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Record W2569066944 · doi:10.1016/j.pmrj.2016.12.004

Patient‐Centered Goal Setting in a Hospital‐Based Outpatient Stroke Rehabilitation Center

2017· article· en· W2569066944 on OpenAlexafffund
Danielle B. Rice, Amanda McIntyre, Magdalena Mirkowski, Shannon Janzen, Ricardo Viana, Eileen Britt, Robert Teasell

Bibliographic record

VenuePM&R · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSt Joseph's Health CareWestern UniversityParkwood InstituteLawson Health Research Institute
FundersSchulich School of Medicine and DentistryAllerganSchulich School of Medicine and Dentistry, Western UniversityWestern University
KeywordsRehabilitationMedicinePatient satisfactionStroke (engine)Goal settingPhysical therapyPhysical medicine and rehabilitationSet (abstract data type)Outpatient clinicPsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Goal-setting can have a positive impact on stroke recovery during rehabilitation. Patient participation in goal formulation can ensure that personally relevant goals are set, and can result in greater satisfaction with the rehabilitation experience, along with improved recovery of stroke deficits. This, however, not yet been studied in a stroke outpatient rehabilitation setting. OBJECTIVE: To assess patient satisfaction of meeting self-selected goals during outpatient rehabilitation following a stroke. DESIGN: Retrospective chart review. SETTING: Stroke patients enrolled in a multidisciplinary outpatient rehabilitation program, who set at least 1 goal during rehabilitation. PARTICIPANTS: Patients recovering from a stroke received therapy through the outpatient rehabilitation program between January 2010 and December 2013. METHODS: Upon admission and discharge from rehabilitation, patients rated their satisfaction with their ability to perform goals that they wanted to achieve. Researchers independently sorted and labeled recurrent themes of goals. Goals were further sorted into International Classification of Functioning, Disability and Health (ICF) categories. To compare the perception of patients' goal satisfaction, repeated-measures analysis of variance was conducted across the 3 ICF goal categorizations. MAIN OUTCOME MEASURE: Goal satisfaction scores. RESULTS: A total of 286 patients were included in the analysis. Patient goals concentrated on themes of improving hand function, mobility, and cognition. Goals were also sorted into ICF categories in which impairment-based and activity limitation-based goals were predominant. Compared to activity-based and participation-based goals, patients with impairment-based goals perceived greater satisfaction with meeting their goals at admission and discharge (P < .001). Patient satisfaction in meeting their first-, second-, and third-listed goals each significantly improved by discharge from the rehabilitation program (P < .001). CONCLUSION: Within an outpatient stroke rehabilitation setting, patients set heterogeneous goals that were predominantly impairment based. Satisfaction in achieving goals significantly improved after receiving therapy. The type of goals that patients set were related to their goal satisfaction scores, with impairment-based goals being rated significantly higher than activity-based and participation-based goals. LEVEL OF EVIDENCE: III.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.273
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations63
Published2017
Admission routes2
Has abstractyes

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