PDF(Pubmed)
Abstract：
UNASSIGNED: Mobile health (mHealth) interventions are increasingly being used for cardiovascular research and physical activity promotion.
UNASSIGNED: As a result, the authors aimed to evaluate which features facilitate and impede routine engagement with mobile fitness applications.
UNASSIGNED: We distributed a pan-Canadian online questionnaire via the behavioral research platform Prolific.co to evaluate what features are associated with the use and routine engagement (ie, daily or weekly use) of mHealth fitness applications and attitudes about data sharing. Binary logistic regression was used to quantify the association between these endpoints and exploratory factors such as the perceived utility of various mHealth application features.
UNASSIGNED: The survey received 694 responses. Most people were women (62%), the median age was 28 years (range: 18-78 years), and most people reported current use of an mHealth fitness application (48%). The perceived importance of personal health (OR: 2.40; 95% CI: 1.34-4.50) was the factor most associated with the current use of an mHealth fitness application. The feature most associated with routine engagement was the ability to track progress toward a goal (OR: 5.10; 95% CI: 2.73-9.61) while the most significant barrier was the absence of goal customization features (OR: 0.44; 95% CI: 0.25-0.81). The acceptance of sharing health data for research was high (56%), and privacy concerns did not significantly affect routine engagement (OR: 0.81; 95% CI: 0.40-1.77). Results were consistent across race and gender.
UNASSIGNED: mHealth interventions have the potential to be scaled across populations. Optimizing applications to improve self-monitoring and personalization could increase routine engagement and, thus, user retention and intervention effectiveness.
UNASSIGNED: As a result, the authors aimed to evaluate which features facilitate and impede routine engagement with mobile fitness applications.
UNASSIGNED: We distributed a pan-Canadian online questionnaire via the behavioral research platform Prolific.co to evaluate what features are associated with the use and routine engagement (ie, daily or weekly use) of mHealth fitness applications and attitudes about data sharing. Binary logistic regression was used to quantify the association between these endpoints and exploratory factors such as the perceived utility of various mHealth application features.
UNASSIGNED: The survey received 694 responses. Most people were women (62%), the median age was 28 years (range: 18-78 years), and most people reported current use of an mHealth fitness application (48%). The perceived importance of personal health (OR: 2.40; 95% CI: 1.34-4.50) was the factor most associated with the current use of an mHealth fitness application. The feature most associated with routine engagement was the ability to track progress toward a goal (OR: 5.10; 95% CI: 2.73-9.61) while the most significant barrier was the absence of goal customization features (OR: 0.44; 95% CI: 0.25-0.81). The acceptance of sharing health data for research was high (56%), and privacy concerns did not significantly affect routine engagement (OR: 0.81; 95% CI: 0.40-1.77). Results were consistent across race and gender.
UNASSIGNED: mHealth interventions have the potential to be scaled across populations. Optimizing applications to improve self-monitoring and personalization could increase routine engagement and, thus, user retention and intervention effectiveness.
摘要：
■移动健康（mHealth）干预措施越来越多地用于心血管研究和身体活动促进。
■因此，作者旨在评估哪些功能促进和阻碍移动健身应用程序的常规参与。
■我们通过行为研究平台Prolific分发了一份泛加拿大在线问卷。co评估与使用和常规参与相关的哪些功能(即，每天或每周使用）mHealth健身应用程序和对数据共享的态度。二元逻辑回归用于量化这些终点与探索性因素之间的关联，例如各种mHealth应用程序功能的感知效用。
■调查收到694份回复。大多数人是女性（62%），中位年龄为28岁（范围：18-78岁），大多数人报告说目前正在使用mHealth健身应用程序（48％）。个人健康的感知重要性（OR：2.40；95％CI：1.34-4.50）是与当前使用mHealth健身应用程序最相关的因素。与常规参与最相关的特征是跟踪目标进展的能力（OR：5.10;95％CI：2.73-9.61），而最重要的障碍是缺乏目标定制特征（OR：0.44;95％CI：0.25-0.81）。对共享健康数据进行研究的接受度很高（56％），隐私问题没有显著影响常规参与(OR:0.81;95%CI:0.40-1.77)。结果在种族和性别之间是一致的。
■m健康干预措施有可能在人群中扩展。优化应用程序以改善自我监控和个性化可以提高日常参与度，因此，用户保留和干预有效性。
■因此，作者旨在评估哪些功能促进和阻碍移动健身应用程序的常规参与。
■我们通过行为研究平台Prolific分发了一份泛加拿大在线问卷。co评估与使用和常规参与相关的哪些功能(即，每天或每周使用）mHealth健身应用程序和对数据共享的态度。二元逻辑回归用于量化这些终点与探索性因素之间的关联，例如各种mHealth应用程序功能的感知效用。
■调查收到694份回复。大多数人是女性（62%），中位年龄为28岁（范围：18-78岁），大多数人报告说目前正在使用mHealth健身应用程序（48％）。个人健康的感知重要性（OR：2.40；95％CI：1.34-4.50）是与当前使用mHealth健身应用程序最相关的因素。与常规参与最相关的特征是跟踪目标进展的能力（OR：5.10;95％CI：2.73-9.61），而最重要的障碍是缺乏目标定制特征（OR：0.44;95％CI：0.25-0.81）。对共享健康数据进行研究的接受度很高（56％），隐私问题没有显著影响常规参与(OR:0.81;95%CI:0.40-1.77)。结果在种族和性别之间是一致的。
■m健康干预措施有可能在人群中扩展。优化应用程序以改善自我监控和个性化可以提高日常参与度，因此，用户保留和干预有效性。
