VOICE FIRST TECHNOLOGY: SIMPLIFYING LIFE FOR COMMUNITY-DWELLING OLDER ADULTS LIVING WITH DEMENTIA
Bibliographic record
Abstract
Abstract Voice first technology offers older adults with dementia support that may maintain independence, reduce social isolation and improve quality of life (QoL). This study investigates the impact of a voice-controlled technology customized to the needs of participants living with dementia and their caregivers. A mixed methods design focused on psychosocial factors and usability characteristics. The purposive sample consisted of older adults with dementia (n=12) and their care partners (n=12)) living independently in the community. Validated measures for cognition, depression, caregiver burden, quality of life and usability were included. Qualitative in-home interviews were conducted to assess impact on social connections and independence. Results indicate that voice first technology can reduce caregiver burden and can support the independence and QoL of older adults with dementia. The discussion considers the value of low cost voice first technology as a way to support older adults with dementia and their caregivers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".