Adam Chekroud, PhD
Cards
About
Titles
Assistant Professor Adjunct, Psychiatry
Biography
Adam's research seeks to improve treatment outcomes in mental health, particularly depression. Specifically, he uses large datasets to develop predictive models to help clinicians make more effective treatment decision. For example, he has developed statistical models that can: anticipate which patients will not initiate treatment; predict which treatment is most likely to help an individual patient (specific medications, psychotherapies, and exercise regimens); and estimate the risk of relapse upon recovery. His research has been featured in JAMA Psychiatry, Lancet Psychiatry, Molecular Psychiatry, and PNAS. He is also co-founder of a mental health startup called Spring Health, based in New York City. Spring works with large employers like GAP and Whole Foods to provide their employees with free and immediate access to high-quality mental healthcare. The company has raised over $8M and has over 600 providers in its network.
Education & Training
- PhD
- Yale University, Psychology (2018)
- MSc
- Oxford University, Neuroscience (2013)
- BA
- Oxford University, Experimental Psychology (2010)
Research
Publications
2024
Illusory generalizability of clinical prediction models
Chekroud A, Hawrilenko M, Loho H, Bondar J, Gueorguieva R, Hasan A, Kambeitz J, Corlett P, Koutsouleris N, Krumholz H, Krystal J, Paulus M. Illusory generalizability of clinical prediction models. Science 2024, 383: 164-167. PMID: 38207039, DOI: 10.1126/science.adg8538.Peer-Reviewed Original Research
2023
Personalized symptom clusters that predict depression treatment outcomes: A replication of machine learning methods
Chen Y, Stewart J, Ge J, Cheng B, Chekroud A, Hellerstein D. Personalized symptom clusters that predict depression treatment outcomes: A replication of machine learning methods. Journal Of Affective Disorders Reports 2023, 11: 100470. DOI: 10.1016/j.jadr.2023.100470.Peer-Reviewed Original ResearchHamilton Rating ScaleSymptom clustersTreatment trajectoriesQuick InventoryTreatment outcomesDouble-blind clinical trialDepressive Symptomatology-Self ReportRating ScaleBest baseline predictorsHAM-D scoresDepression treatment outcomesAnxiety disorder diagnosisQIDS-SR16Depressive illnessEscitalopram monotherapyBaseline variablesClinical trialsBaseline predictorsTreatment efficacyUnipolar depressionDifferent treatment trajectoriesTreatment planLogistic regressionDisorder diagnosisDual treatmentBroadening the Use of Machine Learning in Psychiatry
Adkinson B, Chekroud A. Broadening the Use of Machine Learning in Psychiatry. Biological Psychiatry 2023, 93: 4-5. PMID: 36456077, DOI: 10.1016/j.biopsych.2022.10.006.Peer-Reviewed Original Research
2022
Clinical and Financial Outcomes Associated With a Workplace Mental Health Program Before and During the COVID-19 Pandemic
Bondar J, Morrow C, Gueorguieva R, Brown M, Hawrilenko M, Krystal JH, Corlett PR, Chekroud AM. Clinical and Financial Outcomes Associated With a Workplace Mental Health Program Before and During the COVID-19 Pandemic. JAMA Network Open 2022, 5: e2216349. PMID: 35679044, PMCID: PMC9185188, DOI: 10.1001/jamanetworkopen.2022.16349.Peer-Reviewed Original ResearchConceptsMental health programsHealth programsCohort studyLarge clinical effect sizesPatient Health Questionnaire-9Common mental health conditionsSheehan Disability ScaleClinical effect sizeMental health conditionsMental health symptomsCost of treatmentGeneralized anxiety disorderMental health difficultiesMental health benefitsWorkplace wellness programsCare navigationClinical improvementPrimary outcomeClinical benefitQuestionnaire-9Disability ScaleMedication managementLeast moderate anxietyMixed-effects regressionPerson psychotherapy
2021
Trends in inpatient care for psychiatric disorders in NHS hospitals across England, 1998/99–2019/20: an observational time series analysis
Degli Esposti M, Ziauddeen H, Bowes L, Reeves A, Chekroud A, Humphreys D, Ford T. Trends in inpatient care for psychiatric disorders in NHS hospitals across England, 1998/99–2019/20: an observational time series analysis. Social Psychiatry And Psychiatric Epidemiology 2021, 57: 993-1006. PMID: 34951652, PMCID: PMC8705084, DOI: 10.1007/s00127-021-02215-5.Peer-Reviewed Original ResearchConceptsObservational time series analysisPsychiatric disordersBed daysAdmission ratesHospital activityAge groupsNHS hospitalsBinomial regression modelsNegative binomial regression modelsInpatient psychiatric careMental health needsInpatient hospital activityHospital admissionRegression modelsInpatient carePsychiatric careHealth needsHospitalDisordersCareDepressionAdultsPronounced increaseSame periodChildrenParsing the antidepressant effects of non-invasive brain stimulation and pharmacotherapy: A symptom clustering approach on ELECT-TDCS
Goerigk S, Padberg F, Chekroud A, Kambeitz J, Bühner M, Brunoni A. Parsing the antidepressant effects of non-invasive brain stimulation and pharmacotherapy: A symptom clustering approach on ELECT-TDCS. Brain Stimulation 2021, 14: 906-912. PMID: 34048940, DOI: 10.1016/j.brs.2021.05.008.Peer-Reviewed Original ResearchConceptsTranscranial direct current stimulationNon-invasive brain stimulationDepressive symptomsBrain stimulationEfficacy of tDCSCore depressive symptomsLinear mixed regression modelsDepressive symptom clustersConsiderable inter-individual variabilityDirect current stimulationEscitalopram 20Antidepressant effectsAntidepressant efficacyInter-individual variabilityAtypical symptomsDepressed patientsMixed regression modelsInsomnia symptomsTDCS sessionsPharmacotherapyEscitalopramSymptomsPlaceboSymptom clustersCurrent stimulationThe promise of machine learning in predicting treatment outcomes in psychiatry
Chekroud A, Bondar J, Delgadillo J, Doherty G, Wasil A, Fokkema M, Cohen Z, Belgrave D, DeRubeis R, Iniesta R, Dwyer D, Choi K. The promise of machine learning in predicting treatment outcomes in psychiatry. World Psychiatry 2021, 20: 154-170. PMID: 34002503, PMCID: PMC8129866, DOI: 10.1002/wps.20882.Peer-Reviewed Original Research
2020
Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder
Anderson KM, Collins MA, Kong R, Fang K, Li J, He T, Chekroud AM, Yeo BTT, Holmes AJ. Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder. Proceedings Of The National Academy Of Sciences Of The United States Of America 2020, 117: 25138-25149. PMID: 32958675, PMCID: PMC7547155, DOI: 10.1073/pnas.2008004117.Peer-Reviewed Original ResearchMeSH KeywordsAstrocytesAutopsyBrainCerebral CortexDepressive Disorder, MajorFemaleGene Expression ProfilingGene Expression RegulationGene OntologyGene Regulatory NetworksGenome-Wide Association StudyGenomicsHumansInterneuronsMaleMultifactorial InheritanceNeuroimagingSignal TransductionSingle-Cell AnalysisSomatostatinConceptsGenome-wide association studiesTranscriptional dataTranscriptional correlatesMajor depressive disorderCorrelates of depressionGene transcriptionSpecific genesGene expressionGene dysregulationIntegrative analysisBiological pathwaysAssociation studiesExpression dataGenesMolecular pathwaysCortical gene expressionDepressive disorderEx vivo geneCells associatesIntegrated analysisVivo geneBiological systemsRegulationPathwayUK BiobankPrecision non-implantable neuromodulation therapies: a perspective for the depressed brain
Borrione L, Bellini H, Razza L, Avila A, Baeken C, Brem A, Busatto G, Carvalho A, Chekroud A, Daskalakis Z, Deng Z, Downar J, Gattaz W, Loo C, Lotufo P, da Graça M. Martin M, McClintock S, O’Shea J, Padberg F, Passos I, Salum G, Vanderhasselt M, Fraguas R, Benseñor I, Valiengo L, Brunoni A. Precision non-implantable neuromodulation therapies: a perspective for the depressed brain. Brazilian Journal Of Psychiatry 2020, 42: 403-419. PMID: 32187319, PMCID: PMC7430385, DOI: 10.1590/1516-4446-2019-0741.Peer-Reviewed Original ResearchConceptsMajor depressive disorderSide effectsCurrent first-line treatmentMultiple medication trialsMagnetic seizure therapyFirst-line treatmentCognitive side effectsTranscranial direct current stimulationTranscranial magnetic stimulationDirect current stimulationCognitive behavioral therapyCost-effectiveness analysisClinical respondersSeizure therapyElectroconvulsive therapyMedication trialsPathophysiological mechanismsClinical trialsDepressed patientsDepressive disorderDepressed brainMagnetic stimulationNeuromodulation techniquesCurrent stimulationTherapySymptom clusters in adolescent depression and differential response to treatment: a secondary analysis of the Treatment for Adolescents with Depression Study randomised trial
Bondar J, Caye A, Chekroud A, Kieling C. Symptom clusters in adolescent depression and differential response to treatment: a secondary analysis of the Treatment for Adolescents with Depression Study randomised trial. The Lancet Psychiatry 2020, 7: 337-343. PMID: 32199509, DOI: 10.1016/s2215-0366(20)30060-2.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBayes TheoremChildCognitive Behavioral TherapyCombined Modality TherapyDepressive Disorder, MajorDiagnostic and Statistical Manual of Mental DisordersFemaleFluoxetineHumansMalePsychiatric Status Rating ScalesSelective Serotonin Reuptake InhibitorsTreatment OutcomeUnited StatesConceptsChildren's Depression Rating Scale-RevisedCognitive behavioral therapyCDRS-R scoresSymptom clustersDepression StudyTreatment efficacySecondary analysisMajor depressive disorderDSM-IV diagnosisCo-occurring symptomsSpecific symptom clustersPlacebo groupAcute phaseClinical profileActive treatmentSymptom scoresSleep disturbancesClinical trialsDepressive disorderPill placeboTreatment responseTherapeutic modalitiesSpecific symptomsNew therapiesPhysical complaints
Academic Achievements and Community Involvement
Links & Media
News
- January 12, 2024Source: Yale News
Quest for Personalized Medicine Hits a Snag
- June 09, 2022
Workplace Mental Health Program Evaluated for Clinical and Financial Benefits
- February 13, 2022
Thorne Prize Winner April Koh, YC ’16, Recognized for Success
- January 27, 2020Source: Nature
How Founding a Company Compares to Graduate School