thesis on health belief model

• Open access
• Published: 18 December 2021

The role of health beliefs and health literacy in women's health promoting behaviours based on the health belief model: a descriptive study

• Mahla Ghorbani-Dehbalaei   ORCID: orcid.org/0000-0002-1457-887X 1 ,
• Marzeyeh Loripoor   ORCID: orcid.org/0000-0002-5063-4357 2 &
• Mostafa Nasirzadeh   ORCID: orcid.org/0000-0003-0934-4697 3  

BMC Women's Health volume  21 , Article number:  421 ( 2021 ) Cite this article

10k Accesses

5 Citations

3 Altmetric

Metrics details

Health literacy and health beliefs are factors that can effectively contribute to adoption of preventive behaviors among women. The present study was done to explore the role of health beliefs and health literacy in women's health promoting behaviors based on the health belief model (HBM).

The descriptive study was conducted in 2020 on 431 female students of Rafsanjan University of Medical Sciences (RUMS) who had been selected through stratified sampling. Data collection tool was a questionnaire which covered eight demographic information, 41 health literacy questions and 50 researcher-developed questions of health belief based on HBM constructs. Data were collected electronically and SPSS version 20 and independent t -test, one-way ANOVA, Pearson correlation coefficient and Multiple Linear Regression were used for data analysis at a significance level less than 0.05.

The preventive behaviors were adopted by 75.57% of the population and the total health literacy score was found to be 52.71 out of 100. According to the Multiple regression analysis, self-efficacy (β = 0.414, p  = 0.001) and cues to action (β = 0.299, p  = 0.001) were found to be the first and second robust predictors of behavior, respectively. Health literacy, self-efficacy, cues to action and perceived susceptibility constructs predicted 52.1% of preventive behaviors.

It is recommended that researchers design, implement and evaluate interventions based on behavioral change theories, especially the self-efficacy theory, in order to promote women's health.

Peer Review reports

Given the biological, cultural, social, economic, and political factors, women are more vulnerable than men, and they are more exposed to health risks than men due to physical, sexual, and mental differences [ 1 , 2 ]. Fertility and childbirth, as well as menstruation expose women to specific health risks including menstrual cramps, iron deficiency anemia, genital infections, sexually-transmitted diseases, preterm labor, cervical cancer, breast cancer and female mortality at young ages [ 2 ].

Anemia is the most common nutritional disorder in the world, as many as 12.2% of adolescent girls, 3.8% of young adult women in the world, and 17% of Iranian women suffer from iron deficiency anemia [ 3 , 4 ]. Breast cancer is also the most common cancer among women; it accounts for 30% of all cancers in women, and it is the main cause of 15% of cancer-related deaths in women [ 5 ]. The incidence rate of breast cancer in Iranian women is 5.27 per 100,000 women [ 5 ]. Menstrual health as another important issue for women's health is an integral part of overall health, nevertheless, millions of women around the world, menstruation regularly and increasingly disrupts their physical, mental, and social well-being [ 6 ].

The results of a study conducted by Saadatmand et al. among the students of Islamic Azad University of Qom indicated that only 7.3% had desirable and good menstrual health behaviors [ 7 ].

Health literacy (H.L), as a term first introduced in the 1970s, [ 8 ] generally concerns whether an individual is competent with the complex demands of promoting and maintaining health in the modern society [ 9 ].

H.L is an important element in a woman’s ability to engage in health-promoting activities [ 10 ]. Without a good understanding of health care information, informed decisions leading to desirable health results will be difficult for a woman [ 11 ]. In their review study, Mousavi and Bagherian Sararoudi (2019) confirmed that H.L can be effective in preventing breast cancer and managing the symptoms arising from this disease [ 12 ].

Nutrition and Physical activity are the most important part of a healthy lifestyle in women that directly affects their health problems [ 13 ]. Adopting a low-fat diet, along with increasing the consumption of vegetables, fruits and whole grains, can reduce the risk of death from breast cancer in women [ 14 ]. Improper diet and nutrition patterns among young people can trigger various diseases at later ages [ 15 ]. Researchers argue that several factors are likely to affect the nutritional status of young people; these factors include gender, body weight, length of college years, avoiding certain types of valuable foods, and nutritional patterns formed before entering university [ 15 ]. Different studies have indicated that the consumption of essential nutrients such as iron, zinc, magnesium, calcium and folic acid among college students, especially female students, is less than what is recommended [ 16 ].

Moreover, numerous studies have also confirmed the benefits of regular physical activity as another important factor affecting health, since a sedentary lifestyle is associated with the risk of many chronic diseases; every year, about two million deaths are reported worldwide due to adopting a sedentary lifestyle [ 17 ]. Different studies have reported that awareness, perceived severity, and self-efficacy are the main variables predicting women’s physical activity [ 18 , 19 ].

Behavior change theories and models provide a systematic view of events or successes, and they are assumed as a regular process for analyzing successes or failures, as a training process map, they provide the required guidelines for educational diagnosis and planning, and intervention design, and they facilitate evaluation as well [ 20 , 21 ].

The Health Belief Model (HBM) developed in the 1950s by Godfrey Hochbaum, Irwin Rosenstock, and Rosenstock and Kirscht. The model constructs are perceived susceptibility and severity of diseases, perceived benefits of preventive behavior, perceived barriers to preventive behavior, cause to action and self-efficacy for doing preventive behavior. The definition of model constructs is as follows: "perceived susceptibility; beliefs about the likelihood of getting a disease or condition. Perceived severity; beliefs about the seriousness of contracting a diseases or condition, including consequences. Perceived benefits; beliefs about the positive aspects of adopting a health behavior (e.g., efficacy of the behavior for reducing risk or serious consequences). Perceived barriers; beliefs about the obstacles to performing a behavior, and the negative aspects (both tangible and psychological costs) of adopting a health behavior. Cues to action; internal and external factors that could trigger the health behavior. Self-efficacy; beliefs that one can perform the recommended health behavior" [ 21 ] (Fig.  1 ).

Components of the health belief model [ 21 ]

In their study, Khalilipour Darestani and Panahi reported that beliefs and perceptions of the adolescent's female about Premenstrual Syndrome (susceptibility, severity, benefits, barriers and perceived self-efficacy) in Tehran were moderate and lower than normal [ 22 ].

Given the role and importance of adolescent and young girls in society, the present study has been conducted to evaluate the role of health literacy and health beliefs in student's health promoting behaviors based on the Health Belief Model.

Study design and participants

The descriptive study has been conducted on 431 female students of Rafsanjan University of Medical Sciences selected by stratified sampling method in 2020. After determining the sample size by considering a 20% attrition using the formula n = Z 2 *P (1-P)/d 2 [Z value is equal to 1.96 and P value is based on the study conducted by Saeedi Mottaghi and Koopaei [ 2 ] and is equal to 42% for optimal H.L, and the d value is equal to 0.05], the number of female students in each faculty was determined, and in proportion to their number, the required sample size was determined for each faculty. Then, by referring to the Education Department of each faculty, the link of the questionnaire created on Porsline was sent to as many female students as required. The data collection method was electronic by applying Porsline system.

Data collection tools

Data collection tools included a questionnaire including an assessment of demographic information [age, academic year (being a freshman, sophomore, junior, and senior student), and level of education, being a local student, parents' educational level and occupation].

Health Literacy assessment questionnaire has been taken from the study conducted by Saeedi Kopaei and Mottaghi with 41 questions in five dimensions included menstrual, nutritional, physical activity, breast self-examination and anemia [ 2 ]. The dimensions of the questionnaire, the range of scores, validity and reliability and other features of this tool with the questions are provided in the Additional file 1 .

In the third part, it was attempted to assess the students’ beliefs based on the constructs of the health belief model. This researcher-made questionnaire with 50 questions was designed based on the constructs of the health belief model. Perceived susceptibility and severity about anemia, breast cancer and genital infections and menstrual disorders, perceived benefits aimed at understanding the impact and benefits of exercise and healthy diet in reducing anemia, breast cancer and menstrual disorders, perceived barriers for students to exercise, follow a healthy diet, and engage in menstrual and personal hygiene behaviors, self-efficacy and confidence to perform the mentioned activities, cues to action the concept of students' understanding of the internal and external stimuli that motivate preventive behaviors. Full details of this section with questions are provided in the Additional file 1 .

In this study, preventive behaviors of anemia, breast cancer, genital infections and menstrual disorders were evaluated with 9 questions such as regular exercise, healthy diet and personal hygiene and menstruation. Profile of the questions of this section is provided in the Additional file 1 .

Analysis of statistical data

The data were collected and analyzed by using SPSS V-20. Independent t -test to compare the mean score of a quantitative variable in two groups, one-way ANOVA to compare the mean score of a quantitative variable in several groups, Pearson correlation to determine the correlation between quantitative variables, and Multiple Linear Regression to determine the most important dependent variable predictors have been analyzed at the significance level less than of 0.05.

Description of participants

The mean age of students was 23.50 ± 5.63 years ranging from 18 to 41 years. Around 61% of the students were undergraduate students. As many as 50% were freshmen and senior students, and 54% were non-local students. Moreover, about 70% of the students’ parents had a high school diploma or higher. As many as 50% of the students’ fathers were self-employed, and 31% of the students’ mothers were employed.

Relationship between demographic characteristics and behavior

There was a direct and significant correlation between mean score and standard deviation (M ± SD) of behavior and age (r = 0.09, p  = 0.042). However, one-way ANOVA test did not show a significant difference between the M ± SD of preventive behaviors and the students’ academic year (F = 0.71, p  = 0.64).

One-way ANOVA and independent t -test did not show a significant difference between M ± SD of preventive behaviors in terms of different variables including father’s educational level ( p  = 0.19), mother’s educational level ( p  = 0.22), mother’s occupation ( p  = 0.91), and students’ being local ( p  = 0.10). Students whose father’s job was a “clerk” had the highest score of preventive behaviors (34.59 out of 100), and students whose fathers were “unemployed” had the lowest mean score of preventive behaviors (29.63 out of 100).

One-way ANOVA indicated that there is a significant difference between the M ± SD of preventive behavior based on the occupational status of the students’ fathers ( p  = 0.002). Post-hoc LSD indicated a significant difference between the M ± SD of a student’s preventive behaviors and his/her father’s job; construction worker vs. clerk ( p  = 0.037), clerk vs. unemployed ( p  = 0.001), construction worker vs. self-employed ( p  = 0.039), retired vs. unemployed ( p  = 0.001), unemployed vs. farmer ( p  = 0.032), and unemployed vs self-employed ( p  = 0.001) (Table 1 ).

Moreover, there was a significant difference between the M ± SD of students’ preventive behaviors in different academic levels (bachelor/master/Ph.D.) ( p  = 0.048). By conducting post-hoc LSD test, a significant difference was observed between the mean scores of preventive behaviors of master’s degree students and students of medicine and specialty ( p  = 0.008) (Table 1 ).

Mean score and standard deviation of health literacy, students' beliefs and behavior

Figure  2 shows the M ± SD of H.L and its dimensions i.e. students’ beliefs and preventive behaviors (Fig.  2 ). According to the graph, as many as 75.57% of students had adopted preventive health behaviors, and the total H.L score was 52.71 out of 100. The lowest percentage of H.L is related to Physical activity equal to 40.11%, and the highest percentage is related to menstruation being 77.54%. Moreover, the students’ highest score of beliefs was related to self-efficacy construct being 77.37%.

The scores of behavior, health literacy, and beliefs of female medical students about common diseases

Correlation between preventive behaviors with health literacy and students' beliefs

Table 2 shows the correlation between M ± SD of preventive behaviors with M ± SD of health beliefs and H.L and its dimensions (Table 2 ). The highest correlation was observed between behavior and total H.L (r = 0.414, p  = 0.001), and as for the beliefs, the highest correlation was with self-efficacy (r = 0.642, p  = 0.001). In this study, according multiple regression analysis, the strongest predictors of behaviors are in the following order: self-efficacy (β = 0.414, p  = 0.001), cues to action (β = 0.299, p  = 0.001), H.L (β = 0.170, p  = 0.001), and perceived susceptibility (β = 0.099, p  = 0.005). Thus, Health literacy, self-efficacy, cues to action and perceived susceptibility constructs predicted 52.1% of preventive behaviors (Table 3 ).

In the present study, the H.L score was measured to be 52.71 out of 100. The highest H.L was related to menstruation and the lowest was related to physical activity. In Saeedi Kopaei’s study in Iran, Isfahan city, the total health literacy score of high school female students was 42.6 out of 100. H.L of menstrual health was 68.12 out of 100; it was 54.5% regarding breast self-examination, 48.5% regarding iron deficiency anemia, 81.23% about physical activity and 77.36% for nutrition H.L [ 2 ]. The lowest health literacy was related to anemia and breast self-examination and the highest score was related to physical activity. But in our study, the lowest score related to physical activity. The difference in this result can be attributed to the age of the participants (17.4 years vs. 23.5 years) and high school education versus university. Perhaps the heavy volume of lessons has reduced students' physical activity.

In the study conducted by Ahmadi et al. on female students, the H.L score was reported to be 67.28 out of 100 [ 23 ]. In another study conducted by Dehghankar et al. on female students, as many as 65.6% of the girls in the study had adequate and excellent H.L [ 24 ]. In a national study conducted on the general population in Iran, the mean H.L score was reported to be 69.02 in the general population of Iran [ 25 ]. The results of these studies also report moderate health literacy which is almost similar to the results of the present study.

Although the findings of the aforementioned study, in comparison to those our study, indicate that, contrary to what is expected, female college students of our study are less healthy than the general population, in another national study conducted by Haghdoost et al., H.L in the general population was 51%, and it was close to the findings of our study [ 26 ]. Different factors such as differences in populations investigated, sampling methods, and H.L assessment tools can result in differences in the findings of different studies. Moreover, in the study conducted by Tavousi [ 25 ] et al., it has been indicated that with increasing age (up to 44 years), H.L tends to increase; H.L was higher for people with the age range of 35–44 years those being in the age range of 18–24 years. This is likely to explain the difference between the findings of our study and those of the study conducted by Tavousi et al. [ 25 ].

In this study, there is a significant correlation between total H.L and health-promoting behaviors; when H.L increases, conducting these behaviors increases as well. Like our study, a correlation between H.L and health-promoting behaviors has been indicated in the study conducted (on 375 female college students of Imam Khomeini International University in Qazvin, Iran) by Panahi et al. as well [ 27 ]. The study by Mahdavi et al. conducted among 500 women who referred to family health unit in Tehran, Iran also confirmed the findings of our study on the correlation existing between H.L and preventive behaviors [ 28 ]. 48.6% of participants had low health literacy level, 24.4% had marginal level and only 27% had adequate health literacy level [ 28 ].

Therefore, it seems that promoting public H.L through mass media, social networks, and university curricula are likely to result in increased health-promoting behaviors. It is suggested that by designing, implementing and evaluating educational programs based on risk factors and reducing the burden of diseases in universities, serious attention be paid to the health of female students.

In addition, given the correlation between H.L and health-promoting behaviors and the existence of a significant relationship between health-promoting behaviors and age, educational level (bachelor, master …) and father’s job, it can be hypothesized that H.L has a significant relationship with these factors as well. This has been already indicated in previous studies [ 25 , 26 , 27 , 28 ]. Also, considering the presentation of similar results in several studies on the poor health literacy of Iranian women regarding diseases and health-promoting behaviors, the necessary planning should be done by the Legal Office of Women's Health in the country.

Based on the results of the present study, self-efficacy, cues to action, and perceived susceptibility are the strongest predictors of health-promoting behaviors. Similarly, in a study conducted by Kenari et al. (on school students in Rasht), perceived self-efficacy was identified as the most important predictor of health behaviors. In the study conducted by Kenari et al., the cues to action and benefits were recognized to be the next important predictors [ 29 ]. In confirming our results, a study conducted by Ahmadian et al. (on students in Malaysia) indicated that perceived self-efficacy was the most important predictive factor of behavior. Moreover, in the aforementioned study, perceived barriers have been reported to be a negative factor in predicting behaviors [ 30 ]. Given the correlation between health belief model and health-promoting behaviors, some studies have indicated that a health belief model-based education is likely to increase health-promoting behaviors. For example, in a study on pre-university girls in Tehran, it was indicated that perceived self-efficacy increased significantly after providing education which was based on model. This education was proved to be effective on preventive behaviors [ 22 ]. In a study conducted by Karimi et al. (on nutritional behaviors of pregnant women), perceived benefits were recognized to have the highest correlation. After perceived benefits, it was shown that perceived barriers, susceptibility, severity, and self-efficacy were then correlated with nutritional behaviors [ 31 ]. The type of health-promoting behavior seems to be correlated with different components of the health belief model. For example, although in our study, perceived self-efficacy (as a whole) was most correlated with health-promoting behaviors, it was also partly indicated that having healthy diet, as a health-promoting behavior, is more correlated with perceived benefits, according to the results of Table Two. This has been indicated in the study conducted by Karimi et al. as well [ 31 ]. Also, physical activity behavior is more correlated with cues to action. Thus, these differences need to be attributed to differences in the type of behaviors. In a study conducted by Shirzad et al. (on girls living in child care centers in Tehran), it was shown that perceived susceptibility, benefits, and barriers are the most important predictive factors of health-promoting behaviors [ 32 ]. These differences are possibly owing to differences in social status of the statistical population in comparison to the population of our study.

Electronic response to the questionnaire has both weaknesses and strengths. Its strengths include faster data collection, ensuring that the data is confidential and anonymous, and providing honest answers due to the absence of the researcher. However, in the absence of the researcher, they may ask their friends the answers to some questions or search other sources at the time of completion.

Moreover, one of its strengths is the application of health belief model to assess students’ beliefs and perceptions. Generally speaking, it is suggested that intervention programs based on behavior change theories (such as health belief model and self-efficacy theory) be considered by the related university officials with the aim of promoting students’ H.L and self-efficacy to perform health-promoting behaviors for female students. Because by promoting students' beliefs (perceived susceptibility and severity) about diseases and increasing the benefits and removing barriers to health-promoting behaviors, in addition to increasing self-efficacy, their health literacy will also increase and as a result behavior will change.

Approximately 75% of the students had adopted preventive health behaviors for women’s diseases. The total H.L score was 52.71 out of 100. The lowest percentage of H.L was related to physical activity being 40.11%, and the highest score was related to menstruation being 77.54%. Moreover, the highest score of students’ beliefs was related to self-efficacy construct being 77.37%. The highest correlation was observed between behavior and total H.L (r = 0.414, p  < 0.0001), and as for the beliefs, the highest correlation was with self-efficacy (r = 0.642, p  < 0.0001). In this study, according multiple regression analysis, the strongest predictors of behaviors are self-efficacy (Beta = 0.414, p  < 0.001) and cues to action (Beta = 0.299, p  < 0.001). Thus, Health literacy, self-efficacy, cues to action and perceived susceptibility constructs predicted 52.1% of preventive behaviors.

Availability of data and materials

The data used and analyzed during the current study available from the corresponding author.

Abbreviations

• Health literacy
• Health belief model

Azadeh MA, Tafteh M. The obstacles of happiness from the view of female-headed households of Tehran. J Woman Family Stud. 2016;3(2):33–60.

Google Scholar  

SaeediKoupai M, Motaghi M. Comparing Health literacy in high school female students and their mothers regarding womens health. J Health Lit. 2017;1(4):220–9.

Stoltzfus RJ. Defining iron-deficiency anemia in public health terms: a time for reflection. J Nutr. 2001;131(2):565S-S567.

Article   CAS   Google Scholar  

Shamohammady F, Ghaffari J. Examination of iron deficiency anemia in payam-e noor university of Tehran female students. Peyke Noor J Sci. 2007;1(2):21–8.

Ashrafi AA, Khanjani N, Saber M, Jalili S, Khedmati E. Knowledge and attitude of students at Alzahra University about breast self-examination. Iran J Health Dev. 2012;1(2):112–20.

Critchley HOD, Babayev E, Bulun SE, Clark S, Garcia-Grau I, Gregersen PK, et al. Menstruation: science and society. Am J Obstet Gynecol. 2020;223(5):624–64. https://doi.org/10.1016/j.ajog.2020.06.004 .

Article   PubMed   PubMed Central   Google Scholar  

Saadatmand M, Karimi F, Khalesi M, Tabarraie Y. The Health behaviors study about menstural period in female students of azad qom university in 2007. J Woman Hyg. 2010;1(3):1–11.

Simonds SK. Health education as social policy. Health Educ Monogr. 1974;2:1–10. https://doi.org/10.1177/10901981740020S102 .

Article   Google Scholar  

Kickbusch I, Maag D. Health literacy International encyclopedia of public health. Oxford: Academic Press; 2008. p. 204–11.

Book   Google Scholar  

Moshki M, Mirzania M, Kharazmi A. The relationship of health literacy to quality of life and demographic factors in pregnant women: a cross-sectional study. J Health Lit. 2018;2(4):203–15. https://doi.org/10.22038/jhl.2018.10875 .

Safari Moradabadi A, Aghamolaei T, Ramezankhani A, Dadipoor S. The health literacy of pregnant women in Bandar Abbas. Iran J School Public Health Inst Public Health Res. 2017;15(2):121–32.

Mousavi H, Bagherian R. Health literacy and breast cancer. J Health Psychol. 2019;8(31):91–102.

Gebretatyos H, Amanuel S, Ghirmai L, Gebreyohannes G, Tesfamariam EH. Effect of health education on healthy nutrition and physical activity among female teachers aged 40–60 years in Asmara, Eritrea: a quasiexperimental study. J Nutr Metab. 2020;2020:1–7.

Chlebowski RT, Aragaki AK, Anderson GL, Pan K, Neuhouser ML, Manson JE, et al. Dietary modification and breast cancer mortality: long-term follow-up of the women’s health initiative randomized trial. J Clin Oncol. 2020;38(13):1419–28.

Nikooyeh B, Mahboob S, Razaviey S, Ghaem MS. Nutrition status; zinc, iron and copper serum levels and their relationship with some dietic and anthropometric parameters in the students of Tabriz University of Medical Sciences. J Birjand Univ Med Sci. 2005;12(3):9–15.

Ghaffari M, Tavassoli E, Esmaillzadeh A, Hasanzadeh A. The effect of education based on health belief model on the improvement of osteoporosis preventive nutritional behaviors of second grade middle school girls in Isfahan. Health Serv Res. 2011;6(4):714–23.

Pasdar Y, Izadi N, Khodadost M, Mansori K, Ranjbaran M, Niazi S. Depression and related factors in female students of Kermanshah university of medical sciences. Jorjani Biomed J. 2013;1(2):17–23.

Hatefnia E, Ghazivakili Z. Factors associated with regular physical activity for the prevention of osteoporosis in female employees Alborz University of Medical Sciences: application of health belief model. Alborz Uni Med J. 2016;5(2):78–86.

Jorvand R, Tavousi M, Ghofranipour F. Determinants of the regular physical activity among employees of healthcare network: application of health belief model. J Edu Community Health. 2018;5(3):4–12.

Nasirzadeh M. The process of designing, implementation and evaluation of theory-based educational interventions. J Rafsanjan Uin Med Sic. 2020;19(5):549–52.

Glanze K, Rimer BK, Viswanath K. Health behavior: theory, research, and practice. 5th ed. New York: Wiley; 2015.

Khalilipour M, Panahi R. Effect of education on promoting preventive behaviors of premenstrual syndrome in female adolecents: Health belief model application. J Edu Community Health. 2017;4(2):44–54.

Ahmadi FZ, Mehr-Mohammadi M, Talaee E, Fardanesh H, Paknahad M, Taghizadeh S, et al. Health Literacy among students of Farhangian University. Payesh. 2018;17(3):257–66.

Dehghankar L, Hajikarimbaba M, Panahi R. Health literacy and factors related to it among female students of Imam Khomeini International University in Qazvin, Iran. J School Public Health Inst Public Health Res. 2019;17(3):295–306.

Tavousi M, Haeri- Mehrizi A, Rafiefar S, Solimanian A, Sarbandi F, Ardestani M, et al. Health literacy in Iran: findings from a national study. J Health Monitor. 2016;15(1):95–102.

Haghdoost AA, Karamouzian M, Jamshidi E, Sharifi H, Rakhshani F, Mashayekhi N, et al. Health literacy among Iranian adults: findings from a nationwide population-based survey in 2015. Eastern Mediterr Health J. 2019;25(11):828–36.

Panahi R, Dehghankar L, Abdollahi F, Anbari M, Hosseini N. Health literacy and breast cancer preventive behaviors among students. Payesh. 2019;18(6):547–57.

Mahdavi Zh, Ramezani A, Ghanbari Sh, Khodakarim L. Relationship between health literacy and female cancers preventive behaviors. Payesh. 2017;16(5):613–25.

Kenari Z, Kasmaei P, Rouhani-Tonekaboni N, Ashouri A, Izadirad H, Arbabisarjou A, et al. Predictors of puberty health behaviors based on health belief model in 9th grade female students of public schools in Rasht. Drug Invention Today. 2019;12(7):1575–9.

Ahmadian M, Carmack S, Samah AA, Kreps G, Saidu MB. Psychosocial predictors of breast self-examination among female students in malaysia: a study to assess the roles of body image, self-efficacy and perceived barriers. Asian Pac J Cancer Prev. 2016;17(3):1277–84.

Karimy M, Taher M, Azarpira H. Measure health belief model construct about nutritional practices of pregnant women in Saveh University of Medical Sciences. Avi J Nur Mid Care. 2016;24(3):167–73.

Shirzadi S, Asghari Jafarabadi M, Nadrian H, Mahmoodi H. Determinants of puberty health among female adolescents residing in boarding welfare centers in Tehran: an application of health belief model. Med J Islam Repub Iran. 2016;30:432.

PubMed   PubMed Central   Google Scholar  

Download references

Acknowledgements

The results of the present study have been extracted from a master’s thesis in health education and health promotion. The research project number is 990159. Hereby, all university officials and students are highly appreciated for their cooperation and participation in this research. Moreover, the vice chancellor for research and technology is also appreciated for their financial support.

Rafsanjan University of Medical Sciences.

Author information

Authors and affiliations.

Department of Health Education and Health Promotion, School of Health, Student Research Committee, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

Mahla Ghorbani-Dehbalaei

Department of Midwifery, School of Nursing and Midwifery, Geriatric Care Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

Marzeyeh Loripoor

Department of Health Education and Health Promotion, School of Health, Occupational Safety and Health Center, NICICO, World Safety Organization and Rafsanjan University of Medical Sciences, Rafsanjan, Iran

Mostafa Nasirzadeh

You can also search for this author in PubMed   Google Scholar

Contributions

MN provided research ideas; MN, MGD, ML designed the research scheme; MGd were responsible for the implementation of the research plan and collecting data; MN were responsible for data analysis and manuscript writing; all authors drafted the manuscript; contributed to the manuscript review and approved the final manuscript.

Corresponding author

Correspondence to Mostafa Nasirzadeh .

Ethics declarations

Ethics approval and consent to participate.

The present study has been confirmed by the Ethics Committee of Rafsanjan University of Medical Sciences, and it has received the required ethical code (IR.RUMS.REC.1399.217). Also all ethical principles of the Helsinki ethical declaration have been met and written informed consent were obtained from all the participants in the first page of online questionnaire.

Consent for publication

Not applicable.

Competing interests

There is no conflict of interest.

Additional information

Publisher's note.

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

Supplementary Information

Additional file 1..

Specifications of the questionnaire used in the research.

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

Cite this article.

Ghorbani-Dehbalaei, M., Loripoor, M. & Nasirzadeh, M. The role of health beliefs and health literacy in women's health promoting behaviours based on the health belief model: a descriptive study. BMC Women's Health 21 , 421 (2021). https://doi.org/10.1186/s12905-021-01564-2

Download citation

Received : 19 May 2021

Accepted : 07 December 2021

Published : 18 December 2021

DOI : https://doi.org/10.1186/s12905-021-01564-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Gynecological diseases

BMC Women's Health

ISSN: 1472-6874

• Submission enquiries: [email protected]
• General enquiries: [email protected]

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

How the Health Belief Model Influences Your Behaviors

Elizabeth Boskey, PhD, MPH, CHES, is a social worker, adjunct lecturer, and expert writer in the field of sexually transmitted diseases.

Carly Snyder, MD is a reproductive and perinatal psychiatrist who combines traditional psychiatry with integrative medicine-based treatments.

Blend Images - Jose Luis Pelaez Inc / Brand X Pictures / Getty Images

• Effectiveness

Frequently Asked Questions

The Health Belief Model (HBM) is a tool that scientists use to try to predict health behaviors. It was originally developed in the 1950s and proposed by social psychologists Godfrey Hochbaum, Irwin Rosenstock, and Rosenstock and Kirscht. The model is based on the theory that a person's willingness to change their health behaviors primarily comes from their health perceptions.

According to this model, your individual beliefs about health and health conditions play a role in determining your health-related behaviors. Key factors that affect your approach to health include:

• Any barriers you think might be standing in your way
• Exposure to information that prompts you to take action
• How much of a benefit you think you'll get from engaging in healthy behaviors
• How susceptible you think you are to illness
• What you think the consequences will be of becoming sick
• Your confidence in your ability to succeed

Health experts often look for ways that Health Belief Models can affect the actions people take, including behaviors that can have an impact on both individual and public health.

This article discusses how the Health Belief Model works, the different components of the model, and how this approach can be used to address health-related behaviors.

What Are the Components of the Health Belief Model?

There are six main components of the Health Belief Model. Four of these constructs were main tenets of the theory when it was first developed. Two were added in response to research on the model related to addiction.

Perceived Severity

The probability that a person will change their health behaviors to avoid a consequence depends on how serious they believe the consequences will be. For example:

• If you are young and in love, you are unlikely to avoid kissing your sweetheart on the mouth just because they have the sniffles and you might get their cold. On the other hand, you probably would stop kissing if it might give you a more serious illness.
• Similarly, people are less likely to consider condoms when they think STDs are a minor inconvenience. That's why receptiveness to messages about safe sex increased during the AIDS epidemic. The perceived severity increased enormously. 

The severity of an illness can have a major impact on health outcomes. However, a number of studies have shown that perceived risk of severity is actually the least powerful predictor of whether or not people will engage in preventive health behaviors.

Perceived Susceptibility

People will not change their health behaviors unless they believe that they are at risk. For example:

• Individuals who do not think they will get the flu are less likely to get a yearly flu shot.
• People who think they are unlikely to get skin cancer are less likely to wear sunscreen or limit sun exposure.
• Those who do not think that they are at risk of acquiring HIV from unprotected intercourse are less likely to use a condom.
• Young people who don't think they're at risk of lung cancer are less likely to stop smoking.

Research suggests that perceived susceptibility to illness is an important predictor of preventive health behaviors.  

Perceived Benefits

It's difficult to convince people to change a behavior if there isn't something in it for them. People don't want to give up something they enjoy if they don't also get something in return. For example:

• A person probably won't stop smoking if they don't think that doing so will improve their life in some way.
• A couple might not choose to practice safe sex if they don't see how it could make their sex life better. 
• People might not get vaccinated if they do not think there is an individual benefit for them.

These perceived benefits are often linked to other factors, including the perceived effectiveness of a behavior. If you believe that getting regular exercise and eating a healthy diet can prevent heart disease, that belief increases the perceived benefits of those behaviors.

Perceived Barriers

One of the major reasons people don't change their health behaviors is that they think doing so is going to be hard. Changing health behaviors can require effort, money, and time. Commonly perceived barriers include:

• Amount of effort needed
• Inconvenience
• Social consequences

Sometimes it's not just a matter of physical difficulty, but social difficulty as well. For example, If everyone from your office goes out drinking on Fridays, it may be very difficult to cut down on your alcohol intake. If you think that condoms are a sign of distrust in a relationship, you may be hesitant to bring them up. 

Perceived barriers to healthy behaviors have been shown to be the single most powerful predictor of whether people are willing to engage in healthy behaviors.  

When promoting health-related behaviors such as vaccinations or STD prevention, finding ways to help people overcome perceived barriers is important. Disease prevention programs can often do this by increasing accessibility, reducing costs, or promoting self-efficacy beliefs.

Cues to Action

One of the best things about the Health Belief Model is how realistically it frames people's behaviors. It recognizes the fact that sometimes wanting to change a health behavior isn't enough to actually make someone do it.

Because of this, it includes two more elements that are necessary to get an individual to make the leap. These two elements are cues to action and self-efficacy.

Cues to action are external events that prompt a desire to make a health change. They can be anything from a blood pressure van being present at a health fair, to seeing a condom poster on a train, to having a relative die of cancer. A cue to action is something that helps move someone from wanting to make a health change to actually making the change.

Self-Efficacy

Self-efficacy wasn't added to the model until 1988. Self-efficacy looks at a person's belief in their ability to make a health-related change. It may seem trivial, but faith in your ability to do something has an enormous impact on your actual ability to do it.

Finding ways to improve individual self-efficacy can have a positive impact on health-related behaviors. For example, one study found that women who had a greater sense of self-efficacy toward breastfeeding were more likely to nurse their infants longer. The researchers concluded that teaching mothers to be more confident about breastfeeding would improve infant nutrition.

Thinking that you will fail will almost make certain that you do. Self-efficacy has been found to be one of the most important factors in an individual's ability to successfully negotiate condom use.

There are six components of the Health Belief Model. They are perceived severity, perceived susceptibility, perceived benefits, perceived barriers, cues to action, and self-efficacy.

Examples and Uses of the Health Belief Model

It can be helpful to look at how the Health Belief Model can be applied in different situations. One important aspect of public health is the design of programs that encourage people to engage in healthy behaviors, so understanding how this model can be applied to different situations can be useful.

For example, experts may be interested in understanding public attitudes about cancer screenings. Looking at factors like perceptions of the risk of getting cancer, the benefits of being screened for cancer, and the barriers to being screened can help healthcare professionals look for ways to encourage people to get screened.

The model may also be used for public health programs that are used in different settings. Schools, for example, may rely on educational programs to help children understand challenges regarding health, substance use, physical activity, nutrition, and personal safety. Such programs are often based on the Health Belief Model and work to educate, offer skills training, reduce barriers, and boost self-efficacy.

Healthcare professionals and public health experts can apply the Health Belief Model to create programs and interventions designed to help prevent health problems, encourage treatment behaviors , and support behavior change.

How Effective Is the Health Belief Model?

The Health Belief Model has been used for decades to help produce behavior change interventions. Research suggests that the Health Belief Model can be helpful for designing strategies to help promote healthy behaviors and to improve the prevention and treatment of health conditions. 

In a study published in the journal Health Psychology Review , researchers found that in studies looking at the Health Belief Model, 78% reported significant improvement in behavior adherence. Of the studies they looked at, 39% reported moderate to large effects related to health interventions.

Criticisms of the Health Belief Model

The Health Belief Model is not without criticism. Some of the limitations of this approach to understanding health include:

• It does not take into account how people's decisions may be shaped by habitual behaviors. 
• It focuses on health-related reasons for behaviors but ignores the fact that people often engage in actions for other reasons, such as social acceptance.
• It doesn't address the economic and environmental factors that can affect a person's health behavior. Living in a food desert or lacking the economic resources to afford fresh fruits and vegetables, for example, can be a major barrier to making healthy food choices.
• The model doesn't address the individual beliefs, attitudes, and other characteristics that affect how readily a person can change their behavior.

Critics also suggest that the model focuses on describing health behaviors rather than explaining how to change them. 

Some limitations of the Health Belief Model include it does not adequately address some of the individual factors that affect health behaviors. It also fails to account for how environmental factors, including social variables, impact a person's health choices.

A Word From Verywell

The Health Belief Model can be a helpful way for health educators to design interventions that can improve both individual and public health. By understanding the factors that influence the health choices people make, programs can tackle ways to reduce barriers, improve knowledge, and help people feel more motivated to take action .

It can also be a useful tool for thinking about your own approach to your health. Consider how things such as perceived susceptibility, perceived barriers, self-efficacy, and other elements of the model influence your choices, then look for things that you can do to make healthier choices in your life.

The Health Belief Model was created by social psychologists Irwin M. Rosenstock, Godfrey M. Hochbaum, S. Stephen Kegeles, and Howard Leventhal during the 1950s. It was developed for the U.S. Public Health Services to understand why people fail to engage in healthy behaviors.

One of the main benefits of the Health Belief Model is that it simplifies health-related constructs so they can be more readily tested and implemented in public health settings. Because it emphasizes some of the prerequisites for health behaviors, it can be helpful for addressing the things that need to happen before a person can successfully implement a behavior change.

The Health Promotion Model is a multidimensional approach that takes into account how a person's interaction with their environment affects their health choices. It is similar to the Health Belief Model in some ways, but where the HBM is focused on being health-protective, the Health Promotion Model focuses more on helping people improve their well-being and achieve self-actualization .

Ghorbani-Dehbalaei M, Loripoor M, Nasirzadeh M. The role of health beliefs and health literacy in women’s health promoting behaviours based on the health belief model: a descriptive study .  BMC Women’s Health . 2021;21(1):421.

Jones CL, Jensen JD, Scherr CL, Brown NR, Christy K, Weaver J. The Health Belief Model as an explanatory framework in communication research: Exploring parallel, serial, and moderated mediation .  Health Commun . 2015;30(6):566-576. doi:10.1080/10410236.2013.873363

Loke AY, Chan LK. Maternal breastfeeding self-efficacy and the breastfeeding behaviors of newborns in the practice of exclusive breastfeeding .  J Obstet Gynecol Neonatal Nurs . 2013;42(6):672-684. doi:10.1111/1552-6909.12250

Montanaro EA, Bryan AD. Comparing theory-based condom interventions: Health belief model versus theory of planned behavior . Health Psychol . 2014;33(10):1251-60. doi:10.1037/a0033969

Baghianimoghadam MH, Shogafard G, Sanati HR, Baghianimoghadam B, Mazloomy SS, Askarshahi M. Application of the Health Belief Model in promotion of self-care in heart failure patients . Acta Med Iran . 2013;51(1):52-8.

Jones CJ, Smith H, Llewellyn C. Evaluating the effectiveness of health belief model interventions in improving adherence: a systematic review . Health Psychol Rev . 2014;8(3):253-69. doi:10.1080/17437199.2013.802623

Orji R, Vassileva J, Mandryk R. Towards an effective health interventions design: an extension of the health belief model .  Online J Public Health Inform . 2012;4(3):ojphi.v4i3.4321. doi:10.5210/ojphi.v4i3.4321

Carpenter CJ. A meta-analysis of the effectiveness of health belief model variables in predicting behavior . Health Commun . 2010;25(8):661-9. doi:10.1080/10410236.2010.521906

Galloway RD. Health promotion: causes, beliefs and measurements .  Clin Med Res . 2003;1(3):249-258. doi:10.3121/cmr.1.3.249

By Elizabeth Boskey, PhD Elizabeth Boskey, PhD, MPH, CHES, is a social worker, adjunct lecturer, and expert writer in the field of sexually transmitted diseases. 

• Research article
• Open access
• Published: 17 August 2020

A systematic review of studies that measure parental vaccine attitudes and beliefs in childhood vaccination

• Amalie Dyda   ORCID: orcid.org/0000-0003-2806-4834 1 , 2 ,
• Catherine King 3 , 4 ,
• Aditi Dey 3 , 5 ,
• Julie Leask 6 , 3 &
• Adam G. Dunn 7 , 1  

BMC Public Health volume  20 , Article number:  1253 ( 2020 ) Cite this article

17k Accesses

48 Citations

12 Altmetric

Metrics details

Acceptance of vaccines is an important predictor of vaccine uptake. This has public health implications as those who are not vaccinated are at a higher risk of infection from vaccine preventable diseases. We aimed to examine how parental attitudes and beliefs towards childhood vaccination were measured in questionnaires through a systematic review of the literature .

We systematically reviewed the literature to identify primary research studies using tools to measure vaccine attitudes and beliefs, published between January 2012 and May 2018. Studies were included if they involved a quantitative survey of the attitudes and beliefs of parents about vaccinations recommended for children. We undertook a synthesis of the results with a focus on evaluating the tools used to measure hesitancy.

A total of 116 studies met the inclusion criteria, 99 used a cross sectional study design, 5 used a case control study design, 4 used a pre-post study design and 8 used mixed methods study designs. Sample sizes of included studies ranged from 49 to 12,259. The most commonly used tool was the Parent Attitudes about Childhood Vaccines (PACV) Survey ( n  = 7). The most common theoretical framework used was the Health Belief Model ( n  = 25). Questions eliciting vaccination attitudes and beliefs varied widely.

Conclusions

There was heterogeneity in the types of questionnaires used in studies investigating attitudes and beliefs about vaccination in parents. Methods to measure parental attitudes and beliefs about vaccination could be improved with validated and standardised yet flexible instruments. The use of a standard set of questions should be encouraged in this area of study.

Peer Review reports

Childhood vaccination rates vary widely by country and region, and the reasons for these variations are likely to be context-specific [ 1 , 2 , 3 ]. While access to vaccination is a perennial challenge, acceptance also remains an issue of importance to uptake which is affected by an individual’s feelings, attitudes and beliefs about vaccination [ 4 ]. There is a spectrum of attitudes towards vaccination, including those who are pro-vaccination and accept all vaccines, those who have many concerns but may fully or partially vaccinate, and those who refuse all vaccines [ 5 ]. Those who have questions and concerns have been shown to have lower levels of vaccination uptake [ 6 ] which may have a substantial impact on vaccination coverage and increases the risk of outbreaks [ 7 ]. Not only are unvaccinated individuals at higher risk of infection and adverse health outcomes, but under-vaccinated populations are at higher risk of more severe outbreaks [ 8 , 9 , 10 ].

A range of questionnaires have been developed and tested for measuring vaccination attitudes and beliefs [ 11 ]. The largest recent questionnaires in the area include The Vaccine Confidence Project [ 12 ] which collected 65,819 responses across 67 countries [ 13 ], and the Wellcome Global Monitor 2018 [ 14 ], which collected more than 140,000 responses from 140 countries. Both were based on the same set of questions, which included items about vaccine importance, effectiveness, safety, and religious compatibility.

Studies using questionnaires to understand vaccine attitudes and beliefs often modify existing items to incorporate the local context of a specific country or region. There is high variability with respect to use of behavioural theories to inform constructs and items and the comprehensiveness of validation, such as whether the items predict vaccination uptake. Moreover, high variability in how constructs such as vaccine confidence are measured between different questionnaires makes it difficult to assess how attitudes and beliefs vary globally.

Our aim was to examine how parental attitudes and beliefs towards childhood vaccination were measured in questionnaires through a systematic review of the literature.

Inclusion criteria

Studies were included if they were quantitative primary studies investigating parental vaccine attitudes and/or beliefs, regardless of whether they considered one or a combination of vaccines or vaccine-preventable diseases. For the purpose of this review studies on vaccine hesitancy were included, with vaccine hesitancy defined as “a motivational state of being conflicted about, or opposed to, getting vaccinated” [ 15 ]. Vaccine hesitancy can result in “a delay in acceptance or refusal of vaccines despite availability of vaccination services” [ 16 ]. Studies published after January 2012 were included. Studies were excluded if they investigated vaccination barriers not associated with attitudes or beliefs (e.g. measuring access other than as a factor affecting convenience), adult and adolescent vaccination, or if they were not reported in English. We applied no geographical constraints.

Search strategy

This review was developed in line with the PRISMA guidelines [ 17 ]. Key bibliographic databases were searched to identify relevant articles. The 19 databases searched included: OVID Medline, PsycINFO and Database of Systematic Reviews (see Additional File  1 for the full list of databases searched) Search terms included thesaurus terms (where available) such as ‘Immunization’, ‘Immunization programs’, ‘Vaccines’, ‘Decision Making’, ‘Decision Theory’, ‘Attitude to Health’, ‘Health Behavior’, ‘Risk Assessment’, ‘Trust’, ‘Uncertainty’, ‘Vaccination Refusal’, ‘Anti-Vaccination movement’, ‘Child, Preschool’ and ‘Infant’ These were used with relevant associated text terms. Truncation was utilised to ensure all variant spelling endings of text words were retrieved. The searches were limited to items published from 2012 and ‘Humans’. (see Additional File 1 for the full search strategy). The last search was conducted on 19 May 2018. Articles reviewed for inclusion were limited from January 2012 to May 2018 to avoid duplicating the findings of a 2014 systematic review that reviewed the global literature on vaccine hesitancy [ 5 ].

All titles and abstracts or executive summaries found through the search strategy were screened independently by two authors (Adam Dunn and Amalie Dyda) to determine if they were relevant to the review. The full text of those articles that appeared to meet the inclusion criteria were retrieved and reviewed for relevance independently by the same two authors. The reference lists of all included items were searched to identify any additional items for inclusion.

Data extraction and synthesis

Data were extracted by one author (Amalie Dyda) and confirmed by a second author (Adam Dunn). A standard data extraction form developed by the authors was used. For each study, study design information extracted from the articles included the method of recruitment and the location and type of participants, the number of participants recruited (and completing the study, where appropriate), the vaccine or set of vaccines of relevance to the study, and details of the questions used to measure attitudes and belief about vaccination including any description of behavioural theories used to inform the questionnaire design, and whether the questions were taken directly or adapted from existing instruments. We defined validated questionnaires as those that followed “the process of establishing that a survey item or measure serves the intended purpose. This process can include establishing whether it measures the intended construct using qualitative means (advice from experts, cognitive testing with lay people) and quantitative means (convergent, discriminant, predictive validity)” [ 18 ]. Data extracted from each study were tabulated and grouped by study type and study characteristics including sample size, recruitment method, and location.

The initial search strategy returned 41,570 titles and abstracts, of which 23,201 were removed as duplicates. Title and abstract screening identified 673 full text items for review. Of these, 116 met the inclusion criteria (Fig.  1 ). A review of the reference lists of included articles did not identify any additional items for inclusion.

Summary of the search strategy results and set of included studies

Summary of included studies

Of the included studies, 99 (85.3%) used a cross sectional study design (Additional File  2 ). Sample sizes across all 116 included studies ranged from 49 to 12,259 participants, with a median of 455 participants. Parental attitudes and beliefs about childhood vaccines in general were studied in 57 (49.1%) studies, and attitudes and beliefs about influenza vaccination (including pandemic H1N1 influenza) in 35 (30.2%). The other 24 (20.7%) studies asked participants about attitudes and beliefs for other specific vaccines, such as polio and rotavirus vaccines.

Thirty-four countries were represented in the included studies (Fig.  2 ). The most common country in which studies were conducted was the United States ( n  = 36), followed by Canada ( n  = 9) and the United Kingdom ( n  = 8). When aggregated by the number of participants, the United States included the largest number (40,155 participants), followed by Canada (7200 participants), and the United Kingdom (3273 participants).

Among the set of 116 included studies, 34 countries were represented

Questionnaires and survey instruments

One hundred and fourteen studies used a survey design, with the two remaining studies using interviews. The questions asked of participants varied substantially across the set of included studies. There was heterogeneity both in terms of the specific questions asked of participants as well as the provenance of those questions in theory or from standardised questionnaire sets. Sixty three studies reported at least one aspect of validation.

The most commonly used standard questionnaire was the Parent Attitudes about Childhood Vaccines (PACV) Survey Tool ( n  = 7), used in 4 studies with its full format with 15 questions [ 19 , 20 , 21 , 22 ]. In some studies, the PACV questions were adapted to match the local context or study population, such as in Malaysia [ 21 ] and for expectant parents in the United States [ 19 ]. In 3 studies, a subset of the PACV questions were used [ 23 , 24 , 25 ]. Other questionnaires used included 6 studies based on national immunisation surveys or health department questionnaires [ 26 , 27 , 28 , 29 , 30 , 31 ], 1 study based on the Parental Attitudes toward MMR Vaccine and Trust in Medical Authority questionnaire [ 32 ], and 1 that used the Vaccine Safety, Attitudes, Training and Communication measures [ 33 ].

A total of 62 (53.4%) included studies developed questionnaires using previous literature or previously developed questionnaires, 7 developed questionnaires with experts in the field, 1 used a self-developed scale, and 6 conducted a qualitative data to elicit appropriate questions. The remaining 40 studies did not report having used previous examples as the basis for the designs of their questionnaires.

A variety of theoretical frameworks were used to inform the design of the questionnaires used in the studies. The most common was the Health Belief Model (HBM), which was explicitly stated as having been used to inform the questions in 25 (19.0%) studies [ 30 , 32 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ], followed by the Theory of Planned Behaviour, which was used in 5 (4.3%) studies [ 58 , 59 , 60 , 61 , 62 , 63 ]. Other studies that were adapted from existing questionnaires may have implicitly been based on these or other theoretical frameworks as a consequence of having adapted from other questionnaires but did not explicitly claim the theoretical framework as a basis for their questions.

Questions about intention to vaccinate

Of the 116 included studies, 38 (32.8%) included questions in which parents were directly asked about their vaccination intentions for one or more antigens. The specific questions that were asked varied across the set of studies. Examples included, “If you had another infant today, would you want him or her to get all the recommended shots?, “I would get a flu vaccine for my child under 5, every year, if it was free?”, and “If your child were offered it at some point in the future, would you vaccinate them against swine flu?”. This variation precluded a synthesis of the results, and the proportion of participants responding in the affirmative varied substantially across the set of studies.

Of the 38 studies which asked about vaccination intentions for one or more antigens, 16 (13.8%) of these specifically asked about whether they would have children vaccinated for all childhood vaccines. The percentages in these studies ranged from 75% in a study involving 200 parents in the United States [ 64 ] to 98% in a study involving 54 parents in Canada [ 35 ]. For the 9 (7.8%) studies that asked about intentions in relation to influenza vaccination, the percentages ranged from 29% in a study involving 236 parents in Canada [ 65 ] to 92% in a before and after study at a clinic involving 5284 and 5755 different groups of parents in rural Kenya [ 66 ].

A substantial number of studies quantitatively examine the childhood vaccination attitudes and beliefs of parents across a broad range of countries. A large number of studies did not report using a validated questionnaire. The countries in which the highest number of studies were conducted were the United States, Canada and the United Kingdom, with most other countries having either none or only a small number of studies. There were significant differences in the way in which questionnaires were developed and the questions asked in each of the studies, making synthesis or comparison of findings a challenge. The use of standardised questionnaires globally would allow findings across countries to be compared and help track longitudinal trends.

The geographical distribution of primary studies included in the review was generally consistent with a previous review on attitudes and beliefs regarding vaccination [ 5 ], in which most included studies were conducted in North America and Europe. Among the subset of studies that used standardised questionnaires, there was no clear difference in rates of vaccine hesitancy between countries, nor any clear pattern in the attitudes and beliefs that exhibited the strongest associations with intention. Given that only a relatively small subset used standardised questionnaires, this result is a reflection of the small number of studies rather than evidence of consistency in what matters most to parents exhibiting vaccine hesitancy.

There was little consistency in the provenance of the questions used to measure attitudes and beliefs across studies. A number of studies did not report how the questionnaire or survey instrument was developed, making comparison of these studies difficult. The majority of studies reported construct and item development methods such as basing the questionnaire on previous literature, expert opinion or the use of previously developed surveys.

The use of qualitative evidence is best practice for forming constructs [ 67 ] and the use of a previously validated questionnaire is the most appropriate methodology as this ensures that items have content, construct and predictive validity. Previously developed questionnaires which are not validated may not accurately capture information, which is then repeated if these questionnaires are reused [ 18 ]. However, as there is no agreed upon gold standard survey instrument, a wide range of sources were used for development, resulting in heterogeneity of questionnaires. The most commonly used standard questionnaire was the PACV Survey Tool, which has been validated in two different settings and been shown to identify vaccine hesitant parents. The questionnaire focuses on the domains of ‘Safety and efficacy’, ‘General attitudes’ and ‘Behaviour’ [ 68 , 69 ]. The use of this questionnaire for studies investigating vaccine hesitancy should be encouraged to better allow for comparison across studies.

For theoretical frameworks, we found that the HBM was most commonly used to support the development of questionnaires, which was consistent with previous reviews [ 5 ]. The HBM posits that perceptions of susceptibility, severity, benefit and barriers, cues to action and self-efficacy predict behaviour. This and other models place emphasis on risk appraisals as important predictors of vaccination. Use of the HBM is complicated by the fact that all related perceptions could apply to vaccination uptake as much as disease outcomes. Since these models look at individual psychological factors by design, they are weaker at measuring other factors like false contraindications, social influence, or access to services or vaccines, which are more likely to be effective in increasing uptake, if they are addressed [ 15 ]. Further, many models fail to measure trust, yet trust in vaccination arises as a relevant phenomenon in both qualitative accounts of under-vaccination and the influence of vaccine safety scares [ 15 ]. Trust is often “ill-defined and a loosely measured concept” [ 70 ]. Recent work on the moral foundations of behaviour suggests that measuring constructs such as contamination and liberty are also relevant [ 71 , 72 ]. Further work is needed to incorporate moral foundations, other feelings and attitudes and beliefs and trust into a single model of vaccination behaviour and test its robustness.

Future studies in this area may benefit from considering standardised questions on vaccine attitudes and beliefs and other barriers or facilitators [ 11 ]. Large international surveys based on a standardised set of questions may be useful for providing international comparisons with context-specific additional questions. To consider the local context, qualitative investigations could supplement the broad based quantitative knowledge from surveys. Both forms of data collection are useful but are also resource intensive and relatively slow to report.

Current outbreaks of measles in the US highlight the importance of monitoring and measuring attitudes and beliefs about vaccinations. From 1st January to 18th July 2019 there were a total of 1148 cases of measles identified in the US which is the largest number of infections reported since 1992. Outbreaks are occurring across a number of states, with an outbreak in Rockland County, reporting the majority (78.4%) of cases have not been vaccinated [ 73 ].

The development of the internet has increased the speed with which information and misinformation can spread in the community. This may outpace our ability to measure and report on attitudes and beliefs using current survey methods which are time and resource intensive. Due to the time lag involved, using these methods may limit the ability to support the rapid design of evidence-informed and localised interventions for debunking or mitigating the impact of misinformation.

There were several limitations to the review approach and conduct. The first limitation was that the geographical distribution of the studies included in the review may be biased by the exclusion of studies not written in English. In addition, parental beliefs and attitudes towards influenza vaccination often differ from routine childhood vaccinations [ 74 ]. This childhood vaccine was included as some countries recommend annual influenza vaccination, but this is unlikely to affect the findings regarding tools used to monitor attitudes and beliefs about vaccination.

Despite the number of studies investigating parental attitudes and beliefs about childhood vaccination which were conducted in at least 36 countries, there was heterogeneity in survey designs. Methods to measure parental attitudes and beliefs about vaccination could be improved with validated and standardised yet flexible instruments, supplemented with qualitative investigations. The use of a standard set of validated questions should be encouraged in this area of study to identify, track, and monitor longitudinal trends using quality data.

Availability of data and materials

Not applicable.

Abbreviations

Health belief model

Parent attitudes about childhood vaccines

Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kang Y. Vaccination coverage among children aged 19-35 months - United States, 2017. MMWR Morb Mortal Wkly Rep. 2018;67(40):1123–8.

Article   PubMed   PubMed Central   Google Scholar  

International Institute for Population Sciences (IIPS) and ICF. National family health survey (nfhs-4), 2015–16: India. Mumbai: IIPS; 2017.

Google Scholar  

National Centre for Immunisation Research and Surveillance. Coverage data and reports 2019 [Available from: http://www.ncirs.org.au/health-professionals/coverage-data-and-reports .

Larson HJ. The biggest pandemic risk? Viral misinformation. Nature. 2018;562:309.

Article   CAS   PubMed   Google Scholar  

Larson HJ, Jarrett C, Eckersberger E, Smith DM, Paterson P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 2007-2012. Vaccine. 2014;32(19):2150–9.

Article   PubMed   Google Scholar  

Damnjanović K, Graeber J, Ilić S, Lam WY, Lep Ž, Morales S, et al. Parental decision-making on childhood vaccination. Front Psychol. 2018;9:735.

Smith LE, Amlot R, Weinman J, Yiend J, Rubin GJ. A systematic review of factors affecting vaccine uptake in young children. Vaccine. 2017;35(45):6059–69.

Phadke VK, Bednarczyk RA, Salmon DA, Omer SB. Association between vaccine refusal and vaccine-preventable diseases in the United States: a review of measles and pertussis. JAMA. 2016;315(11):1149–58.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Omer SB, Enger KS, Moulton LH, Halsey NA, Stokley S, Salmon DA. Geographic clustering of nonmedical exemptions to school immunization requirements and associations with geographic clustering of pertussis. Am J Epidemiol. 2008;168(12):1389–96.

Salathe M, Bonhoeffer S. The effect of opinion clustering on disease outbreaks. J R Soc Interface. 2008;5(29):1505–8.

Betsch C, Schmid P, Heinemeier D, Korn L, Holtmann C, Böhm R. Beyond confidence: Development of a measure assessing the 5c psychological antecedents of vaccination. Plos One. 2018;13(12):e0208601-e.

Larson HJ. The state of vaccine confidence. Lancet. 2018;392(10161):2244–6.

Larson HJ, de Figueiredo A, Xiahong Z, Schulz WS, Verger P, Johnston IG, et al. The state of vaccine confidence 2016: global insights through a 67-country survey. EBioMedicine. 2016;12:295–301.

Gallup (2019) wellcome global monitor– first wave findings. 2019.

Brewer NT, Chapman GB, Rothman AJ, Leask J, Kempe A. Increasing vaccination: putting psychological science into action. Psychol Sci Public Interest. 2017;18(3):149–207.

World Health Organization. Report of the SAGE working group on vaccine hesitancy. Geneva: World Health Organization; 2014.

Prisma- preferred reporting items for systematic reviews and meta-analyses 2013 [Available from: http://www.prisma-statement.org/ .

Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best practices for developing and validating scales for health, social, and behavioral research: a primer. Front Public Health. 2018;6:149.

Cunningham RM, Minard CG, Guffey D, Swaim LS, Opel DJ, Boom JA. Prevalence of vaccine hesitancy among expectant mothers in Houston, Texas. Acad Pediatr. 2018;18(2):154–60.

Henrikson NB, Anderson ML, Opel DJ, Dunn J, Marcuse EK, Grossman DC. Longitudinal trends in vaccine hesitancy in a cohort of mothers surveyed in washington state, 2013–2015. Public Health Rep. 2017;132(4):451–4 Available from: http://cochranelibrary-wiley.com/o/cochrane/clcentral/articles/885/CN-01400885/frame.html .

Mohd Azizi FS, Kew Y, Moy FM. Vaccine hesitancy among parents in a multi-ethnic country, Malaysia. Vaccine. 2017;35(22):2955–61.

Orr C, Beck AF. Measuring vaccine hesitancy in a minority community. Clin Pediatr. 2017;56(8):784–8.

Article   Google Scholar  

Oladejo O, Allen K, Amin A, Frew PM, Bednarczyk RA, Omer SB. Comparative analysis of the parent attitudes about childhood vaccines (pacv) short scale and the five categories of vaccine acceptance identified by gust et al. Vaccine. 2016;34(41):4964–8.

Schoeppe J, Cheadle A, Melton M, Faubion T, Miller C, Matthys J, et al. The immunity community: a community engagement strategy for reducing vaccine hesitancy. Health Promot Pract. 2017;18(5):654–61.

Cataldi JR, Dempsey AF, O'Leary ST. Measles, the media, and mmr: impact of the 2014-15 measles outbreak. Vaccine. 2016;34(50):6375–80.

LaVail KH, Kennedy AM. The role of attitudes about vaccine safety, efficacy, and value in explaining parents' reported vaccination behavior. Health Educ Behav. 2013;40(5):544–51.

Luthy KE, Beckstrand RL, Meyers CJH. Common perceptions of parents requesting personal exemption from vaccination. J Sch Nurs. 2013;29(2):95–103.

Schönberger K, Ludwig MS, Wildner M, Kalies H. Timely mmr vaccination in infancy: influence of attitudes and medical advice on the willingness to vaccinate. Klin Padiatr. 2012;224(7):437–42.

Shrestha S, Shrestha M, Wagle RR, Bhandari G. Predictors of incompletion of immunization among children residing in the slums of Kathmandu valley, Nepal: a case-control study. BMC Public Health. 2016;16:970.

Smith PJ, Marcuse EK, Seward JF, Zhao Z, Orenstein WA. Children and adolescents unvaccinated against measles: geographic clustering, parents' beliefs, and missed opportunities. Public Health Rep. 2015;130(5):485–504.

Walsh S, Thomas DR, Mason BW, Evans MR. The impact of the media on the decision of parents in south wales to accept measles-mumps-rubella (mmr) immunization. Epidemiol Infect. 2015;143(3):550–60.

Leonard W. Parental Confidence in U.S. Government and Medical Authorities, Measles (Rubeloa) Knowledge, and MMR Vaccine Compliance (2015). Walden Dissertations and Doctoral Studies; 1718.

Umeh GC, Nomhwange TI, Shamang AF, Zakari F, Musa AI, Dogo PM, et al. Attitude and subjective wellbeing of non-compliant mothers to childhood oral polio vaccine supplemental immunization in northern Nigeria. BMC Public Health. 2018;18(1):231.

Armitage ET, Camara J, Bah S, Forster AS, Clarke E, Kampmann B, et al. Acceptability of intranasal live attenuated influenza vaccine; influenza knowledge and vaccine intent in the Gambia. Vaccine. 2018;36(13):1772–80.

Atkinson KM, Ducharme R, Westeinde J, Wilson SE, Deeks SL, Pascali D, et al. Vaccination attitudes and mobile readiness: a survey of expectant and new mothers. Hum Vaccin Immunotherapeutics. 2015;11(4):1039–45.

Ben Natan M, Kabha S, Yehia M, Hamza O. Factors that influence israeli muslim Arab parents' intention to vaccinate their children against influenza. J Pediatr Nurs-Nurs Care Children Fam. 2016;31(3):293–8.

Chen CH, Chiu PJ, Chih YC, Yeh GL. Determinants of influenza vaccination among young taiwanese children. Vaccine. 2015;33(16):1993–8.

Cheung S, Wang HL, Mascola L, El Amin AN, Pannaraj PS. Parental perceptions and predictors of consent for school-located influenza vaccination in urban elementary school children in the United States. Influenza Other Respir Viruses. 2015;9(5):255–62.

Chun Chau JP, Lo SHS, Chow Choi K, Kin Chau MH, Tong DWK, Kwong T, et al. Factors determining the uptake of influenza vaccination among children with chronic conditions. Pediatr Infect Dis J. 2017;36(7):e197-e202.

He L, Liao QY, Huang YQ, Feng S, Zhuang XM. Parents' perception and their decision on their children's vaccination against seasonal influenza in Guangzhou. Chin Med J. 2015;128(3):327–41.

Hwang JH, Lim CH, Kim DH, Eun BW, Jo DS, Song YH, et al. A survey of parental perception and pattern of action in response to influenza-like illness in their children: including healthcare use and vaccination in Korea. J Korean Med Sci. 2017;32(2):204–11.

Janks M, Cooke S, Odedra A, Kang H, Bellman M, Jordan RE. Factors affecting acceptance and intention to receive pandemic influenza a h1n1 vaccine among primary school children: A cross-sectional study in Birmingham, UK. Influenza Res Treat. 2012;2012:182565.

Kempe A, Daley MF, Pyrzanowski J, Vogt TM, Campagna EJ, Dickinson LM, et al. School-located influenza vaccination with third-party billing: what do parents think? Acad Pediatr. 2014;14(3):241–8.

Lau JT, Mo PK, Cai YS, Tsui HY, Choi KC. Coverage and parental perceptions of influenza vaccination among parents of children aged 6 to 23 months in hong kong. BMC Public Health. 2013;13:1026.

Malosh R, Ohmit SE, Petrie JG, Thompson MG, Aiello AE, Monto AS. Factors associated with influenza vaccine receipt in community dwelling adults and their children. Vaccine. 2014;32(16):1841–7.

Mergler MJ, Omer SB, Pan WKY, Navar-Boggan AM, Orenstein W, Marcuse EK, et al. Association of vaccine-related attitudes and beliefs between parents and health care providers. Vaccine. 2013;31(41):4591–5.

Morin A, Lemaître T, Farrands A, Carrier N, Gagneur A. Maternal knowledge, attitudes and beliefs regarding gastroenteritis and rotavirus vaccine before implementing vaccination program: which key messages in light of a new immunization program? Vaccine. 2012;30(41):5921–7.

O'Leary ST, Barnard J, Lockhart S, Kolasa M, Shmueli D, Dickinson LM, et al. Urban and rural differences in parental attitudes about influenza vaccination and vaccine delivery models. J Rural Health. 2015;31(4):421–30.

Paek HJ, Shin KA, Park K. Determinants of caregivers' vaccination intention with respect to child age group: A cross-sectional survey in south korea. BMJ Open. 2015;5:e008342.

Saitoh A, Sato I, Shinozaki T, Kamiya H, Nagata S. Improved parental attitudes and beliefs through stepwise perinatal vaccination education. Hum Vaccin Immunother. 2017;13(11):2639–45.

Tsuchiya Y, Shida N, Machida K. Flu vaccination acceptance among children and awareness of mothers in japan. In: Spier R, editor. 7th Vaccine & ISV Annual Global Congress, vol. 8: Procedia in Vaccinology. 2014. p. 12–7.

Wagner AL, Boulton ML, Sun X, Mukherjee B, Huang Z, Harmsen IA, et al. Perceptions of measles, pneumonia, and meningitis vaccines among caregivers in shanghai, China, and the health belief model: a cross-sectional study. BMC Pediatr. 2017;17.

Wu CST, Kwong EWY, Wong HT, Lo SH, Wong ASW. Beliefs and knowledge about vaccination against ah1n1pdm09 infection and uptake factors among chinese parents. Int J Environ Res Public Health. 2014;11(2):1989–2002.

Tsuchiya Y, Shida N, Izumi S, Ogasawara M, Kakinuma W, Tsujiuchi T, et al. Factors associated with mothers not vaccinating their children against mumps in Japan. Public Health. 2016;137:95–105.

Schollin Ask L, Hjern A, Lindstrand A, Olen O, Sjögren E, Blennow M, et al. Receiving early information and trusting swedish child health Centre nurses increased parents’ willingness to vaccinate against rotavirus infections. Acta Paediatr. 2017;106(8):1309–16.

Scheuerman O, Zilber E, Davidovits M, Chodick G, Levy I. Nephrologists need to play a key role in improving annual influenza vaccination rates in children with kidney disease. Acta Paediatr. 2017;106(5):812–8.

Peleg N, Zevit N, Shamir R, Chodick G, Levy I. Seasonal influenza vaccination rates and reasons for non-vaccination in children with gastrointestinal disorders. Vaccine. 2015;33(1):182–6.

Dubé E, Bettinger JA, Halperin B, Bradet R, Lavoie F, Sauvageau C, et al. Determinants of parents' decision to vaccinate their children against rotavirus: results of a longitudinal study. Health Educ Res. 2012;27(6):1069–80.

Dube E, Gagnon D, Ouakki M, Bettinger JA, Witteman HO, MacDonald S, et al. Measuring vaccine acceptance among Canadian parents: a survey of the Canadian immunization research network. Vaccine. 2018;36(4):545–52.

Fadel CW, Colson ER, Corwin MJ, Rybin D, Heeren TC, Wang CL, et al. Maternal attitudes and other factors associated with infant vaccination status in the united states, 2011–2014. J Pediatr. 2017;185:136.

Harmsen IA, Lambooij MS, Ruiter RAC, Mollema L, Veldwijk J, van Weert Y, et al. Psychosocial determinants of parents' intention to vaccinate their newborn child against hepatitis b. Vaccine. 2012;30(32):4771–7.

MacDougall DM, Halperin BA, Langley JM, MacKinnon-Cameron D, Li L, Halperin SA, et al. Knowledge, attitudes, beliefs, and behaviors of parents and healthcare providers before and after implementation of a universal rotavirus vaccination program. Vaccine. 2016;34(5):687–95.

Thorpe EL, Zimmerman RK, Steinhart JD, Lewis KN, Michaels MG. Homeschooling parents' practices and beliefs about childhood immunizations. Vaccine. 2012;30(6):1149–53.

Weiner JL, Fisher AM, Nowak GJ, Basket MM, Gellin BG. Childhood immunizations first-time expectant mothers' knowledge, beliefs, intentions, and behaviors. Vaccine. 2015;33:D92–D8.

Dubé E, Gagnon D, Huot C, Paré R, Jacques S, Kossowski A, et al. Influenza immunization of chronically ill children in pediatric tertiary care hospitals. Hum Vaccin Immunotherapeutics. 2014;10(10):2935–41.

Oria PA, Arunga G, Lebo E, Wong JM, Emukule G, Muthoka P, et al. Assessing parents' knowledge and attitudes towards seasonal influenza vaccination of children before and after a seasonal influenza vaccination effectiveness study in low-income urban and rural Kenya, 2010-2011. BMC Public Health. 2013;13.

Opel DJ, Mangione-Smith R, Taylor JA, Korfiatis C, Wiese C, Catz S, et al. Development of a survey to identify vaccine-hesitant parents: the parent attitudes about childhood vaccines survey. Hum Vaccin. 2011;7(4):419–25.

Opel DJ, Taylor JA, Mangione-Smith R, Solomon C, Zhao C, Catz S, et al. Validity and reliability of a survey to identify vaccine-hesitant parents. Vaccine. 2011;29(38):6598–605.

Abd Halim H, Abdul-Razak S, Md Yasin M, Isa MR. Validation study of the parent attitudes about childhood vaccines (PACV) questionnaire: the Malay version. Hum Vaccin Immunother. 2020;16(5):1040–9.

Larson HJ, Clarke RM, Jarrett C, Eckersberger E, Levine Z, Schulz WS, et al. Measuring trust in vaccination: a systematic review. Hum Vaccin Immunotherapeutics. 2018;14(7):1599–609.

Amin AB, Bednarczyk RA, Ray CE, Melchiori KJ, Graham J, Huntsinger JR, et al. Association of moral values with vaccine hesitancy. Nat Hum Behav. 2017;1(12):873–80.

Luz PM, Brown HE, Struchiner CJ. Disgust as an emotional driver of vaccine attitudes and uptake? A mediation analysis. Epidemiol Infect. 2019;147:e182-e.

Centers for Disease Control and Prevention. Measles cases and outbreaks. 2019.

C.S. Mott Children’s Hospital. Inferiority complex? Parents rate flu lower than other vaccines. Mott Poll Rep. 2016;26(1).

Download references

Acknowledgements

This project was funded by the Australian National Health and Medical Research Council (NHMRC) Project Grant APP1128968. The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and affiliations.

Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia

Amalie Dyda & Adam G. Dunn

Department of Health Systems and Populations, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia

Amalie Dyda

National Centre for Immunisation Research & Surveillance, Sydney, NSW, Australia

Catherine King, Aditi Dey & Julie Leask

The University of Sydney, Children’s Hospital at Westmead Clinical School, Faculty of Medicine and Health, Sydney, NSW, Australia

Catherine King

The University of Sydney, School of Medicine, Faculty of Medicine and Health, Sydney, NSW, Australia

The University of Sydney, Susan Wakil School of Nursing and Midwifery, Sydney, NSW, Australia

Julie Leask

The University of Sydney, Discipline of Biomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, Sydney, NSW, Australia

Adam G. Dunn

You can also search for this author in PubMed   Google Scholar

Contributions

A.Dyda led the design and coordination of the review. CK designed and conducted the literature searches and was a contributor in writing the manuscript. A. Dey assisted in the design of the review and provided critical intellectual content throughout. JL was a major contributor to the design of the review and provided critical intellectual content throughout. A. Dunn was also was a major contributor to the design of the review, and assisted with removing duplicates and screening of titles, abstracts and full review of papers for inclusion. All authors contributed to the revision of the manuscript and provided intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Amalie Dyda .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have 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

Additional file 1..

Search strategy. Detailed description of search strategy used for review.

Additional file 2: Table 1.

Summary of included studies. Summary table of each included study with details about study characteristics.

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

Cite this article.

Dyda, A., King, C., Dey, A. et al. A systematic review of studies that measure parental vaccine attitudes and beliefs in childhood vaccination. BMC Public Health 20 , 1253 (2020). https://doi.org/10.1186/s12889-020-09327-8

Download citation

Received : 16 June 2020

Accepted : 02 August 2020

Published : 17 August 2020

DOI : https://doi.org/10.1186/s12889-020-09327-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Immunization/immunisation
• Vaccination
• Vaccines, questionnaire

BMC Public Health

ISSN: 1471-2458

• Submission enquiries: [email protected]
• General enquiries: [email protected]

Advertisement

Supported by

Columbia Students Arrested Over Campus Rally May Face Other Consequences

Students who camped in tents to protest the war in Gaza, including the daughter of Representative Ilhan Omar, may be barred from finishing the semester.

• Share full article

By Troy Closson and Anna Betts

Many of the more than 100 Columbia University and Barnard College students who were arrested after refusing to leave a pro-Palestinian encampment on campus on Thursday woke up to a chilly new reality this week: Columbia said that their IDs would soon stop working, and some of them would not be able to finish the semester.

The students who were arrested were released with summonses. The university said all of the 100 or so students involved in the protest had been informed that they were suspended.

For some of those students, that means they must vacate their student housing, with just weeks before the semester ends.

Yet whatever the consequences, several of the students said in interviews that they were determined to keep protesting Israel’s ongoing war in Gaza.

They said that after being loaded onto buses with their hands tied, they had sung all the way to police headquarters. Many expressed a renewed belief in their cause, and were glad that the eyes of the nation were on Columbia and Barnard , its sister college .

The protests, the arrests and the subsequent disciplinary action came a day after the congressional testimony this week of Columbia’s president, Nemat Shafik, at a hearing about antisemitism on campus. Columbia has said there have been a number of antisemitic episodes, including one attack, and many Jewish students have seen the protests as antisemitic.

Responding to aggressive questioning from the House committee, Columbia officials said some of the protesters on campus had used antisemitic language that might warrant discipline.

But on campus fury was building. The administration called in the Police Department to quell the protests. Arrests — at least 108 — soon followed.

The aggressive response left students shaken — but also, they say, energized.

Among the protesters, whose demands included that Columbia divest from companies connected to Israel, was one particularly high-profile name: Isra Hirsi, a Barnard student who is the daughter of Representative Ilhan Omar, Democrat of Minnesota.

At the congressional hearing on Wednesday, Ms. Omar had questioned Columbia administrators about their treatment of Palestinian and Muslim students. As Ms. Omar spoke in Washington, her daughter was in New York helping to organize the campus encampment of about 50 tents.

Ms. Hirsi, a junior, said in an interview that while she had been “mentally preparing” for being arrested, she was “shocked” at what actually unfolded. She left a precinct house at around 9:30 p.m. “So I was in zip ties for over seven hours,” she said.

Since being released, Ms. Hirsi, 21, said her professors had been supportive, although she was unsure what the future held. Still, she added that she was glad students had put a spotlight on the “hypocrisy coming from the Columbia University administration.”

“Everybody is invigorated,” she said.

“Even at this moment in time, they’re still holding down the south lawn,” she continued. “I think it’s beautiful.”

The next several weeks will be an uncertain period for those who were arrested, as well as for the university’s leaders. Many student protesters remained defiant after the arrests and vowed to continue their demonstrations.

For the unknown number of students who were suspended, a major shake-up looms as the semester ends.

Police officials said the students had received summonses for trespassing. The students said they expected to make initial court appearances next month. All of the students who were at the encampment have been suspended, university officials said, though it was not clear if every student at the encampment had been arrested.

The suspensions prohibit students from attending university events or getting into campus spaces, including dining halls, classrooms and libraries, the university said. It was not clear how long those prohibitions would last.

Some Barnard students said that they had received unexpected email warnings giving them 15 minutes to pack their belongings. Staff members would then escort any suspended students out of their dormitories, these students said they were told.

Some students, including Ms. Hirsi, said they were now bouncing between friends’ apartments. She said that she would fight her interim suspension. She said she had not yet returned to her room because doing so would require going with a chaperone from Barnard’s public safety team.

“I don’t really like the idea of that,” Ms. Hirsi said. “It makes me feel like more of a criminal than I think that I am.”

On Friday, Ms. Omar posted a message on social media saying that her daughter was not a lawbreaker, but a leader. She wrote that she was “enormously proud of her” for “pushing her school to stand against genocide.”

“Stepping up to change what you can’t tolerate is why we as a country have the right to speech, assembly, and petition enshrined in our constitution,” Ms. Omar wrote.

In a sharp editorial published this week , the campus newspaper, The Columbia Daily Spectator, denounced Dr. Shafik’s decision to arrest students and called on her to do more to protect protesters who have been doxxed, saying she had “demonstrated a complete lack of consistency in enforcing her principles, failing to differentiate between speech she personally opposes and speech warranting suppression.”

Dr. Shafik, who goes by Minouche, said in a letter on Thursday announcing her decision to summon the Police Department that the encampment had disrupted campus life and had created an atmosphere of intimidation.

Dr. Shafik said of calling in the police that she had taken “this extraordinary step because these are extraordinary circumstances.”

But many of the protesters, including several Jewish students, objected to the administration’s characterization of the tent demonstration. One Ph.D. candidate at Columbia who declined to give her last name said she was standing by the morals and ethics her Jewish faith had ingrained in her — not menacing her classmates.

Another Jewish sophomore at the university, Iris Hsiang, said it was the college — rather than her peers — that had made her feel unsafe. Her only crime, she said, was “sitting and singing on the lawns.”

She added that the coming commemoration of Passover, which marks Jewish freedom from slavery in Egypt, weighed on her. It was part of why she felt compelled to join the encampment.

“Judaism means standing for the liberation of all people,” she said. “And ‘never again’ means never again for anyone."

Ms. Hsiang was among the students who were shuffled into a series of holding cells and processed at police headquarters over the course of eight hours. Men and women were split up, and officers eventually cut off some of the zip ties. A number of Muslim students struggled to find space for their daily prayers, protesters said.

The Police Department did not respond to a request for comment.

The mood was anxious at times. But the students said they tried to maintain their morale.

“We were chanting all the way through until we were put in our cells,” said Marie Adele Grosso, a 19-year-old Barnard student.

Ms. Grosso said she joined the encampment in part to follow a model of activism her family had set. Her family has loved ones in Gaza.

“I’ve known for a while that this is something I would be willing to be arrested for,” she said.

When her grandmother heard about what had happened on campus, she sent her a text.

“She was proud of me,” Ms. Grosso said.

Eryn Davis and Karla Marie Sanford contributed reporting.

Troy Closson reports on K-12 schools in New York City for The Times. More about Troy Closson

Anna Betts reports on national events, including politics, education, and natural or man-made disasters, among other things. More about Anna Betts

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Community Based Nurs Midwifery
• v.4(1); 2016 Jan

The Effect of Health Belief Model-Based Education on Knowledge and Prostate Cancer Screening Behaviors: A Randomized Controlled Trial

Maryam zare.

1 Department of Community Health Nursing, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran

Fariba Ghodsbin

2 Student Research Committee, Community Based Psychiatric Care Research Center, Department of Community Health Nursing, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran

Iran Jahanbin

3 Community Based Psychiatric Care Research Center, Department of Community Health Nursing, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran

Ali Ariafar

4 Urology Oncology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Sareh Keshavarzi

5 Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

Tayyebe Izadi

6 Department of Medical and Surgical Nursing, School of Nursing and Midwifery, Tabriz University of Medical Sciences, Tabriz, Iran

Background:

Prostate cancer has been reported as the second leading cause of cancer death among men in 2013. Prevention and early detection of cancer are considered as critical factors in controlling the disease and increasing the survival of patients. Therefore, we aimed to investigate the effect of Health Belief Model (HBM)-based education on knowledge and prostate cancer screening behaviors in a randomized controlled trial.

This study was a non-blinded randomized controlled trial. We enrolled 210 men aged 50-70. Balanced block randomization method was used to randomize the final participants who had inclusion criteria into intervention (n=93) and control (n=87) groups. The participants of the intervention group attended training workshops based on HBM. Data were collected using three questionnaires, i.e. demographic questionnaire, Prostate Cancer Screening-Health Belief Model Scale (PCS-HBMS), and the Knowledge about Prostate Cancer Screening questionnaire, all given before and immediately one month after the intervention.

The mean scores of the perceived susceptibility, severity, barriers and benefits increased significantly after the intervention (P>0.05) in the intervention group. In the control group, such a difference was reported only for perceived susceptibility (P>0.05). The rate of participation in prostate cancer screening in the intervention group increased from 7.5% to 24% and 43.3% one month and three months after the intervention, respectively.

Conclusion:

Our findings showed that the health education programs designed based on HBM could positively affect prostate cancer preventive behaviors of individuals by improving their knowledge level and leaving positive effects on perceived susceptibility and severity as well as considering the perceived barriers, benefits and health motivations.

Trial Registration Number: IRCT2013090911691N3

I NTRODUCTION

Studies have reported that men are more prone to diseases and have a higher mortality rate than women. 1 Previous investigations have shown that men adopt more inappropriate lifestyle choices, are less concerned about their health, ignore the warning signs of the disease, and also have late referral to medical centers compared with women. 1

According to the official census published by American Cancer Society, prostate cancer was reported as the second leading cause of cancer death among American men after lung cancer and its incidence ranked the first among all cancers in 2013. 2 However, in Iran, the rate of deaths from prostate cancer is found relatively higher than other types of cancers. Remarkably, with 1309 deaths in 2013, its mortality rate was estimated as 3.85 per 100.000 men in the same year. According to statistical surveys, this was higher than that of esophageal and laryngeal cancer but lower than that of gastric, lung and bronchial cancer. 3

Based on the published statistics, its age-standardized incidence rate in Iran during 2003 to 2008 was reported as 4.69, 7.16, 14.04, 16.65, and 16.02 per 100,000 men, respectively, indicating an increasing trend of the disease in Iran during the mentioned years. 4 About 97% of all prostate cancers occur in men aged 50 and older. 2

Prostate cancer is fully and definitely treatable if diagnosed and detected early before the metastasis of the disease. Since such a cancer is often asymptomatic, it is diagnosed after its progress to the later stage that is incurable. At this stage, it has no definite treatment, so the mortality rate increases. 5 In 2013, the American Cancer Society recommended that men aged older than 50 should be aware about screening for early prostate cancer detection and those who are at risk of developing the disease should receive information about such screening at earlier ages. Ethnicity, a family history of the disease, age and obesity are known as the risk factors of this cancer. 2

Despite being asymptomatic, prostate cancer can be detected early using various diagnostic methods. Digital Rectal Examination (DRE) and Prostatic-Specific Antigen (PSA) are routine testing techniques for early prostate cancer diagnosis. Transrectal Ultrasound (TRUS- guided prostate biopsy is also another most commonly used method of diagnosing the disease. 6

Furthermore, prevention and early detection of cancer are considered as critical factors in controlling the disease and increasing the survival of patients. Therefore, the importance of public health education should be emphasized in developing countries where people have inadequate information about screening methods. 7

Various studies have shown that men with higher levels of knowledge show higher tendency towards such screening . 3 When counseling and education is done based on a specific protocol, it could lead to a change in people’s behavior. 8

Health Belief Model (HBM) has been widely used to measure the health beliefs and behaviors about cancer screening. HBM is a cognitive model that tries to identify patterns of healthy behavior. The perceived susceptibility , severity, benefits, and barriers are four main components of the HBM. Behavior was explained by the HBM as ensuing from the combination of attitudes associated with four concepts.

Perceived susceptibility refers to beliefs about the probability of obtaining a disease or condition.

Perceived Severity: Feelings concerning the seriousness of acquiring a sickness or of leaving it untreated embody evaluations of each medical and clinical consequence (for example, death, disability, and pain) and potential social consequences (such as effects of the work, domestic life, and social relations).

Perceived Benefits focus on the effectiveness of healthy behavior in reducing the threat of the condition. 9 , 10

Perceived Barriers is the potential negative aspects of a particular health behavior, a kind of unconscious, cost-benefit analysis occurring when the individuals know the perceived barriers are more costly than the perceived benefits; then, they take action to do screening. For example, these barriers can be expensive, time consuming, unpleasant, painful or upsetting. These barriers may lead a person away from performing the healthy action.

In addition to the four original concepts, health motivation has also been used as part of the HBM in predicting health related behavior. Health motivation refers to a generalized state of intent that results in behaviors to maintain or improve health. This concept was first introduced for inclusion in the HBM by Becker. The concept of health motivation used in combination with the original four HBM concepts has evidence of significant predictive ability. 10

Therefore, in this study we used HBM focusing on prevention as a reference framework. Currently, there is a lack of consideration towards men’s health, especially the middle-aged and elderly ones. Due to the increasing number of cases with prostate cancer reported by clinical specialists, which are caused by the late referral of the patients, we aimed to investigate the effect of HBM-based education with the purpose of increasing knowledge and the health belief about prostate cancer and prostate cancer screening behaviors.

M ATERIALS AND M ETHODS

This study was approved by the Ethics Committee of Shiraz University of Medical Sciences (Ethics Committee Approval Number: CT-92-6721). In this non-blinded randomized controlled trial, 210 men aged 50-70 were enrolled during April to October 2013. We selected our participants from the population of men who were retired from Shiraz Department of Education, using a simple random sampling method. The researcher referred to the list of the males retired from Shiraz Education Department, using table of random numbers. Their positive and broader insights towards research projects could facilitate easy accessibility to them for further follow-ups and evaluation of the results. Shiraz General Department of Retirement Affairs was chosen as research setting due to the large number of referrals for welfare and administrative affairs.

The sample size was calculated as 105 in each group based on the data of similar studies and using Power SSC statistical software (power: 80%, α: 0.05, mean difference: 1.6, loss rate=20% and SD: 3.2). A simple random sampling method was used to select 210 participants. Quadri- Balanced block randomization method was used to randomize the participants into intervention and control groups. In this study, we had two groups of control and intervention. Therefore, we used two variables, A and B, for them, respectively. By taking two variables A and B in quaternary blocks, six modes of movement were possible. According to the sample size (210), 53 blocks were needed. Then, the blocks were randomly written on paper and the researcher referred to the list of men and placed them in the blocks. Afterwards, 30 men were excluded due to their withdrawal from participation in the study, so the number of final participants was 93 and 87 in the intervention and control groups, respectively ( figure 1 ).

CONSORT Flow diagram of participants

Inclusion criteria were willingness to participate in the study, giving written informed consent, no history of prostate cancer and prostatic hyperplasia with obvious clinical symptoms, age of 50 to 70 years, and lack of severe vision and hearing impairment. However, exclusion criteria were absence in training sessions and participation in similar training courses.

After explaining the aims of the study, written informed consent was obtained from all the participants and their anonymity and confidentiality were guaranteed. Data were collected by the researcher and a trained research assistant through face to face interview by using three different questionnaires including demographic questionnaire, Prostate Cancer Screening- Health Belief Model Scale (PCS-HBM) and the Knowledge Prostate Cancer Screening questionnaire.

The demographic questionnaire was developed by the researcher; it included 13 questions about demographic characteristics of the participants. The questionnaire provided information about age, marital status, educational level and monthly income, history of prostate cancer and prostatic hyperplasia with obvious clinical symptoms, history of undergoing prostate cancer screening using DRE and PSA testing, a family history of the mentioned cancer, knowledge about the disease as well as the methods of acquiring knowledge about it for researcher.

The Prostate Cancer Screening Knowledge questionnaire was developed by Weinrich et al. (2004) and contained 12 questions. Each question had three options “true”, “false” and “I don’t know”. The correct responses were scored 1 and the wrong ones and those answered “I don’t know” were scored 0. Scores ranged from 0 to 12 with higher scores reflecting a higher level of knowledge. Scores lower than 7, 7-9 and 10-12 were considered as low, intermediate, and good, respectively. 11

Prostate Cancer Screening-Health Belief Model Scale (PCS-HBM)which was designed by Capik and Gozum (2011) included 41 items with a 5 point Likert scale anchored at 1=completely disagree and 5=completely agree. The scale consisted of 41 questions and 5 sub-scales including perceived susceptibility (5 items), perceived severity (5 items), health motivations (10 items), perceived barriers (15 items), and perceived benefits (7 items). An increase in the scores for the sub-scales of susceptibility, severity, motivation and benefit and a decrease in the score for the sub-scale of barriers reflected the positive effect of the intervention. 12

PCS-HBM and Prostate Cancer Screening Knowledge questionnaire were translated in Persian using back translation technique, which includes the use of a panel of experts and interpreters to translate the items from the source language to the target language and then they were back-translated to the source language. Then, some changes were made to adapt this instrument to Iranian culture.

After performing a pilot study on 30 men retired from Shiraz Department of Education, the reliability coefficient for PCS-HBM and Prostate Cancer Screening Knowledge questionnaires was calculated, using Cronbach alpha and Kuder Richardson 20technique. After analyzing the data, Kuder Richardson 20 coefficient was calculated as 0.98 for the Knowledge Prostate Cancer Screening Questionnaire and Cronbach’s alpha was calculated as 0.83 for PCS-HBM questionnaire.

To assess the prostate cancer screening behaviors of men in the intervention group, they were given referral forms for free consultation with a urologist and prostate cancer screening. Subsequently, the participation rate of men, who had not been screened within the last year, was examined one and three months after the intervention.

Afterwards, the participants of the intervention group attended training workshops consisting of two four-hour sessions for two days, in groups of 15 participants. The educational program was designed based on pre-test results and structures of health belief model. Educational intervention was performed in the intervention group through lecture, group discussion with questions and answers, and brain storming. The learning process was facilitated by teaching aids, such as videos, photos and booklets.

In the first session, first lecture method was employed due to little information in most of the subjects to make them familiar with prostate cancer, its anatomy, physiology, functions of prostate gland, pathology, and effective risk factors. Then, we used perceived susceptibility structure, talked about the incidence and prevalence rate of prostate cancer in Iran and the world, signs and symptom of prostate cancer, and the current treatment modalities of prostate cancer. Then, with regard to adults’ education theory which considered free discussion as a necessary part of education, the subjects held group discussion. Then, by considering the perceived severity, those whose parents, relatives or a close friend had died as a result of prostate cancer were invited to talk about the severity of the complications of prostate cancer as someone who had experienced it. Next, group members freely discussed about their experiences about complications of prostate cancer. Finally, the complications of the lack of health, especially low levels of primary and secondary prevention, were discussed by the participants.

In the second session, first lecture method was employed due to low level of information in most of the subjects to make them familiar with methods of prostate cancer screening. The subjects had group discussion on benefits and advantages of prostate cancer screening in prevention of prostate cancer, treatability of prostate cancer in the early stage, and cost efficacy of prostate cancer prevention.

In order to help the subjects to brain storm in education, all the inhibiting obstacles in unimportant subjects’ complications of diagnosis of prostate cancer and positive predictive value(PPV) and negative predictive value (NPV) of PSA test were indicated and related strategies were mentioned. Then, the clients discussed about the ear of prostate cancer screening. CDs and slides were shown. Finally, the referral center for prostate cancer screening was introduced to the clients.

All the participants filled out the questionnaires at baseline and after one month. The men participating in the control group received no planned educational program, but the intervention sessions were offered to this group after the study was completed. The collected data were analyzed using SPSS software, version 18. Statistical qualitative tests, Analysis of Covariance (ANCOVA), Chi-square, independent and paired t-test were used as appropriate. The significance level was set at <0/05.

The age range of the participants was 50-70 years and their mean±SD age was 58.1±4.8 and 56.8±5.3 in the intervention and control groups, respectively. Independent t-test showed no significant difference between the two groups with respect to their age P=0.08. 95% of the participants were married. There was a significant difference between the groups in terms of educational level and monthly income; those in the intervention group had a higher educational level and income compared of the participants in the control group (P>0.05).

Regarding the randomized allocation of the participants, the results of ANCOVA showed that the significant difference found between the groups in terms of income and educational level had no compounding effect on the study. The rate of the participants who had no family history of prostate cancer and no experience of undergoing DRE and PSA testing for prostate cancer screening was reported 87.2%, 95.6% and 85.6%, respectively. 86.1% of the men had no knowledge about such screening; however, the other respondents knew about it and reported television (48%), magazines and newspapers (20%), a family member with the same disease (12%), radio (8%), physicians (8%), and friends (4%) as their source of knowledge.

According to table 1 which compares the knowledge level between the intervention and control groups before and after the intervention, 95.7% of the men in the intervention group were at low and intermediate levels before the intervention, while their levels improved to intermediate and good after the intervention. Nevertheless, we observed no significant changes in the control group in this regard ( table 1 ).

Comparison of knowledge level between the intervention and control groups before and after the intervention

Paired t-test showed a statistically significant difference in the mean score of HBM components in the intervention group after being compared with that before the intervention (P>0.05). In the control group, such difference was reported only for perceived susceptibility (P>0.05), while there was no statistically significant difference in the mean scores of perceived severity, barriers, benefits, and motivation (P>0.05).

Independent t-test revealed a statistically significant difference between the intervention and control groups with respect to the mean scores of the perceived susceptibility, severity, barriers and benefits after the intervention (P>0.05) compared with before it (P>0.05). The results of the data analysis showed a statistically significant difference between the intervention and control groups regarding the mean scores of knowledge and motivation before the intervention (P>0.05).

To reach a more accurate result (to control the significance effect of the mean scores of knowledge and HBM components in the intervention and control groups before the intervention), the mean difference scores were compared after the intervention. According to the result of independent t-test, a statistically significant difference was observed between the groups with respect to the mean scores of all HBM components after the intervention (P<0.001) ( table 2 ).

Comparison of the mean score (±SD) of HBM components and knowledge between the intervention and control groups

Paired t-test indicated a significant difference in the mean score of knowledge in the intervention group after the intervention compared with before it (P<0.001), while no significant differences (despite a slight change) were observed in the control group (P=0.808).

The participation rate of men in screening before the intervention, one month and three months after the intervention is shown in table 3 .

The men participating in the intervention group in the screening

D ISCUSSION

The primary objective of this study was to increase participation in the screening and for this aim education based on the health belief model was implemented; then, we investigated the levels of knowledge, scores of the health belief components about prostate cancer, and the rate of participating retired men in prostate cancer screening.

86.1% of the retired men in this study had no knowledge about prostate cancer screening. Similarly, in a study which was conducted in North Florida, 0.83% African American men had some knowledge about prostate cancer screening and 17% did not have any knowledge about it. 13 Another study also indicated that 58% of male New Yorkers were aware of prostate cancer screening in 2000. 14

In our study and another study in Iran, the history of prostate cancer screening was 8.6% and 14.4%, respectively. 15 This rate in the studies by Kris et al. (2007) was 67%; Allen et al.’s study (2010) reported 44%; and in Sheridan (2012) it was reported 59%. 16 - 18

Comparison of the results of these studies with those of our study indicates a low level of awareness about prostate cancer screening and low participation rate in prostate cancer screening among Iranian men.

Our findings were consistent with other studies indicating the significant increase of individuals’ knowledge level about prostate cancer after the intervention. 17 , 19 - 22

A study which was done in Turkey with this tool did not find a significant difference in the level of knowledge in men after an educational intervention by the web. 23 Therefore, it can be concluded that for 50 to 70 year old men, face to face training and the group training could be more effective.

In another study, it was confirmed that print arm is more effective than web arm and usual care to improve knowledge and reduce decisional conflicts about prostate cancer screening. 24

All the aforementioned studies confirmed the importance of education and its effects on promoting the level of the individuals’ knowledge. We also observed a significant increase in the mean score of perceived susceptibility in the intervention group following the educational intervention and such result was similar to other studies on prostate cancer screening, diabetes mellitus and breast self-examination. 23 , 25 - 27

Moreover, most of our participants believed that they might be at risk of prostate cancer. Carmel had a critical review on 46 HBM-related investigations and concluded that “perceived susceptibility” could be the most powerful factor in predicting the behaviors. 28

As to the perceived susceptibility, the belief that the disease can occur without any symptoms leads to initiation of screening behaviors. 29 In our study, the mean score of such a component increased in the control group. Bakhtariaghdam et al. also reached a similar result and suggested it could be due to the fact that taking the pre-test had made the respondents sensitive to the subject. 30 However, Ghaffari et al. believed that it resulted from the curiosity of the participants in the control group to evaluate and complete the questionnaire at the pre-test stage. 31 Similarly, we can conclude that such increase lies in the curiosity of the participants to find out more about the disease and increase their knowledge about it during the interval between pre-test and post-test phases which makes them sensitive to the subjects discussed in the questionnaire.

Reminding our participants of serious complications and the chronic nature of prostate cancer and considering loss of health and the problems caused by such disease as well as high costs of treatment have been important factors which led to improvement of their level of perceived severity. Several investigations showed that evaluation of clinical outcomes by the individuals could also affect this component. 29

Moreover, we found a significant difference between the two groups after the intervention in terms of perceived severity. This finding was in agreement with other studies on the effect of HBM-based education on osteoporosis preventive behaviors and breast self-examination. 29 , 32

Furthermore, independent t-test showed a statistically significant difference between the intervention and control groups with respect to the mean score of perceived benefits after the intervention. Other researchers found similar results in examining the effect of HBM-based educational program on urinary tract infection and Acquired Immune Deficiency Syndrome preventive behaviors. 33 , 34

We believe that medical and health care staff should constantly consult with men about the risk of prostate cancer progression and benefits of screening. Men should also talk with the staff about their fears and obstacles which prevent them from participating in screening programs as it can increase their responsibility for their own health. There are two factors which can facilitate the men’s participation in prostate cancer screening:

• 1- The belief that DRE and PSA tests help diagnose the disease before the appearance of symptoms.
• 2- The belief that early diagnosis and treatment can improve the prognosis of the disease. 35

In the incidence of preventive behaviors, perceived barriers are directly associated with early diagnosis and participation in prostate cancer screening, 23 while education can remove such barriers and make men take action for early detection of the disease. 36

According to both retrospective and prospective studies, “perceived barriers” is found to be the most powerful dimension of HBM in the expression and prediction of health protective behaviors. 29 We observed a significant difference between the groups regarding the mean score of “perceived barriers”. Likewise, other researchers found a significant decrease in the dimension of “perceived barriers” after HBM-based educational intervention in their studies on prostate cancer screening and nutritional behaviors associated with gastric cancer. 23 , 37

Moreover, we tried to decrease the barriers significantly by increasing the participants’ knowledge through education and providing free screening and consulting with a urologist. According to the results, the mean scores of health motivation appeared as significantly different between the groups. Our finding was similar to that of Capık and Gözüm who found an increase in the motivation mean score; however, such increase was not statistically significant. 23

Insignificant increase of motivation could be attributed to the participants’ low levels of knowledge and lack of sufficient information about prostate cancer and screening. Therefore, the significant increase of motivation in our study could be due to the proper knowledge level in the intervention group after training sessions and the efficiency of our educational intervention compared with internet and web-based education for men aged over 50.

Capık and Gözüm reported that the rate of participation in the screening increased after the educational intervention. 23 Furthermore, another study indicated that 48% of the participants who had not been screened within the last year were referred for screening again. 19 Similarly, Weinrich et al. observed that 71.8% of those in the intervention group participated in free screening due to educational intervention. 38

We found out that the participation rate in such screening increased from 7.5% to 24% and 43.3% one month and three months after the intervention, respectively. Finally, we observed that 36 men, who had not been screened within the last year, participated in prostate cancer screening.

One limitation of the present study was the post-test one month after the intervention. Therefore, assessing information in several time intervals after the interventions is recommended in order to examine the long-term effects of interventions on prostate cancer screening behaviors and participation in decision-making regarding the subject. It is also recommended that the follow-up periods of screening should be increased to one year. Further investigations are also required to find out the most important potential barriers to prostate cancer screening in Iran.

Another limitation of this study was selecting the samples from among a particular group of people such as teachers. It appears that the level of education and knowledge is so much higher than the general population. It is recommended that in future studies samples should be chosen from various groups of people such as rural ones to obtain more generalizable results.

C ONCLUSION

Our findings showed that the health education programs designed based on HBM could positively affect the prostate cancer preventive behaviors of our retired participants by improving their knowledge level and HBM components. Hence, we could confirm the efficacy of HBM in adopting the prostate cancer screening behaviors by the participants. Since this type of cancer is treatable in early stages, more attention should be paid to the educational design and planning based on educational theories and models so that we could increase the required knowledge about prostate cancer for early diagnosis and treatment of the disease.

A CKNOWLEDGEMENT

The present article was extracted from the thesis written by Ms. Maryam Zare and financially supported by Shiraz University of Medical Sciences (Grants no 6721). The authors hereby would like to thank Shiraz general department of retirement affairs and all the people who took part in this investigation.

Conflict of Interest: None declared.

R EFERENCES