Diseño y validación de un cuestionario de calidad de los cuidados de Enfermería del Trabajo en los Servicios de Prevención
Bibliographic record
Abstract
Introduction and Aim:The main aim of this study is to draw up a "Questionnaire on Satisfaction with Occupational Health Nursing" (Cuestionario de satisfacción con los cuidados de la enfermería del trabajo -CUSACET), which will enable us to gauge users' perceptions with regard to the occupational health nursing work carried out by the various safety management services. Materials and Method:The questionnaire is designed to encompass three dimensions:1. Sociodemographic: consisting of four items.2. Opinion of the safety management services: consisting of fifteen items.3. Opinion of care received from the nursing staff at the safety management service, measured by twenty-three items.We opted to do the validation according to the basic criteria of Moriyama and by applying Cronbach's Alpha index.To this end, 55 control questionnaires were given out at various safety management services in Cantabria.The questionnaires were collected and the data recorded onto the statistical analysis program SPSS v.15.Results: The criterion established for validity was exceeded, with results above 80% in assessment by experts in accordance with Moriyama's basic criteria.We encountered good internal consistency, as evidenced by a Cronbach Alpha coefficient of 0.837 in each section.Conclusions: This paper presents a new instrument, specifically designed to measure the quality of occupational health nursing care through the perceptions of the users who receive it which is reliable and easy to use.
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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 | 0.017 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".