Understanding caregiver profiles of older adults reporting cognitive decline: A descriptive study from North India
Bibliographic record
Abstract
Abstract Background As India gets closer to an expected 7.6 million dementia cases by 2030, families are tasked with care‐giving in the absence of affordable healthcare and adequate health systems. Those most impacted include elderly caregivers, and are mostly female spouses of persons with dementia. With transitions from joint family systems to more nuclear structures due to urbanization and migration, understanding characteristics of family caregivers will be critical to developing adequate support systems and enabling better home‐based care in urban areas. Method Screening camps were conducted in 8 locations across a North Indian urban area over 7 months, including a government hospital, communities, and senior centers. Assessment measures involved a brief cognitive assessment and screening for mental health, neurological, and preexisting medical issues. Sociodemographic information was collected from the accompanying family member. Both caregiver and the person reporting cognitive complaints were provided information about dementia symptoms with referrals to neurologists, psychiatrists or medical professionals based on screening results. Result A total of 194 persons (112 men, 82 women) were screened after reporting subjective cognitive decline; on evaluation, 4% and 5% had symptoms indicative of dementia and definite cognitive decline, respectively. Findings also indicated that 58% of participants also had symptoms of depression and anxiety, causing concern for caregivers. Majority of participants were accompanied by a family member and only 7 participants lived on their own. Sociodemographic information was collected for a total of 187 caregivers (58% women, 42% men). 67% of caregivers were aged 55 years and above, indicative of caregivers themselves ageing whilst having to take care of an aging relative; 33% were aged 20‐34 years. 97% were immediate family members taking on primary care‐giving responsibilities (51% wives, 26% husbands, 16% sons, 4% daughters) indicating high risk for caregiver burden. More than 75% of those surveyed were educated above high school, indicating rising levels of educational achievement in urban areas. 35% of caregivers were homemakers and women, highlighting necessity for low‐cost or cost‐effective models of home‐based care services. Conclusion Health systems and support mechanisms for the elderly are underdeveloped in India and require effective home‐based care models taking into consideration caregiver characteristics.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".