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社交网络干预对健康行为和结果的影响:系统评价和荟萃分析。

Social network interventions for health behaviours and outcomes: A systematic review and meta-analysis.

机构信息

UKCRC Centre of Excellence for Public Health (NI)/Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom.

Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America.

出版信息

PLoS Med. 2019 Sep 3;16(9):e1002890. doi: 10.1371/journal.pmed.1002890. eCollection 2019 Sep.


DOI:10.1371/journal.pmed.1002890
PMID:31479454
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6719831/
Abstract

BACKGROUND: There has been a growing interest in understanding the effects of social networks on health-related behaviour, with a particular backdrop being the emerging prominence of complexity or systems science in public health. Social network interventions specifically use or alter the characteristics of social networks to generate, accelerate, or maintain health behaviours. We conducted a systematic review and meta-analysis to investigate health behaviour outcomes of social network interventions. METHODS AND FINDINGS: We searched eight databases and two trial registries from 1990 to May 28, 2019, for English-language reports of randomised controlled trials (RCTs) and before-and-after studies investigating social network interventions for health behaviours and outcomes. Trials that did not specifically use social networks or that did not include a comparator group were excluded. We screened studies and extracted data from published reports independently. The primary outcome of health behaviours or outcomes at ≤6 months was assessed by random-effects meta-analysis. Secondary outcomes included those measures at >6-12 months and >12 months. This study is registered with the International Prospective Register of Systematic Reviews, PROSPERO: CRD42015023541. We identified 26,503 reports; after exclusion, 37 studies, conducted between 1996 and 2018 from 11 countries, were eligible for analysis, with a total of 53,891 participants (mean age 32.4 years [SD 12.7]; 45.5% females). A range of study designs were included: 27 used RCT/cluster RCT designs, and 10 used other study designs. Eligible studies addressed a variety of health outcomes, in particular sexual health and substance use. Social network interventions showed a significant intervention effect compared with comparator groups for sexual health outcomes. The pooled odds ratio (OR) was 1.46 (95% confidence interval [CI] 1.01-2.11; I2 = 76%) for sexual health outcomes at ≤6 months and OR 1.51 (95% CI 1.27-1.81; I2 = 40%) for sexual health outcomes at >6-12 months. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in haemoglobin A1c (HbA1c), and smoking cessation. Because of clinical and measurement heterogeneity, it was not appropriate to pool data on these other behaviours in a meta-analysis. For sexual health outcomes, prespecified subgroup analyses were significant for intervention approach (p < 0.001), mean age of participants (p = 0.002), and intervention length (p = 0.05). Overall, 22 of the 37 studies demonstrated a high risk of bias, as measured by the Cochrane Risk of Bias tool. The main study limitations identified were the inclusion of studies of variable quality; difficulty in isolating the effects of specific social network intervention components on health outcomes, as interventions included other active components; and reliance on self-reported outcomes, which have inherent recall and desirability biases. CONCLUSIONS: Our findings suggest that social network interventions can be effective in the short term (<6 months) and longer term (>6 months) for sexual health outcomes. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in HbA1c, and smoking cessation.

摘要

背景:人们越来越关注理解社交网络对健康相关行为的影响,特别是复杂或系统科学在公共卫生领域的新兴重要性。社交网络干预措施专门使用或改变社交网络的特征,以产生、加速或维持健康行为。我们进行了系统评价和荟萃分析,以调查社交网络干预对健康行为结果的影响。

方法和发现:我们从 1990 年至 2019 年 5 月 28 日,在八个数据库和两个试验登记处搜索了英文报告的随机对照试验(RCT)和前瞻性研究,以调查针对健康行为和结果的社交网络干预措施。未专门使用社交网络或未包括对照组的试验被排除在外。我们独立筛选研究并从已发表的报告中提取数据。通过随机效应荟萃分析评估≤6 个月的健康行为或结果的主要结局。次要结局包括>6-12 个月和>12 个月的测量值。本研究在国际前瞻性系统评价注册处注册,PROSPERO:CRD42015023541。我们确定了 26,503 份报告;排除后,有 37 项研究于 1996 年至 2018 年在 11 个国家进行,符合分析条件,共有 53,891 名参与者(平均年龄 32.4 岁[SD 12.7];45.5%为女性)。纳入了多种研究设计:27 项使用 RCT/聚类 RCT 设计,10 项使用其他研究设计。合格研究涉及各种健康结果,特别是性健康和药物使用。与对照组相比,社交网络干预措施对性健康结果有显著的干预效果。在≤6 个月时,性健康结局的汇总优势比(OR)为 1.46(95%置信区间[CI]1.01-2.11;I2 = 76%),在>6-12 个月时,性健康结局的 OR 为 1.51(95%CI 1.27-1.81;I2 = 40%)。在每个时间点,药物风险结局的干预效果均不显著。对于一些其他健康结果,如饮酒不当、幸福感、血红蛋白 A1c(HbA1c)变化和戒烟,也有显著的干预效果。由于临床和测量的异质性,不适合在荟萃分析中对这些其他行为的数据进行汇总。对于性健康结局,按干预方法(p<0.001)、参与者的平均年龄(p=0.002)和干预长度(p=0.05)进行的预设亚组分析有显著差异。总体而言,37 项研究中有 22 项研究被 Cochrane 风险偏倚工具评为高风险。确定的主要研究局限性是纳入了质量不同的研究;难以将社交网络干预特定组成部分对健康结果的影响分离出来,因为干预措施包括其他活跃成分;以及依赖于自我报告的结果,这些结果存在内在的回忆和偏好偏差。

结论:我们的研究结果表明,社交网络干预措施在短期(<6 个月)和长期(>6 个月)内对性健康结果可能是有效的。在每个时间点,药物风险结局的干预效果均不显著。对于一些其他健康结果,如饮酒不当、幸福感、HbA1c 变化和戒烟,也有显著的干预效果。

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