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Record W2539145575 · doi:10.1016/j.jalz.2016.06.960

P1‐212: Application of Actigraphy to Measuring Agitation in Older Adults with Dementia

2016· article· en· W2539145575 on OpenAlexaffabout
Dallas Seitz

Bibliographic record

VenueAlzheimer s & Dementia · 2016
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsActigraphyDementiaPhysical therapyComorbidityPsychomotor agitationMedicinePsychologyPhysical medicine and rehabilitationPsychiatryDiseaseInternal medicineInsomnia

Abstract

fetched live from OpenAlex

Agitation is among the most common behavioral symptoms in dementia. At the present time agitation is commonly assessed using questionnaires which can have limited reliability and validity. Actigraphy, or electronic motion analysis actigraphy may be well suited to assessment of agitation although there have been few studies evaluating actigraphy for the measurement of agitation. We selected individuals aged 65 and older admitted to a geriatric psychiatry dementia inpatient units and one long-term care facility in Ontario. We included individuals with diagnosis of Alzheimer’s disease who could mobilize independently. Baseline measures will included demographics, measures of cognitive impairment, dementia severity, medical comorbidity and medications. Following collection of baseline data, actigraphs (Actigraph wGT3x+) were worn by participants for seven continuous days. The Cohen-Mansfield Agitation Inventory (CMAI) and other behavioral symptom measures were completed by nursing staff for the same time period during which actigraphy was recorded. The study sample was then categorized into two groups: low agitation (CMAI < 50) or high agitation (CMAI ≥ 50). The differences in mean motor activity (MMA) and other actigraphy measures of actigraphy were compared between these groups. A total 20 participants were included in the study sample. The average age of sample was 74.3 years (SD: 8.69), 80% of particants were male, and the mean MMSE score for the study sampl was 11.63 (SD: 9.62). Overall, baseline CMAI scores were 46.7 (SD: 13.25) with 13 participants categorized as having low agitation and 7 as having high agitation. The average duration of time that actigraphs were worn by participants was 6.27 (SD: 1.32) days out of 7 days. The MMA in the high agitation group was significantly higher than the low agitation group (180.23 vs 81.51, P=<0.0001). Overall MMA was strongly correlated with CMAI total scores (r=0.74, P<0.001) as well as verbal agitation and non-aggressive physical agitation scores on the CMAI. Motor activity as measured by actigraphy is highly correlated with standard questionnaire based methods for measuring agitation in individuals with dementia. Additional studies are required to further understand how actigraphy may be used to better characterize and treat agitation in this population.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.282
Teacher spread0.265 · 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

Citations4
Published2016
Admission routes2
Has abstractyes

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