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Record W2441544877 · doi:10.1080/09638288.2016.1185469

Defining mild, moderate, and severe pain in young people with physical disabilities

2016· article· en· W2441544877 on OpenAlexaff
Jordi Miró, Rocío de la Vega, Ester Solé, Mélanie Racine, Mark P. Jensen, Santiago Galán, Joyce M. Engel

Bibliographic record

VenueDisability and Rehabilitation · 2016
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsWestern University
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Neurological Disorders and StrokeInstitució Catalana de Recerca i Estudis AvançatsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentMuscular Dystrophy Association
KeywordsPhysical therapyCerebral palsyMedicineIntensity (physics)Pain catastrophizingYoung adultPhysical medicine and rehabilitationChronic painPhysical disability

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to identify the cutoffs that are most suitable for classifying average and worst pain intensity as being mild, moderate, or severe in young people with physical disabilities. METHOD: Survey study using a convenience sample of 113 young people (mean age = 14.19; SD = 2.9; age range: 8-20) with physical disabilities (namely, spinal cord injury, cerebral palsy, spina bifida, limb deficiency (acquired or congenital), or neuromuscular disease). RESULTS: The findings support a non-linear association between pain intensity and pain interference. In addition, the optimal cutoffs for classifying average and worst pain as mild, moderate, or severe differed. For average pain, the best cutoffs were the following: 0-3 for mild, 4-6 for moderate, and 7-10 for severe pain, whereas the optimal classification for worst pain was 0-4 for mild, 5-6 for moderate, and 7-10 for severe pain. CONCLUSIONS: The findings provide important information that may be used to help make decisions regarding pain treatment in young people with disabilities and also highlight the need to use different cutoffs for classifying pain intensity in young people with disabilities than those that have been suggested for adults with chronic pain. Implications for rehabilitation Most clinical guidelines make treatment recommendations based on classifications of pain intensity as being mild, moderate, and severe that do not have a clear cut association with pain intensity ratings. Cutoffs that are deemed to be the most appropriate for classifying pain intensity as mild, moderate, and severe appear to depend, at least in part, on the pain population that is being studied and pain domain that is being used. This work helps to advance our knowledge regarding the meaning of pain intensity ratings in young people with physical disabilities. Clinicians can use this information to make empirically guided decisions regarding when to intervene in young people with disabilities and chronic 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.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.252
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations27
Published2016
Admission routes1
Has abstractyes

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