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Record W2979441551 · doi:10.21926/obm.geriatr.1903076

The “PRIMING, TIMING, MIMING” Model of Individualized Behavioural Care Planning for Residents with Dementia

2019· article· en· W2979441551 on OpenAlexaff
Lindy A. Kilik

Bibliographic record

VenueOBM Geriatrics · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsQueen's UniversityProvidence Health Care
Fundersnot available
KeywordsDementiaPlan (archaeology)PsychologyOutreachPriming (agriculture)NursingMedicineComputer scienceMedical education

Abstract

fetched live from OpenAlex

The current paper introduces the “Priming/Timing/Miming” Model of Behavioural Care Planning for persons with Dementia. This simple heuristic provides a quick, easy and systematic way to select from the vast number of behavioural strategies offered in the BPSD literature and to organize these in a way that can be incorporated into an individualized Behaviour Care Plan to deliver personal care to persons with dementia and also to develop a larger plan of care. An entire care plan is captured on one double-sided sheet of paper that can be updated by simply highlighting the relevant sections at team meetings. It has also been accommodated into electronic charting. An example using the “Priming/Timing/Miming” Care Plan document is provided. The model and document were developed with Multi-disciplinary input over more than a decade, on several inpatient dementia units. Training to use the model and care plan has been provided to numerous groups including Long-Term Care facilities, Retirement Homes, Dementia Units, Acute Care Hospital Units, Inpatient Acquired Brain Injury Staff and Outreach Teams. The model and care plan document are robust, successfully accommodating a wide range of behavioural presentations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.094
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

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

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 head0.050
GPT teacher head0.336
Teacher spread0.286 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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