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Record W6992179418

"A Labour of Love": Caregiver Perspectives of Aging in Place with Dementia

2024· article· en· W6992179418 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaPhenomenology (philosophy)CredibilityDepictionPerspective (graphical)Lived experienceAged careTriangulationPublic healthAging in place
DOInot available

Abstract

fetched live from OpenAlex

Objective: The majority (69%) of persons with dementia (PwD) in Canada reside at home, relying on support from family and/or friends that act as caregivers (CGs), a particularly stressful and time-consuming role (CIHI, 2018). While PwD wish to age in place, this group is at high risk of long-term care admission (Wiles et al., 2011; Huyer et al., 2020). This research examines the lived experiences of PwD and their CGs who are aging in place, using the social ecological model to provide a comprehensive understanding of the barriers to aging in place.\nMethods: Phenomenology was the theoretical orientation used to guide this research to present an accurate depiction of lived experience. Backgrounds questionnaires were administered to prior for one-on-one semi-structured interviews, which were transcribed verbatim for analysis. Field notes, member checks, and triangulation were used to enhance the credibility of the study.\nResults: Participants emphasized individuality associated with caregiving and dementia journeys. CGs cited positive and negative aspects of aging in place. Through analysis, three themes were developed: (1) “Pivot, pivot, pivot”, (2) They don’t make it easy, and (3) “Balancing act”. \nImplications: Interviews provided knowledge concerning unmet needs and systematic issues faced by CGs and PwD, and their subsequent effect on care provision. Their stories provide a unique perspective of aging in place with dementia from those who experience it firsthand. Overall, these findings shed light on the need for reform in health care policies to address systemic barriers and 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)0.008
metaresearch head score (Gemma)0.011
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 score0.018
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.012
Scholarly communication0.0060.007
Open science0.0010.009
Research integrity0.0020.004
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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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
Published2024
Admission routes1
Has abstractyes

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