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Record W2796174116 · doi:10.5539/gjhs.v10n5p62

Pain Assessment in People With Dementia: Remaining Controversies

2018· article· en· W2796174116 on OpenAlexvenueno aff
Mohammad Rababa

Bibliographic record

VenueGlobal Journal of Health Science · 2018
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaObservational studyPain assessmentPopulationMedicinePain catastrophizingPsychologyPsychiatryChronic painPhysical therapyPain managementDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Pain in people with dementia is under recognized, underestimated, and under-treated due to the complexity of pain assessment in this population.SUMMARY: Self-report tools are the gold standard of pain assessment. However, people with dementia are not always able to clearly and meaningfully self-report their pain. Self-report tools capture the affective experience of pain, which is impaired in people with dementia. Observational pain tools are more useful to assess pain especially in people with advanced dementia who are unable to self-report. Observational pain tools capture the physical component of pain experience, which is unchanged in people with dementia. However, nurses often misunderstand the behavioral changes associated with pain in people with dementia. Also, there is a huge inconsistency in presentation of these behavioral changes associated with pain among people with dementia as behaviors can be due to multiple different unmet needs, pain being one.

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)0.007
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 score0.016
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.341
Teacher spread0.326 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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