University student anxiety and stress – exploring the feasibility, suitability, and benefits of ACT matrix group workshops for university students experiencing anxiety and stress
Bibliographic record
Abstract
The Ontario University and College Health Association (OUCHA), called upon the provincial government for immediate action in regard to the state of post-secondary students’ mental health and lack of adequate supports (OUCHA, 2016), referencing the dire findings of recent and consecutive studies done by the American College Health Association National College Health Assessment II (ACHA-NCHA II). The studies indicated the top factors Ontario students reported as having negative impacts on their academic performance were stress and anxiety (ACHA-NCHA II, 2013, 2016), and the trend is rising. Anxiety and stress have been linked to a multitude of risks including suicide. My qualitative research study explored the benefits of a 1-day ‘Learning What Works’ ACT Matrix Workshop created to introduce a pointof-view to Laurentian students who struggle with problematic symptoms of anxiety and stress. The workshop was based on Acceptance and Commitment Therapy (ACT) and centred around the ACT Matrix, a simple tool designed to foster the noticing of, and if desired, bringing about change to behaviour. The results of this study were gleaned from data collected from pre- and post-workshop surveys and participant discussion groups. Thematic analysis of the data returned favourable results. Post-workshop survey respondents indicated they continued to benefit from their workshop experience four weeks later, and shared ways in which they continue to refer to the ACT Matrix in their lives. Some said the workshop changed their lives. Offering ACT Matrix workshops in university settings could make a positive difference in more students’ mental health.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".