Bibliographic record
Abstract
University students experience a large number of stressors during their studies and many experience poor mental wellness. Despite this, many students do not access mental health services on campus due to several reasons such as awareness, personal and perceived public stigma, and time constraints. The global pandemic has led to a rapid transition to online mental health services at universities, including the University of Calgary’s Student Wellness Services. The purpose of this study was to gain insight into student’s experiences with online counselling, what its benefits and barriers are, and what variables can predict students’ use of online counselling services once in-person services are re-instated. It was found that high value in online counselling predicted higher intentions to continue online counselling, while high value in face-to-face counselling and higher purpose in life predicted lower intentions to continue online counselling. This research adds to the few studies that have studied university students’ experiences with telehealth. In general, students reported similar value and discomfort with both formats of counselling. Convenience and comfort were identified as important benefits to students, while concerns about connecting with the counsellor, privacy, and technical difficulties were identified as important drawbacks of online counselling. Students expressed mixed results on comfort with online and in-person modalities. This study found important implications for policy maker as universities may be able support more students that are struggling if they provide online counselling.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".