Predictors of substance use during treatment for addiction: A network analysis of ecological momentary assessment data.
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 cra...
| Publicado en: | Addiction Vol. 120; no. 1; pp. 48 - 59 |
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| Autores principales: | , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jan2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=181623905&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 181623905 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Jan2025 vid: 120 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 181623905 179312217 181623905 181623905 10.1111/add.16658 181623905 ppf: 48 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Predictors of substance use during treatment for addiction: A network analysis of ecological momentary assessment data. aug: au: Serre, Fuschia Gauld, Christophe Lambert, Laura Baillet, Emmanuelle Beltran, Virginie Daulouede, Jean‐Pierre Micoulaud‐Franchi, Jean‐Arthur Auriacombe, Marc affil: University of Bordeaux, Bordeaux, France sug: subj: Substance Use Disorders Therapy Substance Use Disorders Risk Factors Risk Assessment Human Secondary Analysis Mobile Applications Craving Cues Self-Efficacy Models, Theoretical Funding Source ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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