The feasibility and effectiveness of a novel online mental health literacy course in supporting university student mental health: a pilot study
Bibliographic record
Abstract
BACKGROUND: There is a need for effective universal approaches to promote and support university student mental health that are scalable and sustainable. In this pilot study we assess the feasibility and acceptability of a fully-digitalized, comprehensive mental health literacy course co-created with and tailored to the needs of undergraduate students. We also explore preliminary associations with mental health and positive behaviour change. METHODS: An accredited online mental health literacy course was developed using state-of-the-art pedagogical principles and a reverse mentorship approach. The course was offered as an interdisciplinary undergraduate elective. Students completed an online survey before and after the 12-week course that collected demographic information and assessed mental health knowledge, emotional self-awareness, mental health, stigma, and health-related behaviors using validated measures. Dependent group t-tests were used to compare pre- and post-course levels of knowledge, mental health, sleep quality and substance use. Mental health outcomes of students who completed the course were compared to an age and sex-matched sample of students not enrolled in the course and who completed the same survey measures over the same academic year. Multivariable linear regression was used to examine the effect of course participation on outcomes at follow-up. RESULTS: The course had good uptake and was positively reviewed by participants. Specifically, students found the course engaging, relevant, and applicable, and agreed they would recommend it to their peers. Among course participants there was improvement in mental health knowledge (p < 0.001) and emotional self-awareness (p = 0.02) at course completion. Compared to the matched comparison group, taking the course was associated with reduced alcohol (β = - 0.41, p = 0.01) and cannabis use (β = - 0.35, p = 0.03), and improved sleep quality (β = 1.56, p = 0.09) at the end of the term. CONCLUSIONS: Findings suggest that delivering mental health literacy as an online accredited course may be an acceptable and effective way of promoting university student mental health through improved knowledge, emotional self-awareness, and healthy lifestyle choices. As the course is expanded to larger and more diverse student cohorts we will be able to further examine the short and long-term effectiveness of the course in supporting student mental health and the underlying mechanisms.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".