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Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis

Murphy, MH, McDonough, S M, Nugent, Chris and Mair, Jacqueline L. (2017) Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis. In: 3rd UCL Centre for Behaviour Change Digital Health Conference 2017: Harnessing digital technology for behaviour change, London. Frontiers. 1 pp. [Conference contribution]

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URL: http://www.frontiersin.org/10.3389/conf.FPUBH.2017.03.00033/4089/3rd_UCL_Centre_for_Behaviour_Change_Digital_Health_Conference_2017_Harnessing_digital_technology_fo/all_events/event_abstract

Abstract

Rationale: High levels of sedentary behavior (SB) are strongly associated with several negative health consequences (1). Technologies such as mobile applications (apps), wearable activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. Systematic reviews have not explored the effectiveness of computer, mobile and wearable technology to reduce SB and there is little information regarding the behavior change techniques (BCTs) they contain.Aims: The aim of this systematic review and meta-analysis is to critically evaluate the effectiveness of computer based, mobile and wearable technology interventions targeting SB reduction in healthy adults and to examine the BCTs used. Methodology: Electronic databases (PubMed; MEDLINE; EMBASE; CINAHL; PsycINFO) were searched using predefined search strategies to identify randomised-controlled trials (RCTs) published up to June 2016. Included studies required a control or active comparator group and a pre-post measure of SB. Studies were screened for inclusion and data were extracted. Risk of bias was assessed using the Cochrane Collaboration’s tool for assessing risk of bias in randomised trials (2). Interventions were coded using the BCT taxonomy (v1) (3). Analysis: Where more than one measure of SB was available, objective data was given priority over subjective data. Mean differences and standard deviation (SD) of sedentary time, (min/d) was extracted from SB interventions and controls to permit a random effects meta-analysis. Sensitivity analysis was not possible. Results: 32048 papers (17676 after duplicate removal) were identified from which 17 were included. A variety of computer, mobile and wearable technologies were including, websites (n=7), software prompts (n=6), emails, (n=6), activity monitors (n=3), e-coaching (n = 1) and mobile apps (n=1). Ten studies focused on work place sitting, while seven targeted overall daily SB. Meta-analysis of 15 studies suggested that computer, mobile and wearable technology interventions effectively reduced sitting time by 41.28 min/day (95% CI -60.99, -21.58, n=1402) at end point follow up in favour of the intervention group. Work place interventions reduced SB by 39.88 min/work day (95% CI -59.58, -20.18, 8 studies, n=762) participants and overall daily interventions reduced SB by 45.11 mins/day (95% CI -86.63, -3.60, 7 studies, n=640) favouring the intervention group. Intervention duration ranged from a once off interaction to 24 months. 14 studies were at high risk of bias, two at unclear risk and one low risk of bias. The interventions reported the use of 25 different BCTs (four to 15 per study). 16 studies used behavior substitution. Prompts and cues, and habit reversal, were both utilised in 13 studies. Conclusion: A range of behaviour change techniques were used including behaviour substitution, prompts and cues, and habit reversal. Although computer based, mobile and wearable technology appear to be promising approaches to reduce SB, this finding should be interpreted with caution as the majority of studies were at a high risk of bias.

Item Type:Conference contribution (Poster)
Keywords:sedentary behaviour, computer, mobile, wearable technology, behaviour change
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Life and Health Sciences > School of Sport
Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Health Sciences
Research Institutes and Groups:Institute of Nursing and Health Research > Centre for Health and Rehabilitation Technologies
Institute of Nursing and Health Research
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Sport and Exercise Sciences Research Institute
Sport and Exercise Sciences Research Institute > Centre for Physical Activity and Health
ID Code:37089
Deposited By: Dr Jacqueline Mair
Deposited On:07 Mar 2017 09:54
Last Modified:07 Mar 2017 09:54

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