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

The international journal of behavioral nutrition and physical activity. 2021;18(1):148
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Low physical activity levels are responsible for many non-communicable diseases and a huge cost to health services. Low socioeconomic status is associated with lower physical activity levels and therefore it is important to increase activity amongst this group of people. The use of digital technologies to increase exercise has become popular in recent years, however it is unknown whether they have differing effectiveness depending on the socioeconomic status of the user. This systematic review and meta-analysis of 19 studies aimed to determine whether digital technologies which target physical activity levels are beneficial for those from low socioeconomic status. The results showed that digital interventions targeting activity have differing effectiveness depending on the socioeconomic status, with those from high socioeconomic status benefitting from these interventions, and those from a low socioeconomic status did not. It was concluded that future technologies need to be tailored to target individuals from low socioeconomic status to improve effectiveness. This study could be used by healthcare professionals to understand that digital technologies designed to increase physical activity may not be sufficient for individuals from a low socioeconomic status and extra support and guidance may be needed.

Abstract

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.

Lifestyle medicine

Fundamental Clinical Imbalances : Hormonal ; Neurological
Patient Centred Factors : Mediators/Low socio economic status
Environmental Inputs : Psychosocial influences
Personal Lifestyle Factors : Exercise and movement
Functional Laboratory Testing : Not applicable

Methodological quality

Jadad score : Not applicable
Allocation concealment : Not applicable

Metadata

Nutrition Evidence keywords : Low socioeconomic status ; High socioeconomic status