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Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk

Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk

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Prüfsumme: MD5:a222c1e4dd1680a5e669017f471ccede

WIENERT, Julian, Tim KUHLMANN, Vera STORM, Dominique REINWAND, Sonia LIPPKE, 2019. Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk. In: Research in Sports Medicine. 27(1), pp. 34-49. ISSN 1543-8627. eISSN 1543-8635. Available under: doi: 10.1080/15438627.2018.1502181

@article{Wienert2019-01-02Laten-42954, title={Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk}, year={2019}, doi={10.1080/15438627.2018.1502181}, number={1}, volume={27}, issn={1543-8627}, journal={Research in Sports Medicine}, pages={34--49}, author={Wienert, Julian and Kuhlmann, Tim and Storm, Vera and Reinwand, Dominique and Lippke, Sonia} }

eng 2018-08-02T12:10:47Z Wienert, Julian Storm, Vera 2019-01-02 2018-08-02T12:10:47Z Storm, Vera Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk Kuhlmann, Tim EHealth behaviour change interventions that help participants to adhere to professional physical activity recommendations can help to prevent future events of cardiovascular diseases (CVD). Therefore, identifying user groups of such interventions based on stages of health behaviour change is of great importance to provide tailored content to users instead of one-size-fits-all approaches. Our study used Latent Class Analysis (LCA) to identify underlying classes of users of an eHealth behaviour change intervention based on stages of change and associated variables. We compared participants' self-allocated stage with their latent class stage membership to display the correlation and mean differences between the two approaches. This was done by analysing baseline data of N = 310 people interested in reducing their CVD risk. LCA identified a three-class solution: (non-)intenders (19.4%), non-habituated actors (43.2%) and habituated actors (37.4%). The interrelation between self-allocated and latent class stage membership was moderate (ρ(308) = .49, p < .001). Significant mean differences for (non-)intenders and non-habituated actors were found in social-cognitive variables. Results showed that self-allocated stage outcomes represent a pseudo stage model - linear trends can be reported for stage-associated social-cognitive variables. The study provides information on the validity of stage measures, which can inform future interventions. terms-of-use Reinwand, Dominique Wienert, Julian Kuhlmann, Tim Lippke, Sonia Reinwand, Dominique Lippke, Sonia

Dateiabrufe seit 02.08.2018 (Informationen über die Zugriffsstatistik)

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