Sun, Dec 7, 2025
[Archive]
Volume 18, Issue 4 (2025)
JMED 2025, 18(4): 83-91 |
Back to browse issues page
Ethics code: IR.JMU.REC.1403.062
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Pournarani R, Movahed E, Faryabi R, nasiri N. Psychological factors affecting self-regulated learning among students: an application of the health action process approach. JMED 2025; 18 (4) :83-91
URL: http://edujournal.zums.ac.ir/article-1-2549-en.html
URL: http://edujournal.zums.ac.ir/article-1-2549-en.html
1- Department of Public Health, School of Health, Jiroft University of Medical Sciences, Jiroft, Iran , rezanarani732@gmail.com
2- Department of Public Health, School of Health, Jiroft University of Medical Sciences, Jiroft, Iran
2- Department of Public Health, School of Health, Jiroft University of Medical Sciences, Jiroft, Iran
Abstract: (211 Views)
Background & Objective: Self-Regulated Learning (SRL) helps students do better in school and stay more interested in learning. This study looked at mental factors that affect SRL among students using the Health Action Process Approach (HAPA).
Materials & Methods: This study used a method where data was collected at one point in time. We chose 194 students in 2025 using a multi-stage sampling method. We collected data using two main tools: a standard SRL questionnaire and a researcher-made questionnaire based on HAPA ideas related to SRL. We looked at the data using basic math and multiple regression analysis, with results considered important at p < 0.05.
Results: The analysis showed that risk awareness (Beta = 0.23) and action confidence (Beta = 0.46) strongly predicted SRL intention in the motivation phase, explaining 53% of changes. In the action phase, intention (Beta = 1.39), action planning (Beta = 0.80), and coping planning (Beta=0.60) predicted 49% of SRL strategy changes. In the maintenance phase, maintenance confidence (Beta = 1.44) predicted 56% of SRL changes.
Conclusion: HAPA ideas strongly predicted students' starting, using, and keeping up with SRL strategies. These findings suggest that HAPA's theory framework should be used to help students keep using SRL strategies in school settings.
Materials & Methods: This study used a method where data was collected at one point in time. We chose 194 students in 2025 using a multi-stage sampling method. We collected data using two main tools: a standard SRL questionnaire and a researcher-made questionnaire based on HAPA ideas related to SRL. We looked at the data using basic math and multiple regression analysis, with results considered important at p < 0.05.
Results: The analysis showed that risk awareness (Beta = 0.23) and action confidence (Beta = 0.46) strongly predicted SRL intention in the motivation phase, explaining 53% of changes. In the action phase, intention (Beta = 1.39), action planning (Beta = 0.80), and coping planning (Beta=0.60) predicted 49% of SRL strategy changes. In the maintenance phase, maintenance confidence (Beta = 1.44) predicted 56% of SRL changes.
Conclusion: HAPA ideas strongly predicted students' starting, using, and keeping up with SRL strategies. These findings suggest that HAPA's theory framework should be used to help students keep using SRL strategies in school settings.
Article Type : Orginal Research |
Subject:
Education
Received: 2025/07/29 | Accepted: 2025/11/8 | Published: 2025/11/19
Received: 2025/07/29 | Accepted: 2025/11/8 | Published: 2025/11/19
References
1. Hadi Alsherify MJ, Hassani M. The effectiveness of self-regulated learning strategies on academic self-efficacy, academic motivation, concern and academic achievement. J Psychol Sci. 2025;24(151):77-94.
2. Ozcan M. Factors affecting students' academic achievement according to the teachers' opinion. Educ Reform J. 2021;6(1):1-18 [DOI:10.22596/erj2021.06.01.1.18]
3. Bisri A, Heryatun Y, Navira A. Educational data mining model using support vector machine for student academic performance evaluation. J Educ Learn (EduLearn). 2025;19(1):478-86. [DOI:10.11591/edulearn.v19i1.21609]
4. Hidayatullah A, Csíkos C. Association between psychological need satisfaction and online self-regulated learning. Asia Pac Educ Rev. 2025;26(3):609-19. [DOI:10.1007/s12564-023-09910-9]
5. Abdelhalim SM. An investigation into English majors' self-regulated writing strategies in an online learning context. Lang Teach Res. 2025;29(4):1715-52. [DOI:10.1177/13621688221100296]
6. Dignath C, Veenman MV. The role of direct strategy instruction and indirect activation of self-regulated learning-Evidence from classroom observation studies. Educ Psychol Rev. 2021;33(2):489-533. [DOI:10.1007/s10648-020-09534-0]
7. Zimmerman BJ, Schunk DH. Self-regulated learning and performance. In: Zimmerman BJ, Schunk DH, editors. Handbook of self-regulation of learning and performance. 2nd ed. New York: Routledge; 2011. p. 1-12.
8. Torrington J, Bower M, Burns EC. Elementary students' self‐regulation in computer‐based learning environments: How do self‐report measures, observations and teacher rating relate to task performance?. Br J Educ Technol. 2024;55(1):231-58. [DOI:10.1111/bjet.13338]
9. Woods NN, Mylopoulos M, Brydges R. Informal self-regulated learning on a surgical rotation: uncovering student experiences in context. Adv Health Sci Educ. 2011;16:643-53. [DOI:10.1007/s10459-011-9285-4] [PMID]
10. Schunk DH. Self-regulated learning: the educational legacy of Paul R. Pintrich. Educ Psychol. 2005;40:85-94. [DOI:10.1207/s15326985ep4002_3]
11. Li L, Zhu ML, Shi YQ, Yang LL. Influencing factors of self-regulated learning of medical-related students in a traditional Chinese medical university: a cross-sectional study. BMC Med Educ. 2023;23(1):87. [DOI:10.1186/s12909-023-04051-4] [PMID] []
12. Albelbisi NA, Yusop FD. Factors influencing learners' self-regulated learning skills in a massive open online course (MOOC) environment. Turk Online J Distance Educ. 2021;20(3):1-16. [DOI:10.17718/tojde.598191]
13. Jouhari Z, Haghani F, Changiz T. Factors affecting self-regulated learning in medical students: a qualitative study. Med Educ Online. 2015;20(1):28694. [DOI:10.3402/meo.v20.28694] [PMID] []
14. Schunk DH. Commentary on self-regulation in school contexts. Learn Instr. 2005;15:173-7. [DOI:10.1016/j.learninstruc.2005.04.013]
15. Maleki B, Hosseini SA. The causal model of self-regulated learning in students based on academic self-efficacy and motivational beliefs: the mediating role of psychological capital. J Mod Psychol Res. 2024;18(72):267-77.
16. Schwarzer R. Modeling health behavior change: how to predict and modify the adoption and maintenance of health behaviors. Appl Psychol. 2008;57(1):1-29.
https://doi.org/10.1111/j.1464-0597.2008.00361.x [DOI:10.1111/j.1464-0597.2007.00325.x]
17. Faryabi R, Pournarani R, Movahed E. Adherence of hypertension patients to self-care behaviors based on the health action process approach in Southern Iran. Health Educ Health Promot. 2025;13(2):357-62.
18. Mei J, Xie Y, Huang P, Jin Y, Wang X, Chen Y. The effects of HAPA theory-based case management in patients with metabolic dysfunction-associated steatotic liver disease. Ann Hepatol. 2025;30(2):101790. [DOI:10.1016/j.aohep.2025.101790] [PMID]
19. Pournarani R, Movahed E, Faryabi R, Mehralizadeh A. Investigating factors related to the self-efficacy of parenting skills among mothers in Jiroft City, Kerman Province, Iran. J Health Syst Res. 2025;21(2):183-90.
20. Pournarani R, Faryabi R, Mehralizadeh SD, Yoshany N. Factors influencing substance use relapse in people referring to addiction recovery centers in Jiroft, Kerman. J Educ Community Health. 2023;10(3):173-8. [DOI:10.34172/jech.2147]
21. Liang W, Liu G, Su N, Rhodes RE, Duan Y, Zhang CQ, et al. Understanding parental support for children's 24-hour movement behaviors based on an adapted HAPA framework: a three-wave prospective study. Appl Psychol Health Well-Being. 2025;17(3):e70034. [DOI:10.1111/aphw.70034] [PMID] []
22. Rezaei Rad M, Zarofian F, Majani N, Rezaei Rad M. The relationship of self-efficacy with self-regulated learning in the virtual education of students during the Covid-19 epidemic. J Nurs Educ. 2023;12(2):15-24.
23. Moradi Doliskani M, Yonespour Z, Poya M. The effect of flipped classroom teaching on self-regulatory learning strategies and learning motivation components in research method course among the staff of AJA research center. New Educ Approaches. 2021;16(2):99-116.Zhang CQ, Zhang R, Schwarzer R, Hagger MS. A meta-analysis of the health action process approach. Health Psychol. 2019;38(7):623-37. [DOI:10.1037/hea0000728] [PMID]
24. Mohammadi Zeidi I, Morshedi H, Shokohi A. Predicting psychological factors affecting regular physical activity in hypertensive patients: application of health action process approach model. Nurs Open. 2021;8(1):442-52. [DOI:10.1002/nop2.645] [PMID] []
25. Zhou G, Gan Y, Knoll N, Schwarzer R. Proactive coping moderates the dietary intention-planning-behavior path. Appetite. 2013;70:127-33.Radtke T, Kaklamanou D, Scholz U, Hornung R, Armitage CJ. Are diet-specific compensatory health beliefs predictive of dieting intentions and behaviour? Appetite. 2014;76:36-43. [DOI:10.1016/j.appet.2013.06.097] [PMID]
26. Joveini H, Dehdari T, Hashemian M, Maheri M, Shahrabadi R, Rohban A, et al. Effects of an educational intervention on male students' intention to quit water pipe smoking: an application of the theory of planned behavior (TPB) and health action process approach (HAPA). J Educ Community Health. 2020;7(2):73-80. [DOI:10.29252/jech.7.2.73]
27. Moghimi S, Payandeh A, Seraji M. The effect of educational intervention based on the health behavior process approach model in medication adherence of patients with type two diabetes. Iran J Health Educ Health Promot. 2024;12(2):142-54.
28. Beharu WT. Psychological factors affecting students academic performance among freshman psychology students in Dire Dawa University. J Educ Pract. 2018;9(4):59-65.
29. Schwarzer R, Luszczynska A. How to overcome health-compromising behaviors: the health action process approach. Eur Psychol. 2008;13(2):141-51. [DOI:10.1027/1016-9040.13.2.141]
30. Zhang CQ, Chung PK, Liu JD, Chan DK, Hagger MS, Hamilton K. Health beliefs of wearing facemasks for influenza A/H1N1 prevention: a qualitative investigation of Hong Kong older adults. Asia Pac J Public Health. 2019;31(3):246-56. [DOI:10.1177/1010539519844082] [PMID]
31. Vornanen M, Konttinen H, Peltonen M, Haukkala A. Diabetes and cardiovascular disease risk perception and risk indicators: a 5-year follow-up. Int J Behav Med. 2021;28(3):337-48. [DOI:10.1007/s12529-020-09924-2] [PMID] []
32. Gholami M, Knoll N, Schwarzer R. A meta-analysis of the health action process approach to physical activity. In: Gellert P, editor. Self-regulation and health behavior across the lifespan. 1st ed. Gottingen: Hogrefe Publishing; 2014. p. 71-88.
33. Rouvere J, Blanchard BE, Johnson M, Griffith Fillipo I, Mosser B, Romanelli M, et al. Application of an adapted health action process approach model to predict engagement with a digital mental health website: cross-sectional study. JMIR Hum Factors. 2024;11:e57082. [DOI:10.2196/57082] [PMID] []
34. Baghiani Moghaddam MH, Norouzi S, Morowatisharifabad MA, Norouzi A. Evaluation of the health action process approach to improve mothers' parenting skills. J Health Syst Res. 2014;9(14):1815-28. Available from:
35. Schwarzer R, Richert J, Kreausukon P, Remme L, Wiedemann AU, Reuter T. Translating intentions into nutrition behaviors via planning requires self-efficacy: evidence from Thailand and Germany. Int J Psychol. 2010;45(4):260-8. [DOI:10.1080/00207591003674479] [PMID]
36. Mazloomy Mahmoodabad SS, Gerayllo S, Khaleghi Moori M, Yoshany N, Mizani N. Determinants of skin cancer prevention behaviors in Yazd students: an application of the extended parallel process model. Tolooe Behdasht. 2020;19(5):21-32. [DOI:10.18502/tbj.v19i5.5176]
37. Mohammadi S, Baghiani Moghadam MH, Noorbala MT, Mazloomi SS, Fallahzadeh H, Daya A. Survey about the role of appearance concern with skin cancer prevention behavior based on protection motivation theory. J Dermatol Cosmet. 2010;1(2):70-7. Available from:
38. Joveini H, Rohban A, Eftekhar Ardebili H, Dehdari T, Maheri M, Hashemian M. The effects of an education program on hookah smoking cessation in university students: an application of the Health Action Process Approach (HAPA). J Subst Use. 2020;25(1):62-9. [DOI:10.1080/14659891.2019.1664655]
39. Hamilton K, Smith SR, Keech JJ, Moyers SA, Hagger MS. Application of the health action process approach to social distancing behavior during COVID-19. Appl Psychol Health Well-Being. 2020;12(4):1244-69. [DOI:10.1111/aphw.12231] [PMID] []
40. Mohammadi Zeidi B, Kariman N, Kashi Z, Mohammadi Zeidi I, Alavi Majd H. Predictors of physical activity following gestational diabetes: application of health action process approach. Nurs Open. 2020;7(4):1060-6. [DOI:10.1002/nop2.486] [PMID] []
41. Rhodes RE, Grant S, de Bruijn GJ. Planning and implementation intention interventions. In: Hagger MS, Cameron LD, Hamilton K, Hankonen N, Lintunen T, editors. The handbook of behavior change. Cambridge: Cambridge University Press; 2020. p. 478-94.
42. Labudek S, Fleig L, Jansen CP, Kramer-Gmeiner F, Nerz C, Becker C, et al. Applying social cognition models to explain walking duration in older adults: the role of intrinsic motivation. J Aging Phys Act. 2021;29(5):744-52. [DOI:10.1123/japa.2020-0296] [PMID]
43. Xu H, Su C, Ji Y, Yin F, Yang Y, Yang S, et al. Predicting physical exercise changes in Chinese rural adolescents: the application of the health action process approach model. Psychol Health Med. 2020;25(5):639-51. [DOI:10.1080/13548506.2019.1709653] [PMID]
44. Moodi M, Sharifzadeh G. Factors affecting physical activity behavior based on Transtheoretical Model in the employees of Birjand universities in 2014. J Birjand Univ Med Sci. 2014;21(3):352-61. Available from:
45. Jasemzadeh M, Jaafarzadeh N, Khafaie MA, Malehi AS, Araban M. Predicator of pregnant women's self-care behavior against air pollution: an explanation based on the extended parallel process model (EPPM). Electron Physician. 2016;8(9):2871-7. [DOI:10.19082/2871] [PMID] []
46. Ng B, Wang CJ, Liu WC. Motivational-cognitive profiles of learners: cluster movement. Pers Individ Dif. 2015;85:128-33. [DOI:10.1016/j.paid.2015.04.047]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
