The Effects of Learning About Deathbed Visions (DBVs) on Students’ Knowledge About DBVs and Levels of Death Anxiety
Bibliographic record
Abstract
The purpose of this study was to examine the effects of learning about deathbed visions (DBVs) on undergraduate students' knowledge about DBVs and their levels of death anxiety. Twenty-two students were randomly assigned to a training group (received a 20-minute lecture and slides on DBVs) and 28 students served as an equivalent control (no training) group. Both groups completed a fear of death scale and a DBV knowledge questionnaire on two occasions (approximately one week before and immediately after the training group received the training). Participants in the training group experienced a significant increase in knowledge about DBVs following training compared to the no training group which showed virtually no change in knowledge about DBVs from pre- to post-test. No effect of training on participants' levels of death anxiety was found. Suggestions for future research are offered.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".