Socio-economic inequalities in the breadth of internet use before and during the COVID-19 pandemic among older adults in England.

Understanding digital exclusion in older adults during the COVID-19 pandemic could help tailor responses to future outbreaks. This cohort study used data from older adults aged 60+ years in England who participated in wave nine (2018/2019) of the main English Longitudinal Study of Ageing (ELSA) survey, and/or wave one of the ELSA COVID-19 sub-study (June/July 2020). Using latent class analysis and latent transition analysis, we aimed to identify distinct subgroups of older adults characterised by different patterns of internet use pre- and intra-pandemic, explore the extent to which individuals remained in the same subgroup or transitioned to a different subgroup during the COVID-19 pandemic, and examine longitudinal associations of socio-economic factors (education, occupational class, and wealth) with latent class membership. Preliminary tests showed that the types of internet activities differed between men and women; therefore, subsequent analyses were stratified by biological sex. Three clusters (low, medium, and high) were identified in male participants at both timepoints. Among female participants, three clusters were distinguished pre-pandemic and two (low versus high) during the pandemic. The latent classes were characterised by participants' breadth of internet use. Higher education, occupational class, and wealth were associated with greater odds of membership in the medium and/or high classes, versus the low class, in men and women. A high degree of stability in latent class membership was observed over time. However, men experienced a stark decrease in online health information-seeking. Our results highlight that inequality regarding the range of functional and social opportunities provided by the internet prevailed during the pandemic. Policymakers should ensure that digital access and upskilling initiatives are equitable for all.

Reducing intervention- and research-induced inequalities to tackle the digital divide in health promotion.

Social inequalities are an important contributor to the global burden of disease within and between countries. Using digital technology in health promotion and healthcare is seen by some as a potential lever to reduce these inequalities; however, research suggests that digital technology risks re-enacting or evening widening disparities. Most research on this digital health divide focuses on a small number of social inequality indicators and stems from Western, educated, industrialized, rich, and democratic (WEIRD) countries. There is a need for systematic, international, and interdisciplinary contextualized research on the impact of social inequality indicators in digital health as well as the underlying mechanisms of this digital divide across the globe to reduce health disparities. In June 2023, eighteen multi-disciplinary researchers representing thirteen countries from six continents came together to discuss current issues in the field of digital health promotion and healthcare contributing to the digital divide. Ways that current practices in research contribute to the digital health divide were explored, including intervention development, testing, and implementation. Based on the dialogue, we provide suggestions for overcoming barriers and improving practices across disciplines, countries, and sectors. The research community must actively advocate for system-level changes regarding policy and research to reduce the digital divide and so improve digital health for all.

Socio-economic status and trajectories of a novel multidimensional metric of Active and Healthy Ageing: the English Longitudinal Study of Ageing.

Healthy ageing research largely has a unidimensional focus on physical health, negating the importance of psychosocial factors in the maintenance of a good quality-of-life. In this cohort study, we aimed to identify trajectories of a new multidimensional metric of Active and Healthy Ageing (AHA), including their associations with socio-economic variables. A latent AHA metric was created for 14,755 participants across eight waves of data (collected between 2004 and 2019) from the English Longitudinal Study of Ageing (ELSA), using Bayesian Multilevel Item Response Theory (MLIRT). Then, Growth Mixture Modelling (GMM) was employed to identify sub-groups of individuals with similar trajectories of AHA, and multinomial logistic regression examined associations of these trajectories with socio-economic variables: education, occupational class, and wealth. Three latent classes of AHA trajectories were suggested. Participants in higher quintiles of the wealth distribution had decreased odds of being in the groups with consistently moderate AHA scores (i.e., 'moderate-stable'), or the steepest deterioration (i.e., 'decliners'), compared to the 'high-stable' group. Education and occupational class were not consistently associated with AHA trajectories. Our findings reiterate the need for more holistic measures of AHA and prevention strategies targeted at limiting socio-economic disparities in older adults' quality-of-life.

Cost-effectiveness of a physical activity and behaviour maintenance programme on functional mobility decline in older adults: an economic evaluation of the REACT (Retirement in Action) trial.

BACKGROUND: Mobility limitations in older populations have a substantial impact on health outcomes, quality of life, and social care costs. The Retirement in Action (REACT) randomised controlled trial assessed a 12-month community-based group physical activity and behaviour maintenance intervention to help prevent decline in physical functioning in older adults at increased risk of mobility limitation. We aimed to do an economic evaluation of the REACT trial to investigate whether the intervention is cost-effective. METHODS: In this health economic evaluation, we did cost-effectiveness and cost-utility analyses of the REACT programme versus standard care on the basis of resource use, primary outcome, and health-related quality-of-life data measured in the REACT trial. We also developed a decision analytic Markov model that forecasts the mobility of recipients beyond the 24-month follow-up of the trial and translated this into future costs and potential benefit to health-related quality of life using the National Health Service and Personal Social Services perspective. Participants completed questionnaire booklets at baseline, and at 6, 12, and 24 months after randomisation, which included a resource use questionnaire and the EQ-5D-5L and 36-item short-form survey (SF-36) health-related quality-of-life instruments. The cost of delivering the intervention was estimated by identifying key resources, such as REACT session leader time, time of an individual to coordinate the programme, and venue hire. EQ-5D-5L and SF-36 responses were converted to preference-based utility values, which were used to estimate quality-adjusted life-years (QALYs) over the 24-month trial follow-up using the area-under-the-curve method. We used generalised linear models to examine the effect of the REACT programme on costs and QALYs and adjust for baseline covariates. Costs and QALYs beyond 12 months were discounted at 3·5% per year. This is a pre-planned analysis of the REACT trial; the trial itself is registered with ISRCTN (ISRCTN45627165). FINDINGS: The 12-month REACT programme was estimated to cost £622 per recipient to deliver. The most substantial cost components are the REACT session leader time (£309 per participant), venue hire (£109), and the REACT coordinator time (£80). The base-case analysis of the trial-based economic evaluation showed that reductions in health and social care usage due to the REACT programme could offset the REACT delivery costs (£3943 in the intervention group vs £4043 in the control group; difference: -£103 [95% CI -£695 to £489]) with a health benefit of 0·04 QALYs (0·009-0·071; 1·354 QALYs in the intervention group vs 1·314 QALYs in the control group) within the 24-month timeframe of the trial. INTERPRETATION: The REACT programme could be considered a cost-effective approach for improving the health-related quality of life of older adults at risk of mobility limitations. FUNDING: National Institute for Health Research Public Health Research Programme.

The effectiveness of digital interventions for increasing physical activity in individuals of low socioeconomic status: a systematic review and meta-analysis.

BACKGROUND: Digital technologies such as wearables, websites and mobile applications are increasingly used in interventions targeting physical activity (PA). Increasing access to such technologies makes an attractive prospect for helping individuals of low socioeconomic status (SES) in becoming more active and healthier. However, little is known about their effectiveness in such populations. The aim of this systematic review was to explore whether digital interventions were effective in promoting PA in low SES populations, whether interventions are of equal benefit to higher SES individuals and whether the number or type of behaviour change techniques (BCTs) used in digital PA interventions was associated with intervention effects. METHODS: A systematic search strategy was used to identify eligible studies from MEDLINE, Embase, PsycINFO, Web of Science, Scopus and The Cochrane Library, published between January 1990 and March 2020. Randomised controlled trials, using digital technology as the primary intervention tool, and a control group that did not receive any digital technology-based intervention were included, provided they had a measure of PA as an outcome. Lastly, studies that did not have any measure of SES were excluded from the review. Risk of Bias was assessed using the Cochrane Risk of Bias tool version 2. RESULTS: Of the 14,589 records initially identified, 19 studies were included in the final meta-analysis. Using random-effects models, in low SES there was a standardised mean difference (SMD (95%CI)) in PA between intervention and control groups of 0.06 (- 0.08,0.20). In high SES the SMD was 0.34 (0.22,0.45). Heterogeneity was modest in both low (I2 = 0.18) and high (I2 = 0) SES groups. The studies used a range of digital technologies and BCTs in their interventions, but the main findings were consistent across all of the sub-group analyses (digital interventions with a PA only focus, country, chronic disease, and duration of intervention) and there was no association with the number or type of BCTs. DISCUSSION: Digital interventions targeting PA do not show equivalent efficacy for people of low and high SES. For people of low SES, there is no evidence that digital PA interventions are effective, irrespective of the behaviour change techniques used. In contrast, the same interventions in high SES participants do indicate effectiveness. To reduce inequalities and improve effectiveness, future development of digital interventions aimed at improving PA must make more effort to meet the needs of low SES people within the target population.

Development of the Digital Assessment of Precise Physical Activity (DAPPA) Tool for Older Adults.

Physical activity (PA) is central to maintaining health and wellbeing as we age. Valid, reliable measurement tools are vital for understanding, and evaluating PA. There are limited options for comprehensively, accurately and affordably measuring older adults' PA at scale at present. We aimed to develop a digital PA measurement tool specifically for adults aged 65+ using a person-based approach. We collated evidence from target users, field experts and the relevant literature to learn how older adults comprehend PA and would accept a digital tool. Findings suggest that older adults' PA is often integrated into their daily life activities and that commonly applied terminology (e.g., moderate and vigorous) can be difficult to interpret. We also found that there is increasing familiarity with digital platforms amongst older adults, and that technological simplicity is valued. These findings informed the development of a digital tool that asks users to report their activities across key PA domains and dimensions from the previous 7-days. Users found the tool easy to navigate and comprehensive in terms of activity reporting. However, real-world usability testing revealed that users struggled with seven-day recall. Further work will address the identified issues, including creating a single-day reporting option, before commencing work to validate this new tool.

A community-based physical activity intervention to prevent mobility-related disability for retired older people (REtirement in ACTion (REACT)): study protocol for a randomised controlled trial.

BACKGROUND: The REtirement in ACTion (REACT) study is a multi-centre, pragmatic, two-arm, parallel-group randomised controlled trial (RCT) with an internal pilot phase. It aims to test the effectiveness and cost-effectiveness of a community, group-based physical activity intervention for reducing, or reversing, the progression of functional limitations in older people who are at high risk of mobility-related disability. METHODS/DESIGN: A sample of 768 sedentary, community-dwelling, older people aged 65 years and over with functional limitations, but who are still ambulatory (scores between 4 and 9 out of 12 in the Short Physical Performance Battery test (SPPB)) will be randomised to receive either the REACT intervention, delivered over a period of 12 months by trained facilitators, or a minimal control intervention. The REACT study incorporates comprehensive process and economic evaluation and a nested sub-study which will test the hypothesis that the REACT intervention will slow the rate of brain atrophy and of decline in cognitive function assessed using magnetic resonance imaging (MRI). Outcome data will be collected at baseline, 6, 12 and 24 months for the main study, with MRI sub-study data collected at baseline, 6 and 12 months. The primary outcome analysis (SPPB score at 24 months) will be undertaken blinded to group allocation. Primary comparative analyses will be on an intention-to-treat (ITT) basis with due emphasis placed on confidence intervals. DISCUSSION: REACT represents the first large-scale, pragmatic, community-based trial in the UK to target the non-disabled but high-risk segment of the older population with an intervention to reduce mobility-related disability. A programme that can successfully engage this population in sufficient activity to improve strength, aerobic capacity, coordination and balance would have a major impact on sustaining health and independence. REACT is also the first study of its kind to conduct a full economic and comprehensive process evaluation alongside the RCT. If effective and cost-effective, the REACT intervention has strong potential to be implemented widely in the UK and elsewhere. TRIAL REGISTRATION: ISRCTN, ID: ISRCTN45627165 . Retrospectively registered on 13 June 2016. Trial sponsor: University of Bath. Protocol Version 1.5.

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors.

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

Multidimensional individualised Physical ACTivity (Mi-PACT)--a technology-enabled intervention to promote physical activity in primary care: study protocol for a randomised controlled trial.

BACKGROUND: Low physical activity is a major public health problem. New cost-effective approaches that stimulate meaningful long-term changes in physical activity are required, especially within primary care settings. It is becoming clear that there are various dimensions to physical activity with independent health benefits. Advances in technology mean that it is now possible to generate multidimensional physical activity 'profiles' that provide a more complete representation of physical activity and offer a variety of options that can be tailored to the individual. Mi-PACT is a randomised controlled trial designed to examine whether personalised multidimensional physical activity feedback and self-monitoring alongside trainer-supportive sessions increases physical activity and improves health outcomes in at-risk men and women. METHODS/DESIGN: We aim to recruit 216 patients from within primary care aged 40 to 70 years and at medium or high risk of cardiovascular disease and/or type II diabetes mellitus. Adopting an unequal allocation ratio (intervention: control) of 2:1, participants will be randomised to one of two groups, usual care or the intervention. The control group will receive usual care from their general practitioner (GP) and standardised messages about physical activity for health. The intervention group will receive physical activity monitors and access to a web-based platform for a 3-month period to enable self-monitoring and the provision of personalised feedback regarding the multidimensional nature of physical activity. In addition, this technology-enabled feedback will be discussed with participants on 5 occasions during supportive one-to-one coaching sessions across the 3-month intervention. The primary outcome measure is physical activity, which will be directly assessed using activity monitors for a 7-day period at baseline, post intervention and at 12 months. Secondary measures (at these time-points) include weight loss, fat mass, and markers of metabolic control, motivation and well-being. DISCUSSION: Results from this study will provide insight into the effects of integrated physical activity profiling and self-monitoring combined with in-person support on physical activity and health outcomes in patients at risk of future chronic disease. TRIAL REGISTRATION: ISRCTN18008011 Trial registration date: 31 July 2013.