Validación de una versión en español de la Escala de Conflicto Decisional
Bibliographic record
Abstract
BACKGROUND: In Chile, in approximately 50% of nursing students, nursing was not their first choice as career. Usually, during the first year, these students must decide whether they would like to continue in the same career. A valid tool is needed to identify decisional conflicts and their contributing factors among these students and to develop an appropriate strategy to support them during their decision-making process. AIM: To translate into Spanish and validate the Generic Decisional Conflict Scale (DCS). MATERIAL AND METHODS: The DCS was translated from English to Spanish and was used with 331 first-year nursing students at the Pontificia Universidad Católica de Chile. The scale was assessed for validity and reliability using statistical tests, including factor analysis and Cronbach alpha test. RESULTS: The Spanish version of the DCS had acceptable validity and reliability. Factorial analysis identified four factors and only the item: "advice" loaded the other factors. Cronbach alpha was 0.80. CONCLUSIONS: DCS is a valid and useful instrument to identify decisional conflicts and contributing factors to continue studies among nursing students.
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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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".