Predictive power of PEN-3 cultural model in cervical cancer screening among women: a cross- sectional study in South of Iran

Abstract

Background Cervical cancer (CC) can be prevented through early detection facilitated by screening as well as an early diagnosis and effective treatment of the precancerous lesions. The present research aimed to determine the predictors of cervical cancer screening (CCS) based on the PEN-3 model constructs. Methods A cross-sectional study was conducted between September 2021- March 2022 with 840 women aged 15–49 in the city of Bandar Abbas, in the south of Iran, using a cluster sampling. The participants completed a valid and reliable self-administered questionnaire in person. The questionnaire included demographic characteristics, knowledge toward CC and the constructs of the PEN-3 model toward CCS. A multivariable logistic regression was used to determine the relationship and predictive power of model constructs with behavior as an outcome variable. The data were statistically analyzed in STATA14.2. The p-value < 0.05 was considered statistically significant. Results A total of 810 questionnaires were analyzed (with a return of 95.63%). The mean and standard deviation of the participants’ age was 30.97 ± 5.80 years. Pearson correlation coefficient analysis of all constructs and CCS behavior was statistically significant (P-value < 0.05). The multivariable logistic regression analytic results were enablers toward CCS (coefficient: 0.275) and Nurturers toward CCS (coefficient: 0.182), perceptions toward CCS (coefficient: 0.077) and knowledge toward CC (coefficient: 0.048, marginal significant) were predictors of CCS behavior. For the internal validity of the designed prediction model, a sample of 1000 was selected using the bootstrap sample replacement method which demonstrated the accuracy of the model PEN-3 is about 75% in predicting CCS behavior. Conclusions The results of the present research showed that personal factors such as perceptions and interpersonal factors such as enablers and nurturers toward CCS can predict CCS behavior. Therefore, in order to increase the acceptance of CCS in women, a set of intrapersonal and interpersonal factors should be taken into account.

Data mining for predictive analysis in gynecology: a focus on cervical health

“…To be more specific, Malawi has a mortality rate of 51,5/100,000, with an age-specific mortality rate [3]. Additionally, other results show that each year, 528,000 cases of uterine cancer in women are diagnosed globally, with 200,000 cases of them dying from the disease [4]. The cells of the cuello uterino, the lower portion connecting the uterus with the vagina, are where the cuello uterine cancer (CC) kind of cancer develops.…”