Effects of an Experiential Training Group on Psychological Wellness and Professional Efficacy for Counsellors-in-Training
Bibliographic record
Abstract
Despite the recognized value of an experiential training group in major counselling program accrediting and governing institutions, there is a paucity of research investigating the effectiveness of such a training group for counsellors-in-training (CITs). The present study examined the effects of a wellness-themed training group conducted in Hong Kong on CITs’ psychological wellness and group leader self-efficacy. The Five Factor Wellness Inventory (5F–Wel) and the Group Leader Self-Efficacy Instrument (GLSI) were administered to forty-three CITs of a Hong Kong master’s degree program in counsellor education. A pretest–posttest design was employed to compare psychological wellness and group leader self-efficacy before and after a 12-hour experiential training group. Two research aims were addressed. The findings showed significant increases in group leader self-efficacy and psychological wellness among CIT participants. Further investigation showed that Coping Self, Creative Self and Life Satisfaction improved significantly following the experiential training group. The foci of promoting an awareness of personal resources and identifying personal-fit positive coping strategies in the current group intervention might contribute to the positive results. The present findings have important implications for counsellor educators who have an important role in preparing competent and resilient CITs. The mandatory participation of the CITs as group members in an authentic, feedback experiential training group is recommended in a professional counselling program.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".