Paula Wilbourne, Susan Mirch-Kretschmann, Denise Walker, Michael Varghese, Roberto Arnetoli
{"title":"为员工提供支持健康结果的基于文本的人工智能健康指导和导航:前后观察研究。","authors":"Paula Wilbourne, Susan Mirch-Kretschmann, Denise Walker, Michael Varghese, Roberto Arnetoli","doi":"10.2196/64553","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Limited, timely access to quality mental health treatment harms well-being and quality of life while costing individuals and organizations millions in increased medical spending and reduced productivity. Too few qualified professionals, inconsistent quality, and stigma thwart traditional solutions, creating the need for scalable, science-based solutions.</p><p><strong>Objective: </strong>This report provides an overview of a novel digital health coaching service that consists of artificial intelligence (AI)-assisted, human-delivered, text-based health coaching. This report provides data evaluating the efficacy of this service for delivering mental health support, improving well-being, and enhancing workplace productivity.</p><p><strong>Methods: </strong>This observational study analyzed operational and self-reported health data from employees of subscribing organizations who used Sibly's digital health coaching service. Data included response times, changes in expressed member sentiment, conversation topics, and adherence to motivational interviewing. A subset of members (n=38) provided pre-post self-reported assessment measures of distress, unhealthy days, and presenteeism, having engaged in at least 4 coaching conversations over a minimum of 14 days. Sentiment was evaluated using a natural language processing tool.</p><p><strong>Results: </strong>Sibly provided quick access to interactive human coaching, with a median response time of 132 seconds. Sentiment analysis showed that 57% (878/1540) of conversations increased in positive emotions. The coaches maintained strong fidelity to the techniques of motivational interviewing, with adherence exceeding 90% (387/430). The proportion of users reporting severe distress declined from 33.3% (10/30) at baseline to 6.7% (2/30) at follow-up, representing a 79% relative reduction (P<.001). Participants also reported a reduction in the number of unhealthy days per month, decreasing from 19.57 to 15.87 per month (P=.02). Self-reported productivity improved by 18% during the study period (P<.001). Additionally, 61% (47/77) of users who received referrals to additional employer-sponsored benefits engaged with those resources, demonstrating effective care navigation to relevant support services.</p><p><strong>Conclusions: </strong>This report provides an overview of novel mental health support and navigation services that use AI-enabled, text-based health coaching and care navigation. Data suggest that the services provide effective, scalable mental health support in workplace settings. The platform helped reduce distress, improve well-being, and boost productivity by offering immediate access to trained coaches and personalized guidance. These results are consistent with existing research on digital mental health services. They highlight the potential of AI-assisted coaching to improve access to care. Future research should include larger, diverse populations and more rigorous randomized controlled trials. This formative report provides data that describes and demonstrates a proof of concept for an innovative technology-enabled service that addresses the problems of scalability, access, quality, and stigma that challenge the provision of traditional mental health services.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e64553"},"PeriodicalIF":2.0000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500221/pdf/","citationCount":"0","resultStr":"{\"title\":\"AI-Enabled, Text-Based Health Coaching and Navigation for Employees to Support Health Outcomes: Pre-Post Observational Study.\",\"authors\":\"Paula Wilbourne, Susan Mirch-Kretschmann, Denise Walker, Michael Varghese, Roberto Arnetoli\",\"doi\":\"10.2196/64553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Limited, timely access to quality mental health treatment harms well-being and quality of life while costing individuals and organizations millions in increased medical spending and reduced productivity. Too few qualified professionals, inconsistent quality, and stigma thwart traditional solutions, creating the need for scalable, science-based solutions.</p><p><strong>Objective: </strong>This report provides an overview of a novel digital health coaching service that consists of artificial intelligence (AI)-assisted, human-delivered, text-based health coaching. This report provides data evaluating the efficacy of this service for delivering mental health support, improving well-being, and enhancing workplace productivity.</p><p><strong>Methods: </strong>This observational study analyzed operational and self-reported health data from employees of subscribing organizations who used Sibly's digital health coaching service. Data included response times, changes in expressed member sentiment, conversation topics, and adherence to motivational interviewing. A subset of members (n=38) provided pre-post self-reported assessment measures of distress, unhealthy days, and presenteeism, having engaged in at least 4 coaching conversations over a minimum of 14 days. Sentiment was evaluated using a natural language processing tool.</p><p><strong>Results: </strong>Sibly provided quick access to interactive human coaching, with a median response time of 132 seconds. Sentiment analysis showed that 57% (878/1540) of conversations increased in positive emotions. The coaches maintained strong fidelity to the techniques of motivational interviewing, with adherence exceeding 90% (387/430). The proportion of users reporting severe distress declined from 33.3% (10/30) at baseline to 6.7% (2/30) at follow-up, representing a 79% relative reduction (P<.001). Participants also reported a reduction in the number of unhealthy days per month, decreasing from 19.57 to 15.87 per month (P=.02). Self-reported productivity improved by 18% during the study period (P<.001). Additionally, 61% (47/77) of users who received referrals to additional employer-sponsored benefits engaged with those resources, demonstrating effective care navigation to relevant support services.</p><p><strong>Conclusions: </strong>This report provides an overview of novel mental health support and navigation services that use AI-enabled, text-based health coaching and care navigation. Data suggest that the services provide effective, scalable mental health support in workplace settings. The platform helped reduce distress, improve well-being, and boost productivity by offering immediate access to trained coaches and personalized guidance. These results are consistent with existing research on digital mental health services. They highlight the potential of AI-assisted coaching to improve access to care. Future research should include larger, diverse populations and more rigorous randomized controlled trials. This formative report provides data that describes and demonstrates a proof of concept for an innovative technology-enabled service that addresses the problems of scalability, access, quality, and stigma that challenge the provision of traditional mental health services.</p>\",\"PeriodicalId\":14841,\"journal\":{\"name\":\"JMIR Formative Research\",\"volume\":\"9 \",\"pages\":\"e64553\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500221/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Formative Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/64553\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Formative Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/64553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
AI-Enabled, Text-Based Health Coaching and Navigation for Employees to Support Health Outcomes: Pre-Post Observational Study.
Background: Limited, timely access to quality mental health treatment harms well-being and quality of life while costing individuals and organizations millions in increased medical spending and reduced productivity. Too few qualified professionals, inconsistent quality, and stigma thwart traditional solutions, creating the need for scalable, science-based solutions.
Objective: This report provides an overview of a novel digital health coaching service that consists of artificial intelligence (AI)-assisted, human-delivered, text-based health coaching. This report provides data evaluating the efficacy of this service for delivering mental health support, improving well-being, and enhancing workplace productivity.
Methods: This observational study analyzed operational and self-reported health data from employees of subscribing organizations who used Sibly's digital health coaching service. Data included response times, changes in expressed member sentiment, conversation topics, and adherence to motivational interviewing. A subset of members (n=38) provided pre-post self-reported assessment measures of distress, unhealthy days, and presenteeism, having engaged in at least 4 coaching conversations over a minimum of 14 days. Sentiment was evaluated using a natural language processing tool.
Results: Sibly provided quick access to interactive human coaching, with a median response time of 132 seconds. Sentiment analysis showed that 57% (878/1540) of conversations increased in positive emotions. The coaches maintained strong fidelity to the techniques of motivational interviewing, with adherence exceeding 90% (387/430). The proportion of users reporting severe distress declined from 33.3% (10/30) at baseline to 6.7% (2/30) at follow-up, representing a 79% relative reduction (P<.001). Participants also reported a reduction in the number of unhealthy days per month, decreasing from 19.57 to 15.87 per month (P=.02). Self-reported productivity improved by 18% during the study period (P<.001). Additionally, 61% (47/77) of users who received referrals to additional employer-sponsored benefits engaged with those resources, demonstrating effective care navigation to relevant support services.
Conclusions: This report provides an overview of novel mental health support and navigation services that use AI-enabled, text-based health coaching and care navigation. Data suggest that the services provide effective, scalable mental health support in workplace settings. The platform helped reduce distress, improve well-being, and boost productivity by offering immediate access to trained coaches and personalized guidance. These results are consistent with existing research on digital mental health services. They highlight the potential of AI-assisted coaching to improve access to care. Future research should include larger, diverse populations and more rigorous randomized controlled trials. This formative report provides data that describes and demonstrates a proof of concept for an innovative technology-enabled service that addresses the problems of scalability, access, quality, and stigma that challenge the provision of traditional mental health services.