Effect of continuing nursing intervention after discharge from hospital among dementia patients
Bibliographic record
Abstract
Objective To investigate the effect of continuing nursing intervention on dementia patients′ daily living and the quality of life after discharge from hospital. Methods Totals of 85 cases of dementia patients according to the inclusion criteria were randomly divided into the observation group and the control group. Both groups received conventional neurology treatment of dementia and general life care after discharging from hospital. Besides, the observation group received continuing care, including family rehabilitation training, regular follow-up assessments and physical exercise. After 12 months enrollment, the observation group and the control group were assessed by using the Montreal Cognitive Assessment(MoCA) and Basic Activities of Daily Living (BADL). Results Before the intervention, no significant difference was found in the scores of MoCA and BADL between the control group and the observation group (P>0.05). After 12 months of intervention, the scores of MoCA in the observation group were (16.72±6.83), while those in the control group were (13.33±7.11). There was a significant difference between the two groups (t=2.24, P 0.05). Conclusions Continuing nursing intervention aimed at dementia patients can promote the rehabilitation of cognitive ability and activities of daily living of patients and effectively delay dementia progress. Key words: Dementia; Continuing nursing care; MoCA; BADL
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".