Identifying the presence and timing of discrete mood states prior to therapy

Behaviour Research and Therapy

Volumn 128, Issue , 2020, Pages

  Fisher, Aaron J ^a   Bosley, Hannah G ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Anxiety; Depression; Idiographic analysis; Latent profile analysis; Machine learning; Personalized treatment

Indexed keywords

ADULT; ANGER; ANHEDONIA; ANXIETY; ANXIETY DISORDER; ARTICLE; AVOIDANCE BEHAVIOR; CLINICAL ARTICLE; DATA ANALYSIS; EMOTIONALITY; FEAR; FEMALE; HOPELESSNESS; HUMAN; IRRITABILITY; MAJOR DEPRESSION; MALE; MEASUREMENT ACCURACY; MIDDLE AGED; MOOD; MOOD DISORDER; PATIENT WORRY; PREDICTION; PSYCHOTHERAPY; RUMINATION; TIME SERIES ANALYSIS; YOUNG ADULT; AFFECT; BIOLOGICAL VARIATION; COGNITIVE RUMINATION; DEPRESSION; HOPE; LATENT CLASS ANALYSIS; MACHINE LEARNING; PSYCHOLOGY; TIME FACTOR;

ADULT; AFFECT; ANGER; ANHEDONIA; ANXIETY; ANXIETY DISORDERS; AVOIDANCE LEARNING; BIOLOGICAL VARIATION, INDIVIDUAL; DEPRESSION; DEPRESSIVE DISORDER, MAJOR; FEAR; FEMALE; HOPE; HUMANS; IRRITABLE MOOD; LATENT CLASS ANALYSIS; MACHINE LEARNING; MALE; MIDDLE AGED; PSYCHOTHERAPY; RUMINATION, COGNITIVE; TIME FACTORS; YOUNG ADULT;

EID: 85080048337     PISSN: 00057967     EISSN: 1873622X     Source Type: Journal    
DOI: 10.1016/j.brat.2020.103596     Document Type: Article

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