Low-Burden Detection of Clinical Worsening in Body Dysmorphic Disorder Using Smartphone Sensor and Demographic Data.

• Used smartphone sensor and demographic data to predict daily clinical acuity in BDD. • Collected 3 months of smartphone sensor data and 28 days of EMA data (N = 82). • Random forests moderately to strongly predicted same-day clinical risk and acuity. • Demographic variables and step count were mos...

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Publicado en:	Behavior Therapy Vol. 57; no. 2; pp. 220 - 234
Autores principales:	Weingarden, Hilary, Holstein, Vincent, Jonathan, Geneva K., Armey, Michael, Onnela, Jukka-Pekka, Wilhelm, Sabine
Formato:	Artículo
Publicado:	Elsevier B.V. Mar2026
Materias:	Psychotherapy Body dysmorphic disorder Cell phone tracking Random forest algorithms Suicide risk assessment Clinical deterioration Ecological momentary assessments (Clinical psychology) Machine learning
Acceso en línea:	Ver este registro en EBSCOhost