Promoting Behavioral Change in Mobile Health Interventions for Older Adults: A Scoping Review

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

Exploring the effectiveness of a fitness-app prototype for home care service users in Austria and Italy

An infinite number of fitness apps are available on various app stores. However, hardly any of them are fitted to the needs and requirements of care-dependent people. This paper investigates the effectiveness of a customised fitness-app prototype for increasing physical activity in home care service users. Home care service users from Austria and Italy were randomly assigned to two groups. In total, 216 participants were involved in the field trial, 104 received a tablet with the fitness app and an activity tracker (treatment group), 112 did not (control group). Regularity of physical activity, frequency of fitness exercises and walking behaviour were self-reported by participants at baseline, after 4 months and after 8 months. In addition, the frequency of using the prototype was assessed based on the fitness app's logged usage data. We estimated multilevel mixed-effects ordered logistic models to examine the effects of the intervention. After 4 months, the intervention increased the home care users' probability of agreeing strongly with being physically active on a regular basis by 28 percentage points (p < 0.001; 95% CI: 0.20, 0.36) and their probability of reporting to exercise more than once a week by 45 percentage points (p < 0.001; 95% CI: 0.32, 0.57). Walking behaviour was not affected on group-level but improved for frequent users of the activity tracker. Frequent and regular users of the fitness app benefited most and effects persisted until the end of the 8 months controlled trial. Tailoring a fitness-app prototype to the needs of care-dependent people has the potential to support people with functional limitations to engage in a more active lifestyle. Future research is encouraged to seek further insights into how new technologies can support physical activities in people with long-term care needs.

Digital Technologies for Health Promotion and Disease Prevention in Older People: Protocol for a Scoping Review

BACKGROUND

Digital technologies could contribute to health promotion and disease prevention. It is unclear if and how such digital technologies address the health needs of older people in nonclinical settings (ie, daily life).

OBJECTIVE

This study aims to identify digital technologies for health promotion and disease prevention that target the needs of older people in nonclinical settings by performing a scoping review of the published literature. The scoping review is guided by the framework of Arksey and O'Malley.

METHODS

Our scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The information sources are bibliographic databases (MEDLINE, PsycINFO, CINAHL, and SCOPUS) and bibliographies of any included systematic reviews. Manual searches for additional studies will be performed in Google Scholar and most relevant journals. The electronic search strategy was developed in collaboration with a librarian who performed the search for studies on digital technologies for health promotion and disease prevention targeting the needs of older people. Study selection and data coding will be performed independently by 2 authors. Consensus will be reached by discussion. Eligibility is based on the PCC (Population, Concept, and Context) criteria as follows: (1) older people (population); (2) any digital (health) technology, such as websites, smartphone apps, or wearables (concept); and (3) health promotion and disease prevention in nonclinical (daily life, home, or community) settings (context). Primary studies with any design or reviews with a systematic methodology published in peer-reviewed academic journals will be included. Data items will address study designs, PCC criteria, benefits or barriers related to digital technology use by older people, and evidence gaps. Data will be synthesized using descriptive statistics or narratively described by identifying common themes. Quality appraisal will be performed for any included systematic reviews, using a validated instrument for this study type (A Measurement Tool to Assess Systematic Reviews, version 2 [AMSTAR2]).

RESULTS

Following preliminary literature searches to test and calibrate the search syntax, the electronic literature search was performed in March 2022 and manual searches were completed in June 2022. Study selection based on titles and abstracts was completed in July 2022, and the full-text screen was initiated in July 2022.

CONCLUSIONS

Our scoping review will identify the types of digital technologies, health targets in the context of health promotion and disease prevention, and health benefits or barriers associated with the use of such technologies for older people in nonclinical settings. This knowledge could guide further research on how digital technologies can support healthy aging.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/37729.

Factors influencing participants' engagement with an interactive text-message intervention to improve sun protection behaviors: "SunText" randomized controlled trial

There is growing evidence suggesting that text-message-based interventions are effective to promote sun protection behaviors. However, it is still unclear how engagement and adherence with the intervention messages can be optimized through intervention design. This study evaluated the effect of different combinations of personalized and two-way interactive messages on participant engagement with a theory-based skin cancer prevention intervention. In the SunText study conducted in February-July 2019 in Queensland, Australia participants 18-40 years were randomized to four different text message schedules using a Latin square design. This study analyzed if the order and intensity in which the schedules were received were associated with participants' level of engagement, and if this differed by demographic factors. Out of the 389 participants enrolled in the study, 375 completed the intervention period and remained for analysis. The overall intervention engagement rate was 71% and decreased from the beginning to the end of the study (82.2%-61.4%). The group starting with personalized, but not interactive messaging showed the lowest engagement rate. The intervention involving interactive messages three times a week for 4 weeks achieved the highest engagement rate. The intervention with increasing frequency (personalized and interactive three times a week for 2 weeks; then daily for 2 weeks) had lower engagement than intervention with constant or decreasing frequency. Engagement with two-way interactive messages was high across all intervention groups. Results suggest enhanced engagement with constant or decreasing message frequency compared to increasing frequency.

Behavior change factors and retention in dietary interventions for older adults: scoping review

BACKGROUND AND OBJECTIVES

Although poor diet is a major driver of morbidity and mortality in people 60 and older, few dietary interventions are widely implemented for this population. We mapped behavior change theories, agents, and techniques in dietary interventions for adults 60+ and explored relationships between these factors and ability to retain at least 80% of the study participants.

RESEARCH DESIGN AND METHODS

We conducted a scoping review using MEDLINE, CINAHL, and Web of Science through April 2021 for dietary interventions in adults 60 and older. We collated, summarized, and calculated frequency distributions of behavior change theories, behavior change agents, and behavior change techniques (BCTs) using BCTv1 taxonomy with regard to participant retention across 43 studies.

RESULTS

Only 49% and 30% of the studies reported behavior theory and change agents respectively. Of the studies reporting on theory and agents, the most common were social cognitive theory and the related mechanism of self-efficacy. The most common BCTv1 were "shaping knowledge" and "goals and planning." Several BCTv1 such as "antecedents" and "reward and threat" and evidence for concordance between BCTs and change agents were more common in interventions with higher retention rates.

DISCUSSION AND IMPLICATIONS

Mechanistically concordant studies with BCTs that involve resource allocation and positive reinforcement through rewards may be advantageous for retention in dietary intervention for older adults. Future studies should continue developing theory and mechanism-oriented research. Furthermore, future studies should consider diversifying the portfolio of currently deployed BCTs and strengthening a concordance between BCTs and mechanisms of change.