Exploring psychology and nursing students perceptions of disgust
Bibliographic record
Abstract
Objective : Practitioners can often experience feelings of disgust when exposed to malodorous wounds. This study reports on an investigation to measure a group of psychology and nursing students (n = 158) perceptions of disgust using the Disgust Scale-Revised questionnaire. Methods : Data were collected via anonymous on line survey of 158 psychology and nursing students at two Universities in the UK between June and July 2015. Results : Statistical analysis of the data revealed that the majority of the sample were female (97.3%) with nursing students being more resilient to disgust. Disgust scores diminished with increasing age. Psychology students are more sensitive to actual and perceived vulnerability to disease. Levels of perceived vulnerability fall with increasing age. Discussion and conclusions : Nursing students undertake 50% of their pre-registration programme in clinical practice where they may have been exposed to potentially disgust provoking situations that may sensitize them to such situations. It is unclear whether their disgust diminishes because they become more tolerant, or accustomed to such situations or to other factors. Previous and repeated exposure to situations provoking disgust may however, explain why nursing student responses differ to their psychology counterparts. Nursing students are disgusted less easily than psychology students; although all individuals become slightly more tolerant to certain issues over time. Psychology students are significantly more sensitive to actual and perceived vulnerability to disease than nursing students. Perceived vulnerability falls with increasing age. In order to fully examine the impact of gender on disgust more research is required with a purposive sample.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".