Systematic review of adherence to technology-based falls prevention programs for community-dwelling older adults: Reimagining future interventions

• Published in: PLOS digital health Vol. 3; no. 9; p. e0000579
• Main Authors: Ashe, Maureen C, Dos Santos, Isis Kelly, Erome, Jefferson, Grant, Jared, Mollins, Juliana, Soh, Sze-Ee
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.09.2024; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Medicine and Health Sciences; People and Places; Research and Analysis Methods
• ISSN: 2767-3170; 2767-3170
• DOI: 10.1371/journal.pdig.0000579

Prevention programs, and specifically exercise, can reduce falls among community-dwelling older adults, but low adherence limits the benefits of effective interventions. Technology may overcome some barriers to improve uptake and engagement in prevention programs, although less is known on adherence for providing them via this delivery mode. We aimed to synthesize evidence for adherence to technology-based falls prevention programs in community-dwelling older adults 60 years and older. We conducted a systematic review following standard guidelines to identify randomized controlled trials for remote delivered (i.e., no or limited in-person sessions) technology-based falls prevention programs for community-dwelling older adults. We searched nine sources using Medical Subject Headings (MeSH) terms and keywords (2007-present). The initial search was conducted in June 2023 and updated in December 2023. We also conducted a forward and backward citation search of included studies. Two reviewers independently conducted screening and study assessment; one author extracted data and a second author confirmed findings. We conducted a random effects meta-analysis for adherence, operationalized as participants' completion of program components, and aimed to conduct meta-regressions to examine factors related to program adherence and the association between adherence and functional mobility. We included 11 studies with 569 intervention participants (average mean age 74.5 years). Studies used a variety of technology, such as apps, exergames, or virtual synchronous classes. Risk of bias was low for eight studies. Five interventions automatically collected data for monitoring and completion of exercise sessions, two studies collected participants' online attendance, and four studies used self-reported diaries or attendance sheets. Studies included some behavior change techniques or strategies alongside the technology. There was substantial variability in the way adherence data were reported. The mean (range) percent of participants who did not complete planned sessions (i.e., dropped out or lost to follow-up) was 14% (0-32%). The pooled estimate of the proportion of participants who were adherent to a technology-based falls prevention program was 0.82 (95% CI 0.68, 0.93) for studies that reported the mean number of completed exercise sessions. Many studies needed to provide access to the internet, training, and/or resources (e.g., tablets) to support participants to take part in the intervention. We were unable to conduct the meta-regression for adherence and functional mobility due to an insufficient number of studies. There were no serious adverse events for studies reporting this information (n = 8). The use of technology may confer some benefits for program delivery and data collection. But better reporting of adherence data is needed, as well as routine integration and measurement of training and skill development to use technology, and behavior change strategies within interventions. There may be an opportunity to rethink or reimagine how technology can be used to support people's adoption and integration of physical activity into daily life routines.