Can We Use Commercial Mobile Apps Instead of Research Mobile Apps in Healthcare Research?

Engagement With a Relaxation and Mindfulness Mobile App Among People With Cancer: Exploratory Analysis of Use Data and Self-Reports From a Randomized Controlled Trial

BACKGROUND

Mobile health (mHealth) apps offer unique opportunities to support self-care and behavior change, but poor user engagement limits their effectiveness. This is particularly true for fully automated mHealth apps without any human support. Human support in mHealth apps is associated with better engagement but at the cost of reduced scalability.

OBJECTIVE

This work aimed to (1) describe the theory-informed development of a fully automated relaxation and mindfulness app to reduce distress in people with cancer (CanRelax app 2.0), (2) describe engagement with the app on multiple levels within a fully automated randomized controlled trial over 10 weeks, and (3) examine whether engagement was related to user characteristics.

METHODS

The CanRelax app 2.0 was developed in iterative processes involving input from people with cancer and relevant experts. The app includes evidence-based relaxation exercises, personalized weekly coaching sessions with a rule-based conversational agent, 39 self-enactable behavior change techniques, a self-monitoring dashboard with gamification elements, highly tailored reminder notifications, an educational video clip, and personalized in-app letters. For the larger study, German-speaking adults diagnosed with cancer within the last 5 years were recruited via the web in Switzerland, Austria, and Germany. Engagement was analyzed in a sample of 100 study participants with multiple measures on a micro level (completed coaching sessions, relaxation exercises practiced with the app, and feedback on the app) and a macro level (relaxation exercises practiced without the app and self-efficacy toward self-set weekly relaxation goals).

RESULTS

In week 10, a total of 62% (62/100) of the participants were actively using the CanRelax app 2.0. No associations were identified between engagement and level of distress at baseline, sex assigned at birth, educational attainment, or age. At the micro level, 71.88% (3520/4897) of all relaxation exercises and 714 coaching sessions were completed in the app, and all participants who provided feedback (52/100, 52%) expressed positive app experiences. At the macro level, 28.12% (1377/4897) of relaxation exercises were completed without the app, and participants' self-efficacy remained stable at a high level. At the same time, participants raised their weekly relaxation goals, which indicates a potential relative increase in self-efficacy.

CONCLUSIONS

The CanRelax app 2.0 achieved promising engagement even though it provided no human support. Fully automated social components might have compensated for the lack of human involvement and should be investigated further. More than one-quarter (1377/4897, 28.12%) of all relaxation exercises were practiced without the app, highlighting the importance of assessing engagement on multiple levels.

Perspective of patients with first-episode psychosis, their relatives, and mental health professionals on the design and usability of an app in clinical practice

AIM

Therapeutic non-compliance remains the main difficulty for people with psychotic disorders, standing around 50% in people with schizophrenia. Lack of treatment adherence, either partial or total, to medication has economic and clinical consequences. E-health technologies may be a promising therapeutic tool to improve adherence, with the subsequent reduction in clinical and economic burden. Our aims were to know the preferences on how technologies in mental health treatment should be for use in clinical practice, and to learn about the opinion and preferences on the use of technologies in mental health treatment from the perspectives of patients with FEP, their relatives, and mental health professionals.

METHODS

Forty-one patients with a diagnosis of first-episode psychosis (FEP), 18 relatives and 49 mental health professionals were included in the study. They completed an online survey related to the use, availability and user-skill of online platforms and apps created by a group of experts in psychosis and in the use of technologies. Data were summarized in frequencies, percentages, and means, and Chi-square tests were used to calculate differences between-groups.

RESULTS

An app directed to people with psychosis would be well received by users if it contains psychoeducational material, offers reminders for scheduled visits and treatment and allows online consultations.

CONCLUSIONS

Co-creating an app with users, their families and mental health professionals allows incorporating their preferences to increase its use, improve outpatient care and creating an app that is viable in clinical practice.

Governance of research and product improvement studies in consumer mental health apps. Interviews with researchers and app developers

Consumer mental health apps (MHAs) collect and generate mental health-related data on their users, which can be leveraged for research and product improvement studies. Such studies are associated with ethical issues that may be difficult for researchers and app developers to assess. To improve ethical study conduct, governance through rules, agreements and customs could be relied upon, but their translation into practice is subject to barriers. This qualitative interview study with 17 researchers and app developers looked into the role and impact of governance standards on consumer MHA studies. Interviewees experienced a significant number of rules, agreements and customs, although not all of the governance standards that can potentially be applicable. Standards did have an impact on the interests of researchers and app developers, app users and society, but this impact was mediated by several barriers related to their conceptualization and implementation. Conceptualization barriers impacted the development of a standard, the inclusion of relevant concepts and the coordination between standards. Implementation barriers concerned the resource cost of understanding a standard, as well as suboptimal enforcement. The framework developed in this study can support more effective efforts to improve the governance of future consumer MHA studies.

"Hey Siri, Help Me Take Care of My Child": A Feasibility Study With Caregivers of Children With Special Healthcare Needs Using Voice Interaction and Automatic Speech Recognition in Remote Care Management

Background

About 23% of households in the United States have at least one child who has special healthcare needs. As most care activities occur at home, there is often a disconnect and lack of communication between families, home care nurses, and healthcare providers. Digital health technologies may help bridge this gap.

Objective

We conducted a pre-post study with a voice-enabled medical note taking (diary) app (SpeakHealth) in a real world setting with caregivers (parents, family members) of children with special healthcare needs (CSHCN) to understand feasibility of voice interaction and automatic speech recognition (ASR) for medical note taking at home.

Methods

In total, 41 parents of CSHCN were recruited. Participants completed a pre-study survey collecting demographic details, technology and care management preferences. Out of 41, 24 participants completed the study, using the app for 2 weeks and completing an exit survey. The app facilitated caregiver note-taking using voice interaction and ASR. An exit survey was conducted to collect feedback on technology adoption and changes in technology preferences in care management. We assessed the feasibility of the app by descriptively analyzing survey responses and user data following the key focus areas of acceptability, demand, implementation and integration, adaptation and expansion. In addition, perceived effectiveness of the app was assessed by comparing perceived changes in mobile app preferences among participants. In addition, the voice data, notes, and transcriptions were descriptively analyzed for understanding the feasibility of the app.

Results

The majority of the recruited parents were 35–44 years old (22, 53.7%), part of a two-parent household (30, 73.2%), white (37, 90.2%), had more than one child (31, 75.6%), lived in Ohio (37, 90.2%), used mobile health apps, mobile note taking apps or calendar apps (28, 68.3%) and patient portal apps (22, 53.7%) to track symptoms and health events at home. Caregivers had experience with voice technology as well (32, 78%). Among those completed the post-study survey (in Likert Scale 1–5), ~80% of the caregivers agreed or strongly agreed that using the app would enhance their performance in completing tasks (perceived usefulness; mean = 3.4, SD = 0.8), the app is free of effort (perceived ease of use; mean = 3.2, SD = 0.9), and they would use the app in the future (behavioral intention; mean = 3.1, SD = 0.9). In total, 88 voice interactive patient notes were generated with the majority of the voice recordings being less than 20 s in length (66%). Most noted symptoms and conditions, medications, treatment and therapies, and patient behaviors. More than half of the caregivers reported that voice interaction with the app and using transcribed notes positively changed their preference of technology to use and methods for tracking symptoms and health events at home.

Conclusions

Our findings suggested that voice interaction and ASR use in mobile apps are feasible and effective in keeping track of symptoms and health events at home. Future work is suggested toward using integrated and intelligent systems with voice interactions with broader populations.

REDCap mobile data collection: Using implementation science to explore the potential and pitfalls of a digital health tool in routine voluntary medical male circumcision outreach settings in Zimbabwe

Background

Digital data collection tools improve data quality but are limited by connectivity. ZAZIC, a Zimbabwean consortium focused on scaling up male circumcision (MC) services, provides MC in outreach settings where both data quality and connectivity is poor. ZAZIC implemented REDCap Mobile app for data collection among roving ZAZIC MC nurses. To inform continued scale-up or discontinuation, this paper details if, how, and for whom REDCap improved data quality using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.

Methods

Data were collected for this retrospective, cross-sectional study for nine months, from July 2019 to March 2020, before COVID-19 paused MC services. Data completeness was compared between paper- and REDCap-based tools and between two ZAZIC partners using two sample, one-tailed t-tests.

Results

REDCap reached all roving nurses who reported 26,904 MCs from 1773 submissions. REDCap effectiveness, as measured by data completeness, decreased from 89.2% in paper to 76.6% in REDCap app for Partner 1 (p < 0.001, 95% CI: -0.24, -0.12) but increased modestly from 86.2% to 90.3% in REDCap for Partner 2 (p = 0.05, 95% CI: -.007, 0.12). Adoption of REDCap was 100%; paper-based reporting concluded in October 2019. Implementation varied by partner and user. Maintenance appeared high.

Conclusion

Although initial transition from paper to REDCap showed mixed effectiveness, post-hoc analysis from service resumption found increased REDCap data completeness across partners, suggesting locally-led momentum for REDCap-based data collection. Staff training, consistent mentoring, and continued technical support appear critical for continued use of digital health tools for quality data collection in rural Zimbabwe and similar low connectivity settings.