The impact of Balint work on alexithymia, perceived stress, perceived social support and burnout among physicians working in palliative care: a longitudinal study
Bibliographic record
Abstract
OBJECTIVES: Physicians working with palliative patients have a substantial risk of emotional exhaustion because of their daily confrontation with suffering and death. Common concerns include alexithymia, high stress, low perceived social support and a greater burnout risk. This longitudinal study aimed to evaluate the effectiveness of Balint training in preventing the development of these symptoms in these medical professionals. MATERIAL AND METHODS: ). A split-plot ANOVA analysis was used for evaluating the significance of Balint groups participation, with gender and age considered as auxiliary variables. RESULTS: In the study group, Balint training significantly improved the scores of global burnout (F(1, 64) = 25.104, p < 0.0001), 2 of its components (emotional exhaustion (F(1, 64) = 18.390, p < 0.0001) and depersonalization (F(1, 64) = 10.957, p < 0.002), alexithymia (F(1, 64) = 3.461, p < 0.0001) and perceived social support (F(1, 64) = 57.883, p < 0.0001), but not the scores of perceived stress and low personal accomplishment. Gender had an additional contribution in decreasing alexithymia (F(1, 64) = 7.436, p < 0.009) and increasing perceived social support (F(1, 64) = 15.426, p < 0.0001), with higher effects in men. CONCLUSIONS: This study points to the potential usefulness of Balint training in addressing alexithymia and burnout, and in improving perceived social support among physicians working with palliative patients. As the Balint method is easily understood and does not require special investments, it could represent a cost-effective instrument of addressing job-related psychological risks. Int J Occup Med Environ Health. 2019;32(1):53-63.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".