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Int J Behav Nutr Phys Act. 2017 Aug 11;14(1):105. doi: 10.1186/s12966-017-0561-4.

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

Author information

1
, Shore Rd, Newtownabbey, BT37 0QB, Northern Ireland. stephenson-a@email.ulster.ac.uk.
2
Centre for Health and Rehabilitation Technologies, Institute of Nursing and Health Research, Faculty of Life and Health Sciences, Ulster University, Shore Rd, Newtownabbey, BT37 0QB, Northern Ireland.
3
UKCRC Centre of Excellence for Public Health (Northern Ireland), Belfast, Northern Ireland.
4
School of Physiotherapy, University of Otago, Dunedin, New Zealand.
5
, Shore Rd, Newtownabbey, BT37 0QB, Northern Ireland.
6
Computer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Shore Rd, Newtownabbey, BT37 0QB, Northern Ireland.

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.

KEYWORDS:

Behaviour change; Digital technology; Randomised-controlled trials; Sedentary behaviour; Systematic review

PMID:
28800736
PMCID:
PMC5553917
DOI:
10.1186/s12966-017-0561-4
[Indexed for MEDLINE]
Free PMC Article

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