Minding many minds: An assessment of mental health and resilience among undergraduate and graduate students; a mixed methods exploratory study
Bibliographic record
Abstract
Objective/Participants: The American College Health Association (ACHA) found that 65.4% of Ontario (Canada) students feel overwhelming anxiety and 89.5% of students feel overwhelmed by all of their obligations. Thus, this study assessed the current state of full-time undergraduate (UGS) and graduate students’ (GS) mental health and resilience.Methods: A total of 598-796 UGS and GS completed three questionnaires (BRS, MHI, and SF-36) and a demographic questionnaire, which were distributed campus-wide. Focus groups/individual interviews (n = 30) explored students’ mental health- and resilience-related experiences.Results/Conclusions: Quantitatively, participants produced normal levels of resilience on the BRS, below-the-norm levels of anxiety on the MHI, and above-the-norm levels of physical functioning, but below-the-norm levels of six mental-health-related constructs on the SF-36. Qualitatively, GS and UGS felt physical activity (PA) benefited their mental health and resilience, and voiced the need for more counselors. Overall, participants’ mental health and resilience were similar to the population.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".