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Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users
This study examines fitness app use patterns and their correlates among Chinese users from the perspectives of uses and gratification theory and self-determination theory. Our sample comprised 632 users of WeRun, the fitness plugin of WeChat, the largest Chinese mobile social networking app; partici...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518310/ https://www.ncbi.nlm.nih.gov/pubmed/36078395 http://dx.doi.org/10.3390/ijerph191710679 |
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author | Jiang, Li Crystal Sun, Mengru Huang, Guanxiong |
author_facet | Jiang, Li Crystal Sun, Mengru Huang, Guanxiong |
author_sort | Jiang, Li Crystal |
collection | PubMed |
description | This study examines fitness app use patterns and their correlates among Chinese users from the perspectives of uses and gratification theory and self-determination theory. Our sample comprised 632 users of WeRun, the fitness plugin of WeChat, the largest Chinese mobile social networking app; participants completed an online survey and provided self-tracked physical activity data, which were subjected to latent class analysis. Based on the four-class latent class model (which yielded the best model fit and the most interpretable results), 30.5%, 27.5%, 24.7%, and 17.3% of the users were categorized as light users, reward-oriented users, lifestyle-oriented users, and interaction-oriented users, respectively. Moreover, class membership was associated with gender, age, education, income, life satisfaction, autonomy, and platform-based motivations. There is a significant heterogeneity in fitness app use and exercise behaviors. Platform-based motivations and autonomy are important classification factors, as users are looking for specific kinds of gratification from their use of fitness apps. Demographics and individual characteristics are also explanatory factors for class membership. The study findings suggest that fitness app designers should segment users based on motivation and gratification. |
format | Online Article Text |
id | pubmed-9518310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95183102022-09-29 Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users Jiang, Li Crystal Sun, Mengru Huang, Guanxiong Int J Environ Res Public Health Article This study examines fitness app use patterns and their correlates among Chinese users from the perspectives of uses and gratification theory and self-determination theory. Our sample comprised 632 users of WeRun, the fitness plugin of WeChat, the largest Chinese mobile social networking app; participants completed an online survey and provided self-tracked physical activity data, which were subjected to latent class analysis. Based on the four-class latent class model (which yielded the best model fit and the most interpretable results), 30.5%, 27.5%, 24.7%, and 17.3% of the users were categorized as light users, reward-oriented users, lifestyle-oriented users, and interaction-oriented users, respectively. Moreover, class membership was associated with gender, age, education, income, life satisfaction, autonomy, and platform-based motivations. There is a significant heterogeneity in fitness app use and exercise behaviors. Platform-based motivations and autonomy are important classification factors, as users are looking for specific kinds of gratification from their use of fitness apps. Demographics and individual characteristics are also explanatory factors for class membership. The study findings suggest that fitness app designers should segment users based on motivation and gratification. MDPI 2022-08-27 /pmc/articles/PMC9518310/ /pubmed/36078395 http://dx.doi.org/10.3390/ijerph191710679 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jiang, Li Crystal Sun, Mengru Huang, Guanxiong Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title | Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title_full | Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title_fullStr | Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title_full_unstemmed | Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title_short | Uncovering the Heterogeneity in Fitness App Use: A Latent Class Analysis of Chinese Users |
title_sort | uncovering the heterogeneity in fitness app use: a latent class analysis of chinese users |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518310/ https://www.ncbi.nlm.nih.gov/pubmed/36078395 http://dx.doi.org/10.3390/ijerph191710679 |
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