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基于网络的成功干预酒精消费、暴食和赌博行为改变技术的识别:系统评价。

Identification of Behavior Change Techniques From Successful Web-Based Interventions Targeting Alcohol Consumption, Binge Eating, and Gambling: Systematic Review.

机构信息

School of Psychology, University of Liverpool, Liverpool, United Kingdom.

出版信息

J Med Internet Res. 2021 Feb 9;23(2):e22694. doi: 10.2196/22694.

DOI:10.2196/22694
PMID:33560243
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7902193/
Abstract

BACKGROUND

Web-based interventions are thought to overcome barriers to treatment, such as accessibility and geographical location, which can undermine the effectiveness of traditional face-to-face interventions. Owing to these features, researchers are increasingly testing the efficacy of web-based interventions as ways to reduce alcohol misuse, binge eating, and gambling. However, many web-based interventions have poorly defined mechanisms of action; therefore, it is often uncertain how they propose to bring about behavior change.

OBJECTIVE

This systematic review aims to identify effective behavior change techniques (BCTs) present in web-based interventions aimed at reducing alcohol consumption, binge eating, or gambling.

METHODS

This systematic review covered research conducted in the last 20 years. Inclusion criteria for interventions were web-based administration; targeting alcohol use, binge eating, and/or gambling; and reporting on baseline and postintervention measures of behavior. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines were followed. We coded intervention effectiveness, study quality, and BCTs present in the interventions.

RESULTS

Following removal of 4152 ineligible articles, 45 were included in the review: 32 (71%) targeted alcohol misuse, 6 (13%) targeted binge eating, and 7 (16%) targeted gambling. In total, 5 frequency counts were performed to identify the most commonly used BCTs: all studies, effective interventions, high-quality studies at 2 thresholds, and both high quality and effective studies. The results obtained from this were integrated to identify 7 BCTs. These 7 BCTs were problem solving, feedback on behavior, self-monitoring of behavior, self-monitoring of outcomes, instruction on how to perform a behavior, information about social and health consequences, and social comparison. A total of 4 BCTs were found in all frequency counts: feedback on behavior, self-monitoring of behavior, instruction on how to perform a behavior, and social comparison. Self-monitoring of outcomes of behavior was found in 3 of the 5 frequency counts, problem solving was found in 2 frequency counts, and information about social and health consequences was found in 1 frequency count.

CONCLUSIONS

This systematic review identified 7 of the most frequently used BCTs used in web-based interventions focused on alcohol misuse, binge eating, and gambling. These results can inform the development of evidence-based eHealth interventions that have the potential to lead to effective, positive behavior changes in all 3 areas.

摘要

背景

基于网络的干预措施被认为可以克服治疗障碍,例如可及性和地理位置,这些障碍会降低传统面对面干预的效果。由于这些特点,研究人员越来越多地测试基于网络的干预措施的功效,以减少酗酒、暴食和赌博。然而,许多基于网络的干预措施的作用机制定义不明确;因此,通常不确定它们如何提出带来行为改变。

目的

本系统评价旨在确定旨在减少饮酒、暴食或赌博的基于网络的干预措施中存在的有效行为改变技术(BCT)。

方法

本系统评价涵盖了过去 20 年开展的研究。干预措施的纳入标准为:基于网络管理;针对酒精使用、暴食和/或赌博;并报告行为的基线和干预后测量结果。本研究遵循 PRISMA(系统评价和荟萃分析的首选报告项目)指南。我们对干预措施的效果、研究质量和存在的 BCT 进行了编码。

结果

在剔除 4152 篇不相关的文章后,有 45 篇文章被纳入本综述:32 篇(71%)针对酒精滥用,6 篇(13%)针对暴食,7 篇(16%)针对赌博。总共进行了 5 次频率计数,以确定最常用的 BCT:所有研究、有效干预、2 个阈值的高质量研究以及高质量和有效的研究。从这些结果中整合出 7 个 BCT。这 7 个 BCT 是解决问题、行为反馈、行为自我监测、结果自我监测、如何执行行为的指导、有关社会和健康后果的信息以及社会比较。在所有频率计数中,共有 4 个 BCT 被发现:行为反馈、行为自我监测、如何执行行为的指导和社会比较。在 5 次频率计数中,有 3 次发现了结果自我监测行为,2 次发现了解决问题,1 次发现了有关社会和健康后果的信息。

结论

本系统评价确定了 7 个最常用于专注于酗酒、暴食和赌博的基于网络的干预措施中的 BCT。这些结果可以为基于电子健康的干预措施的开发提供信息,这些干预措施有可能在这三个领域都带来有效的、积极的行为改变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b95/7902193/c13845b491b3/jmir_v23i2e22694_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b95/7902193/c13845b491b3/jmir_v23i2e22694_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b95/7902193/c13845b491b3/jmir_v23i2e22694_fig1.jpg

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