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Record W4312066943 · doi:10.1177/02692155221144891

Exemplary post-discharge stroke rehabilitation programs: A multiple case study

2022· article· en· W4312066943 on OpenAlexafffundabout
Mary Egan, Debbie Laliberté Rudman, Monique Lanoix, Matthew J. Meyer, Elizabeth Linkewich, Phyllis Montgomery, Jenn Fearn, Beth Donnelly, Margo Collver, Shauna Daly

Bibliographic record

VenueClinical Rehabilitation · 2022
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsBruyèreOttawa HospitalLaurentian UniversityHealth Sciences CentreLondon Health Sciences CentreSunnybrook Health Science CentreWestern UniversityHealth Sciences NorthSaint Paul UniversityUniversity of Ottawa
FundersInstitute of Health Services and Policy Research
KeywordsRehabilitationExploratory researchQualitative researchService providerFocus groupMedicineNursingStroke (engine)Health careBest practiceService (business)PsychologyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to identify essential aspects of exemplary post-discharge stroke rehabilitation as perceived by patients, care partners, rehabilitation providers, and administrators. DESIGN: We carried out an exploratory qualitative, multiple case study. Stroke network representatives from four regions of the province of Ontario, Canada each nominated one post-discharge rehabilitation program they felt was exemplary. SETTING: The programs included: a mixed home- and clinic-based service; a home-based service; a clinic-based service with a stroke community navigator and; an out-patient clinic-based service. PARTICIPANTS: Participants included 32 patients, 16 of their care partners, 23 providers, and 5 administrators. METHODS: We carried out semi-structured qualitative interviews with patients and care partners, focus groups with providers, and semi-structured interviews with administrators. Health records of patient participants were reviewed. Using an interpretivist-informed inductive content analysis, we developed overarching categories and subcategories first for each program and then across programs. RESULTS: Across four regions with differing types of programs, exemplary care was characterized by three essential components: stroke and stroke rehabilitation knowledge, relationship built through personalized respectful care, and a commitment to high quality, person-centered care. CONCLUSION: Exemplary post-discharge care included knowledge regarding identification and treatment of stroke-related impairment, that is, information found in best practice guidelines. However, expertise related to building relationship through providing personalized respectful care, within a mutually supportive, improvement-oriented team was also essential. Additionally, administrators played a crucial role in ensuring continued ability to deliver exemplary care.

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)0.005
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.043
GPT teacher head0.383
Teacher spread0.340 · 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 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

Citations3
Published2022
Admission routes3
Has abstractyes

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