Fantasy Proneness Correlates With the Intensity of Near-Death Experience
Bibliographic record
Abstract
Little is known about the personality characteristics of those who have experienced a "Near-Death Experience" (NDE). One interesting candidate is fantasy proneness. We studied this trait in individuals who developed NDEs in the presence (i.e., classical NDEs) or absence (i.e., NDEs-like) of a life-threatening situation. We surveyed a total of 228 individuals. From those, 108 qualified as NDE experiencers (i.e., Greyson NDE scale total score ≥7): 51 had their NDEs in the context of a life-threatening situation; 57 had their NDEs not related to a life-threatening situation. From those who did not meet the criteria to be considered "experiencers," 20 had their NDE in the absence of a life-threatening situation; 50 had faced death but did not recall a NDE and finally, 50 were healthy people without a history of life threat and/or NDE. All participants completed a measure of NDE intensity (the Greyson NDE scale) and a measure of fantasy proneness (the Creative Experiences Questionnaire). People reporting NDEs-like scored higher on fantasy proneness than those reporting classical NDEs, individuals whose experiences did not meet the NDE criteria and matched controls. By contrast, individuals reporting classical NDEs did not show different engagement in fantasy as matched controls. The reported intensity of the experiences was positively correlated with engagement in fantasy. Our findings support the view that strong engagement in fantasy by individuals recalling NDEs-like might make these persons more likely to report such subjective experiences when exposed to suitable physiological and/or psychological conditions (e.g., meditation, syncope).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".