2025
Psychometric Evaluation of Aurora- a : An Augmented Assessment of Analytical, Practical, and Creative Abilities in Middle Childhood and Early Adolescence
Hein S, Tan M, Ahmed Y, Elliott J, Bolden D, Sternberg R, Grigorenko E. Psychometric Evaluation of Aurora- a : An Augmented Assessment of Analytical, Practical, and Creative Abilities in Middle Childhood and Early Adolescence. Merrill-Palmer Quarterly 2025 DOI: 10.1353/mpq.0.a955196.Peer-Reviewed Original ResearchMiddle childhoodEarly adolescenceExploratory structural equation modelingConfirmatory factor analysisCreative abilitiesAssessment of academic performanceIntelligence testsVerbal competenceStructural equation modelingPsychometric evaluationAdequate reliabilityFactor analysisAcademic performanceEquation modelingAssessment of analytesAdolescentsMultifaceted natureChildhoodSubtestsAbilityCompetenceUnidimensionalityGoodness-of-fitItemsStrong correlationsMotives for pornography use and women's sexual wellbeing: Insights from a 42-country study
Gewirtz-Meydan A, Feder H, Nagy L, Koós M, Kraus S, Demetrovics Z, Potenza M, Ballester-Arnal R, Batthyány D, Bergeron S, Billieux J, Briken P, Burkauskas J, Cárdenas-López G, Carvalho J, Castro-Calvo J, Chen L, Ciocca G, Corazza O, Csako R, Fernandez D, Fernandez E, Fujiwara H, Fuss J, Gabrhelík R, Gjoneska B, Gola M, Grubbs J, Hashim H, Islam S, Ismail M, Jiménez-Martínez M, Jurin T, Kalina O, Klein V, Költő A, Lee C, Lee S, Lewczuk K, Lin C, Lochner C, López-Alvarado S, Lukavská K, Mayta-Tristán P, Miller D, Orosová O, Orosz G, team S, Ponce F, Quintana G, Garzola G, Ramos-Diaz J, Rigaud K, Rousseau A, De Tubino Scanavino M, Schulmeyer M, Sharan P, Shibata M, Shoib, Sigre-Leirós V, Sniewski L, Spasovski O, Steibliene V, Stein D, Strizek J, Štulhofer A, Ünsal B, Vaillancourt-Morel M, Van Hout M, Bőthe B. Motives for pornography use and women's sexual wellbeing: Insights from a 42-country study. Journal Of Behavioral Addictions 2025, 14: 114-130. PMID: 39945771, PMCID: PMC11974412, DOI: 10.1556/2006.2024.00040.Peer-Reviewed Original ResearchConceptsPornography useSexual wellbeingWomen's motivationsSexual desireLack of sexual satisfactionSexual satisfactionSexual function problemsSelf-report survey designGrowing body of researchPornography use motivationsWomen's sexual wellbeingBody of researchPornographyHigher sexual desireSexual curiosityWellbeingMeasures of sexual functionMultifaceted natureParticipant ageWomenGrowing bodySurvey designLongitudinal designDesireParticipants
2024
Predicting OCD severity from religiosity and personality: A machine learning and neural network approach
Zaboski B, Wilens A, McNamara J, Muller G. Predicting OCD severity from religiosity and personality: A machine learning and neural network approach. Journal Of Mood And Anxiety Disorders 2024, 8: 100089. DOI: 10.1016/j.xjmad.2024.100089.Peer-Reviewed Original ResearchObsessive-compulsive disorderOCD severityObsessive-compulsive disorder severityObsessive-compulsive disorder heterogeneityComplex psychological phenomenonDeep learning techniquesPersonality traitsItem-level featuresNeural network modelNeural network approachPsychological phenomenaMachine learning modelsLearning techniquesMachine learningLearning modelsNetwork modelDisordersNetwork approachMultifaceted natureAggregate scorePrediction accuracyPersonsMachineSeverityDemographic factors
2023
Longitudinal perspectives of riding with a cannabis-impaired driver
Banz B, Camenga D, Li K, Zuniga V, Iannotti R, Grayton C, Haynie D, Simons-Morton B, Curry L, Vaca F. Longitudinal perspectives of riding with a cannabis-impaired driver. Accident Analysis & Prevention 2023, 193: 107300. PMID: 37717297, PMCID: PMC10757553, DOI: 10.1016/j.aap.2023.107300.Peer-Reviewed Original ResearchConceptsCannabis-impaired driversYoung adulthoodTrajectory classesHigh schoolNEXT Generation Health StudyAdolescent health behaviorsYoung driversSemi-structured interviewsLongitudinal perspectiveEveryday activitiesMultifaceted natureAdulthoodHealth behaviorsQualitative interviewsUnique themesParticipantsSchoolsTheoretical modelInterviewsLegal concernsPerceptionContextEmergeDriversThemes
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