[Cross-Cultural Adaptaton and Validation of the Attitudes Towards Men in Nursing Scale (ATMINS)].
Bibliographic record
Abstract
Introduction: Aiming at detecting possible causes for the lack of male nursing professionals, Bartfay et al. developed a questionnaire named Attitudes Towards Men in Nursing Scale (ATMINS), which they tested a university in Ontario, Canada. Objective: Achieve a cross-cultural adaptation and validation of the Attitudes Towards Men in Nursing Scale (ATMINS), in order to evaluate if results achieved using a Spanish sample are comparable with the Canadian study's results. Participantsm, Materials, and Method: Participants were recruited in universities of Alicante and Donostia (Basque Country). To assure voluntary participation in the study, all candidates were informed about the objective of the study and giving enough time to read the questionnaire. The questionnaire used was the Attitudes Toward Men in Nursing Scale (ATMINS), translated to Spanish. The Spanish version of the ARMINS scale was handed over to a total of 142 students from the Nursing Universities of Alicante and Donostia. Time needed to fill the questionnaires didn't exceed 5 minutes in any case, and no difficulty was observed during implementation. After testing the scale, an internal consistency analysis was performed using Cronbach's Alpha with correction by eliminating items. Validation of construct was done via Exploratory Factorial analysis with Varimax rotation. Results: The results show a reliability which does not reach a moderate degree. Eliminating item 6 in all subsamples, as well as the total sample suppressing any of the other 5 items, increases internal consistency. The exploratory factorial analysis supports a bi-factorial structure of the questionnaire with very high saturation on each factor and a negative charge inside factor 2 for item 6. The negative charge of item 6 keeps the saturation (0.717) after its inversion. By performing an internal consistency analysis taking only into account items of factor 1, the scale's consistency improves with results close to 0.70. Conclusion: The revised scale is a tool which enables easy and fast application. It is valid for the Spanish sample and provides an acceptable internal consistency. The results obtained in both universities in Spain and in Canada are comparable.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".