Virtual Life Story Club Intervention to Improve Loneliness and Apathy in Community-Dwelling Older Adults: Protocol for a Mixed Methods Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Reminiscence therapy is a noninvasive, nonpharmacological intervention that has been shown to improve cognition, mood, functional status, quality of life, and apathy in older adults. Group reminiscence therapy combines structured social engagement and recounting of personal stories that address both social connection (a risk factor for cognitive decline) and cognition. Life Story Club is an established, nonprofit organization that provides virtual group reminiscence therapy for older adults to reduce loneliness and promote a sense of belonging and has not been formally studied. OBJECTIVE: This study aims to explore the feasibility of a Life Story Club intervention to improve loneliness and apathy in community-dwelling older adults. METHODS: A prospective, single-arm, single-center, pilot study will be conducted to compare loneliness and apathy in 50 lonely individuals without dementia at baseline who receive a virtual group reminiscence therapy intervention. The intervention will be delivered weekly over 12 weeks. Loneliness will be assessed with the UCLA Loneliness Scale and apathy will be assessed with the Apathy Evaluation Scale before and after the intervention. Feasibility will be assessed using quantitative and qualitative measures including feasibility of screening and enrollment, acceptability, and program satisfaction. Qualitative interviews will be conducted with a subset of 30 individuals to explore acceptability, barriers, and facilitators of the intervention. RESULTS: The proposed study is funded by a pilot grant from the Institute for Clinical and Translational Research at Albert Einstein College of Medicine. Recruitment and data collection are planned for July 2025. CONCLUSIONS: This study will provide evidence for the feasibility of virtual group reminiscence therapy for community-dwelling older adults to reduce loneliness and apathy. Our approach is both innovative and pragmatic because we will leverage an existing community-based service, with an established infrastructure and track record within the community to deliver the intervention. As such, the proposed research has the potential for broad implications for community-based research and aligns with multiple translational science principles. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/70518.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".