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Reason: Public access is not allowed according to the IRB. Access to the data must be approved by the project PI.

Supporting data for “Application of Statistical Learning Methods to Predict Psychopathological Symptoms and Well-being in Young People”

dataset
posted on 2022-12-02, 09:41 authored by Zhiqian FangZhiqian Fang

The current data is originally collected from the naturalistic study of the LevelMind@JC project. The LevelMind@JC is a four-year youth mental wellness hub project funded by the Hong Kong Jockey Club Charities Trust. The primary purpose of the naturalistic study is to monitor the different aspects of youths' mental health, including psychological distress, functioning, and quality of life.      

All hub users are expected to complete a brief assessment every time they visit a mental wellness hub. Each assessment takes approximately 2 minutes and includes questions regarding their distress level, functioning, and quality of life. Participants have the option to report their demographics. 

The current dataset is a subset of the original data from the naturalistic study, which included only variables that were used in the thesis project "Application of Statistical Learning Methods to Predict Psychopathological Symptoms and Well-being among Young People". This subset of variables was used to develop a classification and regression tree model that predicts youths' mental health outcomes at follow-up based on their baseline indicators. 


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