Psychometric Properties of the Patient Advocacy Scale for Intensive Care Nurses
Bibliographic record
Abstract
Patient advocacy exercised by an intensive care nurse refers to the defense of the patient’s interests and rights and can be measured if, for that, there are valid, reliable and reliable instruments, that is, which have their psychometric properties proven. Therefore, the patient’s advocacy processes would be permanently monitored and evaluated, also, the practice would become more visible. Perform psychometric validation of the Patient Advocacy Scale for Intensive Care Nurses (EAPEnf-ICU). Instrumental research for instrument validation, with exploratory and confirmatory factor analysis. Carried out from January to June 2021 with 377 Brazilian intensive care nurses, selected by non-probabilistic convenience sampling. Data were collected by means of Google Forms, organized on Excel ® 2010 software and analyzed on R software. The Ethics Committee approved the study. Participants received information about the research, agreed to respond to the questionnaire and were guaranteed anonymity. From the scale structural exploration by analyzing exploratory, confirmatory and internal consistency of the measurement instrument, the final version of the EAPEnf-ICU was composed of 54 items, distributed in 5 dimensions/factors: Factor 1—Clinical and organizational advocacy in intensive care; Factor 2—Barriers associated with the intensive care clinical and organizational complexity; Factor 3—Attitudes to promote the autonomy of patients and family members in intensive care; Factor 4—Barriers associated with divergences and ethical-professional limits in intensive care, and Factor 5—Intensive care nurse’s personal and professional background. Findings point that the instrument presented in this study is valid and reliable for assessing the aforementioned construct, as it presents theoretical and empirical consistency, identifying five dimensions related to the exercise of patient advocacy by the intensive care nurse.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".