Therapists in training: Brief interventions to ease negative self-evaluations and improve affective well-being
Bibliographic record
Abstract
Clinical and counselling psychology trainees take on many different roles throughout the course of their graduate training, including intensive course loads, research, and clinical training. Previous research has identified significant distress and psychological symptoms reported by graduate students in clinical training. Also documented are complex barriers to receiving help for their mental health concerns. The aim of the current study was to better understand the experiences of graduate therapist trainees by tracking them over time to investigate the psychological difficulties they experience, and to examine the efficacy of brief online exercises designed to combat self-criticism and induce self-compassion. 254 clinical and counselling psychology trainees were recruited from 50 graduate programs across Canada and the United States. Participants completed baseline measures assessing self-compassion, self-criticism, positive, negative, and compassionate affect, depression, anxiety, dysfunctional attitudes, fear of negative evaluation, stress, and professional self-doubt. Participants were randomly assigned to one of three groups, a “working with self-criticism” condition, a “loving kindness meditation” condition, or a waitlist control condition. Following the baseline measures, trainees completed the online interventions for eight weeks, then completed measures at post-test and a one-month follow-up. Results indicated that the therapist trainees experienced moderate to severe levels of distress on most psychological outcome measures at baseline. However, it was found that the two active conditions were effective in reducing self-criticism and fear of negative evaluation, while increasing compassionate affect compared to the control condition. The results support the value of self-care and reflective practices among clinical and counselling trainees. Clinical implications and future directions are discussed.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".