Evaluating the effects of telenursing on patients' activities of daily living and instrumental activities of daily living after myocardial infarction: A randomized controlled trial study
Bibliographic record
Abstract
AIM: This study aimed to assess the effects of telenursing on patients' activities of daily living and instrumental activities of daily living (ADLs and IADLs) following a myocardial infarction (MI). METHODS: This randomized, parallel-group, controlled trial was conducted on 95 patients post-MI from 2018 to 2019. Patients were randomly assigned to the intervention (telenursing) and control groups using permuted block randomization. Through telephone calls, telenursing was performed twice a week during the first six consecutive weeks, then once a week until week 12. ADL and IADL questionnaires were completed by both groups before intervention and 12 weeks later. The CONSORT 2010 checklist was used to report the study protocol. RESULTS: The mean age of patients was 56.8 ± 11.07 and 54.2 ± 9.8 years in the telenursing and control group, respectively. The mean ADL and IADL scores in the telenursing group were substantially greater than in the control group [4.57 (3.18, 5.97); P < 0.001 and 4.40 (3.06, 5.75); P < 0.001, respectively]. The odds of a higher degree of independence (no disabilities vs. mild disabilities and disability as well as no disabilities and mild disabilities vs. disability) regarding ADLs and IADLs were significantly greater in the telenursing group as compared with the control group (P < 0.001 and P < 0.001, respectively). CONCLUSIONS: Our findings suggest that the use of telenursing intervention may increase patients' ADLs and IADLs after an MI and may enhance their independence. Geriatr Gerontol Int 2022; 22: 616-622.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".