Recommendations for a ‘Wellbeing Curriculum’ to Mitigate Undergraduate Psychological Distress Associated with Lack of Careers Confidence and Poor University Engagement
Bibliographic record
Abstract
To foster a ‘wellbeing curriculum’ in a climate with an increasingly competitive graduate jobs market, we believe it is critical to support undergraduate career development and to develop positive peer and educator relationships, particularly for non-vocational degree programs. However, these relationships between undergraduate wellbeing and their career development or peer/educator relationships have not been specifically examined. This study used a mixed methods approach to examine if poor career development or university engagement (quality of relationships with peers or educators, use of the university careers and counselling services, time studying) were associated with psychological distress for students in non-vocational degree programs. Undergraduates (biomedical science; n=1100) from five Australian universities participated in a survey to investigate relationships between psychological distress, as determined by their responses to the Depression, Anxiety and Stress Scales, and their career development or university engagement. Almost half of the students lacked confidence in their ‘future employment and job prospects’. Students’ psychological distress was significantly correlated with lack of confidence with their career development, poor relationships with their peers and educators and little use of the counselling service. Further exploration of these factors in student focus groups highlighted stress associated with academic competition between students and a critical need for undergraduate career development, especially industry placements. We provide pivotal recommendations to promote undergraduate and educator wellbeing, by developing a ‘wellbeing curriculum’ that supports career development and positive relationships between students and their peers and educators, particularly vital for non-vocational degrees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".