Factor affecting the activities of daily living among aging people during the COVID-19 pandemic – a structural equation modelling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: The activities of daily living (ADLs) are a set of basic skills necessary for self-care. The inability of elderly people to perform ADLs leads to dependence, insecure conditions, and poor quality of life. The COVID-19 pandemic has affected all aspects of the daily life of the elderly. This study aimed to determine the factors associated with ADLs among elderly people during the COVID-19 pandemic using structural equation modelling/path analysis. Material and methods: It was a descriptive-analytical study which had conducted on 487 elderly people who were selected randomly to participate in the study. Data collection tools included a demographic information questionnaire, an activities of daily living questionnaire, a knee pain and personal performance questionnaire Western Ontario and McMaster Universities Osteoarthritis (WOMAC), and the falls efficacy scale, which were completed by interview and self-report methods. SPSS-22 and AMOS software were used for data analysis. Results: < 0.001, root mean square error of approximation = 0.063). These variables explained 64% of the ADL variance. Conclusions: The structures of this model (FOF and WOMAC) can be used as a reference framework to design effective interventions for improving ADLs among elderly people during the COVID-19 epidemic. It is also recommended that a multi-component program be provided, which includes exercise and psychological strategies for this population during the COVID-19 pandemic through online videos, distance health programs, etc.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it