Influence of Language-Based Learning Disorder on Vulnerability to Depression among Adolescents in Secondary Schools in Meru County, Kenya
Bibliographic record
Abstract
Adolescents should be able to score high in reading, write intelligibly and speak fluently so as to gain self-acceptance, achieve social roles, and be able to make friends and maintain healthy relationships. However, depression in adolescents causes poor psychosocial status and increases comorbidity to mental disorders. Therefore, the study sought to investigate effect of language-based learning disorder (LBLD) on vulnerability to depression among adolescents in secondary schools in Meru County, Kenya. The study used cross-section research approach and descriptive research design on a target population of 389 secondary schools in Meru County. The respondents were 389 principals, 1415 English language teachers and 311, 200 students. A sample size of 27 principals, 176 English language teachers and 297 students was obtained using purposive and simple random sampling methods respectively. The principals were interviewed; English language teachers answered questionnaires, and students undertook the Montreal Cognitive Assessment Tool [MoCA] test. MoCA assesses different cognitive domains, such as attention and concentration, executive functions, memory, language, vasoconstriction skills, conceptual thinking, calculations, and orientation. Pilot study was done in Ikuu Girls’ Secondary School, Chuka Boys and Ndagani Mixed Secondary School in Tharaka Nithi County. Using purposive sampling method, the study selected 3 principals, 18 English language teachers, and 30 students for the pre-test. Data was analyzed using descriptive statistics such as frequency, percentage and median. Inferential statistics such as linear regression and multiple regressions and regression coefficients were established. The findings revealed that schools lacked adequate resources and capacity to mitigate causes and consequences of language-based learning disorders. The study recommended that schools should put in place appropriate programs and engage experts to identify learners with language-based learning disorders. They should also seek early interventions to avert effect of LBLDS on learners.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".