Phenomenological characteristics of autobiographical future thinking in nurses with burnout: a case-control study
Bibliographic record
Abstract
Objective Nurses constitute the largest group of healthcare workers worldwide, and job burnout is very common among them. This study aims to explore abnormal future thinking in nurses with burnout. Additionally, the study investigates whether these manifestations worsen as burnout progresses. Methods The study was conducted in inpatient ward nurses at a tertiary hospital in Hangzhou, China. In the first phase, two group of nurses were recruited: nurses with burnout ( N = 70) and nurses without burnout ( N = 70). In the second phase, three groups were recruited according to the burnout levels: mild burnout ( N = 43), moderate burnout ( N = 42) and severe burnout ( N = 43). Data on job burnout were obtained using the Chinese Maslach Burnout Inventory. The Sentence Completion for Events in the Future Test (SCEFT) was employed to measure the content of future thinking, which was evaluated by two raters in terms of the specificity, emotional valence, and concrete content of the imagined future events. The proportions of specific types of events among all the produced events were calculated. Results The results revealed that nurses with burnout, compared to nurses without burnout, imagined fewer specific future events, positive events, and events related to relationships and achievement. They also had more omissions. As the level of burnout increased, their impairment in future thinking worsened. Furthermore, the results also revealed that the scores of emotional exhaustion, depersonalization, and personal accomplishment had significant correlations with the proportions of positive events and events related to relationships and achievement/mastery in nurses’ future thinking content. Conclusion The future thinking ability of nurses with burnout was impaired, and this impairment worsened as the symptoms of burnout progressed. The findings of the present study have important implications for nurse caring and advocate effective interventions targeting positive future thinking to mitigate nurses’ burnout.
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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 | 0.001 | 0.002 |
| 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".