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

MH Murphy, S M McDonough, Chris Nugent, Jacqueline L. Mair

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages1
Publication statusE-pub ahead of print - 22 Feb 2017
Event3rd UCL Centre for Behaviour Change Digital Health Conference 2017: Harnessing digital technology for behaviour change - London
Duration: 22 Feb 2017 → …

Conference

Conference3rd UCL Centre for Behaviour Change Digital Health Conference 2017: Harnessing digital technology for behaviour change
Period22/02/17 → …

Fingerprint

Meta-Analysis
Technology
Mobile Applications
Workplace
Habits
Cues
Software
Behavior Control
PubMed
MEDLINE
Randomized Controlled Trials

Keywords

  • sedentary behaviour
  • computer
  • mobile
  • wearable technology
  • behaviour change

Cite this

@inproceedings{0082aaa216dd4407a90aaf595d169642,
title = "Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis",
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.",
keywords = "sedentary behaviour, computer, mobile, wearable technology, behaviour change",
author = "MH Murphy and McDonough, {S M} and Chris Nugent and Mair, {Jacqueline L.}",
year = "2017",
month = "2",
day = "22",
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booktitle = "Unknown Host Publication",

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Murphy, MH, McDonough, SM, Nugent, C & Mair, JL 2017, Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis. in Unknown Host Publication. 3rd UCL Centre for Behaviour Change Digital Health Conference 2017: Harnessing digital technology for behaviour change, 22/02/17.

Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis. / Murphy, MH; McDonough, S M; Nugent, Chris; Mair, Jacqueline L.

Unknown Host Publication. 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Using computer, mobile and wearable technology interventions to change sedentary behaviours: a systematic review and meta-analysis

AU - Murphy, MH

AU - McDonough, S M

AU - Nugent, Chris

AU - Mair, Jacqueline L.

PY - 2017/2/22

Y1 - 2017/2/22

N2 - 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.

AB - 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.

KW - sedentary behaviour

KW - computer

KW - mobile

KW - wearable technology

KW - behaviour change

M3 - Conference contribution

BT - Unknown Host Publication

ER -