Exploratory analysis of the professional quality of life in an Italian radiotherapy department: The role of empathy and alexithymia
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: Professional quality of life (QoL) is crucial for healthcare workers as it affects performance at work and interaction with patients, but little is known about stressors influencing radiation oncology professionals. The present study aims to explore the professional QoL of radiation oncologists (ROs) and radiation therapists (RTTs) in an Italian radiotherapy department and to report data about the possible impact of personality factors, such as alexithymia and empathy. Material and methods: Participants filled out three validated questionnaires measuring the professional QoL, alexithymia, and empathy: (i) Professional Quality of Life Scale (ProQOL); (ii) Toronto Alexithymia Scale (TAS-20); (iii) Interpersonal Reactivity Index (IRI). Correlation, regression analyses and non-parametric tests were run. Results: A total of 48 professionals completed the survey (66.7% ROs, 33.3% RTTs). Considering the ProQOL dimensions, moderate levels of risk for burnout (BO) and secondary traumatic stress (STS) were found. BO was found to be predictive by TAS-20 total score (β=.37, p =.010), while STS resulted to be predictive by TAS-20 total score (β=.54, p <.001) and IRI Empathic Concern subscale (β=.45, p <.001). No significant differences were found between ROs and RTTs for all the considered variables, except for TAS-20 total score ( p =.032), higher for RTTs. Conclusions: Results showed no evidence of high risk of burnout and no intrinsic differences regarding the professional QoL between ROs and RTTs. Findings suggest a significant role of alexithymia and empathy predicting professional QoL. These results underscore the importance of promoting a positive work environment and emotional competencies to prevent high stress levels.
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.
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 | 0.000 |
| 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 it