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Record W4206028279 · doi:10.1002/alz.055872

Novel measures to assess the association of IPA agitation criteria domains with cognition, caregiver burden and quality of life in dementia

2021· article· en· W4206028279 on OpenAlexaffabout
Lily T Guan, Ramnik Sekhon, Sharanjit Kaur, Hung‐Yu Chen, Vineetha K.V. Warriyar, Amer M. Burhan, Sarah Colman, Peter Derkach, Sarah Elmi, Maria Hussain, Linda Krisman, Vasavan Nair, Soham Rej, Aviva Rostas, David L. Streiner, Lisa Van Bussel, Tarek K. Rajji, Sanjeev Kumar, Zahinoor Ismail

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsHotchkiss Brain InstituteOntario Shores Centre for Mental Health SciencesWest Park Healthcare CentreWestern UniversityUniversity of TorontoCentre for Addiction and Mental HealthMcMaster UniversityQueen's UniversityToronto Dementia Research AllianceParkwood InstituteMcGill UniversityDouglas Mental Health University InstituteUniversity of Calgary
Fundersnot available
KeywordsDementiaCognitionRating scaleQuality of life (healthcare)PsychologyClinical Dementia RatingClinical psychologyAggressionMontreal Cognitive AssessmentCaregiver burdenCognitive impairmentPsychiatryDiseaseMedicineInternal medicineDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Background Syndromic agitation as per International Psychogeriatric Association (IPA) criteria consists of three domains: verbal aggression (VA), physical aggression (PA), and excessive motor activity (EMA). The relationships between these domains and cognition, caregiver burden, and patient quality of life are not well established. We examined these associations utilizing data from a multisite clinical trial using novel measures for these domains. Method Baseline participant data (n=128) from Standardizing Care for Neuropsychiatric Symptoms and Quality of Life in Dementia (StaN) study were utilized. Recently described IPA domain‐specific measures were implemented: domain prevalence was assessed with the NPI‐C‐IPA (derived from the Neuropsychiatric Inventory Clinician rating scale) and the CMAI‐IPA (derived from the Cohen Mansfield Agitation Inventory). Kendall’s Tau‐B was utilized for correlations between agitation domains from both scales and the Montreal Cognitive Assessment (MoCA), Severe Cognitive Impairment Rating Scale (SCIRS), Zarit Burden Inventory (ZBI), and Alzheimer’s Disease Related Quality of Life (ADRQL). Result Using the NPI‐C‐IPA, 58.3% of participants had EMA, 58.3% VA, and 72.2% PA. With the CMAI‐IPA, 70.1% had EMA, 66.9% VA, and 45.2% PA. PA in both derived rating scales was correlated with poorer performance on the SCIRS (NPI‐C‐IPA: τb= ‐.21, p = .01, CMAI‐IPA: τb= ‐.29, p<.001). NPI‐C‐IPA EMA was correlated with poorer MoCA performance (τb= ‐.31, p=.01). Agitation in all three domains on the NPI‐C‐IPA was correlated with greater caregiver burden (EMA: τb=.16, p =.02, VA: τb=.14, p=.04, PA: τb=.15, p =.02), whereas only EMA was correlated with caregiver burden on the CMAI‐IPA (τb=.13, p=.04). Across both derived scales, the PA and VA domains were significantly correlated with poorer patient quality of life (NPI‐C‐IPA VA: τb = ‐.13, p=.04, NPI‐C‐IPA PA: τb= ‐.16, p=.01, CMAI‐IPA VA: τb= ‐.14, p =.03, CMAI‐IPA PA: τb = ‐.26, p <.001). Conclusion The NPI‐C‐IPA and CMAI‐IPA both capture the IPA agitation domains, although differently. Domains measured with the NPI‐C‐IPA were more likely to correlate with the cognitive, caregiver burden, and quality of life outcomes compared to the CMAI‐IPA. Further research is required to determine the clinical significance of the differences in associations, and other salient domain‐specific features of the IPA agitation syndrome.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.122
GPT teacher head0.398
Teacher spread0.277 · 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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