Factors explaining men's intentions to support their partner's participation in cervical cancer screening

Cervical cancer is the fourth most common cancer in women globally and a leading cause of mortality in LMICs, with India contributing a substantial share of cases and deaths. While HPV vaccination and condom use are primary prevention strategies, screening remains the mainstay in India due to cost and implementation challenges of vaccination. Despite opportunistic and emerging programmatic screening (NPCDCS), uptake is low, influenced by psychological, social, and structural factors. Men often influence women’s health decisions in India, and prior evidence suggests poor male knowledge and potential opposition to screening. Guided by behaviour theories (HBM, PMT, TPB) and prior work indicating a modified TPB (attitudes, subjective norms, structural barriers, and habits) best predicts women’s screening intentions, this study aimed to test a similar model for men’s intention to support their partners’ participation in cervical cancer screening and to assess moderation by health literacy and education.

Prior studies in LMICs show low knowledge of cervical cancer among men and significant influence of male partners on women’s screening decisions. WHO recommends male involvement in education for cervical cancer prevention. The TPB and other health behaviour models (HBM, PMT) have been used to predict screening; a recent review found HBM frequently used for interventions and TPB effective for predicting intention. Authors’ previous work among Indian women indicated that a modified TPB model incorporating attitudes, subjective norms, structural barriers, and habits enhances prediction of screening intentions. Literature also links health literacy to preventive behaviours and screening uptake, suggesting its potential role in shaping attitudes and intentions toward screening.

Design and setting: Cross-sectional survey among male partners of sexually active women in Karnataka, India. Data collection occurred April–August 2020 through trained ASHAs under researcher supervision. Sampling and participants: Targeted sexually active men aged 20–60 years who could read Kannada or English. Sample size of 385 was calculated via Cochran’s formula (p=0.5, d=5%, Z=1.96); 500 participants were recruited using a multi-step approach: (1) identify low- or no-cost cervical screening centers per district, (2) select two areas per district (one accessible and one less accessible) via judgmental sampling, (3) consecutively approach eligible participants in both areas. Measures: Structured questionnaire (54 items) with five sections: (1) sociodemographics and healthcare access/decision-making; (2) knowledge of cervical cancer (etiology, risk factors, warning signs) and screening (procedures, need for routine screening) via 8 items (score 0–16; KR-20=0.88); (3) modified TPB constructs: attitude toward screening (7 items, 5-point Likert, α=0.70), subjective norms (6 items, α=0.72), perceived structural barriers (5 items, α=0.83), and habit (dichotomous: routine health check-ups yes/no); (4) health literacy via HLS-IND-Q16 (Kannada/English) scored on a 5-point scale, transformed to an index 0–50 using HL=(Average−1)×(50/3), with >33 indicating adequate literacy; (5) intention to support wife’s screening (yes/no). Instrument development included translation to Kannada, expert review, and pretesting for cultural relevance and clarity. Analysis: SPSS v25 used for descriptive statistics (frequencies, means, SD). Bivariate analyses included chi-square tests for categorical predictors and independent t-tests for continuous variables comparing men with and without intention to support screening. Logistic regressions assessed predictors of intention and variance explained (Nagelkerke R²). Model 1 included knowledge and awareness; Model 2 added attitude, subjective norms, habit, and perceived structural barriers. Hosmer-Lemeshow tested model fit. Moderation by health literacy and education on the links between attitude/subjective norms and intention was tested using Hayes’ PROCESS macro with 5000 bootstrap samples.

- 68% of men reported a positive intention to support their partner’s cervical cancer screening. - Education: Men with at least secondary education were more likely to intend support (p<0.05). - Knowledge and awareness: 66% had never heard of cervical cancer; only 12% knew someone with cervical cancer. Just 7.8% recognized HPV/sexual transmission as the cause; 21% could not identify any risk factors. Over half (61%) did not know warning signs. The vast majority (95.4%) were unaware of screening procedures, and 82% did not know screening is needed irrespective of symptoms. - Health literacy: Mean HL=29.05 (<33 cutoff for adequate); 78.8% had limited HL. Those intending to support had higher HL (30.6) than those not intending (25.6). - Attitudes and norms: Many men reported negative attitudes; 46% were anxious about the procedure, 30.4% felt uncomfortable, 35.8% feared the outcome. Subjective norms were not significantly associated with intention. - Perceived structural barriers: Health system–related concerns were common (63%), followed by lack of time (27%), poor accessibility (20.6%), and cost (15.6%). - Bivariate findings: Positive intention associated with greater awareness of screening, more positive attitudes, fewer perceived structural barriers, and higher health literacy; norms were not related. - Multivariate models: Model 1 (knowledge + awareness) explained 3.9% of variance (Adj R²≈0.035). Model 2 (adding attitude, norms, habit, structural barriers) explained 19% (Adj R²≈0.179). Significant predictors in Model 2: attitude (OR=1.18, 95% CI 1.09–1.27) and habit of routine health checks (OR=3.04, 95% CI 1.98–4.65). Knowledge and awareness were marginal; subjective norms and structural barriers were not significant. Reduced model (awareness, attitudes, habits) had good fit and explained 16% of variance. - Moderation: Education significantly moderated the relationships of knowledge and awareness with attitude (knowledge×education: β=0.43, SE=0.17, p=0.0128; awareness×education: β=−1.77, SE=0.47, p<0.001), indicating higher education amplifies the effect of knowledge/awareness on positive attitudes. Health literacy did not significantly moderate these associations.

Findings indicate that beyond knowledge deficits, men’s attitudes toward screening and their habitual engagement in routine health checks are key drivers of their intention to support partners’ cervical screening. This aligns with modified TPB applications showing attitudes and habits as strong predictors of screening intentions. Although health literacy correlated positively with knowledge, awareness, and attitudes, it did not moderate associations; education did, strengthening how knowledge/awareness translate into positive attitudes. Subjective norms were not predictive in this context, potentially reflecting measurement differences or contextual factors. Structural/health system barriers were widely perceived, suggesting that even men inclined to support screening recognize systemic obstacles. Addressing attitudes, increasing knowledge and awareness, and reducing structural barriers are essential to enhance male support and, consequently, women’s screening uptake in India.

This study extends a modified TPB framework to men, showing that attitudes towards cervical screening and men's routine screening habits significantly shape their intention to support their wives’ participation. Given widespread low knowledge and limited health literacy, interventions should actively educate men on cervical cancer and screening procedures, foster positive attitudes, and reduce perceived and actual structural barriers. Implementing community-level screening and strengthening community health centers may improve access and engagement. Future research should measure actual supportive behaviors and screening outcomes, evaluate interventions targeting male engagement, and further examine interactions among socio-cognitive and structural factors.

- Self-reported survey data may be subject to social desirability and interviewer-related biases (data collected by health workers). - The outcome measured was intention, not actual supportive behavior; intention–behavior gaps may limit generalizability to real-world actions. - Potential interactions among variables exist; while modeled statistically, direct and indirect effects warrant further investigation (e.g., longitudinal or cohort designs within NPCDCS to assess behavior).