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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oai:animorepository.dlsu.edu.ph:etd_bachelors-190932022-02-11T07:38:36Z Profiling young adults and adolescents based on risk behaviors using latent class analysis Sison, Coleen Kate S. Soriano, Katrine Joyce A. 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. 2018-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/18580 Bachelor's Theses English Animo Repository Physical Sciences and Mathematics |
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De La Salle University |
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De La Salle University Library |
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Asia |
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Philippines Philippines |
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De La Salle University Library |
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DLSU Institutional Repository |
| language |
English |
| topic |
Physical Sciences and Mathematics |
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Physical Sciences and Mathematics Sison, Coleen Kate S. Soriano, Katrine Joyce A. Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| description |
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. |
| format |
text |
| author |
Sison, Coleen Kate S. Soriano, Katrine Joyce A. |
| author_facet |
Sison, Coleen Kate S. Soriano, Katrine Joyce A. |
| author_sort |
Sison, Coleen Kate S. |
| title |
Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| title_short |
Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| title_full |
Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| title_fullStr |
Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| title_full_unstemmed |
Profiling young adults and adolescents based on risk behaviors using latent class analysis |
| title_sort |
profiling young adults and adolescents based on risk behaviors using latent class analysis |
| publisher |
Animo Repository |
| publishDate |
2018 |
| url |
https://animorepository.dlsu.edu.ph/etd_bachelors/18580 |
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1772835100015198208 |