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Record W2215739320 · doi:10.1155/2011/463407

Evaluation of the Iconic Pain Assessment Tool by a Heterogeneous Group of People in Pain

2011· article· en· W2215739320 on OpenAlexafffund
Chitra Lalloo, James L. Henry

Bibliographic record

VenuePain Research and Management · 2011
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoMcMaster University
KeywordsContext (archaeology)Chronic painRating scalePopulationSample (material)Pain assessmentPsychologyPhysical therapyMedicineApplied psychologyPhysical medicine and rehabilitationPain managementDevelopmental psychology

Abstract

fetched live from OpenAlex

The Iconic Pain Assessment Tool (IPAT) is a novel web-based instrument for the self-report of pain quality, intensity and location in the form of a permanent diary. Originally designed for people with central poststroke pain, the tool is being adapted for a larger, more diverse patient population. The present study aimed to collect evaluative feedback on the IPAT from a heterogeneous sample of individuals with chronic pain. The specific study aims were to evaluate participant comfort with the tool including enjoyment, ease of use and comfort with the electronic medium; to assess perceived value of the tool for communicating pain quality, intensity and location; to gauge participant intent to share their pain diaries with others and use the tool on a regular basis to track their pain over time; to assess the perceived descriptiveness of current IPAT icons and the numerical rating scale; and to identify strengths and weaknesses of the tool to refine the existing prototype. Written and verbal feedback from individuals with a variety of chronic pain conditions (n=23) were collected in the context of these objectives. Overall, the IPAT was positively endorsed by this heterogeneous sample of people in pain. The authors concluded that the IPAT is a user-friendly instrument that has the potential to help people express, document and share their personal experience with 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 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)0.069
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0690.001
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 head0.062
GPT teacher head0.370
Teacher spread0.308 · 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.

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

Citations29
Published2011
Admission routes2
Has abstractyes

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