Profiling young adults and adolescents based on risk behaviors using latent class analysis

• Main Authors: Sison, Coleen Kate S., Soriano, Katrine Joyce A.
• Format: text
• Language: English
• Published: Animo Repository 2018
• Subjects: Physical Sciences and Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/18580
• Institution: De La Salle University

Numerous literatures have stressed that detection of risk behaviors can assist a person towards reducing injury. Latent Class Analysis (LCA) was used in determining the optimal number of latent classes for six risk indicators variables: alcohol consumption in a day, cigarette smoking in a day, marijuana use in the past 30 days, number of sexual partners for the past 3 months, depression, and suicidal ideation. The analysis has resulted to four distinct latent classes: High Risk, Low Risk, Poor Mental Health, and Legal Substance User. The respondents were profiled using the Multiple-Group LCA, and the output has provided the prevalence of each socio-demographic trait (e.g. age, sex, family structure, social support, occupational status and socio-economic status) among the four latent classes formed.