Mathematical Modeling of Intoxicated Risky Decision Making
Mathematical Modeling of Intoxicated Risky Decision Making
批准号:
9759539
负责人:
Laura E Hatz
金额:
$3.53万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2021-06-30
关键词:
AcuteAgeAlcohol consumptionAlcohol or Other Drugs useAlcoholic IntoxicationAlcoholsAreaBehaviorBehavioralBehavioral inhibitionBeveragesChoice BehaviorCognitiveComplexConsumptionCuesDataDecision MakingDecision ModelingDevelopmentDiffusionDoseDouble-Blind MethodEducational workshopFosteringGamblingGoalsHealthHumanImpulsivityIndividual DifferencesJudgmentLaboratoriesMeasuresMethodsModelingParticipantPatient Self-ReportPerformancePersonsPharmacologyPlacebo EffectPlacebosProcessReaction TimeResearchResearch PersonnelRiskRisk-TakingSamplingSex BehaviorSexually Transmitted DiseasesStatistical Data InterpretationStructureTechniquesTestingTrainingTranslatingVariantWitWorkaddictionalcohol consequencesalcohol effectalcohol pharmacologybasebehavior measurementbreath alcohol measurementcareercognitive processdesigndiscountdiscountingheuristicshigh risk sexual behaviorindexinginfection riskinnovationmathematical modelmeetingsmultidisciplinarynovelpreferencepreventprogramspsychologicrecruitsexual risk takingskill acquisitionskillssymposiumtherapy designtrait
中文摘要
(7)项目总结/摘要
长期目标:本应用程序的首要目标是(1)使用数学模型,
决策,以更好地了解参与酒精相关的负面行为的风险,并(2)使用
过程模型来测试关于酒精对冲动性认知过程的影响的新假设。
申请人的主要职业目标是开发一个研究计划,将复杂的定量分析
使用严格的实验室成瘾技术建模方法来描述酒精对风险的影响
采取行动。
具体目标:拟议的项目旨在(1)模拟急性酒精对决策策略的影响
和风险性行为偏好的可变性,以及(2)应用过程模型(例如,扩散模型),
传统的冲动性实验室测量将行为数据分解为心理相关的
认知处理的组成部分(例如,证据积累率、非决策过程)。为了
完成拟议的项目,申请人将获得广泛的培训,在创新的数学
在判断和决策领域的专家建模技术。培训将通过
(1)课程作业,(2)出席会议和讲习班,(3)与专家顾问举行会议,
认知过程模型和酒精相关的冲动。
方法:申请人将招募40名参与者(年龄21-29岁),完成受试者内双盲
酒精/安慰剂给药研究。每个参与者将完成三个会议,在此期间,他们将
饮用低-中等剂量的酒精、中-高剂量的酒精或安慰剂饮料
(在各届会议上平衡)。饮料管理后,参与者将完成延迟
贴现任务,暗示去/不去任务,以及评估假设的货币和性决策的任务。
将使用旨在评估离散特征的数学建模方法(例如,
决策策略,偏好变异性,证据积累率)的选择行为,而不是
通过传统的分析技术。统计分析将评估(1)酒精剂量和安慰剂
对决策特征的影响,以及(2)这些特征与自我报告的酒精之间的关联-
相关的负面行为。
意义:本项目的结果将增加对酒精相关因素的理解。
风险决策。这些发现将有助于阐明酒精的药理作用的个体差异,
对冒险行为的影响,并可能最终有助于为预防和减少伤害提供信息
与酒精使用有关。
英文摘要
(7) Project Summary/Abstract
Long Term Objectives: The overarching goals of this application are to (1) use mathematical models of
decision making to better understand risk for engagement in alcohol-related negative behaviors, and to (2) use
process models to test novel hypotheses about alcohol’s effects on cognitive processes underlying impulsivity.
The applicant’s main career objective is to develop a program of research integrating sophisticated quantitative
modeling approaches with rigorous laboratory addictions techniques to characterize alcohol’s effects on risk
taking behaviors.
Specific Aims: The proposed project aims to (1) model acute alcohol effects on decision making strategies
and variability in preference in risky sexual behavior, and (2) apply process models (e.g., diffusion models) to
traditional laboratory measures of impulsivity to decompose behavioral data into psychologically relevant
components of cognitive processing (e.g., rate of evidence accumulation, non-decision processes). In order to
complete the proposed project, the applicant will receive extensive training in innovative mathematical
modeling techniques from experts in the field of judgment and decision making. Training will be obtained via
(1) coursework, (2) conference and workshop attendance, and (3) meetings with expert consultants in
cognitive process models and alcohol-related impulsivity.
Method: The applicant will recruit 40 participants (ages 21-29) to complete a within-subjects double-blind
alcohol/placebo administration study. Each participant will complete three sessions during which they will
consume a low-moderate dose of alcohol, a moderate-high dose of alcohol, or a placebo beverage
(counterbalanced across sessions). Following beverage administration, participants will complete a delay
discounting task, cued go/no-go task, and tasks assessing hypothetical monetary and sexual decision making.
Data will be analyzed using mathematical modeling approaches designed to assess discrete features (e.g.,
decision making strategy, preference variability, evidence accumulation rate) of choice behavior that are not
assessed via traditional analytic techniques. Statistical analyses will assess (1) alcohol dose and placebo
effects on features of decision making and (2) associations between these features and self-reported alcohol-
related negative behaviors.
Significance: Results from this project will increase understanding of factors contributing to alcohol-related
risky decision making. These findings will help to clarify individual differences in alcohol’s pharmacological
effects on risk taking behaviors, and may ultimately help to inform efforts to prevent and reduce harm
associated with alcohol use.
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