Bibliographic record
Abstract
Abstract A scarcity of studies have examined the factors associated with mild cognitive impairment (MCI) as well as moderate cognitive impairment-as considered as dementia- among nursing home residents (NHRs). The aim of this study was to recognize the nature of relationship between the health risk variables, such as comorbidities, length of stay at hospital, the quality of life, the occurrence of depression, disability, and frailty, and dementia in NHRs. The study deployed cross-sectional design, using a convenient sample of 182 nursing home residents. The settings of the study were in the middle region of Jordan. Both stages of the MCI and dementia were determined through Montreal cognitive assessment (MoCA). Bivariate and multivariate analyses were utilized to explore the relationship between the health risk variables, and each of the MCI and dementia. There were significant differences between the stages of cognitive impairment (The MCI and dementia) in terms of age, the quality of life, comorbidities, depression, frailty. The variation in mental ability scores was dependent on the marital status of the participants, the monthly income, recently hospitalized, the level of depression, and frailty among older adults residing at nursing homes. The results of this study contribute significantly to building a healthcare management protocol to deal with nursing home residents with depressive symptoms as well as the deferral of the trajectory of development of dementia among those risky residents.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".