Evaluation of the effectiveness of educational technology in the prevention of falls in the surgical medical clinic
Bibliographic record
Abstract
Objective: To evaluate the effectiveness of a flipchart as an educational technology for patient education on preventing falls in hospitalized patients.Methods: This is a quasi-experimental study, being a pilot study type, with a quantitative approach, carried out in a hospital in the northern region of the State of Ceará, Brazil. Thirty-one patients represented the sample from August to November 2019. For the collection of information, it has been applied a structured instrument that includes two parts: a) Clinical-epidemiological data; b) Fall prevention knowledge test.Results: In the pre-test, there was a median of correct answers of 17 (interquartile range = 8), while in the post-test the median of correct answers was 20 (interquartile range = 6). Significance was observed in the increase in average of theoretical correct answers (p < .000).Conclusions: The flipchart is an effective technology to be used in health education to prevent falls, favoring an increased perception of risks in the hospital environment.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".