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人工智能虚拟健康教练提供的体力活动和饮食计划:概念验证研究。

A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study.

机构信息

Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia.

Melbourne Centre for Behaviour Change, School of Psychological Sciences and School of Health Sciences, University of Melbourne, Melbourne, Australia.

出版信息

JMIR Mhealth Uhealth. 2020 Jul 10;8(7):e17558. doi: 10.2196/17558.

Abstract

BACKGROUND

Poor diet and physical inactivity are leading modifiable causes of death and disease. Advances in artificial intelligence technology present tantalizing opportunities for creating virtual health coaches capable of providing personalized support at scale.

OBJECTIVE

This proof of concept study aimed to test the feasibility (recruitment and retention) and preliminary efficacy of physical activity and Mediterranean-style dietary intervention (MedLiPal) delivered via artificially intelligent virtual health coach.

METHODS

This 12-week single-arm pre-post study took place in Adelaide, Australia, from March to August 2019. Participants were inactive community-dwelling adults aged 45 to 75 years, recruited through news stories, social media posts, and flyers. The program included access to an artificially intelligent chatbot, Paola, who guided participants through a computer-based individualized introductory session, weekly check-ins, and goal setting, and was available 24/7 to answer questions. Participants used a Garmin Vivofit4 tracker to monitor daily steps, a website with educational materials and recipes, and a printed diet and activity log sheet. Primary outcomes included feasibility (based on recruitment and retention) and preliminary efficacy for changing physical activity and diet. Secondary outcomes were body composition (based on height, weight, and waist circumference) and blood pressure.

RESULTS

Over 4 weeks, 99 potential participants registered expressions of interest, with 81 of those screened meeting eligibility criteria. Participants completed a mean of 109.8 (95% CI 1.9-217.7) more minutes of physical activity at week 12 compared with baseline. Mediterranean diet scores increased from a mean of 3.8 out of 14 at baseline, to 9.6 at 12 weeks (mean improvement 5.7 points, 95% CI 4.2-7.3). After 12 weeks, participants lost an average 1.3 kg (95% CI -0.1 to -2.5 kg) and 2.1 cm from their waist circumference (95% CI -3.5 to -0.7 cm). There were no significant changes in blood pressure. Feasibility was excellent in terms of recruitment, retention (90% at 12 weeks), and safety (no adverse events).

CONCLUSIONS

An artificially intelligent virtual assistant-led lifestyle-modification intervention was feasible and achieved measurable improvements in physical activity, diet, and body composition at 12 weeks. Future research examining artificially intelligent interventions at scale, and for other health purposes, is warranted.

摘要

背景

不良饮食和缺乏身体活动是导致死亡和疾病的主要可改变因素。人工智能技术的进步为创建能够大规模提供个性化支持的虚拟健康教练提供了诱人的机会。

目的

本概念验证研究旨在测试通过人工智能虚拟健康教练提供的身体活动和地中海式饮食干预(MedLiPal)的可行性(招募和保留)和初步疗效。

方法

这项为期 12 周的单臂前后研究于 2019 年 3 月至 8 月在澳大利亚阿德莱德进行。参与者是不活跃的社区居住成年人,年龄在 45 至 75 岁之间,通过新闻报道、社交媒体帖子和传单招募。该计划包括访问人工智能聊天机器人 Paola,她通过基于计算机的个性化介绍会议、每周签到和目标设定来指导参与者,并且 24/7 随时回答问题。参与者使用 Garmin Vivofit4 追踪器来监测每日步数,使用带有教育材料和食谱的网站,以及打印的饮食和活动日志表。主要结果包括改变身体活动和饮食的可行性(基于招募和保留)和初步疗效。次要结果是身体成分(基于身高、体重和腰围)和血压。

结果

在 4 周内,99 名潜在参与者表达了兴趣,其中 81 名经过筛选符合资格标准。与基线相比,参与者在第 12 周的身体活动增加了平均 109.8(95%CI 1.9-217.7)分钟。地中海饮食评分从基线时的 14 分中的 3.8 分,提高到第 12 周时的 9.6 分(平均提高 5.7 分,95%CI 4.2-7.3)。12 周后,参与者平均减轻 1.3 公斤(95%CI -0.1 至 -2.5 公斤),腰围减少 2.1 厘米(95%CI -3.5 至 -0.7 厘米)。血压没有明显变化。在招募、保留(第 12 周时为 90%)和安全性(无不良事件)方面,可行性非常好。

结论

人工智能虚拟助手主导的生活方式改变干预措施是可行的,在 12 周内可显著改善身体活动、饮食和身体成分。需要进一步研究人工智能干预措施的规模和其他健康目的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba37/7382010/c46e8f158d1c/mhealth_v8i7e17558_fig1.jpg

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