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Record W7117317396 · doi:10.1002/alz70858_106983

Discrepancies in Dementia Severity Perceptions: Exploring the Agreement Between Care Partners and Clinical Assessments

2025· article· en· W7117317396 on OpenAlexaff
Paige DiStefano, Harmonie Chan, Jyothy Nair, M. Kate Stewart, Samantha Shune, Nan Uzbalis, Ashwini Namasivayam‐MacDonald

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDementiaPerceptionAgreementClinical judgmentClinical PracticeMEDLINECognition

Abstract

fetched live from OpenAlex

BACKGROUND: Informal family care partners are crucial in dementia care, serving as primary advocates and caregivers. A caregivers' perception of their care recipient's dementia severity, whether they overestimate or underestimate the progression, can impact care satisfaction and applicability. Overestimation may lead to unnecessary interventions or distress, while underestimation can delay critical support. Caregivers offer valuable insights extending beyond clinical scores, capturing nuances essential for effective care planning. This study investigates the agreement between caregivers' perception of dementia severity and clinical severity assessment, and how demographic and contextual factors influence accuracy. METHOD: Data were collected from a convenience sample of 22 dyads. Caregivers were eligible if they were 18 years or older, spoke and read English, and provided unpaid care to a family member with dementia for at least 2 months. Caregivers completed surveys ranking their perception of their care recipient's dementia severity (e.g., mild, moderate, severe, very severe), along with various demographic and contextual factors. A collapsed version of the Clinical Dementia Rating (CDR) scale, administered by certified staff, objectively measured dementia severity. Agreement between caregivers' perceived dementia severity and CDR severity was evaluated, and additional analyses identified predictors of accuracy. RESULT: Forty-five percent of caregivers (age = 62.8±14.7; 82% female) overestimated their care recipients' (age = 81±9.6; 50% female) dementia severity (i.e., 70% of mild cases; 17% of moderate; 100% of severe), and eighteen percent underestimated severity (i.e., 17% of moderate cases; 75% of very severe). There was a significant positive association between caregivers' perceived dementia severity and CDR severity (p = 0.041), indicating that perceived severity increased as CDR severity increased (OR=2.4). There was weak agreement between perceived and CDR severity (K = 0.1; p >0.05). No demographic or contextual factors influenced perception accuracy. CONCLUSION: While caregivers' perceptions of dementia severity often diverge from clinical assessments, they reflect the lived reality. Acknowledging the tendency to overestimate, improved communication and education between dyads and providers is vital. Dynamic knowledge sharing will help align expectations and ensure sufficient support is provided based on the needs of the care recipient, not solely their clinical score.

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)0.021
metaresearch head score (Gemma)0.064
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.108
GPT teacher head0.442
Teacher spread0.334 · 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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