“I don't feel fully prepared”: a qualitative study of recently graduated students' mental health experiences of the transition out of university
Bibliographic record
Abstract
OBJECTIVE: This study aimed to better understand the mental health experiences of students as they prepared to transition out of university. PARTICIPANTS: Participants included 18 recently graduated students from a Canadian university. METHODS: Virtual one-on-one semi-structured qualitative interviews were conducted and analyzed following the protocol for content analysis and using QSR NVivo. RESULTS: Four main themes were identified, including: distress and feelings of doubt, the importance of connections, the impact of the COVID-19 pandemic, and experiences with mental health service use. Participants discussed feeling pressured to succeed and a fear of failure, uncertainty and unpreparedness for next steps, the importance of connections to peers and professors, a lack of motivation and feeling 'unfinished' due to the COVID-19 pandemic response, and the need for flexible and accessible mental health services to address immediate and longer-term needs. CONCLUSION: Results have implications for better support of students as they prepare for graduation.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".