Literature DB >> 24617994

Computerized recovery support for substance use disorders: predictors of posttreatment usage.

Audrey A Klein1.   

Abstract

OBJECTIVE: The primary goal of this study was to examine which characteristics differentiated patients who highly engaged with a computerized recovery support program after alcohol/drug treatment from those who did not engage with the program.
MATERIALS AND METHODS: The program delivered individually tailored clinical content in a multimedia format over 18 months following residential treatment. A key component of the program was access to a recovery coach, a licensed drug and alcohol counselor. Posttreatment logins to the program, the amount of clinical content accessed, and the number of recovery coach contacts were measured.
RESULTS: Several factors were found to predict program engagement, including several demographic variables, the number of recovery coach contacts, motivation to be in recovery, and attendance at 12-step groups.
CONCLUSIONS: These findings, combined with others in the literature, suggest that low engagement with computerized health programs is a widespread problem. Because many of these programs show therapeutic promise, future studies should continue to increase understanding of factors associated with high engagement so that efforts to increase engagement may be applied more effectively.

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Mesh:

Year:  2014        PMID: 24617994     DOI: 10.1089/tmj.2013.0252

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  3 in total

1.  A randomized clinical trial of the Recovery Line among methadone treatment patients with ongoing illicit drug use.

Authors:  Brent A Moore; Frank D Buono; Daniel P Lloyd; Destiny M B Printz; David A Fiellin; Declan T Barry
Journal:  J Subst Abuse Treat       Date:  2018-11-24

2.  Customized recommendations and reminder text messages for automated, computer-based treatment during methadone.

Authors:  Brent A Moore; Frank D Buono; Destiny M B Printz; Daniel P Lloyd; David A Fiellin; Christopher J Cutter; Richard S Schottenfeld; Declan T Barry
Journal:  Exp Clin Psychopharmacol       Date:  2017-12       Impact factor: 3.157

Review 3.  e-Addictology: An Overview of New Technologies for Assessing and Intervening in Addictive Behaviors.

Authors:  Florian Ferreri; Alexis Bourla; Stephane Mouchabac; Laurent Karila
Journal:  Front Psychiatry       Date:  2018-03-01       Impact factor: 4.157

  3 in total

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