Designing a mobile application to promote physical activity in spousal care partners of persons living with dementia and their care-recipient

Background: Care partners of persons living with dementia and their care-recipient have low levels of physical activity. Mobile applications have demonstrated effectiveness in promoting physical activity among older adults. The purpose of this study was to explore the perceptions of spousal care partners of persons with dementia and their care-recipient on the design and content of a mobile application intended to promote physical activity.Methods: Semi-structured interviews were conducted with 14 care partners and their care-recipient. After the interviews were transcribed verbatim, thematic analysis was performed.Results: Four themes emerged from the participants' responses related to the design and content of a mobile application to promote physical activity: 1) exercise preferences and habits, 2) barriers to exercise, 3) motivations for exercise, and 4) mobile application preferences and supportive features.Conclusion: Findings lay the foundation for designing an effective user-friendly mobile application to promote physical activity that caters to the diverse needs, preferences, and challenges among spousal care partners of persons with dementia and their care-recipient.

A systematic umbrella review and meta-meta-analysis of eHealth and mHealth interventions for improving lifestyle behaviours

The aim of this meta-meta-analysis was to systematically review randomised controlled trial (RCT) evidence examining the effectiveness of e- and m-Health interventions designed to improve physical activity, sedentary behaviour, healthy eating and sleep. Nine electronic databases were searched for eligible studies published from inception to 1 June 2023. Systematic reviews with meta-analyses of RCTs that evaluate e- and m-Health interventions designed to improve physical activity, sedentary behaviour, sleep and healthy eating in any adult population were included. Forty-seven meta-analyses were included, comprising of 507 RCTs and 206,873 participants. Interventions involved mobile apps, web-based and SMS interventions, with 14 focused on physical activity, 3 for diet, 4 for sleep and 26 evaluating multiple behaviours. Meta-meta-analyses showed that e- and m-Health interventions resulted in improvements in steps/day (mean difference, MD = 1329 [95% CI = 593.9, 2065.7] steps/day), moderate-to-vigorous physical activity (MD = 55.1 [95% CI = 13.8, 96.4] min/week), total physical activity (MD = 44.8 [95% CI = 21.6, 67.9] min/week), sedentary behaviour (MD = -426.3 [95% CI = -850.2, -2.3] min/week), fruit and vegetable consumption (MD = 0.57 [95% CI = 0.11, 1.02] servings/day), energy intake (MD = -102.9 kcals/day), saturated fat consumption (MD = -5.5 grams/day), and bodyweight (MD = -1.89 [95% CI = -2.42, -1.36] kg). Analyses based on standardised mean differences (SMD) showed improvements in sleep quality (SMD = 0.56, 95% CI = 0.40, 0.72) and insomnia severity (SMD = -0.90, 95% CI = -1.14, -0.65). Most subgroup analyses were not significant, suggesting that a variety of e- and m-Health interventions are effective across diverse age and health populations. These interventions offer scalable and accessible approaches to help individuals adopt and sustain healthier behaviours, with implications for broader public health and healthcare challenges.

Feasibility and Preliminary Efficacy of Virtual Rehabilitation for Middle and Older Aged Veterans With Mobility Limitations: A Pilot Study

Objective

To evaluate the feasibility and preliminary efficacy of the transition of an outpatient center-based rehabilitation program for middle and older aged Veterans with mobility limitations to a tele-health platform.

Design

Non-randomized non-controlled pilot study including 10 treatment sessions over 8 weeks and assessments at baseline, 8, 16, and 24 weeks.

Setting

VA Boston Healthcare System ambulatory care between August 2020 and March 2021.

Participants

Veterans aged 50 years and older (n=178) were contacted via letter to participate, and 21 enrolled in the study.

Intervention

Participants had virtual intervention sessions with a physical therapist who addressed impairments linked to mobility decline and a coaching program promoting exercise adherence.

Main Outcome Measures

Ambulatory Measure for Post-Acute Care (AM-PAC), Phone-FITT, and Self-Efficacy for Exercise (SEE) scale.

Results

Completers (n=14, mean age 74.9 years, 86% men) averaged 9.8 out of 10 visits. Changes in the Ambulatory Measure for Post-Acute Care (AM-PAC) exceeded clinically meaningful change after 8 and 24 weeks of treatment, at 4.1 units and 4.3 units respectively. Statistically significant improvements from baseline in AM-PAC and Phone-FITT were observed after 8 weeks of treatment and at 24 weeks. No significant changes were observed in exercise self-efficacy.

Conclusions

In this group of veterans, telerehab was feasible and demonstrated preliminary efficacy in both mobility and physical activity, thus justifying further investigation in a larger scale clinical trial.

Social Support, eHealth Literacy, and mHealth Use in Older Adults With Diabetes: Moderated Mediating Effect of the Perceived Importance of App Design

Mobile healthcare has emerged as a prominent technological solution for self-management of health. However, the development and utilization of tailored mobile healthcare applications for older adults with diabetes mellitus remain limited. This study examined the relationship between social support and mobile healthcare use and further explored how this relationship varies with eHealth literacy and application design among older adults with diabetes mellitus. A descriptive cross-sectional trial was conducted with a structured self-report questionnaire, surveying 252 South Korean older adults with diabetes mellitus via offline and online modes. The mediating effect and moderated mediating effect were analyzed with the PROCESS macro of SPSS. eHealth literacy mediated the relationship between social support and mobile healthcare use. High levels of eHealth literacy and social support may increase mobile healthcare use among older adults with diabetes. Application design aesthetics facilitated mobile healthcare use. Future researchers, healthcare providers, and developers can contribute to the development of tailored mobile healthcare applications for older adults with diabetes mellitus by considering application design aspects such as font size, color, and menu configuration.

Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

E-Health Interventions for Older Adults With Frailty: A Systematic Review

OBJECTIVE

: To systematically review the efficacy of e-Health interventions on physical performance, activity and quality of life in older adults with sarcopenia or frailty.

METHODS

: A systematic review was conducted by searching the MEDLINE, Embase, Cochrane Library, CINHAL, Web of Science, and the Physiotherapy Evidence Database for experimental studies published in English from 1990 to 2021. E-Health studies investigating physical activity, physical performance, quality of life, and activity of daily living assessment in adults aged ≥65 years with sarcopenia or frailty were selected.

RESULTS

: Among the 3,164 identified articles screened, a total of 4 studies complied with the inclusion criteria. The studies were heterogeneous by participant characteristics, type of e-Health intervention, and outcome measurement. Age criteria for participant selection and sex distribution were different between studies. Each study used different criteria for frailty, and no study used sarcopenia as a selection criteria. E-Health interventions were various across studies. Two studies used frailty status as an outcome measure and showed conflicting results. Muscle strength was assessed in 2 studies, and meta-analysis showed statistically significant improvement after intervention (standardized mean difference, 0.51; 95% confidence interval, 0.07-0.94; p=0.80, I2=0%).

CONCLUSION

: This systematic review found insufficient evidence to support the efficacy of e-Health interventions. Nevertheless, the studies included in this review showed positive effects of e-Health interventions on improving muscle strength, physical activity, and quality of life in older adults with frailty.

Effectiveness of Interventions Promoting Physical Activity and Reducing Sedentary Behavior in Community-Dwelling Older Adults: An Umbrella Review With Application to Saudi Arabia

BACKGROUND

As Saudi Arabia is expected to face population aging in the future, the burden of diseases arising from inadequate physical activity (PA) and excess sedentary behavior (SB) may subsequently increase without successful interventions. The present study critically reviews the global literature on the effectiveness of PA interventions targeting community-dwelling older adults to draw on lessons and applications for future interventions in Saudi Arabia.

METHODS

This umbrella review of systematic reviews included interventions designed to increase PA and/or reduce SB in community-dwelling older adults. We conducted searches in July 2022 in two electronic databases-PubMed and Embase-and identified relevant peer-reviewed systematic reviews in English.

RESULTS

Fifteen systematic reviews focusing on community-dwelling older adults were included. Several reviews reported that PA- or SB-based interventions, including eHealth interventions (such as automated advice, tele-counseling, digital PA coaching, automated PA tracking and feedback, online resources, online social support, and video demonstrations), mHealth interventions, and non-eHealth interventions (such as goal setting, individualized feedback, motivational sessions, phone calls, face-to-face education, counseling, supervised exercise sessions, sending educational materials to participants' homes, music, and social marketing programs), were effective in the short term (e.g., ≤ 3 months) but with wide heterogeneity in findings and methodologies. There were limited studies on PA- and SB-based interventions that could be effective for one year or more after the intervention. Most reviews were heavily skewed toward studies carried out in Western communities, limiting their generalizability to Saudi Arabia and other parts of the world.

CONCLUSION

There is evidence that some PA and SB interventions may be effective in the short term, but high-quality evidence regarding long-term effects is lacking. The cultural, climate, and environmental barriers related to PA and SB in Saudi Arabia require an innovative approach and research to evaluate such interventions in older individuals in the long term.

The effects of an e-health brisk walking intervention in increasing moderate-to-vigorous physical activity in physically inactive older people with cognitive frailty: study protocol for a randomized controlled trial

BACKGROUND

Cognitive frailty is a risk for many adverse health outcomes that are commonly observed in older people. Physical activity is known to be effective to reserve cognitive frailty but the prevalence of physical inactivity is still high in older people. E-health enhances behavioural change effects through an innovative way to deliver behavioural change methods that can enhance the behavioural change effects. However, its effects on older people with cognitive frailty, its effects compared with conventional behavioural change methods, and the sustainability of the effects are unclear.

METHODS

This study employs a single-blinded, two-parallel-group, non-inferiority, randomized controlled trial design with a 1:1 group allocation ratio. Eligible participants are aged 60 years or above, have cognitive frailty and physical inactivity, and possess a smartphone for more than six months. The study will be conducted in community settings. In the intervention group, participants will receive a 2-week brisk-walking training followed by a 12-week e-health intervention. In the control group, participants will receive a 2-week brisk-walking training followed by a 12-week conventional behavioural change intervention. The primary outcome is minutes of moderate-to-vigorous physical activity (MVPA). This study aims to recruit a total of 184 participants. Generalized estimating equations (GEE) will be used to examine the effects of the intervention.

ETHICS AND DISSEMINATION

The trial has been registered at ClinicalTrials.gov (Identifier: NCT05758740) on 7th March 2023, https://clinicaltrials.gov/ct2/show/NCT05758740 , and all items come from the World Health Organization Trial Registration Data Set. It has been approved by the Research Ethics Committee of Tung Wah College, Hong Kong (reference number: REC2022136). The findings will be disseminated in peer-reviewed journals and presented at international conferences relevant to the subject fields.

TRIAL REGISTRATION

The trial has been registered at ClinicalTrials.gov (Identifier: NCT05758740) and all items come from the World Health Organization Trial Registration Data Set. The latest version of the protocol was published online on 7th March 2023.

Adding Mobile Elements to Online Physical Activity Interventions for Adults Aged Over 50 Years: Prototype Development Study

BACKGROUND

Only a minority of adults aged over 50 years meet physical activity (PA) guidelines of the World Health Organization (WHO). eHealth interventions are proven effective tools to help this population increase its PA levels in the short term, among which the Active Plus and I Move interventions have been developed by our own research group. To achieve long-term effects, increase intervention use, and decrease dropout rates, 3 emergent but different mobile elements (an activity tracker, an ecological momentary intervention [EMI] program, and a chatbot) were added separately to Active Plus and I Move. In this study, the prototype development and pilot-testing of these interventions is described.

OBJECTIVE

This study aims to enhance 2 existing PA-stimulating computer-based interventions with 3 mobile elements (an activity tracker, an EMI program, or a chatbot) and test the prototypes on usability and appreciation within a target population of adults aged over 50 years.

METHODS

A systematic design protocol consisting of development, evaluation, and adaptation procedures was followed with involvement of the target population. Literature searches separated per mobile element and interviews with the target population (N=11) led to 6 prototypes: Active Plus or I Move including (1) an activity tracker, (2) EMI, or (3) a chatbot. These prototypes were tested on usability and appreciation during pilot tests (N=47) and subsequently fine-tuned based on the results.

RESULTS

The literature searches and interviews provided important recommendations on the preferences of the target population, which enabled us to develop prototypes. The subsequent pilot tests showed that the mobile elements scored moderate to good on usability, with average System Usability Scale (SUS) scores of 52.2-82.2, and moderate to good on enjoyment and satisfaction, with average scores ranging from 5.1 to 8.1 on a scale of 1-10. The activity tracker received the best scores, followed by EMI, followed by the chatbot. Based on the findings, the activity tracker interventions were fine-tuned and technical difficulties regarding EMI and the chatbot were solved, which is expected to further improve usability and appreciation.

CONCLUSIONS

During this study, 6 prototypes of online PA interventions with added mobile elements were developed and tested for usability and appreciation. Although all prototypes scored moderate to high on usability, enjoyment, and satisfaction, it can be concluded that the integration of an activity tracker with a computer-based PA intervention is the most promising option among the 3 mobile elements tested during this study. The prototype development steps of the systematic design protocol followed can be considered useful and successful for the purposes of this study. The interventions can now be evaluated on a larger scale through a randomized controlled trial.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/31677.

Co-designing implementation strategies to promote remote physical activity programs in frail older community-dwellers

Background

The "AGIL Barcelona (AGILBcn)" community-based integrated care program is a multicomponent healthy aging intervention for frail older adults. In this context, the present study aimed to identify implementation strategies to optimize the accessibility, acceptability, and adaptability of mobile health (mhealth) interventions to enhance physical activity in frail older adults, and to prioritize action points according to their importance and feasibility, through a co-design process.

Material and methods

A mixed methods approach was used. In the qualitative phase, a method adapted from the World Café was applied in 6 virtual groups to identify strategies to facilitate the virtual physical activity program. In the quantitative phase, prioritization and feasibility of the strategies was analyzed through surveys. Strategies were ranked based on priority vs. feasibility, revealing if strategies should either be: implemented first; if possible; taken into account for future consideration; or directly disregarded. The convenience sample included older adults (n = 7), community professionals (n = 9) and health professionals (n = 13). Qualitative data were analyzed by summative content analysis and quantitative data by nonparametric descriptive analyses.

Results

A total of 27 strategies were identified and grouped into four categories: general strategies for reducing barriers; specific strategies for facilitating the use of a digital application; specific strategies for facilitating participation in virtual exercise groups; and specific strategies for facilitating external support. According to the ranking of strategies, the first ones to be implemented included: digital literacy, digital capability assessment, family technology support, weekly telephone follow-up by professionals, personalizing exercises, and virtual exercises in small groups.

Conclusion

The active participation of all stakeholders enabled us to identify potential strategies for implementing person-oriented technology in physical activity programs and for engaging older adults.

Middle-aged and older adults' acceptance of mobile nutrition and fitness apps: A systematic mixed studies review

BACKGROUND

To promote healthy aging, the support of digital mobile health tools such as mobile applications (apps) addressing a healthy diet or physical activity appears promising, particularly when initiated before entering old age. For such tools to be effective, middle-aged and older adults' acceptance need to be studied in depth.

OBJECTIVE

The aim of this systematic review was to provide an integrative synthesis of the current state of research regarding the question in how far middle-aged and older adults (people aged 50 years and above) accept mobile nutrition and fitness apps to gain a deeper understanding of the influencing factors shaping this target group's usage behaviour and needs.

METHODS

The review process followed the PRISMA guidelines. The databases Medline, Embase, Web of Science as well as reference lists were systematically searched. Study quality was assessed using the MMAT and AXIS appraisal tools. Data of the included studies were extracted and thereupon narratively synthesized, involving thematic analysis.

RESULTS

Of N = 8823 articles screened, n = 7 studies could be identified-five quantitative, cross-sectional ones and two qualitative studies. Overall, the synthesized findings showed a lower acceptance among middle-aged and older adults compared to younger populations, which was particularly reflected in lower usage rates and more negative attitudes towards such apps (e.g., Perceived usefulness, Ease of use). The target group's acceptance of fitness apps was greater compared to nutrition apps. Findings on contextual factors and social determinants were inconsistent (e.g., regarding gender differences).

CONCLUSION

While cross-study comparability was limited, the synthesized evidence underscores the importance to target mobile nutrition and fitness apps to the distinctive and heterogeneous needs of middle-aged and, particularly, of older adults. The scarcity of the existing body of knowledge highlights the need of further (longitudinal) research.

PROSPERO PROTOCOL REGISTER NUMBER

CRD42020159409.

Usability evaluation of mHealth apps for elderly individuals: a scoping review

BACKGROUND

Usability is a key factor affecting the acceptance of mobile health applications (mHealth apps) for elderly individuals, but traditional usability evaluation methods may not be suitable for use in this population because of aging barriers. The objectives of this study were to identify, explore, and summarize the current state of the literature on the usability evaluation of mHealth apps for older adults and to incorporate these methods into the appropriate evaluation stage.

METHODS

Electronic searches were conducted in 10 databases. Inclusion criteria were articles focused on the usability evaluation of mHealth apps designed for older adults. The included studies were classified according to the mHealth app usability evaluation framework, and the suitability of evaluation methods for use among the elderly was analyzed.

RESULTS

Ninety-six articles met the inclusion criteria. Research activity increased steeply after 2013 (n = 92). Satisfaction (n = 74) and learnability (n = 60) were the most frequently evaluated critical measures, while memorability (n = 13) was the least evaluated. The ratios of satisfaction, learnability, operability, and understandability measures were significantly related to the different stages of evaluation (P < 0.05). The methods used for usability evaluation were questionnaire (n = 68), interview (n = 36), concurrent thinking aloud (n = 25), performance metrics (n = 25), behavioral observation log (n = 14), screen recording (n = 3), eye tracking (n = 1), retrospective thinking aloud (n = 1), and feedback log (n = 1). Thirty-two studies developed their own evaluation tool to assess unique design features for elderly individuals.

CONCLUSION

In the past five years, the number of studies in the field of usability evaluation of mHealth apps for the elderly has increased rapidly. The mHealth apps are often used as an auxiliary means of self-management to help the elderly manage their wellness and disease. According to the three stages of the mHealth app usability evaluation framework, the critical measures and evaluation methods are inconsistent. Future research should focus on selecting specific critical measures relevant to aging characteristics and adapting usability evaluation methods to elderly individuals by improving traditional tools, introducing automated evaluation tools and optimizing evaluation processes.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

BACKGROUND

There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes.

METHODS

We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner.

RESULTS

A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction.

CONCLUSIONS

The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.

Successful Aging for Community-Dwelling Older Adults: An Experimental Study with a Tablet App

Mobile health (mHealth) technologies offer an opportunity to enable the care and support of community-dwelling older adults, however, research examining the use of mHealth in delivering quality of life (QoL) improvements in the older population is limited. We developed a tablet application (eSeniorCare) based on the Successful Aging framework and investigated its feasibility among older adults with low socioeconomic status. Twenty five participants (females = 14, mean age = 65 years) used the app to set and track medication intake reminders and health goals, and to play selected casual mobile games for 24 weeks. The Older person QoL and Short Health (SF12v2) surveys were administered before and after the study. The Wilcoxon rank tests were used to determine differences from baseline, and thematic analysis was used to analyze post-study interview data. The improvements in health-related QoL (HRQoL) scores were statistically significant (V=41.5, p=0.005856) across all participants. The frequent eSeniorCare users experienced statistically significant improvements in their physical health (V=13, p=0.04546) and HRQoL (V=7.5, p=0.0050307) scores. Participants reported that the eSeniorCare app motivated timely medication intake and health goals achievement, whereas tablet games promoted mental stimulation. Participants were willing to use mobile apps to self-manage their medications (70%) and adopt healthy activities (72%), while 92% wanted to recommend eSeniorCare to a friend. This study shows the feasibility and possible impact of an mHealth tool on the health-related QoL in older adults with a low socioeconomic status. mHealth support tools and future research to determine their effects are warranted for this population.

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.

Going digital - a commentary on the terminology used at the intersection of physical activity and digital health

In recent years digital technologies have become a major means for providing health-related services and this trend was strongly reinforced by the current Coronavirus disease 2019 (COVID-19) pandemic. As it is well-known that regular physical activity has positive effects on individual physical and mental health and thus is an important prerequisite for healthy aging, digital technologies are also increasingly used to promote unstructured and structured forms of physical activity. However, in the course of this development, several terms (e.g., Digital Health, Electronic Health, Mobile Health, Telehealth, Telemedicine, and Telerehabilitation) have been introduced to refer to the application of digital technologies to provide health-related services such as physical interventions. Unfortunately, the above-mentioned terms are often used in several different ways, but also relatively interchangeably. Given that ambiguous terminology is a major source of difficulty in scientific communication which can impede the progress of theoretical and empirical research, this article aims to make the reader aware of the subtle differences between the relevant terms which are applied at the intersection of physical activity and Digital Health and to provide state-of-art definitions for them.

Effects of the exercise mobile app and distance supervision on the functional performance of the older adults. Protocol of a clinical, randomized, controlled trial

Objective: To check the effects of the exercise mobile app with face-to-face and distance supervision on the functional performance, postural balance, and lower limb strength of older adults. Methods: This is a protocol of a controlled, randomized, and blind clinical trial in which we will recruit older adults of both genders, who will be randomized into two types of training: a control group (exercises using a mobile app with face-to-face monitoring by the therapist) and an experimental group (exercises with a mobile app without face-to-face monitoring by the therapist). The training will be carried out with the free app "Exercício para idosos", which should be installed on the participants' smartphones. The participants should do the proposed exercises three times a week for eight consecutive weeks. The evaluations will be conducted in person pre-training and after the 12th and 24th sessions. Functional performance, postural balance, and lower limb strength will be assessed. The data in each evaluation will be compared as well as the difference between the groups. It is believed that physical exercise apps for older people will benefit both groups by improving functional capacity, postural balance, and lower limbs of older adults.

The Implementation of Behavior Change Techniques in mHealth Apps for Sleep: Systematic Review

Background

Mobile health (mHealth) apps targeting health behaviors using behavior change techniques (BCTs) have been successful in promoting healthy behaviors; however, their efficacy with sleep is unclear. Some work has shown success in promoting sleep through mHealth, whereas there have been reports that sleep apps can be adverse and lead to unhealthy obsessions with achieving perfect sleep.

Objective

This study aims to report and describe the use of BCTs in mHealth apps for sleep with the following research questions: How many BCTs are used on average in sleep apps, and does this relate to their effectiveness on sleep outcomes? Are there specific BCTs used more or less often in sleep apps, and does this relate to their effectiveness on sleep outcomes? Does the effect of mHealth app interventions on sleep change when distinguishing between dimension and measurement of sleep?

Methods

We conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review articles on mHealth app interventions for sleep published between 2010 and 2020.

Results

A total of 12 studies met the eligibility criteria. Most studies reported positive sleep outcomes, and there were no negative effects reported. Sleep quality was the most common dimension of sleep targeted. Subjective measures of sleep were used across all apps, whereas objective measures were often assessed but rarely reported as part of results. The average number of BCTs used was 7.67 (SD 2.32; range 3-11) of 16. Of the 12 studies, the most commonly used BCTs were feedback and monitoring (n=11, 92%), shaping knowledge (n=11, 92%), goals and planning (n=10, 83%), and antecedents (n=10, 83%), whereas the least common were scheduled consequences (n=0, 0%), self-belief (n=0, 0%), and covert learning (n=0, 0%). Most apps used a similar set of BCTs that unfortunately did not allow us to distinguish which BCTs were present when studies reported more positive outcomes.

Conclusions

Our study describes the peer-reviewed literature on sleep apps and provides a foundation for further examination and optimization of BCTs used in mHealth apps for sleep. We found strong evidence that mHealth apps are effective in improving sleep, and the potential reasons for the lack of adverse sleep outcome reporting are discussed. We found evidence that the type of BCTs used in mHealth apps for sleep differed from other health outcomes, although more research is needed to understand how BCTs can be implemented effectively to improve sleep using mHealth and the mechanisms of action through which they are effective (eg, self-efficacy, social norms, and attitudes).

Web-Based Versus Print-Based Physical Activity Intervention for Community-Dwelling Older Adults: Crossover Randomized Trial

Background

Fewer than half of older German adults engage in the recommended levels of endurance training.

Objective

The study aim is to compare the acceptance and effectiveness of two interventions for physical activity (PA) promotion among initially inactive community-dwelling older adults ≥60 years in a 9-month, crossover randomized trial.

Methods

Participants were recruited in person and randomized to one of the following interventions for self-monitoring PA: a print-based intervention (PRINT: 113/242, 46.7%) or a web-based intervention (WEB: 129/242, 53.3%). Furthermore, 29.5% (38/129) of those in the web-based intervention group received a PA tracker in addition to WEB (WEB+). After randomization, the participants and researchers were not blinded. The participants’ baseline intervention preferences were retrospectively assessed. All the intervention groups were offered 10 weekly face-to-face group sessions. Afterward, participants could choose to stay in their group or cross over to one of the other groups, and group sessions were continued monthly for another 6 months. 3D accelerometers to assess PA and sedentary behavior (SB) at baseline (T0), 3-month follow-up (T1), and 9-month follow-up (T2) were used. Adherence to PA recommendations, attendance of group sessions, and intervention acceptance were assessed using self-administered paper-based questionnaires. Linear mixed models were used to calculate differences in moderate to vigorous PA (MVPA) and SB between time points and intervention groups.

Results

Of the 242 initially recruited participants, 91 (37.6%) were randomized to the WEB group; 38 (15.7%) to the WEB+ group; and 113 (46.7%) to the PRINT group. Overall, 80.6% (195/242) of the participants completed T1. Only 0.4% (1/242) of the participants changed from the WEB group to the PRINT group and 6.2% (15/242) moved from the PRINT group to the WEB group (WEB-WEB: 103/249, (41.4%); PRINT-PRINT: 76/249, 30.5%) when offered to cross over at T1. Furthermore, 66.1% (160/242) of participants completed T2. MVPA in minutes per day increased between baseline and T1, but these within-group changes disappeared after adjusting for covariates. MVPA decreased by 9 minutes per day between baseline and T2 (β_time=−9.37, 95% CI −18.58 to −0.16), regardless of the intervention group (WEB vs PRINT: β_group*time=−3.76, 95% CI −13.33 to 5.82, WEB+ vs PRINT: β_group*time=1.40, 95% CI −11.04 to 13.83). Of the participants, 18.6% (38/204) met the PA recommendations at T0, 16.4% (26/159) at T1, and 20.3% (28/138) at T2. For SB, there were no significant group differences or group-by-time interactions at T1 or T2. Intervention acceptance was generally high. The use of intervention material was high to moderate at T1 and decreased by T2.

Conclusions

There was little movement between intervention groups at T1 when given the choice, and participation was not associated with increases in PA or decreases in SB over time.

Trial Registration

German Clinical Trials Register DRKS00016073; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016073

Behavioural interventions to promote physical activity in a multiethnic population at high risk of diabetes: PROPELS three-arm RCT

BACKGROUND

Type 2 diabetes is a leading cause of mortality globally and accounts for significant health resource expenditure. Increased physical activity can reduce the risk of diabetes. However, the longer-term clinical effectiveness and cost-effectiveness of physical activity interventions in those at high risk of type 2 diabetes is unknown.

OBJECTIVES

To investigate whether or not Walking Away from Diabetes (Walking Away) - a low-resource, 3-hour group-based behavioural intervention designed to promote physical activity through pedometer use in those with prediabetes - leads to sustained increases in physical activity when delivered with and without an integrated mobile health intervention compared with control.

DESIGN

Three-arm, parallel-group, pragmatic, superiority randomised controlled trial with follow-up conducted at 12 and 48 months.

SETTING

Primary care and the community.

PARTICIPANTS

Adults whose primary care record included a prediabetic blood glucose measurement recorded within the past 5 years [HbA_1c ≥ 42 mmol/mol (6.0%), < 48 mmol/mol (6.5%) mmol/mol; fasting glucose ≥ 5.5 mmol/l, < 7.0 mmol/l; or 2-hour post-challenge glucose ≥ 7.8 mmol/l, < 11.1 mmol/l] were recruited between December 2013 and February 2015. Data collection was completed in July 2019.

INTERVENTIONS

Participants were randomised (1 : 1 : 1) using a web-based tool to (1) control (information leaflet), (2) Walking Away with annual group-based support or (3) Walking Away Plus (comprising Walking Away, annual group-based support and a mobile health intervention that provided automated, individually tailored text messages to prompt pedometer use and goal-setting and provide feedback, in addition to biannual telephone calls). Participants and data collectors were not blinded; however, the staff who processed the accelerometer data were blinded to allocation.

MAIN OUTCOME MEASURES

The primary outcome was accelerometer-measured ambulatory activity (steps per day) at 48 months. Other objective and self-reported measures of physical activity were also assessed.

RESULTS

A total of 1366 individuals were randomised (median age 61 years, median body mass index 28.4 kg/m², median ambulatory activity 6638 steps per day, women 49%, black and minority ethnicity 28%). Accelerometer data were available for 1017 (74%) and 993 (73%) individuals at 12 and 48 months, respectively. The primary outcome assessment at 48 months found no differences in ambulatory activity compared with control in either group (Walking Away Plus: 121 steps per day, 97.5% confidence interval -290 to 532 steps per day; Walking Away: 91 steps per day, 97.5% confidence interval -282 to 463). This was consistent across ethnic groups. At the intermediate 12-month assessment, the Walking Away Plus group had increased their ambulatory activity by 547 (97.5% confidence interval 211 to 882) steps per day compared with control and were 1.61 (97.5% confidence interval 1.05 to 2.45) times more likely to achieve 150 minutes per week of objectively assessed unbouted moderate to vigorous physical activity. In the Walking Away group, there were no differences compared with control at 12 months. Secondary anthropometric, biomechanical and mental health outcomes were unaltered in either intervention study arm compared with control at 12 or 48 months, with the exception of small, but sustained, reductions in body weight in the Walking Away study arm (≈ 1 kg) at the 12- and 48-month follow-ups. Lifetime cost-effectiveness modelling suggested that usual care had the highest probability of being cost-effective at a threshold of £20,000 per quality-adjusted life-year. Of 50 serious adverse events, only one (myocardial infarction) was deemed possibly related to the intervention and led to the withdrawal of the participant from the study.

LIMITATIONS

Loss to follow-up, although the results were unaltered when missing data were replaced using multiple imputation.

CONCLUSIONS

Combining a physical activity intervention with text messaging and telephone support resulted in modest, but clinically meaningful, changes in physical activity at 12 months, but the changes were not sustained at 48 months.

FUTURE WORK

Future research is needed to investigate which intervention types, components and features can help to maintain physical activity behaviour change over the longer term.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN83465245.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 77. See the NIHR Journals Library website for further project information.

A Behavioral Lifestyle Intervention to Improve Frailty in Overweight or Obese Older Adults with Type 2 Diabetes: A Feasibility Study

BACKGROUND

Older adults with Type 2 diabetes (T2D) are more likely to be frail, which increases the risk for disability and mortality.

OBJECTIVES

To determine the feasibility of a behavioral lifestyle intervention, enhanced with mobile health technology for self-monitoring of diet and activity, to improve frailty in overweight/obese older adults (≥65 years) diagnosed with T2D.

DESIGN, SETTING, AND PARTICIPANTS

Single arm, 6-month study of a behavioral lifestyle intervention in 20 overweight/obese (BMI>25) older adults (≥ 65 years) with self-reported T2D diagnosis who owned a smartphone. A Fitbit tracker was provided to all participants for self-monitoring of diet and physical activity. Our primary outcome of feasibility was measured by session attendance, adherence to Fitbit usage to self-monitor diet and physical activity, and study retention. Secondary outcomes included the preliminary efficacy of the intervention on frailty, physical function, quality of life, and T2D-related outcomes.

RESULTS

Eighteen participants completed the study. The mean age was 71.5 (SD ± 5.3) years, 56% were female, and half were Hispanic. At baseline, 13 (72%) were pre-frail, 4 (22%) were frail, and 1 (6%) were non-frail. At follow-up, frailty scores improved significantly from 1.61 ± 1.15 to 0.94 ± 0.94 (p=0.01) and bodyweight improved from 205.66 ± 45.52 lbs. to 198.33 ± 43.6 lbs. (p=<0.001).

CONCLUSION

This study provides evidence for the feasibility of a behavioral lifestyle intervention in overweight/obese older adults with T2D and preliminary results support its potential efficacy in improving frailty score.

Feasibility of Real-time Behavior Monitoring Via Mobile Technology in Czech Adults Aged 50 Years and Above: 12-Week Study With Ecological Momentary Assessment

Background

Czech older adults have lower rates of physical activity than the average population and lag behind in the use of digital technologies, compared with their peers from other European countries.

Objective

This study aims to assess the feasibility of intensive behavior monitoring through technology in Czech adults aged ≥50 years.

Methods

Participants (N=30; mean age 61.2 years, SD 6.8 years, range 50-74 years; 16/30, 53% male; 7/30, 23% retired) were monitored for 12 weeks while wearing a Fitbit Charge 2 monitor and completed three 8-day bursts of intensive data collection through surveys presented on a custom-made mobile app. Web-based surveys were also completed before and at the end of the 12-week period (along with poststudy focus groups) to evaluate participants’ perceptions of their experience in the study.

Results

All 30 participants completed the study. Across the three 8-day bursts, participants completed 1454 out of 1744 (83% compliance rate) surveys administered 3 times per day on a pseudorandom schedule, 451 out of 559 (81% compliance rate) end-of-day surveys, and 736 episodes of self-reported planned physical activity (with 29/736, 3.9% of the reports initiated but returned without data). The overall rating of using the mobile app and Fitbit was above average (74.5 out of 100 on the System Usability Scale). The majority reported that the Fitbit (27/30, 90%) and mobile app (25/30, 83%) were easy to use and rated their experience positively (25/30, 83%). Focus groups revealed that some surveys were missed owing to notifications not being noticed or that participants needed a longer time window for survey completion. Some found wearing the monitor in hot weather or at night uncomfortable, but overall, participants were highly motivated to complete the surveys and be compliant with the study procedures.

Conclusions

The use of a mobile survey app coupled with a wearable device appears feasible for use among Czech older adults. Participants in this study tolerated the intensive assessment schedule well, but lower compliance may be expected in studies of more diverse groups of older adults. Some difficulties were noted with the pairing and synchronization of devices on some types of smartphones, posing challenges for large-scale studies.

Mobile health applications for older adults: a systematic review of interface and persuasive feature design

OBJECTIVE

Mobile-based interventions have the potential to promote healthy aging among older adults. However, the adoption and use of mobile health applications are often low due to inappropriate designs. The aim of this systematic review is to identify, synthesize, and report interface and persuasive feature design recommendations of mobile health applications for elderly users to facilitate adoption and improve health-related outcomes.

MATERIALS AND METHODS

We searched PubMed, Embase, PsycINFO, CINAHL, and Scopus databases to identify studies that discussed and evaluated elderly-friendly interface and persuasive feature designs of mobile health applications using an elderly cohort.

RESULTS

We included 74 studies in our analysis. Our analysis revealed a total of 9 elderly-friendly interface design recommendations: 3 recommendations were targeted at perceptual capabilities of elderly users, 2 at motor coordination problems, and 4 at cognitive and memory deterioration. We also compiled and reported 5 categories of persuasive features: reminders, social features, game elements, personalized interventions, and health education.

DISCUSSION

Only 5 studies included design elements that were based on theories. Moreover, the majority of the included studies evaluated the application as a whole without examining end-user perceptions and the effectiveness of each single design feature. Finally, most studies had methodological limitations, and better research designs are needed to quantify the effectiveness of the application designs rigorously.

CONCLUSIONS

This review synthesizes elderly-friendly interface and persuasive feature design recommendations for mobile health applications from the existing literature and provides recommendations for future research in this area and guidelines for designers.

eHealth interventions targeting nutrition, physical activity, sedentary behavior, or obesity in adults: A scoping review of systematic reviews

A vast body of evidence regarding eHealth interventions for nutrition, physical activity, sedentary behavior, and obesity exists. This scoping review of systematic reviews aimed to evaluate the current level of evidence in this growing field. Seven electronic databases were searched for systematic reviews published until October 27, 2019. The systematic reviews must have included adult participants only and have evaluated eHealth behavioral interventions with the primary aim of changing nutrition, physical activity, and sedentary behavior or treating or preventing overweight and obesity. One hundred and six systematic reviews, published from 2006 to 2019, were included. Almost all (n = 98) reviews evaluated the efficacy of interventions. Over half (n = 61) included interventions focused on physical activity, followed by treatment of obesity (n = 28), nutrition (n = 22), prevention of obesity (n = 18), and sedentary behavior (n = 6). Many reviews (n = 46) evaluated one type of eHealth intervention only, while 60 included two or more types. Most reviews (n = 67) were rated as being of critically low methodological quality. This scoping review identified an increasing volume of systematic reviews evaluating eHealth interventions. It highlights several evidence gaps (e.g., evaluation of other outcomes, such as reach, engagement, or cost effectiveness), guiding future research efforts in this area.

Team VA Video Connect (VVC) to optimize mobility and physical activity in post-hospital discharge older veterans: baseline assessment

Background

Telehealth is increasingly used for rehabilitation and exercise but few studies include older adult participants with comorbidities and impairment, particularly cognitive. Using Veterans Administration Video Connect (VVC), the aim of the present study is to present the screening, recruitment, baseline assessment, and initial telehealth utilization of post-hospital discharge Veterans in a VVC home-telehealth based program to enhance mobility and physical activity.

Methods

Older adult Veterans (n = 45, mean age 73), recently discharged from the hospital with physical therapy goals, were VVC-assessed in self-report and performance-based measures, using test adaptations as necessary, by a clinical pharmacy specialist and social worker team.

Results

Basic and instrumental ADL disabilities were common as were low mobility (Short Portable Performance Battery) and physical activity levels (measured by actigraphy). Half had Montreal Cognitive Assessment (MoCA) scores in the mild cognitive impairment range (< 24). Over 2/3 of the participants used VA-supplied tablets. While half of the Veterans were fully successful in VVC, 1/3 of these and an additional group with at least one failed connection requested in-person visits for assistance. One-quarter had no VVC success and sought help for tablet troubleshooting, and half of these eventually “gave up” trying to connect; difficulty with using the computer and physical impairment (particularly dexterity) were described prominently in this group. On the other hand, Veterans with at least mild cognitive impairment (based on MoCA scores) were present in all connectivity groups and most of these used caregiver support to facilitate VVC.

Conclusions

Disabled older post-hospital discharged Veterans with physical therapy goals can be VVC-assessed and enrolled into a mobility/physical activity intervention. A substantial proportion required technical support, including in-person support for many. Yet, VVC seems feasible in those with mild cognitive impairment, assuming the presence of an able caregiver. Modifications of assessment tools were needed for the VVC interface, and while appearing feasible, will require further study.

Trial registration

ClinicalTrials.gov NCT 04045054 05/08/2019.

Is mHealth a Useful Tool for Self-Assessment and Rehabilitation of People with Multiple Sclerosis? A Systematic Review

The development of mobile technology and mobile Internet offers new possibilities in rehabilitation and clinical assessment in a longitudinal perspective for multiple sclerosis management. However, because the mobile health applications (mHealth) have only been developed recently, the level of evidence supporting the use of mHealth in people with multiple sclerosis (pwMS) is currently unclear. Therefore, this review aims to list and describe the different mHealth available for rehabilitation and self-assessment of pwMS and to define the level of evidence supporting these interventions for functioning problems categorized within the International Classification of Functioning, Disability and Health (ICF). In total, 36 studies, performed with 22 different mHealth, were included in this review, 30 about rehabilitation and six for self-assessment, representing 3091 patients. For rehabilitation, most of the studies were focusing on cognitive function and fatigue. Concerning the efficacy, we found a small but significant effect of the use of mHealth for cognitive training (Standardized Mean Difference (SMD) = 0.28 [0.12; 0.45]) and moderate effect for fatigue (SMD = 0.61 [0.47; 0.76]). mHealth is a promising tool in pwMS but more studies are needed to validate these solutions in the other ICF categories. More replications studies are also needed as most of the mHealth have only been assessed in one single study.

An mHealth-Facilitated Personalized Intervention for Physical Activity and Sleep in Community-Dwelling Older Adults

This randomized controlled pilot trial tested the preliminary effect of a 24-week mHealth-facilitated, personalized intervention on physical activity (PA) and sleep in 21 community-dwelling older adults. The intervention included a personalized exercise prescription, training, goal setting, and financial incentives. mHealth strategies, including self-monitoring, motivational messages, activity reminders, and phone coaching, were used to facilitate PA participation. PA and sleep were measured using actigraphy and questionnaires at baseline and 8-, 16-, and 24-week visits. Participants in the intervention group had lower objective PA levels at 24 weeks than at 8 and 16 weeks, although levels of PA remained higher than at baseline. Compared with the control group, the intervention increased PA at 8, 16, and 24 weeks; improved subjective sleep quality at 16 and 24 weeks; and increased actigraphy-measured sleep duration and sleep efficiency at 24 weeks. mHealth PA interventions may benefit PA and sleep in older adults. Strategies for maintaining long-term PA behavioral changes are needed.

Effectiveness of a reablement training program for homecare staff on older adults' sedentary behavior: A cluster randomized controlled trial

BACKGROUND/OBJECTIVES

Homecare staff often take over activities instead of "doing activities with" clients, thereby hampering clients from remaining active in daily life. Training and supporting staff to integrate reablement into their working practices may reduce clients' sedentary behavior and improve their independence. This study evaluated the effectiveness of the "Stay Active at Home" (SAaH) reablement training program for homecare staff on older homecare clients' sedentary behavior.

DESIGN

Cluster randomized controlled trial (c-RCT).

SETTING

Dutch homecare (10 nursing teams comprising a total of 313 staff members).

PARTICIPANTS

264 clients (aged ≥65 years).

INTERVENTION

SAaH seeks to equip staff with knowledge, attitude, and skills on reablement, and to provide social and organizational support to implement reablement in homecare practice. SAaH consists of program meetings, practical assignments, and weekly newsletters over a 9-month period. The control group received no additional training and delivered care as usual.

MEASUREMENTS

Sedentary behavior (primary outcome) was measured using tri-axial wrist-worn accelerometers. Secondary outcomes included daily functioning (GARS), physical functioning (SPPB), psychological functioning (PHQ-9), and falls. Data were collected at baseline and at 12 months; data on falls were also collected at 6 months. Intention-to-treat analyses using mixed-effects linear and logistic regression were performed.

RESULTS

We found no statistically significant differences between the study groups for sedentary time expressed as daily minutes (adjusted mean difference: β 18.5 (95% confidence interval [CI] -22.4, 59.3), p = 0.374) and as proportion of wake/wear time (β 0.6 [95% CI -1.5, 2.6], p = 0.589) or for most secondary outcomes.

CONCLUSION

Our c-RCT showed no evidence for the effectiveness of SAaH for all client outcomes. Refining SAaH, by adding components that intervene directly on homecare clients, may optimize the program and require further research. Additional research should explore the effectiveness of SAaH on behavioral determinants of clients and staff and cost-effectiveness.

Use of a Personal Sleep Self-Monitoring Device for Sleep Self-Management: A Feasibility Study

The purpose of the current study was to establish feasibility of personal sleep monitoring devices (PSMDs) as an intervention for sleep self-management in older adults. This study followed a mixed-methods experimental design based on the World Health Organization's International Classification of Functioning, Disability, and Health, and the proposed conceptual model of symptom management in a social context. Results showed an acceptable recruitment and retention rate of participants, and acceptability of PSMDs by users. Participants were able to meaningfully interpret PSMD data as evidenced by the numeracy evaluation scores, initiate sleep goals, and share their sleep data and goals with friends or relatives. Findings support extending this research protocol to a larger sample. Future studies for sleep health self-management and personally tailored interventions using personal sleep monitoring are recommended. [Journal of Gerontological Nursing, 47(1), 28-34.].

User-centered development of a smartphone application (Fit2Thrive) to promote physical activity in breast cancer survivors

Increased moderate and vigorous physical activity (MVPA) is associated with better health outcomes in breast cancer survivors; yet, most are insufficiently active. Smartphone applications (apps) to promote MVPA have high scalability potential, but few evidence-based apps exist. The purpose is to describe the testing and usability of Fit2Thrive, a MVPA promotion app for breast cancer survivors. A user-centered, iterative design process was utilized on three independent groups of participants. Two groups of breast cancer survivors (group 1 n = 8; group 2: n = 14) performed app usability field testing by interacting with the app for ≥3 days in a free-living environment. App refinements occurred following each field test. The Post-Study System Usability Questionnaire (PSSUQ) and the User Version Mobile Application Rating Scale (uMARS) assessed app usability and quality on a 7- and 5-point scale, respectively, and women provided qualitative written feedback. A third group (n = 15) rated potential app notification content. Quantitative data were analyzed using descriptive statistics. Qualitative data were analyzed using a directed content analysis. The PSSUQ app usability score (M1= 3.8; SD = 1.4 vs. M2= 3.2; SD = 1.1; lower scores are better) and uMARS app quality score (M1 = 3.4; SD = 1.3 vs. M2= 3.4; SD = 0.6; higher scores are better) appeared to improve in Field Test 2. Group 1 participants identified app "clunkiness," whereas group 2 participants identified issues with error messaging/functionality. Group 3 "liked" 53% of the self-monitoring, 71% of the entry reminder, 60% of the motivational, and 70% of the goal accomplishment notifications. Breast cancer survivors indicated that the Fit2Thrive app was acceptable and participants were able to use the app. Future work will test the efficacy of this app to increase MVPA.

Mobile health apps to reduce sedentary behavior: a scoping review

Given the continued increase in mobile health applications (apps) aimed at healthcare and the recognition of sedentary behavior (SB) as a public health problem, the goal of this scoping review study was to summarize the effects of interventions based on mobile health apps designed to reduce SB in adults, with a specific focus on SB. The electronic databases PubMed, PsycINFO, SportDISCUS, Web of Science, and manual searches in reference lists were conducted on papers published up to September 2020. Nine out of the 897 studies researched were included and composed the descriptive synthesis. The investigations found in the present study showed a decrease in time spent on television viewing and in total time spent sitting, as well as an increase in the number of SB breaks after interventions based on mobile health apps. In conclusion, despite the growing interest in intervention programs in SB, only nine studies have used smartphone apps as a strategy to reduce SB in adults. Mobile health apps were proved to be effective in SB reduction, as assessed by different parameters, and should be encouraged. However, further studies are needed to verify the long-term effects of the utilization of such applications.

Interventions for reducing sedentary behaviour in community-dwelling older adults

BACKGROUND

Older adults are the most sedentary segment of society, often spending in excess of 8.5 hours a day sitting. Large amounts of time spent sedentary, defined as time spend sitting or in a reclining posture without spending energy, has been linked to an increased risk of chronic diseases, frailty, loss of function, disablement, social isolation, and premature death.

OBJECTIVES

To evaluate the effectiveness of interventions aimed at reducing sedentary behaviour amongst older adults living independently in the community compared to control conditions involving either no intervention or interventions that do not target sedentary behaviour.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, PsycINFO, PEDro, EPPI-Centre databases (Trials Register of Promoting Health Interventions (TRoPHI) and the Obesity and Sedentary behaviour Database), WHO ICTRP, and ClinicalTrials.gov up to 18 January 2021. We also screened the reference lists of included articles and contacted authors to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs. We included interventions purposefully designed to reduce sedentary time in older adults (aged 60 or over) living independently in the community. We included studies if some of the participants had multiple comorbidities, but excluded interventions that recruited clinical populations specifically (e.g. stroke survivors).

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and full-text articles to determine study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. Any disagreements in study screening or data extraction were settled by a third review author.

MAIN RESULTS

We included seven studies in the review, six RCTs and one cluster-RCT, with a total of 397 participants. The majority of participants were female (n = 284), white, and highly educated. All trials were conducted in high-income countries. All studies evaluated individually based behaviour change interventions using a combination of behaviour change techniques such as goal setting, education, and behaviour monitoring or feedback. Four of the seven studies also measured secondary outcomes. The main sources of bias were related to selection bias (N = 2), performance bias (N = 6), blinding of outcome assessment (N = 2), and incomplete outcome data (N = 2) and selective reporting (N=1). The overall risk of bias was judged as unclear. Primary outcomes The evidence suggests that interventions to change sedentary behaviour in community-dwelling older adults may reduce sedentary time (mean difference (MD) -44.91 min/day, 95% confidence interval (CI) -93.13 to 3.32; 397 participants; 7 studies; I² = 73%; low-certainty evidence). We could not pool evidence on the effect of interventions on breaks in sedentary behaviour or time spent in specific domains such as TV time, as data from only one study were available for these outcomes. Secondary outcomes We are uncertain whether interventions to reduce sedentary behaviour have any impact on the physical or mental health outcomes of community-dwelling older adults. We were able to pool change data for the following outcomes. • Physical function (MD 0.14 Short Physical Performance Battery (SPPB) score, 95% CI -0.38 to 0.66; higher score is favourable; 98 participants; 2 studies; I² = 26%; low-certainty evidence). • Waist circumference (MD 1.14 cm, 95% CI -1.64 to 3.93; 100 participants; 2 studies; I² = 0%; low-certainty evidence). • Fitness (MD -5.16 m in the 6-minute walk test, 95% CI -36.49 to 26.17; higher score is favourable; 80 participants; 2 studies; I² = 29%; low-certainty evidence). • Blood pressure: systolic (MD -3.91 mmHg, 95% CI -10.95 to 3.13; 138 participants; 3 studies; I² = 73%; very low-certainty evidence) and diastolic (MD -0.06 mmHg, 95% CI -5.72 to 5.60; 138 participants; 3 studies; I² = 97%; very low-certainty evidence). • Glucose blood levels (MD 2.20 mg/dL, 95% CI -6.46 to 10.86; 100 participants; 2 studies; I² = 0%; low-certainty evidence). No data were available on cognitive function, cost-effectiveness or adverse effects.

AUTHORS' CONCLUSIONS

It is not clear whether interventions to reduce sedentary behaviour are effective at reducing sedentary time in community-dwelling older adults. We are uncertain if these interventions have any impact on the physical or mental health of community-dwelling older adults. There were few studies, and the certainty of the evidence is very low to low, mainly due to inconsistency in findings and imprecision. Future studies should consider interventions aimed at modifying the environment, policy, and social and cultural norms. Future studies should also use device-based measures of sedentary time, recruit larger samples, and gather information about quality of life, cost-effectiveness, and adverse event data.

Effectiveness of Digital Interventions for Reducing Behavioral Risks of Cardiovascular Disease in Nonclinical Adult Populations: Systematic Review of Reviews

BACKGROUND

Digital health interventions are increasingly being used as a supplement or replacement for face-to-face services as a part of predictive prevention. They may be offered to those who are at high risk of cardiovascular disease and need to improve their diet, increase physical activity, stop smoking, or reduce alcohol consumption. Despite the popularity of these interventions, there is no overall summary and comparison of the effectiveness of different modes of delivery of a digital intervention to inform policy.

OBJECTIVE

This review aims to summarize the effectiveness of digital interventions in improving behavioral and health outcomes related to physical activity, smoking, alcohol consumption, or diet in nonclinical adult populations and to identify the effectiveness of different modes of delivery of digital interventions.

METHODS

We reviewed articles published in the English language between January 1, 2009, and February 25, 2019, that presented a systematic review with a narrative synthesis or meta-analysis of any study design examining digital intervention effectiveness; data related to adults (≥18 years) in high-income countries; and data on behavioral or health outcomes related to diet, physical activity, smoking, or alcohol, alone or in any combination. Any time frame or comparator was considered eligible. We searched MEDLINE, Embase, PsycINFO, Cochrane Reviews, and gray literature. The AMSTAR-2 tool was used to assess review confidence ratings.

RESULTS

We found 92 reviews from the academic literature (47 with meta-analyses) and 2 gray literature items (1 with a meta-analysis). Digital interventions were typically more effective than no intervention, but the effect sizes were small. Evidence on the effectiveness of digital interventions compared with face-to-face interventions was mixed. Most trials reported that intent-to-treat analysis and attrition rates were often high. Studies with long follow-up periods were scarce. However, we found that digital interventions may be effective for up to 6 months after the end of the intervention but that the effects dissipated by 12 months. There were small positive effects of digital interventions on smoking cessation and alcohol reduction; possible effectiveness in combined diet and physical activity interventions; no effectiveness for interventions targeting physical activity alone, except for when interventions were delivered by mobile phone, which had medium-sized effects; and no effectiveness observed for interventions targeting diet alone. Mobile interventions were particularly effective. Internet-based interventions were generally effective.

CONCLUSIONS

Digital interventions have small positive effects on smoking, alcohol consumption, and in interventions that target a combination of diet and physical activity. Small effects may have been due to the low efficacy of treatment or due to nonadherence. In addition, our ability to make inferences from the literature we reviewed was limited as those interventions were heterogeneous, many reviews had critically low AMSTAR-2 ratings, analysis was typically intent-to-treat, and follow-up times were relatively short.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42019126074; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=126074.

Exploring Breaks in Sedentary Behavior of Older Adults Immediately After Receiving Personalized Haptic Feedback: Intervention Study

BACKGROUND

"Push" components of mobile health interventions may be promising to create conscious awareness of habitual sedentary behavior; however, the effect of these components on the near-time, proximal outcome, being breaks in sedentary behavior immediately after receiving a push notification, is still unknown, especially in older adults.

OBJECTIVE

The aims of this study are to examine if older adults break their sedentary behavior immediately after receiving personalized haptic feedback on prolonged sedentary behavior and if the percentage of breaks differs depending on the time of the day when the feedback is provided.

METHODS

A total of 26 Flemish older adults (mean age 64.4 years, SD 3.8) wore a triaxial accelerometer (Activator, PAL Technologies Ltd) for 3 weeks. The accelerometer generated personalized haptic feedback by means of vibrations each time a participant sat for 30 uninterrupted minutes. Accelerometer data on sedentary behavior were used to estimate the proximal outcome, which was sedentary behavior breaks immediately (within 1, 3, and 5 minutes) after receiving personalized haptic feedback. Generalized estimating equations were used to investigate whether or not participants broke up their sedentary behavior immediately after receiving haptic feedback. A time-related variable was added to the model to investigate if the sedentary behavior breaks differed depending on the time of day.

RESULTS

A total of 2628 vibrations were provided to the participants during the 3-week intervention period. Of these 2628 vibrations, 379 (14.4%), 570 (21.7%), and 798 (30.4%) resulted in a sedentary behavior break within 1, 3 and 5 minutes, respectively. Although the 1-minute interval did not reveal significant differences in the percentage of breaks depending on the time at which the haptic feedback was provided, the 3- and 5-minute intervals did show significant differences in the percentage of breaks depending on the time at which the haptic feedback was provided. Concretely, the percentage of sedentary behavior breaks was significantly higher if personalized haptic feedback was provided between noon and 3 PM compared to if the feedback was provided between 6 and 9 AM (odds ratio 1.58, 95% CI 1.01-2.47, within 3 minutes; odds ratio 1.78, 95% CI 1.11-2.84, within 5 minutes).

CONCLUSIONS

The majority of haptic vibrations, especially those in the morning, did not result in a break in the sedentary behavior of older adults. As such, simply bringing habitual sedentary behavior into conscious awareness seems to be insufficient to target sedentary behavior. More research is needed to optimize push components in interventions aimed at the reduction of the sedentary behavior of older adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04003324; https://clinicaltrials.gov/ct2/show/NCT04003324.

The effect of a consumer-based activity tracker intervention on accelerometer-measured sedentary time among retirees: a randomized controlled REACT trial

Background

Effective strategies to reverse the increasing trend of sedentary behavior after retirement are needed. The aim of this study was to examine the effect of 12-month activity tracker-based intervention on daily total and prolonged sedentary time (≥60 minutes) among recent retirees.

Methods

Randomization to intervention and control groups was performed to 231 retirees (mean age 65.2 [SD 1.1] years, 83% women). Intervention participants wore a consumer-based wrist-worn activity tracker (Polar Loop 2, Polar, Kempele, Finland), including daily activity goal, every day and night for 12 months. The activity tracker also gave vibrating reminders to break up uninterrupted inactivity periods after 55 minutes. A wrist-worn triaxial ActiGraph wGT3X-BT accelerometer was used to measure sedentary time at baseline and at 3-, 6-, and 12-month time points.

Results

The use of an activity tracker did not reduce daily total or prolonged sedentary time over 12 months (p values for time * group interaction 0.39 and 0.27, respectively). In the post hoc analysis focusing on short- and medium-term effects on prolonged sedentary time, no differences between the intervention and control groups over 3 months were found, but a tendency for a greater decrease in prolonged sedentary time in the intervention group over 6 months was seen (mean difference in changes between the groups 29 minutes, 95% CI −2 to 61).

Conclusions

The activity tracker with inactivity alerts did not elicit changes in sedentary time over 12 months among recent retirees. Alternative approaches may be needed to achieve long-term changes in sedentary time among retirees.

Clinical Trials registration Number: NCT03320746

Mobile Apps for Older Adults: Systematic Search and Evaluation Within Online Stores

Background

Through the increasingly aging population, the health care system is confronted with various challenges such as expanding health care costs. To manage these challenges, mobile apps may represent a cost-effective and low-threshold approach to support older adults.

Objective

This systematic review aimed to evaluate the quality, characteristics, as well as privacy and security measures of mobile apps for older adults in the European commercial app stores.

Methods

In the European Google Play and App Store, a web crawler systematically searched for mobile apps for older adults. The identified mobile apps were evaluated by two independent reviewers using the German version of the Mobile Application Rating Scale. A correlation between the user star rating and overall rating was calculated. An exploratory regression analysis was conducted to determine whether the obligation to pay fees predicted overall quality.

Results

In total, 83 of 1217 identified mobile apps were included in the analysis. Generally, the mobile apps for older adults were of moderate quality (mean 3.22 [SD 0.68]). Four mobile apps (5%) were evidence-based; 49% (41/83) had no security measures. The user star rating correlated significantly positively with the overall rating (r=.30, P=.01). Obligation to pay fees could not predict overall quality.

Conclusions

There is an extensive quality range within mobile apps for older adults, indicating deficits in terms of information quality, data protection, and security precautions, as well as a lack of evidence-based approaches. Central databases are needed to identify high-quality mobile apps.

Effect of eHealth to increase physical activity in healthy adults over 55 years: A systematic review and meta-analysis

To estimate the effect of eHealth interventions on increasing physical activity (PA) in healthy adults over 55 years, a systematic review and meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. MEDLINE, Cochrane, Web of Science, SPORTDiscus, and Scopus databases were searched, from inception to February 2020, for experimental studies reporting the effect of eHealth interventions on steps/day, daily moderate-to-vigorous physical activity (MVPA min/day), PA min/week, and MVPA min/week among adults over 55 years. The DerSimonian and Laird method was used to compute a pooled effect size (ES) estimate and the respective 95% confidence interval (95% CI). Eighteen studies were included in this meta-analysis with adults whose age ranged from 58 to 74.2 years. The interventions lasted between four and 52 weeks. The ES estimates of eHealth interventions on increasing PA were 0.59 (95% CI: 0.15-1.02) for steps/day, 0.49 (95% CI: 0.17-0.80) for daily MVPA, 0.13 (95% CI: 0.01-0.24) for total weekly PA and 0.31 (95% CI: 0.13-0.48) for weekly MVPA. Considering clinical improvements, the mean change difference estimates were an increase of 1616.28 steps/day (95% CI: 386.25-2846.31), 7.41 minutes of daily MVPA (95% CI: 3.24-11.57), 40.54 minutes of total weekly PA (95% CI: -8.71 to 89.79) and 56.35 minutes of weekly MVPA (95% CI: 17.43-95.27). In conclusion, eHealth interventions are effective in increasing PA levels among adults over 55 years, resulting in increased steps/day, MVPA min/day, PA min/week and MVPA min/week.

Promoting Strength Training Among Baby Boomers: Message Framing Effects on Motivation and Behavior

BACKGROUND

Regular participation in strength training significantly enhances older adults' physical and functional health, yet only 14% of adults over age 50 report engaging in strength training at least twice per week. Exercise messages about why and how older adults should engage in strength training could influence their perceptions of and participation in the behavior. This study was designed to promote strength training among adults aged 50-70 and to determine whether the message frame accompanying a brief workout would have an impact on participants' motivation, self-efficacy, and/or physical activity behavior.

METHODS

Participants (N = 308) were randomly assigned to one of four message conditions: Easy Intrinsic, Hard Intrinsic, Easy Extrinsic, or Hard Extrinsic. Immediately after completing baseline measures of motivation and physical activity, participants received the recommended strength training workout and corresponding motivational message. They completed follow-up measures of motivation and physical activity 2 weeks later.

RESULTS

Controlled regulation was higher at follow-up among participants exposed to an extrinsic message relative to an intrinsic message (F(3,208) = 3.08, p = .03). Strength training (Z = - 5.95, p < .001) and moderate physical activity (Z = - 3.23, p = .001) increased among participants not engaging in regular strength training at baseline.

CONCLUSIONS

These results suggest message framing may have a short-term impact on Baby Boomers' physical activity motivation, such that emphasizing extrinsic goals (i.e., weight loss and appearance) may contribute to controlled motivation. However, repeated measurements are needed to determine the longer-term maintenance and influence of these effects.

Effects of an mHealth Brisk Walking Intervention on Increasing Physical Activity in Older People With Cognitive Frailty: Pilot Randomized Controlled Trial

BACKGROUND

Cognitive frailty is the coexistence of physical frailty and cognitive impairment and is an at-risk state for many adverse health outcomes. Moderate-to-vigorous physical activity (MVPA) is protective against the progression of cognitive frailty. Physical inactivity is common in older people, and brisk walking is a feasible form of physical activity that can enhance their MVPA. Mobile health (mHealth) employing persuasive technology has been successful in increasing the levels of physical activity in older people. However, its feasibility and effects on older people with cognitive frailty are unclear.

OBJECTIVE

We aimed to identify the issues related to the feasibility of an mHealth intervention and the trial (ie, recruitment, retention, participation, and compliance) and to examine the effects of the intervention on cognitive function, physical frailty, walking time, and MVPA.

METHODS

An open-label, parallel design, randomized controlled trial (RCT) was employed. The eligibility criteria for the participants were age ≥60 years, having cognitive frailty, and having physical inactivity. In the intervention group, participants received both conventional behavior change intervention and mHealth (ie, smartphone-assisted program using Samsung Health and WhatsApp) interventions. In the control group, participants received conventional behavior change intervention only. The outcomes included cognitive function, frailty, walking time, and MVPA. Permuted block randomization in 1:1 ratio was used. The feasibility issue was described in terms of participant recruitment, retention, participation, and compliance. Wilcoxon signed-rank test was used to test the within-group effects in both groups separately.

RESULTS

We recruited 99 participants; 33 eligible participants were randomized into either the intervention group (n=16) or the control (n=17) group. The median age was 71.0 years (IQR 9.0) and the majority of them were females (28/33, 85%). The recruitment rate was 33% (33/99), the participant retention rate was 91% (30/33), and the attendance rate of all the face-to-face sessions was 100% (33/33). The majority of the smartphone messages were read by the participants within 30 minutes (91/216, 42.1%). ActiGraph (58/66 days, 88%) and smartphone (54/56 days, 97%) wearing compliances were good. After the interventions, cognitive function improvement was significant in both the intervention (P=.003) and the control (P=.009) groups. The increase in frailty reduction (P=.005), walking time (P=.03), step count (P=.02), brisk walking time (P=.009), peak cadence (P=.003), and MVPA time (P=.02) were significant only in the intervention group.

CONCLUSIONS

Our mHealth intervention is feasible for implementation in older people with cognitive impairment and is effective at enhancing compliance with the brisk walking training program delivered by the conventional behavior change interventions. We provide preliminary evidence that this mHealth intervention can increase MVPA time to an extent sufficient to yield clinical benefits (ie, reduction in cognitive frailty). A full-powered and assessor-blinded RCT should be employed in the future to warrant these effects.

TRIAL REGISTRATION

HKU Clinical Trials Registry HKUCTR-2283; http://www.hkuctr.com/Study/Show/31df4708944944bd99e730d839db4756.

The Role of Psychological Factors in Older Adults' Readiness to Use eHealth Technology: Cross-Sectional Questionnaire Study

BACKGROUND

Information and communication technology (ICT) use among older adults has been on the rise in recent years. However, the predictors and mechanisms behind older adults' acceptance and use of ICT are not clear.

OBJECTIVE

This study aimed to systematically describe ICT usage among Czech older adults and to evaluate the factors influencing their ICT use and readiness to use digital technology to promote health (eHealth readiness). The primary focus was on psychological factors and the role of persons close to older adults.

METHODS

The research utilized cross-sectional survey data from a quota-based sample of Czech older adults (>50 years) and persons close to them further referred to as close persons (N=250 dyads). A structural equation modeling framework was used to evaluate relationships between psychological factors, ICT use, and eHealth readiness.

RESULTS

Czech older adults' use of ICT is low with the exception of cell phone usage (cell phone usage by 173/250, 69.2%; other devices used by 50/250, 20.0% of older adults or less). Apart from age (β=-.21; P<.001), eHealth readiness was predicted by ICT use (β=.65; P<.001). eHealth readiness was also indirectly affected by the need for cognitive closure (NFCC): individuals with a high need for closure perceived more barriers to ICT (β=.23; P=.01) and more reported barriers were linked to lower ICT usage (β=-.21; P=.001). The expected positive relationships between eHealth readiness of persons close to older adults and ICT use and eHealth readiness of older adults were not significant, but the total effect of eHealth readiness of persons close to older adults on eHealth readiness of older adults was positive and significant (β=.18; P=.01), indicating some level of influence of persons close to them on older adults' attitudes and behaviors.

CONCLUSIONS

This study provided the first systematic examination of Czech older adults' ICT usage and eHealth readiness. Novel predictors (NFCC and close persons' variables) were evaluated and yielded actionable results. More research is needed to clarify the role of persons close to older adults.

Body, Soul and Spirit, an adaptation of two evidence-based interventions to promote physical activity and healthy eating among adults in churches in Lagos Nigeria: a three-arm cluster randomized controlled pilot trial

BACKGROUND

Physical inactivity and unhealthy eating are two leading behavioral risk factors contributing to preventable non-communicable diseases (NCDs). Evidence-based interventions (EBI) using community-engaged approaches to address these risks abound in high-income countries. Comparatively, evidence of such interventions is sparse in low- and middle-income countries, where NCD mortality is greater. This paper describes the protocol for the development of the cultural adaptation and pilot testing of a combination of two EBI (i.e., Body and Soul and the Healthy Body Healthy Spirit), in church-based settings in Lagos, Nigeria. In addition, we describe the development of the inclusion of an additional component, i.e., faith-based text messages, into one of the treatment arms. Our objective is to assess the feasibility of developing and implementing the adapted interventions with the ultimate aim of developing a fully powered trial.

METHODS

This pilot study will assess the design and implementation of a three-arm cluster-randomized pilot trial in 12 randomly selected Anglican churches (4 in each arm). First, we will design a cultural adaptation of the two EBI's to form a multifaceted combined intervention known as the Body Soul and Spirit. The second treatment arm, i.e., Body Soul and Spirit Plus, will retain all the components of Body Soul and Spirit with the inclusion of faith-based text messages using mobile phones. Participants in the control arm will receive information leaflets designed to increase physical activity and healthy food consumption. The outcome measures include participant recruitment and retention, program participation and satisfaction, and data collection completion rates. The outcomes for the proposed definitive trial will be the number of servings of fruit and vegetables and minutes of moderate to vigorous physical activity per day will be assessed at baseline, 3 and 6-month follow-up. Implementation outcomes will be assessed using qualitative and quantitative methods.

DISCUSSION

The study will enhance the understanding of how best to design and implement behavioral interventions in church-based settings using community-based participatory approaches. It will also inform the development of a definitive randomized controlled trial.

TRIAL REGISTRATION

Pan African Clinical Trials Registry on 12th July 2018. PACTR201807136835945. Available at https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=3481.

The effect of e-health interventions promoting physical activity in older people: a systematic review and meta-analysis

INTRODUCTION

The objectives of this review paper were to synthesize the data from randomized controlled trials in the literature to come to a conclusion on the effects of e-health interventions on promoting physical activity in older people.

METHODS

The Medline, CINAHL, Embase, PsycINFO, and SportDiscus databases were searched for articles about studies that 1) recruited subjects with a mean age of > 50 years, 2) tested e-health interventions, 3) employed control groups with no or less advanced e-health strategies, 4) measured physical activity as an outcome, 5) were published between 1st January 2008 and 31st May 2019, and 6) employed randomized controlled trials. The risk of bias in individual studies was assessed using the Physiotherapy Evidence Database scale. To examine the effects of the interventions, variables quantifying the amount of physical activity were extracted. The within-group effects of individual studies were summarized using Hedges g and 95% confidence intervals. Between-group effects were summarized by meta-analyses using RevMan 5.0 with a random effect model.

RESULTS

Of the 2810 identified studies, 38 were eligible, 25 were included in the meta-analyses. The within-group effect sizes (Hedges g) of physical activity in the intervention group at T1 ranged from small to large: physical activity time (0.12 to 0.84), step counts (- 0.01 to 11.19), energy expenditure (- 0.05 to 0.86), walking time (0.13 to 3.33), and sedentary time (- 0.12 to - 0.28). The delayed effects as observed in T2 and T3 also ranged from small to large: physical activity time (0.24 to 1.24) and energy expenditure (0.15 to 1.32). In the meta-analysis, the between-group effect of the e-health intervention on physical activity time measured by questionnaires, physical activity time measured by objective wearable devices, energy expenditure, and step counts were all significant with minimal heterogeneity.

CONCLUSION

E-health interventions are effective at increasing the time spent on physical activity, energy expenditure in physical activity, and the number of walking steps. It is recommended that e-health interventions be included in guidelines to enhance physical activity in older people. Further studies should be conducted to determine the most effective e-health strategies.