Dying to Work: A Thematic Analysis of How Near-Death Experiences Affect Employees’ Work Lives
Bibliographic record
Abstract
Near-death experiences (NDEs) refer to the experiences people have when they are close to death as a result of medical emergencies or accidents (Kelly et al., 2007). Such experiences often have life-changing effects referred to as aftereffects. However, there is virtually no research on NDE aftereffects in the context of work. In the present study, we interviewed 14 working adults to explore how an NDE affected their work lives. Using thematic analysis, we categorized the interview data into six themes: insights and new realizations, personal transformations, reprioritization of work, job changes, motivation, and changed relationships. These themes offer conceptual and practical insights into the factors that promote thriving careers, which apply to those who have had NDEs and, importantly, also those who have not. Recommendations for future research are proposed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".