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Record W4386386519 · doi:10.1111/iwj.14371

Facilitators and barriers to pressure injury prevention, management and education: Perspectives from healthcare professionals—A qualitative study

2023· article· en· W4386386519 on OpenAlexaff
Nicole Cesca, Ann Szczepanski, Walee Malik, Manpreet Kaur Cheema, Tilak Dutta, Jill I. Cameron, Sharon Gabison

Bibliographic record

VenueInternational Wound Journal · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineQualitative researchNursingHealth carePsychological interventionPressure injuryHealth professionalsFamily medicine

Abstract

fetched live from OpenAlex

This study aims to (1) characterize healthcare professionals' (HCPs') experiences related to the prevention and management of pressure injuries (PIs) and (2) explore the educational needs of individuals with a past or current history of PIs and their caregivers from the perspective of HCPs. This is a qualitative descriptive study. HCPs (n = 18) were interviewed using a semi-structured interview guide. Interviews were audio-recorded, transcribed verbatim and coded using NVivo. Three overarching themes encompassing various dimensions were identified: (1) Facilitators related to PI prevention and management, (2) Challenges related to PI prevention and management and (3) Recommendations for improving patient and caregiver PI education. HCPs identified a greater number of challenges than facilitators related to PI care. This study emphasizes the importance of a patient-centred and interprofessional approach to patient education for PI prevention and management. Meaningful interventions focused on the patient may improve health literacy and empower patients and caregivers in PI care. Investing in preventive measures and raising awareness are crucial to reducing PI incidence. The findings have implications for HCPs and researchers seeking to enhance patient care and promote effective PI prevention strategies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.999

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)0.0020.000

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 head0.035
GPT teacher head0.485
Teacher spread0.451 · 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 designQualitative
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

Citations9
Published2023
Admission routes1
Has abstractyes

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