使用人工智能支持的数字生物标志物评估个性化健康应用程序(Aspire2B)的可接受性和实用性:参与增强试点研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES
Calissa J Leslie-Miller, Shellen R Goltz, Pamela L Barrios, Christopher C Cushing, Teena Badshah, Corey T Ungaro, Shankang Qu, Yulia Berezhnaya, Tristin D Brisbois
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引用次数: 0

摘要

背景:全球对促进健康有着极大的兴趣,移动健康应用程序等数字解决方案被广泛下载;然而,为了长期的行为改变而保持参与是一个挑战。开发一个被广泛接受的移动健康应用程序是推进个性化健康干预的必要条件。目的:本研究的主要目的是评估Aspire2B健康应用程序(由Salus Optima提供支持),该应用程序旨在通过结合基于证据的行为改变策略来超越参与者参与度的行业标准,并评估其作为数字健康解决方案的可接受性(例如,喜欢面部扫描)和实用性(例如,愿意使用面部扫描技术获取其他健康见解)。方法:研究人员于2022年3月至5月在美国招募了年龄在18-65岁之间的智能手机和健身追踪器用户。参与者下载该应用程序后将获得5美元的奖励,而不会有进一步的使用奖励。在完成入职(即关于生活方式行为的调查问题)之后,参与者被安排参加为期四周的营养、睡眠或健身挑战。在挑战过程中,参与者根据自己的意愿使用各种应用程序功能,例如面部扫描以获取健康信息(例如心率和生物年龄)、食谱和锻炼视频。这些与应用的互动被累积评估为用户粘性指标。参与者还被要求回答一些启动后的问题,以评估生活方式行为的变化和使用应用程序功能的体验(例如,面部扫描体验的可接受性)。结果:在创建账户的398人中,85.9%(342/398)完成了登录和面部扫描。在此之后,74.9%(298/398)的用户完成了关于当前健康行为的额外调查问题。值得注意的是,从第2周到第4周,用户与应用的互动相对稳定(173/398,43.5%),比行业标准高出约3倍。此外,参与者平均每周完成2.1-2.7次面部扫描,约7%(24/342)的参与者在4周内保持定期使用面部扫描技术。在完成离职问题的用户中,88.8%(111/125)认为Aspire2B可信,64.8%(81/125)喜欢面部扫描体验,7.2%(9/125)不喜欢面部扫描体验,83.2%(104/125)表示他们会使用面部扫描技术来了解他们的健康状况。结论:这些发现突出了Aspire2B的初始用户粘性,随后在4周的时间内保持了显著的用户粘性。此外,用户表示使用面部扫描技术进行健康洞察的可信度和意愿很高。这些发现共同证明了个性化健康应用程序使用人工智能支持的数字生物标志物和有证据支持的行为改变技术的能力,可以产生积极的用户感知并提供长期参与。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the Acceptability and Utility of a Personalized Wellness App (Aspire2B) Using AI-Enabled Digital Biomarkers: Engagement Enhancement Pilot Study.

Background: There is significant global interest in promoting wellness, with digital solutions like mobile health apps being broadly downloaded; yet, there is a challenge in maintaining engagement for long-term behavior change. Developing a widely accepted mobile wellness app is imperative for advancing personalized wellness interventions.

Objective: The primary objective of this study was to evaluate the Aspire2B wellness app (powered by Salus Optima), designed to exceed industry standards for participant engagement by incorporating evidence-based behavior change strategies and to assess its acceptability (eg, liking the face scan) and utility (eg, willing to use the face scan technology for other health insights) as a digital health solution.

Methods: Participants aged 18-65 years, who were smartphone and fitness tracker users, were recruited in the United States during March-May 2022. Participants received US $5 compensation for downloading the app, with no further incentive for usage. Following completion of onboarding (ie, survey questions about lifestyle behaviors), participants were placed in either a nutrition, sleep, or fitness 4-week challenge. During the challenge, participants used various app features at their own will, such as a facial scan for wellness insights (eg, heart rate and biological age), recipes, and workout videos. These interactions with the app were cumulatively evaluated as engagement metrics. Participants were also asked to answer offboarding questions to evaluate any changes to lifestyle behaviors and experience using the app features (eg, acceptability of face scan experience).

Results: Out of the 398 people who created an account, 85.9% (342/398) completed onboarding and a face scan. Following this, 74.9% (298/398) of users completed additional survey questions about current wellness behaviors. Notably, interaction with the app was relatively stable from week 2 to 4 (173/398, 43.5%), outperforming industry standards by roughly 3×. In addition, on average, participants completed 2.1-2.7 face scans per week, with approximately 7% (24/342) of participants maintaining regular use of face scan technology for 4 weeks. In users who completed offboarding questions, 88.8% (111/125) found Aspire2B credible, 64.8% (81/125) liked the face scan experience, 7.2% (9/125) disliked the face scan experience, and 83.2% (104/125) said they would use face scan technology for other insights into their health.

Conclusions: These findings highlight strong initial engagement with Aspire2B, followed by significant sustained user engagement over a 4-week period. Furthermore, users indicated high levels of credibility and willingness to use face scan technology for wellness insights. These findings collectively demonstrate the capability of a personalized wellness app using AI-enabled digital biomarkers and evidence-supported behavior change techniques to yield positive user perception and provide long-term engagement.

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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
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