Initial evaluation of a personalized advantage index to determine which individuals may benefit from mindfulness-based cognitive therapy for suicide prevention

IF 4.2 2区 心理学 Q1 PSYCHOLOGY, CLINICAL Behaviour Research and Therapy Pub Date : 2024-09-18 DOI:10.1016/j.brat.2024.104637
Catherine E. Myers , Chintan V. Dave , Megan S. Chesin , Brian P. Marx , Lauren M. St. Hill , Vibha Reddy , Rachael B. Miller , Arlene King , Alejandro Interian
{"title":"Initial evaluation of a personalized advantage index to determine which individuals may benefit from mindfulness-based cognitive therapy for suicide prevention","authors":"Catherine E. Myers ,&nbsp;Chintan V. Dave ,&nbsp;Megan S. Chesin ,&nbsp;Brian P. Marx ,&nbsp;Lauren M. St. Hill ,&nbsp;Vibha Reddy ,&nbsp;Rachael B. Miller ,&nbsp;Arlene King ,&nbsp;Alejandro Interian","doi":"10.1016/j.brat.2024.104637","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>Develop and evaluate a treatment matching algorithm to predict differential treatment response to Mindfulness-Based Cognitive Therapy for suicide prevention (MBCT-S) versus enhanced treatment-as-usual (eTAU).</div></div><div><h3>Methods</h3><div>Analyses used data from Veterans at high-risk for suicide assigned to either MBCT-S (n = 71) or eTAU (n = 69) in a randomized clinical trial. Potential predictors (n = 55) included available demographic, clinical, and neurocognitive variables. Random forest models were used to predict risk of suicidal event (suicidal behaviors, or ideation resulting in hospitalization or emergency department visit) within 12 months following randomization, characterize the prediction, and develop a Personalized Advantage Index (PAI).</div></div><div><h3>Results</h3><div>A slightly better prediction model emerged for MBCT-S (AUC = 0.70) than eTAU (AUC = 0.63). Important outcome predictors for participants in the MBCT-S arm included PTSD diagnosis, decisional efficiency on a neurocognitive task (Go/No-Go), prior-year mental health residential treatment, and non-suicidal self-injury. Significant predictors for participants in the eTAU arm included past-year acute psychiatric hospitalizations, past-year outpatient psychotherapy visits, past-year suicidal ideation severity, and attentional control (indexed by Stroop task). A moderation analysis showed that fewer suicidal events occurred among those randomized to their PAI-indicated optimal treatment.</div></div><div><h3>Conclusions</h3><div>PAI-guided treatment assignment may enhance suicide prevention outcomes. However, prior to real-world application, additional research is required to improve model accuracy and evaluate model generalization.</div></div>","PeriodicalId":48457,"journal":{"name":"Behaviour Research and Therapy","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behaviour Research and Therapy","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0005796724001645","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Objective

Develop and evaluate a treatment matching algorithm to predict differential treatment response to Mindfulness-Based Cognitive Therapy for suicide prevention (MBCT-S) versus enhanced treatment-as-usual (eTAU).

Methods

Analyses used data from Veterans at high-risk for suicide assigned to either MBCT-S (n = 71) or eTAU (n = 69) in a randomized clinical trial. Potential predictors (n = 55) included available demographic, clinical, and neurocognitive variables. Random forest models were used to predict risk of suicidal event (suicidal behaviors, or ideation resulting in hospitalization or emergency department visit) within 12 months following randomization, characterize the prediction, and develop a Personalized Advantage Index (PAI).

Results

A slightly better prediction model emerged for MBCT-S (AUC = 0.70) than eTAU (AUC = 0.63). Important outcome predictors for participants in the MBCT-S arm included PTSD diagnosis, decisional efficiency on a neurocognitive task (Go/No-Go), prior-year mental health residential treatment, and non-suicidal self-injury. Significant predictors for participants in the eTAU arm included past-year acute psychiatric hospitalizations, past-year outpatient psychotherapy visits, past-year suicidal ideation severity, and attentional control (indexed by Stroop task). A moderation analysis showed that fewer suicidal events occurred among those randomized to their PAI-indicated optimal treatment.

Conclusions

PAI-guided treatment assignment may enhance suicide prevention outcomes. However, prior to real-world application, additional research is required to improve model accuracy and evaluate model generalization.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
对个性化优势指数进行初步评估,以确定哪些人可能受益于以正念为基础的认知疗法来预防自杀。
目的:开发并评估一种治疗匹配算法,以预测基于正念的认知疗法预防自杀(MBCT-S)与强化治疗(eTAU)的不同治疗反应:开发并评估一种治疗匹配算法,以预测预防自杀的正念认知疗法(MBCT-S)与常规强化治疗(eTAU)的不同治疗反应:分析使用了在随机临床试验中被分配接受MBCT-S(n = 71)或eTAU(n = 69)治疗的高自杀风险退伍军人的数据。潜在的预测因素(n = 55)包括现有的人口统计学、临床和神经认知变量。随机森林模型用于预测随机化后12个月内发生自杀事件(自杀行为或导致住院或急诊就诊的意念)的风险,描述预测结果,并制定个性化优势指数(PAI):结果:MBCT-S(AUC = 0.70)的预测模型略优于 eTAU(AUC = 0.63)。MBCT-S组参与者的重要结果预测因素包括创伤后应激障碍诊断、神经认知任务(Go/No-Go)的决策效率、前一年的心理健康住院治疗以及非自杀性自伤。eTAU治疗组参与者的重要预测因素包括过去一年的急性精神病住院治疗、过去一年的门诊心理治疗就诊次数、过去一年的自杀意念严重程度和注意力控制(以Stroop任务为指标)。调节分析表明,在随机接受PAI指示的最佳治疗的患者中,自杀事件发生率较低:结论:PAI 指导下的治疗分配可提高自杀预防效果。然而,在实际应用之前,还需要进行更多的研究来提高模型的准确性并评估模型的通用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Behaviour Research and Therapy
Behaviour Research and Therapy PSYCHOLOGY, CLINICAL-
CiteScore
7.50
自引率
7.30%
发文量
148
期刊介绍: The major focus of Behaviour Research and Therapy is an experimental psychopathology approach to understanding emotional and behavioral disorders and their prevention and treatment, using cognitive, behavioral, and psychophysiological (including neural) methods and models. This includes laboratory-based experimental studies with healthy, at risk and subclinical individuals that inform clinical application as well as studies with clinically severe samples. The following types of submissions are encouraged: theoretical reviews of mechanisms that contribute to psychopathology and that offer new treatment targets; tests of novel, mechanistically focused psychological interventions, especially ones that include theory-driven or experimentally-derived predictors, moderators and mediators; and innovations in dissemination and implementation of evidence-based practices into clinical practice in psychology and associated fields, especially those that target underlying mechanisms or focus on novel approaches to treatment delivery. In addition to traditional psychological disorders, the scope of the journal includes behavioural medicine (e.g., chronic pain). The journal will not consider manuscripts dealing primarily with measurement, psychometric analyses, and personality assessment.
期刊最新文献
The future of the eating disorder field: Inclusive, aware of systems, and personalized Active contextualization reduces traumatic memory intrusions via memory integration Augmented Depression Therapy for young adults: A mixed methods randomised multiple baseline case series evaluation Leveraging occasional reinforced extinction via mental imagery of the unconditioned stimulus to optimize extinction learning Examining the moderating role of depressive symptoms on the dynamic interplay between cognitive reappraisal and rumination: Evidence from experience sampling
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1