A Change Talk Model for Abstinence Based on Web-Based Anonymous Gambler Chat Meeting Data by Using an Automatic Change Talk Classifier: Development Study.

Published in: Journal of medical Internet research (2021)

Abstinence likelihood among gamblers can be increased by providing personalized evaluation values and indicating the optimal proportion of change talks. Moreover, this may help to prevent severe mental, social, and financial problems caused by the gambling disorder.

Keyphrases

mental health
smoking cessation
healthcare
machine learning
early onset
deep learning
big data
artificial intelligence
data analysis
health insurance