Exploration of Risk Factors for Mild and Major Neurocognitive Disorders in A Sample of Elderly Population
Bibliographic record
Abstract
Background: Early identification and management of modifiable risk factors for neurocognitive disorders is becoming more important to slow progression of the disease, which would be very beneficial for both the patient and the caregiver. Aim: Assessing risk factors for mild and major neurocognitive disorders among a sample of elderly population in Suez Canal Area. Patients and Methods: This cross-sectional comparative analytical study was conducted on a sample of 156 elderly people ≥60 years old in Suez Canal Area over the period from March 2022 to February 2023. Study tools included a semi-structured clinical interview to assess sociodemographic, medical and lifestyle risk factors, DSM-5 criteria to diagnose mild and major neurocognitive disorders, The Montreal Cognitive Assessment scale to assess cognitive function, and The Activities of Daily Living Questionnaire to assess functional impairment and dependency. Results: Mild and major neurocognitive disorders have multiple sociodemographic, medical and lifestyle risk factors, including: aging, lower education, female gender, non-married status, unemployment and physical work, lower income, less physical, cognitive and social activities, increased number of chronic diseases and family history of cognitive impairment. Conclusion: Multiple modifiable risk factors for mild and major neurocognitive disorders could be identified, and their management may contribute to lowering burden of neurocognitive disorders.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".