{"title":"发展文化相关的设计指南,鼓励体育活动:一个社会认知理论的观点","authors":"Kiemute Oyibo, Rita Orji, Julita Vassileva","doi":"10.1007/s41666-018-0026-9","DOIUrl":null,"url":null,"abstract":"<p><p>The prevalence of physical inactivity and non-communicable diseases is on the rise worldwide. This calls for a systematic approach in addressing the problem, which is almost becoming a global epidemic. Research has shown that theory-driven interventions are more likely to be effective than uninformed interventions. However, research on the determinants of physical activity and the moderating effect of culture is scarce. To bridge this gap, we conducted a large-scale comparative study of the determinants of physical activity among 633 participants from individualist and collectivist cultures. Using the Social Cognitive Theory, a widely applied behavioral theory in health interventions, we modeled the determinants of physical activity for each culture and mapped them to implementable strategies in the application domain. Our structural equation model shows that, in the individualist culture, <i>Self-Efficacy</i> (β<sub>T</sub> = 0.55, <i>p</i> < 0.001) and <i>Self-Regulation</i> (β<sub>T</sub> = 0.33, <i>p</i> < 0.001) are the strongest determinants of <i>Physical Activity</i>. However, in the collectivist culture, <i>Social Support</i> (β<sub>T</sub> = 0.42, <i>p</i> < 0.001) and <i>Outcome Expectation</i> (β<sub>T</sub> = 0.11, <i>p</i> < 0.01) are the strongest determinants of <i>Physical Activity</i>. We discussed these findings, mapped the respective behavioral determinants to the corresponding persuasive strategies in the health domain and provided a set of general design guidelines for tailoring the strategies to the respective cultures.</p>","PeriodicalId":36444,"journal":{"name":"Journal of Healthcare Informatics Research","volume":"2 1","pages":"319-352"},"PeriodicalIF":5.9000,"publicationDate":"2018-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982739/pdf/","citationCount":"0","resultStr":"{\"title\":\"Developing Culturally Relevant Design Guidelines for Encouraging Physical Activity: a Social Cognitive Theory Perspective.\",\"authors\":\"Kiemute Oyibo, Rita Orji, Julita Vassileva\",\"doi\":\"10.1007/s41666-018-0026-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The prevalence of physical inactivity and non-communicable diseases is on the rise worldwide. This calls for a systematic approach in addressing the problem, which is almost becoming a global epidemic. Research has shown that theory-driven interventions are more likely to be effective than uninformed interventions. However, research on the determinants of physical activity and the moderating effect of culture is scarce. To bridge this gap, we conducted a large-scale comparative study of the determinants of physical activity among 633 participants from individualist and collectivist cultures. Using the Social Cognitive Theory, a widely applied behavioral theory in health interventions, we modeled the determinants of physical activity for each culture and mapped them to implementable strategies in the application domain. Our structural equation model shows that, in the individualist culture, <i>Self-Efficacy</i> (β<sub>T</sub> = 0.55, <i>p</i> < 0.001) and <i>Self-Regulation</i> (β<sub>T</sub> = 0.33, <i>p</i> < 0.001) are the strongest determinants of <i>Physical Activity</i>. However, in the collectivist culture, <i>Social Support</i> (β<sub>T</sub> = 0.42, <i>p</i> < 0.001) and <i>Outcome Expectation</i> (β<sub>T</sub> = 0.11, <i>p</i> < 0.01) are the strongest determinants of <i>Physical Activity</i>. We discussed these findings, mapped the respective behavioral determinants to the corresponding persuasive strategies in the health domain and provided a set of general design guidelines for tailoring the strategies to the respective cultures.</p>\",\"PeriodicalId\":36444,\"journal\":{\"name\":\"Journal of Healthcare Informatics Research\",\"volume\":\"2 1\",\"pages\":\"319-352\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2018-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982739/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Healthcare Informatics Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41666-018-0026-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/12/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Healthcare Informatics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41666-018-0026-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
Developing Culturally Relevant Design Guidelines for Encouraging Physical Activity: a Social Cognitive Theory Perspective.
The prevalence of physical inactivity and non-communicable diseases is on the rise worldwide. This calls for a systematic approach in addressing the problem, which is almost becoming a global epidemic. Research has shown that theory-driven interventions are more likely to be effective than uninformed interventions. However, research on the determinants of physical activity and the moderating effect of culture is scarce. To bridge this gap, we conducted a large-scale comparative study of the determinants of physical activity among 633 participants from individualist and collectivist cultures. Using the Social Cognitive Theory, a widely applied behavioral theory in health interventions, we modeled the determinants of physical activity for each culture and mapped them to implementable strategies in the application domain. Our structural equation model shows that, in the individualist culture, Self-Efficacy (βT = 0.55, p < 0.001) and Self-Regulation (βT = 0.33, p < 0.001) are the strongest determinants of Physical Activity. However, in the collectivist culture, Social Support (βT = 0.42, p < 0.001) and Outcome Expectation (βT = 0.11, p < 0.01) are the strongest determinants of Physical Activity. We discussed these findings, mapped the respective behavioral determinants to the corresponding persuasive strategies in the health domain and provided a set of general design guidelines for tailoring the strategies to the respective cultures.
期刊介绍:
Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics. The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications. Topics include but are not limited to: · healthcare software architecture, framework, design, and engineering;· electronic health records· medical data mining· predictive modeling· medical information retrieval· medical natural language processing· healthcare information systems· smart health and connected health· social media analytics· mobile healthcare· medical signal processing· human factors in healthcare· usability studies in healthcare· user-interface design for medical devices and healthcare software· health service delivery· health games· security and privacy in healthcare· medical recommender system· healthcare workflow management· disease profiling and personalized treatment· visualization of medical data· intelligent medical devices and sensors· RFID solutions for healthcare· healthcare decision analytics and support systems· epidemiological surveillance systems and intervention modeling· consumer and clinician health information needs, seeking, sharing, and use· semantic Web, linked data, and ontology· collaboration technologies for healthcare· assistive and adaptive ubiquitous computing technologies· statistics and quality of medical data· healthcare delivery in developing countries· health systems modeling and simulation· computer-aided diagnosis