IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i8p4700-d793083.html
   My bibliography  Save this article

Sense of Coherence Predicts Physical Activity Maintenance and Health-Related Quality of Life: A 3-Year Longitudinal Study on Cardiovascular Patients

Author

Listed:
  • Roberta Adorni

    (Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy)

  • Andrea Greco

    (Department of Human and Social Sciences, University of Bergamo, 24129 Bergamo, Italy)

  • Marco D’Addario

    (Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy)

  • Francesco Zanatta

    (Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy)

  • Francesco Fattirolli

    (Cardiac Rehabilitation Unit, Department of Medical and Surgical Critical Care, University of Florence, 50139 Florence, Italy
    Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy)

  • Cristina Franzelli

    (Cardiac/Pulmonary Rehabilitation, ASST Gaetano Pini-CTO, 20122 Milan, Italy)

  • Alessandro Maloberti

    (School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy
    Cardiology IV, “A. De Gasperis” Department, Ospedale Niguarda Ca’ Granda, 20162 Milan, Italy)

  • Cristina Giannattasio

    (School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy
    Cardiology IV, “A. De Gasperis” Department, Ospedale Niguarda Ca’ Granda, 20162 Milan, Italy)

  • Patrizia Steca

    (Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy)

Abstract

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. A physically active lifestyle can improve the health-related quality of life (HRQoL) of people with CVD. Nevertheless, adherence to a physically active lifestyle is poor. This study examined the longitudinal (pre-event, 6-, 12-, 24-, and 36-month follow-ups) physical activity profiles in 275 patients (mean age = 57.1 years; SD = 7.87; 84% men) after the first acute coronary event. Moreover, it investigated the associations among physical activity, sense of coherence (SOC), and HRQoL. Physical activity profiles were identified through latent class growth analysis, and linear regressions were then performed to explore the association between physical activity, SOC, and HRQoL. After the cardiovascular event, 62% of patients reached adequate physical activity levels and maintained them over time (virtuous profile). The remaining 38% could not implement (23%) or maintain (15%) a healthy behavior. A strong SOC at baseline (standardized β = 0.19, p = 0.002) predicted the probability of belonging to the virtuous profile. Moreover, a strong SOC at baseline (standardized β = 0.27, p < 0.001), together with the probability of belonging to the virtuous profile (standardized β = 0.16, p = 0.031), predicted a better HRQoL at the final follow-up. Findings showed a strong relationship between SOC, the ability to adopt a physically active lifestyle stably over time, and HRQoL in patients with CVD. They suggest the importance of tailoring physical activity interventions by promoting resilience resources such as SOC to improve patients’ quality of life after an acute coronary event.

Suggested Citation

  • Roberta Adorni & Andrea Greco & Marco D’Addario & Francesco Zanatta & Francesco Fattirolli & Cristina Franzelli & Alessandro Maloberti & Cristina Giannattasio & Patrizia Steca, 2022. "Sense of Coherence Predicts Physical Activity Maintenance and Health-Related Quality of Life: A 3-Year Longitudinal Study on Cardiovascular Patients," IJERPH, MDPI, vol. 19(8), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4700-:d:793083
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/8/4700/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/8/4700/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gilles Celeux & Gilda Soromenho, 1996. "An entropy criterion for assessing the number of clusters in a mixture model," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 195-212, September.
    2. Jian Wang & Liuna Geng, 2019. "Effects of Socioeconomic Status on Physical and Psychological Health: Lifestyle as a Mediator," IJERPH, MDPI, vol. 16(2), pages 1-9, January.
    3. Bram M.A. van Bakel & Esmée A. Bakker & Femke de Vries & Dick H.J. Thijssen & Thijs M.H. Eijsvogels, 2021. "Changes in Physical Activity and Sedentary Behaviour in Cardiovascular Disease Patients during the COVID-19 Lockdown," IJERPH, MDPI, vol. 18(22), pages 1-14, November.
    4. Bengt Muthén & Kerby Shedden, 1999. "Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm," Biometrics, The International Biometric Society, vol. 55(2), pages 463-469, June.
    5. Kathrin Wunsch & Korbinian Kienberger & Claudia Niessner, 2022. "Changes in Physical Activity Patterns Due to the Covid-19 Pandemic: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(4), pages 1-48, February.
    6. Antonovsky, Aaron, 1993. "The structure and properties of the sense of coherence scale," Social Science & Medicine, Elsevier, vol. 36(6), pages 725-733, March.
    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. Joanna F. Dipnall & Belinda J. Gabbe & Warwick J. Teague & Ben Beck, 2020. "Identifying Homogeneous Patterns of Injury in Paediatric Trauma Patients to Improve Risk-Adjusted Models of Mortality and Functional Outcomes," IJERPH, MDPI, vol. 17(3), pages 1-20, January.
    2. Pennoni, Fulvia & Romeo, Isabella, 2016. "Latent Markov and growth mixture models for ordinal individual responses with covariates: a comparison," MPRA Paper 72939, University Library of Munich, Germany.
    3. Anindita Chakravarty & Rajdeep Grewal & V. Sambamurthy, 2013. "Information Technology Competencies, Organizational Agility, and Firm Performance: Enabling and Facilitating Roles," Information Systems Research, INFORMS, vol. 24(4), pages 976-997, December.
    4. Heike Heidemeier & Anja Göritz, 2013. "Individual Differences in How Work and Nonwork Life Domains Contribute to Life Satisfaction: Using Factor Mixture Modeling for Classification," Journal of Happiness Studies, Springer, vol. 14(6), pages 1765-1788, December.
    5. Wei Zhao & Limin Peng & John Hanfelt, 2022. "Semiparametric latent class analysis of recurrent event data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1175-1197, September.
    6. Zachary K. Collier & Haobai Zhang & Bridgette Johnson, 2021. "Finite Mixture Modeling for Program Evaluation: Resampling and Pre-processing Approaches," Evaluation Review, , vol. 45(6), pages 309-333, December.
    7. Jost Reinecke & Daniel Seddig, 2011. "Growth mixture models in longitudinal research," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 415-434, December.
    8. Jumin Park & Debra K. Moser & Kathleen Griffith & Jeffrey R. Harring & Meg Johantgen, 2019. "Exploring Symptom Clusters in People With Heart Failure," Clinical Nursing Research, , vol. 28(2), pages 165-181, February.
    9. Kiero Guerra-Peña & Zoilo Emilio García-Batista & Sarah Depaoli & Luis Eduardo Garrido, 2020. "Class enumeration false positive in skew-t family of continuous growth mixture models," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-19, April.
    10. Bartolucci Francesco & Murphy Thomas Brendan, 2015. "A finite mixture latent trajectory model for modeling ultrarunners’ behavior in a 24-hour race," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(4), pages 193-203, December.
    11. Kristin Thomas & Evalill Nilsson & Karin Festin & Pontus Henriksson & Mats Lowén & Marie Löf & Margareta Kristenson, 2020. "Associations of Psychosocial Factors with Multiple Health Behaviors: A Population-Based Study of Middle-Aged Men and Women," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    12. Ana Raquel Nunes, 2021. "Exploring the interactions between vulnerability, resilience and adaptation to extreme temperatures," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(3), pages 2261-2293, December.
    13. Julian Aichholzer & Sylvia Kritzinger & Carolina Plescia, 2021. "National identity profiles and support for the European Union," European Union Politics, , vol. 22(2), pages 293-315, June.
    14. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    15. Mia M. Vainio & Daiva Daukantaitė, 2016. "Grit and Different Aspects of Well-Being: Direct and Indirect Relationships via Sense of Coherence and Authenticity," Journal of Happiness Studies, Springer, vol. 17(5), pages 2119-2147, October.
    16. Michael Prendergast & David Huang & Yih-Ing Hser, 2008. "Patterns of Crime and Drug Use Trajectories in Relation to Treatment Initiation and 5-Year Outcomes," Evaluation Review, , vol. 32(1), pages 59-82, February.
    17. Jacky C. K. Ng & Joanne Y. H. Chong & Hilary K. Y. Ng, 2023. "The way I see the world, the way I envy others: a person-centered investigation of worldviews and the malicious and benign forms of envy among adolescents and adults," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    18. Gillian C. Williams & Karen A. Patte & Mark A. Ferro & Scott T. Leatherdale, 2021. "Associations between Longitudinal Patterns of Substance Use and Anxiety and Depression Symptoms among a Sample of Canadian Secondary School Students," IJERPH, MDPI, vol. 18(19), pages 1-14, October.
    19. Mélissa Lemoine & Gerhard Gmel & Simon Foster & Simon Marmet & Joseph Studer, 2020. "Multiple trajectories of alcohol use and the development of alcohol use disorder: Do Swiss men mature-out of problematic alcohol use during emerging adulthood?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    20. Sarstedt, Marko & Salcher, André, 2007. "Modellselektion in Finite Mixture PLS-Modellen," Discussion Papers in Business Administration 1394, University of Munich, Munich School of Management.

    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:19:y:2022:i:8:p:4700-:d:793083. 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.