Behavior Change Techniques Within Digital Interventions for the Treatment of Eating Disorders: Systematic Review and Meta-Analysis.

IF 4.8 2区 医学 Q1 PSYCHIATRY
Jmir Mental Health Pub Date : 2024-08-01 DOI:10.2196/57577
Pamela Carien Thomas, Kristina Curtis, Henry W W Potts, Pippa Bark, Rachel Perowne, Tasmin Rookes, Sarah Rowe
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引用次数: 0

Abstract

Background: Previous systematic reviews of digital eating disorder interventions have demonstrated effectiveness at improving symptoms of eating disorders; however, our understanding of how these interventions work and what contributes to their effectiveness is limited. Understanding the behavior change techniques (BCTs) that are most commonly included within effective interventions may provide valuable information for researchers and developers. Establishing whether these techniques have been informed by theory will identify whether they target those mechanisms of action that have been identified as core to changing eating disorder behaviors. It will also evaluate the importance of a theoretical approach to digital intervention design.

Objective: This study aims to define the BCTs within digital self-management interventions or minimally guided self-help interventions for adults with eating disorders that have been evaluated within randomized controlled trials. It also assessed which of the digital interventions were grounded in theory and the range of modes of delivery included.

Methods: A literature search identified randomized controlled trials of digital intervention for the treatment of adults with eating disorders with minimal therapist support. Each digital intervention was coded for BCTs using the established BCT Taxonomy v1; for the application of theory using an adapted version of the theory coding scheme (TCS); and for modes of delivery using the Mode of Delivery Ontology. A meta-analysis evaluated the evidence that any individual BCT moderated effect size or that other potential factors such as the application of theory or number of modes of delivery had an effect on eating disorder outcomes.

Results: Digital interventions included an average of 14 (SD 2.6; range 9-18) BCTs. Self-monitoring of behavior was included in all effective interventions, with Problem-solving, Information about antecedents, Feedback on behavior, Self-monitoring of outcomes of behavior, and Action planning identified in >75% (13/17) of effective interventions. Social support and Information about health consequences were more evident in effective interventions at follow-up compared with postintervention measurement. The mean number of modes of delivery was 4 (SD 1.6; range 2-7) out of 12 possible modes, with most interventions (15/17, 88%) being web based. Digital interventions that had a higher score on the TCS had a greater effect size than those with a lower TCS score (subgroup differences: χ21=9.7; P=.002; I²=89.7%) within the meta-analysis. No other subgroup analyses had statistically significant results.

Conclusions: There was a high level of consistency in terms of the most common BCTs within effective interventions; however, there was no evidence that any specific BCT contributed to intervention efficacy. The interventions that were more strongly informed by theory demonstrated greater improvements in eating disorder outcomes compared to waitlist or treatment-as-usual controls. These results can be used to inform the development of future digital eating disorder interventions.

Trial registration: PROSPERO CRD42023410060; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=410060.

治疗进食障碍的数字化干预措施中的行为改变技术:系统回顾与元分析》。
背景:以前对数字化饮食失调干预措施的系统性回顾表明,这些措施在改善饮食失调症状方面很有效;但是,我们对这些干预措施如何发挥作用以及是什么促成了它们的有效性的了解还很有限。了解有效干预措施中最常采用的行为改变技术(BCT)可为研究人员和开发人员提供有价值的信息。确定这些技巧是否有理论依据,可以确定它们是否针对那些已被确定为改变进食障碍行为核心的作用机制。它还将评估理论方法对数字干预设计的重要性:本研究旨在确定针对成人饮食失调症患者的数字化自我管理干预或最小指导自助干预中的BCTs,这些干预已在随机对照试验中进行了评估。该研究还评估了哪些数字化干预措施是以理论为基础的,以及所包括的一系列实施模式:方法:通过文献检索,确定了针对成人饮食失调症治疗的数字干预的随机对照试验,这些试验只需要极少的治疗师支持。每项数字干预均使用已建立的BCT分类标准v1对BCT进行编码;使用改编版理论编码方案(TCS)对理论应用进行编码;使用 "提供模式本体 "对提供模式进行编码。一项荟萃分析评估了是否有证据表明任何一种BCT会调节效果大小,或其他潜在因素(如理论应用或提供模式的数量)会对饮食失调的结果产生影响:数字干预平均包括 14 种 BCT(标准差 2.6;范围 9-18)。所有有效的干预措施中都包括行为自我监控,超过 75% (13/17)的有效干预措施中确定了问题解决、前因信息、行为反馈、行为结果自我监控和行动规划。与干预后的测量结果相比,社会支持和有关健康后果的信息在后续有效干预中更为明显。在 12 种可能的干预方式中,平均干预方式为 4 种(标准差为 1.6;范围为 2-7),大多数干预方式(15/17,88%)基于网络。在荟萃分析中,TCS得分较高的数字化干预措施比TCS得分较低的干预措施具有更大的效果(亚组差异:χ21=9.7;P=.002;I²=89.7%)。其他亚组分析结果均无统计学意义:有效干预中最常见的 BCT 具有高度的一致性;但是,没有证据表明任何特定的 BCT 对干预效果有促进作用。与等待名单或照常治疗对照组相比,理论依据更强的干预对饮食失调症结果的改善更大。这些结果可为未来数字化饮食失调干预措施的开发提供参考:ProCORD42023410060; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=410060.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Jmir Mental Health
Jmir Mental Health Medicine-Psychiatry and Mental Health
CiteScore
10.80
自引率
3.80%
发文量
104
审稿时长
16 weeks
期刊介绍: JMIR Mental Health (JMH, ISSN 2368-7959) is a PubMed-indexed, peer-reviewed sister journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR Mental Health focusses on digital health and Internet interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations.
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