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

Customized recommendations and reminder text messages for automated, computer-based treatment during methadone.
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在美沙酮期间进行基于计算机的自动化治疗的定制建议和提醒短信。

DOI:
10.1037/pha0000149
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发表时间:
2017
影响因子:
2.3
通讯作者:
Barry,DeclanT
Barry,DeclanT
中科院分区:
医学3区
文献类型:
--
作者:
Moore,BrentA;Buono,FrankD;Printz,DestinyMB;Lloyd,DanielP;Fiellin,DavidA;Cutter,ChristopherJ;Schottenfeld,RichardS;Barry,DeclanT

文献摘要

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The Recovery Line is an automated, computer-based intervention based on cognitive behavioral therapy (CBT) designed to provide real-time assistance by phone for patients in methadone maintenance. Preliminary efficacy findings were promising, however, as with other computer-based systems for substance use disorder, patient system use was less than recommended. Development and evaluation of system functions to increase patient engagement and use is needed. Thus, we conducted two randomized trials to evaluate system functions designed to increase patient use of the Recovery Line among methadone-maintained patients with continued illicit drug use. In Trial 1 (n= 60), patients received customized, system use recommendations or no recommendations on each Recovery Line call. Ratings of system usability were higher for customized recommendations (CR), but number of calls and total call time did not differ by condition. Trial 2 evaluated characteristics of reminder messages (message frame and reminder latency). Participants (N= 67) received gain-and loss-frame reminder messages, and were randomly assigned to immediate, short, or long term message latency. Although message framing had no effect, gender interacted with latency condition such that females did not differ by message latency, while males had significantly greater total contact time in the short latency conditions. Number of calls differed by condition over time such that the shorter latencies led to greater calls initially, but dissipated over time. Overall the study indicates that computer-based self-management systems can be adapted to increase patient engagement and use.(PsycInfo Database Record (c) 2020 APA, all rights reserved)