How Do the Attitudes and Beliefs Towards Mental Health- Seeking Behaviour Differ Between Racialized and Non-Racialized Students in a University Environment
Bibliographic record
Abstract
The purpose of this research study was to explore the perceptions of racialized and non-racialized students at York Universitys Keele campus towards seeking help for mental health problems. A convenience sample consisting of 491 students participated in the cross-sectional survey. The majority (n = 413, 84.1%) were identified as Canadian racialized, mainly Asian, South Asian, Caribbean, Middle Eastern and African students. The remainder (n = 78, 15.9%) were Canadian non-racialized, (English, French, Italian and Portuguese) students identifying with dominant Canadian culture. Most of the students (n = 77.4%) were female. All of the participants completed the Attitudes Toward Seeking Professional Help Scale; Beliefs About Psychological Services Scale; Vancouver Index of Acculturation; Race-Related Events Scale; Centre for Epidemiological Studies Depression Scale, and the Beck Anxiety Inventory. Attitudes and intentions toward seeking help were more negative among the racialized students. A higher level of stigma was also a predictor of negative attitudes and lower intentions towards seeking mental health counseling amongst the racialized group. Stigmatization among the racialized and non-racialized male students was higher than among the female students. The older racialized students tended to have higher positive scores for attitudes toward seeking help than younger students. Attitudes toward seeking help were more positive among the students who lived with their families. Previous mental diagnosis was also a significant predictor of attitudes toward seeking help. Very few racialized and non-racialized students used the counselling services or the online information system at York university to obtain information on mental health issues. The findings of this research study advocate university governance, healthcare professionals, and counsellors need to improve their services to address the specific needs and concerns of racialized students. Future research should focus on how findings can be translated into practice by designing culturally adaptive treatment modalities, including electronic media, that focus on resolving mental health problems among racialized and non-racialized students.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".