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Record W2163074191 · doi:10.1310/tsr2103-228

Determining the Barriers and Facilitators to Adopting Best Practices in the Management of Poststroke Unilateral Spatial Neglect: Results of a Qualitative Study

2014· article· en· W2163074191 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2014
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsIntervention (counseling)NeglectBest practiceOccupational therapyMultidisciplinary approachMedicineAffect (linguistics)Acute carePsychologyNursingPhysical therapyHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: A gap exists between best and actual management of poststroke unilateral spatial neglect (USN). Given the negative impact of USN on poststroke recovery, knowledge translation efforts are needed to optimize USN management. To date, no study has investigated the specific barriers and facilitators affecting USN management during the acute care process. OBJECTIVE: To identify the facilitators and barriers that affect evidence-based practice use by occupational therapists (the primary discipline managing USN) when treating individuals with acute poststroke USN. METHODS: Focus group methodology elicited information from 9 acute care occupational therapists. RESULTS: Key barriers identified included lack of basic evidence-based practice skills specific to USN treatment and personal motivation to change current practices and engrained habits. Key facilitators included the presence of a multidisciplinary stroke team, recent graduation, and an environment with access to learning time and resources. Synthesized Web-based learning was also seen as important to uptake of best practices. CONCLUSION: It is estimated that upwards of 40% of patients experience poststroke USN in the acute phase, and we have evidence of poor early management. This study identified several modifiable factors that prepare the ground for the creation and testing of a multimodal knowledge translation intervention aimed at improving clinicians' best practice management of poststroke USN.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.049
GPT teacher head0.362
Teacher spread0.313 · 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