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研究基于智能手机应用程序的干预措施实施后饮食失调症状网络结构的变化。

Investigating change in network structure of eating disorder symptoms after delivery of a smartphone app-based intervention.

作者信息

Linardon Jake, Greenwood Christopher J, Aarsman Stephanie, Fuller-Tyszkiewicz Matthew

机构信息

School of Psychology, Deakin University, Geelong, Victoria, Australia.

Center for Social and Early Emotional Development, Deakin University, Burwood, Victoria, Australia.

出版信息

Psychol Med. 2024 Jul;54(10):2698-2706. doi: 10.1017/S0033291724000813. Epub 2024 Apr 8.

Abstract

BACKGROUND

Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption.

METHODS

Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist ( = 155), intervention responder ( = 49), and intervention non-responder ( = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure.

RESULTS

Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness.

CONCLUSION

Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

摘要

背景

饮食失调(ED)研究采用了精神病理学的网络视角,该视角提出精神疾病可被概念化为一个由相互作用的症状组成的复杂系统。然而,现有的采用网络视角的干预研究未能发现症状减轻与这些症状之间关联强度的降低相一致。我们认为这可能反映了网络理论与研究设计及分析之间未能保持一致。我们针对预期会被基于应用程序的干预打乱的特定症状关联提出假设,并测试一系列用于识别这种干预引起的打乱的统计指标的敏感性。

方法

对参与一款认知行为智能手机应用程序随机对照试验的反复暴饮暴食个体的数据进行分析。参与者被分为三组之一:等待名单组(n = 155)、干预响应者组(n = 49)和干预无响应者组(n = 77)。比较了几种统计检验(双变量关联、基于网络的强度统计、网络不变性检验)识别网络结构变化的能力。

结果

在响应者组中,通过从基线到干预后双变量相关性的变化观察到了对特定症状关联的假设打乱,但从基于症状和全网络的网络分析统计中并不明显。当将干预组一起评估而忽略治疗反应性的异质性时,效应被掩盖了。

结论

研究结果与我们的观点一致,即研究设计和分析方法会影响准确检验网络理论预测的能力。我们最后为未来基于网络理论的干预研究提供了关键建议。

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