IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2020i1p28-d466730.html
   My bibliography  Save this article

Combining the Integrated-Change Model with Self-Determination Theory: Application in Physical Activity

Author

Listed:
  • Kei Long Cheung

    (Health Behaviour Change Research Group, Department of Health Sciences, College of Health and Life Sciences, Brunel University London, London UB8 3PH, UK)

  • Sander Matthijs Eggers

    (Central Bureau for Statistics (CBS), 6401CZ Heerlen, The Netherlands
    Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, 6200MD Maastricht, The Netherlands)

  • Hein de Vries

    (Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, 6200MD Maastricht, The Netherlands)

Abstract

Background : Critically testing and integrating theoretical models can aid health promotion research and intervention planning. This study aimed to critically compare and integrate Self-Determination Theory (SDT) and Integrated-Change Model (ICM) for explaining physical activity behaviour. Methods : A dataset was used with Dutch adults, consisting of information on demographics and socio–cognitive and behavioural determinants. There were three measurements over a period of six months, with the baseline sample consisting of 1867 participants. Confirmatory factor analysis was conducted to assess the reliability of the items and their corresponding scales. To examine cognitive pathways, we applied Structural Equation Modelling (SEM). Results : For SDT, none of the pathways were significant but the model fit was decent (R 2 = 0.20; RMSEA = 0.07; CFI = 0.91). For ICM, the model fit was similar (R 2 = 0.19; RMSEA = 0.07; CFI = 0.73), with many significant pathways, as stipulated by the theory. The integration of STD and ICM constructs revealed similar explained behavioural variance (R 2 = 21%), with no significantly different model fit. Conclusion : The integration of SDT and ICM added no value as a prediction model. However, the integrated model explains the underlying mechanism of STD constructs, as well as the determinants of attitude, social influences, and self-efficacy. In the context of intervention design, ICM or the integrated model seem most useful as it reveals the stages and pathways to behaviour change.

Suggested Citation

  • Kei Long Cheung & Sander Matthijs Eggers & Hein de Vries, 2020. "Combining the Integrated-Change Model with Self-Determination Theory: Application in Physical Activity," IJERPH, MDPI, vol. 18(1), pages 1-13, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2020:i:1:p:28-:d:466730
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/1/28/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/1/28/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dang Vu, Hoai Nam & Nielsen, Martin Reinhardt, 2022. "Understanding determinants of the intention to buy rhino horn in Vietnam through the Theory of Planned Behaviour and the Theory of Interpersonal Behaviour," Ecological Economics, Elsevier, vol. 195(C).
    2. Sara Manca & Ferdinando Fornara, 2019. "Attitude Toward Sustainable Transport as a Function of Source and Argument Reliability and Anticipated Emotions," Sustainability, MDPI, vol. 11(12), pages 1-10, June.
    3. Sebastian Kurten & David Winant & Kathleen Beullens, 2021. "Mothers Matter: Using Regression Tree Algorithms to Predict Adolescents’ Sharing of Drunk References on Social Media," IJERPH, MDPI, vol. 18(21), pages 1-16, October.
    4. Jonathan Jan Pieters & Alinda Kokkinou & Ton Kollenburg, 2022. "Understanding Blockchain Technology Adoption by Non-experts: an Application of the Unified Theory of Acceptance and Use of Technology (UTAUT)," SN Operations Research Forum, Springer, vol. 3(1), pages 1-19, March.
    5. Bouscasse, H. & Bonnel, P., 2016. "Socio-psychological determinants of mode choice habits," Working Papers 2016-05, Grenoble Applied Economics Laboratory (GAEL).
    6. Marjolein C. J. Caniëls & Wim Lambrechts & Johannes (Joost) Platje & Anna Motylska-Kuźma & Bartosz Fortuński, 2021. "50 Shades of Green: Insights into Personal Values and Worldviews as Drivers of Green Purchasing Intention, Behaviour, and Experience," Sustainability, MDPI, vol. 13(8), pages 1-18, April.
    7. Richard Blaese & Schneider Noemi & Liebig Brigitte, 2021. "Should I Stay, or Should I Go? Job satisfaction as a moderating factor between outcome expectations and entrepreneurial intention among academics," International Entrepreneurship and Management Journal, Springer, vol. 17(3), pages 1357-1386, September.
    8. Lea Marie Heidbreder & Julia Steinhorst & Manfred Schmitt, 2020. "Plastic-Free July: An Experimental Study of Limiting and Promoting Factors in Encouraging a Reduction of Single-Use Plastic Consumption," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    9. Shneor, Rotem & Munim, Ziaul Haque, 2019. "Reward crowdfunding contribution as planned behaviour: An extended framework," Journal of Business Research, Elsevier, vol. 103(C), pages 56-70.
    10. Hössinger, Reinhard & Peer, Stefanie & Juschten, Maria, 2023. "Give citizens a task: An innovative tool to compose policy bundles that reach the climate goal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    11. Leonidou, Leonidas C. & Eteokleous, Pantelitsa P. & Christofi, Anna-Maria & Korfiatis, Nikolaos, 2022. "Drivers, outcomes, and moderators of consumer intention to buy organic goods: Meta-analysis, implications, and future agenda," Journal of Business Research, Elsevier, vol. 151(C), pages 339-354.
    12. Ling Xu & Jianghua Liu, 2020. "The Turnover Intention among Grassroots Family Planning Staff in the Context of China’s Universal Two-Child Policy: A Case Study of the Xi’an City," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    13. Ricci, Elena Claire & Banterle, Alessandro & Stranieri, Stefanella, 2018. "Trust to Go Green: An Exploration of Consumer Intentions for Eco-friendly Convenience Food," Ecological Economics, Elsevier, vol. 148(C), pages 54-65.
    14. Manning, Mark & Lucas, Todd & Purrington, Kristen & Thompson, Hayley & Albrecht, Terrance L. & Penner, Louis, 2023. "Moderators of the effects of perceived racism and discrimination on cancer-related health behaviors among two samples of African Americans," Social Science & Medicine, Elsevier, vol. 316(C).
    15. Huang, Guei-Hua & Korfiatis, Nikolaos & Chang, Chun-Tuan, 2018. "Mobile shopping cart abandonment: The roles of conflicts, ambivalence, and hesitation," Journal of Business Research, Elsevier, vol. 85(C), pages 165-174.
    16. Manning, Mark & Albrecht, Terrance L. & Yilmaz-Saab, Zeynep & Penner, Louis & Norman, Andria & Purrington, Kristen, 2017. "Explaining between-race differences in African-American and European-American women's responses to breast density notification," Social Science & Medicine, Elsevier, vol. 195(C), pages 149-158.
    17. Andrzej Cwynar & Wiktor Cwynar & Monika Baryła-Matejczuk & Moises Betancort, 2019. "Sustainable Debt Behaviour and Well-Being of Young Adults: The Role of Parental Financial Socialisation Process," Sustainability, MDPI, vol. 11(24), pages 1-26, December.
    18. Raf Buyle & Mathias Van Compernolle & Eveline Vlassenroot & Ziggy Vanlishout & Peter Mechant & Erik Mannens, 2018. "“Technology Readiness and Acceptance Model” as a Predictor for the Use Intention of Data Standards in Smart Cities," Media and Communication, Cogitatio Press, vol. 6(4), pages 127-139.
    19. Djenna Hutmacher & Melanie Eckelt & Andreas Bund & Georges Steffgen, 2020. "Does Motivation in Physical Education Have an Impact on Out-of-School Physical Activity over Time? A Longitudinal Approach," IJERPH, MDPI, vol. 17(19), pages 1-18, October.
    20. Cindy Helinski & Gerhard Schewe, 2022. "The Influence of Consumer Preferences and Perceived Benefits in the Context of B2C Fashion Renting Intentions of Young Women," Sustainability, MDPI, vol. 14(15), pages 1-25, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2020:i:1:p:28-:d:466730. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.