Treatment Effect Heterogeneity in Psychosocial Treatments for Substance Use Disorders
药物使用障碍心理社会治疗的治疗效果异质性
基本信息
- 批准号:10683066
- 负责人:
- 金额:$ 28.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-07-31
- 项目状态:未结题
- 来源:
- 关键词:AbstinenceAccelerationAddressAgeAlgorithmsClinicalClinical Trials NetworkDataData AnalysesDiseaseDrug abuseEducationFamily psychotherapyFrequenciesGoalsHealth PersonnelHeterogeneityIncentivesIndividualInterventionMeasuresMethodologyMethodsMotivationNational Institute of Drug AbuseOutcomeParticipantPatientsPerformancePersonsPhenotypeProviderRandomized, Controlled TrialsRecoveryResearchRiskSafetySeveritiesStatistical MethodsSubgroupSubstance Use DisorderSymptomsSystemTechniquesTestingTherapeuticTreatment outcomeWorkclinically relevantdata harmonizationdata sharingdrug abstinenceeffectiveness evaluationevidence baseexercise programexperienceforestindividual patientindividual variationmotivational enhancement therapynovelpolysubstance useprecision medicinepreventpsychiatric comorbiditypsychosocialresponsescreeningsexshared repositorysociodemographicssubstance usesubstance use treatmenttreatment as usualtreatment effecttreatment research
项目摘要
Project Summary
The goal of this application, submitted in response to PAR-19-368, “Accelerating the Pace of Drug Abuse
Research Using Existing Data” is to leverage data from the NIDA Clinical Trials Network to enhance our
understanding of treatment effect heterogeneity in psychosocial treatments for substance use disorders.
Treatment effect heterogeneity is particularly a concern in research of substance use disorder treatments, in
part due to heterogeneous sub-phenotypes of patients in symptom profile, disease course, and recovery
trajectory. Nevertheless, analysis of treatment effect heterogeneity in substance use disorder research has
been often conducted in a suboptimal manner using subgroup analysis (i.e., estimating impacts separately
within groups defined by a single covariate), which could result in finding spurious differences in treatment
effects by subgroup due to the performance of multiple statistical tests and random variability across patients.
Another challenge of single covariate-based subgroup analysis is that most covariates have small moderating
effects and their individual contribution to treatment effect heterogeneity is not meaningfully informative to
treatment decisions. Our objective is to apply a novel statistical method, causal forest approach, to
systematically examine treatment effect heterogeneity of psychosocial treatments for substance use disorders.
This study uses data from 12 randomized controlled trials in the NIDA Clinical Trials Network which examined
effectiveness of nine distinct psychosocial treatments against treatment-as-usual condition (Motivational
Incentives, Motivational Enhancement Therapy, Screening Motivational Assessment, Therapeutic Education
System, Brief Strategic Family Therapy, Twelve-Step Facilitation, Motivational Interviewing, Seeking Safety,
and Exercise Program). For each type of psychosocial treatment, we propose to implement the causal forest
approach to estimate the expected effect of a treatment for each individual while taking into account multiple
covariates simultaneously. The estimated treatment effects will be used to test the presence and degree of
treatment effect heterogeneity in each type of psychosocial treatment. Using the variable importance measure
obtained from the causal forest, we also plan to identify the most important covariates contributing to treatment
effect heterogeneity in each type of psychosocial treatment. These analyses will be repeated for multiple
outcomes (e.g., abstinence, reduction in frequency of target substance use) to examine whether and how the
degree of treatment effect heterogeneity as well as common effect moderators differ across outcomes. Overall,
these analyses will grow the evidence base that can be used by treatment providers to guide treatment
decisions for individual patients with substance use disorders.
项目总结
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Ryoko Susukida其他文献
Ryoko Susukida的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Ryoko Susukida', 18)}}的其他基金
Treatment Effect Heterogeneity in Psychosocial Treatments for Substance Use Disorders
药物使用障碍心理社会治疗的治疗效果异质性
- 批准号:
10363799 - 财政年份:2022
- 资助金额:
$ 28.66万 - 项目类别:
相似海外基金
EXCESS: The role of excess topography and peak ground acceleration on earthquake-preconditioning of landslides
过量:过量地形和峰值地面加速度对滑坡地震预处理的作用
- 批准号:
NE/Y000080/1 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Research Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328975 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Continuing Grant
SHINE: Origin and Evolution of Compressible Fluctuations in the Solar Wind and Their Role in Solar Wind Heating and Acceleration
SHINE:太阳风可压缩脉动的起源和演化及其在太阳风加热和加速中的作用
- 批准号:
2400967 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Standard Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328973 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Continuing Grant
Market Entry Acceleration of the Murb Wind Turbine into Remote Telecoms Power
默布风力涡轮机加速进入远程电信电力市场
- 批准号:
10112700 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Collaborative R&D
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328972 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Continuing Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328974 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Continuing Grant
Collaborative Research: A new understanding of droplet breakup: hydrodynamic instability under complex acceleration
合作研究:对液滴破碎的新认识:复杂加速下的流体动力学不稳定性
- 批准号:
2332916 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Standard Grant
Collaborative Research: A new understanding of droplet breakup: hydrodynamic instability under complex acceleration
合作研究:对液滴破碎的新认识:复杂加速下的流体动力学不稳定性
- 批准号:
2332917 - 财政年份:2024
- 资助金额:
$ 28.66万 - 项目类别:
Standard Grant
Study of the Particle Acceleration and Transport in PWN through X-ray Spectro-polarimetry and GeV Gamma-ray Observtions
通过 X 射线光谱偏振法和 GeV 伽马射线观测研究 PWN 中的粒子加速和输运
- 批准号:
23H01186 - 财政年份:2023
- 资助金额:
$ 28.66万 - 项目类别:
Grant-in-Aid for Scientific Research (B)














{{item.name}}会员




