Stephenson Aoife, McDonough Suzanne M, Murphy Marie H, Nugent Chris D, Mair Jacqueline L
, Shore Rd, Newtownabbey, BT37 0QB, Northern Ireland.
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.
Int J Behav Nutr Phys Act. 2017 Aug 11;14(1):105. doi: 10.1186/s12966-017-0561-4.
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.
背景:高水平的久坐行为(SB)与负面健康后果相关。诸如移动应用程序、活动监测器、提示软件、短信、电子邮件和网站等技术增强型解决方案正被用于减少久坐行为。本文旨在评估此类旨在减少健康成年人久坐行为的技术增强型干预措施的有效性,并研究所使用的行为改变技术(BCT)。 方法:检索了五个电子数据库,以识别截至2016年6月发表的随机对照试验(RCT)。使用计算机、移动或可穿戴技术促进久坐行为减少且以久坐时间作为结果指标的干预措施符合纳入标准。使用Cochrane协作网的工具评估偏倚风险,并使用行为改变技术分类法(第1版)对干预措施进行编码。 结果:对15/17项随机对照试验的荟萃分析表明,计算机、移动和可穿戴技术工具使每天的久坐时间平均减少了-41.28分钟(分钟/天)(95%置信区间-60.99,-21.58,I² = 77%,n = 1402),在终点随访时干预组更有利。汇总效应显示,在短期(≤3个月)、中期(>3至6个月)和长期随访(>6个月)时,平均减少时间分别为-42.42分钟/天、-37.23分钟/天和-1.65分钟/天。总体而言,16/17项研究被认为具有高或不明确的偏倚风险,1/17项被判定为低偏倚风险。干预措施的计算机、移动和可穿戴组件总共编码了46种行为改变技术(14种独特的)。编码最频繁的是“提示与线索”、“行为自我监测”、“社会支持(未明确说明)”和“目标设定(行为)”。 结论:使用计算机、移动和可穿戴技术的干预措施在减少久坐行为方面可能有效。有效性在短期内最为显著,且随时间推移而降低。这些干预措施中实施了一系列行为改变技术。未来的研究需要改进干预措施中行为改变技术的报告,并通过使用更严格控制的研究设计、长期随访、久坐行为的客观测量方法以及纳入减少失访的策略来解决综述中发现的方法学缺陷。 试验注册:该综述方案已在PROSPERO注册:CRD42016038187。
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