Quality of life, mood and cognitive performance in older adults with cognitive impairment during the first wave of COVID 19 in Argentina
Bibliographic record
Abstract
Abstract Background In Argentina, government has established lock down on 19 March in order to decrease SARS‐COV 2 infection. These restrictions have remained effective for long time, with increase of anxiety depression and insomnia as shown in several studies. Older population was particularly at risk due to greater limitations to go out. Our objective was to evaluate the impact of confinement in quality of life, mood and cognitive performance of older adults with cognitive impairment. Method Longitudinal descriptive‐observational study. Patients with cognitive impairment (CDR 0.5‐1) attending to virtual cognitive stimulation sessions have participated. Participants have completed by themselves Quality of Life in Alzheimer's Disease scale (QOL AD), Beck Depression Inventory (BDI‐II), Test your Memory (TYM) and an attention and executive battery created by our institution. Same assessments were done at the beginning of the lock down and 7 months later. SPSS program was used and means, standard deviations and paired‐samples t test were calculated. Result 51 adults (43 women, mean age: 68.53 SD: 8.06, mean education: 14.33 SD: 2.63) were included. An increase in BDI ‐II score ( p = 0.049) and worse performance in one of the executive attention tests ( p = 0.012) were found. No significant differences in total score of QOL‐AD ( p = 0.090), TYM (p = 0.067), verbal fluency ( p = 0.323) or memory tests ( p = 0.098) were found. Reviewing sub items, differences in changes in sleep habits ( p = 0.021), decrease in the energy level ( p = 0.004), worse subjective record of memory capacity ( p = 0.028) and decrease in ability to do housework ( p = 0.007) were found. In those who lived alone a higher score in BDI ‐ II ( p = 0.030) and TYM ( p = 0.22) were found. Conclusion This is the first longitudinal study that measures the impact of lockdown on quality of life and cognitive performance in older adults with cognitive impairment in Argentina. Lockdown and isolation have shown worsening of mood and some quality of life variables and decrease in attention. Finally, our results show an increase in depressive symptoms in those patients who lived alone.
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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 | 0.000 | 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 | 0.001 |
| 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".