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Record W4220690471 · doi:10.1002/9781119701170.ch40

Pain in older adults: a brief clinical guide

2022· other· en· W4220690471 on OpenAlexaff
Thomas Hadjistavropoulos, Una E. Makris

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsModalitiesPsychosocialPsychological interventionMedicineContext (archaeology)DementiaPhysical therapyEpidemiologyPain managementPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Pain affects people of all ages with epidemiological studies reporting exceedingly high prevalence rates of pain in general community samples and even higher rates in institutional settings. Psychosocial interventions are normally offered either within the context of interdisciplinary treatment or in combination with other treatment modalities such as physiotherapy or pharmacological treatment. Several psychosocial pain management interventions have shown considerable initial promise with older adults although more research needed in this area. Pharmacological therapies for pain management are used, often in conjunction with non-pharmacologic modalities, when pain and functional limitations persist despite trials of other modalities. Non-pharmacological approaches may suffice for mild or mild-to-moderate pain. Research with seniors with dementia, who reside in long-term care facilities, has supported the view that the use of regular and routine pain assessment leads to improved pain management practices.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0440.034

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 head0.017
GPT teacher head0.323
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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