Assessment of knowledge and attitude of undergraduate students’ of Ahmadu Bello University Zaria towards depression
Bibliographic record
Abstract
Background and Aims: Depression is a leading cause of disability worldwide and was projected to become the second most burdensome disease by 2020. While there is growing literature on the mental health literacy of adults, there has not been a parallel interest in mental health awareness of young people in Nigeria. Thus, the objective of this study was to assess the knowledge of and attitudes towards depression in undergraduate students. Methods: The study was a cross-sectional survey conducted from August to November 2019. Ethical approval for the study was sought from the University’s research ethics committee. Consenting students across all levels were then sampled and recruited. Participants were presented with the ‘friend in need’ questionnaire designed to elicit the participants’ recognition of mental health disorders depicted in the form of a vignette. Results: Out of the 415 questionnaires distributed, only 365 were adequately filled indicating an 88% response rate. The majority of the participants were female (62.5%) and a total of 132 respondents (36.2%) correctly identified and labelled the depression vignette. Insomnia was the most identified symptom (29%) of depression by the participants. More than onequarter (30%) of the participants reported that they would be extremely worried about the depressed character and believed it will take the character longer than a few months to recover (54%). Friends were the most recommended source of help (33.1%), followed by professionals (30.7%) and then others. Conclusion: It was established that university undergraduate students do not have adequate knowledge about depression.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".