2023
The reliability and validity of the revised Green et al. paranoid thoughts scale in individuals at clinical high‐risk for psychosis
Williams T, Walker E, Strauss G, Woods S, Powers A, Corlett P, Schiffman J, Waltz J, Gold J, Silverstein S, Ellman L, Zinbarg R, Mittal V. The reliability and validity of the revised Green et al. paranoid thoughts scale in individuals at clinical high‐risk for psychosis. Acta Psychiatrica Scandinavica 2023, 147: 623-633. PMID: 36905387, PMCID: PMC10463775, DOI: 10.1111/acps.13545.Peer-Reviewed Original ResearchConceptsCHR individualsClinical controlFull psychosisHealthy controlsGeneral populationPsychosis symptomsCHR participantsPoor social functioningGreen Paranoid Thoughts ScalePsychosisGroup differencesSocial functioningConfirmatory factor analysisParanoid Thoughts ScaleInterview measuresSeverity continuumTwo-factor structureCritical populationSelf-report measuresPresent studyDiscriminant validityPsychometric indicesParanoid thoughtsIndividualsParticipants
2022
Three prominent self-report risk measures show unique and overlapping utility in characterizing those at clinical high-risk for psychosis
Williams TF, Powers AR, Ellman LM, Corlett PR, Strauss GP, Schiffman J, Waltz JA, Silverstein SM, Woods SW, Walker EF, Gold JM, Mittal VA. Three prominent self-report risk measures show unique and overlapping utility in characterizing those at clinical high-risk for psychosis. Schizophrenia Research 2022, 244: 58-65. PMID: 35597134, PMCID: PMC9829103, DOI: 10.1016/j.schres.2022.05.006.Peer-Reviewed Original ResearchConceptsProdromal Questionnaire-BriefPositive symptomsSelf-report questionnairesSpecific positive symptomsStructured Clinical InterviewClinical high riskCriterion validityHealthy controlsSpecific symptomsHigh riskDiscriminant validityPsychosis symptomsClinical InterviewCHR individualsStrong convergent validitySymptomsPsychosis riskNeuropsychological testsConsistent significant correlationLimited specificitySignificant correlationConvergent validityPsychosisConstruct validityQuestionnaire
2020
Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience
Gold JM, Corlett PR, Strauss GP, Schiffman J, Ellman LM, Walker EF, Powers AR, Woods SW, Waltz JA, Silverstein SM, Mittal VA. Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience. Schizophrenia Bulletin 2020, 46: 1346-1352. PMID: 32648913, PMCID: PMC7707066, DOI: 10.1093/schbul/sbaa091.Peer-Reviewed Original ResearchConceptsClinical high riskComputational cognitive neuroscienceNew behavioral measureCognitive neuroscienceBehavioral measuresPsychosis risk predictionCognitive mechanismsTrait vulnerabilityDisorganization symptomsNeural systemsPsychosis symptomsPsychosis riskSpecialized interviewsPhenotype measuresNeuroscienceCHR assessmentTreatment targetsPsychotic disordersCourse of illnessInterview methodPsychosisNew treatment targetsIllness progressionPositive predictive valueMeasures