Profiling young adults and adolescents based on risk behaviors using latent class analysis
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, marij...
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| Main Authors: | , |
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| 格式: | text |
| 語言: | English |
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Animo Repository
2018
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| 在線閱讀: | https://animorepository.dlsu.edu.ph/etd_bachelors/18580 |
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| 機構: | De La Salle University |
| 語言: | English |
| 總結: | 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. |
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