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Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19
During the coronavirus disease 2019 (COVID-19) pandemic, many countries imposed restrictions and quarantines on the population, which led to a decrease in people’s physical activity (PA) and severely damaged their mental health. As a result, people engaged in fitness activities with the help of fitn...
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/PMC9740845/ https://www.ncbi.nlm.nih.gov/pubmed/36497534 http://dx.doi.org/10.3390/ijerph192315460 |
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author | Guo, Yanlong Ma, Xueqing Chen, Denghang Zhang, Han |
author_facet | Guo, Yanlong Ma, Xueqing Chen, Denghang Zhang, Han |
author_sort | Guo, Yanlong |
collection | PubMed |
description | During the coronavirus disease 2019 (COVID-19) pandemic, many countries imposed restrictions and quarantines on the population, which led to a decrease in people’s physical activity (PA) and severely damaged their mental health. As a result, people engaged in fitness activities with the help of fitness apps, which improved their resistance to the virus and reduced the occurrence of psychological problems, such as anxiety and depression. However, the churn rate of fitness apps is high. As such, our purpose in this study was to analyze the factors that influence the use of fitness apps by adults aged 18–65 years in the context of COVID-19, with the aim of contributing to the analysis of mobile fitness user behavior and related product design practices. We constructed a decision target program model using the analytic hierarchy process (AHP), and we analyzed and inductively screened 11 evaluation indicators, which we combined with an indicator design questionnaire. We distributed 420 questionnaires; of the respondents, 347 knew about or used fitness apps. Among these 347, we recovered 310 valid questionnaires after removing invalid questionnaires with a short completion time, for an effective questionnaire recovery rate of 89.33%. We used the AHP and entropy method to calculate and evaluate the weight coefficient of each influencing factor and to determine an influencing factor index. Our conclusions were as follows: first, the effect of perceived usefulness on the use of fitness apps by the study groups was the most notable. Second, personal motivation and perceived ease of use considerably influenced the adult group’s willingness to use fitness apps. Finally, the perceived cost had relatively little effect on the use of fitness apps by adults, and the study group was much more concerned with the privacy cost than the expense cost. |
format | Online Article Text |
id | pubmed-9740845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97408452022-12-11 Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 Guo, Yanlong Ma, Xueqing Chen, Denghang Zhang, Han Int J Environ Res Public Health Article During the coronavirus disease 2019 (COVID-19) pandemic, many countries imposed restrictions and quarantines on the population, which led to a decrease in people’s physical activity (PA) and severely damaged their mental health. As a result, people engaged in fitness activities with the help of fitness apps, which improved their resistance to the virus and reduced the occurrence of psychological problems, such as anxiety and depression. However, the churn rate of fitness apps is high. As such, our purpose in this study was to analyze the factors that influence the use of fitness apps by adults aged 18–65 years in the context of COVID-19, with the aim of contributing to the analysis of mobile fitness user behavior and related product design practices. We constructed a decision target program model using the analytic hierarchy process (AHP), and we analyzed and inductively screened 11 evaluation indicators, which we combined with an indicator design questionnaire. We distributed 420 questionnaires; of the respondents, 347 knew about or used fitness apps. Among these 347, we recovered 310 valid questionnaires after removing invalid questionnaires with a short completion time, for an effective questionnaire recovery rate of 89.33%. We used the AHP and entropy method to calculate and evaluate the weight coefficient of each influencing factor and to determine an influencing factor index. Our conclusions were as follows: first, the effect of perceived usefulness on the use of fitness apps by the study groups was the most notable. Second, personal motivation and perceived ease of use considerably influenced the adult group’s willingness to use fitness apps. Finally, the perceived cost had relatively little effect on the use of fitness apps by adults, and the study group was much more concerned with the privacy cost than the expense cost. MDPI 2022-11-22 /pmc/articles/PMC9740845/ /pubmed/36497534 http://dx.doi.org/10.3390/ijerph192315460 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 Guo, Yanlong Ma, Xueqing Chen, Denghang Zhang, Han Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title | Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title_full | Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title_fullStr | Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title_full_unstemmed | Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title_short | Factors Influencing Use of Fitness Apps by Adults under Influence of COVID-19 |
title_sort | factors influencing use of fitness apps by adults under influence of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740845/ https://www.ncbi.nlm.nih.gov/pubmed/36497534 http://dx.doi.org/10.3390/ijerph192315460 |
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