Psychological health among institutionalized senior citizens of Ernakulam district
Bibliographic record
Abstract
ABSTRACT Introduction: Institutionalized senior citizens are facing a lot of psychosocial issues, of which dementia and depression are the most common ones. The present study intends to assess psychological health (cognition, depressive symptoms, self-esteem, sleep quality, and quality of life) among institutionalized senior citizens of Ernakulam district. Materials and Methods: This cross-sectional study was conducted among 236 senior citizens residing at five selected old-age homes of Ernakulam district. Sociopersonal data sheet, Montreal cognitive assessment, Geriatric Depression Scale-Long Form, Rosenberg self-esteem scale, Pittsburgh Sleep Quality Index, and WHOQOL-OLD scale were used to collect data from the study participants. Results: The average age of participants was 71.01 ± 12.01. The mean scores of cognition and quality of life among participants were 15.80 ± 5.51 and 85.05 ± 20.25, respectively. While only 2.5% of participants reported normal cognition, 40.7% of participants had depression of varying severity. The majority of participants had moderate self-esteem (65.3%). About 36.4% were reported as poor sleepers and 15.2% of participants reported poor or very poor quality of life. Participants with high cognitive scores, high self-esteem, better sleep quality, and low depressive symptoms reported better quality of life. As expected, participants with high self-esteem reported less depressive symptoms. Conclusion: The goal of adding quality rather than quantity to lives can be achieved by focusing on the psychological health (cognition, depressive symptoms, self-esteem, and sleep quality) of institutionalized senior citizens.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".