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Record W4408096074 · doi:10.1080/01609513.2025.2471365

Effectiveness of a fitness- and socialization-based intervention for couples living with young-onset dementia

2025· article· en· W4408096074 on OpenAlexaff
Christina E. Gallucci, Anna Santiago, Elaine Kohn, Lisa Benaim, Susana Braslavski, Arlene Consky, Anne Max, Yael Bar, Adriana Shnall

Bibliographic record

VenueSocial Work With Groups · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsSocializationIntervention (counseling)DementiaPsychologyDevelopmental psychologyClinical psychologyGerontologyPsychiatryMedicineDisease

Abstract

fetched live from OpenAlex

There is a dearth of age- and life stage-appropriate supports available to spousal couples living with young-onset dementia (YOD; dementia that develops under 65). The purpose of this study was to design, implement, and evaluate the effectiveness of a novel, social worker-led group fitness- and socialization-based support program for individuals with YOD and their spousal caregivers. Caregivers’ program experiences were explored during a focus group, supplemented with quantitative survey data. Six YOD couples participated in the program, five of which attended the focus group. Three themes were generated: Navigating Life with YOD, Perceived Effectiveness of the Program on Psychosocial Outcomes, and Program Feedback and Scaling Considerations. The results suggest that this low-cost, feasible, and tailored intervention was valued by YOD couples, as it enabled them to participate in a meaningful fitness and socialization activity together to promote self-care, improve psychosocial outcomes, and connect with others facing similar experiences.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.303
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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