Assessing Substance Use and Its Contributory Factors Among University Undergraduates in Lagos State, Nigeria
Bibliographic record
Abstract
This study assess Substance uses and its contributory factors among Tertiary Institution Undergraduates in Lagos State, Nigeria. This research which adopted descriptive design was conducted in two Universities within Lagos State, Lagos State University and University of Lagos. Data was collected from a total number of 416 undergraduates, selected from the two Universities using multi-stage sampling techniques. This study adopted a validated questionnaire as the instrument for data collection from the respondents. The data obtained from the respondents was analyses using SPSS version 27. Findings revealed that, most of the respondents were 23 years and below (98.6%), with more male (63.7%) than female (36.3%). Furthermore, majority of the respondents were found to be substance users (61.5%), with only a quarter found to be substance abusers (26.2%). Findings also revealed that, a considerable rate of respondents who use substances were influence by their family background (60.1%) and level of socialization (84.6%). The study also concluded that, family background factors as well as level of socialization among undergraduate being a major contributor to abuse of substances.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".