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Record W2077293160 · doi:10.1097/bcr.0b013e31820aaf09

Health Professionalsʼ and Consumersʼ Opinion: What Is Considered Important When Rating Burn Scars From Photographs?

2011· article· en· W2077293160 on OpenAlexaboutno aff
Megan Simons, Zephanie Tyack

Bibliographic record

VenueJournal of Burn Care & Research · 2011
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRating scaleScarsHealth careVascularityScale (ratio)Surgery

Abstract

fetched live from OpenAlex

With advances in wound care technology, there is a trend toward patients undertaking specialist burns treatment in an outpatient capacity. Photographic scar evaluation is a part of this trend in some health services because it permits scar assessment by different health professionals, both within and across outpatient services, to assess the impact of scar management strategies. The aim of this study was to explore the parameters considered integral to scar assessment when completing photographic scar evaluation. First, opinions were sought from 38 burn health professionals in 2 tertiary pediatric hospitals who participated in focus groups where in-person and in-photograph scar rating were completed using three burn scar rating scales (modified Vancouver scar scale, Manchester scar scale, and patient and observer scar assessment scale) presented with a standard format and instructions. Second, 36 occupational therapists and physiotherapists from Australia and New Zealand completed questionnaires. Third, 10 healthcare consumers from 1 tertiary pediatric hospital participated in face-to-face or telephone interviews. Parameters believed to be assessed using photographic evaluation of burns scarring were vascularity, surface area, color, contour, height, and overall opinion. However, surface area was considered questionable as an indicator of scar maturity. These parameters mostly differ from those considered important in a burn scar outcome measure when rating scars in-person: height/thickness, vascularity, color, pliability, joint function, and patient/client opinion. A categorical scale with visual descriptors, as well as specific strategies to improve photographic technique, may go some way to addressing the perceived difficulty in rating these parameters using burn scar photographs.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.182
GPT teacher head0.450
Teacher spread0.269 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

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