Changes in Self-Reported Health and Psychosocial Outcomes in Older Adults Enrolled in Sedentary Behavior Intervention Study

Assessing the Effectiveness of eHealth Interventions to Manage Multiple Lifestyle Risk Behaviors Among Older Adults: Systematic Review and Meta-Analysis

BACKGROUND

Developing adverse lifestyle behaviors increases the risk of a variety of chronic age-related diseases, including cardiovascular disease, obesity, and Alzheimer disease. There is limited evidence regarding the effectiveness of eHealth-based multiple health behavior change (MHBC) interventions to manage lifestyle risk behaviors.

OBJECTIVE

The purpose of this systematic evaluation was to assess the effectiveness of eHealth MHBC interventions in changing ≥2 major lifestyle risk behaviors in people aged ≥50 years.

METHODS

The literature search was conducted in 6 electronic databases-PubMed, Embase, Web of Science, Scopus, Cochrane Library, and SPORTDiscus-from inception to May 1, 2024. Eligible studies were randomized controlled trials of eHealth interventions targeting ≥2 of 6 behaviors of interest: alcohol use, smoking, diet, physical activity (PA), sedentary behavior, and sleep.

RESULTS

A total of 34 articles with 35 studies were included. eHealth-based MHBC interventions significantly increased smoking cessation rates (odds ratio 2.09, 95% CI 1.62-2.70; P<.001), fruit intake (standardized mean difference [SMD] 0.18, 95% CI 0.04-0.32; P=.01), vegetable intake (SMD 0.17, 95% CI 0.05-0.28; P=.003), self-reported total PA (SMD 0.22, 95% CI 0.02-0.43; P=.03), and objectively measured moderate to vigorous PA (SMD 0.25, 95% CI 0.09-0.41; P=.002); in addition, the interventions decreased fat intake (SMD -0.23, 95% CI -0.33 to -0.13; P<.001). No effects were observed for alcohol use, sedentary behavior, or sleep. A sensitivity analysis was conducted to test the robustness of the pooled results. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework.

CONCLUSIONS

eHealth-based MHBC interventions may be a promising strategy to increase PA, improve diet, and reduce smoking among older adults. However, the effect sizes were small. Further high-quality, older adult-oriented research is needed to develop eHealth interventions that can change multiple behaviors.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42023444418; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023444418.

Predictors of Mental Health Outcomes in a Multidisciplinary Weight Management Program for Class 3 Obesity

This study aimed to examine the potential predictors of improvement in mental health outcomes following participation in an intensive non-surgical outpatient weight management program (WMP) in an Australian public hospital. This was a retrospective cohort study of all adults with Class 3 obesity (BMI ≥ 40 kg/m2) who enrolled in the WMP from March 2018 to June 2021. The participants completed the Eating Disorder Examination Questionnaire Short Version (EDE-QS), Kessler-10 Psychological Distress Scale, and 36-Item Short-Form Survey (SF-36) at baseline and 12-month follow-up. A total of 115 patients completed 12 months in the WMP and were included in the study, with 76.5% being female, a mean ± SD age at baseline of 51.3 ± 13.8 years, a weight of 146 ± 26 kg, and a BMI of 51.1 ± 8.6 kg/m2. The participants lost an average of 8.6 ± 0.2 kg over 12 months, and greater weight loss at follow-up was significantly associated with improved global EDE-QS scores, psychological distress, and improved mental health quality of life. However, improvements in most mental health outcomes were not predicted by weight loss alone. Notably, a lower eating disorder risk at baseline was associated with less psychological distress at follow-up and greater weight loss at follow-up. Our results also found an association between reduced psychological distress and reduced binge eating frequency. These findings support the inclusion components of obesity interventions that target the psychological correlates of obesity to support improved outcomes in people with Class 3 obesity. Future studies should aim to identify which aspects of the WMP helped improve people's psychological outcomes.

Digital interventions to reduce social isolation and loneliness in older adults: An evidence and gap map

Background

Social isolation and loneliness are more common in older adults and are associated with a serious impact on their well-being, mental health, physical health, and longevity. They are a public health concern highlighted by the COVID-19 pandemic restrictions, hence the need for digital technology tools to enable remotely delivered interventions to alleviate the impact of social isolation and loneliness during the COVID-19 restrictions.

Objectives

To map available evidence on the effects of digital interventions to mitigate social isolation and/or loneliness in older adults in all settings except hospital settings.

Search Methods

We searched the following databases from inception to May 16, 2021, with no language restrictions. Ovid MEDLINE, Embase, APA PsycInfo via Ovid, CINAHL via EBSCO, Web of Science via Clarivate, ProQuest (all databases), International Bibliography of the Social Sciences (IBSS) via ProQuest, EBSCO (all databases except CINAHL), Global Index Medicus, and Epistemonikos.

Selection Criteria

Titles and abstracts and full text of potentially eligible articles were independently screened in duplicate following the eligibility criteria.

Data Collection and Analysis

We developed and pilot tested a data extraction code set in Eppi-Reviewer and data were individually extracted and coded based on an intervention-outcome framework which was also used to define the dimensions of the evidence and gap map.

Main Results

We included 200 articles (103 primary studies and 97 systematic reviews) that assessed the effects of digital interventions to reduce social isolation and/or loneliness in older adults. Most of the systematic reviews (72%) were classified as critically low quality, only 2% as high quality and 25% were published since the COVID-19 pandemic. The evidence is unevenly distributed with clusters predominantly in high-income countries and none in low-income countries. The most common interventions identified are digital interventions to enhance social interactions with family and friends and the community via videoconferencing and telephone calls. Digital interventions to enhance social support, particularly socially assistive robots, and virtual pets were also common. Most interventions focused on reducing loneliness and depression and improving quality of life of older adults. Major gaps were identified in community level outcomes and process indicators. No included studies or reviews assessed affordability or digital divide although the value of accessibility and barriers caused by digital divide were discussed in three primary studies and three reviews. Adverse effects were reported in only two studies and six reviews. No study or review included participants from the LGBTQIA2S+ community and only one study restricted participants to 80 years and older. Very few described how at-risk populations were recruited or conducted any equity analysis to assess differences in effects for populations experiencing inequities across PROGRESS-Plus categories.

Authors' Conclusions

The restrictions placed on people during the pandemic have shone a spotlight onto social isolation and loneliness, particularly for older adults. This evidence and gap map shows available evidence on the effectiveness of digital interventions for reducing social isolation or loneliness in older adults. Although the evidence is relatively large and recent, it is unevenly distributed and there is need for more high-quality research. This map can guide researchers and funders to consider areas of major gaps as priorities for further research.

Physical Activity and Cognition in Sedentary Older Adults: A Systematic Review and Meta-Analysis

Background:

Epidemiologic evidence suggests that physical activity benefits cognition, but results from randomized trials in sedentary individuals are limited and inconsistent.

Objective:

To evaluate the effects of physical activity on cognition among sedentary older adults.

Objective:

A systematic literature search for eligible studies published up to January 1, 2021, was performed on six international (PubMed, Cochrane Library, Web of Science, Sinomed, FMRS, and OVID) and three Chinese databases (Wanfang, China National Knowledge Infrastructure, and VIP). We estimated the effect of physical activity on the cognition of sedentary elderly by standardized mean differences (SMD) and 95% confidence intervals (CI) using a random-effects model. We evaluated publication bias using funnel plots and heterogeneity using I² statistics. Subgroup analyses were conducted by baseline cognition, intervention duration, activity type, and country.

Results:

Seven randomized controlled trials (RCTs) comprising 321 (experimental group, 164; control group, 157) sedentary older adults were included in the meta-analysis. Physical activity significantly improved cognition in sedentary elderly adults compared with controls (SMD: 0.50, 95% CI:0.09–0.92). Subgroup analyses showed significant effects of baseline cognition impairment (SMD: 9.80, 95% CI: 5.81–13.80), intervention duration > 12 weeks (SMD: 2.85, 95% CI: 0.73–4.96), aerobic exercise (SMD: 0.74, CI: 0.19–1.29), and countries other than the United States (SMD: 10.50, 95% CI: 7.08–13.92).

Conclusion:

Physical activity might have a general positive effect on the cognition of sedentary older adults. Intervention > 12 weeks and aerobic exercise can effectively delay their cognitive decline; however, more rigorous RCTs are needed to support our findings.

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.

Protocol for a randomized controlled trial of sitting reduction to improve cardiometabolic health in older adults

Older adults with obesity spend the majority of their waking hours sedentary. Given substantial barriers to regular physical activity in this population, approaches to reduce sedentary time could be an effective health promotion strategy. We present the protocol of a randomized controlled trial to reduce sitting time in older adults with a body mass index of 30 kg/m² or above. Participants (N = 284) will be randomized to receive a sitting reduction intervention (termed I-STAND) or a healthy living focused attention control condition. I-STAND includes 10 contacts with a health coach (10 sessions total) and participants receive a wrist-worn prompting device and portable standing desk. The healthy living condition includes 10 sessions with a health coach to set goals around various topics relating to healthy aging. Participants receive their assigned intervention for 6 months. After 6 months, those receiving the I-STAND condition are re-randomized to receive five booster health coaching sessions by 'phone or no further contact; healthy living participants receive no further contact and those in both conditions are followed for an additional 6 months. Measurements initially included wearing an activPAL device and completing several biometric tests (e.g., blood pressure, HbA1c), at baseline, 3 months, 6 months, and 12 months; however, during the COVID-19 pandemic we shifted to remote assessments and were unable to collect all of these measures. The primary outcomes remained activPAL-assessed sitting time and blood pressure. Recruitment is anticipated to be completed in 2022.

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.

A Home-Based Mobile Health Intervention to Replace Sedentary Time With Light Physical Activity in Older Cancer Survivors: Randomized Controlled Pilot Trial

Background

Older cancer survivors are at risk of the development or worsening of both age- and treatment-related morbidity. Sedentary behavior increases the risk of or exacerbates these chronic conditions. Light-intensity physical activity (LPA) is more common in older adults and is associated with better health and well-being. Thus, replacing sedentary time with LPA may provide a more successful strategy to reduce sedentary time and increase physical activity.

Objective

This study primarily aims to evaluate the feasibility, acceptability, and preliminary efficacy of a home-based mobile health (mHealth) intervention to interrupt and replace sedentary time with LPA (standing and stepping). The secondary objective of this study is to examine changes in objective measures of physical activity, physical performance, and self-reported quality of life.

Methods

Overall, 54 cancer survivors (aged 60-84 years) were randomized in a 1:1:1 allocation to the tech support intervention group, tech support plus health coaching intervention group, or waitlist control group. Intervention participants received a Jawbone UP2 activity monitor for use with their smartphone app for 13 weeks. Tech support and health coaching were provided via 5 telephone calls during the 13-week intervention. Sedentary behavior and physical activity were objectively measured using an activPAL monitor for 7 days before and after the intervention.

Results

Participants included survivors of breast cancer (21/54, 39%), prostate cancer (16/54, 30%), and a variety of other cancer types; a mean of 4.4 years (SD 1.6) had passed since their cancer diagnosis. Participants, on average, were 70 years old (SD 4.8), 55% (30/54) female, 24% (13/54) Hispanic, and 81% (44/54) overweight or obese. Malfunction of the Jawbone trackers occurred in one-third of the intervention group, resulting in enrollment stopping at 54 rather than the initial goal of 60 participants. Despite these technical issues, the retention in the intervention was high (47/54, 87%). Adherence was high for wearing the tracker (29/29, 100%) and checking the app daily (28/29, 96%) but low for specific aspects related to the sedentary features of the tracker and app (21%-25%). The acceptability of the intervention was moderately high (81%). There were no significant between-group differences in total sedentary time, number of breaks, or number of prolonged sedentary bouts. There were no significant between-group differences in physical activity. The only significant within-group change occurred within the health coaching group, which increased by 1675 daily steps (95% CI 444-2906; P=.009). This increase was caused by moderate-intensity stepping rather than light-intensity stepping (+15.2 minutes per day; 95% CI 4.1-26.2; P=.008).

Conclusions

A home-based mHealth program to disrupt and replace sedentary time with stepping was feasible among and acceptable to older cancer survivors. Future studies are needed to evaluate the optimal approach for replacing sedentary behavior with standing and/or physical activity in this population.

Trial Registration

ClinicalTrials.gov NCT03632694; https://clinicaltrials.gov/ct2/show/NCT03632694

The Effects of Displacing Sedentary Behavior With Two Distinct Patterns of Light Activity on Health Outcomes in Older Adults (Implications for COVID-19 Quarantine)

Rationale: The COVID-19 pandemic is limiting outdoor and community-based activities, especially for older adults owing to the requirement for self-isolation, potentially increasing prolonged sedentary behavior (SB). Given a poor tolerance for intense exercise, SB displacement with light intensity physical activity (LIPA) is a promising health enhancing alternative. Therefore, the aims of this study were to investigate the effects of two different types of SB displacement on health outcomes in older adults and any differential impact of associated LIPA pattern.

Method: 28 older women (age: 73 ± 5 years, height: 1.60 ± 0.07 m, weight: 67 ± 10 kg, and BMI: 26.1 ± 3.6 kg/m²) underwent overnight fasted dual energy x-ray absorptiometry (DEXA) imaging, blood sampling, and functional assessments before being randomly allocated to one of two groups: (1) single continuous bout of 45–50 min LIPA daily (n = 14); or (2) SB fragmentation (SBF; ~48 min LIPA daily, 2 min LIPA for every 30 min of SB; n = 14). Compliance was systematically monitored using tri-axial accelerometery. All measures were taken at weeks 0 and 8.

Results: Physical behavior significantly altered (decreased SB/increased LIPA; p < 0.05) and to a similar extent in both groups. We observed a significant reduction in serum triglycerides [p = 0.045, effect size (ɳ_p²) = 0.15; SBF: −0.26 ± 0.77 mmol/L, LIPA: −0.26 ± 0.51 mmol/L], improved 30 s sit-to-stand (STS) count (p = 0.002, ɳ_p² = 0.32, 2 ± 3 STS) and speed (p = 0.009, ɳ_p² = 0.35, −10 ± 33%), as well as increased average handgrip strength (p = 0.001, ɳ_p² = 0.45, 6 ± 12%), and gait speed (p = 0.005, ɳ_p² = 0.27, 0.09 ± 0.16 m/s) in both groups. Interestingly, SBF caused a greater increase in peak handgrip strength (8 ± 14%), compared to LIPA (2 ± 10%; p = 0.04, ɳ_p² = 0.38).

Conclusion: SB displacement induced significant improvements in fasting triglycerides, gait speed, as-well as STS endurance/speed in older women. Frequent vs. continuous SB displacement also caused greater increases in handgrip strength. While both SB displacement protocols display promise as efficacious home-based interventions for self-isolating older adults, our results would suggest a physical functioning advantage of the SBF protocol for certain outcomes.

Enabling Older Adults' Health Self-Management through Self-Report and Visualization-A Systematic Literature Review

Aging is associated with a progressive decline in health, resulting in increased medical care and costs. Mobile technology may facilitate health self-management, thus increasing the quality of care and reducing costs. Although the development of technology offers opportunities in monitoring the health of older adults, it is not clear whether these technologies allow older adults to manage their health data themselves. This paper presents a review of the literature on mobile health technologies for older adults, focusing on whether these technologies enable the visualization of monitored data and the self-reporting of additional information by the older adults. The systematic search considered studies published between 2009 and 2019 in five online databases. We screened 609 articles and identified 95 that met our inclusion and exclusion criteria. Smartphones and tablets are the most frequently reported technology for older adults to enter additional data to the one that is monitored automatically. The recorded information is displayed on the monitoring device and screens of external devices such as computers. Future designs of mobile health technology should allow older users to enter additional information and visualize data; this could enable them to understand their own data as well as improve their experience with technology.