The feasibility and impact of online peer support on the well-being of higher education students
Bibliographic record
Abstract
Purpose Peer support has been identified as an important protective factor for mental health and overall well-being. The purpose of this study is to examine the feasibility of implementing an online peer support group and its impact on measures of well-being. Design/methodology/approach A mixed-methods randomized controlled trial design was used to examine the feasibility and impact of online peer support. Comparisons in well-being were made between the online peer support group and an in-person peer support group and control group. Participants were randomly assigned to a control group or either a six-week in-person or online peer support group. All participants completed an online survey measuring constructs of well-being pre- and post-condition. Additionally, qualitative data regarding the benefits of peer support and in particular the efficacy of the online format were collected from participants. Analysis of variance and post hoc tests determined significant differences within and between the groups. Findings Both the online and face-to-face peer support groups scored significantly higher on post-test measures of well-being than pre-test scores and control group scores. Qualitative narratives and significant quantitative findings supported the feasibility of peer support offered online. Post-condition outcomes showed that online peer support is as effective as in-person peer support for improving well-being. Originality/value To the best of the authors’ knowledge, this study is the first of its kind to compare online and in-person peer support programs for students in higher education. The results have direct implications for higher education students and practitioners, especially at times when face-to-face support is not feasible.
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 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 | 0.006 | 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 | 0.000 | 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".