Modelling Longitudinal Directional Associations Between Self-regulation, Physical Activity, and Habit: Results from a Cross-lagged Panel Model



The directionality of associations between self-regulatory variables, behavior, and automaticity is seldomly tested. In this study, we aimed to examine a volitional, self-regulatory sequence of variables proposed in the Health Action Process Approach framework (intention → action plans → action control → behavior) and its relationship with the construct of automaticity of the physical activity habit.


Longitudinal data was collected from high school students (N = 203, Mage = 15.39 (SD = 1.43), 52% women) at three measurement points. First, a confirmatory factor analysis measurement model was used to examine the study variables across measurement points. Next, a cross-lagged panel model was used to test directionality between variables.


After adequate fit of the measurement model was confirmed, a mechanism integrating self-regulation with behavior and automaticity was examined. The hypothesized directionality between variables was verified overall by cross-lagged analysis. However, for the intention-action plan association, the inverse relationship was found: plans were associated with subsequent intentions, but intentions did not predict plans. Moreover, automaticity was not associated with subsequent physical activity behavior.


In general, our findings supported the hypothesized longitudinal direction of the associations, confirming that self-regulation may lead to behavior performance and automaticity. Unexpected findings and implications for intervention and future research are discussed.

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  1. 1.

    Pedersen BK, Saltin B. Exercise as medicine - evidence for prescribing exercise as therapy in 26 different chronic diseases. Scand J Med Sci Sport. 2015;25(3):1–72.

    Article  Google Scholar 

  2. 2.

    World Health Organization. Global recommendations on physical activity for health. Geneva World Heal Organ [Internet]. 2010; Available from:

  3. 3.

    Owens S, Galloway R, Gutin B. The case for vigorous physical activity in youth. Am J Lifestyle Med. 2017;11(2):96–115.

    PubMed  Article  Google Scholar 

  4. 4.

    Costigan SA, Lubans DR, Lonsdale C, Sanders T, Del Pozo Cruz B. Associations between physical activity intensity and well-being in adolescents. Prev Med (Baltim). 125:55–61.

  5. 5.

    Physical Activity Guidelines Advisory Committee. 2018 Physical Activity Guidelines Advisory Committee Scientific Report. US Department of Health and Human Services. 2018.

  6. 6.

    Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants. Lancet Child Adolesc Heal. 2020;4(1):23–35.

    Article  Google Scholar 

  7. 7.

    Shull ER, Dowda M, Saunders RP, McIver K, Pate RR. Sport participation, physical activity and sedentary behavior in the transition from middle school to high school. J Sci Med Sport. 2020;23(4):385–9.

    PubMed  Article  Google Scholar 

  8. 8.

    Ryu S, Kim H, Kang M, Pedisic Z, Loprinzi PD. Secular trends in sedentary behavior among high school students in the United States, 2003 to 2015. Am J Heal Promot. 2019;33(8):1174–81.

    Article  Google Scholar 

  9. 9.

    Bray SR, Born HA. Transition to university and vigorous physical activity: implications for health and psychological well-being. J Am Coll Heal. 2004;52(4):181–8.

    Article  Google Scholar 

  10. 10.

    Miller J, Pereira M, Wolfson J, Laska M, Nelson T, Neumark-Sztainer D. Developmental trends and determinants of physical activity from adolescence to adulthood differ by ethnicity/race and sex. J Phys Act Heal. 2018;15(5):345–54.

    Article  Google Scholar 

  11. 11.

    Telama R, Yang X, Leskinen E, Kankaanpää A, Hirvensalo M, Tammelin T, et al. Tracking of physical activity from early childhood through youth into adulthood. Med Sci Sports Exerc. 2014;46(5):955–62.

    PubMed  Article  Google Scholar 

  12. 12.

    Davis R, Campbell R, Hildon Z, Hobbs L, Michie S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol Rev. 2015;9(3):323–44.

    PubMed  Article  Google Scholar 

  13. 13.

    Lally P, Gardner B. Promoting habit formation. Health Psychol Rev. 2013;7(1):137–58.

    Article  Google Scholar 

  14. 14.

    Zhang CQ, Zhang R, Schwarzer R, Hagger MS. A meta-analysis of the health action process approach. Heal Psychol. 2019;38(7):623–37.

    Article  Google Scholar 

  15. 15.

    Kearney MW. Cross-lagged panel analysis. In: Allen M, editor. The SAGE encyclopedia of communication research methods [Internet]. Thousand Oaks, California; 2017. p. 313–4. Available from:

  16. 16.

    Cole DA, Maxwell SE. Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling. J Abnorm Psychol. 2003;112(4):558–77.

    PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Hayes AF. Introduction to mediation, moderation, and conditional process analysis. Second Edi. New York, NY: Guilford. 2017. 1–692 p.

  18. 18.

    Reyes Fernández B, Fleig L, Godinho CA, Montenegro Montenegro E, Knoll N, Schwarzer R. Action control bridges the planning-behaviour gap: a longitudinal study on physical exercise in young adults. Psychol Health [Internet]. 2015;30(8):911–23. Available from:

  19. 19.

    Godinho CA, Alvarez MJ, Lima ML, Schwarzer R. Will is not enough: coping planning and action control as mediators in the prediction of fruit and vegetable intake. Br J Health Psychol. 2014;19(4):856–70.

    PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Fleig L, Pomp S, Parschau L, Barz M, Lange D, Schwarzer R, et al. From intentions via planning and behavior to physical exercise habits. Psychol Sport Exerc. 2013;14(5):632–9.

    Article  Google Scholar 

  21. 21.

    Kwasnicka D, Dombrowski SU, White M, Sniehotta F. Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories. Health Psychol Rev. 2016;10(3):277–96.

    PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Mazar A, Wood W. Defining habit in psychology. In: Verplanken B, editor. The psychology of habit. Cham: Springer; 2018. p. 13–29.

    Google Scholar 

  23. 23.

    Gardner B. A review and analysis of the use of “habit” in understanding, predicting and influencing health-related behaviour. Health Psychol Rev. 2015;9(3):277–95.

    Article  Google Scholar 

  24. 24.

    Gardner B. Habit as automaticity, not frequency. Eur Heal Psychol. 2012;14(2):32–6.

    Google Scholar 

  25. 25.

    Prochaska JO, DiClemente C. Transtheoretical therapy: toward a more integrative model of change. Psychother Theory Res Pract [Internet]. 1982;19(3):276–88. Available from:

  26. 26.

    Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.

    Article  Google Scholar 

  27. 27.

    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.

    Article  Google Scholar 

  28. 28.

    Gardner B, Rebar AL. Habit formation and behavior change. In: Oxford research encyclopedia of psychology. USA: Oxford University Press; 2019.

  29. 29.

    Sevil J, García-González L, Abós Á, Generelo E, Aibar A. Can high schools be an effective setting to promote healthy lifestyles? Effects of a multiple behavior change intervention in adolescents. J Adolesc Heal. 2019;64(4):478–86.

    Article  Google Scholar 

  30. 30.

    Prochaska JO, DiClemente C. The transtheoretical approach. In: Norcross JC, Goldfried MR, editors. Handbook of psychotherapy integration. 2nd ed. Oxford University Press; 2005. p. 147–71.

  31. 31.

    Lally P, Van Jaarsveld CHM, Potts HWW, Wardle J. How are habits formed: modelling habit formation in the real world. Eur J Soc Psychol. 2010.

  32. 32.

    Orbell S, Verplanken B. The automatic component of habit in health behavior: habit as cue-contingent automaticity. Heal Psychol. 2010;29(4):374–83.

    Article  Google Scholar 

  33. 33.

    Sniehotta FF, Scholz U, Schwarzer R. Bridging the intention-behaviour gap: planning, self-efficacy, and action control in the adoption and maintenance of physical exercise. Psychol Heal. 2005;20(2):143–60.

    Article  Google Scholar 

  34. 34.

    Sheeran P, Webb TL. The intention–behavior gap. Soc Personal Psychol Compass. 2016;10(9):503–18.

    Article  Google Scholar 

  35. 35.

    Sheeran P. Intention—behavior relations: a conceptual and empirical review. Eur Rev Soc Psychol [Internet]. 2002;12(1):1–36. Available from:

  36. 36.

    Reyes Fernández B, Knoll N, Hamilton K, Schwarzer R. Social-cognitive antecedents of handwashing: action control bridges the planning–behaviour gap. Psychol Heal. 2016;31(8):993–1004.

    Article  Google Scholar 

  37. 37.

    Allen M. Cross-lagged panel analysis. In: The SAGE encyclopedia of communication research methods. 2017.

  38. 38.

    Gardner B, Abraham C, Lally P, de Bruijn GJ. Towards parsimony in habit measurement: testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index. Int J Behav Nutr Phys Act. 2012;9(1):112–23.

    Article  Google Scholar 

  39. 39.

    Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, et al. The physical activity guidelines for Americans. JAMA - J Am Med Assoc. 2018;320(19):2020–8.

    Article  Google Scholar 

  40. 40.

    Luszczynska A, Cao DS, Malach N, Pietron K, Mazurkiewicz, M. Schwarzer R. Intentions, planning, and self-efficacy predict physical activity in Chinese and Polish adolescents: two moderated mediation analyses. Int J Clin Heal Psychol. 2010;10(2):265–78.

  41. 41.

    Barz M, Parschau L, Warner LM, Lange D, Fleig L, Knoll N, et al. Planning and preparatory actions facilitate physical activity maintenance. Psychol Sport Exerc. 2014;15(5):516–20.

    Article  Google Scholar 

  42. 42.

    Kline RB. Principles and practice of structural equation modeling. New York: The Guilford Press; 2011.

    Google Scholar 

  43. 43.

    Little T. Longitudinal structural equation modeling. New York: Guilford Press; 2013.

    Google Scholar 

  44. 44.

    Landis RS, Beal DJ, Tesluk PE. A comparison of approaches to forming composite measures in structural equation models. Organ Res Methods. 2000;3:186–207.

    Article  Google Scholar 

  45. 45.

    Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International Physical Activity Questionnaire (IPAQ): 12-country reliability and validity. Med Sci Sport Exerc. 2003;35(8):1381–95.

    Article  Google Scholar 

  46. 46.

    Hallal PC, Gomez LF, Parra DC, Lobelo F, Mosquera J, Florindo AA, et al. Lessons learned after 10 years of IPAQ use in Brazil and Colombia. J Phys Act Heal. 2010;7(2):259–64.

    Article  Google Scholar 

  47. 47.

    van Bree RJH, Mudde AN, Bolman C, van Stralen MM, Peels DA, de Vries H, et al. Are action planning and physical activity mediators of the intention-habit relationship? Psychol Sport Exerc. 2016;27:243–51.

    Article  Google Scholar 

  48. 48.

    Verplanken B, Orbell S. Reflections on past behavior: a self-report index of habit strength. J Appl Soc Psychol [Internet]. 2003;33(6):1313–30. Available from:

  49. 49.

    Reyes Fernández B, Monge-Rojas R, Solano López AL, Cardemill E. Re-evaluating the self report habit index: the cases of physical activity and snacking habits. Psychol Health. 2019;34(10):1161–78.

    PubMed  Article  Google Scholar 

  50. 50.

    Kremers SPJ, Brug J. Habit strength of physical activity and sedentary behavior among children and adolescents. Pediatr Exerc Sci. 2008;20(1):5–17.

    PubMed  Article  Google Scholar 

  51. 51.

    Tabachnick BG, Fidell LS. Using multivariate statistics (6th ed.). Using multivariate statistics 5th ed. Pearson; 2014.

  52. 52.

    Weston R, Gore PAJ. A brief guide to structural equation modeling. Couns Psychol. 2006;34(5):719–51.

    Article  Google Scholar 

  53. 53.

    Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2014;43(1):115–35.

    Article  Google Scholar 

  54. 54.

    Ertl MM, Rentería R, Dillon FR, Babino R, De La Rosa M, Brenner RE. Longitudinal associations between marianismo beliefs and acculturative stress among Latina immigrants during initial years in the United States. J Couns Psychol. 2019.

  55. 55.

    Graham JW. Missing data analysis: making it work in the real world. Annu Rev Psychol. 2009;60:549–76.

    PubMed  Article  Google Scholar 

  56. 56.

    Enders CK. Using the expectation maximization algorithm to estimate coefficient alpha for scales with item-level missing data. Psychol Methods. 2003;8(3):322–37.

    PubMed  Article  Google Scholar 

  57. 57.

    Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B. 1977;39(1):1–38.

    Google Scholar 

  58. 58.

    Arbuckle J. Ibm Spss Amos 19: user’s guide. IBM Spss Amos. 2010.

  59. 59.

    Hu LT, Bentler PM. Cut-off criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55.

    Article  Google Scholar 

  60. 60.

    Marsh HW, Hau KT, Wen Z. In search of golden rules: comment on hypothesis-testing approaches to setting cut-off values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Struct Equ Model. 2004;11(3):320–41.

    Article  Google Scholar 

  61. 61.

    Cangur S, Ercan I. Comparison of model fit indices used in structural equation modeling under multivariate normality. J Mod Appl Stat Methods. 2015;79(11):532–40.

    Google Scholar 

  62. 62.

    Hooper D, Coughlan J, Mullen MR. Structural equation modelling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6(1):53–60.

    Google Scholar 

  63. 63.

    Heene M, Hilbert S, Draxler C, Ziegler M, Bühner M. Masking misfit in confirmatory factor analysis by increasing unique variances: a cautionary note on the usefulness of cut-off values of fit indices. Psychol Methods. 2011;16(3):319–36.

    PubMed  Article  Google Scholar 

  64. 64.

    West SG, Finch JF, Curran PJ. Structural equation models with nonnormal variables: problems and remedies. In: Structural equation modeling: concepts, issues and applications. 1995. p. 56–75.

  65. 65.

    Kaushal N, Rhodes RE, Meldrum JT, Spence JC. The role of habit in different phases of exercise. Br J Health Psychol. 2017;22(3):429–48.

    PubMed  Article  Google Scholar 

  66. 66.

    Sniehotta FF. Towards a theory of intentional behaviour change: plans, planning, and self-regulation. Br J Health Psychol. 2009;14(2):261–73.

    PubMed  Article  Google Scholar 

  67. 67.

    Lhakhang P, Hamilton K, Sud N, Sud S, Kroon J, Knoll N, et al. Combining self-management cues with incentives to promote interdental cleaning among Indian periodontal disease outpatients. BMC Oral Health. 2016;16(1).

  68. 68.

    Verplanken B, Roy D. Empowering interventions to promote sustainable lifestyles: testing the habit discontinuity hypothesis in a field experiment. J Environ Psychol. 2016;45(Suppl C):127–34.

    Article  Google Scholar 

  69. 69.

    Hagger MS, Luszczynska A. Implementation intention and action planning interventions in health contexts: state of the research and proposals for the way forward. Appl Psychol Heal Well-Being. 2014;6(1):1–47.

    Article  Google Scholar 

  70. 70.

    Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Heal Psychol. 2009;28(6):690–701.

    Article  Google Scholar 

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Correspondence to Benjamín Reyes Fernández.

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As per Costa Rican legislation, parental informed consent and adolescent informed assent were obtained for all participants included in the study. All procedures performed in studies involving human subjects were in accordance with the standards of the Ethical Review Committee and the 1964 Declaration of Helsinki and its amendments.

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Monge-Rojas, R., Godinho, C.A. & Reyes Fernández, B. Modelling Longitudinal Directional Associations Between Self-regulation, Physical Activity, and Habit: Results from a Cross-lagged Panel Model. Int.J. Behav. Med. (2020).

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  • Physical activity
  • Automaticity
  • Habit
  • Self-regulation
  • HAPA model