Types of analysis of validation studies in nursing: scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective. To identify and map the types of analysis in nursing validation studies.
 Methods. This is a scoping review with collection carried out in July 2020. The following data extraction indicators were considered: year of publication, country of origin, type of study, level of evidence, scientific references for validation and types of analyses. Data were collected in the following bases: U.S. National Library of Medicine, Cumulative Index to Nursing and Allied Health Literature, SCOPUS, COCHRANE, Web of Science, PSYCHINFO, Latin American and Caribbean Literature in Health Sciences, CAPES Theses and Dissertation Portal, Education Resources Information Center, The National Library of Australia's Trobe, Academic Archive Online, DART-Europe E-Theses Portal, Electronic Theses Online Service, Open Access Scientific Repository of Portugal, National ETD Portal, Theses Canada, Theses and dissertations from Latin America.
 Results. The sample consisted of 881 studies, with a predominance of articles (841; 95.5%), with a prevalence of publications in 2019 (152;17.2%), of Brazilian origin (377; 42.8%), of the methodological study type (352; 39.9%). Polit and Beck stood out as the methodological reference (207; 23.5%) and Cronbach's Alpha (421; 47.8%) as the statistical test. Regarding the type of analysis, the exploratory factor analysis and the content validation index stood out.
 Conclusion. The use of at least one method of analysis was evident in more than half of the studies, which implied the need to carry out several statistical tests in order to evaluate the validation of the instrument used and show its reliability
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it