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Predictors of substance use during treatment for addiction: A network analysis of ecological momentary assessment data.
Serre, Fuschia; Gauld, Christophe; Lambert, Laura; Baillet, Emmanuelle; Beltran, Virginie; Daulouede, Jean-Pierre; Micoulaud-Franchi, Jean-Arthur; Auriacombe, Marc.
Afiliação
  • Serre F; University of Bordeaux, Bordeaux, France.
  • Gauld C; CNRS, SANPSY, UMR 6033, Bordeaux, France.
  • Lambert L; Pôle Interétablissement d'Addictologie, CH Ch. Perrens and CHU de Bordeaux, Bordeaux, France.
  • Baillet E; University of Bordeaux, Bordeaux, France.
  • Beltran V; CNRS, SANPSY, UMR 6033, Bordeaux, France.
  • Daulouede JP; Department of Child Psychiatry, Université de Lyon, Lyon, France.
  • Micoulaud-Franchi JA; Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS and Université Claude Bernard Lyon 1, Lyon, France.
  • Auriacombe M; University of Bordeaux, Bordeaux, France.
Addiction ; 2024 Aug 30.
Article em En | MEDLINE | ID: mdl-39210697
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Addiction Assunto da revista: TRANSTORNOS RELACIONADOS COM SUBSTANCIAS Ano de publicação: 2024 Tipo de documento: Article País de afiliação: França País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Addiction Assunto da revista: TRANSTORNOS RELACIONADOS COM SUBSTANCIAS Ano de publicação: 2024 Tipo de documento: Article País de afiliação: França País de publicação: Reino Unido