Eficacia de medios audiovisuales en la educación del cuidado posoperatorio de pacientes sometidos a artroscopia de rodilla en el Hospital III Yanahuara Essalud, Arequipa 2018.
Bibliographic record
Abstract
Introduction: In recent years, the use of educational tools based on video has become increasingly common among health professionals as a strategy to improve understanding and recall of patients about information related to their health status. and self-care, especially in the postoperative period. Arthroscopy is a minimally invasive surgical procedure with low mortality widely practiced in hospitals nationwide, so having patients with a postoperative knee is quite common. There are still no studies on this at the local, regional or national level. \nMethods: It is a prospective, quantitative, case-control type design study - experimental. A sample was taken of 164 patients (82 in the case group or intervention group and 82 in the control group) who underwent knee arthroscopy in the first quarter of 2018. The aim was to determine the effectiveness of the use of audiovisual media in the education of postoperative care. For the analysis of the data the Odds Ratio (OR), the Chi square test (X2) and 95% confidence intervals were used; through the statistical program SPSS v20.0. \nResults: It was evidenced that the patients to whom the educational audiovisual material was shown obtained a higher percentage of correct answers with respect to the patients who only received routine instruction by the health personnel, 93.8% and 81.3% respectively. Thus, patients in the intervention group had a probability of correctly answering the questions up to 3.49 times more than the patients in the control group. Phenomenon that was repeated in all study variables, these findings being statistically significant with a p-value less than 0.05 in all cases. \nConclusions: The present study clearly demonstrated the efficacy and usefulness of videobased educational audiovisual media as a reinforcement to impart knowledge about postoperative self-care in patients undergoing knee arthroscopy at Hospital III Yanahuara ESSALUD in the city of Arequipa in 2018. A In turn, it was evidenced that the age, sex and origin of the patient do not influence the effectiveness of video-based educational audiovisual media. It is recommended to perform new studies in this regard in our environment to evaluate its long-term efficacy and see if the acquisition of knowledge imparted influences the incidence of postoperative arthroscopic complications and the patient's recovery time.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".