eHealth interventions to promote objectively measured physical activity in community-dwelling older people

Umbrella review of social inequality in digital interventions targeting dietary and physical activity behaviors

Digital interventions are increasingly utilized as a lever to promote population health, yet not everyone may equally benefit from them. This umbrella review pooled the insights from available systematic and scoping reviews regarding potential social inequalities in digital intervention uptake, engagement and effectiveness, focusing on the promotion of weight-related behaviors (diet, physical activity, sedentary behavior) and weight loss (maintenance) in adults. Six databases were searched from 1970 to October 2023. Forty-six reviews were included, of which most focused on physical activity and intervention effectiveness. Age and gender/ sex differences were most frequently studied. Most reviews found digital interventions to be effective irrespective of age, while men benefitted more from digital interventions than women. Other inequality indicators (e.g., income, education) were rarely studied, despite them being potential causes of a digital divide. A more systematic and thorough exploration of inequalities in digital health is required to promote health for all.

The effectiveness of digital physical activity interventions in older adults: a systematic umbrella review and meta-meta-analysis

BACKGROUND

Physical activity is important for healthy ageing, however most older adults are inactive. Numerous reviews with a range of inclusion criteria have been conducted on digital interventions to promote physical activity in older adults, and a synthesis of these is needed. Therefore, the objective of this study is to conduct an umbrella review and meta-meta-analysis on the effectiveness of digital interventions to promote physical activity in older adults.

METHODS

Nine databases were searched from January 2010 to December 2023. Systematic reviews and meta-analyses of primary studies using digital physical activity interventions to target healthy older adults or clinical populations of older adults with a self-reported or device measured physical activity outcome were eligible for inclusion.

RESULTS

In total, 22 systematic reviews and meta-analyses covering 185 primary research papers were eligible for inclusion. The total number of participants across all primary studies was 28,198. Most (21, 95%) reviews and meta-analyses were rated as having a low or critically low AMSTAR-2 confidence rating. Of the 22 included systematic reviews, 13 (59%) conducted a meta-analysis and 10 (45%) conducted a narrative synthesis. Most systematic reviews with a narrative synthesis found strong evidence for a positive effect or moderate evidence for a positive effect for physical activity outcomes (7/9, 78%) and steps (3/3, 100%). The meta-meta-analysis of primary papers included in meta-analyses demonstrated a significant moderate effect for steps and a significant small effect for total PA and MVPA. The strength of effect did not vary by intervention components (activity tracker, app-based, SMS/phone, web-based, and face-to-face), population (primary or secondary prevention), control group (none, other digital intervention, or non-digital intervention), or outcome measurement (self-reported or device measured). Only 3 (14%) reviews included longer term follow up outcomes after the end of the intervention, with mixed results.

CONCLUSIONS

Evidence from 22 reviews and meta-analyses suggests that digital physical activity interventions are effective at increasing physical activity in older adults. Further primary research is needed in adults 65 years and over exclusively, and with longer-term follow up of physical activity outcomes. Future reviews should include a published protocol and interpret results according to risk-of-bias.

The efficacy of online physical activity interventions with added mobile elements within adults aged 50 years and over: Randomized controlled trial

Electronic health (eHealth) and mobile health (mHealth) could stimulate physical activity (PA) in a time-efficient and cost-effective way. This randomized controlled trial aims to investigate effects on moderate-to-vigorous PA (MVPA) of different combined computer- and mobile-based PA interventions targeted at adults aged 50 years and over. Participants (N = 954) were randomly allocated to a basic existing computer-based intervention (Active Plus [AP] or I Move [IM]) supplemented with one of three mobile elements being (1) activity tracker (AT), (2) ecological momentary intervention (EMI), or (3) chatbot (CB) or a control group (CG). MVPA was assessed via the SQUASH at baseline (T0), 3 months (T1), and 6 months (T2) and via accelerometers at T0 and T2. No intervention effects were found on objective (p = .502) and subjective (p = .368) MVPA for main research groups (AP/IM + AT, AP/IM + EMI, AP/IM + CB). Preliminary MVPA findings for subgroups (AP + AT, AP + EMI, AP + CB, IM + AT, IM + EMI, IM + CB) combined with drop-out data showed potential for the computer-based intervention AP with an integrated AT. Based on these preliminary findings, eHealth developers can be recommended to integrate ATs with existing computer-based PA interventions. However, further research is recommended to confirm the findings as a result of the exploratory nature of the subgroup analyses.

Vitality at home: a phenomenological study of tele-exercise in women aged 80 and older

BACKGROUND

Since the onset of coronavirus 2019, there has been an upsurge of tele-exercise delivery. Previous studies showed old adults find tele-exercise feasible and acceptable. However, there is limited understanding of the oldest-old's experiences.

METHOD

This study used the interpretative phenomenological approach. Two semi-structured interviews and home visits were conducted with six oldest-old women, aged between 81 and 91 years, who participated in tele-exercise classes.

RESULTS

Four superordinate themes were identified: ambivalent perception of safety, ease in regular participation, reminded and guided to move the aged body, and technological adaptation.

CONCLUSION

Our findings indicate that tele-exercise has the potential to assist the oldest-old living in the community in maintaining an adequate activity levels at home, which they perceive as the safest place. Emerging themes provide insights into their lived experiences, enabling service providers to enhance tele-exercise services for this group in the tele-health era.

Older adults' perceptions and experiences of engaging in web- and mobile-based physical activity interventions: A systematic review and qualitative meta-synthesis

BACKGROUND

Web- and mobile-based physical activity interventions effectively promote physical and mental health among older adults, but participation and adherence are suboptimal.

METHODS

This qualitative review used the mega-aggregation approach. Searches were conducted in five databases from the earliest to November 2023. Quality assessment and data extraction used JBI tools. Data synthesis used the COM-B model as a guide.

RESULTS

Sixteen sub-themes were identified from the eight studies and categorized into the COM-B model. Sub‑themes were physical and psychological changes, digital skills and knowledge, older adult-friendly design, integration into daily routines, social influence, family engagement and support, health benefits and impairments, accessibility and flexibility, low cost, visibility and interaction, instructions and feedback, personalization and progression, incentives, self-efficacy, visual cues, self-monitoring.

DISCUSSION

Web- and mobile-based interventions motivate older adults to engage in physical activity, but modifications are necessary. This includes age-appropriate interfaces and contents, tailored behavioral change techniques, and family engagement.

A social media game to increase physical activity among older adult women: protocol of a randomized controlled trial to evaluate CHALLENGE

BACKGROUND

Older adult women often do not engage in sufficient physical activity (PA) and can encounter biological changes that exacerbate the negative effects of inadequate activity. Wearable activity monitors can facilitate PA initiation, but evidence of sustained behavior change is lacking. Supplementing wearable technologies with intervention content that evokes enjoyment, interest, meaning, and personal values associated with PA may support long term adherence. In this paper, we present the protocol of an NIA-funded study designed to evaluate the efficacy of CHALLENGE for increasing step count and motivation for PA in insufficiently active older women (Challenges for Healthy Aging: Leveraging Limits for Engaging Networked Game-based Exercise). CHALLENGE uses social media to supplement wearable activity monitors with the autonomy-supportive frame of a game. We hypothesize that CHALLENGE will engender playful experiences that will improve motivation for exercise and lead to sustained increases in step count.

METHODS

We will recruit 300 healthy, community dwelling older adult women on a rolling basis and randomize them to receive either the CHALLENGE intervention (experimental arm) or an activity monitor-only intervention (comparison arm). Participants in both groups will receive a wearable activity monitor and personalized weekly feedback emails. In the experimental group, participants will also be added to a private Facebook group, where study staff will post weekly challenges that are designed to elicit playful experiences while walking. Assessments at baseline and 6, 12, and 18 months will measure PA and motivation-related constructs. We will fit linear mixed-effects models to evaluate differences in step count and motivational constructs, and longitudinal mediation models to evaluate if interventional effects are mediated by changes in motivation. We will also conduct thematic content analysis of text and photos posted to Facebook and transcripts from individual interviews.

DISCUSSION

By taking part in a year-long intervention centered on imbuing walking behaviors with playful and celebratory experiences, participating older adult women may internalize changes to their identity and relationship with PA that facilitate sustained behavior change. Study results will have implications for how we can harness powerful and increasingly ubiquitous technologies for health promotion to the vast and growing population of older adults in the U.S. and abroad.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT04095923. Registered September 17th, 2019.

The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults

This study aimed to assess the moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults. In the Active for Life trial, 243 inactive adults aged 65+ years were randomised into: (1) tailoring + Fitbit (n = 78), (2) tailoring-only (n = 96) or (3) control (n = 69). For the current study, participants were categorised as having higher (n = 146) or lower (n = 97) social support based on the Duke Social Support Index (DSSI_10). Moderate-to-vigorous physical activity (MVPA) was measured through accelerometers at baseline and post-intervention. A linear mixed model analysis demonstrated that among participants with lower social support, the tailoring + Fitbit participants, but not the tailoring only participants increased their MVPA more than the control. Among participants with higher social support, no differences in MVPA changes were observed between groups. Web-based computer-tailored interventions with Fitbit integration may be more effective in older adults with lower levels of social support.

The association of technology acceptance and physical activity on frailty in older adults during the COVID-19 pandemic period

BACKGROUND

Physical activity was known to be the protective factor against frailty. Technology acceptance is associated with behavioural intention to technology usage. Technology has been effective in promoting healthy behaviour of physical activity. The purposes of this study were to examine the association between physical activity and technology acceptance with frailty and examine the moderation effect of technology acceptance on physical activity and frailty. We hypothesize that 1) physical activity and technology acceptance are associated with frailty, and 2) technology acceptance moderates the association of physical activity with frailty.

METHODS

This study employed a cross-sectional design and was conducted in the community settings of Hong Kong in 2021. Eligible participants were old people aged ≥60 and were community-dwelling. Key variables included physical activity measured by Rapid Assessment of Physical Activity (RAPA), social network measured by Lubben Social Network Scale-Six items (LSNS-6); depressive symptoms measured by Patient Health Questionnaire-Nine items (PHQ-9), technology acceptance measured by Senior Technology Acceptance Model-14 items (STAM-14) and frailty measured by Fatigue, Resistance, Ambulation, Illnesses, & Loss of Weight scale (FRAIL). Ordinal logistic regression was employed to test the hypotheses. The moderation effect was examined by introducing an interaction term formed by the multiplication of an independent variable (i.e., physical activity) and a moderating variable (i.e., technology acceptance).

RESULTS

This study recruited 380 eligible participants with a mean age of 66.5 years. Technology acceptance (Beta = - 0.031, p < 0.001, Pseudo-R2 = 0.087) and physical activity (Beta = - 0.182, p = 0.003, Pseudo-R2 = 0.027) were associated with frailty in the unadjusted models. Technology acceptance (Beta = - 0.066, p < 0.001) and physical activity (Beta = - 1.192, p < 0.001) were also associated with frailty in the fully adjusted model (Pseudo-R2 = 0.352). Interaction term formed by the multiplication of technology acceptance and physical activity (Beta = 0.012, p = 0.001) was associated with frailty. Physical activity was significantly associated with frailty in the lower technology acceptance subgroup (Beta = - 0.313, p = 0.002) in the subgroup analysis. However, in the subgroup of higher technology acceptance, the association of physical activity (Beta = 0.104, p = 408) on frailty became positive but not significant.

CONCLUSIONS

This study showed that physical activity and technology acceptance were associated with frailty, and technology acceptance moderated the association of physical activity with frailty. This study recommends engaging older adults in physical activity to combat frailty preferentially in those with a lower level of technology acceptance.

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.

Using home monitoring technology to study the effects of traumatic brain injury on older multimorbid adults: protocol for a feasibility study

INTRODUCTION

The prevalence of traumatic brain injury (TBI) among older adults is increasing exponentially. The sequelae can be severe in older adults and interact with age-related conditions such as multimorbidity. Despite this, TBI research in older adults is sparse. Minder, an in-home monitoring system developed by the UK Dementia Research Institute Centre for Care Research and Technology, uses infrared sensors and a bed mat to passively collect sleep and activity data. Similar systems have been used to monitor the health of older adults living with dementia. We will assess the feasibility of using this system to study changes in the health status of older adults in the early period post-TBI.

METHODS AND ANALYSIS

The study will recruit 15 inpatients (>60 years) with a moderate-severe TBI, who will have their daily activity and sleep patterns monitored using passive and wearable sensors over 6 months. Participants will report on their health during weekly calls, which will be used to validate sensor data. Physical, functional and cognitive assessments will be conducted across the duration of the study. Activity levels and sleep patterns derived from sensor data will be calculated and visualised using activity maps. Within-participant analysis will be performed to determine if participants are deviating from their own routines. We will apply machine learning approaches to activity and sleep data to assess whether the changes in these data can predict clinical events. Qualitative analysis of interviews conducted with participants, carers and clinical staff will assess acceptability and utility of the system.

ETHICS AND DISSEMINATION

Ethical approval for this study has been granted by the London-Camberwell St Giles Research Ethics Committee (REC) (REC number: 17/LO/2066). Results will be submitted for publication in peer-reviewed journals, presented at conferences and inform the design of a larger trial assessing recovery after TBI.

The effect of m-health applications on self-care improvement in older adults: A systematic review

PARTICIPANTS

Four electronic databases were searched on March 6, 2020 including Scopus, PubMed, ISI, and Embase.

METHODS

Our search consisted of concepts of "self-care," "elderly" and "Mobile device." English journal papers and, RCTs conducted for individuals older than 60 in the last 10 years were included. A narrative approach was used to synthesize the data due to the heterogeneous nature of the data.

RESULTS

Initially, 3047 studies were obtained and finally 19 studies were identified for deep analysis. 13 outcomes were identified in m-health interventions to help older adults' self-care. Each outcome has at least one or more positive results. The psychological status and clinical outcome measures were all significantly improved.

CONCLUSION

According to the findings, it is not possible to draw a definite positive decision about the effectiveness of interventions on older adults because the measures are very diverse and have been measured with different tools. However, it might be declared that m-health interventions have one or more positive results and can be used along with other interventions to improve the health of older adults.

Engagement, acceptability, usability and satisfaction with Active for Life, a computer-tailored web-based physical activity intervention using Fitbits in older adults

BACKGROUND

Preliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with 'Active for Life,' a web-based physical activity intervention providing computer-tailored physical activity advice to older adults.

METHODS

Inactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction.

RESULTS

At post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p = .14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p = .56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p = .41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p = .003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options.

CONCLUSIONS

This study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374901.

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.

Interventions simultaneously promoting social participation and physical activity in community living older adults: A systematic review

Background

In recent years, there has been a global trend toward an increase in life expectancy and the proportion of elderly people among the population. In this regard, it becomes important to promote active and healthy aging. Physical inactivity and social isolation are both risk factors of many chronic illnesses and highly prevalent in older adults. This challenges communities to develop interventions that reduce these risk factors among elderly populations. The main aims of this study were to summarize community-based interventions that aim to simultaneously promote social participation and physical activity in older adults and to examine their effects.

Methods

We performed a systematic review based on the PRISMA standards. Literature searches were conducted in six scientific databases in July 2021. Articles were included if they had an interventional design, focused on older adults living in the community and measured social participation and physical activity as an outcome. The data were summarized narratively due to the heterogeneity of studies and the variety of outcome measures.

Results

Overall, 46 articles published in English were included. The studies were grouped in (1) interventions with main focus on physical activity promotion; (2) social activities that included a physical activity component; (3) health behavior interventions/ health education interventions; (4) multicomponent interventions; (5) environmental interventions. The majority of the reviewed studies reported positive effects of interventions on physical activity and/or social participation. No study reported negative effects. Analysis of quantitative studies showed that multicomponent interventions have great positive effects on both outcomes. In qualitative studies positive effects were found regardless of intervention type.

Conclusion

This review summarizes the evidence about the effects of community-based interventions that aim to promote social participation and physical activity in older adults. Multicomponent interventions seem to be most suitable for simultaneous promotion of physical activity and social participation. However, high variability in measurement methods used to assess both social participation and physical activity in the included studies made it difficult to compare studies and to indicate the most effective.

Systematic review registration

www.crd.york.ac.uk, identifier: PROSPERO [CRD42021268270].

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.

Translational Potential of High-Resistance Inspiratory Muscle Strength Training

Age-associated cardiovascular (CV) dysfunction increases the risk for CV diseases. Aerobic exercise training can improve CV function, but only a minority of adults meet aerobic exercise guidelines. High-resistance inspiratory muscle strength training is a time-efficient lifestyle intervention that may promote adherence and improve CV function. However, further investigation is needed to translate inspiratory muscle strength training into the public health domain.

The Effectiveness of a Computer-Tailored Web-Based Physical Activity Intervention Using Fitbit Activity Trackers in Older Adults (Active for Life): Randomized Controlled Trial

BACKGROUND

Physical activity is an integral part of healthy aging; yet, most adults aged ≥65 years are not sufficiently active. Preliminary evidence suggests that web-based interventions with computer-tailored advice and Fitbit activity trackers may be well suited for older adults.

OBJECTIVE

The aim of this study was to examine the effectiveness of Active for Life, a 12-week web-based physical activity intervention with 6 web-based modules of computer-tailored advice to increase physical activity in older Australians.

METHODS

Participants were recruited both through the web and offline and were randomly assigned to 1 of 3 trial arms: tailoring+Fitbit, tailoring only, or a wait-list control. The computer-tailored advice was based on either participants' Fitbit data (tailoring+Fitbit participants) or self-reported physical activity (tailoring-only participants). The main outcome was change in wrist-worn accelerometer (ActiGraph GT9X)-measured moderate to vigorous physical activity (MVPA) from baseline to after the intervention (week 12). The secondary outcomes were change in self-reported physical activity measured by means of the Active Australia Survey at the midintervention point (6 weeks), after the intervention (week 12), and at follow-up (week 24). Participants had a face-to-face meeting at baseline for a demonstration of the intervention and at baseline and week 12 to return the accelerometers. Generalized linear mixed model analyses were conducted with a γ distribution and log link to compare MVPA and self-reported physical activity changes over time within each trial arm and between each of the trial arms.

RESULTS

A total of 243 participants were randomly assigned to tailoring+Fitbit (n=78, 32.1%), tailoring only (n=96, 39.5%), and wait-list control (n=69, 28.4%). Attrition was 28.8% (70/243) at 6 weeks, 31.7% (77/243) at 12 weeks, and 35.4% (86/243) at 24 weeks. No significant overall time by group interaction was observed for MVPA (P=.05). There were no significant within-group changes for MVPA over time in the tailoring+Fitbit group (+3%, 95% CI -24% to 40%) or the tailoring-only group (-4%, 95% CI -24% to 30%); however, a significant decline was seen in the control group (-35%, 95% CI -52% to -11%). The tailoring+Fitbit group participants increased their MVPA 59% (95% CI 6%-138%) more than those in the control group. A significant time by group interaction was observed for self-reported physical activity (P=.02). All groups increased their self-reported physical activity from baseline to week 6, week 12, and week 24, and this increase was greater in the tailoring+Fitbit group than in the control group at 6 weeks (+61%, 95% CI 11%-133%).

CONCLUSIONS

A computer-tailored physical activity intervention with Fitbit integration resulted in improved MVPA outcomes in comparison with a control group in older adults.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12618000646246; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12618000646246.

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 (βtime=-9.37, 95% CI -18.58 to -0.16), regardless of the intervention group (WEB vs PRINT: βgroup*time=-3.76, 95% CI -13.33 to 5.82, WEB+ vs PRINT: βgroup*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.

Impact of Activity Tracker Usage in Combination with a Physical Activity Intervention on Physical and Cognitive Parameters in Healthy Adults Aged 60+: A Randomized Controlled Trial

Regular physical activity (PA) is of central importance for healthy aging and has a well-known impact on helping older adults maintain their cognitive and physical health. Thus, we aimed to compare the effectiveness of two physical activity interventions primarily conducted at home (print-based or web-based vs. web-based plus the use of an activity tracker) on cognitive and physical health parameters in older adults. Data of participants (n = 551, 60–80 years) were analyzed after being randomly allocated to a waitlist control group (CG), a web-based or print-based intervention group (IG) or a web-based intervention group that also included the use of an activity tracker (AG). Measured parameters were grip strength, endurance (two-minute step test), gait speed (four-meter walk test), cognition (Simon task; balanced integration score (BIS), reaction time and accuracy) and physical self-concept (Physical Self-Description Questionnaire (PSDQ)). We found the highest effect sizes in all measured dimensions for AG (grip strength, endurance, gait speed, reaction time, physical self-concept), followed by IG (endurance, gait speed, reaction time, physical self-concept) and CG (endurance, gait speed, BIS). Findings suggest that a combined web-based and activity tracker intervention may improve physical functions, physical self-concept, and cognition in community-dwelling older adults.

Increasing the Effectiveness of a Physical Activity Smartphone Intervention With Positive Suggestions: Randomized Controlled Trial

Background

eHealth interventions have the potential to increase the physical activity of users. However, their effectiveness varies, and they often have only short-term effects. A possible way of enhancing their effectiveness is to increase the positive outcome expectations of users by giving them positive suggestions regarding the effectiveness of the intervention. It has been shown that when individuals have positive expectations regarding various types of interventions, they tend to benefit from these interventions more.

Objective

The main objective of this web-based study is to investigate whether positive suggestions can change the expectations of participants regarding the effectiveness of a smartphone physical activity intervention and subsequently enhance the number of steps the participants take during the intervention. In addition, we study whether suggestions affect perceived app effectiveness, engagement with the app, self-reported vitality, and fatigue of the participants.

Methods

This study involved a 21-day fully automated physical activity intervention aimed at helping participants to walk more steps. The intervention was delivered via a smartphone-based app that delivered specific tasks to participants (eg, setting activity goals or looking for social support) and recorded their daily step count. Participants were randomized to either a positive suggestions group (69/133, 51.9%) or a control group (64/133, 48.1%). Positive suggestions emphasizing the effectiveness of the intervention were implemented in a web-based flyer sent to the participants before the intervention. Suggestions were repeated on days 8 and 15 of the intervention via the app.

Results

Participants significantly increased their daily step count from baseline compared with 21 days of the intervention (t₁₀₇=−8.62; P<.001) regardless of the suggestions. Participants in the positive suggestions group had more positive expectations regarding the app (B=−1.61, SE 0.47; P<.001) and higher expected engagement with the app (B=3.80, SE 0.63; P<.001) than the participants in the control group. No effects of suggestions on the step count (B=−22.05, SE 334.90; P=.95), perceived effectiveness of the app (B=0.78, SE 0.69; P=.26), engagement with the app (B=0.78, SE 0.75; P=.29), and vitality (B=0.01, SE 0.11; P=.95) were found. Positive suggestions decreased the fatigue of the participants during the 3 weeks of the intervention (B=0.11, SE 0.02; P<.001).

Conclusions

Although the suggestions did not affect the number of daily steps, they increased the positive expectations of the participants and decreased their fatigue. These results indicate that adding positive suggestions to eHealth physical activity interventions might be a promising way of influencing subjective but not objective outcomes of interventions. Future research should focus on finding ways of strengthening the suggestions, as they have the potential to boost the effectiveness of eHealth interventions.

Trial Registration

Open Science Framework 10.17605/OSF.IO/CWJES; https://osf.io/cwjes

The feasibility and acceptability of digital technology for health and wellbeing in social housing residents in Cornwall: A qualitative scoping study

Objective

The aim of this study was to explore the feasibility and acceptability of digital technology for improving health and wellbeing in social housing residents living in a deprived area in Cornwall, England.

Methods

Qualitative scoping study with focus groups and telephone interviews (23 participants in total). Focus groups and interviews were audio-recorded, transcribed verbatim and analysed thematically.

Results

Levels of use and experience with digital technology were diverse in this group, ranging from ‘willing and unable’ to ‘expert’ on a self-perceived scale. Overall, participants had positive perceptions of technology and were keen to try new technologies. Five categories of factors influencing technology use were identified: functional, physical / health, psychological and attitudinal, technology-associated barriers, and privacy, safety and security. Preferred types of digital technology were wearable activity monitors (e.g. Fitbit®), virtual assistants (e.g. Amazon Alexa) and social messaging (e.g. WhatsApp). There was a strong consensus that technology should be easy to use and should have a clear purpose. There was a need to improve awareness, knowledge and confidence in technology use and participants desired further training and support.

Conclusions

There is a need and desire to use digital technology to improve health, wellbeing and social connectedness in social housing residents in Cornwall. The findings will be used to inform a digital training and support programme for the participants of the Smartline project. This study also serves as a template for future research that seeks to scope the feasibility and acceptability of different digital interventions in similar populations.

Effectiveness of eHealth interventions for cancer-related pain, fatigue, and sleep disorders in cancer survivors: A systematic review and meta-analysis of randomized controlled trials

PURPOSE

To systematically evaluate the effects of Electronic health (eHealth) interventions on fatigue, pain, and sleep disorders in cancer survivors.

DESIGN

A systematic review and meta-analysis was conducted.

METHODS

Relevant studies were searched from five databases (MEDLINE, Embase, the Cochrane Central Register of Controlled trials, CINAHL, and PsycINFO). The comprehensive literature search was done in December 2020. Only randomized controlled trials (RCTs) that examined the effects of eHealth interventions among cancer survivors were included.

FINDINGS

Twenty-five RCTs were included. The meta-analysis showed that eHealth interventions had a positive impact on pain interference (SMD = -0.37, 95% CI: -0.54 to -0.20, p = 0.0001) and sleep disorders (SMD = -0.43, 95% CI: -0.77 to -0.08, p = 0.02) but not on pain severity or fatigue in cancer survivors. The sensitivity and subgroup analyses indicated that the pooled results were robust and reliable.

CONCLUSION

eHealth interventions are effective in improving pain interference and sleep disorders in cancer survivors. Additional high-quality RCTs are needed to test the effectiveness of eHealth interventions on fatigue, pain, and sleep disorders in cancer survivors.

CLINICAL RELEVANCE

This systematic review and meta-analysis provides evidence to offer effective and sustainable eHealth care for symptom management among cancer survivors.

Adapting Chinese Qigong Mind-Body Exercise for Healthy Aging in Older Community-Dwelling Low-income Latino Adults: Pilot Feasibility Study

BACKGROUND

Research translating the evidence for the benefit of mind-body exercise in older Latinos with limited access to community-based healthy aging programs is sparse.

OBJECTIVE

This study aimed to evaluate the feasibility of Function Improvement Exercises for Older Sedentary Community-Dwelling Latino Residents (FITxOlder), a Community Health Worker (CHW)-led, mobile technology-facilitated Chinese Qigong mind-body exercise program for healthy aging and to explore its impact on physical and cognitive function and quality of life (QoL) in older community-dwelling low-income Latino adults.

METHODS

This study was designed as a Stage 1 feasibility study to develop and pilot-test FITxOlder. In Phase 1 (Stage 1A), a working group of seniors, CHWs, and senior center staff guided the adaptation of Chinese Qigong into a healthy aging program. In Phase 2 (Stage 1B), 49 older Latino adults participated in a 3-arm controlled study to test the feasibility and preliminary effect of CHW-led FITxOlder on physical and cognitive function and QoL measures over 16 weeks.

RESULTS

Although the COVID-19 pandemic disrupted the implementation of the study protocol, we found favorable results regarding participant recruitment, retention, and fidelity of implementation. Notable findings included an 89.3% participant retention, 79.4% of the participants completed at least 70% of the weekly exercise goal, and no report of adverse events. The effects on intervention outcome measures were modest.

CONCLUSIONS

FITxOlder is feasible for promoting healthy aging in older Latino adults; future research needs to compare its feasibility with other low-impact exercise programs for healthy aging using a randomized controlled trial.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04284137; https://clinicaltrials.gov/ct2/show/NCT04284137.

The Effect of Commercial Activity Tracker Based Physical Activity Intervention on Body Composition and Cardiometabolic Health Among Recent Retirees

The REACT is a commercial activity tracker based intervention, which primarily aimed to increase physical activity. This study examines the secondary outcomes of the physical activity intervention on body composition and cardiometabolic health indicators. Overall 231 recently retired Finnish men and women [65.2 (SD 1.1) years, 83% women] took part to the study. The participants were randomized into intervention (n = 117) and control (n = 114) groups. The intervention group members used a commercial activity tracker (Polar Loop 2, Polar, Kempele, Finland) with a daily activity goal and inactivity alerts every day for 12 months. Controls received no intervention. Secondary health outcomes included body weight, fat mass, fat free mass, waist circumference, blood pressure, indicators of glucose and lipid metabolisms, and high-sensitivity C-reactive protein, and they were measured at baseline and at 12-months end point. Hierarchical linear mixed models were used to examine the differences between the groups over time, and no differences in the mean changes of the body composition and cardiometabolic health indicators between the groups were found (group*time interaction &gt;0.20 for all measures). Fat free mass, waist circumference, blood pressure, and low density lipoprotein levels decreased in both groups over the 12 months. These findings state that 1-year daily use of commercial activity tracker does not induce different cardiometabolic health effects when compared to the non-user controls among general population of recent retirees.

Current Evidence and Directions for Future Research in eHealth Physical Activity Interventions for Adults Affected by Cancer: Systematic Review

Background

Physical activity (PA) interventions can increase PA and improve well-being among adults affected by cancer; however, most adults do not meet cancer-specific PA recommendations. Lack of time, facility access, and travel distances are barriers to participation in PA interventions. eHealth technologies may address some of these barriers, serving as a viable way to promote PA behavior change in this population. However, no review from July 2018 has synthesized available evidence across eHealth and cancer types or examined the use of behavioral theory and behavior change techniques (BCTs), leaving important gaps in knowledge.

Objective

This review aims to provide a comprehensive, updated overview of evidence on eHealth PA interventions for adults with cancer by describing the current state of the literature, exploring associations between intervention characteristics and effectiveness, and identifying future research needs.

Methods

MEDLINE, Embase, CINAHL, SportDiscus, Scopus, and CENTRAL were searched for eHealth PA interventions for adults affected by cancer. Study selection and data extraction were performed in duplicate, with consultation from the senior author (NCR). BCT coding, risk of bias, and completeness of reporting were performed using standardized tools. Results were summarized via narrative synthesis and harvest plots. Weight analyses were conducted to explore the associations between intervention characteristics and effectiveness.

Results

A total of 71 articles (67 studies) involving 6655 participants (mean age 56.7 years, SD 8.2) were included. Nearly 50% (32/67) of the articles were published after July 2018. Significant postintervention PA increases were noted in 52% (35/67) of the studies, and PA maintenance was noted in 41% (5/12) of the studies that included a follow-up. Study duration, primary objectives, and eHealth modality (eg, websites, activity trackers, and SMS text messaging) varied widely. Social cognitive theory (23/67, 34%) was the most used theory. The mean number of BCTs used across the studies was 13.5 (SD 5.5), with self-monitoring, credible sources, and goal setting being used in >90% of studies. Weight analyses showed the greatest associations between increased PA levels and PA as a primary outcome (0.621), interventions using websites (0.656) or mobile apps (0.563), interventions integrating multiple behavioral theories (0.750), and interventions using BCTs of problem solving (0.657) and action planning (0.645). All studies had concerns with high risk of bias, mostly because of the risk of confounding, measurement bias, and incomplete reporting.

Conclusions

A range of eHealth PA interventions may increase PA levels among adults affected by cancer, and specific components (eg, websites, use of theory, and action planning) may be linked to greater effectiveness. However, more work is needed to ascertain and optimize effectiveness, measure long-term effects, and address concerns with bias and incomplete reporting. This evidence is required to support arguments for integrating eHealth within PA promotion in oncology.

The Effect of Consumer-based Activity Tracker Intervention on Physical Activity among Recent Retirees-An RCT Study

PURPOSE

The randomized controlled trial REACT (NCT03320746) examined the effect of a 12-month consumer-based activity tracker intervention on accelerometer-measured physical activity among recent retirees.

METHODS

Altogether 231 recently retired Finnish adults (age, 65.2 ± 1.1 yr, mean ± SD; 83% women) were randomized to intervention and control groups. Intervention participants were requested to wear a commercial wrist-worn activity tracker (Polar Loop 2; Polar, Kempele, Finland) for 12 months, to try to reach the daily activity goals shown on the tracker display, and to upload their activity data to a Web-based program every week. The control group received no intervention. Accelerometer-based outcome measurements of daily total, light physical activity (LPA), and moderate to vigorous (MVPA) physical activity were conducted at baseline and at 3-, 6-, and 12-month time points. Hierarchical linear mixed models were used to examine the differences between the groups over time. All analyses were performed by intention-to-treat principle and adjusted for wake wear time.

RESULTS

The use of a commercial activity tracker did not increase daily total activity, LPA, or MVPA over the 12-months period when compared with nonuser controls (group-time interaction, P = 0.39, 0.23, and 0.77, respectively). There was an increase in LPA over the first 6 months in both the intervention (26 min·d-1, 95% confidence interval [CI] = 13 to 39) and the control (14 min·d-1, 95% CI = 1 to 27) groups, but the difference between the groups was not significant (12 min·d-1, 95% CI = -6 to 30). In both groups, LPA decreased from 6 to 12 months.

CONCLUSION

The 12-month use of a commercial activity tracker does not appear to elicit significant changes in the daily total activity among a general population sample of recent retirees, thus highlighting the need to explore other alternatives to increase physical activity in this target group.

The Impact of a Telehealth Intervention on Activity Profiles in Older Adults during the COVID-19 Pandemic: A Pilot Study

Background: Physical inactivity during the COVID-19 pandemic is a public health concern for older adults. Telehealth presents a safe platform for conducting health-related interventions that may have additional benefits such as widespread reach. Our pilot study sought to examine how a telehealth intervention changed activity profiles in older adults during the COVID-19 pandemic. Methods: There were n = 13 adults aged 70.6 ± 4.5 years that participated in a 6 week telehealth intervention during the COVID-19 pandemic. The didactic intervention contents were shared online, and participants worked with trained interviewers over the telephone to discuss physical activity. At baseline and post-intervention, the Multimedia Activity Recall for Children and Adults examined activity profiles, while accelerometry estimated time spent sedentary and in physical activity. Results: Relative to the baseline measures, there was an 88 min/day (95% confidence interval (CI): 39, 137) increase in computer time and 36 min/day (CI: 10, 62) reduction in time spent in active transport at post-intervention. Moderate-to-vigorous physical activity participation also increased by an estimated 2 min/day (CI: −21, 26) and 12 min/week (CI: −154, 180), but this trend was not statistically significant. Conclusion: We recommend that support be provided to older adults transitioning to telehealth, especially as migration to telehealth progresses.

The Relevance of Diet, Physical Activity, Exercise, and Persuasive Technology in the Prevention and Treatment of Sarcopenic Obesity in Older Adults

The aging population faces two conditions that threaten healthy aging: high fat mass (obesity) and low muscle mass and function (sarcopenia). The combination of both-referred to as sarcopenic obesity-synergistically increases the risk of adverse health outcomes. The two conditions often co-occur because they reinforce each other and share common etiologies, including poor nutrition and inactivity. All aging people are at risk of gaining weight and losing muscle mass and could benefit from improvements in physical activity, exercise and dietary intake. one specific window of opportunity is during the transient time of retirement, as older adults already need to restructure their daily activities. It is key to change lifestyle behavior in a sustainable manner, providing scientifically proven, personalized, and acceptable principles that can be integrated in daily life. Health technologies (e.g., applications) can provide promising tools to deliver personalized and appealing lifestyle interventions to a large group of people while keeping health care costs low. Several studies show that health technologies have a strong positive effect on physical activity, exercise and dietary intake. Specifically, health technology is increasingly applied to older people, although strong evidence for long term effects in changing lifestyle behavior is generally lacking. Concluding, technology could play an important role in the highly warranted prevention of sarcopenic obesity in older adults. Although health technology seems to be a promising tool to stimulate changes in physical activity, exercise and dietary intake, studies on long lasting effects and specifically targeted on older people around the time of retirement are warranted.

Unobtrusive Sensors for the Assessment of Older Adult's Frailty: A Scoping Review

Ubiquity (devices becoming part of the context) and transparency (devices not interfering with daily activities) are very significant in healthcare monitoring applications for elders. The present study undertakes a scoping review to map the literature on sensor-based unobtrusive monitoring of older adults' frailty. We aim to determine what types of devices comply with unobtrusiveness requirements, which frailty markers have been unobtrusively assessed, which unsupervised devices have been tested, the relationships between sensor outcomes and frailty markers, and which devices can assess multiple markers. SCOPUS, PUBMED, and Web of Science were used to identify papers published 2010-2020. We selected 67 documents involving non-hospitalized older adults (65+ y.o.) and assessing frailty level or some specific frailty-marker with some sensor. Among the nine types of body worn sensors, only inertial measurement units (IMUs) on the waist and wrist-worn sensors comply with ubiquity. The former can transparently assess all variables but weight loss. Wrist-worn devices have not been tested in unsupervised conditions. Unsupervised presence detectors can predict frailty, slowness, performance, and physical activity. Waist IMUs and presence detectors are the most promising candidates for unobtrusive and unsupervised monitoring of frailty. Further research is necessary to give specific predictions of frailty level with unsupervised waist IMUs.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Tasks and responsibilities in physical activity promotion of older patients during hospitalization: A nurse perspective

Aim

To investigate how nurses perceive tasks and responsibilities in physical activity promotion of hospitalized older patients and which factors are of influence.

Design

Mixed methods sequential explanatory design.

Methods

One hundred and eight nurses participated in a questionnaire survey and 51 nurses in a subsequent in‐depth interview. Data were collected on tasks and responsibilities in physical activity promotion and their influencing factors as perceived by nurses. Quantitative data were analysed using descriptive statistics and a deductive approach with directed content analysis was used for the data from the interviews.

Results

Nurses perceived to have a dominant role in physical activity promotion of older patients during hospitalization. Ninety per cent of the nurses stated to be responsible for physical activity promotion and 32% stated to be satisfied with the actual level of physical activity of their patients. Nurses have specified to be responsible for signalling and performing physical activity promotion tasks and had final responsibility for transfers from bed to chair and promotion of daily activities. Influencing factors were low patient motivation, high workload causing priority shifts of tasks and the role of physicians.

Applying the Electronic Health Literacy Lens: Systematic Review of Electronic Health Interventions Targeted at Socially Disadvantaged Groups

BACKGROUND

Electronic health (eHealth) has the potential to improve health outcomes. However, eHealth systems need to match the eHealth literacy needs of users to be equitably adopted. Socially disadvantaged groups have lower access and skills to use technologies and are at risk of being digitally marginalized, leading to the potential widening of health disparities.

OBJECTIVE

This systematic review aims to explore the role of eHealth literacy and user involvement in developing eHealth interventions targeted at socially disadvantaged groups.

METHODS

A systematic search was conducted across 10 databases for eHealth interventions targeted at older adults, ethnic minority groups, low-income groups, low-literacy groups, and rural communities. The eHealth Literacy Framework was used to examine the eHealth literacy components of reviewed interventions. The results were analyzed using narrative synthesis.

RESULTS

A total of 51 studies reporting on the results of 48 interventions were evaluated. Most studies were targeted at older adults and ethnic minorities, with only 2 studies focusing on low-literacy groups. eHealth literacy was not considered in the development of any of the studies, and no eHealth literacy assessment was conducted. User involvement in designing interventions was limited, and eHealth intervention developmental frameworks were rarely used. Strategies to assist users in engaging with technical systems were seldom included in the interventions, and accessibility features were limited. The results of the included studies also provided inconclusive evidence on the effectiveness of eHealth interventions.

CONCLUSIONS

The findings highlight that eHealth literacy is generally overlooked in developing eHealth interventions targeted at socially disadvantaged groups, whereas evidence about the effectiveness of such interventions is limited. To ensure equal access and inclusiveness in the age of eHealth, eHealth literacy of disadvantaged groups needs to be addressed to help avoid a digital divide. This will assist the realization of recent technological advancements and, importantly, improve health equity.

Digital Technology to Deliver a Lifestyle-Integrated Exercise Intervention in Young Seniors-The PreventIT Feasibility Randomized Controlled Trial

Background: Behavioral change is the key to alter individuals' lifestyle from sedentary to active. The aim was to assess the feasibility of delivering a Lifestyle-integrated Functional Exercise programme and evaluate the delivery of the intervention by use of digital technology (eLiFE) to prevent functional decline in 61–70 year-old adults.

Methods: This multicentre, feasibility randomized controlled trial was run in three countries (Norway, Germany, and the Netherlands). Out of 7,500 potential participants, 926 seniors (12%) were screened and 180 participants randomized to eLiFE (n = 61), aLiFE (n = 59), and control group (n = 60). eLiFE participants used an application on smartphones and smartwatches while aLiFE participants used traditional paper-based versions of the same lifestyle-integrated exercise intervention. Participants were followed for 12 months, with assessments at baseline, after a 6 month active trainer-supported intervention, and after a further 6 months of unsupervised continuation of the programme.

Results: At 6 months, 87% of participants completed post-test, and 77% completed the final assessment at 12 months. Participants were willing to be part of the programme, with compliance and reported adherence relatively high. Despite small errors during start-up in the technological component, intervention delivery by use of technology appeared acceptable. No serious adverse events were related to the interventions. All groups improved regarding clinical outcomes over time, and complexity metrics show potential as outcome measure in young seniors.

Conclusion: This feasibility RCT provides evidence that an ICT-based lifestyle-integrated exercise intervention, focusing on behavioral change, is feasible and safe for young seniors.

Clinical Trial Registration:ClinicalTrials.gov, identifier: NCT03065088. Registered on 14 February 2017.

A Lower Leg Physical Activity Intervention for Individuals With Chronic Venous Leg Ulcers: Randomized Controlled Trial

BACKGROUND

Individuals with venous leg ulcers (VLUs) suffer disproportionately with multiple chronic conditions, are often physically deconditioned, and demonstrate high levels of physical inactivity.

OBJECTIVE

The primary objective of this randomized controlled trial was to establish the feasibility of a mobile health (mHealth) physical activity exercise app for individuals with VLUs to improve lower leg function.

METHODS

In a 6-week study, adults with VLUs were recruited from 2 wound centers in South Carolina, United States, and enrolled if they were aged 18 years or older with impaired functional mobility and an ankle-brachial index between 0.8 and 1.3. Participants were randomized 1:1 to receive evidence-based, phased, nonexertive physical conditioning activities for lower leg function (FOOTFIT) or FOOTFIT+ with an added patient-provider communication feature. The mHealth Conditioning Activities for Lower Leg Function app also provided automated educational and motivational messages and user reports. Foot movement on the VLU-affected leg was tracked by a Bluetooth-enabled triaxial accelerometer. The study was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to assess the feasibility of reach, adherence, acceptability, implementation, and maintenance.

RESULTS

A total of 24 patients were recruited, enrolled, and randomized in the study. Most patients reported difficulty following the protocol for exercising and using the accelerometer and mobile phone and did not use the provider contact feature. However, all patients were adherent to the 6-week exercise program more than 85% of the time for duration, whereas 33% (8/24) of patients adhered more than 85% for the frequency of performing the exercises. Across the three exercise levels, adherence did not differ between the two groups. Confidence limits around the difference in proportions ranged from -0.4 to 0.7. Providers in FOOTFIT+ were inconsistent in checking participant progress reports because of lack of time from competing work commitments. The technology became outdated quickly, making maintenance problematic. Participants said they would continue to exercise their foot and legs and liked being able to follow along with the demonstrations of each level of exercise provided through the app.

CONCLUSIONS

The findings of this study suggest that despite initial interest in using the app, several components of the program as originally designed had limited acceptability and feasibility. Future refinements should include the use of more modern technology including smaller wearable accelerometers, mobile phones or tablets with larger screens, an app designed with larger graphics, automated reporting for providers, and more engaging user features.

TRIAL REGISTRATION

ClinicalTrials.gov NTC02632695; https://clinicaltrials.gov/ct2/show/NCT02632695.

Does a Web-Based Exercise Programming System Improve Home Exercise Adherence for People With Musculoskeletal Conditions?: A Randomized Controlled Trial

OBJECTIVE

The aim of the study was to evaluate whether a web-based exercise programming system improves adherence to a home exercise program for people with musculoskeletal conditions.

DESIGN

Eligible patients with a musculoskeletal condition presenting to a physical therapist in private practice were randomized to the following: (a) control (home exercise prescribed by therapist's usual methods) or (b) intervention (home exercise prescribed using a web-based exercise programming system). The primary outcome was self-rated exercise adherence measured at week 3 via 11-point Numeric Rating Scales. Secondary outcomes were satisfaction with exercise delivery and confidence in ability to undertake prescribed exercise. Process measures were also included.

RESULTS

We enrolled 305 participants, with loss to follow-up of 14.5% (22/152) and 13.7% (21/153) in intervention and control groups, respectively. Compared with controls, the intervention group reported higher exercise adherence (mean difference Numeric Rating Scale units (95% confidence intervals): adherence overall -1.0 [-1.6 to -0.3] and regarding number of exercises in session -0.7 [-1.3 to -0.1], number of repetitions -0.8 [-1.4 to -0.2], and number of sessions -1.0 [-1.6 to -0.3]). The intervention group showed greater confidence to exercise than control, with no difference in satisfaction.

CONCLUSIONS

A web-based exercise programming system improved home exercise adherence and confidence in ability to undertake exercise, although the clinical relevance of the results needs to be established.

A narrative synthesis systematic review of digital self-monitoring interventions for middle-aged and older adults

OBJECTIVE

Self-monitoring is crucial to raise awareness for own behaviors and emotions, and thus facilitate self-management. The composition of self-monitoring within interventions, however, varies and guidelines are currently unavailable. This review aimed to provide a comprehensive overview of technology-based self-monitoring interventions that intend to improve health in middle-aged and older adults (>45 years).

METHODS

Five online databases were systematically searched and articles were independently screened. A narrative synthesis of 26 studies with 21 unique interventions was conducted. Primary focus lay on the composition of self-monitoring within interventions, including technology used, health-aspects monitored, and type of feedback provided. Secondly, the usability of/adherence to the self-monitoring treatment, intervention effects, and their sustainability were examined.

FINDINGS

Studies concentrated on middle-aged adults (mean of 51 years). Mobile technologies seem necessary to ensure flexible self-monitoring in everyday life. Social health aspects were rarely monitored. Mechanisms and the sustainability of intervention effect are understudied.

CONCLUSION

Digital self-monitoring technologies hold promise for future trials as they seem suitable to understand and support health-related self-management. Key elements including automatic and personal feedback following the blended care principle were highlighted and may guide study designs. Prospectively, research is especially needed to study sustained self-monitoring to support disease prevention and lasting lifestyle changes.

Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis

Background

High sedentary time, low physical activity (PA), and low physical fitness place older adults at increased risk of chronic diseases, functional decline, and premature mortality. Mobile health (mHealth) apps, apps that run on mobile platforms, may help promote active living.

Objective

We aimed to quantify the effect of mHealth app interventions on sedentary time, PA, and fitness in older adults.

Methods

We systematically searched five electronic databases for trials investigating the effects of mHealth app interventions on sedentary time, PA, and fitness among community-dwelling older adults aged 55 years and older. We calculated pooled standardized mean differences (SMDs) in these outcomes between the intervention and control groups after the intervention period. We performed a Cochrane risk of bias assessment and Grading of Recommendations, Assessment, Development, and Evaluation certainty assessment.

Results

Overall, six trials (486 participants, 66.7% [324/486] women; age mean 68 [SD 6] years) were included (five of these trials were included in the meta-analysis). mHealth app interventions may be associated with decreases in sedentary time (SMD=−0.49; 95% CI −1.02 to 0.03), increases in PA (506 steps/day; 95% CI −80 to 1092), and increases in fitness (SMD=0.31; 95% CI −0.09 to 0.70) in trials of 3 months or shorter and with increases in PA (753 steps/day; 95% CI −147 to 1652) in trials of 6 months or longer. Risk of bias was low for all but one study. The quality of evidence was moderate for PA and sedentary time and low for fitness.

Conclusions

mHealth app interventions have the potential to promote changes in sedentary time and PA over the short term, but the results did not achieve statistical significance, possibly because studies were underpowered by small participant numbers. We highlight a need for larger trials with longer follow-up to clarify if apps deliver sustained clinically important effects.

Effects of two web-based interventions promoting physical activity among older adults compared to a delayed intervention control group in Northwestern Germany: Results of the PROMOTE community-based intervention trial

Regular physical activity (PA) is of central importance for healthy ageing. However, in Germany, only 42% of older adults currently reach the PA recommendations of the World Health Organization. The aim of this study was to examine the effects of two web-based interventions on PA in adults aged 65-75 years living in Northwestern Germany compared to a delayed intervention control group (CG). 589 older adults were randomized to one of the three groups. Participants in intervention group 1 (IG1) received access to a web-based intervention for ten weeks assisting them in self-tracking PA behavior. Participants in IG2 received the intervention of IG1 and additionally an activity tracker to objectively track PA behavior. To analyze differences in objectively measured moderate-to-vigorous PA and sedentary time between baseline and follow-up (12 weeks after baseline), linear mixed models were used. The interaction effects revealed a decrease in minutes spent on moderate-to-vigorous PA in bouts of 10 min by 11 min per week in IG1 participants (β = -11.08, 95% CI: (-35.03; 12.87)). In comparison, IG2 participants were 7 min more physically active at follow-up (β = 7.48, 95% CI: (-17.64; 32.60)). Sedentary time in bouts of 30 min per week increased in IG1 participants (β = 106.77, 95% CI: (-47.69; 261.23)) and decreased in IG2 participants at follow-up (β = -16.45, 95% CI: (-178.83; 145.94)). Participation in the two web-based interventions did not lead to significant increases in moderate-to-vigorous PA or significant decreases in sedentary time compared to the CG. The study was registered at the German Clinical Trials Register (DRKS00010052, 07-11-2016).

Validity of pervasive computing based continuous physical activity assessment in community-dwelling old and oldest-old

In older adults, physical activity is crucial for healthy aging and associated with numerous health indicators and outcomes. Regular assessments of physical activity can help detect early health-related changes and manage physical activity targeted interventions. The quantification of physical activity, however, is difficult as commonly used self-reported measures are biased and rather unprecise point in time measurements. Modern alternatives are commonly based on wearable technologies which are accurate but suffer from usability and compliance issues. In this study, we assessed the potential of an unobtrusive ambient-sensor based system for continuous, long-term physical activity quantification. Towards this goal, we analysed one year of longitudinal sensor- and medical-records stemming from thirteen community-dwelling old and oldest old subjects. Based on the sensor data the daily number of room-transitions as well as the raw sensor activity were calculated. We did find the number of room-transitions, and to some degree also the raw sensor activity, to capture numerous known associations of physical activity with cognitive, well-being and motor health indicators and outcomes. The results of this study indicate that such low-cost unobtrusive ambient-sensor systems can provide an adequate approximation of older adults’ overall physical activity, sufficient to capture relevant associations with health indicators and outcomes.

Factors influencing physical activity participation among older people with low activity levels

Despite the well-documented health benefits of physical activity in older adults, participation levels remain low. With rapid global population ageing, intensive efforts are needed to encourage higher levels of participation to ameliorate the negative effects of physical inactivity for older individuals and society as a whole. The aim of this qualitative study was to inform future physical activity promotion interventions by examining factors contributing to low activity levels among older people undertaking less than half the recommended level of moderate-to-vigorous physical activity (MVPA). Semi-structured interviews were conducted with 102 (65% female) community-dwelling Western Australians aged 60+ years (mean = 71.52, standard deviation = 6.26) who engaged in ⩽75 minutes of MVPA per week as measured by accelerometers. Several modifiable and unmodifiable barriers were identified, of which poor health featured most prominently. Lifetime physical inactivity, caring duties, low motivation, misperceptions of physical activity and ageing, and a lack of affordable and attractive options were the other barriers identified. The results suggest that strategies are needed to raise awareness of current physical activity guidelines, normalise engagement in MVPA throughout the lifespan, develop initiatives to motivate participation, improve the availability of affordable physical activity programmes that are attractive to this population segment, and facilitate participation among those with intensive caring responsibilities.