The Psychometric Properties of the Health Belief Model Scale for Exercise in the Turkish Population

Abstract

Background and Purpose: Personal health and exercise belief is an essential component of creating physical activity and exercise programs. The Health Belief Model Scale for Exercise (HBSE) is an instrument that evaluates this component. Our study aims to translate the HBSE into Turkish and to investigate its psychometric properties in the adult population. Methods: After the translation process, we included 180 participants (age: 28 (25/36) years, gender: 115/65) in our study. Explanatory factor analysis was performed. Internal consistency was measured by Cronbach alpha and test-retest reliability was assessed using the intra-class correlation coefficient (ICC). Convergent, divergent, and known-groups validity (gender, educational level, marital status, and regular exercise habit) were used for construct validity. Results: Factor analysis indicated six factors (factor-loadings=0.664 to 0.900). Cronbach α coefficients ranged from 0.706 to 0.842 and ICC ranged from 0.710 to 0.956. It was seen that the HBSE subscores with the scales that were used for convergent validity had a moderate-strong correlation (Rho=0.614 to 752 and <0.001). Age and BMI were not related to the HBSE scores (p>0.05). The HBSE total scores were higher in women and the person whom with regular exercise habits (p<0.05). Conclusion: The results highlighted that the Turkish version of the HBSE is a reliable and valid instrument to assess exercise belief.

Keywords

• Health belief model
• physical activity
• exercise
• psychometrics.

The Psychometric Properties of the Health Belief Model Scale for Exercise in the Turkish Population

Abstract

References

1. Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh MA, et al. Exercise and physical activity for older adults. Med Sci Sports Exerc [Internet]. 2009;41(7):1510–1530.
2. Sallis R, Franklin B, Joy L, Ross R, Sabgir D, Stone J. Strategies for Promoting Physical Activity in Clinical Practice. Prog Cardiovasc Dis. 2015;57(4):375–386.
3. Bauman A, Merom D, Bull FC, Buchner DM, Fiatarone Singh MA. Updating the Evidence for Physical Activity: Summative Reviews of the Epidemiological Evidence, Prevalence, and Interventions to Promote “Active Aging.” Gerontologist. 2016;56 (2):S268–S280.
4. Sherwood NE, Jeffery RW. The behavioral determinants of exercise: implications for physical activity interventions. Annu Rev Nutr. 2000;20:21–44.
5. Glanz, Karen, Barbara K. Rimer KV. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. Karen Glanz, Barbara K. Rimer KV, editor. Vol. 116, Annals of Internal Medicine. John Wiley & Sons; 2008. p. 45–62.
6. Rahmati-Najarkolaei F, Tavafan SS, Fesharaki MG, Jafari MR. Factors predicting nutrition and physical activity behaviors due to cardiovascular disease in Tehran university students: application of health belief model. Iran Red Crescent Med J. 2015;17(3):1–6.
7. Dailey KD. Application of the health belief model to increase exercise behavior. California State University; Fullerton: 2001. p. 63.
8. Wu S, Feng X, Sun X. Development and evaluation of the health belief model scale for exercise. Int J Nurs Sci. 2020 Sep 10;7:S23–30.

9. Çiftçi N, Kadıoğlu H. Validity and Reliability of the Exercise Health Belief Model Scale. Clin Exp Heal Sci. 2020;10(4):369–374.
10. Ortabag T, Ceylan S, Akyuz A, Bebs H. The Validity and Reliability of the Exercise Benefits/Barriers Scale for Turkish Military Nursing Students. South African J Res Sport Phys Educ Recreat. 2010;32(2):55–70.
11. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res. 2010;19(4):539–549. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976). 2000;25(24):3186–3191.
12. Liu CC, Tsai LT. Factors Influencing Regular Exercise Habits of Women in Taiwan. Int J Environ Res Public Health. 2021;18(22):11960.
13. Sechrist KR, Walker SN, Pender NJ. Development and psychometric evaluation of the exercise benefits/barriers scale. Res Nurs Health. 1987;10(6):357–365.
14. Urdan T, Pajares F, editors. Guide for constructing self-efficacy scales. In: Self-Efficacy Beliefs of Adolescents. Information Age Publishing; 2006. p. 307–337.
15. Marcus BH, Rakowski W, Rossi JS. Assessing motivational readiness and decision making for exercise. Health Psychol. 1992;11(4):257–261.
16. Gümüş Y, Kitiş Y. The Validity and Reliability of Exercise Behavior Change Scales. J Hacettepe Univ Fac Nurs. 2015;3(2):1–19.
17. Huskisson EC. Measurement of Pain. Lancet. 1974;304(7889):1127–1131.
18. Howard MC. A Review of Exploratory Factor Analysis Decisions and Overview of Current Practices: What We Are Doing and How Can We Improve? Int J Hum-Comput Int. 2016;32(1):51–62.
19. Fitzpatrick R, Davey C, Buxton MJ, Jones DR. Evaluating patient-based outcome measures for use in clinical trials: a review. Health Technol Assess (Rockv). 1998;2(14): 1-74.
20. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 2016;15(2):155–163.
21. Schober P, Schwarte LA. Correlation Coefficients: Appropriate Use and Interpretation. Anesth Analg. 2018;126(5):1763–1768.
22. Terwee CB, Mokkink LB, Van Poppel MNM, Chinapaw MJM, Van Mechelen W, De Vet HCW. Qualitative attributes and measurement properties of physical activity questionnaires: a checklist. Sports Med. 2010;40(7):525–537.
23. Anthoine E, Moret L, Regnault A, Sbille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes. 2014;12:176.
24. Andresen EM. Criteria for assessing the tools of disability outcomes research. Arch Phys Med Rehabil. 2000;81(12 Suppl 2):S15-20.
25. Bujang MA, Baharum N. A simplified guide to determination of sample size requirements for estimating the value of intraclass correlation coefficient: A review. Arch Orofac Sci. 2017;12(1):1–11.
26. Bouma AJ, van Wilgen P, Dijkstra A. The barrier-belief approach in the counseling of physical activity. Patient Educ Couns. 2015;98(2):129–136.
27. Ha FJ, Hare DL, Cameron JD, Toukhsati SR. Heart Failure and Exercise: A Narrative Review of the Role of Self-Efficacy. Heart Lung Circ. 2018;27(1):22–27.
28. Prochaska JO, Velicer WF. The transtheoretical model of health behavior change. Am J Heal Promot. 1997;12(1):38–48.
29. Biddle SJ, Psychology C. Theories of exercise behavior. Int J Sport. 2000;31(2):290–304. Umberson D. Gender, marital status and the social control of health behavior. Soc Sci Med. 1992;34(8):907–917.
30. Lillard LA, Waite LJ. ’Til Death Do Us Part: Marital Disruption and Mortality. Am J Sociol. 2015;100(5):1131–1156.
31. Mao HY, Hsu HC, Lee S Da. Gender differences in related influential factors of regular exercise behavior among people in Taiwan in 2007: A cross-sectional study. PLoS One. 2020;15(1):e0228191.
32. Bauman A, Bull F, Chey T, Craig CL, Ainsworth BE, Sallis JF, et al. The International Prevalence Study on Physical Activity: results from 20 countries. Int J Behav Nutr Phys Act. 2009;6:21.
33. Chen YJ, Huang YH, Lu FH, Wu JS, Lin LL, Chang CJ, et al. The correlates of leisure time physical activity among an adults population from southern Taiwan. BMC Public Health. 2011;11:427.
34. Cheah YK, Poh BK. The determinants of participation in physical activity in malaysia. Osong public Heal Res Perspect. 2014;5(1):20–27.
35. Molanorouzi K, Khoo S, Morris T. Motives for adult participation in physical activity: type of activity, age, and gender. BMC Public Health. 2015;15:66.
36. Tsai LT, Lo FE, Yang CC, Keller JJ, Lyu SY. Gender differences in recreational sports participation among Taiwanese adults. Int J Environ Res Public Health. 2015;12(1):829–840.