03 0.176 Total score 71 (9) 64 (11) 2848.00 < 0.001 0.483 Values are median (IQR). Mann-Whitney U test was applied. Rank-biserial correlation (r) is reported as an effect size (small ≈ 0.1, medium ≈ 0.3, large ≥ 0.5). † For the barriers/self-efficacy subscale, higher scores indicate fewer barriers and greater self-efficacy. Odds of not being screened (median‑based low vs high) were higher for women with low scores on the subscales and the total score: perceived severity OR = 3.04 (95% CI 1.72–5.38), perceived susceptibility OR = 3.33 (1.88–5.92), barriers/self‑efficacy OR = 2.86 (1.61–5.05) and total score OR = 4.41 (2.46–7.87). For benefits, OR = 1.17 (0.68-2.00) and the association was not significant (p = 0.68) (Table 4 ). Table 4 Odds of not being screened for cervical cancer by low vs high attitude scale scores (median split) Subscale Not screened n/N (%)-Low Not screened n/N (%)-High OR (low vs high) 95% CI p Perceived severity 73/118 (61.9) 32/92 (34.8) 3.04 1.72–5.38 < 0.001 Perceived susceptibility 75/120 (62.5) 30/90 (33.3) 3.33 1.88–5.92 < 0.001 Perceived barriers/self-efficacy † 75/124 (60.5) 30/86 (34.9) 2.86 1.61–5.05 < 0.001 Perceived benefits 58/112 (51.8) 47/98 (48.0) 1.17 0.68-2.00 0.68 Total score 75/113 (66.4) 30/97 (30.9) 4.41 2.46–7.87 < 0.001 † On this subscale, higher scores indicate fewer barriers and greater self‑efficacy. Event = not screened; Reference = high score (≥ median); Low score = < median. ORs and 95% CIs are from 2×2 tables. Using the total score, ROC analysis showed AUC = 0.742 (p < 0.001). An optimal cut‑off of 66.5 yielded specificity 65.7% and sensitivity 70.5% for predicting having undergone screening (Fig. 1 ). Discussion This case-control study was conducted in a centre implementing Türkiye’s national cancer screening standards to delineate the perceptual dimensions underlying women’s cervical cancer screening test uptake using a scale grounded in the Health Belief Model (HBM). The findings indicate a clear and consistent association between HBM components and screening behaviour: higher perceived severity and higher perceived susceptibility, as well as lower perceived barriers/higher self‑efficacy, were each associated with a significant reduction in the odds of not undergoing a screening test. The total scale score provided the strongest discrimination (OR = 4.41). An AUC of 0.742 for the total score suggests that concise, scale‑based assessments could be integrated into service workflows; nevertheless, ROC‑derived thresholds are not a substitute for clinical decision‑making. Overall, the pattern aligns with WHO’s elimination strategy (90-70-90) and Türkiye’s HPV‑DNA primary screening approach, offering behavioural targets to improve participation across the Eastern Mediterranean Region (EMR) [ 2 – 5 , 7 ]. Perceived threat (severity and susceptibility) emerged as a strong determinant in this study, consistent with meta‑analytical and scoping syntheses demonstrating that HBM constructs explain health behaviours [ 8 , 9 ]. Regional evidence points in the same direction: in Iran, a study of women’s genital warts prevention behaviours identified perceived severity, susceptibility and self‑efficacy as direct determinants [ 15 ]. Among women living with HIV in rural Uganda, participation in cervical cancer screening-conducted in line with national guidance using VIA and/or cytology-was independently predicted by perceived susceptibility and perceived severity [ 16 ]. Taken together, these data support targeting counselling and reminder messages-within KETEM services-in ways that ethically and accurately reinforce perceived threat, thereby facilitating behaviour change. Findings on barriers/self‑efficacy reaffirm the central role of believing one can perform the recommended action. Self‑efficacy is theoretically a core driver of behaviour change [ 17 ] and is positioned as a key leverage point in contemporary HBM formulations [ 18 ]. In the EMR, salient barriers include privacy, fear of pain/embarrassment, logistics of scheduling/transport, and access to female providers; among young adults in Gulf countries, awareness of screening and vaccination remains limited and perceived barriers are substantial [ 7 , 19 ]. Our results therefore highlight the potential impact of service arrangements such as female provider options, flexible appointments, on‑site screening teams, and counselling/reminders to reduce barriers and enhance self‑efficacy. Although perceived benefits followed the expected direction in our data, the association did not reach statistical significance; this may reflect masking by barriers/self‑efficacy or a ceiling effect in this sample. Even so, the literature consistently supports systematic effects of benefits and barriers on preventive behaviours [ 8 , 9 ]. From a programme standpoint, HPV‑DNA primary screening remains the foundation of Türkiye’s standards; while VIA/cytology are still used in resource‑constrained settings, WHO’s 2021 guideline recommends HPV‑DNA testing as the preferred method [ 4 , 5 , 11 ]. In the present study, screening behaviour was operationalised as having a Pap smear; interpretation should consider the primacy of HPV‑DNA and triage steps in the national algorithm [ 4 , 5 , 11 ]. Given marked EMR‑wide variation in cervical cancer burden and participation [ 7 ], our findings have practical value for region‑tailored communication materials and access‑facilitating service designs. Regarding ROC performance, a 66.5‑point threshold provided 70.5% sensitivity and 65.7% specificity; such a criterion can be used for prioritisation, but only alongside field protocols that account for the costs of misclassification [ 20 ]. Embedding brief, scale‑based assessments into routine counselling could standardise risk communication and contribute to programme goals [ 2 , 3 , 5 , 7 ]. Strengths and limitations Conducting the study within KETEM, the frontline programme implementer, enabled concurrent access to women who had and had not undergone a screening test through the same entry point, likely reducing misclassification. The sample size was pre‑planned and achieved, and the HBM‑based attitudes were measured multidimensionally, with additional ROC assessment of discrimination. By design, a case-control study yields odds ratios (ORs); relative risks cannot be directly estimated. Dichotomising scale scores at the median can entail information loss and may inflate apparent effect sizes. The single‑centre setting and reliance on self‑report introduce potential biases, and some potential confounders (e.g. HPV vaccination status, prior abnormal Pap results) may not have been fully accounted for. These limitations warrant cautious generalisation. Conclusions and recommendations Conclusions. Perceived threat (severity, susceptibility) and barriers/self‑efficacy are key determinants of women’s participation in cervical cancer screening; the total belief score discriminates screening behaviour better than individual subscales (AUC = 0.742; OR = 4.41). This pattern provides a strong basis for behaviourally targeted strategies to increase participation across the EMR [ 2 , 3 , 5 , 7 , 11 ]. Along with this, the following recommendations can be listed in line with the aims and objectives of the study: Integrate barrier‑reduction and self‑efficacy-enhancing measures into routine services (privacy‑protecting processes, access to female providers, rapid scheduling, on‑site screening teams, structured counselling/reminders). Deploy evidence‑based, culturally attuned messages that ethically strengthen perceived threat. Pilot the use of the total scale score for prioritisation (e.g. threshold 66.5) within protocols that explicitly consider misclassification costs. Future research should employ multicentre designs with multivariable analyses and incorporate variables such as HPV vaccination and history of abnormal Pap results. Abbreviations EMR Eastern Mediterranean Region HBM Health Belief Model HPV Human papillomavirus HPV-DNA Human papillomavirus deoxyribonucleic acid HSGM General Directorate of Public Health KETEM Cancer Early Diagnosis, Screening and Education Centre Pap Papanicolaou VIA Visual inspection with acetic acid WHO World Health Organization Declarations Acknowledgements We would like to thank all the interviewers for sharing their experiences and contributing to the data collection process. Author Contributions U.A., F.B., B.B., and I.K. conceptualised and designed the study, designed the data collection instrument, collected data, and contributed to initial manuscript drafting. U.A, F.B, and B.B. contributed equally to this work and should be considered joint first authors. Contributed to the conceptualisation and design of the study, contributed to data interpretation, and critically reviewed and revised the manuscript for important intellectual content. U.A. and B.B. contributed to the conceptualisation and design of the study, contributed to designing the data collection instrument, supervised data collection, analysed and interpreted the data, and drafted the initial manuscript. All authors have reviewed, revised, and approved the final manuscript. Funding The authors received no specific funding for this work. Data Availability Statement The data that support the findings of this study are available from the corresponding author, [UA], upon reasonable request. Ethical Approval and Administrative Permissions Ethical approval was obtained from the Harran University Faculty of Medicine Clinical Research Ethics Committee (session 02.12.2024, decision HRU/24.19.34). Institutional permission was granted by the Sanlıurfa Provincial Health Directorate (16.10.2024, decision 380284). Written informed consent was obtained from all participants. All procedures complied with the Declaration of Helsinki and institutional standards. Consent for publication Not applicable. Competing interests The authors declare that there are no conflicts of interest regarding the publication of this paper. References World Health Organization. Cervical cancer - Key facts. 5 Mar 2024. Available at: https://www.who.int/news-room/fact-sheets/detail/cervical-cancer (Accessed 12 Sep 2025). World Health Organization. Global strategy to accelerate the elimination of cervical cancer as a public health problem. Geneva: WHO; 2020. Available at: https://www.who.int/publications-detail-redirect/9789240014107 (Accessed 12 Sep 2025). World Health Organization. Cervical cancer elimination initiative: Targets 90-70-90 by 2030. Available at: https://www.who.int/initiatives/cervical-cancer-elimination-initiative (Accessed 12 Sep 2025). World Health Organization. WHO guideline for screening and treatment of cervical pre‑cancer lesions for cervical cancer prevention. 2nd ed. Geneva: WHO; 2021. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7723261","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":548304822,"identity":"a314eab5-76dd-48a5-8373-cc5795ee1364","order_by":0,"name":"Ufuk 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Directorate","correspondingAuthor":false,"prefix":"","firstName":"Feyyaz","middleName":"","lastName":"BARLAS","suffix":""},{"id":548304824,"identity":"6e4182b9-443f-4439-b91e-f2b24fc1aaa5","order_by":2,"name":"Burcu BEYAZGUL","email":"","orcid":"","institution":"Harran University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Burcu","middleName":"","lastName":"BEYAZGUL","suffix":""},{"id":548304825,"identity":"888c1666-d630-42ab-8489-1e74d16d9d8d","order_by":3,"name":"Ibrahim KORUK","email":"","orcid":"","institution":"Harran University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"","lastName":"KORUK","suffix":""}],"badges":[],"createdAt":"2025-09-26 15:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7723261/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7723261/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96555026,"identity":"fde184b6-a4e6-443f-b471-8c03ba29ffa0","added_by":"auto","created_at":"2025-11-23 11:37:01","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":131990,"visible":true,"origin":"","legend":"","description":"","filename":"BlindedmanuscriptBMC.docx","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/b8de26cb4761f83166d0c030.docx"},{"id":96604733,"identity":"db239782-4f3d-450f-9e5e-42c1367d174d","added_by":"auto","created_at":"2025-11-24 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11:37:01","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":65179,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/1938b1f7dba0497153c0c858.png"},{"id":96555025,"identity":"967d6846-3b37-49ad-9d50-7f17079fc3b7","added_by":"auto","created_at":"2025-11-23 11:37:01","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22153,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/222cb642d0850ad9a0d0e438.png"},{"id":96555027,"identity":"2483c3d1-dd5e-46c2-a4e9-dfb23db5a56d","added_by":"auto","created_at":"2025-11-23 11:37:01","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78272,"visible":true,"origin":"","legend":"","description":"","filename":"7c920ed7e34e4de39660845957935ad21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/5f43a9ad8848c0c9236b3c96.xml"},{"id":96555030,"identity":"a25e198c-9111-4628-ba95-2d75d80fe909","added_by":"auto","created_at":"2025-11-23 11:37:01","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":86981,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/f4b2da988a56989357b150fb.html"},{"id":96555022,"identity":"aa8af5b6-7349-4d7d-bd18-fb3998673d8b","added_by":"auto","created_at":"2025-11-23 11:37:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":65179,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve of the HBM‑based attitude total score for discriminating women who had undergone cervical cancer screening (AUC = 0.742). At the 66.5 cut‑off, sensitivity = 70.5% and specificity = 65.7%; the dashed diagonal denotes the no‑discrimination line.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/6483c93b423bc90d4bd0b273.png"},{"id":96708180,"identity":"bc77ec17-9118-47c0-991c-83e7ccc3d75e","added_by":"auto","created_at":"2025-11-25 09:58:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":966931,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7723261/v1/a6141bd0-040b-49cf-9ea6-4bbffd0715eb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health Belief Model-based determinants of women’s participation in cervical cancer screening: A case-control study from southeastern Turkey","fulltext":[{"header":"Background","content":"\u003cp\u003eCervical cancer is the fourth most common cancer among women worldwide; in 2022 approximately 660,000 new cases and 350,000 deaths were reported (the vast majority in low‑ and middle‑income countries) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This burden reflects marked global inequities in access to vaccination, screening and effective treatment. In response, the World Health Organization (WHO) has adopted the elimination targets 90-70-90: 90% of girls fully vaccinated against HPV by age 15; 70% of women screened with a high‑performance test at ages 35 and 45; and 90% of women with pre‑cancer or cancer receiving appropriate treatment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWHO\u0026rsquo;s 2021 guideline recommends HPV‑DNA testing as the preferred screening method over visual inspection with acetic acid (VIA) or cytology (Pap smear); 5\u0026ndash;10‑year intervals are advised for HPV‑negative women, with more frequent intervals for women living with HIV [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. T\u0026uuml;rkiye\u0026rsquo;s national cancer screening programme recommends HPV‑DNA testing every 5 years for women aged 30\u0026ndash;65, with appropriate triage (cytology/colposcopy) for positive results [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. At the country level, approximately 2,532 new cervical cancer cases and 1,245 deaths are estimated annually, underscoring the need to achieve elimination targets [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWithin the Eastern Mediterranean Region (EMR), cervical cancer ranks sixth among women; in 2022 there were about 16,000 new cases and \u0026gt;\u0026thinsp;10,000 deaths. Substantial gaps remain in scaling up screening and vaccination across countries in the region. Participation in screening is shaped by individual‑ and system‑level factors including sociocultural norms, privacy/embarrassment, fear of pain, structural barriers to access and health literacy [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe Health Belief Model (HBM) is frequently used to explain the psychosocial determinants of screening behaviour. Multiple syntheses indicate that perceived benefits and perceived barriers are among the strongest correlates of behaviour, with perceived susceptibility and perceived severity also playing important roles [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Testing this theoretical framework-aligned with an HPV‑DNA‑based national screening strategy-within a neighbouring sociocultural context can inform the design of behavioural interventions and the integration of primary and secondary prevention [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to examine, among women aged 30\u0026ndash;65 years, the association between having undergone cervical cancer screening (within a national programme prioritising HPV‑DNA with cytology triage where appropriate) and HBM components-perceived susceptibility, perceived severity, perceived benefits and perceived barriers/self‑efficacy; to assess discriminative performance; and to identify which perceptual domains should be prioritised to enhance screening participation. Using a case-control design, we seek to add practice‑oriented findings with high policy transferability to the limited research from our region.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and reporting\u003c/h2\u003e\u003cp\u003eThis research is an observational epidemiological case-control study. Reporting follows the STROBE checklist for case-control studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eResearch area: Structure of KETEM\u003c/h3\u003e\n\u003cp\u003eThe study was conducted at the Cancer Early Diagnosis, Screening and Education Centre (KETEM) affiliated with the XXXX XXXX District Health Directorate. KETEMs provide community‑based cancer screening, counselling and education; they increase access to screening through annual population‑based plans and primary‑care referrals. Breast, cervical and colorectal screening are implemented according to national standards; HPV‑DNA primary cervical screening algorithms and triage processes (cytology/colposcopy) are standardized in routine practice. KETEM thus enables access to women who have and have not undergone screening within the same service pathway, supporting a comparative sample and reducing misclassification through standardized workflows. In T\u0026uuml;rkiye\u0026rsquo;s national programme, women aged 30\u0026ndash;65 years are offered HPV‑DNA testing every 5 years with triage for positives; KETEMs are the front‑line implementers of this programme [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eStudy population, sample and participant selection\u003c/h3\u003e\n\u003cp\u003eThe target population comprised women aged 30\u0026ndash;65 years presenting to KETEM. Between November and December 2024, consecutive attendees who met eligibility criteria were invited. The case group included women who had not previously undergone cervical cancer screening; the control group comprised women who had a cervical smear at the centre. (Note: while the national programme is HPV‑DNA‑based, during fieldwork the operational indicator of screening behaviour was \u0026ldquo;having a smear taken\u0026rdquo;.) A 1:1 sampling ratio was achieved, yielding 210 participants (105 cases, 105 controls) for analysis.\u003c/p\u003e\u003cp\u003eEligibility criteria;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInclusion\u003c/strong\u003e\u003cp\u003eage 30\u0026ndash;65 years; provision of informed consent; ability to understand and respond in Turkish.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eExclusion\u003c/strong\u003e\u003cp\u003eprior hysterectomy or a diagnosis of cervical cancer; cognitive/communication limitations precluding questionnaire completion; repeat attendance during the study period (duplicate record).\u003c/p\u003e\u003c/p\u003e\n\u003ch3\u003eSample size and power\u003c/h3\u003e\n\u003cp\u003eFollowing a pilot, G*Power 3.1 was used to estimate the required sample size for two independent groups assuming a small effect size (0.20), α\u0026thinsp;=\u0026thinsp;0.05 and power\u0026thinsp;=\u0026thinsp;0.95; a minimum of 105 participants per group was targeted and achieved [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eVariables and measurements\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable\u003c/strong\u003e\u003cp\u003e\u0026ldquo;Having undergone cervical cancer screening\u0026rdquo;, operationalized as having a cervical smear at KETEM (yes/no).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eIndependent variables\u003c/strong\u003e\u003cp\u003etotal and subscale scores of the Health Belief Model (HBM)-based Sexually Transmitted Infections Attitude Scale (19 items; perceived susceptibility, perceived severity, perceived benefits, perceived barriers/self‑efficacy) and sociodemographic/sexual‑reproductive characteristics (age, education, marital status, perceived income, sexual activity, family‑planning method use). On the barriers/self‑efficacy subscale, higher scores indicate fewer barriers/greater self‑efficacy. The scale was developed in Turkish; the original study reported Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.74; internal consistency (total and subscales) was re‑evaluated in the present study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData collection\u003c/h2\u003e\u003cp\u003eTrained researchers administered a face‑to‑face questionnaire at KETEM (approximately 10\u0026ndash;12 minutes). Screening status was cross‑checked with centre records wherever feasible and duplicates were prevented. Data confidentiality was ensured using anonymized identifiers.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003e\u003cb\u003eand administrative permissions\u003c/b\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003eEthical approval was obtained from the Harran University Faculty of Medicine Clinical Research Ethics Committee (session 02.12.2024, decision HRU/24.19.34). Institutional permission was granted by the Sanlıurfa Provincial Health Directorate (16.10.2024, decision 380284). Written informed consent was obtained from all participants. All procedures complied with the Declaration of Helsinki and institutional standards.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAnalyses were performed using IBM SPSS Statistics, Version 26.0 (IBM Corp., Armonk, NY, USA). Normality of continuous variables was assessed using the Kolmogorov-Smirnov test, distributional plots, and skewness/kurtosis. Categorical variables were summarized as n (%); continuous variables as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and median (IQR) as appropriate. Chi‑square tests were used for categorical comparisons and Mann-Whitney U tests for continuous variables (effect sizes were reported as rank-biserial correlation (r) for Mann-Whitney U test). To examine associations between scale scores and screening status, scores were dichotomized at the median (low/high) and odds ratios (ORs) were calculated. Receiver Operating Characteristic (ROC) analysis was used to evaluate the discriminative performance of the total score (area under the curve, AUC) and to identify an optimal cut‑off. Statistical significance was set at two‑sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 210 women were included; 105 had undergone cervical cancer screening and 105 had not. The median age was 45.0 years (30.0\u0026ndash;63.0) among those who had been screened and 42.0 years (30.0\u0026ndash;65.0) among those not screened, with no difference by age (p\u0026thinsp;=\u0026thinsp;0.21). Groups were also similar by education (p\u0026thinsp;=\u0026thinsp;0.26), gainful employment (p\u0026thinsp;=\u0026thinsp;0.64), marital status (p\u0026thinsp;=\u0026thinsp;0.07) and perceived income (p\u0026thinsp;=\u0026thinsp;0.30) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eSociodemographic characteristics of participants by cervical cancer screening status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScreened\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot screened\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eχ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\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\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28 (58.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20 (41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e6.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiterate, no schooling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (30.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (69.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32 (52.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (47.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18 (56.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (43.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12 (46.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (53.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUniversity or higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (40.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (60.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\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\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e96 (50.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e93 (49.2)\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/Divorced/Separated/Widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (28.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15 (71.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.07\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\u003e99 (52.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90 (47.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived income\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\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33 (57.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24 (42.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42 (49.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43 (50.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30 (44.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38 (55.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eScreened\u0026thinsp;=\u0026thinsp;had undergone cervical cancer screening; Not screened\u0026thinsp;=\u0026thinsp;had not undergone cervical cancer screening. Values are presented as n (%). Chi-square test was used\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eScreening uptake did not differ by sexual activity (active: 50.0% vs inactive: 50.0%; p\u0026thinsp;=\u0026thinsp;1.00) or by use of any family‑planning method (yes: 50.0% vs no: 50.0%; p\u0026thinsp;=\u0026thinsp;1.00). There was a difference across method types (p\u0026thinsp;=\u0026thinsp;0.04), driven by the condom and tubal ligation groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eSexual activity and family-planning use in relation to cervical screening status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScreened\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot screened\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eχ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSexual activity\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\u003eActive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInactive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26 (50.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUse of any family-planning method\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\u003e43 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.00\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\u003e62 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62 (50.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eType of family-planning method\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\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\u003eOral contraceptive pill\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e10.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCondom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (28.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15 (71.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntrauterine device\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17 (45.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20 (54.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWithdrawal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (60.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4 (40.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTubal ligation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (20.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026dagger; Fisher\u0026rsquo;s exact test recommended due to small expected counts; the overall difference was mainly contributed by the condom and tubal-ligation groups. Screened\u0026thinsp;=\u0026thinsp;had undergone cervical cancer screening; Not screened\u0026thinsp;=\u0026thinsp;had not undergone cervical cancer screening.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eScores on the HBM‑based Sexually Transmitted Infections Attitude Scale (subscales and total) were significantly higher in women who had undergone screening than in those who had not [median (IQR); mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD]: For perceived severity, 22 (4); 21.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 vs 20 (3); 20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 among those not screened (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.339). For perceived susceptibility, 12 (7); 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4 vs 10 (5); 9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.314); for barriers/self-efficacy, 17 (3); 16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 vs 16 (3); 15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.355); for benefits, 19 (4); 19.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 vs 19 (4); 17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 (p\u0026thinsp;=\u0026thinsp;0.03, r\u0026thinsp;=\u0026thinsp;0.176). The total score was 71 (9); 69.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 among screened vs 64 (11); 63.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 among non-screened (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.483) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eAttitude scale scores by cervical screening status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubscale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScreened\u003c/p\u003e\u003cp\u003emedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot screened\u003c/p\u003e\u003cp\u003emedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eU\u003c/p\u003e\u003cp\u003estatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003erank-biserial r\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived severity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3646.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived susceptibility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3781.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.314\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived barriers/self-efficacy\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3555.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.355\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived benefits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4541.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71 (9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2848.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.483\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues are median (IQR). Mann-Whitney U test was applied. Rank-biserial correlation (r) is reported as an effect size (small\u0026thinsp;\u0026asymp;\u0026thinsp;0.1, medium\u0026thinsp;\u0026asymp;\u0026thinsp;0.3, large\u0026thinsp;\u0026ge;\u0026thinsp;0.5). \u0026dagger; For the barriers/self-efficacy subscale, higher scores indicate fewer barriers and greater self-efficacy.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eOdds of not being screened (median‑based low vs high) were higher for women with low scores on the subscales and the total score: perceived severity OR\u0026thinsp;=\u0026thinsp;3.04 (95% CI 1.72\u0026ndash;5.38), perceived susceptibility OR\u0026thinsp;=\u0026thinsp;3.33 (1.88\u0026ndash;5.92), barriers/self‑efficacy OR\u0026thinsp;=\u0026thinsp;2.86 (1.61\u0026ndash;5.05) and total score OR\u0026thinsp;=\u0026thinsp;4.41 (2.46\u0026ndash;7.87). For benefits, OR\u0026thinsp;=\u0026thinsp;1.17 (0.68-2.00) and the association was not significant (p\u0026thinsp;=\u0026thinsp;0.68) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eOdds of not being screened for cervical cancer by low vs high attitude scale scores (median split)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubscale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot screened\u003c/p\u003e\u003cp\u003en/N (%)-Low\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot screened\u003c/p\u003e\u003cp\u003en/N (%)-High\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003cp\u003e(low vs high)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived severity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73/118 (61.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32/92 (34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.72\u0026ndash;5.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived susceptibility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e75/120 (62.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30/90 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.88\u0026ndash;5.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived barriers/self-efficacy\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e75/124 (60.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30/86 (34.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.61\u0026ndash;5.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived benefits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58/112 (51.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47/98 (48.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68-2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e75/113 (66.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30/97 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.46\u0026ndash;7.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026dagger; On this subscale, higher scores indicate fewer barriers and greater self‑efficacy.\u003c/p\u003e\u003cp\u003eEvent\u0026thinsp;=\u0026thinsp;not screened; Reference\u0026thinsp;=\u0026thinsp;high score (\u0026ge;\u0026thinsp;median); Low score\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;median. ORs and 95% CIs are from 2\u0026times;2 tables.\u003c/p\u003e\u003cp\u003eUsing the total score, ROC analysis showed AUC\u0026thinsp;=\u0026thinsp;0.742 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). An optimal cut‑off of 66.5 yielded specificity 65.7% and sensitivity 70.5% for predicting having undergone screening (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis case-control study was conducted in a centre implementing Türkiye’s national cancer screening standards to delineate the perceptual dimensions underlying women’s cervical cancer screening test uptake using a scale grounded in the Health Belief Model (HBM). The findings indicate a clear and consistent association between HBM components and screening behaviour: higher perceived severity and higher perceived susceptibility, as well as lower perceived barriers/higher self‑efficacy, were each associated with a significant reduction in the odds of not undergoing a screening test. The total scale score provided the strongest discrimination (OR = 4.41). An AUC of 0.742 for the total score suggests that concise, scale‑based assessments could be integrated into service workflows; nevertheless, ROC‑derived thresholds are not a substitute for clinical decision‑making. Overall, the pattern aligns with WHO’s elimination strategy (90-70-90) and Türkiye’s HPV‑DNA primary screening approach, offering behavioural targets to improve participation across the Eastern Mediterranean Region (EMR) [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePerceived threat (severity and susceptibility) emerged as a strong determinant in this study, consistent with meta‑analytical and scoping syntheses demonstrating that HBM constructs explain health behaviours [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Regional evidence points in the same direction: in Iran, a study of women’s genital warts prevention behaviours identified perceived severity, susceptibility and self‑efficacy as direct determinants [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Among women living with HIV in rural Uganda, participation in cervical cancer screening-conducted in line with national guidance using VIA and/or cytology-was independently predicted by perceived susceptibility and perceived severity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Taken together, these data support targeting counselling and reminder messages-within KETEM services-in ways that ethically and accurately reinforce perceived threat, thereby facilitating behaviour change.\u003c/p\u003e\u003cp\u003eFindings on barriers/self‑efficacy reaffirm the central role of believing one can perform the recommended action. Self‑efficacy is theoretically a core driver of behaviour change [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and is positioned as a key leverage point in contemporary HBM formulations [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the EMR, salient barriers include privacy, fear of pain/embarrassment, logistics of scheduling/transport, and access to female providers; among young adults in Gulf countries, awareness of screening and vaccination remains limited and perceived barriers are substantial [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Our results therefore highlight the potential impact of service arrangements such as female provider options, flexible appointments, on‑site screening teams, and counselling/reminders to reduce barriers and enhance self‑efficacy. Although perceived benefits followed the expected direction in our data, the association did not reach statistical significance; this may reflect masking by barriers/self‑efficacy or a ceiling effect in this sample. Even so, the literature consistently supports systematic effects of benefits and barriers on preventive behaviours [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFrom a programme standpoint, HPV‑DNA primary screening remains the foundation of Türkiye’s standards; while VIA/cytology are still used in resource‑constrained settings, WHO’s 2021 guideline recommends HPV‑DNA testing as the preferred method [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In the present study, screening behaviour was operationalised as having a Pap smear; interpretation should consider the primacy of HPV‑DNA and triage steps in the national algorithm [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Given marked EMR‑wide variation in cervical cancer burden and participation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], our findings have practical value for region‑tailored communication materials and access‑facilitating service designs.\u003c/p\u003e\u003cp\u003eRegarding ROC performance, a 66.5‑point threshold provided 70.5% sensitivity and 65.7% specificity; such a criterion can be used for prioritisation, but only alongside field protocols that account for the costs of misclassification [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Embedding brief, scale‑based assessments into routine counselling could standardise risk communication and contribute to programme goals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eConducting the study within KETEM, the frontline programme implementer, enabled concurrent access to women who had and had not undergone a screening test through the same entry point, likely reducing misclassification. The sample size was pre‑planned and achieved, and the HBM‑based attitudes were measured multidimensionally, with additional ROC assessment of discrimination.\u003c/p\u003e\u003cp\u003eBy design, a case-control study yields odds ratios (ORs); relative risks cannot be directly estimated. Dichotomising scale scores at the median can entail information loss and may inflate apparent effect sizes. The single‑centre setting and reliance on self‑report introduce potential biases, and some potential confounders (e.g. HPV vaccination status, prior abnormal Pap results) may not have been fully accounted for. These limitations warrant cautious generalisation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions and recommendations","content":"\u003cp\u003eConclusions. Perceived threat (severity, susceptibility) and barriers/self‑efficacy are key determinants of women’s participation in cervical cancer screening; the total belief score discriminates screening behaviour better than individual subscales (AUC = 0.742; OR = 4.41). This pattern provides a strong basis for behaviourally targeted strategies to increase participation across the EMR [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Along with this, the following recommendations can be listed in line with the aims and objectives of the study:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIntegrate barrier‑reduction and self‑efficacy-enhancing measures into routine services (privacy‑protecting processes, access to female providers, rapid scheduling, on‑site screening teams, structured counselling/reminders).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eDeploy evidence‑based, culturally attuned messages that ethically strengthen perceived threat.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePilot the use of the total scale score for prioritisation (e.g. threshold 66.5) within protocols that explicitly consider misclassification costs.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eFuture research should employ multicentre designs with multivariable analyses and incorporate variables such as HPV vaccination and history of abnormal Pap results.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEMR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Eastern Mediterranean Region\u003c/p\u003e\n\u003cp\u003eHBM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Health Belief Model\u003c/p\u003e\n\u003cp\u003eHPV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human papillomavirus\u003c/p\u003e\n\u003cp\u003eHPV-DNA \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Human papillomavirus deoxyribonucleic acid\u003c/p\u003e\n\u003cp\u003eHSGM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;General Directorate of Public Health\u003c/p\u003e\n\u003cp\u003eKETEM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cancer Early Diagnosis, Screening and Education Centre\u003c/p\u003e\n\u003cp\u003ePap \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Papanicolaou\u003c/p\u003e\n\u003cp\u003eVIA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Visual inspection with acetic acid\u003c/p\u003e\n\u003cp\u003eWHO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the interviewers for sharing their experiences and contributing to the data collection process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eU.A., F.B., B.B., and I.K. conceptualised and designed the study, designed the data collection instrument, collected data, and contributed to initial manuscript drafting. U.A, F.B, and B.B. contributed equally to this work and should be considered joint first authors. Contributed to the conceptualisation and design of the study, contributed to data interpretation, and critically reviewed and revised the manuscript for important intellectual content. U.A. and B.B. contributed to the conceptualisation and design of the study, contributed to designing the data collection instrument, supervised data collection, analysed and interpreted the data, and drafted the initial manuscript. All authors have reviewed, revised, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, [UA], upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Administrative Permissions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Harran University Faculty of Medicine Clinical Research Ethics Committee (session 02.12.2024, decision HRU/24.19.34). Institutional permission was granted by the Sanlıurfa Provincial Health Directorate (16.10.2024, decision 380284). Written informed consent was obtained from all participants. All procedures complied with the Declaration of Helsinki and institutional standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest regarding the publication of this paper.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Cervical cancer - Key facts. 5 Mar 2024. Available at: https://www.who.int/news-room/fact-sheets/detail/cervical-cancer (Accessed 12 Sep 2025). \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Global strategy to accelerate the elimination of cervical cancer as a public health problem. Geneva: WHO; 2020. Available at: https://www.who.int/publications-detail-redirect/9789240014107 (Accessed 12 Sep 2025). \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Cervical cancer elimination initiative: Targets 90-70-90 by 2030. Available at: https://www.who.int/initiatives/cervical-cancer-elimination-initiative (Accessed 12 Sep 2025). \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO guideline for screening and treatment of cervical pre‑cancer lesions for cervical cancer prevention. 2nd ed. Geneva: WHO; 2021. Available at: https://www.who.int/publications/i/item/9789240030824 (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eRepublic of Turkey Ministry of Health, General Directorate of Public Health (HSGM). Cancer screenings - Cervical cancer screening (ages 30-65; HPV‑DNA every 5 years). Available at: https://hsgm.saglik.gov.tr/tr/kanser-taramalari (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eICO/IARC HPV Information Centre. Turkey - Human Papillomavirus and Related Cancers, Fact Sheet 2023. 10 Mar 2023. Available at: https://hpvcentre.net/statistics/reports/TUR_FS.pdf (Accessed 12 Sep 2025). \u003c/li\u003e\n\u003cli\u003eWHO EMRO. Cervical Cancer Awareness Month 2024 - Eastern Mediterranean Region figures. Available at: https://www.emro.who.int/noncommunicable-diseases/campaigns/cervical-cancer-awareness-month-2024.html (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eCarpenter CJ. A meta-analysis of the effectiveness of Health Belief Model variables in predicting behavior. Health Commun. 2010;25(8):661-669. doi:10.1080/10410236.2010.521906.\u003c/li\u003e\n\u003cli\u003eSulat JS, Prabandari YS, Sanusi R, Hapsari ED, Santoso B. The validity of Health Belief Model variables in predicting behavioral change: a scoping review. Health Educ. 2018;118(6):499-512. doi:10.1108/HE-05-2018-0027.\u003c/li\u003e\n\u003cli\u003eEQUATOR Network. STROBE Statement-Checklist for case-control studies. Available at: https://www.equator-network.org/reporting-guidelines/strobe/ (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eGeneral Directorate of Public Health (HSGM). Cervical Cancer Screening Programme National Standards. Ankara: Republic of Turkey Ministry of Health; 2012. Available at:https://hsgm.saglik.gov.tr/depo/Mevzuat/Genel_Nitelikli_Yazi_ve_Gorusler/\nServiks_Kanseri_Tarama_Programi_\nUlusal_Standartlari.pdf (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eGeneral Directorate of Public Health (HSGM). Addresses of Cancer Early Diagnosis, Screening and Education Centres (KETEM) - national network. Available at: https://hsgm.saglik.gov.tr/tr/ketem.html (Accessed 12 Sep 2025).\u003c/li\u003e\n\u003cli\u003eFaul F, Erdfelder E, Buchner A, Lang A‑G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149-1160. doi:10.3758/BRM.41.4.1149.\u003c/li\u003e\n\u003cli\u003eBeyazg\u0026uuml;l B, Koruk F, Koruk İ. Development of a scale for attitude toward sexually transmitted infections based on the Health Belief Model. Eur J Obstet Gynecol Reprod Biol. 2024;298:42-48. doi:10.1016/j.ejogrb.2024.04.036. \u003c/li\u003e\n\u003cli\u003eShahsavari S, Alavi A, Razmjoue P, Mohseni S, Ranae V, Hosseini Z, et al. A predictive model of genital warts preventive behaviors among women in southern Iran: application of the Health Belief Model. BMC Womens Health. 2022;22(1):63. doi:10.1186/s12905-022-01610-9.\u003c/li\u003e\n\u003cli\u003eVigneshwaran E, Goruntla N, Bommireddy BR, Mantargi MJS, Mopuri B, Thammisetty DP, et al. Prevalence and predictors of cervical cancer screening among HIV‑positive women in rural western Uganda: insights from the Health Belief Model. BMC Cancer. 2023;23(1):1216. doi:10.1186/s12885-023-11406-6.\u003c/li\u003e\n\u003cli\u003eBandura A. Self‑efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191-215. doi:10.1037/0033-295X.84.2.191.\u003c/li\u003e\n\u003cli\u003eSkinner CS, Tiro J, Champion VL. The Health Belief Model. In: Glanz K, Rimer BK, Viswanath K, editors. Health Behavior: Theory, Research, and Practice. 5th ed. San Francisco (CA): Jossey‑Bass; 2015. p. 75-94.\u003c/li\u003e\n\u003cli\u003eMahmoud I, Al Eid MMA, Mohamed MA, Aladwani AJ, El Amin NEM. Human papillomavirus vaccination and Pap test uptake, awareness and barriers among young adults in Gulf Cooperation Council countries: a comparative cross‑sectional survey. J Infect Public Health. 2024;17(10):102525. doi:10.1016/j.jiph.2024.102525.\u003c/li\u003e\n\u003cli\u003eHajian‑Tilaki K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med. 2013;4(2):627-635. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755824/ (Accessed 12 Sep 2025).\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-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cervical screening, Screening uptake, Papanicolaou (Pap) test, Health Belief Model, Women’s health","lastPublishedDoi":"10.21203/rs.3.rs-7723261/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7723261/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIn line with the World Health Organization\u0026rsquo;s elimination targets, HPV‑DNA-based cervical cancer screening is the standard; however, screening uptake remains suboptimal in many settings. To assess, in a centre implementing T\u0026uuml;rkiye\u0026rsquo;s national cancer screening standards, the relationship between women\u0026rsquo;s screening status and a Health Belief Model (HBM)-based, 19‑item attitude scale; and to provide clear, practice‑oriented findings on screening behaviour.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn a case-control design, women aged 30\u0026ndash;65 years were studied (November-December 2024). A total of 210 participants (1:1 screened vs not screened) were included. The HBM‑based scale and sociodemographic variables were administered. Chi‑square tests were used for categorical variables and Mann-Whitney U tests for continuous variables. Scale scores were dichotomised at the median (low/high) and odds ratios (ORs) were calculated from 2\u0026times;2 tables (two‑sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eScale scores were significantly higher among women who had undergone screening [median (IQR)]: perceived severity 22(4) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.339), perceived susceptibility 12(7) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.314), perceived barriers/self-efficacy 17(3) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.355), perceived benefits 19(4) (p\u0026thinsp;=\u0026thinsp;0.03, r\u0026thinsp;=\u0026thinsp;0.176), and total score 71(9) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.483).Women with low scores had higher odds of not being screened: severity OR\u0026thinsp;=\u0026thinsp;3.04, susceptibility OR\u0026thinsp;=\u0026thinsp;3.33, barriers/self‑efficacy OR\u0026thinsp;=\u0026thinsp;2.86, total score OR\u0026thinsp;=\u0026thinsp;4.41 (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); benefits OR\u0026thinsp;=\u0026thinsp;1.17 (not significant, p\u0026thinsp;=\u0026thinsp;0.68).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe HBM‑based attitude scale indicates that perceived threat (severity, susceptibility) and barriers/self‑efficacy are strongly associated with women\u0026rsquo;s screening behaviour; the total belief score discriminates better than individual subscales. Findings support culturally sensitive communication and service arrangements focused on reducing barriers and enhancing self‑efficacy to improve screening participation.\u003c/p\u003e","manuscriptTitle":"Health Belief Model-based determinants of women’s participation in cervical cancer screening: A case-control study from southeastern Turkey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-23 11:36:56","doi":"10.21203/rs.3.rs-7723261/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-02T12:30:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-20T17:44:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T20:01:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102185014207593892903068746222167489158","date":"2025-11-17T19:47:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79973964431901512616119034527228120019","date":"2025-11-12T15:56:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-11T21:28:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-21T06:40:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-01T06:11:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-30T17:42:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2025-09-30T16:32:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5284275b-d3f5-4951-bdd1-143c5ab6e1e8","owner":[],"postedDate":"November 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T17:08:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-23 11:36:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7723261","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7723261","identity":"rs-7723261","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}