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2017 | 88 | 2 | 85-117
Article title

Predicting adolescents’ quality of life using discriminat analysis

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EN
Abstracts
EN
Psychosocial functioning and depression is associated with a wide range of impacts on adolescents’ quality of life. In Nigeria, studies assessing the importance of psychosocial functioning and depression in distinguishing between the categories of quality of life and classifying adolescents into these categories have been limited in literature. This study investigated the domains of psychosocial functioning and child depression that significantly distinguish between the categories of quality of life and also classify into these groups. Data for 2019 adolescents aged 10-19 were obtained in a Benue State cross-sectional study. Preliminary analyses on their socio-demographic information were performed using descriptive statistics. Differences between categories (groups) of Quality of Life (low, moderate and excellent) on the basis of the attributes of the adolescents in terms of their psychosocial functioning and depression status, indicating which attributes contribute most to group separation were investigated using discriminant analysis. Chi-square analysis was used to assess the association between socio-demographic characteristics of the adolescents and levels of Quality of Life. The inter-relationships between the domains of Quality of Life and the adolescents age, position in the family, domains of psychosocial functioning and child depression status was assessed using correlation analysis. Prosocial behaviour (F=82.41, p<0.001) and ineffectiveness (F=31.19, p<0.001) were strong significant discriminating variables that predict adolescents’ levels of total quality of life. Adolescent’s psychosocial functioning and depression status relates with their physical health, psychological health, social relationship, environmental health and total quality of life.
Discipline
Publisher

Year
Volume
88
Issue
2
Pages
85-117
Physical description
Contributors
  • Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Nigeria
References
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Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-2962206b-82e9-456b-a816-6f6a05e54960
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