Behind the Scenes of a Technologically Enhanced Intervention for Caregivers of People With Dementia: Protocol for a Feasibility and Acceptability Study
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease affects 55 million people worldwide. As the disease progresses, these individuals require a devoted caregiver, often a family member, who provides evolving complex care. Caregivers can experience a variety of ongoing stressors, resulting in reductions in caregiver emotional well-being (and other quality-of-life indicators). Information and communication technologies provide an excellent opportunity to train caregivers remotely and help them to manage these stressors and related distress. OBJECTIVE: This protocol describes the theoretical rationale, study design, and methods of a new, technologically enhanced psychoeducational skill-building intervention for caregivers of people with dementia that includes a virtual reality component. METHODS: Through Alzheimer's Eyes is a 4-week, single-arm, pre-post test pilot study consisting of 4 sessions of 90 minutes each that are delivered by videoconferencing. These sessions include a weekly virtual reality experience characterizing the journey of an older Latina with Alzheimer's disease from her perspective to help caregivers see through the eyes of a person with dementia. The 4 sessions cover the skill-training topics of communication, managing challenging behaviors and unhelpful thoughts, the importance of self-care, and mindfulness-all of which are key components designed to reduce stress and distress in family caregivers. Individual interviews conducted before and after the intervention gather participant insights into the intervention, evaluate its feasibility and acceptability, and assess its impact on key outcomes. RESULTS: Data collection for the study started in January 2022, and the results are expected to be submitted for publication in the second half of 2023. Twenty caregivers from the United States have completed the workshop to date. Preliminary data gathered from these participants support the intervention's feasibility and acceptability. CONCLUSIONS: Through Alzheimer's Eyes leverages existing technology combined with psychoeducational skill building to help caregivers manage their stress, regardless of their location. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42655.
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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 | 0.030 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.048 | 0.008 |
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".