Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults with Emotional Distress
Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults with Emotional Distress
批准号:
10031359
负责人:
Olusola A. Ajilore
金额:
$211.25万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-03 至 2022-07-25
关键词:
AddressAdultAffectAmygdaloid structureAnxietyAreaArtificial IntelligenceAttitudeBrainCaringClinicalCognitionCognitiveComputer softwareDevelopmentDevicesDorsalDoseEmotionalEmotionsEngineeringEnrollmentEvaluationFaceFocus GroupsFunctional Magnetic Resonance ImagingFunctional disorderFutureGeneralized Anxiety DisorderHealthHealth PromotionHealth ResourcesHumanImage AnalysisIntelligenceLateralLengthMachine LearningMeasurementMeasuresMediatingMedicineMental DepressionMental HealthMental Health ServicesMoodsNamesNeurosciencesOutcomeParticipantPatient Outcomes AssessmentsPatient Self-ReportPatientsPersonal SatisfactionPersonsPhasePrefrontal CortexProblem SolvingProceduresProcess MeasureProductivityProfessional counselorProtocols documentationPsychotherapyPublic HealthQuality of lifeQuestionnairesRandomizedRandomized Clinical TrialsResearchSecureSpecific qualifier valueStressSurveysSymptomsTechniquesTestingTherapeuticTimeTrainingTranslatingTreatment EfficacyUnited States National Institutes of HealthVoiceVoice TrainingWaiting Listsactive controlactive methodanxiety symptomsarmbasebehavioral health interventionclinical decision supportcognitive controlcopingcostdepressive symptomsdigitaldisabilityefficacy testingemotional distressexperiencefollow up assessmentformative assessmentimprovedinnovationinsightintelligent agentiterative designknowledge basemeetingsneural circuitneuromechanismnew technologynovelproblem solving therapyprototyperecruitrelating to nervous systemsocial stigmatargeted treatmenttheoriestreatment armtreatment optimizationusabilityuser centered designvirtual
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PROJECT SUMMARY
BACKGROUND: Depression and anxiety are the leading causes of disability and lost productivity, and are
often underdiagnosed and undertreated owing to access, cost, and stigma barriers. Novel and scalable
psychotherapies are urgently needed. Advances in artificial intelligence (AI) offer a transformative opportunity
to develop intelligent voice assistants as virtual health agents accessible on personal devices. Meanwhile,
major advances in human neuroscience have fueled a paradigm shift to study brain mechanisms underlying
behavioral health interventions. OBJECTIVES: Leveraging our collaborative team’s transdisciplinary expertise
in these emerging areas, we will develop and rigorously test a novel voice-enabled, AI virtual agent named
Lumen, trained on Problem Solving Therapy (PST), for patients with moderate, untreated depressive and/or
anxiety symptoms. We will investigate the effect of Lumen on engagement of a priori neural targets—amygdala
for emotional reactivity and dorsal lateral prefrontal cortex (DLPFC) for cognitive control—as putative
mechanisms. DESIGN/ METHODS: The project has 2 phases. In the R61 phase (years 1-2), we will further
develop Lumen building on the current prototype and conduct iterative user-centered design evaluations that
include focus groups, scenario-based clinician evaluations, and a formative user study with 20 participants. We
will pilot test Lumen in a 2-arm randomized clinical trial (RCT, Study 1), with 60 participants with depression
and/or anxiety randomized in a 2:1 ratio to receive PST with Lumen (n=40) on a secure study iPad or be on a
waitlist (n=20). At weeks 0 and 14, participants will complete functional magnetic resonance imaging (fMRI) to
assess neural target engagement as well as validated surveys of patient-reported outcomes (e.g., depressive
and anxiety symptoms, functioning, quality of life). In addition, they will complete naturalistic end-of-day
assessments of mood, stress, appraisal and coping for 7 days every 2 weeks. If the Go milestone criteria are
met, the R33 phase (years 3-5) will include a 3-arm RCT (Study 2) with 200 new participants randomized in a
2:1:1 ratio to 1 of 3 arms: Lumen (n=100), waitlist control (n=50), and in-person PST as active control (n=50).
Participants will complete baseline and follow-up assessments using a refined measurement protocol based on
Study 1. SPECIFIC AIMS: R61 aims are to (1) establish the functionality, usability, and treatment fidelity of
Lumen; and (2) demonstrate feasibility, acceptability, and neural target engagement according to pre-specified
Go milestone criteria. R33 aims are to (1) confirm neural target engagement by a superiority test (primary)
comparing the Lumen and waitlist control arms and a noninferiority test (secondary) comparing the Lumen and
in-person PST arms; and (2) examine the relationships of target engagement to outcomes. The results will
provide the basis for future confirmatory efficacy testing of Lumen. IMPACT: This project’s public health impact
lies in that a mechanistically tested, PST-trained AI agent could bring proven psychotherapy to people with
depression/anxiety who do not seek professional help or who desire more personalized, connected care.
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DOI:
10.1038/s41398-023-02462-x
发表时间:
2023-05-12
期刊:
TRANSLATIONAL PSYCHIATRY
影响因子:
6.8
作者:
[Kannampallil, Thomas, Ajilore, Olusola A., Lv, Nan, Smyth, Joshua M., Wittels, Nancy E., Ronneberg, Corina R., Kumar, Vikas, Xiao, Lan, Dosala, Susanth, Barve, Amruta, Zhang, Aifeng, Tan, Kevin C., Cao, Kevin K., Patel, Charmi R., Gerber, Ben S., Johnson, Jillian A., Kringle, Emily A., Ma, Jun]
通讯作者:
Ma, Jun
DOI:
10.2196/49715
发表时间:
2023-11-06
期刊:
JMIR HUMAN FACTORS
影响因子:
2.7
作者:
[Lv, Nan, Kannampallil, Thomas, Xiao, Lan, Ronneberg, Corina R, Kumar, Vikas, Wittels, Nancy E, Ajilore, Olusola A, Smyth, Joshua M, Ma, Jun]
通讯作者:
Ma, Jun
DOI:
10.2196/38092
发表时间:
2022-08-12
期刊:
JMIR FORMATIVE RESEARCH
影响因子:
2.2
作者:
[Kannampallil, Thomas, Ronneberg, Corina R., Wittels, Nancy E., Kumar, Vikas, Lv, Nan, Smyth, Joshua M., Gerber, Ben S., Kringle, Emily A., Johnson, Jillian A., Yu, Philip, Steinman, Lesley E., Ajilore, Olu A., Ma, Jun]
通讯作者:
Ma, Jun
Associations between daily step count trajectories and clinical outcomes among adults with comorbid obesity and depression.
患有肥胖症和抑郁症的成年人的每日步数轨迹与临床结果之间的关联。
DOI:
10.1016/j.mhpa.2023.100512
发表时间:
2023
期刊:
Mental health and physical activity
影响因子:
4.7
作者:
[Kringle,EmilyA, Tucker,Danielle, Wu,Yichao, Lv,Nan, Kannampallil,Thomas, Barve,Amruta, Dosala,Sushanth, Wittels,Nancy, Dai,Ruixuan, Ma,Jun]
通讯作者:
Ma,Jun
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
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批准号:10406131
-
项目类别:
-
资助金额:$22.93万
-
财政年份:2020
-
负责人:Olusola A. Ajilore
-
依托单位:
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
-
批准号:10542659
-
项目类别:
-
资助金额:$63.09万
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财政年份:2020
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负责人:Olusola A. Ajilore
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依托单位:
3/3-Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression
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批准号:10532208
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项目类别:
-
资助金额:$56.21万
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财政年份:2020
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负责人:Olusola A. Ajilore
-
依托单位:
Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults with Emotional Distress
-
批准号:10671735
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项目类别:
-
资助金额:$108.83万
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财政年份:2020
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负责人:Olusola A. Ajilore
-
依托单位:
Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults with Emotional Distress
-
批准号:10611145
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项目类别:
-
资助金额:$108.87万
-
财政年份:2020
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负责人:Olusola A. Ajilore
-
依托单位:
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
-
批准号:10320061
-
项目类别:
-
资助金额:$62.77万
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财政年份:2020
-
负责人:Olusola A. Ajilore
-
依托单位:
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
-
批准号:10115131
-
项目类别:
-
资助金额:$57.94万
-
财政年份:2020
-
负责人:Olusola A. Ajilore
-
依托单位:
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
-
批准号:9912649
-
项目类别:
-
资助金额:$62.18万
-
财政年份:2020
-
负责人:Olusola A. Ajilore
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依托单位:
3/3-Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression
-
批准号:10078636
-
项目类别:
-
资助金额:$60.52万
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财政年份:2020
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负责人:Olusola A. Ajilore
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依托单位:
3/3-Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression
-
批准号:10304162
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项目类别:
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资助金额:$64.59万
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财政年份:2020
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Improving white matter integrity with thyroid hormone
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批准号:9182242
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负责人:Olusola A. Ajilore
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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批准号:8171073
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项目类别:
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资助金额:$0.61万
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财政年份:2010
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负责人:Olusola A. Ajilore
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依托单位:
Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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批准号:7587566
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负责人:Olusola A. Ajilore
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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批准号:7955684
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Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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财政年份:2009
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负责人:Olusola A. Ajilore
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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