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The Role of Qualitative Research in Understanding Diabetic Foot Ulcers and Amputation

2014· review· en· W2026507818 on OpenAlexaff
Janet L. Kuhnke, Patricia Hill Bailey, M. Gail Woodbury, M Burrows

Bibliographic record

VenueAdvances in Skin & Wound Care · 2014
Typereview
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsSt. Lawrence CollegeLaurentian UniversityQueen's University
Fundersnot available
KeywordsQualitative researchMedicineCompetence (human resources)AmputationDiabetic footDiseaseDiabetes mellitusNursingPerspective (graphical)SurgeryPathologyPsychology

Abstract

fetched live from OpenAlex

PURPOSE: To enhance the learner's competence with knowledge about using qualitative methodologies to understand diabetic foot ulcers and amputations. TARGET AUDIENCE: This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVES: After participating in this educational activity, the participant should be better able to:1. Analyze qualitative research methodologies.2. Summarize how conclusions from qualitative research relate to diabetes mellitus and its complications. Persons living with diabetes are at high risk for foot complications, lower extremity trauma, injury, ulceration, infection, and potential amputation. Qualitative health research helps to explore and understand more fully the complexities of diabetes. Qualitative health research seeks to understand what is happening and going on for the individual and his/her support persons. In addition, qualitative health research enables clinicians to appreciate how different qualitative research approaches can explore illness from the perspective of the individual living with the disease.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.113
GPT teacher head0.498
Teacher spread0.385 · 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 designOther design
Domainnot available
GenreReview

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

Citations8
Published2014
Admission routes1
Has abstractyes

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