The feasibility and effectiveness of compassionate mind training as a test anxiety intervention for adolescents: A preliminary investigation
Bibliographic record
Abstract
Abstract Test anxiety can have a deleterious impact on academic achievement and adversely affect adolescent well‐being, both concurrently and in later life. The current study explored the use of compassionate mind training (CMT) as a school‐based intervention for test anxiety among adolescents. Participants were 47 adolescents, aged 16–17 years, attending a post‐primary school in the UK and enrolled to take qualifications beyond compulsory education. Participants were quasi‐randomly allocated on the basis of timetable availability into an intervention group that received eight sessions of CMT (n = 22) or a control group (n = 25). Participants in both groups completed pre‐ and post‐intervention measures of test anxiety, general anxiety and self‐compassion. Attendance and retention rates were used as an index of intervention feasibility. The findings indicated that CMT was a feasible and effective intervention. Adolescents receiving CMT showed significant reductions in test anxiety and general anxiety, as well as a significant improvement in self‐compassion following the intervention compared with the control group. The findings highlight the potential value of CMT in supporting young people suffering from test anxiety in schools. The implications for counselling practice are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".