University Student Mentor Experiences of the Comfort Corner Well-being Program
Bibliographic record
Abstract
University Students’ psychological well-being can impact their health, academic performance, retention, and ability to complete university. Participation in peer mentoring well-being programs has been found to help improve student outcomes. This study aimed to explore student mentors’ experiences of a co-designed university student peer-to-peer well-being program, the “Comfort Corner”. The study utilised a sequential mixed methods design collecting survey and interview data from student mentors about their experiences, knowledge and attitudes about psychological well-being as well as their skills and confidence to support the psychological well-being of their peers. Thirteen student mentors completed pre-post program surveys which revealed higher post-program scores on assessments related to their perceived communication skills (pre-test M=84.3, SD=13.7, post-test M=86.7, SD=11.5) and their knowledge about psychological well-being (pre-test M=10.9, SD=5.4, post-test M=15.6, SD=2.7). All 8 student mentors who completed a post-program satisfaction survey indicated that the peer-mentoring program improved their skills and was very useful (100% respectively). Thematic analysis of interviews conducted with 10 student mentors revealed 2 themes, 1) understanding psychological well-being and, 2) knowing how to engage and help others as accounting for improvements in student mentors’ skills and knowledge. Student mentors described their experience with Comfort Corner under a central theme, ‘fostering a community of support for students on campus’, they felt Comfort Corner provided welcoming, safe, and supportive space for students. These findings revealed the benefits of co-design using a student as partners framework for a peer mentoring well-being program in improving areas of student mentors’ skills and knowledge as well as promoting a sense of belonging and connection for students enrolled in higher education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".