Practice and experience of group therapy in improving the subjective well-being of elderly patients with long-term hospitalization
Bibliographic record
Abstract
Objective To investigate the application effect of group therapy in improving the subjective well-being (SWB) of elderly patients with long-term hospitalization. Methods Totally 100 cases of elderly patients admitted in geriatric ward of Ningbo First Hospital for long-time were selected. Newfoundland scale of happiness (MUNSH) scale and the negative life events questionnaire were used to investigate elderly inpatients, and patients with MUNSH≤12 points received group therapy. Patients were divided into several groups to receive the intervention according to the negative life events. One year after intervention, patients receiving group therapy were evaluated again by using MUNSH scale to evaluate the intervention effect. Results Among 100 elderly patients, there were 32 cases of high SWB, 3 cases of low SWB, and 65 cases of medium SWB. 53 cases of patients had sleep disorders, and 62.26% of them had low SWB. After intervention, the scores of negative experience and emotion of elderly patients were lower than those before intervention (P<0.05) ; the scores of positive emotion and positive experience and the total MUNSH score were higher than those before intervention (P<0.05) . Conclusions According to the different influencing factors, group interventions can significantly improve the SWB level of elderly patients with long-term hospitalization, so as to improve their quality of life. Key words: Elderly patients; Subjective well-being; Group therapy
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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 | 0.001 |
| 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 | 0.001 |
| 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".