Cited by 291Physical Activity and HealthMobile Health and mHealth ApplicationsContext-Aware Activity Recognition Systems

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Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis

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Stephenson, Aoife, McDonough, Suzanne M., Murphy, Marie H., Nugent, Chris D., Mair, Jacqueline L.·2017·International Journal of Behavioral Nutrition and Physical Activity

DOI 10.1186/s12966-017-0561-4PMC PMC5553917

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Abstract

BACKGROUND: High levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. The aim of this paper is to evaluate the effectiveness of such technology enhanced interventions aimed at reducing SB in healthy adults and to examine the behaviour change techniques (BCTs) used. METHODS: Five electronic databases were searched to identify randomised-controlled trials (RCTs), published up to June 2016. Interventions using computer, mobile or wearable technologies to facilitate a reduction in SB, using a measure of sedentary time as an outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Collaboration's tool and interventions were coded using the BCT Taxonomy (v1). RESULTS: Meta-analysis of 15/17 RCTs suggested that computer, mobile and wearable technology tools resulted in a mean reduction of -41.28 min per day (min/day) of sitting time (95% CI -60.99, -21.58, I2 = 77%, n = 1402), in favour of the intervention group at end point follow-up. The pooled effects showed mean reductions at short (≤ 3 months), medium (>3 to 6 months), and long-term follow-up (>6 months) of -42.42 min/day, -37.23 min/day and -1.65 min/day, respectively. Overall, 16/17 studies were deemed as having a high or unclear risk of bias, and 1/17 was judged to be at a low risk of bias. A total of 46 BCTs (14 unique) were coded for the computer, mobile and wearable components of the interventions. The most frequently coded were "prompts and cues", "self-monitoring of behaviour", "social support (unspecified)" and "goal setting (behaviour)". CONCLUSION: Interventions using computer, mobile and wearable technologies can be effective in reducing SB. Effectiveness appeared most prominent in the short-term and lessened over time. A range of BCTs have been implemented in these interventions. Future studies need to improve reporting of BCTs within interventions and address the methodological flaws identified within the review through the use of more rigorously controlled study designs with longer-term follow-ups, objective measures of SB and the incorporation of strategies to reduce attrition. TRIAL REGISTRATION: The review protocol was registered with PROSPERO: CRD42016038187.

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Fig. 1 PRISMA flow diagramCC BY · PubMed Central

Fig. 2 Risk of bias graphCC BY · PubMed Central

Fig. 3 Risk of bias summaryCC BY · PubMed Central

Fig. 4 Effects of intervention versus control on SBCC BY · PubMed Central

Fig. 5 Effects of workplace intervention versus control on workplace SB- short medium and long-termCC BY · PubMed Central

Fig. 6 Effects of overall daily SB interventions versus control on daily SB- short, medium and long-termCC BY · PubMed Central

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Authors: Stephenson, A., McDonough, S. M., Murphy, M. H., Nugent, C. D., & Mair, J. L.
Affiliations: University of Ulster (GB)
Corresponding author: Stephenson, Aoife
ORCID: Stephenson, Aoife
McDonough, Suzanne M.
Murphy, Marie H.
Nugent, Chris D.
Mair, Jacqueline L.
Venue: International Journal of Behavioral Nutrition and Physical Activity
Publisher: Springer Science and Business Media LLC
Published: 2017-08-11
Volume: 14
Issue: 1
Pages: 105-105
ISSN: 1479-5868 (ISSN-L)
DOI: 10.1186/s12966-017-0561-4
PMC: PMC5553917
OpenAlex: W2744204866
Cited by: 290
References: 59
Citations by year: 2026: 16 · 2025: 28 · 2024: 29 · 2023: 25 · 2022: 44 · 2021: 49 · 2020: 52 · 2019: 22 · 2018: 20 · 2017: 4
FWCI: 3.29
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: International Journal of Behavioral Nutrition and Physical Activity (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Ulster University Research Portal (Ulster University) (submittedVersion, cc-by)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Edinburgh Napier Research Repository (Edinburgh Napier University) (submittedVersion, cc-by)
Funders: Ulster University (PhD Scholarship)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords: sedentary behavior, technology-based interventions, mobile application, wearable activity trackers, computer-based intervention, behaviour change techniques, sitting time reduction, self-monitoring, prompts and cues, social support, goal setting, healthy adults, intervention effectiveness, attrition, long-term follow-up, risk of bias
MeSH terms: Wearable Electronic Devices, Health Promotion, Humans, Health Behavior, Randomized Controlled Trials as Topic, Databases, Factual, Sedentary Behavior, Mobile Applications

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Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis

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