Experiences of mobile health in promoting physical activity: A qualitative systematic review and meta-ethnography

"I think it was helpful but not as helpful as it could have been" - a qualitative study of the experiences and perspectives of using fitness apps among manual wheelchair users with spinal cord injury

PURPOSE

To gain knowledge of the experiences and perceptions of using fitness apps by full-time wheelchair users with spinal cord injury (SCI) and to explore experiences and perceptions of using these apps in relation to barriers to and facilitators of physical activity (PA).

MATERIALS AND METHODS

A qualitative design was employed. Semi-structured interviews were conducted with ten manual wheelchair users with SCI. Data were analysed using reflexive thematic analysis.

RESULTS

Four themes were developed: 1) App functionality and experience, 2) Enhancing motivation, 3) Precursors to engagement and 4) Knowledge gaps. Experience and perception were strongly influenced by app design, particularly the presence or absence of features tailored for wheelchair users. Many apps incorporated the use wearable or mountable sensors. Fitness apps were perceived to increase motivation, although, this had its limitations. Conversely, apps were reported to have limited influence on commonly reported barriers to PA. Furthermore, the data highlighted gaps in knowledge which created barriers to effective app use.

CONCLUSIONS

Fitness apps were perceived to increase motivation to engage in PA in manual wheelchair users with SCI. However, more needs to be done to further develop app features for wheelchair users with SCI and to address remaining barriers to engagement.

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview

BACKGROUND

Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing.

OBJECTIVE

First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field.

METHODS

A scoping review was conducted based on the framework by Arksey and O'Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given.

RESULTS

In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages.

CONCLUSIONS

The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.

Feasibility of a 10-week community-based mobile health rehabilitation program using the WalkWithMe application in late sub-acute and chronic stroke survivors in a low resource setting: A pilot study

 Physical functioning can be increased in people with stroke by using a mobile health application. This study aimed to investigate the feasibility of a 10-week community-based program using the WalkWithMe (WWM) application in people with late sub-acute and chronic stroke in Benin. An interventional pilot study with mixed methods research design was used examining the application of an unsupervised individualized mobile Health (mHealth) instructed training program. Main outcome included the application usage, safety, adherence, perceived enjoyment, mHealth quality, patient experiences and pre-post efficacy measures. Nine adults, five males, median age of 60 years and time since stroke of 12 months participated in this study. For most participants adherence with the application was over 70%. However, some usability problems were observed due to incorrect understanding and use by participants and technical problems. The application was very fun, stimulating and enjoyable. Significant improvements were found with median (pre/post measures) of locomotors skill (1.4/3.4); impairments (38/40), Barthel Index (85/95), activity limitation (2.1/3.1), and quality of life (194/218). A trend towards significant improvement was found with 6 minutes walking test (181/220, p = 0.06). The WWM application is perceived as a potential approach to increase physical activity and functioning among people with stroke in Benin.

Attraction and achievement as 2 attributes of gamification in healthcare: an evolutionary concept analysis

This study conducted a conceptual analysis of gamification in healthcare utilizing Rogers’ evolutionary concept analysis methodology to identify its attributes and provide a method for its applications in the healthcare field. Gamification has recently been used as a health intervention and education method, but the concept is used inconsistently and confusingly. A literature review was conducted to derive definitions, surrogate terms, antecedents, influencing factors, attributes (characteristics with dimensions and features), related concepts, consequences, implications, and hypotheses from various academic fields. A total of 56 journal articles in English and Korean, published between August 2 and August 7, 2023, were extracted from databases such as PubMed Central, the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery Digital Library, the Research Information Sharing Service, and the Korean Studies Information Service System, using the keywords “gamification” and “healthcare.” These articles were then analyzed. Gamification in healthcare is defined as the application of game elements in health-related contexts to improve health outcomes. The attributes of this concept were categorized into 2 main areas: attraction and achievement. These categories encompass various strategies for synchronization, enjoyable engagement, visual rewards, and goal-reinforcing frames. Through a multidisciplinary analysis of the concept’s attributes and influencing factors, this paper provides practical strategies for implementing gamification in health interventions. When developing a gamification strategy, healthcare providers can reference this analysis to ensure the game elements are used both appropriately and effectively.

Lessons and Untapped Potential of Smartphone-Based Physical Activity Interventions for Mental Health: Narrative Review

BACKGROUND

Physical activity has well-known and broad health benefits, including antidepressive and anxiolytic effects. However, only approximately half of Americans meet even the minimum exercise recommendations. Individuals with anxiety, depression, or related conditions are even less likely to do so. With the advent of mobile sensors and phones, experts have quickly noted the utility of technology for the enhanced measurement of and intervention for physical activity. In addition to being more accessible than in-person approaches, technology-driven interventions may uniquely engage key mechanisms of behavior change such as self-awareness.

OBJECTIVE

This study aims to provide a narrative overview and specific recommendations for future research on smartphone-based physical activity interventions for psychological disorders or concerns.

METHODS

In this paper, we summarized early efforts to adapt and test smartphone-based or smartphone-supported physical activity interventions for mental health. The included articles described or reported smartphone-delivered or smartphone-supported interventions intended to increase physical activity or reduce sedentary behavior and included an emotional disorder, concern, or symptom as an outcome measure. We attempted to extract details regarding the intervention designs, trial designs, study populations, outcome measures, and inclusion of adaptations specifically for mental health. In taking a narrative lens, we drew attention to the type of work that has been done and used these exemplars to discuss key directions to build on.

RESULTS

To date, most studies have examined mental health outcomes as secondary or exploratory variables largely in the context of managing medical concerns (eg, cancer and diabetes). Few trials have recruited psychiatric populations or explicitly aimed to target psychiatric concerns. Consequently, although there are encouraging signals that smartphone-based physical activity interventions could be feasible, acceptable, and efficacious for individuals with mental illnesses, this remains an underexplored area.

CONCLUSIONS

Promising avenues for tailoring validated smartphone-based interventions include adding psychoeducation (eg, the relationship between depression, physical activity, and inactivity), offering psychosocial treatment in parallel (eg, cognitive restructuring), and adding personalized coaching. To conclude, we offer specific recommendations for future research, treatment development, and implementation in this area, which remains open and promising for flexible, highly scalable support.

Promoting Physical and Mental Health among Children and Adolescents via Gamification-A Conceptual Systematic Review

The rapid growth in digital technology usage among children and adolescents has highlighted the need for novel approaches to promote their physical and mental health. This paper investigates the viability of gamification-the application of game mechanics to non-gaming contexts-as a potent instrument for health promotion and mental health support. This conceptual systematic review seeks to examine the various published articles promoting children and adolescents' physical and mental health through gamified techniques. These interventions can provide an interactive and engaging platform for encouraging physical activity, promoting healthy nutrition, enhancing emotional regulation, and promoting mental health. The significance of this topic stems from the pervasive use of electronic games, beginning at a young age, which makes them popular educational tools. For the review to be systematic and reproducible, the PsycINFO, Scopus, PubMed, and Elsevier databases were searched and the PRISMA method was utilized for the analysis. After analyzing the research data, empirical studies assessing the use of gamification in promoting adolescents' physical and mental health are discussed. In conclusion, gamification has demonstrated promise for promoting children's and adolescents' physical and mental health. It improves motivation, commitment, and adherence to healthy behaviors. However, additional research is required to evaluate gamification interventions' long-term effectiveness and sustainability in promoting health behaviors among this population.

Sequential multiple assignment randomised trial to develop an adaptive mobile health intervention to increase physical activity in people poststroke in the community setting in Ireland: TAPAS trial protocol

INTRODUCTION

Stroke is the second-leading cause of death and disability globally. Participation in physical activity (PA) is a cornerstone of secondary prevention in stroke care. Given the heterogeneous nature of stroke, PA interventions that are adaptive to individual performance are recommended. Mobile health (mHealth) has been identified as a potential approach to supporting PA poststroke. To this end, we aim to use a Sequential Multiple Assignment Randomised Trial (SMART) design to develop an adaptive, user-informed mHealth intervention to improve PA poststroke.

METHODS AND ANALYSIS

The components included in the 12-week intervention are based on empirical evidence and behavioural change theory and will include treatments to increase participation in Structured Exercise and Lifestyle or a combination of both. 117 participants will be randomly assigned to one of the two treatment components. At 6 weeks postinitial randomisation, participants will be classified as responders or non-responders based on participants' change in step count. Non-responders to the initial treatment will be randomly assigned to a different treatment allocation. The primary outcome will be PA (steps/day), feasibility and secondary clinical and cost outcomes will also be included. A SMART design will be used to evaluate the optimum adaptive PA intervention among community-dwelling, ambulatory people poststroke.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the Health Service Executive Mid-Western Ethics Committee (REC Ref: 026/2022). The findings will be submitted for publication and presented at relevant national and international academic conferences TRIALS REGISTRATION NUMBER: NCT05606770.

The effects of mobile technology-based support on young women with depressive symptoms: A block randomized controlled trial

BACKGROUND

The current body of knowledge highlights the potential role of mobile technology as a medium to deliver support for psychological and physical health. This study evaluated the influence of mobile technology support on depressive symptoms and physical activity in female university students.

METHODS

A block randomized controlled trial design with a single site was used. Ninety-nine participants were block-randomized into 3 arms: Experimental Group 1 (emotional and informational support group), Experimental Group 2 (informational support group), and the control group. Interventions were delivered via mobile technology for 2 weeks. Data on depressive symptoms and physical activity were collected from 84 participants at baseline and on Days 8 and 15. Data analyses included descriptive statistics, t tests, one-way analysis of variance, and repeated-measures analysis of variance.

RESULTS

This study showed no interaction effect of time and group on depressive symptom scores and physical activity, considering the emotional and informational support from mobile technology. However, Experimental Group 1 exhibited a significant reduction in depressive symptoms during the first week of the study compared to Experimental Group 2 and the control group. While physical activity in Experimental Group 2 and control group increased only during the first week of the study and subsequently decreased, Experimental Group 1 showed an initial increase during the first week that was sustained into the second week.

CONCLUSIONS

Since informational and emotional support showed a strong effect over a short period of time, mobile technology offering emotional support could be used to provide crisis interventions for depression among young women when a short-term impact is required.

Investigating Ecological Momentary Assessed Physical Activity and Core Executive Functions in 18- to 24-Year-Old Undergraduate Students

Although evidence for young children (<10) and older adults (>64) highlights an association between physical activity (PA) and executive functions (EFs), there is a paucity of research on adolescents aged 18-24 years. Thus, this study examined the associations between PA and EF and the difference in EF between individuals who achieve the moderate-to-vigorous (MVPA) guidelines and those who do not. Forty-seven participants engaged in a Stroop task, a reverse Corsi-block test, and a task-switching test, to measure inhibition, working memory, and cognitive flexibility, respectively. An ecological momentary assessment (EMA) was used to determine the participant's MVPA and step count, through the "Pathverse" app. Multiple regressions were run to predict the task-switch cost, the Stroop effect, and the backward Corsi span from time spent in MVPA. A two-way ANCOVA examined the effects of achieving the MVPA guidelines on EF. MVPA and step count did not significantly predict EF. There were no significant differences in EF between participants achieving the MVPA guidelines and those that did not. Time spent in MVPA and step count were not significantly associated with working memory, cognitive flexibility, or inhibition in adolescents. Further research is warranted to understand other factors that may significantly affect EF, within and outside an individual's control.

The Future of Stress Management: Integration of Smartwatches and HRV Technology

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management by measuring heart rate, heart rate variability (HRV), and various metrics related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and biofeedback using smartwatches pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. We apply various algorithms and methodologies employed for HRV analysis and stress detection including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers with using smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions.

Stimulating the Uptake of Preconception Care by Women With a Vulnerable Health Status Through mHealth App-Based Nudging (Pregnant Faster): Cocreation Design and Protocol for a Cohort Study

BACKGROUND

Women with a low socioeconomic status often have a vulnerable health status due to an accumulation of health-deteriorating factors such as poor lifestyle behaviors, including inadequate nutrition, mental stressors, and impaired health literacy and agency, which puts them at an unnecessary high risk of adverse pregnancy outcomes. Adequately preparing for pregnancy through preconception care (PCC) uptake and lifestyle improvement can improve these outcomes. We hypothesize that nudging is a successful way of encouraging engagement in PCC. A nudge is a behavioral intervention that changes choice behavior through influencing incentives. The mobile health (mHealth) app-based loyalty program Pregnant Faster aims to reward women in an ethically justified way and nudges to engage in pregnancy preparation by visiting a PCC consultation.

OBJECTIVE

Here, we first describe the process of the cocreation of the mHealth app Pregnant Faster that aims to increase engagement in pregnancy preparation by women with a vulnerable health status. Second, we describe the cohort study design to assess the feasibility of Pregnant Faster.

METHODS

The content of the app is based on the eHealth lifestyle coaching program Smarter Pregnancy, which has proven to be effective in ameliorating preconceptional lifestyle behaviors (folic acid, vegetables, fruits, smoking, and alcohol) and an interview study pertaining to the preferences of the target group with regard to an mHealth app stimulating PCC uptake. For moral guidance on the design, an ethical framework was developed based on the bioethical principles of Beauchamp and Childress. The app was further developed through iterative cocreation with the target group and health care providers. For 4 weeks, participants will engage with Pregnant Faster, during which opportunities will arise to earn coins such as reading informative blogs and registering for a PCC consultation. Coins can be spent on small fun rewards, such as folic acid, fruits, and mascara. Pregnant Faster's feasibility will be tested in a study including 40 women aged 18 to 45 years, who are preconceptional or <8 weeks pregnant, with a low educational level, and living in a deprived neighborhood. The latter 2 factors will serve as a proxy of a low socioeconomic status. Recruitment will take place through flyers, social media, and health care practices. After finalization, participants will evaluate the app through the "mHealth App Usability Questionnaire" and additional interviews or questionnaires.

RESULTS

Results are expected to be published by December 2023.

CONCLUSIONS

Pregnant Faster has been designed through iterative cocreation with the target group and health care professionals. With the designed study, we will test Pregnant Faster's feasibility. If overall user satisfaction and PCC uptake is achieved, the app will be further developed and the cohort will be continued with an additional 400 inclusions to establish effectiveness.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45293.

Influencing Factors to mHealth Uptake With Indigenous Populations: Qualitative Systematic Review

BACKGROUND

The advancements and abundance of mobile phones and portable health devices have created an opportunity to use mobile health (mHealth) for population health systems. There is increasing evidence for the feasibility and acceptance of mHealth with Indigenous populations. Providing a synthesis of qualitative findings of mHealth with Indigenous populations will gain insights into the strengths and challenges to mHealth use in Indigenous populations.

OBJECTIVE

This review aimed to identify and synthesize qualitative data pertaining to the experiences and perceptions of mHealth from the perspectives of end users (patients and service providers) living in the colonial settler democracies of Canada, Australia, New Zealand, the United States, the Pacific Islands, and the Sápmi region of northern Europe.

METHODS

In May 2021, systematic searches of peer-reviewed, scientific papers were conducted across the 5 databases of PubMed, CINAHL, Embase, PsycINFO, and Web of Science. Qualitative or mixed method studies were included where a mHealth intervention was the primary focus for responding to health challenges with Indigenous populations. Two authors independently screened papers for eligibility and assessed the risk of bias using a modified version of the Critical Appraisal Skills Programme. A meta-aggregative approach was used to analyze the findings of included studies.

RESULTS

Seventeen papers met the eligibility criteria, 8 studies with patients, 7 studies with service providers, and 2 studies that included both patients and service providers. Studies were conducted in Australia (n=10), Canada (n=2), New Zealand (n=2), Papua New Guinea (n=1), the United States (n=1), and Samoa (n=1). Our interpretation of these qualitative findings shows commonalities between Indigenous patients' and service providers' perceptions of mHealth. We summarize our findings in six themes: (1) mHealth literacy, (2) mHealth as a facilitator for connection and support, (3) mHealth content needed to be culturally relevant, (4) mHealth security and confidentiality, (5) mHealth supporting rather than replacing service providers, and (6) workplace and organizational capacity.

CONCLUSIONS

This research suggests that mHealth can meet the needs of both patients and service providers when the mHealth intervention is culturally relevant, accounts for digital and health literacy, incorporates interactive components, is supported by workplaces, fits into health provider workflows, and meets security and confidentiality standards. Future mHealth research with Indigenous populations should partner with key representatives (eg, patients, service providers, and executive leaders) in the mHealth design appropriate to the purpose, people, setting, and delivery.

Barriers to and Facilitators of Digital Health Among Culturally and Linguistically Diverse Populations: Qualitative Systematic Review

BACKGROUND

Health care systems have become increasingly more reliant on patients' ability to navigate the digital world. However, little research has been conducted on why some communities are less able or less likely to successfully engage with digital health technologies (DHTs), particularly among culturally and linguistically diverse (CaLD) populations.

OBJECTIVE

This systematic review aimed to determine the barriers to and facilitators of interacting with DHTs from the perspectives of CaLD population groups, including racial or ethnic minority groups, immigrants and refugees, and Indigenous or First Nations people.

METHODS

A systematic review and thematic synthesis of qualitative studies was conducted. Peer-reviewed literature published between January 2011 and June 2022 was searched across 3 electronic databases. Terms for digital health were combined with terms for cultural or linguistic diversity, ethnic minority groups, or Indigenous and First Nations people and terms related to barriers to accessing digital technologies. A qualitative thematic synthesis was conducted to identify descriptive and analytical themes of barriers to and facilitators of interacting with DHTs. Quality appraisal was performed using the Mixed Methods Appraisal Tool.

RESULTS

Of the 1418 studies identified in the electronic search, a total of 34 (2.4%) were included in this review. Half of the included studies (17/34, 50%) were conducted in the United States. There was considerable variation in terms of the CaLD backgrounds of the participants. In total, 26% (9/34) of the studies focused on Indigenous or First Nations communities, 41% (14/34) were conducted among ethnic minority populations, 15% (5/34) of the studies were conducted among immigrants, and 18% (6/34) were conducted in refugee communities. Of the 34 studies, 21 (62%) described the development or evaluation of a digital health intervention, whereas 13 (38%) studies did not include an intervention but instead focused on elucidating participants' views and behaviors in relation to digital health. From the 34 studies analyzed, 18 descriptive themes were identified, each describing barriers to and facilitators of interacting with DHTs, which were grouped into 7 overarching analytical themes: using technology, design components, language, culture, health and medical, trustworthiness, and interaction with others.

CONCLUSIONS

This study identified several analytic and descriptive themes influencing access to and uptake of DHTs among CaLD populations, including Indigenous and First Nations groups. We found that cultural factors affected all identified themes to some degree and that cultural and linguistic perspectives should be considered in the design and delivery of DHTs, with this best served through the inclusion of the target communities at all stages of development. This may improve the potential of DHTs to be more acceptable, appropriate, and accessible to population groups currently at risk of not obtaining the full benefits of digital health.

mHealth App Barriers, Usability, and Personalization: A Cross-Sectional Study from Egypt and Saudi Arabia

Mobile health (mHealth) has emerged as a substantial segment of eHealth. Herein, we conducted a cross-sectional study to investigate mHealth app barriers, usability, and personalization in Egypt and Saudi Arabia. We used a Google survey to recruit participants from both countries between the 15th of September and the 15th of October 2022. Among 299 participants (247 from Egypt and 52 from Saudi Arabia), aged ≥ 18 years, 27.4% reported mHealth app use. In the age-, sex-, and country-adjusted regression models, age > 25 years: OR (95% CI) = 1.98 (1.11, 3.54), residing in Saudi Arabia: OR (95% CI) = 4.33 (2.22, 8.48), and physical activity: OR (95% CI) = 2.53 (1.44, 4.44) were associated with mHealth app use. The main mHealth app purposes were lifestyle promotion (35.4%), diet and nutrition (30.5%), and administrative services (13.4%). On a scale from 20 to 100, mHealth app usability scores were 46.3% (20−40), 7.3% (41−60), 31.7% (61−80), and 14.7% (81−100). According to 93.9% of users, mHealth app features were modifiable to meet personal health goals, while 37% stated that mHealth apps helped them set new personal health goals. In conclusion, age, residing in Saudi Arabia (compared to Egypt), and physical activity were positively associated with mHealth app use. mHealth app feature personalization and helping users set new personal health goals were largely reported, suggesting that mHealth has the potential to help put personalized healthcare into practice.

Experiences of Health-Promoting Activities among Individuals with Knee Pain: The Halland Osteoarthritis Cohort

Knee pain is an early sign of knee osteoarthritis (KOA) and a risk factor for chronic widespread pain (CWP). Early prevention is vital, and more research is needed to understand health-promoting activities for individuals with knee pain from a patient perspective. This study aimed to explore how individuals with knee pain experienced health-promoting activities. Explorative qualitative design with inductive approach was applied to explore the experiences of 22 individuals (13 women, 9 men; median age: 52). Semi-structured interviews were conducted and analysed using latent qualitative content analysis. The results revealed health-promoting activities in individuals with knee pain and were interpreted in the overall theme, striving for balance in everyday life. Two categories explored the content in health-promoting activities: (1) Caring for the body-being physically active, having a healthy diet, and utilising support; and (2) Managing life stressors-allowing for recovery, promoting vitality, and safeguarding healthy relationships. In conclusion, individuals with knee pain described various health-promoting activities. They strived for balance in everyday life by caring for the body and managing life stressors. We suggest that a broader approach to everyday life can be helpful in treatment plans and health promotion to manage and prevent KOA and CWP, while striving for a healthy lifestyle.

Older adults and family caregivers’ experience of digital health technology in frailty care: A systematic review and meta-ethnography protocol

Background: Digital health technology has been identified as a valuable tool to support older adults with frailty needs in their home setting. Despite the numerous technologies and evaluations of these innovations, a synthesis of the older person and family caregivers’ experience using technology for support self-management has not been conducted to date.

Methods and analysis: A systematic review and meta-ethnography will be conducted in accordance with the PRISMA and eMERGe reporting guidelines. Four peer-reviewed empirical evidence databases will be searched (Medline (Ovid), CINAHL, EMBASE, PsycINFO) using a defined search strategy. Studies containing qualitative data on the experiences of older people or family caregivers of using digital health technology to support frailty care will be included. Covidence software will be used to screen studies and extract data. The Critical Appraisal Skills Programme (CASP) checklist for qualitative research will be used by two independent reviewers to appraise all included papers. A meta-ethnography will be undertaken in accordance with the seven-phase method described by Noblit and Hare: (1) Getting started, (2) Deciding what is relevant to the initial interest, (3) Reading the studies, (4) Determining how the studies are related, (5) Translating the studies into one another, (6) Synthesizing translations and (7) Expressing the synthesis.

Discussion: To the best of our knowledge, this will be the first systematic review to integrate and synthesize the findings of qualitative studies of older citizens’ experience of digital health technology. The findings of this meta-ethnography will endeavour to inform future research, policy and clinical practice. In particular, the results will help to inform the design of future digital health technology to meet the needs of older adults.

PROSPERO registration number: CRD42022314608.

Electronic Health Interventions for Patients With Breast Cancer: Systematic Review and Meta-Analyses

PURPOSE

Ongoing supportive care using electronic health (eHealth) interventions has the potential to provide remote support and improve health outcomes for patients with breast cancer. This study aimed to evaluate the effectiveness of eHealth interventions on patient-reported outcomes (quality of life [QOL], self-efficacy, and mental or physical health) for patients during and after breast cancer treatment and patient-reported experience measures (acceptability and engagement).

METHODS

Systematic review with meta-analyses (random-effects model) of randomized controlled trials was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Nine databases were searched using a prespecified search strategy. Patient-directed eHealth interventions for adult patients during or after active breast cancer treatment measuring QOL, self-efficacy, and mental (depressive, anxiety, and distress symptoms) or physical (physical activity, nutrition, and fatigue) health outcomes were included. Data from eligible full-text articles were independently extracted by six observers.

RESULTS

Thirty-two unique studies (4,790 patients) were included. All were health self-management interventions, and most were multicomponent (videos, forums, and electronic reminder systems) websites. Meta-analyses revealed a significant effect of eHealth interventions on QOL (standardized mean difference [SMD], 0.20 [95% CI, 0.03 to 0.36]), self-efficacy (SMD, 0.45 [95% CI, 0.24 to 0.65]), distress (SMD, -0.41 [95% CI,-0.63 to -0.20]), and fatigue (SMD, -0.37 [95% CI, -0.61 to -0.13]). Twenty-five studies (78.1%) measured patient-reported experience measures. Acceptability (n = 9) was high, with high ratings for satisfaction (range, 71%-100%), usefulness (range, 71%-95%), and ease-of-use (range, 73%-92%). Engagement (n = 25) decreased over time, but disease-focused information and interactive support were most engaging.

CONCLUSION

eHealth interventions may provide an acceptable and effective strategy for improving QOL, distress, self-efficacy, and fatigue among patients with breast cancer.

Older adults and family caregivers’ experience of digital health technology in frailty care: A systematic review and meta-ethnography protocol

Background: Digital health technology has been identified as a valuable tool to support older adults with frailty needs in their home setting. Despite the numerous technologies and evaluations of these innovations, a synthesis of the older person and family caregivers’ experience using technology for support self-management has not been conducted to date. Methods and analysis: A systematic review and meta-ethnography will be conducted in accordance with the PRISMA and eMERGe reporting guidelines. Four peer-reviewed empirical evidence databases will be searched (Medline (Ovid), CINAHL, EMBASE, PsycINFO) using a defined search strategy. Studies containing qualitative data on the experiences of older people or family caregivers of using digital health technology to support frailty care will be included. Covidence software will be used to screen studies and extract data. The Critical Appraisal Skills Programme (CASP) checklist for qualitative research will be used by two independent reviewers to appraise all included papers. A meta-ethnography will be undertaken in accordance with the seven-phase method described by Noblit and Hare: (1) Getting started, (2) Deciding what is relevant to the initial interest, (3) Reading the studies, (4) Determining how the studies are related, (5) Translating the studies into one another, (6) Synthesizing translations and (7) Expressing the synthesis. Discussion: To the best of our knowledge, this will be the first systematic review to integrate and synthesize the findings of qualitative studies of older citizens’ experience of digital health technology. The findings of this meta-ethnography will endeavour to inform future research, policy and clinical practice. In particular, the results will help to inform the design of future digital health technology to meet the needs of older adults. PROSPERO registration number: Submitted 05/04/2022 and currently under review.

Using mobile health applications to enhance physical activity in Saudi Arabia: a cross-sectional study on users' perceptions

BACKGROUND

This research aims to assess the users' perceptions of usability and quality of mobile health applications used for promoting physical activity in Saudi Arabia.

METHODS

This was a quantitative cross-sectional study. A survey was developed based on the Technology Acceptance Model (TAM) and the Mobile Application Rating Scale (MARS) and distributed among the Saudi population through social media to assess the users' perceptions of using mobile applications to enhance physical activity. The survey questionnaire consisted of 27 questions in six sections, including demographics (nine items), perceived usefulness (three items), perceived ease of use (three items), attitudes (three items), user experience (six items) and subjective quality (three items). All the participants were in Saudi Arabia and >15 y of age.

RESULTS

A total of 195 m-Health users participated in the survey. Of the total participants, 25.1% were overweight and 21.0% were obese. The workout frequency of most users was rarely (32.3%) and three to four times a week (29.2%). In addition, 55.9% of the users agreed that the application they use served all fitness levels and >80% either agreed or strongly agreed that it was easy for them to learn how to use the application. More than 70% of users agreed or strongly agreed that the application enhanced their knowledge of workouts and physical activity and >90% would recommend the application to others. There were no differences identified between the male and female participants and younger (<40 y) and older (>40 y) participants with respect to perceived usefulness and ease of use, attitudes, experiences and subjective quality. However, significant differences were observed between participants <40 y and >40 y of age in terms of perceived ease of use of mHealth applications.

CONCLUSION

mHealth users across Saudi Arabia believe that the mHealth applications have good usability and quality factors. As a result, they can motivate people and help them achieve their goals in relation to physical activities.

The Effect of Wearable Tracking Devices on Cardiorespiratory Fitness Among Inactive Adults: Crossover Study

Background

Modern lifestyle is associated with a high prevalence of physical inactivity.

Objective

This study aims to investigate the effect of a wearable tracking device on cardiorespiratory fitness among inactive adults and to explore if personal characteristics and health outcomes can predict adoption of the device.

Methods

In total, 62 inactive adults were recruited for this study. A control period (4 weeks) was followed by an intervention period (8 weeks) where participants were instructed to register and follow their physical activity (PA) behavior on a wrist-worn tracking device. Data collected included estimated cardiorespiratory fitness, body composition, blood pressure, perceived stress levels, and self-reported adoption of using the tracking device.

Results

In total, 50 participants completed the study (mean age 48, SD 13 years, 84% women). Relative to the control period, participants increased cardiorespiratory fitness by 1.52 mL/kg/minute (95% CI 0.82-2.22; P<.001), self-reported PA by 140 minutes per week (95% CI 93.3-187.1; P<.001), daily step count by 982 (95% CI 492-1471; P<.001), and participants’ fat percentage decreased by 0.48% (95% CI –0.84 to –0.13; P=.009). No difference was observed in blood pressure (systolic: 95% CI –2.16 to 3.57, P=.63; diastolic: 95% CI –0.70 to 2.55; P=.27) or perceived stress (95% CI –0.86 to 1.78; P=.49). No associations were found between adoption of the wearable tracking device and age, gender, personality, or education. However, participants with a low perceived stress at baseline were more likely to rate the use of a wearable tracking device highly motivating.

Conclusions

Tracking health behavior using a wearable tracking device increases PA resulting in an improved cardiorespiratory fitness among inactive adults.

Understanding Engagement Strategies in Digital Interventions for Mental Health Promotion: Scoping Review

BACKGROUND

Digital interventions offer a solution to address the high demand for mental health promotion, especially when facing physical contact restrictions or lacking accessibility. Engagement with digital interventions is critical for their effectiveness; however, retaining users' engagement throughout the intervention is challenging. It remains unclear what strategies facilitate engagement with digital interventions that target mental health promotion.

OBJECTIVE

Our aim is to conduct a scoping review to investigate user engagement strategies and methods to evaluate engagement with digital interventions that target mental health promotion in adults.

METHODS

This scoping review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews. The search was conducted in 7 electronic databases from inception to April 2020. The inclusion criteria for studies were as follows: adult (aged ≥18 years) users of digital interventions for mental health promotion from the general population; any digital intervention for mental health promotion; and user engagement strategies described in the intervention design. We extracted the following data items: study characteristics, digital intervention (type and engagement strategy), evaluation of engagement strategy (method and result specifying whether the strategy was effective at facilitating engagement), and features of engagement (extent of use and subjective experience of users).

RESULTS

A total of 2766 studies were identified, of which 16 (0.58%) met the inclusion criteria. The 16 studies included randomized controlled trials (6/16, 37%), studies analyzing process data (5/16, 31%), observational studies (3/16, 19%), and qualitative studies (2/16, 13%). The digital interventions for mental health promotion were either web based (12/16, 75%) or mobile app based (4/16, 25%). The engagement strategies included personalized feedback about intervention content or users' mental health status; guidance regarding content and progress through e-coaching; social forums, and interactivity with peers; content gamification; reminders; and flexibility and ease of use. These engagement strategies were deemed effective based on qualitative user feedback or responses on questionnaires or tools (4/16, 25%), usability data (5/16, 31%), or both (7/16, 44%). Most studies identified personalized support in the form of e-coaching, peer support through a social platform, personalized feedback, or joint videoconference sessions as an engaging feature.

CONCLUSIONS

Personalized support during the intervention, access to social support, and personalized feedback seem to promote engagement with digital interventions for mental health promotion. These findings need to be interpreted with caution because the included studies were heterogeneous, had small sample sizes, and typically did not address engagement as the primary outcome. Despite the importance of user engagement for the effectiveness of digital interventions, this field has not yet received much attention. Further research is needed on the effectiveness of different strategies required to facilitate user engagement in digital interventions for mental health promotion.

A Review of the Quality and Impact of Mobile Health Apps

Mobile health applications (apps) have transformed the possibilities for health promotion and disease self-management; however, their promise is not fully realized owing to their reliance on commercial ecosystems for development and distribution. This review provides an overview of the types of mobile health apps and describes key stakeholders in terms of how apps are used, developed, and regulated. I outline key challenges facing consumers, public health professionals, and policy makers in evaluating the quality of health apps and summarize what is known about the impact of apps on health outcomes and health equity. I suggest that factors within the wider mobile ecosystem largely define the impact of health apps and, most notably, practices around the collection and commercialization of user data. Finally, I suggest that upstream public health strategies, grounded in an understanding of corporate influences on health, are necessary to promote healthy digital environments in which mobile health app innovation can flourish. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Older Women's Experiences of a Community-Led Walking Programme Using Activity Trackers

Promoting physical activity amongst older adults represents a major public health goal and community-led exercise programmes present benefits in promoting active lifestyles. Commercial activity trackers potentially encourage positive behaviour change with respect to physical exercise. This qualitative study investigated the experiences and attitudes of older adults following a 6-week community-led walking programme utilising activity trackers. Eleven community-dwelling older women aged 60+ completed individual phone interviews following their involvement in the programme. The programme, codesigned with a group of senior citizens, equipped participants with wrist-worn activity trackers and included biweekly check-in sessions with a researcher to monitor progress and support motivation. Interviews explored participants’ experiences of the programme and of using activity trackers for the purpose of becoming more active. A thematic analysis produced three main themes: ‘programme as a source of motivation’, ‘user experiences with the technology’ and ‘views on social dimension of the programme’. Overall, participants highlighted the self-monitoring function of activity trackers as most beneficial for their exercise levels. This study provides insights into the personal and social factors perceived by older adults in relation to being part of a community-led programme using activity trackers. It highlights the role of the programme and trackers in maintaining motivation to stay active.

Experiences with and Perception of a Web-Based Mindfulness, Nutrition, and Fitness Platform Reported by First-Year University Students: A Qualitative Study

BACKGROUND

My Viva Plan (MVP) (https://www.myvivainc.com/) is a web-based application developed by a dietitian that aims to support healthy living by providing resources and self-monitoring tools to help promote a healthy diet, healthy mind, and physical fitness. First-year university students have the potential to benefit because poor dietary choices, limited physical activity, and high stress are prevalent in this population. In addition, they are also active technology users.

OBJECTIVE

This study aims to understand experiences and perception of MVP by first-year university students using this tool as part of a 12-week randomized controlled trial.

DESIGN

One-on-one semistructured interviews were conducted following a 12-week intervention involving use of MVP.

PARTICIPANTS/SETTING

First-year university students from the University of Alberta, Edmonton, Canada (n = 32).

INTERVENTION

Participants were instructed to use MVP as much as possible for 12 weeks in either the fall/2018 or winter/2019 semesters.

QUALITATIVE DATA ANALYSIS

Interviews were audio-recorded, transcribed verbatim, and analyzed abductively using content analysis.

RESULTS

Participants reported varied use of MVP across the 12-week period. Data were categorized using the HealthChange Methodology (Behaviors, Emotions, 37 Situations, Thinking) framework. Participants provided various examples of emotions (eg, motivation, stress), situations (eg, time, living arrangements, finances), and thinking (eg, self-awareness, level of satisfaction with MVP, and how MVP was or could be better tailored for students) that acted as either facilitators or barriers to MVP use and explained their behaviors associated with this tool.

CONCLUSIONS

Overall, participant behaviors regarding MVP varied and were influenced by several factors, including their emotions, situations, and thinking. The Behaviors, Emotions, Situations, Thinking framework may be helpful for dietitians to identify barriers and facilitators affecting their client's use of ehealth tools for lifestyle behavior change. This information can be used to optimize client support when using these tools.

Insights into mobile health application market via a content analysis of marketplace data with machine learning

BACKGROUND

Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come.

OBJECTIVE

This study aims to investigate the current landscape of smartphone apps that focus on improving and sustaining health and wellbeing. Understanding the categories that popular apps focus on and the relevant features provided to users, which lead to higher user scores and downloads will offer insights to enable higher adoption in the general populace. This study on 1,000 mobile health applications aims to shed light on the reasons why particular apps are liked and adopted while many are not.

METHODS

User-generated data (i.e. review scores) and company-generated data (i.e. app descriptions) were collected from app marketplaces and manually coded and categorized by two researchers. For analysis, Artificial Neural Networks, Random Forest and Naïve Bayes Artificial Intelligence algorithms were used.

RESULTS

The analysis led to features that attracted more download behavior and higher user scores. The findings suggest that apps that mention a privacy policy or provide videos in description lead to higher user scores, whereas free apps with in-app purchase possibilities, social networking and sharing features and feedback mechanisms lead to higher number of downloads. Moreover, differences in user scores and the total number of downloads are detected in distinct subcategories of mobile health apps.

CONCLUSION

This study contributes to the current knowledge of m-health application use by reviewing mobile health applications using content analysis and machine learning algorithms. The content analysis adds significant value by providing classification, keywords and factors that influence download behavior and user scores in a m-health context.

The Use of Small Electronic Devices and Health: Feasibility of Interventions for a Forthcoming Crossover Design

Background

Modern lifestyle is heavily affected by technology such as smartphones, tablets, and other small computers; yet it remains unclear how our health and well-being are affected by the heavy use of these devices.

Objective

This feasibility study aims to test two different interventions of an experimental protocol for a forthcoming large-scale community-based study and get estimates of parameters for sample size calculation. The aim of the large-scale study is to investigate the effect of (1) a wearable tracking device on aerobic capacity (VO₂max/kg) and the effect of (2) restricting media use on total sleep time.

Methods

Twenty healthy participants were included and equipped with a wrist-worn device tracking physical activity and sleep. Participants were allocated to either a physical activity group, which was instructed to use the wrist-worn device to support exercise, or a sleep silent group, which was instructed to remove or switch off all electronic devices in the bedroom (except the wrist-worn tracking device). The intervention lasted approximately 4 weeks. Data collected included blood pressure, submaximal cycle ergometer test, self-reported technology use, and compliance of using the wearable tracking device.

Results

All participants wore the wearable tracking device 95.8% (SD 4.4%) of the time. Participants in the physical activity group increased aerobic capacity from 30.38 (SD 8.98) to 32.1 (SD 8.71) mL/kg/min (t=–2.31, P=.046) and decreased their systolic blood pressure from 126.5 (SD 15.8) mm Hg to 121.8 (SD 11.7) mm Hg (t=2.72, P=.02). The sleep silent group prolonged their time offline before bedtime from 18.1 (SD 19.4) minutes to 27.2 (SD 17.3) minutes (t=–2.94, P=.02).

Conclusions

The two interventions are feasible to conduct. Participants were willing to wear the tracking device on their wrist and restrict all media use in their bedroom and thereby reduce bedtime technology use. Our results also suggest that tracking physical activity using a wearable device is accompanied by noteworthy health benefits. We outline necessary adjustments for a forthcoming large-scale study.

Promotion of Physical Activity in Older People Using mHealth and eHealth Technologies: Rapid Review of Reviews

BACKGROUND

Older people are at increased risk of adverse health events because of reduced physical activity. There is concern that activity levels are further reduced in the context of the COVID-19 pandemic, as many older people are practicing physical and social distancing to minimize transmission. Mobile health (mHealth) and eHealth technologies may offer a means by which older people can engage in physical activity while physically distancing.

OBJECTIVE

The objective of this study was to assess the evidence for mHealth or eHealth technology in the promotion of physical activity among older people aged 50 years or older.

METHODS

We conducted a rapid review of reviews using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched for systematic reviews published in the English language in 3 electronic databases: MEDLINE, CINAHL Plus, and Scopus. Two reviewers used predefined inclusion criteria to select relevant reviews and extracted data on review characteristics and intervention effectiveness. Two independent raters assessed review quality using the AMSTAR-2 tool.

RESULTS

Titles and abstracts (n=472) were screened, and 14 full-text reviews were assessed for eligibility. Initially, we included 5 reviews but excluded 1 from the narrative as it was judged to be of critically low quality. Three reviews concluded that mHealth or eHealth interventions were effective in increasing physical activity. One review found that the evidence was inconclusive.

CONCLUSIONS

There is low to moderate evidence that interventions delivered via mHealth or eHealth approaches may be effective in increasing physical activity in older adults in the short term. Components of successful interventions include self-monitoring, incorporation of theory and behavior change techniques, and social and professional support.

Can Smartphone-Derived Step Data Predict Laboratory-Induced Real-Life Like Fall-Risk in Community- Dwelling Older Adults?

Background: As age progresses, decline in physical function predisposes older adults to high fall-risk, especially on exposure to environmental perturbations such as slips and trips. However, there is limited evidence of association between daily community ambulation, an easily modifiable factor of physical activity (PA), and fall-risk. Smartphones, equipped with accelerometers, can quantify, and display daily ambulation-related PA simplistically in terms of number of steps. If any association between daily steps and fall-risks is established, smartphones due to its convenience and prevalence could provide health professionals with a meaningful outcome measure, in addition to existing clinical measurements, to identify older adults at high fall-risk. Objective: This study aimed to explore whether smartphone-derived step data during older adults' community ambulation alone or together with commonly used clinical fall-risk measurements could predict falls following laboratory-induced real-life like slips and trips. Relationship between step data and PA questionnaire and clinical fall-risk assessments were examined as well. Methods: Forty-nine community-dwelling older adults (age 60-90 years) completed Berg Balance Scale (BBS), Activities-specific Balance Confidence scale (ABC), Timed Up-and-Go (TUG), and Physical Activity Scale for the Elderly (PASE). One-week and 1-month smartphone steps data were retrieved. Participants' 1-year fall history was noted. All participants' fall outcomes to laboratory-induced slip-and-trip perturbations were recorded. Logistic regression was performed to identify a model that best predicts laboratory falls. Pearson correlations examined relationships between study variables. Results: A model including age, TUG, and fall history significantly predicted laboratory falls with a sensitivity of 94.3%, specificity of 58.3%, and an overall accuracy of 85.1%. Neither 1-week nor 1-month steps data could predict laboratory falls. One-month steps data significantly positively correlated with BBS (r = 0.386, p = 0.006) and ABC (r = 0.369, p = 0.012), and negatively correlated with fall history (r _p = -0.293, p = 0.041). Conclusion: Older participants with fall history and higher TUG scores were more likely to fall in the laboratory. No association between smartphone steps data and laboratory fall-risk was established in our study population of healthy community-dwelling older adults which calls for further studies on varied populations. Although modest, results do reveal a relationship between steps data and functional balance deficits and fear of falls.

Engagement Features in Physical Activity Smartphone Apps: Focus Group Study With Sedentary People

Background

Engagement with physical activity mobile apps has been reported to be a core precondition for their effectiveness in digital behavior change interventions. However, to date, little attention has been paid to understanding the perspectives, needs, expectations, and experiences of potential users with physical activity mobile apps.

Objective

The aim of this study was to investigate the features that are judged to be important for engagement with a physical activity mobile app and the reasons for their importance.

Methods

A qualitative focus-group methodology with elements of co-design was adopted in this study. Participants reporting sedentary lifestyles and willingness to improve their physical activity behavior through mobile technology were recruited. The focus group sessions consisted of 13 participants (8 men and 5 women, mean [SD] age 41.9 [7.1] years). Two researchers conducted the data analysis independently by using the inductive thematic approach.

Results

Four main themes emerged in relation to the research question and were named as follows: “physical activity participation motives,” “autonomy and self-regulation,” “need for relatedness,” and “smart.” Additionally, 2 subthemes originated from “physical activity participation motives” (ie, “medical guidance” and “weight loss and fitness for health”) and “smart” (ie, “action planning” and “adaptable and tailored”).

Conclusions

Features enhancing autonomy and self-regulation and positively affecting health and physical well-being as well as the need for relatedness, adaptability, and flexibility should be considered as core elements in the engagement of potential users with physical activity mobile apps. The emerged findings may orient future research and interventions aiming to foster engagement of potential users with physical activity apps.

Effects of a Collective Family-Based Mobile Health Intervention Called "SMARTFAMILY" on Promoting Physical Activity and Healthy Eating: Protocol for a Randomized Controlled Trial

BACKGROUND

Numerous smartphone apps are targeting physical activity and healthy eating, but empirical evidence on their effectiveness for initialization and maintenance of behavior change, especially in children and adolescents, is still limited.

OBJECTIVE

The aim of this study was to conceptualize a theory-based and evidence-based mHealth intervention called SMARTFAMILY (SF) that targets physical activity and healthy eating in a collective family-based setting. Subsequently, the app will be refined and re-evaluated to analyze additional effects of just-in-time adaptive interventions (JITAIs) and gamification features.

METHODS

A smartphone app based on behavior change theories and behavior change techniques was developed and implemented and will be evaluated with family members individually and cooperatively (SF trial). Existing evidence and gained results were used to refine and will be used to re-evaluate the app (SF2.0 trial). Both trials are cluster randomized controlled trials with 3 measurement occasions. The intervention group uses the app for 3 consecutive weeks, whereas the control group receives no treatment. Baseline measurements (T₀) and postintervention measurements (T₁) include physical activity (ie, self-reported and accelerometry) and healthy eating measurements (ie, self-reported fruit and vegetable intake) as the primary outcomes. The secondary outcomes (ie, self-reported) are intrinsic motivation, behavior-specific self-efficacy, and the family health climate, complemented by an intentional measure in SF2.0. Four weeks following T₁, a follow-up assessment (T₂) is completed by the participants, consisting of all questionnaire items to assess the stability of the intervention effects. Mixed-method analysis of covariance will be used to calculate the primary intervention effects (ie, physical activity, fruit and vegetable intake) while controlling for covariates, including family health climate, behavior-specific self-efficacy, and intrinsic motivation.

RESULTS

This study is funded by the German Federal Ministry of Education and Research and ethically approved by the Karlsruhe Institute of Technology. For both trials, it is hypothesized that the apps will positively influence physical activity and healthy eating in the whole family. Furthermore, SF2.0 is expected to produce stronger effects (ie, higher effect sizes) compared to SF. SF app development and piloting are completed. Data acquisition for the SF trial is terminated and discontinued due to the COVID-19 pandemic. SF2.0 app development and piloting are completed, while data acquisition is ongoing. Participant recruitment for the SF 2.0 trial started in February 2020. The results for SF are expected to be published in mid-2021, and the results of SF2.0 are expected to be published in mid-2022.

CONCLUSIONS

In this study, it is hypothesized that targeting the whole family will facilitate behavior change at the individual level and the family level, as the implemented strategies address changes in daily family life. Furthermore, subsequent app development (SF2.0) with supplementary addition of motivation-enhancing features and a JITAI approach is expected to enhance positive intervention effects.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00010415; https://tinyurl.com/yyo87yyu.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/20534.

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial

Background

Though maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical activity tracker, a Bluetooth-enabled scale, and an app-based dashboard. We tested whether adding personalized coaching components (Stay Strong+Coaching) would improve physical activity compared to Stay Strong alone.

Objective

The goal of this study is to compare 12-month outcomes from Stay Strong alone versus Stay Strong+Coaching.

Methods

Participants (n=357) were recruited from a national random sample of US veterans of recent wars and randomly assigned to the Stay Strong app alone (n=179) or Stay Strong+Coaching (n=178); both programs lasted 12 months. Personalized coaching components for Stay Strong+Coaching comprised of automated in-app motivational messages (3 per week), telephone-based human health coaching (up to 3 calls), and personalized weekly goal setting. All aspects of the enrollment process and program delivery were accomplished virtually for both groups, except for the telephone-based coaching. The primary outcome was change in physical activity at 12 months postbaseline, measured by average weekly Active Minutes, captured by the Fitbit Charge 2 device. Secondary outcomes included changes in step counts, weight, and patient activation.

Results

The average age of participants was 39.8 (SD 8.7) years, and 25.2% (90/357) were female. Active Minutes decreased from baseline to 12 months for both groups (P<.001) with no between-group differences at 6 months (P=.82) or 12 months (P=.98). However, at 12 months, many participants in both groups did not record Active Minutes, leading to missing data in 67.0% (120/179) for Stay Strong and 61.8% (110/178) for Stay Strong+Coaching. Average baseline weight for participants in Stay Strong and Stay Strong+Coaching was 214 lbs and 198 lbs, respectively, with no difference at baseline (P=.54) or at 6 months (P=.28) or 12 months (P=.18) postbaseline based on administrative weights, which had lower rates of missing data. Changes in the number of steps recorded and patient activation also did not differ by arm.

Conclusions

Adding personalized health coaching comprised of in-app automated messages, up to 3 coaching calls, plus automated weekly personalized goals, did not improve levels of physical activity compared to using a smartphone app alone. Physical activity in both groups decreased over time. Sustaining long-term adherence and engagement in this mHealth intervention proved difficult; approximately two-thirds of the trial’s 357 participants failed to sync their Fitbit device at 12 months and, thus, were lost to follow-up.

Trial Registration

ClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293

International Registered Report Identifier (IRRID)

RR2-10.2196/12526

A Persuasive mHealth Behavioral Change Intervention for Promoting Physical Activity in the Workplace: Feasibility Randomized Controlled Trial

Background

Employees in an office setting are more likely to remain physically inactive. Physical inactivity has become one of the major barriers to overcoming the risk factors for anxiety, depression, coronary heart disease, certain cancers, and type 2 diabetes. Currently, there is a gap in mobile health (mHealth) apps to promote physical activity (PA) for workers in the workplace. Studies on behavior change theories have concluded that health apps generally lack the use of theoretical constructs.

Objective

The objective of this study was to study the feasibility of a persuasive app aimed at encouraging PA among employees and to understand the motivational aspects behind the implementation of mHealth apps among office workers.

Methods

A 4-week study using a mixed methods (quantitative and qualitative) design was conducted with office-based employees in cities in 4 countries: Oulu, Finland; Carlow, Ireland; London, United Kingdom; and Dhaka, Bangladesh. Of the 220 invited participants (experimental group, n=115; control group, n=105), 84 participated (experimental group, n=56; control group, n=28), consisting of working-age volunteers working in an office setting. Participants used 2 different interventions: The experimental group used an mHealth app for PA motivation, and the control group used a paper diary. The purpose was to motivate employees to engage in healthier behavior regarding the promotion of PA in the workplace. A user-centered design process was followed to design, develop, and evaluate the mHealth app, incorporating self-determination theory (SDT) and using game elements. The paper diary had no specific theory-driven approach, design technique, nor game elements.

Results

Compliance with app usage remained relatively low, with 27 participants (experimental group, n=20; control group, n=7) completing the study. The results support the original hypothesis that the mHealth app would help increase PA (ie, promoting daily walking in the workplace) in comparison to a paper diary (P=.033). The mHealth app supported 2 of the basic SDT psychological needs, namely autonomy (P=.004) and competence (P=.014), but not the needs of relatedness (P=.535).

Conclusions

The SDT-based mHealth application motivated employees to increase their PA in the workplace. However, compliance with app usage remained low. Future research should further develop the app based on user feedback and test it in a larger sample.

mHealth Research Applied to Regulated and Unregulated Behavioral Health Sciences

Behavioral scientists are developing new methods and frameworks that leverage mobile health technologies to optimize individual level behavior change. Pervasive sensors and mobile apps allow researchers to passively observe human behaviors "in the wild" 24/7 which supports delivery of personalized interventions in the real-world environment. This is all possible because these technologies contain an incredible array of sensors that allow applications to constantly record user location and can contextualize current environmental conditions through barometers, thermometers, and ambient light sensors and can also capture audio and video of the user and their surroundings through multiple integrated high-definition cameras and microphones. These tools are a game changer in behavioral health research and, not surprisingly, introduce new ethical, regulatory/legal and social implications described in this article.

Right care, first time: a highly personalised and measurement-based care model to manage youth mental health

Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change. Consequently, the effects of adolescent-onset mood and psychotic syndromes can have long term consequences. A key clinical challenge for youth mental health is to develop and test new systems that align with current evidence for comorbid presentations and underlying neurobiology, and are useful for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. Our highly personalised and measurement-based care model includes three core concepts: ▶ A multidimensional assessment and outcomes framework that includes: social and occupational function; self-harm, suicidal thoughts and behaviour; alcohol or other substance misuse; physical health; and illness trajectory. ▶ Clinical stage. ▶ Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on proposed pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). The model explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within this highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care as well as utilisation of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality, mental health care for young people. CHAPTER 1: MULTIDIMENSIONAL OUTCOMES IN YOUTH MENTAL HEALTH CARE: WHAT MATTERS AND WHY?: Mood and psychotic syndromes present one of the most serious public health challenges that we face in the 21st century. Factors including prevalence, age of onset, and chronicity contribute to substantial burden and secondary risks such as alcohol or other substance misuse. Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change; thus, effects can have long term consequences. We propose five key domains which make up a multidimensional outcomes framework that aims to address the specific needs of young people presenting to health services with emerging mental illness. These include social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Impairment and concurrent morbidity are well established in young people by the time they present for mental health care. Despite this, services and health professionals tend to focus on only one aspect of the presentation - illness type, stage and trajectory - and are often at odds with the preferences of young people and their families. There is a need to address the disconnect between mental health, physical health and social services and interventions, to ensure that youth mental health care focuses on the outcomes that matter to young people. CHAPTER 2: COMBINING CLINICAL STAGE AND PATHOPHYSIOLOGICAL MECHANISMS TO UNDERSTAND ILLNESS TRAJECTORIES IN YOUNG PEOPLE WITH EMERGING MOOD AND PSYCHOTIC SYNDROMES: Traditional diagnostic classification systems for mental disorders map poorly onto the early stages of illness experienced by young people, and purport categorical distinctions that are not readily supported by research into genetic, environmental and neurobiological risk factors. Consequently, a key clinical challenge in youth mental health is to develop and test new classification systems that align with current evidence on comorbid presentations, are consistent with current understanding of underlying neurobiology, and provide utility for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. This chapter outlines a transdiagnostic framework for classifying common adolescent-onset mood and psychotic syndromes, combining two independent but complementary dimensions: clinical staging, and three proposed pathophysiological mechanisms. Clinical staging reflects the progression of mental disorders and is in line with the concept used in general medicine, where more advanced stages are associated with a poorer prognosis and a need for more intensive interventions with a higher risk-to-benefit ratio. The three proposed pathophysiological mechanisms are neurodevelopmental abnormalities, hyperarousal and circadian dysfunction, which, over time, have illness trajectories (or pathways) to psychosis, anxious depression and bipolar spectrum disorders, respectively. The transdiagnostic framework has been evaluated in young people presenting to youth mental health clinics of the University of Sydney's Brain and Mind Centre, alongside a range of clinical and objective measures. Our research to date provides support for this framework, and we are now exploring its application to the development of more personalised models of care. CHAPTER 3: A COMPREHENSIVE ASSESSMENT FRAMEWORK FOR YOUTH MENTAL HEALTH: GUIDING HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE USING MULTIDIMENSIONAL AND OBJECTIVE MEASURES: There is an urgent need for improved care for young people with mental health problems, in particular those with subthreshold mental disorders that are not sufficiently severe to meet traditional diagnostic criteria. New comprehensive assessment frameworks are needed to capture the biopsychosocial profile of a young person to drive highly personalised and measurement-based mental health care. We present a range of multidimensional measures involving five key domains: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Objective measures include: neuropsychological function; sleep-wake behaviours and circadian rhythms; metabolic and immune markers; and brain structure and function. The recommended multidimensional measures facilitate the development of a comprehensive clinical picture. The objective measures help to further develop informative and novel insights into underlying pathophysiological mechanisms and illness trajectories to guide personalised care plans. A panel of specific multidimensional and objective measures are recommended as standard clinical practice, while others are recommended secondarily to provide deeper insights with the aim of revealing alternative clinical paths for targeted interventions and treatments matched to the clinical stage and proposed pathophysiological mechanisms of the young person. CHAPTER 4: PERSONALISING CARE OPTIONS IN YOUTH MENTAL HEALTH: USING MULTIDIMENSIONAL ASSESSMENT, CLINICAL STAGE, PATHOPHYSIOLOGICAL MECHANISMS, AND INDIVIDUAL ILLNESS TRAJECTORIES TO GUIDE TREATMENT SELECTION: New models of mental health care for young people require that interventions be matched to illness type, clinical stage, underlying pathophysiological mechanisms and individual illness trajectories. Narrow syndrome-focused classifications often direct clinical attention away from other key factors such as functional impairment, self-harm and suicidality, alcohol or other substance misuse, and poor physical health. By contrast, we outline a treatment selection guide for early intervention for adolescent-onset mood and psychotic syndromes (ie, active treatments and indicated and more specific secondary prevention strategies). This guide is based on experiences with the Brain and Mind Centre's highly personalised and measurement-based care model to manage youth mental health. The model incorporates three complementary core concepts: ▶A multidimensional assessment and outcomes framework including: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness trajectory. ▶Clinical stage. ▶Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on three underlying pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). These core concepts are not mutually exclusive and together may facilitate improved outcomes through a clinical stage-appropriate and transdiagnostic framework that helps guide decisions regarding the provision of appropriate and effective care options. Given its emphasis on adolescent-onset mood and psychotic syndromes, the Brain and Mind Centre's model of care also respects a fundamental developmental perspective - categorising childhood problems (eg, anxiety and neurodevelopmental difficulties) as risk factors and respecting the fact that young people are in a period of major biological and social transition. Based on these factors, a range of social, psychological and pharmacological interventions are recommended, with an emphasis on balancing the personal benefit-to-cost ratio. CHAPTER 5: A SERVICE DELIVERY MODEL TO SUPPORT HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE IN YOUTH MENTAL HEALTH: Over the past decade, we have seen a growing focus on creating mental health service delivery models that better meet the unique needs of young Australians. Recent policy directives from the Australian Government recommend the adoption of stepped-care services to improve the appropriateness of care, determined by severity of need. Here, we propose that a highly personalised approach enhances stepped-care models by incorporating clinical staging and a young person's current and multidimensional needs. It explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within a highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care and use of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality of, mental health care for young people.

Smartphone-Based Health Program for Improving Physical Activity and Tackling Obesity for Young Adults: A Systematic Review and Meta-Analysis

The need for physical activity for health promotion is recognized, yet young adults still perform insufficient physical activity. Smartphone health programs can be applied easily without time and space constraints, and various mobile health programs based on smartphone applications have recently been developed and applied. This study aimed to measure the effects of mobile smartphone-based health programs on physical activity and obesity outcomes in young adults through a systematic review and meta-analysis. We searched publications in English through electronic databases up to May 2019. Studies were included that provided interventions to improve physical activity using smartphone applications for young adults. After assessing study quality, data were extracted and synthesized concerning whether smartphone interventions affect health outcomes including physical activity and weight using Meta-Analysis software. Four randomized controlled studies and a quasi-experimental study were analyzed. They provided information related to health management, diet, physical activity, and personalized feedback using smartphone applications. The meta-analysis showed that smartphone-based health interventions significantly affect weight loss and increase physical activity. This study provides modest evidence for using smartphone health programs to improve young adults' physical activity, weight control, and body mass index (BMI). Future research is needed to understand long-term effects and the reliability of increasing physical activity through smartphone health programs.

Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review

BACKGROUND

Maintaining weight after weight loss is a major health challenge, and eHealth (electronic health) solutions may be a way to meet this challenge. Application of behavior change techniques (BCTs) and persuasive system design (PSD) principles in eHealth development may contribute to the design of technologies that positively influence behavior and motivation to support the sustainable health behavior change needed.

OBJECTIVE

This review aimed to identify BCTs and PSD principles applied in eHealth interventions to support weight loss and weight loss maintenance, as well as techniques and principles applied to stimulate motivation and adherence for long-term weight loss maintenance.

METHODS

A systematic literature search was conducted in PsycINFO, Ovid MEDLINE (including PubMed), EMBASE, Scopus, Web of Science, and AMED, from January 1, 2007 to June 30, 2018. Arksey and O'Malley's scoping review methodology was applied. Publications on eHealth interventions were included if focusing on weight loss or weight loss maintenance, in combination with motivation or adherence and behavior change.

RESULTS

The search identified 317 publications, of which 45 met the inclusion criteria. Of the 45 publications, 11 (24%) focused on weight loss maintenance, and 34 (76%) focused on weight loss. Mobile phones were the most frequently used technology (28/45, 62%). Frequently used wearables were activity trackers (14/45, 31%), as well as other monitoring technologies such as wireless or digital scales (8/45, 18%). All included publications were anchored in behavior change theories. Feedback and monitoring and goals and planning were core behavior change technique clusters applied in the majority of included publications. Social support and associations through prompts and cues to support and maintain new habits were more frequently used in weight loss maintenance than weight loss interventions. In both types of interventions, frequently applied persuasive principles were self-monitoring, goal setting, and feedback. Tailoring, reminders, personalization, and rewards were additional principles frequently applied in weight loss maintenance interventions. Results did not reveal an ideal combination of techniques or principles to stimulate motivation, adherence, and weight loss maintenance. However, the most frequently mentioned individual techniques and principles applied to stimulate motivation were, personalization, simulation, praise, and feedback, whereas associations were frequently mentioned to stimulate adherence. eHealth interventions that found significant effects for weight loss maintenance all applied self-monitoring, feedback, goal setting, and shaping knowledge, combined with a human social support component to support healthy behaviors.

CONCLUSIONS

To our knowledge, this is the first review examining key BCTs and PSD principles applied in weight loss maintenance interventions compared with those of weight loss interventions. This review identified several techniques and principles applied to stimulate motivation and adherence. Future research should aim to examine which eHealth design combinations can be the most effective in support of long-term behavior change and weight loss maintenance.

Exploring the perspectives of stroke survivors and healthcare professionals on the use of mobile health to promote physical activity: A qualitative study protocol

Background: Physical inactivity is both the second-highest population attributable risk factor for and a common consequence of stroke. Despite well-documented health benefits associated with physical activity, its levels typically remain below recommended guidelines in stroke survivors. Consequently, calls have been made for novel interventions targeting the promotion of physical activity in stroke survivors. Mobile health is an emerging field which can offer personalised health interventions through mobile and wireless technology. However, a paucity of research has focused on mobile health to promote physical activity in stroke survivors and, more broadly, this field has been criticised for not incorporating the views of stakeholders. This study aims to explore the perspectives of stroke survivors and healthcare professionals on the development of a mobile health intervention for the promotion of physical activity. Methods: The current study will employ a qualitative descriptive approach using separate, semi-structured focus groups for two key stakeholder groups. Community-dwelling stroke survivors will be recruited through an early supported discharge service for acute stroke and stroke support groups. Healthcare professionals will be recruited through the same early supported discharge service, relevant professional bodies and Twitter. The final number of focus groups will depend on data saturation. Thematic analysis will be conducted using NVivo 12 and findings will be reported in accordance with the Consolidated Criteria for Reporting Qualitative Studies. Conclusion: This study was granted ethical approval from the HSE Mid-Western Regional Hospital Research Ethics Committee and the Faculty of Education and Health Sciences Research Ethics Committee at the University of Limerick. Output will consist of recommendations for the development of a mobile health intervention aimed at the promotion of physical activity in stroke survivors. Findings will be disseminated locally through presentations at stroke support groups, as well as internationally through academic conferences and peer-reviewed journals.