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Record W1969507824 · doi:10.1097/won.0b013e3181d73aab

Bates-Jensen Wound Assessment Tool

2010· article· en· W1969507824 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.

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2010
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsKahnawake Education CenterRichmond HospitalYork UniversitySouthlake Regional Health CenterCARE Canada
Fundersnot available
KeywordsBATESWound careMedicineLikert scaleSurgeryPsychology

Abstract

fetched live from OpenAlex

PURPOSE: A group of 3 WOC nurses and a nurse researcher, in partnership with the author of the Bates Wound Assessment Tool (BWAT), sought to validate wound photographs depicting each characteristic of the instrument. INSTRUMENT: The BWAT contains 13 items that assess wound size, depth, edges, undermining, necrotic tissue type, amount of necrotic, granulation and epithelialization tissue, exudate type and amount, surrounding skin color, edema, and induration. These are rated using a modified Likert scale; a score of 1 indicates the healthiest and 5 indicates the most unhealthy attribute for each characteristic. In 2001, the PSST was revised and renamed the Bates-Jensen Wound Assessment Tool to reflect the global use of the tool with wound types beyond pressure ulcers. METHODS: Phase 1 involved the selection of digitalized wound photographs for 11 of the BWAT wound characteristics by the researchers. The photographs needed to be of high resolution and good quality for eventual publication and validated by the original BWAT author as being representative of the intended characteristic. In phase 2, a face-to-face validation exercise was completed to include, edit, or exclude these photographs. Corrections were made; additional photographs were obtained for the remaining characteristics and to replace those not validated. Phase 3 involved an electronic survey that achieved validation online. PARTICIPANTS: Phase 2 participants consisted of 15 WOC nurses with a mean of 11.5 years of experience with wounds. Phase 3 had 8 WOC nurses and 1 master's prepared wound care specialist, with approximately 10 years of experience. One third of participants in each phase were familiar with the BWAT. In a separate exercise to rate photographs that would be used for testing the implementation of the pictorial guide, 7 WOC nurses and 2 RNs who used the BWAT regularly and 2 researchers participated in a face-to-face discussion. RESULTS: A total of 214 photographs were reviewed in this study. Seventy-three percent (n = 55) of the photographs for the pictorial guide were endorsed in phase 2, and 100% (n = 53) in phase 3 to demonstrate the 65 BWAT characteristics. In addition, photographs that could be used for a competency exercise and for pre- and posttests were also rated by the panels. CONCLUSIONS: The photographic content of the BWAT pictorial guide has been validated by a small group of wound care experts. The purpose of the exercise was to create a visual learning aid to enhance the education around wound assessment and as a resource for nurses in practice. Now published in a pocket guide format, it is a standardized way to teach BWAT wound assessment skills in a consistent format.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.404
Teacher spread0.383 · 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