Skip to main content

Prediction of cervical cancer screening: application of the information-motivation-behavioral skills model

Abstract

Introduction

Screening is an effective method for preventing cervical cancer. The present study aimed to determine the predictability of cervical cancer screening using the information-motivation-behavioral skills (IMB) model, as this model can help understand the factors that influence health-related behaviors.

Method

The present cross-sectional study examined 310 women aged 20 to 60 in Isfahan, Iran, between 2020 and 2021. To this end, comprehensive health centers and gynecology clinics of hospitals were randomly selected by lot. Women who met the study’s inclusion criteria were selected via convenience sampling. An IMB skills questionnaire developed by researchers comprised the data collection tool. The data were analyzed using SPSS 22 software, descriptive and regression tests, and AMOS 24.0 software.

Findings

Approximately 18.1% of the participants had never undergone routine cervical cancer screening. The regression model results indicated that the model components accurately predicted regular cervical cancer screening (P < 0.00). Path analysis revealed that information (β = 0.05, P = 0.002), motivation (β = 0.187, P = 0.026), and behavioral skills (β = 0.95, P < 0.001) were directly associated with regular cervical cancer screening. Furthermore, behavioral skills had the greatest direct effect on regular cervical cancer screening.

Discussion and conclusion

The results demonstrated that the IMB model accurately predicted cervical cancer screening. Therefore, it is possible to improve cervical cancer screening in women by designing and implementing interventions based on this model’s components, particularly those that improve behavioral skills.

Peer Review reports

Introduction

Cervical cancer is the fourth most prevalent cancer in women worldwide [1] and the second most common cancer of the reproductive tract after ovarian cancer in Iran [2]. The incidence and mortality rates of cervical cancer are significantly higher in regions with a low or moderate Human Development Index (HDI). Meanwhile, between 84 and 90% of cancer deaths occur in low- and middle-income countries [3]. Advanced cervical cancer is one of the leading causes of death from this cancer [4], whereas this disease is curable if detected in its precancerous stage [5]. Early cancer detection through screening is an important factor in reducing cancer-related mortality. Screening is a cost-effective and potent method of preventing cervical cancer [6, 7], and this method has been recommended, particularly for countries with high morbidity and mortality rates [8]. The program for cervical cancer screening aims to conduct screening at appropriate and regular intervals [9]. According to studies, regular screening reduces the risk of dying from cervical cancer [10, 11]. Regular screening is recommended from the age of 21 to 65 for women who are sexually active [12]. According to Iran’s national guidelines, cervical cancer screening is performed in women aged 30 to 59 years, and if a person is under 30 or over 59 years of age, or in the intervals between regular examinations, there are suspicious symptoms of cervical cancer (abnormal bleeding, pain during sexual intercourse and foul-smelling discharge from the genital tract) should perform more complete evaluations to confirm or rule out cervical cancer [13]. The Healthy People 2020 program recommends that at least 93% of women undergo regular cervical cancer screening [14].

Despite the recommendation, only 60% of women in developed countries and 20% of women in developing countries undergo the Pap smear test, according to studies [8, 15]. Moreover, women are not routinely screened in certain countries [16]. Mohebi et al. [17] reported that only 11.25% of Iranian women routinely received a Pap smear.

In Iran, the cervical cancer prevention program is implemented on an opportunistic foundation [18]. The aim of the preformation of the cervical cancer prevention program is early diagnosis and screening of cervical cancer, identification of people suspected of or suffering from cervical cancer, and then the treatment and care of patients [13].

According to a systematic review, less than 45% of Iranian women had undergone a Pap smear test at least once. Approximately half of the Iranian women were aware of cervical cancer and the Pap smear test [19]. Izadi et al. [20] revealed that only 34% of women participated in cervical cancer screening.

Using behavior change patterns can be extremely beneficial in identifying and predicting cervical cancer screening factors. To this end, a theory that is effective in predicting behavior, mediating factors that affect behavior, and measures that result in behavioral change should be selected to examine health behaviors [21].

The information-motivation-behavioral skills (IMB) model is a method for understanding the social and psychological factors influencing health-related behavior. This model also determines and predicts health behavior changes [22]. Behavioral change requires specific information, motivation, and behavioral skills, according to the IMB model (Fig. 1).

Fig. 1
figure 1

Information, motivation and behavioral skills model

This model’s components are essential for predicting and promoting healthy behavior. The IMB model is designed in a simple way to comprehend and intended to meet the needs of the public to improve their health [23].

According to the IMB model, breast cancer screening adherence is contingent on the levels of information, motivation, and behavioral skills, and there is a correlation between having information about the age of initiation and time of screening repetition, risk factors, and symptoms of cancer, family members’ support, and behavioral skills with screening [24]. According to studies, cervical cancer screening is also associated with knowledge, awareness, the husband’s support and approval, recommendations from acquaintances, friends, and family, recommendations from doctors and health personnel, previous Pap smear results, and screening history [25,26,27,28,29,30].

Even though the IMB model has been examined in various health fields, including breast cancer screening, self-care of diabetes, prevention of sexually-transmitted diseases, condom use, HIV prevention, adherence to AIDS treatment, and tuberculosis infection control [21, 22, 24, 31,32,33,34,35,36,37,38,39,40], little is known about its use in cervical cancer screening [41]. In addition, despite the fact screening can prevent cervical cancer, some women do not undergo it regularly, and cervical cancer is still considered a global health concern, mainly in developing countries [10, 17, 42,43,44]. Therefore, the purpose of the present study was to determine whether the information-motivation-behavioral skills (IMB) model can predict cervical cancer screening.

Method

The current study employed a cross-sectional design and included 20-60-year-old women who visited health centers and gynecological clinics in Isfahan, Iran, between October 2020 and May 2021. The sample size was calculated using article related to analysis which is mentioned five or ten observations per estimated parameter [45]. The study enrolled a total of 310 women eligible for cervical cancer screening.

In the present study, comprehensive health centers and gynecological clinics of hospitals were randomly selected by lot. Six community health centers were selected randomly from all centers, and the Beheshti gynecological clinic was chosen randomly from two clinics of hospitals in Isfahan. Women who met the inclusion criteria were enrolled in the study using convenience sampling. The inclusion criteria included possessing an Iranian nationality, being married, aged between 20 and 60 years, and providing consent to participate in the study.

Women were recruited when they attended the centers and clinic. This was when they were approached by the researcher. Before they entered the research, the necessary information about the research was provided to them and informed consent was obtained from them. The participants were assured that their names will remain anonymous.

Measures

The first questionnaire included demographic information (age, education level, occupation, and income) and details about the Pap smear test. So that a single question was used to evaluate cervical cancer screening (do you regularly receive a pap smear?). The question was scored using a Likert scale (1: never, 2: rarely, 3: occasionally, 4: always). Furthermore, three questionnaires including cervical cancer screening information questionnaire, cervical cancer screening motivation questionnaire and cervical cancer screening behavioral skills questionnaire were used.

Cervical cancer screening information questionnaire

This questionnaire was developed by the researchers and contained 17 questions regarding cervical cancer risk factors, cervical cancer symptoms, cervical cancer prevention, screening initiation and termination time, Pap smear test location, and Pap smear test results. The questions were formulated where respondents could choose between “correct,” “incorrect,” and “I don’t know.’

Cervical cancer screening motivation questionnaire

This questionnaire was developed by the researchers and consisted of three questions regarding personal motivation (Easy to perform pap smear, the importance of health and increasing survival) and three on social motivation (Recommendation to perform pap smear by husband, family and health care providers) to undergo the Pap smear test. The questions were scored using a 5-point Likert scale (1: strongly disagree to 5: strongly agree).

Cervical cancer screening behavioral skills questionnaire

This questionnaire was developed by the researchers and included four questions regarding behavioral skills for Pap smear (planning and time management, overcoming fear, spending money, and visiting service centers). The questions were scored using a 5-point Likert scale (1: strongly disagree to 5: strongly agree).

Validity and reliability of the tool

The questionnaires were distributed to 13 faculty members from the Department of Midwifery and Reproductive Health and Health Education and Promotion to assess the qualitative content’s validity. To this end, expert feedback was gained on the content, grammar, and appropriate expressions. Two methods were used to examine the content validity: the content validity ratio (CVR) and the content validity index (CVI). CVR was calculated based on the content validity ratio formula as fallows.

$$\left(\mathrm{Ne}-\mathrm N/2\right)/\left(\mathrm N/2\right),\;\mathrm{Ne}\:=\:\mathrm{number}\;\mathrm{of}\;\mathrm{essentials}\;\mathrm{for}\;\mathrm{an}\;\mathrm{item}\;\mathrm{and}\;\mathrm N=\mathrm{number}\;\mathrm{of}\;\mathrm{experts}$$

To calculate CVR, 13 experts were asked to rate the necessity of each item on a 3-point Likert scale ranging from “necessary” to “not necessary”. Given the presence of 13 experts, the CVR approval criterion was set at 0.54 for each question [46].

To examine CVI, experts’ opinions on each item’s relevance, clarity, and simplicity were calculated using a 4-point Likert scale. A question would be eliminated if its CVI was less than 0.7 [47]. Of these, totally nine items were excluded after assessment (one item from the motivation, two items from the behavioral skills and six items from the information).

Determining content validity led to the information questionnaire with 17 questions, the motivation questionnaire with 6 questions, and the behavioral skills questionnaire with 4 questions.

The reliability of the questionnaires was confirmed by calculating Cronbach’s alpha coefficients for several subjects (information [0.750], motivation [0.702], and behavioral skills [0.871]). The whole questionnaires obtained an acceptable score.

Statistical analysis

The descriptive statistical test (frequency distribution and percentage) and multinomial logistic regression tests were conducted using SPSS 22 software. Multinomial logistic regression was used to examine the correlation between the components of the IMB model with cervical cancer screening. In the analysis, “never” was used as a reference for rarely, occasionally, and always.

AMOS 24.0 was utilized for path analysis. Maximum likelihood estimation was employed as the parameter estimation method. In addition, chi-square and comparative indices NFI, RFI, IFI, TLI, and CFI were utilized to assess the model’s fitness. The variables were comprised of four categories, which were consisted of never, rarely, occasionally and always.

Findings

According to the findings, the majority of the research subjects (39.7%) were between the ages of 31 and 40, were homemakers (82.3%), held a high school diploma (34.5%), and had moderate income levels (64.8%) (Table 1).

Table 1 Demographic information of the subjects in the study

Approximately 18.1% of the participants had never undergone routine cervical cancer screening. In addition, 24.2%, 25.5%, and 32.3% of participants reported undergoing cervical cancer screening rarely, occasionally, and frequently, respectively. The multinomial logistic regression analysis results indicated that the components of the model sufficiently predicted cervical cancer screening (P < 0.001) (Table 2).

Table 2 Multinomial logistic regression analysis IMB model with cervical cancer screening

Path analysis indicated that the model had an acceptable fit (CMIN = 6.89, df = 2, P = 0.032) (RFI = 0.926, IFI = 0.990, TLI = 0.949, CFI = 0.990, NFI = 0.986). The results indicated that information (β = 0.05, P = 0.002), motivation (β = 0.187, P = 0.026), and behavioral skills (β = 0.95, P < 0.001) has a direct effect on regular cervical cancer screening (Table 3). Furthermore, information (β = 0.137, P = 0.024) and motivation (β = 2.062, P < 0.001) had a direct effect on behavioral skills. Among the factors of information, motivation, and behavioral skills, behavioral skills had the most significant direct effect on regular cervical cancer screening (Fig. 2; Table 3).

Table 3 Path coefficients and the variance in IMB constructs explained
Fig. 2
figure 2

Prediction cervical cancer screening based on IMB model amos software. Chi-square = 6.89. Degrees of freedom = 2. Probability level = .032. *P<0/05. ***. P<0/001

Discussion

The current study sought to investigate the prediction of cervical cancer screening using the IMB model. According to the findings, the IMB model could predict cervical cancer screening in women. In the current study, the components of the IMB model predicted regular cervical cancer screening. To this end, a regular cervical cancer screening was found to correlate significantly with information, motivation, and behavioral skills.

According to studies, there are relationships between cancer screening information and motivation for women [48, 49]. Vinarti et al. [50] reported that motivation was related to cervical cancer screening. Suls et al. claimed that information determined health behavior and influenced the performance of preventive behavior. Consequently, information alone may serve as a predictor of behavior [23].

In addition, motivation is a factor that can influence the promotion of health-related behaviors. It includes personal motivation, which includes belief and attitude toward a particular health behavior, and social motivation, which includes perceived social support or social norms for engaging in the behavior [51]. People typically seek health improvement and information acquisition due to personal and social motivations [23].

Gu et al. [52] regarded previous screening experience and beliefs about cervical cancer screening as crucial factors in fostering future motivation for screening. Kalichman et al. [37] also reported a significant association between motivation and AIDS prevention behaviors. These findings were consistent with those of the present study. Moreover, increasing knowledge increased their motivation to undergo cervical cancer screening [41]. The results of the current study indicated a correlation between information and motivation regarding cervical cancer screening. According to Gao et al., motivation and information may have reciprocal effects on diabetes self-care [35].

Individuals with more information are more motivated to engage in healthy behaviors. In addition, those with greater motivation seek to expand their information on health-related behaviors [24]. In several studies, researchers have reported that individuals must possess the requisite behavioral skills to change their health-centered behaviors [22, 24, 33]. In the present study, behavioral skills had the greatest direct influence on regular Pap smear testing.

Behavioral skills are required for engaging in particular health behavior. Increasing behavioral skills adjusts the behavior of individuals and improves their health. In the IMB model, these skills emphasize increased objective skills and perceived self-efficacy to perform health behaviors [51]. According to several studies, information and motivation affect the performance of certain health behaviors by fostering behavioral skills [21, 36, 41]. Misevich et al. [24] found a correlation between information and motivation and the behavioral skills required to perform monthly breast examinations. Mayberry et al. [34] also reported that information and motivation were associated with diabetes treatment adherence behavioral skills. These findings were consistent with those of the present study. This model indicates that changes in behavior largely result from changes in behavioral skills, primarily the result of changes in information and motivation [36].

Notably, the IMB model does not account for all determinants of health behavior performance, including mental health, access to medical services, medical history, norms, and cultural factors [24, 53]. Based on the results of the present study, this model can provide a comprehensive framework for predicting cervical cancer screening in women.

To the best of the authors’ knowledge, the present study was the first to be conducted based on the IMB model, which examined the roles of information, motivation, and behavioral skills in cervical cancer screening. Despite research on the roles of information and motivation variables in cervical cancer screening [48, 49], no research has been conducted on the roles of behavioral skills as direct and mediating variables in cervical cancer screening.

Even though the results of this study supported the use of the IMB model for predicting cervical cancer screening, it was not possible to investigate other causal relationships influencing cervical cancer screening in this study.

There is another issue that should be mentioned. The term virginity as the absence of sex before marriage is considered as a value in some societies [54]. Due to the prevailing culture of the society, only married women were included in the study. It is one of the limitations of present study which may affect the generalizability of the results. Another limitation related to self-reported Pap smear examinations in women.

Conclusion

According to the findings of this study, the IMB model provided an appropriate framework for predicting cervical cancer screening. Information and motivation were associated with behavioral skills in cervical cancer screening, and behavioral skills were the most significant predictors of screening. Consequently, it is possible to improve cervical cancer screening in women by designing and implementing necessary interventions based on this model, particularly by improving behavioral skills.

Availability of data and materials

The datasets generated during the current study are available from the corresponding author on reasonable request.

Abbreviations

IMB:

Information–motivation–behavioral skills model

CVI:

Content validity index

CVR:

Content validity ratio

CMIN:

χ2

RFI:

Relative fit index

IFI:

Incremental fit index

TLI:

Tucker-Lewis index

CFI:

Confirmatory factor analytic

NFI:

Normed fit index

DF:

Degree of freedom

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2021;71(3):209–49.

    Article  Google Scholar 

  2. Zendehdel K. Cancer statistics in IR Iran in 2018. Basic and Clinical. Can Res. 2019;12(4):159–65.

    Google Scholar 

  3. Hull R, Mbele M, Makhafola T, Hicks C, Wang SM, Reis RM, et al. Cervical cancer in low and middle–income countries. Oncol Lett. 2020;20(3):2058–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Kantelhardt EJ, Moelle U, Begoihn M, Addissie A, Trocchi P, Yonas B, et al. Cervical cancer in Ethiopia: survival of 1,059 patients who received oncologic therapy. Oncologist. 2014;19(7):727–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Alfaro K, Soler M, Maza M, Flores M, López L, Rauda JC, et al. Cervical Cancer Prevention in El Salvador: gains to date and challenges for the future. Cancers. 2022;14(11):2776.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Chen C-P, Kung P-T, Wang Y-H, Tsai W-C. Effect of time interval from diagnosis to treatment for cervical cancer on survival: a nationwide cohort study. PLoS One. 2019;14(9):e0221946.

  7. Sankaranarayanan R, Budukh AM, Rajkumar R. Effective screening programmes for cervical cancer in low-and middle-income developing countries. Bull World Health Organ. 2001;79:954–62.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Brisson M, Kim JJ, Canfell K, Drolet M, Gingras G, Burger EA, et al. Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet. 2020;395(10224):575–90.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wong FL, Miller JW. Centers for disease control and prevention’s national breast and cervical cancer early detection program: increasing access to screening. J Womens Health. 2019;28(4):427–31.

    Article  Google Scholar 

  10. Grangé G, Malvy D, Lançon F, Gaudin A-F, El Hasnaoui A. Factors associated with regular cervical cancer screening. Int J Gynecol Obstet. 2008;102(1):28–33.

    Article  Google Scholar 

  11. Mubiayi N, Bogaert E, Boman F, Leblanc E, Vinatier D, Leroy J, et al. Histoire Du suivi cytologique de 148 femmes atteintes d’un cancer invasif du col utérin. Gynécol Obstét Fertil. 2002;30(3):210–7.

    Article  CAS  PubMed  Google Scholar 

  12. DiSaia PJ, Creasman WT, Mannell RS, McMeekin S, Mutch DG. Clinical gynecologic oncology e-book: Elsevier Health Sciences; 2017.

  13. Koosha A, Maleki A, Najmi M, Dini M, Arjomandpour M. Collection of Basic interventions for non-communicable diseases in. In: the Primary Health Care System of Iran, editor. Executive instructions and educational content of midwives. Tehran: Office of Non-Communicable Diseases ManagementMinistry of Health; 2016.

    Google Scholar 

  14. Brown ML, Klabunde CN, Cronin KA, White MC, Richardson LC, McNeel TS. Challenges in meeting Healthy People 2020 objectives for cancer-related preventive services, National Health Interview Survey, 2008 and 2010. Prev Chronic Dis. 2014;11:E29.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gakidou E, Nordhagen S, Obermeyer Z. Coverage of cervical cancer screening in 57 countries: low average levels and large inequalities. PLoS Med. 2008;5(6): e132.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Refaei M, Nayeri ND, Khakbazan Z, Yazdkhasti M, Shayan A. Exploring effective contextual factors for regular cervical cancer screening in Iranian women: a qualitative study. Asian Pac J Cancer Prev. 2018;19(2):533.

    PubMed  PubMed Central  Google Scholar 

  17. Mohebi S, Sharifirad G, Gharlipour Z, Kamran A. The study of pap smear conduction and its related factors based on health belief model in women referring to health care centers in Qom during 2014. J Educ Community Health. 2016;2(4):25–33.

    Article  Google Scholar 

  18. Amin R, Kolahi A-A, Jahanmehr N, Abadi A-R, Sohrabi M-R. Disparities in cervical cancer screening participation in Iran: a cross-sectional analysis of the 2016 nationwide STEPS survey. BMC Public Health. 2020;20(1):1–8.

    Article  Google Scholar 

  19. Majidi A, Majidi S, Salimzadeh S, Khazaee-Pool M, Sadjadi A, Salimzadeh H, et al. Cancer screening awareness and practice in a middle income country; a systematic review from Iran. Asian Pac J cancer Prevention: APJCP. 2017;18(12):3187.

    Google Scholar 

  20. Izadi S, Shakerian S. Performance Indicators of Cervical Cancer Screening Program Based on The Guidelines of Iran Ministry of Health and Medical Education. Int J Cancer Manag. 2021;14(2):e102030.

  21. Nelson LA, Wallston KA, Kripalani S, LeStourgeon LM, Williamson SE, Mayberry LS. Assessing barriers to diabetes medication adherence using the information-motivation-behavioral skills model. Diabetes Res Clin Pract. 2018;142:374–84.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Talley CH, Yang L, Williams KP. Breast cancer screening paved with good intentions: application of the information–motivation–behavioral skills model to racial/ethnic minority women. J Immigr Minor Health. 2017;19(6):1362–71.

    Article  PubMed  Google Scholar 

  23. Suls J, Wallston KA. Social psychological foundations of health and illness. John Wiley & Sons; 2008.

  24. Misovich SJ, Martinez T, Fisher JD, Bryan A, Catapano N. Predicting breast Self-Examination: a test of the information‐motivation‐behavioral skills model 1. J Appl Soc Psychol. 2003;33(4):775–90.

    Article  Google Scholar 

  25. Agurto I, Bishop A, Sanchez G, Betancourt Z, Robles S. Perceived barriers and benefits to cervical cancer screening in Latin America. Prev Med. 2004;39(1):91–8.

    Article  CAS  PubMed  Google Scholar 

  26. Christie-de Jong F. Knowledge, practice and barriers concerning cervical cancer screening among female overseas Filipino workers: a web-based mixed methods approach. United Kingdom: Lancaster University; 2017.

    Google Scholar 

  27. de Peralta AM. Health beliefs and socio-cultural factors that predict cervical cancer screening behaviors among hispanic women in seven cities in the Upstate of. South Carolina: Clemson University; 2011.

    Google Scholar 

  28. Dodo A. Sociocultural Barriers to Breast and Cervical Cancer Screening Among Women in Kaduna, Northern Nigeria. 2018.

  29. Hatefnia E, Ghazivakili Z. Identify some of effective factors that predict self-care behavior in pap smear based on Womenś Health beliefs in City Karaj. Alborz Univ Med J. 2015;4(4):223–30.

    Article  Google Scholar 

  30. Lee F-H, Wang H-H, Yang Y-M, Huang J-J, Tsai H-M. Influencing factors of intention to receive pap tests in Vietnamese women who immigrated to Taiwan for marriage. Asian Nurs Res. 2016;10(3):189–94.

    Article  Google Scholar 

  31. Ndebele M, Kasese-Hara M, Greyling M. Application of the information, motivation and behavioural skills model for targeting HIV risk behaviour amongst adolescent learners in South Africa. SAHARA-J: J Social Aspects HIV/AIDS. 2012;9:37–47.

    Article  Google Scholar 

  32. Kanjee Z, Amico K, Li F, Mbolekwa K, Moll A, Friedland G. Tuberculosis infection control in a high drug-resistance setting in rural South Africa: information, motivation, and behavioral skills. J Infect Public Health. 2012;5(1):67–81.

    Article  CAS  PubMed  Google Scholar 

  33. Starace F, Massa A, Amico KR, Fisher JD. Adherence to antiretroviral therapy: an empirical test of the information-motivation-behavioral skills model. Health Psychol. 2006;25(2): 153.

    Article  PubMed  Google Scholar 

  34. Mayberry LS, Osborn CY. Empirical validation of the information–motivation–behavioral skills model of diabetes medication adherence: a framework for intervention. Diabetes Care. 2014;37(5):1246–53.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Gao J, Wang J, Zhu Y, Yu J. Validation of an information–motivation–behavioral skills model of self-care among Chinese adults with type 2 diabetes. BMC Public Health. 2013;13(1):1–6.

    Article  CAS  Google Scholar 

  36. Anderson ES, Wagstaff DA, Heckman TG, Winett RA, Roffman RA, Solomon LJ, et al. Information-motivation-behavioral skills (IMB) model: testing direct and mediated treatment effects on condom use among women in low-income housing. Ann Behav Med. 2006;31(1):70–9.

    Article  PubMed  Google Scholar 

  37. Kalichman SC, Picciano JF, Roffman RA. Motivation to reduce HIV risk behaviors in the context of the information, motivation and behavioral skills (IMB) model of HIV prevention. J Health Psychol. 2008;13(5):680–9.

    Article  PubMed  Google Scholar 

  38. DeBate RD, Gatto A, Rafal G. The effects of stigma on determinants of mental health help-seeking behaviors among male college students: an application of the information-motivation-behavioral skills model. Am J Men’s Health. 2018;12(5):1286–96.

    Article  Google Scholar 

  39. Osborn CY, Egede LE. Validation of an information–motivation–behavioral skills model of diabetes self-care (IMB-DSC). Patient Educ Couns. 2010;79(1):49–54.

    Article  PubMed  Google Scholar 

  40. Dubov A, Altice FL, Fraenkel L. An information–motivation–behavioral skills model of PrEP uptake. AIDS Behav. 2018;22(11):3603–16.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Wells A, Allen-Brown V, Alam N, Skulski C, Jackson AL, Herzog TJ. The importance of information, motivation, and behavioral skills (IMB): Healthcare provider perspectives on improving adherence to cervical cancer screening among at-risk women. Public Health Pract. 2021;2:100079.

    Article  Google Scholar 

  42. Canfell K, Kim JJ, Brisson M, Keane A, Simms KT, Caruana M, et al. Mortality impact of achieving WHO cervical cancer elimination targets: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet. 2020;395(10224):591–603.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Ifediora CO. Re-thinking breast and cervical cancer preventive campaigns in developing countries: the case for interventions at high schools. BMC Public Health. 2019;19(1):503.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Mosayebi M, Tavakoli-Fard N. Evaluation of pap smear screening history in patients with cervical cancer in Isfahan province during 2014–2016. Medicinski časopis. 2018;52(4):134–9.

    Article  Google Scholar 

  45. Bentler PM, Chou CP. Practical issues in structural modeling. Sociol Methods Res. 1987;16(1):78–117.

    Article  Google Scholar 

  46. Lawshe CH. A quantitative approach to content validity. Pers Psychol. 1975;28(4):563–75.

    Article  Google Scholar 

  47. Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459–67.

    Article  PubMed  Google Scholar 

  48. Parrott NE. Self-efficacy and rural women’s performance of breast and cervical cancer detection practices. J Health Communication. 2001;6(3):219–33.

    Article  PubMed  Google Scholar 

  49. Ghalavandi S, Heidarnia A, Zarei F, Beiranvand R. Knowledge, attitude, practice, and self-efficacy of women regarding cervical cancer screening. Obstet Gynecol Sci. 2021;64(2):216–25.

    Article  PubMed  Google Scholar 

  50. Winarti E, Santoso B, Suhatno S, Hargono R. Trigger, Self efficacy and motivation in the implementation of cervical cancer screening. Health Notions. 2018;2(4):494–9.

    Google Scholar 

  51. Chang SJ, Choi S, Kim S-A, Song M. Intervention strategies based on information-motivation-behavioral skills model for health behavior change: a systematic review. Asian Nurs Res. 2014;8(3):172–81.

    Article  Google Scholar 

  52. Gu C, Chan CW, He G-P, Choi K, Yang S-B. Chinese women’s motivation to receive future screening: the role of social-demographic factors, knowledge and risk perception of cervical cancer. Eur J Oncol Nurs. 2013;17(2):154–61.

    Article  PubMed  Google Scholar 

  53. Fisher JD, Fisher WA, Amico KR, Harman JJ. An information-motivation-behavioral skills model of adherence to antiretroviral therapy. Health Psychol. 2006;25(4): 462.

    Article  PubMed  Google Scholar 

  54. Mehrolhassani MH, Yazdi-Feyzabadi V, Mirzaei S, Zolala F, Haghdoost A-A, Oroomiei N. The concept of virginity from the perspective of Iranian adolescents: a qualitative study. BMC Public Health. 2020;20(1):717.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the contribution of all the women and other participations will involve in the study.

Funding

This research was funded by the Isfahan University of Medical Sciences, Isfahan, Iran (Grant no: 55059). The funder had no direct role in study design, data collection, analysis, and writing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

MSE, MGh, MN and MS were involved in the study design. MGh and MSE will collect data and analyze the data for the study purpose. MSE, MGh, MN and MS contributed to drafting and revising the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mitra Savabi-Esfahani.

Ethics declarations

Ethics approval and consent to participate

The present study was approved by the Ethics Committee of Isfahan University of Medical Sciences (IR.MUI.NUREMA.REC.1400.063). Subjects provided written informed consent to participate in the study. Participants were instructed not to disclose their identities on the questionnaires, and all information was kept confidential. Participation in the research had no financial burden on the subjects, and they were free to withdraw at any time. If the participant was illiterate, a literate witness was selected. The literate witness, who had no conflict of interest, provided sufficient information to the participants and answered their questions. Informed consent was obtained from the literate witness. Therefore, the informed consent form was included the participant’s signature or fingerprint, the researcher’s signature, and the signature of a literate witness. All methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghasemi, M., Savabi-Esfahani, M., Noroozi, M. et al. Prediction of cervical cancer screening: application of the information-motivation-behavioral skills model. BMC Cancer 24, 351 (2024). https://doi.org/10.1186/s12885-024-12098-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12885-024-12098-9

Keywords