Mapping the co-evolution of Craving, Affect, Stressors, and Access to Alcohol (CASA) using responsive EMA
Mapping the co-evolution of Craving, Affect, Stressors, and Access to Alcohol (CASA) using responsive EMA
批准号:
10403674
负责人:
Bilal Khan
金额:
$14.58万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-05-10 至 2024-04-30
关键词:
AddressAdherenceAdultAffectAftercareAlaskaAlcohol abuseAlcohol consumptionAlcoholsAttentionBehavioralBuffersCaringCellular PhoneChronicCitiesCognitiveCommunitiesComputer softwareDataData AnalysesData CollectionData SetDevelopmentDiagnosisDimensionsDrug usageDrug userEcological momentary assessmentEnrollmentEnvironmental ImpactEnvironmental Risk FactorEventEvidence based interventionEvolutionExposure toFailureFemaleFoundationsFrequenciesFutureGoalsGrainGreat PlainsHandHomelessnessHousingIncentivesIndependent LivingIndividualInterventionInterviewKnowledgeLinkLocationMental HealthMethodologyModalityModelingMonitorMoodsNational Institute on Alcohol Abuse and AlcoholismNew York CityOutcomeParticipantPathway interactionsPatientsPatternPersonsPhasePilot ProjectsPopulationPovertyPrevalenceProcessProtocols documentationPublic HealthPuerto RicoRecoveryRelapseResearchResearch PersonnelResidential FacilitiesResidential TreatmentRiskRisk BehaviorsRisk FactorsRoleRuralSocial supportSourceStressSuicide preventionSystemTechnologyTeenagersTestingTimeTranscendWorkalcohol abuse therapyalcohol availabilityalcohol outlet densityalcohol use disorderbasecohortcontextual factorscostcost effectivecravingdata accessdata modelingdesigndisorder later incidence preventiondistilled alcoholic beveragedrinkingenvironmental stressorexperiencehigh riskimprovedinnovationinpatient serviceintervention deliverymHealthmachine learning algorithmmachine learning modelmeetingsmembermobile computingnegative affectnext generationnovelprecision medicinepredictive modelingproblem drinkerprogramsprotective factorspsychologicpsychosocialpublic health researchrecruitrelapse predictionrelapse riskresponseservice interventionsobrietysocialspatiotemporalstressorsubstance usesubstance use treatmentsuccesstreatment programtreatment services
中文摘要
摘要
英文摘要
ABSTRACT
Recovering from Alcohol Use Disorders (AUD) following treatment is difficult, with 43-83% relapsing post-
discharge. These chronically high rates arise, in part, because of a gap in our knowledge about the co-evolution
of in the moment risk mechanisms associated with relapse among those recovering from AUD, including Craving,
Negative Affect, Stressors and Access to alcohol (CASA). These four factors co-evolve among important
protective factors that buffer relapse risk (e.g., improved sober support and psychosocial function associated
with post-treatment community AUD recovery programs), and context-based risk factors such as near-at-hand
places where alcohol is available. The immediate goal of this project is to develop the means to assess and
understand the impact of these environmental/contextual factors for recovering alcoholics, towards a longer term
research objective of developing effective just-in-time interventions that mitigate the risk of relapse. In this project,
we will leverage novel assessment methodologies via a responsive ecological momentary assessment (rEMA)
system developed by our team. This app-based system allows researchers to incorporate geospatial, time-
specific and event-specific criteria for enhanced monitoring of (and just-in-time delivery of interventions to)
recovering patients in post-treatment settings. Consistent with PA-18-620 from NIAAA, this project aims to build
foundational evidence and refine the data collection/analysis strategy needed to achieve our long term objective,
via the following specific aims: Aim 1) Pilot the use of our rEMA platform to capture fine-grained longitudinal data
on Craving, Affect, Stressors and Access to alcohol among 60 recovering alcoholics across 30 days, to evaluate
CASA construct validity within rEMA data and assess the extent and impact of data missingness; Aim 2) Test
incentive modalities that will inform us regarding best practices that maximize adherence to the rEMA protocol;
Aim 3) Develop analytic strategies based machine-learning models of rEMA data, to forecast imminent risk and
quantify causal pathways among CASA variables. To accomplish these aims, we will recruit and enroll adults
(n=60; 50% female) in non-hospitalized residential AUD treatments in the Central Plains. Using smartphone
assessment with GPS monitoring technology, we will collect longitudinal behavioral and experiential data from
each participant over 30 days. Analysis of these data will advance our understanding of co-evolving
contextual/social-environmental factors that impact the success/failure of the recovery effort, while establishing
foundational evidence from which time/event-specific smartphone-based just-in-time interventions may be
developed. The final phase of the project includes the creation of an advisory and dissemination board composed
of local and national-level stakeholders, AUD treatment practitioners and other researchers that will guide the
development of such an intervention. Included in this group are the directors of two non-hospitalized residential
substance treatment facilities that function as community partners for the project through all project stages.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1371/journal.pone.0288940
发表时间:
2023
期刊:
PloS one
影响因子:
3.7
作者:
[]
通讯作者:
Mapping the co-evolution of Craving, Affect, Stressors, and Access to Alcohol (CASA) using responsive EMA
-
批准号:10196353
-
项目类别:
-
资助金额:$26.24万
-
财政年份:2021
-
负责人:Bilal Khan
-
依托单位:
Longitudinal Networks Core
-
批准号:10117084
-
项目类别:
-
资助金额:$45.42万
-
财政年份:2019
-
负责人:Bilal Khan
-
依托单位:
Longitudinal Networks Core
-
批准号:10377944
-
项目类别:
-
资助金额:$39.5万
-
财政年份:2019
-
负责人:Bilal Khan
-
依托单位:
Longitudinal Networks Core
-
批准号:9908116
-
项目类别:
-
资助金额:$49.44万
-
财政年份:--
-
负责人:Bilal Khan
-
依托单位:
海外基金