Loneliness and Neuropsychiatric Symptoms in Cognitively Impaired Older Adults during COVID-19 Pandemic
Bibliographic record
Abstract
Abstract Background: Cognitively impaired older adults living in the community have been vulnerable to the effects of COVID-19 confinement. The current study’s objectives were to examine the prevalence of loneliness in such adults along with impact of COVID-19 on neuropsychiatric symptoms and functional status. Methods: A cross-sectional study was conducted in community dwelling cognitively impaired older Veterans (N=41). Demographic data such as age, gender, race, and rurality were collected. Loneliness data were collected with the 3-item Loneliness Questionnaire. Cognition was assessed with the Tele-Montreal Cognitive Assessment (T-MoCA) and functional status of instrumental activities of daily living was assessed with the Functional Activities Questionnaire (FAQ). Neuropsychiatry symptoms including severity and distress were collected using the Neuropsychiatric Inventory (NPI), and change during COVID was also recorded for each symptom. Results: Demographic characteristics included: mean age of 71.9 (±8.6) years, 95.1% male, 46.3% rural, 75.6% Caucasian, and 19.5% African American. Loneliness was prevalent in most participants (62.5%). T-MoCA and FAQ mean scores were 15.1 (±4.5) and 10.0 (±8.6), respectively. Mean NPI total severity and total distress were 8.4 (±5.9) and 11.4 (±8.5), respectively. Irritability was most frequently reported symptom (65%), followed by agitation (57.5%), anxiety (55%), depression (50%), and night-time behavior (50%). A majority of the participants reported worsening of neuropsychiatric symptoms during COVID (71.1%). Among those that reported worsening neuropsychiatric symptoms, 70.4% noted an increase in ≥ two symptoms. Conclusion: Older adults with pre-existent cognitive impairment may be at high risk for loneliness and worsening of neuropsychiatric symptoms during the COVID pandemic.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".