Exploring the Feasibility of Using ChatGPT to Create Just-in-Time Adaptive Physical Activity mHealth Intervention Content: Case Study.

BACKGROUND: Achieving physical activity (PA) guidelines' recommendation of 150 minutes of moderate-to-vigorous PA per week has been shown to reduce the risk of many chronic conditions. Despite the overwhelming evidence in this field, PA levels remain low globally. By creating engaging mobile health (mHealth) interventions through strategies such as just-in-time adaptive interventions (JITAIs) that are tailored to an individual's dynamic state, there is potential to increase PA levels. However, generating personalized content can take a long time due to various versions of content required for the personalization algorithms. ChatGPT presents an incredible opportunity to rapidly produce tailored content; however, there is a lack of studies exploring its feasibility. OBJECTIVE: This study aimed to (1) explore the feasibility of using ChatGPT to create content for a PA JITAI mobile app and (2) describe lessons learned and future recommendations for using ChatGPT in the development of mHealth JITAI content. METHODS: During phase 1, we used Pathverse, a no-code app builder, and ChatGPT to develop a JITAI app to help parents support their child's PA levels. The intervention was developed based on the Multi-Process Action Control (M-PAC) framework, and the necessary behavior change techniques targeting the M-PAC constructs were implemented in the app design to help parents support their child's PA. The acceptability of using ChatGPT for this purpose was discussed to determine its feasibility. In phase 2, we summarized the lessons we learned during the JITAI content development process using ChatGPT and generated recommendations to inform future similar use cases. RESULTS: In phase 1, by using specific prompts, we efficiently generated content for 13 lessons relating to increasing parental support for their child's PA following the M-PAC framework. It was determined that using ChatGPT for this case study to develop PA content for a JITAI was acceptable. In phase 2, we summarized our recommendations into the following six steps when using ChatGPT to create content for mHealth behavior interventions: (1) determine target behavior, (2) ground the intervention in behavior change theory, (3) design the intervention structure, (4) input intervention structure and behavior change constructs into ChatGPT, (5) revise the ChatGPT response, and (6) customize the response to be used in the intervention. CONCLUSIONS: ChatGPT offers a remarkable opportunity for rapid content creation in the context of an mHealth JITAI. Although our case study demonstrated that ChatGPT was acceptable, it is essential to approach its use, along with other language models, with caution. Before delivering content to population groups, expert review is crucial to ensure accuracy and relevancy. Future research and application of these guidelines are imperative as we deepen our understanding of ChatGPT and its interactions with human input.

The Development of a Hypertension Prevention and Financial-Incentive mHealth Program Using a "No-Code" Mobile App Builder: Development and Usability Study.

BACKGROUND: Regular physical activity (PA) is a key lifestyle component for hypertension prevention. Previous studies have shown that mobile health (mHealth) apps can be an effective tool for improving PA behaviors. However, adherence to and poor engagement with these apps is a challenge. A potential solution to overcome this challenge may be to combine financial incentives with innovative behavior theory, such as the Multiprocess Action Control (M-PAC) framework. Currently, there is a lack of PA financial incentive-driven M-PAC mHealth programs aimed at hypertension prevention. OBJECTIVE: We aimed to describe the process of developing an 8-week mHealth PA and financial-incentive hypertension education program (Healthy Hearts) and to evaluate usability of the Healthy Hearts program. METHODS: The first 2 stages of the Integrate, Design, Assess, and Share framework were used to guide the development of the Healthy Hearts program. The development process consisted of 2 phases. In phase 1, the research team met to discuss implementing the M-PAC framework to adopt an existing web-based hypertension prevention program to a mobile app. The app was developed using a no-code app development platform, Pathverse (Pathverse Inc), to help decrease overall development time. In phase 2, we created a prototype and conducted usability testing to evaluate lesson 1 of the Healthy Hearts program to further enhance the user experience. We used semistructured interviews and the mHealth App Usability Questionnaire to evaluate program acceptability and usability. RESULTS: Intervention development among the research team successfully created an 8-week financial-incentive hypertension education program for adults aged 40-65 years who did not currently meet the Canadian Physical Activity Guidelines (<150 minutes of moderate to vigorous PA per week). This program lasted 8 weeks and comprised 25 lessons guided by the M-PAC framework. The program used various behavior change techniques to further support PA adherence. Usability testing of the first lesson was successful, with 6 participants recruited for 2 rounds of testing. Feedback was gathered to enhance the content, layout, and design of the Healthy Hearts program to prepare the mHealth program for feasibility testing. Results of round 1 of usability testing suggested that the content delivered in the lessons was long. Therefore, the content was divided into multiple lessons before round 2 of usability testing, where feedback was only on design preferences. A minimum viable product was created with these results. CONCLUSIONS: The iterative development process and the usability assessments suggested by the Integrate, Design, Assess, and Share framework enabled participants to provide valuable feedback on the content, design, and layout of the program before advancing to feasibility testing. Furthermore, the use of the "no-code" app development tool enabled our team to rapidly make changes to the app based on user feedback during the iterative design process.

Effects of Mobile-Based Financial Incentive Interventions for Adults at Risk of Developing Hypertension: Feasibility Randomized Controlled Trial.

BACKGROUND: Hypertension is the leading modifiable risk factor for cardiovascular disease and mortality. Adopting lifestyle modifications, like increasing physical activity (PA), can be an effective strategy in blood pressure (BP) control, but many adults do not meet the PA guidelines. Financial incentive interventions have the power to increase PA levels but are often limited due to cost. Further, mobile health technologies can make these programs more scalable. There is a gap in the literature about the most feasible and effective financial incentive PA framework; thus, pay-per-minute (PPM) and self-funded investment incentive (SFII) frameworks were explored. OBJECTIVE: The aims were to (1) determine the feasibility (recruitment, engagement, and acceptability) of an 8-week mobile-based PPM and SFII hypertension prevention PA program and (2) explore the effects of PPM and SFII interventions relative to a control on the PA levels, BP, and PA motivation. METHODS: In total, 55 adults aged 40-65 years not meeting the Canadian PA guidelines were recruited from Facebook and randomized into the following groups: financial incentive groups, PPM or SFII, receiving up to CAD $20 each (at the time of writing: CAD $1=US $0.74), or a control group without financial incentive. PPM participants received CAD $0.02 for each minute of moderate-to-vigorous PA (MVPA) per week up to the PA guidelines and the SFII received CAD $2.50 for each week they met the PA guidelines. Feasibility outcome measures (recruitment, engagement, and acceptability) were assessed. Secondary outcomes included changes in PA outcomes (MVPA and daily steps) relative to baseline were compared among PPM, SFII, and control groups at 4 and 8 weeks using linear regressions. Changes in BP and relative autonomy index relative to baseline were compared among the groups at follow-up. RESULTS: Participants were randomized to the PPM (n=19), SFII (n=18), or control (n=18) groups. The recruitment, retention rate, and engagement were 77%, 75%, and 65%, respectively. The intervention received overall positive feedback, with 90% of comments praising the intervention structure, financial incentive, and educational materials. Relative to the control at 4 weeks, the PPM and SFII arms increased their MVPA with medium effect (PPM vs control: η2p=0.06, mean 117.8, SD 514 minutes; SFII vs control: η2p=0.08, mean 145.3, SD 616 minutes). At 8 weeks, PPM maintained a small effect in MVPA relative to the control (η2p=0.01, mean 22.8, SD 249 minutes) and SFII displayed a medium effect size (η2p=0.07, mean 113.8, SD 256 minutes). Small effects were observed for PPM and SFII relative to the control for systolic blood pressure (SBP) and diastolic blood pressure (DBP) (PPM: η2p=0.12, Δmean SBP 7.1, SD 23.61 mm Hg; η2p=0.04, Δmean DBP 3.5, SD 6.2 mm Hg; SFII: η2p=0.01, Δmean SBP -0.4, SD 1.4 mm Hg; η2p=0.02, Δmean DBP -2.3, SD 7.7 mm Hg) and relative autonomy index (PPM: η2p=0.01; SFII: η2p=0.03). CONCLUSIONS: The feasibility metrics and preliminary findings suggest that a future full-scale randomized controlled trial examining the efficacy of PPM and SFII relative to a control is feasible, and studies with longer duration are warranted.

A "No-Code" App Design Platform for Mobile Health Research: Development and Usability Study.

BACKGROUND: A challenge facing researchers conducting mobile health (mHealth) research is the amount of resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of "no-code" software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. OBJECTIVE: We aimed to describe the development process and the lessons learned to build Pathverse, a no-code mHealth app design platform. METHODS: The study took place between November 2019 and December 2021. We used a participatory research framework to develop the mHealth app design platform. In phase 1, we worked with researchers to gather key platform feature requirements and conducted an exploratory literature search to determine needs related to this platform. In phase 2, we used an agile software framework (Scrum) to develop the platform. Each development sprint cycle was 4 weeks in length. We created a minimum viable product at the end of 7 sprint cycles. In phase 3, we used a convenience sample of adults (n=5) to gather user feedback through usability and acceptability testing. In phase 4, we further developed the platform based on user feedback, following the V-model software development process. RESULTS: Our team consulted end users (ie, researchers) and utilized behavior change technique taxonomy and behavior change models (ie, the multi-process action control framework) to guide the development of features. The first version of the Pathverse platform included features that allowed researchers to (1) design customized multimedia app content (eg, interactive lessons), (2) set content delivery logic (eg, only show new lessons when completing the previous lesson), (3) implement customized participant surveys, (4) provide self-monitoring tools, (5) set personalized goals, and (6) customize app notifications. Usability and acceptability testing revealed that researchers found the platform easy to navigate and that the features were intuitive to use. Potential improvements include the ability to deliver adaptive interventions and add features such as community group chat. CONCLUSIONS: To our knowledge, Pathverse is the first no-code mHealth app design platform for developing mHealth interventions for behavior. We successfully used behavior change models and the behavior change technique taxonomy to inform the feature requirements of Pathverse. Overall, the use of a participatory framework, combined with the agile and hybrid-agile software development process, enabled our team to successfully develop the Pathverse platform.