Prediction of patient admission and readmission in adults from a Colombian cohort with bipolar disorder using artificial intelligence.

Introduction: Bipolar disorder (BD) is a chronically progressive mental condition, associated with a reduced quality of life and greater disability. Patient admissions are preventable events with a considerable impact on global functioning and social adjustment. While machine learning (ML) approaches have proven prediction ability in other diseases, little is known about their utility to predict patient admissions in this pathology.

Screening for "substance abuse" among school-based youth in Mexico using the Problem Oriented Screening Instrument (POSIT) for Teenagers.

Indices of classification accuracy of the Substance Use/Abuse scale of a Spanish-language version of the Problem Oriented Screening Instrument for Teenagers (POSIT) were evaluated among school-based youth in Mexico. Participants were 1203 youth attending one middle school (N = 619) and one high school (N = 584) in the third largest city of Coahuila, a northern border state in Mexico in May 1998. More than 94% of youth enrolled in the participating middle school and 89% of youth enrolled in the participating high school completed the International Longitudinal Survey of Adolescent Health.