Development of a Web-Based Acceptance and Commitment Therapy Intervention to Support Lifestyle Behavior Change and Well-Being in Health Care Staff: Participatory Design Study

Adaptation of ACTivate Your Wellbeing, a Digital Health and Well-being Program for Young Persons: Co-design Approach

BACKGROUND

ACTivate your wellbeing is a digital health and well-being program designed to support and encourage positive lifestyle behavior change. The website includes 5 lifestyle behavior change modules and a 12-week well-being intervention based on acceptance and commitment therapy. It was timely to adapt the resource for a new audience in the wake of the COVID-19 pandemic. Young persons' mental health needs have increased substantially, and lifestyle behaviors play a critical role in both mental and physical health statuses.

OBJECTIVE

This study aimed to adapt an existing health and well-being website for use by young persons aged 16 to 24 years.

METHODS

A 3-staged participatory, co-design approach was adopted. The participants reviewed the existing program and provided feedback (stage 1) before cocreating new content (stage 2). Finally, the updated program underwent formative evaluation (stage 3). Two groups were created: one had access for 3 weeks and the other could self-select their study duration. The options were 3 weeks, 60 days, or 90 days. Outcome measures were the Warwick and Edinburgh Mental Well-being Scale, 4-item Patient Health Questionnaire, and Acceptance and Action Questionnaire version 2.

RESULTS

Stage 1 identified that the website was appealing to the new audience (19/24, 79%), and the 3 web-based focus group discussions explored data from the written review in more depth to identify and clarify the main areas for update and adaptation. Overall, 3 themes were developed, and the data informed the creation of 6 tasks for use in 5 web-based co-design workshops. Stage 2 led to the cocreation of 36 outputs, including a new name, new content, scenarios, images, and a new user dashboard, which included streaks and an updated color scheme. After the website update program was completed, 40 participants registered to use the website for formative evaluation (stage 3). Data analysis revealed differences in engagement, completion, and mean well-being after intervention between the 2 groups. The completion rate was 68% in the 3-week duration group, and well-being scores improved after intervention.

CONCLUSIONS

Young persons engaged actively with the participatory design process. The participants discussed the updates they desired during the web-based discussions, which worked well via Zoom (Zoom Video Communications Inc) when small groups were used. The participants easily cocreated new content during the web-based co-design workshops. The web-based format enabled a range of participants to take part, share their ideas, search for images, and design digital content creatively together. The Zoom software enabled screen sharing and collaborative whiteboard use, which helped the cocreation process. The formative evaluation suggested that younger users who engage more with the website for a shorter duration may benefit more.

eHealth-Based Psychosocial Interventions for Adults With Insomnia: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Worldwide, insomnia remains a highly prevalent public health problem. eHealth presents a novel opportunity to deliver effective, accessible, and affordable insomnia treatments on a population-wide scale. However, there is no quantitative integration of evidence regarding the effectiveness of eHealth-based psychosocial interventions on insomnia.

OBJECTIVE

We aimed to evaluate the effectiveness of eHealth-based psychosocial interventions for insomnia and investigate the influence of specific study characteristics and intervention features on these effects.

METHODS

We searched PubMed, Embase, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials from database inception to February 16, 2021, for publications investigating eHealth-based psychosocial interventions targeting insomnia and updated the search of PubMed to December 6, 2021. We also screened gray literature for unpublished data. Eligible studies were randomized controlled trials of eHealth-based psychosocial interventions targeting adults with insomnia. Random-effects meta-analysis models were used to assess primary and secondary outcomes. Primary outcomes were insomnia severity and sleep quality. Meta-analyses were performed by pooling the effects of eHealth-based psychosocial interventions on insomnia compared with inactive and in-person conditions. We performed subgroup analyses and metaregressions to explore specific factors that affected the effectiveness. Secondary outcomes included sleep diary parameters and mental health-related outcomes.

RESULTS

Of the 19,980 identified records, 37 randomized controlled trials (13,227 participants) were included. eHealth-based psychosocial interventions significantly reduced insomnia severity (Hedges g=-1.01, 95% CI -1.12 to -0.89; P<.001) and improved sleep quality (Hedges g=-0.58, 95% CI -0.75 to -0.41; P<.001) compared with inactive control conditions, with no evidence of publication bias. We found no significant difference compared with in-person treatment in alleviating insomnia severity (Hedges g=0.41, 95% CI -0.02 to 0.85; P=.06) and a significant advantage for in-person treatment in enhancing sleep quality (Hedges g=0.56, 95% CI 0.24-0.88; P<.001). eHealth-based psychosocial interventions had significantly larger effects (P=.01) on alleviating insomnia severity in clinical samples than in subclinical samples. eHealth-based psychosocial interventions that incorporated guidance from trained therapists had a significantly greater effect on insomnia severity (P=.05) and sleep quality (P=.02) than those with guidance from animated therapists or no guidance. Higher baseline insomnia severity and longer intervention duration were associated with a larger reduction in insomnia severity (P=.004). eHealth-based psychosocial interventions significantly improved each secondary outcome.

CONCLUSIONS

eHealth interventions for insomnia are effective in improving sleep and mental health and can be considered a promising treatment for insomnia. Our findings support the wider dissemination of eHealth interventions and their further promotion in a stepped-care model. Offering blended care could improve treatment effectiveness. Future research needs to elucidate which specific intervention components are most important to achieve intervention effectiveness. Blended eHealth interventions may be tailored to benefit people with low socioeconomic status, limited access to health care, or lack of eHealth literacy.

Use of a Mobile App for the Process Evaluation of an Intervention in Health Care: Development and Usability Study

BACKGROUND

Process evaluation measures the context in which an outcome was or was not achieved through the ongoing monitoring of operations. Mobile apps are a potentially less burdensome tool for collecting these metrics in real time from participants. Research-driven apps are not always developed while paying attention to their usability for target users. Usability testing uncovers gaps in researchers', developers', and users' mental models of what an efficient, effective, and satisfying product looks like and facilitates design improvement. Models may vary by user demographics.

OBJECTIVE

This study describes the development of a mobile app for collecting process evaluation metrics in an intervention study with health care workers that uses feedback at multiple stages to refine the app design, quantify usage based on workers' overall adoption of the app and the app's specific function, and compare the demographic and job characteristics of end users.

METHODS

An app was developed to evaluate the Center for Promotion of Health in the New England Workplace Healthy Workplace Participatory Program, which trains teams to develop solutions for workforce health obstacles. Labor-management health and safety committee members, program champions, and managers were invited to use the app. An accompanying website was available for team facilitators. The app's 4 functions were meeting creation, postmeeting surveys, project time logs, and chat messages. Google Analytics recorded screen time. Two stages of pilot tests assessed functionality and usability across different device software, hardware, and platforms. In stage 1, student testers assessed the first functional prototype by performing task scenarios expected from end users. Feedback was used to fix issues and inform further development. In stage 2, the app was offered to all study participants; volunteers completed task scenarios and provided feedback at deployment. End user data for 18 months after deployment were summarized and compared by user characteristics.

RESULTS

In stage 1, functionality problems were documented and fixed. The System Usability Scale scores from 7 student testers corresponded to good usability (mobile app=72.9; website=72.5), whereas 15 end users rated usability as ok (mobile app=64.7; website=62.5). Predominant usability themes from student testers were flexibility and efficiency and visibility of system status; end users prioritized flexibility andefficiency and recognition rather than recall. Both student testers and end users suggested useful features that would have resulted in the large-scale restructuring of the back end; these were considered for their benefits versus cost. In stage 2, the median total use time over 18 months was 10.9 minutes (IQR 23.8) and 14.5 visits (IQR 12.5). There were no observable patterns in use by demographic characteristics.

CONCLUSIONS

Occupational health researchers developing a mobile app should budget for early and iterative testing to find and fix problems or usability issues, which can increase eventual product use and prevent potential gaps in data.