Department of Public Health, Faculty of Health Sciences, University of Stavanger, Stavanger, Norway.
Department of Rehabilitation Science and Health Technology, Faculty of Health Sciences, OsloMet - Oslo Metropolitan University, Oslo, Norway.
J Med Internet Res. 2023 Apr 20;25:e38307. doi: 10.2196/38307.
The number of people with noncommunicable diseases is increasing. Noncommunicable diseases are the major cause of disability and premature mortality worldwide, associated with negative workplace outcomes such as sickness absence and reduced work productivity. There is a need to identify scalable interventions and their active components to relieve disease and treatment burden and facilitate work participation. eHealth interventions have shown potential in clinical and general populations to increase well-being and physical activity and could be well suited for workplace settings.
We aimed to provide an overview of the effectiveness of eHealth interventions at the workplace targeting employee health behaviors and map behavior change techniques (BCTs) used in these interventions.
A systematic literature search was performed in PubMed, Embase, PsycINFO, Cochrane CENTRAL, and CINAHL in September 2020 and updated in September 2021. Extracted data included participant characteristics, setting, eHealth intervention type, mode of delivery, reported outcomes, effect sizes, and attrition rates. Quality and risk of bias of the included studies were assessed using the Cochrane Collaboration risk-of-bias 2 tool. BCTs were mapped in accordance with the BCT Taxonomy v1. The review was reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.
In total, 17 randomized controlled trials met the inclusion criteria. The measured outcomes, treatment and follow-up periods, content of eHealth interventions, and workplace contexts had high heterogeneity. Of the 17 studies, 4 (24%) reported unequivocally significant findings for all primary outcomes, with effect sizes ranging from small to large. Furthermore, 53% (9/17) of the studies reported mixed results, and 24% (4/17) reported nonsignificant results. The most frequently targeted behavior was physical activity (15/17, 88% of the studies); the least frequently targeted behavior was smoking (2/17, 12% of the studies). Attrition varied greatly across the studies (0%-37%). Risk of bias was high in 65% (11/17) of the studies, with some concerns in the remaining 35% (6/17). Interventions used various BCTs, and the most frequently used were feedback and monitoring (14/17, 82%), goals and planning (10/17, 59%), antecedents (10/17, 59%), and social support (7/17, 41%).
This review suggests that, although eHealth interventions may have potential, there are still unanswered questions regarding their effectiveness and what drives the mechanism behind these effects. Low methodological quality, high heterogeneity and complexity, the characteristics of the included samples, and often high attrition rates challenge the investigation of the effectiveness and the making of sound inferences about the effect sizes and significance of the results. To address this, new studies and methods are needed. A megastudy design in which different interventions are evaluated in the same population over the same period on the same outcomes may solve some of the challenges.
PROSPERO CRD42020202777; https://www-crd-york-ac-uk/prospero/display_record.php?RecordID=202777.
非传染性疾病患者人数不断增加。非传染性疾病是全世界残疾和过早死亡的主要原因,与病假和工作生产力下降等负面工作结果相关。因此,有必要确定可扩展的干预措施及其有效组成部分,以减轻疾病和治疗负担,并促进工作参与。电子健康干预措施已显示出在临床和普通人群中增加幸福感和体育活动的潜力,并且非常适合工作场所环境。
我们旨在提供针对员工健康行为的工作场所电子健康干预措施的有效性概述,并绘制这些干预措施中使用的行为改变技术(BCT)。
我们于 2020 年 9 月在 PubMed、Embase、PsycINFO、Cochrane 中心数据库和 CINAHL 中进行了系统文献检索,并于 2021 年 9 月进行了更新。提取的数据包括参与者特征、环境、电子健康干预类型、交付模式、报告结果、效应量和辍学率。使用 Cochrane 协作风险偏倚 2 工具评估纳入研究的质量和风险偏倚。BCT 按照 BCT 分类学 v1 进行映射。综述报告按照 PRISMA(系统评价和荟萃分析的首选报告项目)清单进行。
共有 17 项随机对照试验符合纳入标准。测量的结果、治疗和随访期、电子健康干预的内容以及工作场所背景存在高度异质性。在 17 项研究中,有 4 项(24%)对所有主要结果报告了明确的显著结果,效应量范围从小到大。此外,53%(9/17)的研究报告了混合结果,24%(4/17)的研究报告了无显著结果。研究中最常针对的行为是体育活动(15/17,88%的研究);最不常针对的行为是吸烟(2/17,12%的研究)。研究之间的辍学率差异很大(0%-37%)。在 65%(11/17)的研究中,风险偏倚较高,其余 35%(6/17)存在一些担忧。干预措施使用了各种 BCT,最常用的是反馈和监测(17/17,82%)、目标和计划(17/17,59%)、前因(17/17,59%)和社会支持(7/17,41%)。
这项综述表明,尽管电子健康干预措施可能具有潜力,但它们的有效性以及驱动这些效果背后机制的问题仍然没有答案。低方法学质量、高度异质性和复杂性、纳入样本的特征以及高辍学率经常挑战对有效性的调查,并对效应量和结果的显著性进行合理推断。为了解决这些问题,需要开展新的研究和方法。在同一人群中,在同一时期内,对相同结果评估不同的干预措施的大规模研究设计可能会解决一些挑战。
PROSPERO CRD42020202777;https://www-crd-york-ac-uk/prospero/display_record.php?RecordID=202777。