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Record W4414361100 · doi:10.1017/s0714980825100287

Caregiver Perspectives of Aging in Place with Dementia: A Qualitative Exploration of Barriers Using the Social Ecological Model

2025· article· en· W4414361100 on OpenAlexaffabout
Jeanne Russell, Paula C. Fletcher

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsDementiaAging in placeFocus groupQualitative researchHealthy agingSocial ecological modelSocial supportIndependent living

Abstract

fetched live from OpenAlex

Abstract Most persons living with dementia in Canada reside at home, relying on support from family and/or friends as caregivers. Evidentially, knowledge gaps exist when trying to understand how caregivers and persons living with dementia can be better supported in their community and health care environments. This research examined the effect of aging in place with a focus on providing a comprehensive understanding of the barriers to aging in place for persons living with dementia and their caregivers using the social-ecological model. Fourteen caregivers were recruited to participate in one-on-one semi-structured interviews. The subsequent theme, they do not make it easy , emphasizes issues faced with community and societal domains of aging in place care. These findings shed light on the unmet needs of persons living with dementia and their caregivers while aging in place, as well as the need to address systemic barriers to sincerely promote aging in place for all persons.

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)0.014
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0150.010
Scholarly communication0.0050.004
Open science0.0020.007
Research integrity0.0010.003
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 head0.040
GPT teacher head0.352
Teacher spread0.312 · 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 designQualitative
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 routes2
Has abstractyes

Explore more

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