Efficacy of health ecology-based health education on early rehabilitation outcomes in stroke patients
Bibliographic record
Abstract
Background Stroke is a leading global cause of disability and mortality in adults, and early rehabilitation is critical for improving patients’ functional recovery and quality of life; however, conventional rehabilitation models often focus solely on medical interventions and overlook the impact of the patient’s comprehensive ecological environment on recovery, making it necessary to explore more holistic intervention approaches. To investigate the efficacy of health ecology theory-based health education in early stroke rehabilitation and its impacts on neurological/motor/cognitive function, psychological status, and metabolic biomarkers. Methods A total of 150 stroke patients during June–October 2024 were randomized into control and intervention groups based on interventions. Outcomes assessed included National Institutes of Health Stroke Scale (NIHSS) for neurological deficit, Fugl-Meyer Assessment (FMA) for motor function, Modified Barthel Index (MBI) for activities of daily living, Montreal Cognitive Assessment (MoCA) for cognition, Hospital Anxiety and Depression Scale (HADS) for psychological status, and metabolic biomarkers glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C). Structural equation modeling (SEM) was employed to analyze path relationships among metabolic_indices, recovery_effect, and mental_status. Results The intervention group demonstrated significantly greater improvement in NIHSS, FMA, MoCA, HbA1c, and LDL-C. Multivariate linear regression models showed moderate-to-substantial explanatory power, particularly for LDL-C and HbA1c (adjusted R 2 ≈ 30%). Although models for HADS and MBI had lower explanatory power, the intervention effect remained statistically significant ( p < 0.05). SEM revealed a significant positive path from mental_status to metabolic_indices ( β = 0.42). The negative path from recovery_effect to metabolic_indices (β = −0.45) signified that better recovery correlated with better metabolic profiles. A significant indirect effect of the intervention on metabolic_indices via improved mental_status was identified ( β = 1.00 × 0.42). Conclusion Health ecology-based health education effectively improves neurological/motor/cognitive function and metabolic control during early stroke rehabilitation. The intervention establishes a “physiological-psychological-social” virtuous cycle through multidimensional effects, providing an innovative framework for collaborative stroke recovery management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".