Predisposing Factors to Drug Abuse Among In-School Adolescents in Ilorin, Kwara State, Nigeria
Bibliographic record
Abstract
Drug abuse among in-school adolescents is a problem which the government of Nigeria and indeed some other countries are yet to find a lasting solution to. Drug abuse among school children can disrupt the smooth running of teaching and learning in school. One of the ways of solving the problem is by trying to find out what leads in-school adolescents into the act. The objectives of this study were to examine the predisposing factors to drug abuse among in-school adolescents in Kwara State and to examine the influence of the variables of gender, age, religion and level of study on the respondents’ response on the predisposing factors. A descriptive research design was adopted for the study. The population for the study comprised of the adolescents in secondary school and university. A sample of 403 students were selected through a multistage sampling procedure in order to participate in the study. Data was collected via a questionnaire titled ‘Predisposing Factors to Drug Abuse (PFDA)’. The questionnaire was validated by experts in test and measurement design. It has a reliability coefficient of 0.68 which adjudged the instrument to be reliable. Data was analysed with mean, rank order, t-test and analysis of variance. Hypotheses were tested at a 0.05 level of significance. Findings showed that the factors that predispose in-school adolescents to drug abuse were: peer influence, depression, lack of good parental care, low self-esteem, poor academic performance, among other factors. Findings further revealed that age, gender, religion and level of education did not make the respondents differ in their responses on the predisposing factors to drug abuse among in-school adolescents. It is recommended that counsellors, parents and stake holders in education should initiate a serious campaign regarding sensitization against drug abuse. It is also recommended that academic programs should be learner-centred.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".