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Record W2096518596 · doi:10.1177/0164027507312113

Social Representations of Barriers to Care Early in the Careers of Caregivers of Persons With Alzheimer's Disease

2008· article· en· W2096518596 on OpenAlexaff
Normand Carpentier, Francine Ducharme, Marie‐Jeanne Kergoat, Howard Bergman

Bibliographic record

VenueResearch on Aging · 2008
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsMcGill UniversityUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsDenialDementiaPsychologyCognitionSet (abstract data type)DiseaseFamily caregiversCognitive impairmentGerontologyDevelopmental psychologyPsychiatryMedicinePsychotherapist

Abstract

fetched live from OpenAlex

The first signs of cognitive impairment in the elderly generally elicit much concern among family members. Reactions run from denial to the active search for information. Some families manage to set up relatively well-organized networks of informal support to help both caregivers and elderly relatives. However, little is known about the processes underlying the different pathways that families follow at the onset of Alzheimer-type dementia in elderly relatives. To gain a better understanding of barriers to care early in the caregiving career, from the first signs of illness to diagnosis, the authors conducted interviews with 52 caregivers recruited at two cognition clinics. Barriers to help resources were analyzed from the viewpoint of social representations. This approach allowed the consideration of a broad range of individual and group phenomena capable of fashioning caregivers' representations of this period. The results confirmed the importance of the symbolic dimension of experience in steering social practice.

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)0.003
metaresearch head score (Gemma)0.013
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 score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.125
GPT teacher head0.463
Teacher spread0.337 · 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

Citations86
Published2008
Admission routes1
Has abstractyes

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