Maher Carol A, Lewis Lucy K, Ferrar Katia, Marshall Simon, De Bourdeaudhuij Ilse, Vandelanotte Corneel
Health and Use of Time Group, University of South Australia, Adelaide, Australia.
J Med Internet Res. 2014 Feb 14;16(2):e40. doi: 10.2196/jmir.2952.
The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change.
The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions.
Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized.
A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from -0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity).
To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.
Web 2.0技术和在线社交网络的迅猛发展为开展健康行为改变活动提供了巨大潜力。然而,目前尚不清楚如何才能最好地利用在线社交网络来实现健康行为的改变。
本研究旨在系统回顾有关在线社交网络健康行为干预有效性的现有证据水平。
使用全面的检索策略,对2000年至今的八个数据库(Scopus、CINAHL、Medline、ProQuest、EMBASE、PsycINFO、Cochrane、科学引文索引和通信与大众传媒全文数据库)进行检索。研究纳入标准基于PICOS格式,其中“人群”包括儿童或成人人群,涵盖健康人群和患病人群;“干预措施”涉及针对关键可改变健康行为(烟草和酒精消费、饮食摄入、身体活动和久坐行为)的行为改变干预措施,这些措施全部或部分通过在线社交网络实施;“对照”在前后对照研究设计中为对照组或自身对照;“结局”包括健康行为改变以及与之密切相关的变量(如健康行为改变的理论中介因素,如自我效能感);“研究设计”包括在同行评审的完整文献中报道的实验研究。对干预效果的报告进行了总结,并尽可能计算效应量(科恩d值和95%置信区间)。对干预措施中社交网络部分的失访率(完成研究的人数百分比)、参与度(实际使用情况)和保真度(实际使用情况/预期使用情况)进行了审查。
在去除重复项后,从数据库检索中总共识别出2040项研究,其中10项符合纳入标准。这些研究共涉及113988名参与者(人数从n = 10到n = 107907不等)。干预措施包括商业在线健康社交网络网站(n = 2)、研究性健康社交网络网站(n = 3)以及部分通过现有的流行在线社交网络网站(Facebook,n = 4;Twitter,n = 1)实施的多成分干预措施。10项纳入研究中的9项报告称,在健康行为改变或与行为改变相关的结局的某些方面有显著改善。行为改变的效应量范围广泛,从-0.05(95%CI 0.45 - 0.35)到0.84(95%CI 0.49 - 1.19),但总体效应量较小且无统计学意义。参与者失访率在0 - 84%之间。参与度和保真度相对较低,大多数研究的保真度为5 - 15%(有一项例外,保真度达到105%)。
迄今为止,仅有非常有限的证据表明纳入在线社交网络的干预措施可能有效;然而,该研究领域尚处于起步阶段。需要进一步研究以确定如何最大限度地提高留存率和参与度,行为改变能否长期维持,以及如何利用在线社交网络实现大规模传播。并为未来研究提供了具体建议。