Internalizing and Externalizing Problems in Grade 5 Bangladeshi Children Sample: A Latent Class Tree (LCT) Approach
Research Square Platform LLC, 2023
Online
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Zugriff:
Background Internalizing and externalizing problems are frequent during middle aged children and are often comorbid. The current study aimed to explore subgroup of children at grade 5 in Bangladesh. Methods The well-known Strength and Difficulties Questionnaire was administered to 912 children (48% girls), aged 9–13 years (M = 11.54; SD = 1.12). Latent class analysis (LCA) and Latent Class Tree (LCT) was carried out to make a comparison in identifying risk profiles in children according to their symptoms and explore association between latent classes and gender and having siblings. Results Four latent classes were found under behavioral internalizing and externalizing subscales. We have: “no difficulties” (37.51%), “some difficulties” (25.96%), “challenging” (19.73%) and “very challenging” (16.80%) based on traditional LCA. Whereas for LTA, we have: “no difficulties” (35.45%), “some difficulties” (27.64%), “challenging” (15.26%) and “very challenging” (21.65%). Children belonging to “very challenging” group for externalizing problem showed highest scores for hyperactivity/inattention compared to conduct problems. Whereas children belonging to “very challenging” group for internalizing problem showed highest risk on emotional symptoms. Conclusion This finding emphasizes the necessity of improving population-level knowledge of Bangladeshi child and youth mental health in the middle years, between early childhood and high school, to avoid future comorbidity and more severe symptoms. In addition, LCT ensures that the output of the LC tree model is compatible with the output of the LCA model suggests Latent Class Tree (LCT) as an alternative approach of LCA.
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Internalizing and Externalizing Problems in Grade 5 Bangladeshi Children Sample: A Latent Class Tree (LCT) Approach
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Autor/in / Beteiligte Person: | Rahman, Azizur ; Akter, Mariam |
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Veröffentlichung: | Research Square Platform LLC, 2023 |
Medientyp: | unknown |
DOI: | 10.21203/rs.3.rs-2874075/v1 |
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