The protective impact of telecare on persons with dementia and their caregivers during the COVID‐19 pandemic
Bibliographic record
Abstract
BACKGROUND: Social distancing under the COVID‐19 pandemic has restricted access to community services for older adults with neurocognitive disorder (NCD) and their caregivers. Telehealth is a viable alternative to face‐to‐face service delivery. Telephone calls alone, however, may be insufficient. Here, we evaluated whether supplementary telehealth via video‐conferencing platforms could bring additional benefits to care‐recipient with NCD and their spousal caregivers at home. METHOD: Sixty older adults NCD‐and‐caregiver dyads were recruited through an activity centre. The impact of additional services delivered to both care‐recipient and caregiver through video conference (n=30) was compared with telehealth targeted at caregivers by telephone only (n=30), over 4 weeks in a pretest‐posttest design. Interviews and questionnaires were conducted at baseline and study’s end. RESULT: Supplementary telemedicine had averted the deterioration in the Montreal Cognitive Assessment evident in the telephone‐only group (η (p) (2)=0.50). It also reversed the falling trend in quality of life observed in the telephone only group (QoL‐AD, η (p) (2)=0.23). Varying degrees of improvements in physical and mental health (Short‐Form 36 v2), perceived burden (Zarit Burden Interview Scale) and self‐efficacy (Revised Caregiving Self‐Efficacy Scale) were observed among caregivers in the video‐conferencing group, which were absent in the telephone‐only group (η (p) (2)=0.23–0.51). CONCLUSION: Telehealth by video conference was associated with improved resilience and wellbeing to both people with NCD and their caregivers at home. The benefits were visible already after 4 weeks and unmatched by telephone alone. Video conference as the modus operandi of telehealth beyond the context of pandemic‐related social distancing should be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".