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Lockwood KG, Kulkarni PR, Paruthi J, Buch LS, Chaffard M, Schitter EC, Branch OH, Graham SA. Evaluating a New Digital App-Based Program for Heart Health: Feasibility and Acceptability Pilot Study. JMIR Form Res 2024; 8:e50446. [PMID: 38787598 PMCID: PMC11161712 DOI: 10.2196/50446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 03/14/2024] [Accepted: 04/11/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Cardiovascular disease (CVD) is the leading cause of death in the United States, affecting a significant proportion of adults. Digital health lifestyle change programs have emerged as a promising method of CVD prevention, offering benefits such as on-demand support, lower cost, and increased scalability. Prior research has shown the effectiveness of digital health interventions in reducing negative CVD outcomes. This pilot study focuses on the Lark Heart Health program, a fully digital artificial intelligence (AI)-powered smartphone app, providing synchronous CVD risk counseling, educational content, and personalized coaching. OBJECTIVE This pilot study evaluated the feasibility and acceptability of a fully digital AI-powered lifestyle change program called Lark Heart Health. Primary analyses assessed (1) participant satisfaction, (2) engagement with the program, and (3) the submission of health screeners. Secondary analyses were conducted to evaluate weight loss outcomes, given that a major focus of the Heart Health program is weight management. METHODS This study enrolled 509 participants in the 90-day real-world single-arm pilot study of the Heart Health app. Participants engaged with the app by participating in coaching conversations, logging meals, tracking weight, and completing educational lessons. The study outcomes included participant satisfaction, app engagement, the completion of screeners, and weight loss. RESULTS On average, Heart Health study participants were aged 60.9 (SD 10.3; range 40-75) years, with average BMI indicating class I obesity. Of the 509 participants, 489 (96.1%) stayed enrolled until the end of the study (dropout rate: 3.9%). Study retention, based on providing a weight measurement during month 3, was 80% (407/509; 95% CI 76.2%-83.4%). Participant satisfaction scores indicated high satisfaction with the overall app experience, with an average score of ≥4 out of 5 for all satisfaction indicators. Participants also showed high engagement with the app, with 83.4% (408/489; 95% CI 80.1%-86.7%) of the sample engaging in ≥5 coaching conversations in month 3. The results indicated that participants were successfully able to submit health screeners within the app, with 90% (440/489; 95% CI 87%-92.5%) submitting all 3 screeners measured in the study. Finally, secondary analyses showed that participants lost weight during the program, with analyses showing an average weight nadir of 3.8% (SD 2.9%; 95% CI 3.5%-4.1%). CONCLUSIONS The study results indicate that participants in this study were satisfied with their experience using the Heart Health app, highly engaged with the app features, and willing and able to complete health screening surveys in the app. These acceptability and feasibility results provide a key first step in the process of evidence generation for a new AI-powered digital program for heart health. Future work can expand these results to test outcomes with a commercial version of the Heart Health app in a diverse real-world sample.
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Affiliation(s)
| | | | | | | | | | - Eva C Schitter
- Roche Information Solutions, Santa Clara, CA, United States
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Gannamani R, Castela Forte J, Folkertsma P, Hermans S, Kumaraswamy S, van Dam S, Chavannes N, van Os H, Pijl H, Wolffenbuttel BHR. A Digitally Enabled Combined Lifestyle Intervention for Weight Loss: Pilot Study in a Dutch General Population Cohort. JMIR Form Res 2024; 8:e38891. [PMID: 38329792 PMCID: PMC10884913 DOI: 10.2196/38891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 05/04/2023] [Accepted: 09/25/2023] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Overweight and obesity rates among the general population of the Netherlands keep increasing. Combined lifestyle interventions (CLIs) focused on physical activity, nutrition, sleep, and stress management can be effective in reducing weight and improving health behaviors. Currently available CLIs for weight loss (CLI-WLs) in the Netherlands consist of face-to-face and community-based sessions, which face scalability challenges. A digitally enabled CLI-WL with digital and human components may provide a solution for this challenge; however, the feasibility of such an intervention has not yet been assessed in the Netherlands. OBJECTIVE The aim of this study was two-fold: (1) to determine how weight and other secondary cardiometabolic outcomes (lipids and blood pressure) change over time in a Dutch population with overweight or obesity and cardiometabolic risk participating in a pilot digitally enabled CLI-WL and (2) to collect feedback from participants to guide the further development of future iterations of the intervention. METHODS Participants followed a 16-week digitally enabled lifestyle coaching program rooted in the Fogg Behavior Model, focused on nutrition, physical activity, and other health behaviors, from January 2020 to December 2021. Participants could access the digital app to register and track health behaviors, weight, and anthropometrics data at any time. We retrospectively analyzed changes in weight, blood pressure, and lipids for remeasured users. Surveys and semistructured interviews were conducted to assess critical positive and improvement points reported by participants and health care professionals. RESULTS Of the 420 participants evaluated at baseline, 53 participated in the pilot. Of these, 37 (70%) were classified as overweight and 16 (30%) had obesity. Mean weight loss of 4.2% occurred at a median of 10 months postintervention. The subpopulation with obesity (n=16) showed a 5.6% weight loss on average. Total cholesterol decreased by 10.2% and low-density lipoprotein cholesterol decreased by 12.9% on average. Systolic and diastolic blood pressure decreased by 3.5% and 7.5%, respectively. Participants identified the possibility of setting clear action plans to work toward and the multiple weekly touch points with coaches as two of the most positive and distinctive components of the digitally enabled intervention. Surveys and interviews demonstrated that the digital implementation of a CLI-WL is feasible and well-received by both participants and health care professionals. CONCLUSIONS Albeit preliminary, these findings suggest that a behavioral lifestyle program with a digital component can achieve greater weight loss than reported for currently available offline CLI-WLs. Thus, a digitally enabled CLI-WL is feasible and may be a scalable alternative to offline CLI-WL programs. Evidence from future studies in a Dutch population may help elucidate the mechanisms behind the effectiveness of a digitally enabled CLI-WL.
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Affiliation(s)
- Rahul Gannamani
- Ancora Health BV, Groningen, Netherlands
- Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - José Castela Forte
- Ancora Health BV, Groningen, Netherlands
- Department of Clinical Pharmacy and Pharmacology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Pytrik Folkertsma
- Ancora Health BV, Groningen, Netherlands
- Department of Endocrinology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | | | | | - Sipko van Dam
- Ancora Health BV, Groningen, Netherlands
- Department of Endocrinology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Niels Chavannes
- Department of Public Health and Primary Care, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
- National eHealth Living Lab, Leiden, Netherlands
| | - Hendrikus van Os
- Department of Public Health and Primary Care, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
- National eHealth Living Lab, Leiden, Netherlands
| | - Hanno Pijl
- Department of Endocrinology, Leiden University Medical Center, Leiden University, Leiden, Netherlands
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
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Ross J, Hawkes RE, Miles LM, Cotterill S, Bower P, Murray E. Design and Early Use of the Nationally Implemented Healthier You National Health Service Digital Diabetes Prevention Programme: Mixed Methods Study. J Med Internet Res 2023; 25:e47436. [PMID: 37590056 PMCID: PMC10472174 DOI: 10.2196/47436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/28/2023] [Accepted: 06/26/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND The Healthier You National Health Service Digital Diabetes Prevention Programme (NHS-digital-DPP) is a 9-month digital behavior change intervention delivered by 4 independent providers that is implemented nationally across England. No studies have explored the design features included by service providers of digital diabetes prevention programs to promote engagement, and little is known about how participants of nationally implemented digital diabetes prevention programs such as this one make use of them. OBJECTIVE This study aimed to understand engagement with the NHS-digital-DPP. The specific objectives were to describe how engagement with the NHS-digital-DPP is promoted via design features and strategies and describe participants' early engagement with the NHS-digital-DPP apps. METHODS Mixed methods were used. The qualitative study was a secondary analysis of documents detailing the NHS-digital-DPP intervention design and interviews with program developers (n=6). Data were deductively coded according to an established framework of engagement with digital health interventions. For the quantitative study, anonymous use data collected over 9 months for each provider representing participants' first 30 days of use of the apps were obtained for participants enrolled in the NHS-digital-DPP. Use data fields were categorized into 4 intervention features (Track, Learn, Coach Interactions, and Peer Support). The amount of engagement with the intervention features was calculated for the entire cohort, and the differences between providers were explored statistically. RESULTS Data were available for 12,857 participants who enrolled in the NHS-digital-DPP during the data collection phase. Overall, 94.37% (12,133/12,857) of those enrolled engaged with the apps in the first 30 days. The median (IQR) number of days of use was 11 (2-25). Track features were engaged with the most (number of tracking events: median 46, IQR 3-22), and Peer Support features were the least engaged with, a median value of 0 (IQR 0-0). Differences in engagement with features were observed across providers. Qualitative findings offer explanations for the variations, including suggesting the importance of health coaches, reminders, and regular content updates to facilitate early engagement. CONCLUSIONS Almost all participants in the NHS-digital-DPP started using the apps. Differences across providers identified by the mixed methods analysis provide the opportunity to identify features that are important for engagement with digital health interventions and could inform the design of other digital behavior change interventions.
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Affiliation(s)
- Jamie Ross
- Centre for Primary Care, Wolfson Institute of Population Health Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Rhiannon E Hawkes
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Lisa M Miles
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Sarah Cotterill
- Centre for Biostatistics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Peter Bower
- NIHR Applied Research Collaboration Greater Manchester, Centre for Primary Care and Health Services Research, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Elizabeth Murray
- e-health unit, Department of Primary Care and Population Health, Institute of Epidemiology & Health Care, University College London, London, United Kingdom
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Buis L, Rikhy M, Lockwood KG, Branch OH, Graham SA. The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination. JMIR Mhealth Uhealth 2023; 11:e40865. [PMID: 36735288 PMCID: PMC9938433 DOI: 10.2196/40865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/23/2022] [Accepted: 01/18/2023] [Indexed: 01/20/2023] Open
Affiliation(s)
| | - Mohit Rikhy
- Lark Health, Mountain View, CA, United States
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Graham SA, Pitter V, Hori JH, Stein N, Branch OH. Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence. Digit Health 2022; 8:20552076221130619. [PMID: 36238752 PMCID: PMC9551332 DOI: 10.1177/20552076221130619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 09/17/2022] [Indexed: 11/07/2022] Open
Abstract
Objective The National Diabetes Prevention Program (DPP) reduces diabetes incidence and
associated medical costs but is typically staffing-intensive, limiting
scalability. We evaluated an alternative delivery method with 3933 members
of a program powered by conversational Artificial Intelligence (AI) called
Lark DPP that has full recognition from the Centers for
Disease Control and Prevention (CDC). Methods We compared weight loss maintenance at 12 months between two groups: 1) CDC
qualifiers who completed ≥4 educational lessons over 9 months (n = 191)
and 2) non-qualifiers who did not complete the required CDC lessons but
provided weigh-ins at 12 months (n = 223). For a secondary aim, we removed
the requirement for a 12-month weight and used logistic regression to
investigate predictors of weight nadir in 3148 members. Results CDC qualifiers maintained greater weight loss at 12 months than
non-qualifiers (M = 5.3%, SE = .8 vs. M = 3.3%, SE = .8;
p = .015), with 40% achieving ≥5%. The weight nadir
of 3148 members was 4.2% (SE = .1), with 35% achieving ≥5%. Male sex
(β = .11; P = .009), weeks with ≥2
weigh-ins (β = .68; P < .0001), and
days with an AI-powered coaching exchange (β = .43;
P < .0001) were associated with a greater likelihood
of achieving ≥5% weight loss. Conclusions An AI-powered DPP facilitated weight loss and maintenance commensurate with
outcomes of other digital and in-person programs not powered by AI. Beyond
CDC lesson completion, engaging with AI coaching and frequent weighing
increased the likelihood of achieving ≥5% weight loss. An AI-powered program
is an effective method to deliver the DPP in a scalable, resource-efficient
manner to keep pace with the prediabetes epidemic.
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Affiliation(s)
- Sarah A. Graham
- OraLee H. Branch, Lark Health, 2570 El
Camino Real, Mountain View, CA 94040, USA.
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