Active lifestyles in older adults: an integrated predictive model of physical activity and exercise

Federica Galli, Andrea Chirico, Luca Mallia, Laura Girelli, Michelino De Laurentiis, Fabio Lucidi, Antonio Giordano, Gerardo Botti, Federica Galli, Andrea Chirico, Luca Mallia, Laura Girelli, Michelino De Laurentiis, Fabio Lucidi, Antonio Giordano, Gerardo Botti

Abstract

Physical activity and exercise have been identified as behaviors to preserve physical and mental health in older adults. The aim of the present study was to test the Integrated Behavior Change model in exercise and physical activity behaviors. The study evaluated two different samples of older adults: the first engaged in exercise class, the second doing spontaneous physical activity. The key analyses relied on Variance-Based Structural Modeling, which were performed by means of WARP PLS 6.0 statistical software. The analyses estimated the Integrated Behavior Change model in predicting exercise and physical activity, in a longitudinal design across two months of assessment. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research.

Keywords: Gerotarget; exercise; health; older adults; physical activity; well-being.

Conflict of interest statement

CONFLICTS OF INTEREST No conflicts of interest for all the authors of the study.

Figures

Figure 1. The Integrated Behavior Change model…
Figure 1. The Integrated Behavior Change model linking perceived autonomy support, autonomous motivation, attitudes, subjective norms, perceived behavioral control, intention and planning on behavior
Figure 2. The Integrated Behavior Change model…
Figure 2. The Integrated Behavior Change model linking perceived autonomy support, autonomous motivation, attitudes, subjective norms, perceived behavioral control, intention and planning on Exercise behavior
Note Standardized path coefficients for the structural equation model estimated controlling for behavior measured at Time 1 are reported in parentheses. The effects of past behavior measured at Time 1 on each variable in the model figure were omitted for clarity. These paths were freely estimated in the VB-SEM analysis but not depicted in diagram: past behavior → perceived autonomy support (β = –.15, p = .017); past behavior → autonomous motivation (β = .21, p = .001); past behavior → attitude (β = –.09, p = .11); past behavior → subjective norm (β = –.32, p < .001); past behavior → perceived behavioral control (β = .06, p = .207); past behavior → intention (β = .13, p =.03); past behavior → planning (β = .22, p < .001); past behavior → behavior at Time 2 (β = .49, p < .001). Dashed lines indicate paths that were not statistically significant (p > .05) in the SEM analysis without controlling for past behavior. ***p < .001; **p < .01; *p < .05.
Figure 3. The Integrated Behavior Change model…
Figure 3. The Integrated Behavior Change model linking perceived autonomy support, autonomous motivation, attitudes, subjective norms, perceived behavioral control, intention and planning on Physical Activity behavior
Note: Standardized path coefficients for the structural equation model estimated controlling for behavior measured at Time 1 are reported in parentheses. The effects of past behavior measured at Time 1 on each variable in the model figure were omitted for clarity. These paths were freely estimated in the VB-SEM analysis but not depicted in diagram: past behavior → perceived autonomy support (β = .31, p < .001); past behavior → autonomous motivation (β = .31, p < .001); past behavior → attitude (β = .28, p < .001); past behavior → subjective norm (β = .18, p = .032); past behavior → perceived behavioral control (β = .31, p < .001); past behavior → intention (β = .14, p =.07); past behavior → planning (β = .25, p =.005); past behavior → behavior at Time 2 (β = .65, p < .001). Dashed lines indicate paths that were not statistically significant (p > .05) in the SEM analysis without controlling for past behavior. ***p < .001; **p <.001; *p <.05.

References

    1. He W, Goodkind D, Kowal P. An Aging World: 2015. International Population Reports. U.S. Government Printing Office, Washington DC. 2016. .
    1. United Nations, Department of Economic and Social Affairs World Population Prospects: the 2015 Revision. New York, 2015.
    1. ISTAT Statistiche Istat. 2017.
    1. North MS, Fiske ST. Modern attitudes toward older adults in the aging world: a cross-cultural meta-analysis. Psychol Bull. 2015;141:993–1021. .
    1. Paterson D, Warburton D. Physical activity and functional limitations in older adults: a systematic review related to Canada’s Physical Activity Guidelines. Int J Behav Nutr Phys Act. 2010;7:38. .
    1. Bouaziz W, Vogel T, Schmitt E, Kaltenbach G, Geny B, Lang PO. Health benefits of aerobic training programs in adults aged 70 and over: a systematic review. Arch Gerontol Geriatr. 2017;69:110–27. .
    1. Lindwall M, Larsman P, Hagger MS. The reciprocal relationship between physical activity and depression in older European adults: A prospective cross-lagged panel design using share data. Health Psychol. 2011;30:453–62. .
    1. Dionigi R. Competitive sport and aging: the need for qualitative sociological research. J Aging Phys Act. 2006;14:365–79. .
    1. Alsaleh E, Windle R, Blake H. Behavioural intervention to increase physical activity in adults with coronary heart disease in Jordan. BMC Public Health. 2016;16:643. .
    1. Dogra S, Weir P, Gayman A, Horton S. Aging across the physical activity spectrum: from sedentary behaviour to sport participation. J Exerc Mov Sport. 2016;48:162.
    1. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100:126–31. .
    1. Pot N, Keizer R. Physical activity and sport participation: A systematic review of the impact of fatherhood. Prev Med Rep. 2016;4:121–27. .
    1. WHO Regional Office for Europe. Italy: Physical Activity Factsheet; 2015
    1. Rhodes RE, Pfaeffli LA. Mediators of physical activity behaviour change among adult non-clinical populations: a review update. Int J Behav Nutr Phys Act. 2010;7:37. .
    1. Rhodes RE, De Bruijn GJ. How big is the physical activity intention-behaviour gap? A meta-analysis using the action control framework. Br J Health Psychol. 2013;18:296–309. .
    1. Deci EL, Ryan RM. Intrinsic motivation and self-determination in human behavior. Springer US. 1985 .
    1. Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991;50:179–211. .
    1. Schwarzer R, Luszczynska A. How to overcome health-compromising behaviors: the health action process approach. Eur Psychol. 2008;13:141–51. .
    1. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55:68–78. .
    1. Ryan RM, Williams GC, Patrick H, Deci EL. Self-determination theory and physical activity: the dynamics of motivation in development and wellness. Hell J Psychol. 2009;6:107–24. .
    1. Reifsteck EJ, Gill DL, Labban JD. “Athletes” and “exercisers”: understanding identity, motivation, and physical activity participation in former college athletes. Sport Exerc Perform Psychol. 2016;5:25–38. .
    1. Girelli L, Hagger M, Mallia L, Lucidi F. From perceived autonomy support to intentional behaviour: testing an integrated model in three healthy-eating behaviours. Appetite. 2016;96:280–92. .
    1. Hagger MS, Chatzisarantis NL, Culverhouse T, Biddle SJ. the processes by which perceived autonomy support in physical education promotes leisure-time physical activity intentions and behavior: a trans-contextual model. J Educ Psychol. 2003;95:784–95. .
    1. Gutin B, Yin Z, Humphries MC, Barbeau P. Relations of moderate and vigorous physical activity to fitness and fatness in adolescents. Am J Clin Nutr. 2005;81:746–50. .
    1. Dacey M, Baltzell A, Zaichkowsky L. Older adults’ intrinsic and extrinsic motivation toward physical activity. Am J Health Behav. 2008;32:570. .
    1. Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM. Exercise, physical activity, and self-determination theory: A systematic review. Int J Behav Nutr Phys Act. 2012;9:78. .
    1. Fishbein M. A theory of reasoned action: some applications and implications. Nebr Symp Motiv. 1980;27:65–116.
    1. Young MD, Plotnikoff RC, Collins CE, Callister R, Morgan PJ. Social cognitive theory and physical activity: A systematic review and meta-analysis. Obes Rev. 2014;15:983–95. .
    1. Armitage CJ. Can the Theory of Planned Behavior predict the maintenance of physical activity? Health Psychol. 2005;24:235–45. .
    1. Hagger MS, Chatzisarantis NL, Biddle SJ. A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: predictive validity and the contribution of additional variables. J Sport Exerc Psychol. 2002;24:3–32. .
    1. Lucidi F, Grano C, Barbaranelli C, Violani C. Social-cognitive determinants of physical activity attendance in older adults. J Aging Phys Act. 2006;14:344–59. .
    1. Motalebi SA, Iranagh JA, Abdollahi A, Lim WK. Applying of theory of planned behavior to promote physical activity and exercise behavior among older adults. J Phys Educ Sport. 2014;14:562–68. .
    1. Schwarzer R. Self-Efficacy: Thought Control of Action. Hemisphere Publishing Corporation; 1992. Self-efficacy in the adoption and maintenance of health behaviors:theorectical approaches and a new model; pp. 217–44.
    1. Bandura A. Self-efficacy mechanism in human agency. Am Psychol. 1982;37:122–47. .
    1. Heckhausen H, Gollwitzer PM. Thought contents and cognitive functioning in motivational versus volitional states of mind. Motiv Emot. 1987;11:101–20. .
    1. Hattar A, Hagger MS, Pal S. Weight-loss intervention using implementation intentions and mental imagery: a randomised control trial study protocol. BMC Public Health. 2015;15:196. .
    1. Bélanger-Gravel A, Godin G, Amireault S. A meta-analytic review of the effect of implementation intentions on physical activity. Health Psychol Rev. 2013;7:23–54. .
    1. Maher JP, Conroy DE. A dual-process model of older adults’ sedentary behavior motivation underlying sedentary behavior. Health Psychol. 2016;35:262–72. .
    1. Hagger MS, Chatzisarantis NL. Integrating the theory of planned behaviour and self-determination theory in health behaviour: A meta-analysis. Br J Health Psychol. 2009;14:275–302. .
    1. Hagger MS, Chatzisarantis NL. The trans-contextual model of motivation. In: Hagger MS, Chatzisarantis NL, editors. Intrinsic motivation and self-determination in exercise and sport. Champaign, IL, US: Human Kinetics; 2007. pp. 53–70,309–313.
    1. Hagger MS, Chatzisarantis NL. An integrated behavior change model for physical activity. Exerc Sport Sci Rev. 2014;42:62–69. .
    1. Norman P, Conner M. The Theory of Planned Behavior and Exercise: evidence for the mediating and moderating roles of planning on intention-behavior relationships. J Sport Exerc Psychol. 2005;27:488–504. .
    1. Wiedemann AU, Schu B, Sniehotta F, Scholz U, Schwarzer R. Disentangling the relation between intentions, planning, and behaviour: A moderated mediation analysis. Psychol Health. 2009;24:67–79. .
    1. Mullan BA, Wong C, Kothe EJ. Predicting adolescents’ safe food handling using an extended theory of planned behavior. Food Control. 2013;31:454–60. .
    1. Hagger MS, Sultan S, Hardcastle SJ, Chatzisarantis NL. Perceived autonomy support and autonomous motivation toward mathematics activities in educational and out-of-school contexts is related to mathematics homework behavior and attainment. Contemp Educ Psychol. 2015;41:111–23. .
    1. Hagger MS, Chatzisarantis NL, Biddle SJ. The influence of autonomous and controlling motives on physical activity intentions within the Theory of Planned Behaviour. Br J Health Psychol. 2002;7:283–97. .
    1. Ajzen I. Residual effects of past on later behavior: habituation and reasoned action perspectives. Personal Soc Psychol Rev. 2002;6:107–22. .
    1. Ouellette JA, Wood W. Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior. Psychol Bull. 1998;124:54–74. .
    1. Sutton S. The past predicts the future: Interpreting behaviour–behaviour relationships in social psychological models of health behaviour. In: Rutter D, Quine L, editors. Social psychology and health: European perspectives. Brookfield, VT, UD: Avebury/Ashgate Publishing Co.; 1994. pp. 71–88.
    1. Ryan RM, Connell JP. Perceived locus of causality and internalization: examining reasons for acting in two domains. J Pers Soc Psychol. 1989;57:749–61. .
    1. Hambleton RK, Patsula L. Adapting tests for use in multiple languages and cultures. Soc Indic Res. 1998;45:153–71. .
    1. Hagger MS, Chatzisarantis NL, Hein V, Pihu M, Soós I, Karsai I. The perceived autonomy support scale for exercise settings (PASSES): development, validity, and cross-cultural invariance in young people. Psychol Sport Exerc. 2007;8:632–53. .
    1. Ng A, Kennedy P, Hutchinson B, Ingram A, Vondrell S, Goodman T, Miller D. Self-efficacy and health status improve after a wellness program in persons with multiple sclerosis. Disabil Rehabil. 2013;35:1039–44. .
    1. Markland D, Tobin V. A modification to the behavioural regulation in exercise questionnaire to include an assessment of amotivation. J Sport Exerc Psychol. 2004;26:191–96. .
    1. Verloigne M, De Bourdeaudhuij I, Tanghe A, D’Hondt E, Theuwis L, Vansteenkiste M, Deforche B. Self-determined motivation towards physical activity in adolescents treated for obesity: an observational study. Int J Behav Nutr Phys Act. 2011;8:97. .
    1. Wachter D, De Hert M. A review of physical activity correlates in patients with bipolar disorder. J Affect Disord. 2013;145:285–91. .
    1. 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 Health. 2005;20:143–60. .
    1. Godin G, Shephard RJ. Godin Leisure-Time Exercise Questionnaire. Med Sci Sports Exerc. 1997;29:36–38. .
    1. Kock N. WarpPLS User Manual Version 6.0. 2017 .
    1. Esposito Vinzi V, Chin WW, Henseler J, Wang H, editors. Handbook of partial least squares: concepts, methods and applications. Springer-Verlag Berlin Heidelberg. 2010. .
    1. Tenenhaus M, Vinzi VE, Chatelin YM, Lauro C. PLS path modeling. Comput Stat Data Anal. 2005;48:159–205. .

Source: PubMed

Sponzoři a spolupracovníci

Zdravotní podmínky

Drogové intervence

3
Předplatit