Evidence map›Paper›PMID 37219032›Full record

ArticleJournal of studies on alcohol and drugs2023

Patient-Concerned Other Dyads' 12-Step Involvement and Patients' Substance Use: A Latent Class Growth Model Analysis.

Christine Timko, Michael A Cucciare, Mai Chee Lor, Michael Stein, Noel Vest

Abstract read
In one paragraph

Article in Journal of studies on alcohol and drugs, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Christine TimkoCenter for Innovation to Implementation, Department of Veterans Affairs Health Care System, Palo Alto, California.
Michael A CucciareDepartment of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Mai Chee LorCenter for Innovation to Implementation, Department of Veterans Affairs Health Care System, Palo Alto, California.
Michael SteinBoston University School of Public Health, Department of Community Health Sciences, Boston, Massachusetts.
Noel VestDepartment of Health Law, Policy and Management, Boston University School of Public Health, Boston, Massachusetts.

Funding

Intensive Referral to Al-Anon: Benefits to Concerned Others and Their DrinkersR01AA024136 · NIAAA · PALO ALTO VETERANS INSTIT FOR RESEARCH · PI CUCCIARE, MICHAEL ANTHONY, TIMKO, CHRISTINE D · 2016 to 2019
$1.5M
Collegiate recovery programming in the U.S.: An implementation science and mixed methods studyK01DA053391 · NIDA · STANFORD UNIVERSITY · PI Noel Adam Vest · 2022 to 2026
$882k
HSRD VA RCS 00-001NIAAA NIH HHS R01 AA024136NIDA NIH HHS K01 DA053391NIDA NIH HHS L30 DA056944
6 · The paper itself

Abstract

objectiveThis study aimed to inform clinical practice by identifying subgroups of patient-concerned other (CO) dyads. Patients with alcohol use disorders (AUDs) were characterized on Alcoholics Anonymous (AA) involvement and substance use together with COs' Al-Anon involvement. Predictors and recovery maintenance outcomes of subgroup membership were examined.

methodParticipants were 279 patient-CO dyads. Patients were in residential treatment for AUD. Parallel latent class growth model analysis characterized 12-step involvement and substance use at treatment entry and 3-, 6-, and 12-month follow-ups.

resultsThree classes were as follows: 38% Low AA/Low Al-Anon (patients' low AA and COs' low Al-Anon involvement, and patients' high-to-moderate substance use), 10% High AA/High Al-Anon (patients' high AA and COs' high Al-Anon involvement, and patients' moderate-to-low substance use), and 52% High AA/Low Al-Anon (patients' high AA and COs' low Al-Anon involvement, and patients' moderate-to-low substance use). At follow-up, the Low AA/Low Al-Anon classes' patients were less likely to have spirituality as recovery support, confidence about staying abstinent, and satisfaction with recovery progress. The High AA classes' COs had less concern about patients' drinking and scored higher on positive aspects of relationships with patients.

conclusionsClinicians should encourage patients' and COs' 12-step group involvement (12-step practices' engagement). Among patients treated for AUD, AA involvement was related to better outcomes, and to COs' lessened concern about the patients' drinking. COs' Al-Anon involvement was associated with having a more positive view of their relationship with the patient. That more than one third of dyads had low 12-step group involvement suggests that treatment programs may need to facilitate involvement in non-12-step mutual-help groups.

Indexed as

AlcoholismSubstance-Related DisordersAlcoholics AnonymousHumansQuality of Life

Identifiers

PMID37219032
PMCPMC10600972

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.