Black Student Mental Health: An Analysis of Accessibility of Mental Health Resources at Queen’s University
Bibliographic record
Abstract
This study seeks to answer four primary questions: first, how/why does being Black impact a student’s mental health? Second, how does race impact how Black students seek care? Third, what are the barriers to care that Black students face? Fourth, what can ideally be done to improve the mental healthcare system? A recruitment letter was distributed on Facebook and Instagram advertising a $25 Amazon gift card for a 30-minute interview. 30 students were interviewed. Interviewees are self-identified Black students at all levels of study, from undergraduate to professional studies and recently graduated from Queen’s University (Canada). All participants were asked the same questions. Interviews were analyzed using a constant comparative method to examine the barriers to care and ways to improve the system. Participants identified several barriers to care, such as a lack of racially representative advertisements, financial and insurance barriers; long wait times; a lack of mental health education; negative perception of mental healthcare; a fear of being misunderstood due to a lack of culturally competent mental health professionals; and a lack of racially diverse counsellors. However, participants also provided hope for the mental health system by recommending that university administration and provincial and federal governments take many measures to improve the mental healthcare system, including implementing cultural competence training; establishing online booking systems; building inclusive mental health education programs; collaborating with lawmakers and politicians to integrate mental healthcare into primary care, and prioritizing mental healthcare in Canadian healthcare funding models. While there are several barriers to care, there are clear and tangible ways to make mental healthcare more accessible for Black students. This study contributes to current scholarship by adding to the field of critical Black geographies. It has not only identified barriers Black students face but provides valuable ways forward for institutions of higher learning and government to increase access to mental healthcare.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".