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成瘾治疗期间物质使用的预测因素:生态瞬时评估数据的网络分析

Predictors of substance use during treatment for addiction: A network analysis of ecological momentary assessment data.

作者信息

Serre Fuschia, Gauld Christophe, Lambert Laura, Baillet Emmanuelle, Beltran Virginie, Daulouede Jean-Pierre, Micoulaud-Franchi Jean-Arthur, Auriacombe Marc

机构信息

University of Bordeaux, Bordeaux, France.

CNRS, SANPSY, UMR 6033, Bordeaux, France.

出版信息

Addiction. 2025 Jan;120(1):48-58. doi: 10.1111/add.16658. Epub 2024 Aug 30.

Abstract

BACKGROUND AND AIMS

Ecological momentary assessment (EMA) studies have previously demonstrated a prospective influence of craving on substance use in the following hours. Conceptualizing substance use as a dynamic system of causal elements could provide valuable insights into the interaction of craving with other symptoms in the process of relapse. The aim of this study was to improve the understanding of these daily life dynamic inter-relationships by applying dynamic networks analyses to EMA data sets.

DESIGN, SETTING AND PARTICIPANTS: Secondary analyses were conducted on time-series data from two 2-week EMA studies. Data were collected in French outpatient addiction treatment centres. A total of 211 outpatients beginning treatment for alcohol, tobacco, cannabis, stimulants and opiate addiction took part.

MEASUREMENTS

Using mobile technologies, participants were questioned four times per day relative to substance use, craving, exposure to cues, mood, self-efficacy and pharmacological addiction treatment use. Multi-level vector auto-regression models were used to explore contemporaneous, temporal and between-subjects networks.

FINDINGS

Among the 8260 daily evaluations, the temporal network model, which depicts the lagged associations of symptoms within participants, demonstrated a unidirectional association between craving intensity at one time (T0) and primary substance use at the next assessment (T1, r = 0.1), after controlling for the effect of all other variables. A greater self-efficacy at T0 was associated with fewer cues (r = -0.04), less craving (r = -0.1) and less substance use at T1 (r = -0.07), and craving presented a negative feedback loop with self-efficacy (r = -0.09).

CONCLUSIONS

Dynamic network analyses showed that, among outpatients beginning treatment for addiction, high craving, together with low self-efficacy, appear to predict substance use more strongly than low mood or high exposure to cues.

摘要

背景与目的

生态瞬时评估(EMA)研究先前已证明,渴望在接下来的数小时内对物质使用具有前瞻性影响。将物质使用概念化为一个由因果要素构成的动态系统,可能会为复发过程中渴望与其他症状的相互作用提供有价值的见解。本研究的目的是通过将动态网络分析应用于EMA数据集,增进对这些日常生活中动态相互关系的理解。

设计、地点与参与者:对两项为期两周的EMA研究的时间序列数据进行了二次分析。数据在法国门诊成瘾治疗中心收集。共有211名开始接受酒精、烟草、大麻、兴奋剂和阿片类成瘾治疗的门诊患者参与。

测量

使用移动技术,每天就物质使用、渴望、接触线索、情绪、自我效能感和药物成瘾治疗使用情况对参与者进行四次询问。使用多层次向量自回归模型来探索同期、时间和个体间网络。

研究结果

在8260次每日评估中,描绘参与者内症状滞后关联的时间网络模型显示,在控制所有其他变量的影响后,某一时刻(T0)的渴望强度与下一次评估(T1)时的主要物质使用之间存在单向关联(r = 0.1)。T0时较高的自我效能感与T1时较少的线索(r = -0.04)、较少的渴望(r = -0.1)和较少的物质使用(r = -0.07)相关,并且渴望与自我效能感呈现负反馈循环(r = -0.09)。

结论

动态网络分析表明,在开始接受成瘾治疗的门诊患者中,高渴望与低自我效能感似乎比低情绪或高接触线索更能强烈预测物质使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6080/11638523/bb9063c46dee/ADD-120-48-g003.jpg

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