Study on the effect of the ballistocardiography-based “Internet + Smart Bed” health management system on the quality of life of elderly users with chronic diseases
Bibliographic record
Abstract
Background: To study the effect of the "Internet + Smart Bed" health management system (IPBS) established with ballistocardiography (BCG) technology on the quality of life of elderly patients with chronic diseases. Methods: test and Bayesian methods were used to establish a generalized linear regression model to evaluate the effect of the IPBS on the quality of life of the subjects in the experiment. The control group (n=71) received routine examination and daily health risk management in pension facilities. Health service workers provided daily door-to-door care, and the users received regular diet, exercise, and medication supervision and guidance. The intervention group (n=79) was composed of users with chronic diseases, who accepted the IPBS. The health service workers, in addition to implementing routine examination and health risk management, conducted continuous monitoring and intervention management of the users' vital signs by means of the IPBS. Results: test analysis. After 15 months of follow-up in the intervention group, the rates of body function, emotion, behavior compliance (BC), and health knowledge (HK) awareness were 1.47 times, 1.75 times, 1.53 times, and 1.69 times higher than those in the control group, respectively. In the intervention group, after using the IPBS, all scores of quality of life were better than those before use, and the differences were statistically significant P=0 or P=0.1 (P<0.05). In the control group, there were no statistically significant differences before and after observation (P>0.05). Conclusions: Routine management in elderly users with chronic diseases by means of the IPBS, which could change the users' bad living habits and eating habits, raise the patients' HK awareness, and comprehensively improve the quality of life of patients with chronic diseases, is a self-health management model worthy of application and promotion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".