Exploring the Knowledge and Behavioural Responses of Tertiary Students towards Mental Health and Illnesses: A Cross-Sectional Study
Bibliographic record
Abstract
The mental health and wellbeing of tertiary students is a concern around the world.The study explored the knowledge, attitudes and behavioural responses towards mental illnesses among undergraduates.A total of 450 students were selected using a 3stage sampling technique.Data was collected using a self-administered semi-structured questionnaire.A total of 10 Focus Group Discussions was also conducted.The quantitative data were analyzed using descriptive and Chi-square statistics.Furthermore, Spearman rank correlation coefficient was utilized to evaluate the relationship between variables.The information from the FGDs were transcribed and analyzed for themes and contents.Respondents' mean age was 20.4 ± 2.4 years with the majority (52.4%) in the 20 and 24 years age group.The mean knowledge score for mental illness was 15.7 ± 3.3 indicative of an overall good knowledge about mental illness.The mean attitudinal score of respondents was 9.6 ± 2.7 indicative of an overall positive attitude towards mental illness.The mean perception score of respondents was 6.6 ± 1.7 indicative of an overall positive perception about mental illness.There was a significant association between class level of respondents and their knowledge about mental illness (p<0.05).There was also a significant association between age of respondents and their attitude towards mental illness (p<0.05).The correlation revealed significant positive correlations between knowledge and attitudes towards mental illness (r<0.0,p<0.01).Various derogatory words, phrases and slangs were used to describe individuals with mental illness by the participants.Reasons for stigmatization and discrimination against persons with mental illness were fear from lack of understanding about mental illness and fear of attack from such a person.The study recorded generally positive attitudes toward persons with mental illnesses; however, several stigmatizing perceptions were evident in the study findings.Increased mental health awareness and education can reduce the stigma toward mental illness.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".