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Record W602669826 · doi:10.1155/2009/642352

Assessing Pain in Children with Intellectual Disabilities

2009· review· en· W602669826 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePain Research and Management · 2009
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsSaint Mary's UniversityIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health Research
KeywordsIntellectual disabilityPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Children with intellectual and developmental disabilities suffer more often from pain than their typically developing peers. Their pain can be difficult to manage, and assessment is often complicated by their limited communication skills, multiple complex pain problems and the presence of maladaptive behaviours. However, current research does provide some guidance for assessing their pain. Although self-report is an alternative for a small number of higher-functioning children, observational measures have the most consistent evidence to support their use at this time. For this reason, the Noncommunicating Children's Pain Checklist--Postoperative Version is recommended for children and youth 18 years of age or younger. However, other measures should be consulted for specific applications. Changes in function and maladaptive behaviour should also be considered as possible reflections of pain. In addition, children's coping skills should be considered because improving these may reduce the negative impact of pain.

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.

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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.435
Teacher spread0.316 · 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