Evaluation of the Relationship Between Frailty, Polypharmacy, and Depression in People 65 Years of Age and Older
Bibliographic record
Abstract
Objectives: This study aims to determine the level of frailty in patients aged 65 and over who apply to the family medicine clinic to evaluate the relationship between polypharmacy, depression, and socio-demographic characteristics with frailty. Materials and Methods:This is a single-center, cross-sectional, descriptive survey.One hundred forty-four participants aged 65 and over who applied to the family medicine clinic at Training and Research Hospital in Izmir were included.The Yesavage Geriatric Depression Scale (GDS)-Short Form was used to measure participants' depression levels, and the Edmonton Frail Scale (EFS) was used to determine the level of frailty.The data obtained were analyzed using IBM SPSS 21.0, and a statistical significance value of p <0.05 was accepted.Results: The group with the highest percentage of participants was under 75 years old, constituting 65.32% of the total group.According to the GDS score average, a significant relationship was found between depression and gender, education level, monthly income, and falls.According to the EFS-TR score average, a significant relationship was found between frailty and age, gender, education level, marital status, monthly income, lifestyle, number of medications used, number of emergency hospital admissions, and falls.A moderate positive correlation was found between GDS and EFS. Conclusion:The study found that many socio-demographic characteristics affect depression and frailty.It was observed that frailty increases as depression and polypharmacy increase, but there was no significant relationship between polypharmacy and depression.These results are important for better support and protection of elderly individuals in health and social care.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".