Empathy, self-compassion, and depression correlations among health professionals in Northern Greece
Bibliographic record
Abstract
OBJECTIVE: Aim: To study and record the level of empathy and self-compassion of the medical and nursing staff of a general hospital in North Greece, and to investigate their connection to depression levels.. PATIENTS AND METHODS: Materials and Methods: The study sample consists of 88 people (66 women and 22 men), medical and nursing staff of the General Hospital of Kavala (northern Greece) who filled out a questionnaire. The questionnaire consists of 4 parts: 1) socio-demographic data; 2) the Toronto Empathy Questionnaire (TEQ); 3) Self- Compassion Scale (SCS), and 4) the Beck Depression Inventory (BDI). For the statistical processing of the data, SPSS v.25 software was used. RESULTS: Results: The mean total value for TEQ indicates moderate high level of empathy (M = 40.5). For self-compassion the mean total value for SCS was moderate (M = 82.6) and the BDI shows a low level of depression (M = 28.7). A high level of empathy corresponds to a high level of self-compassion (ρ(88) = 0.263, p = 0013). Older ages correspond to a lower level of depression (ρ(88) = -0.218, p = .042). CONCLUSION: Conclusions: Empathy is a key factor for the creation of the therapeutic relationship between the patient and the healthcare provider, while increasing the level of the health provider's self-compassion. Increased levels of self-compassion and older age among providers may correspond to lower levels of depression.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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 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".