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Record W4387411610 · doi:10.5014/ajot.2023.050193

Being and Becoming an Evidence-Based Practitioner: Occupational Therapists’ Journey Toward Expertise

2023· article· en· W4387411610 on OpenAlexaffabout
Aliki Thomas, Fatima Amari, Maria Mylopoulos, Brigitte Vachon, Anita Menon, Annie Rochette

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of TorontoInstitut Universitaire en Santé Mentale de QuébecMcGill UniversityUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsThematic analysisEvidence-based practiceOccupational therapyContext (archaeology)Openness to experiencePsychologyKnowledge translationRelevance (law)RehabilitationMedical educationQualitative researchNursingMedicineKnowledge managementSocial psychologyAlternative medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Despite mounting evidence for the management of various health care conditions, the uptake of scientific evidence in occupational therapy is often suboptimal. Although positive attitudes and self-efficacy are key to evidence-based practices (EBPs), how one becomes an evidence-based practitioner, and how expertise in EBP manifests in practice, remains unclear. OBJECTIVE: To describe how expert evidence-based practitioners conceptualize and enact their expertise in stroke rehabilitation. DESIGN: Qualitative interpretive descriptive study using in-depth semistructured interviews with eight occupational therapists identified as expert evidence-based practitioners in a previous study. Transcripts were analyzed using an inductive thematic content analysis, and emergent themes were identified. SETTINGS: Rehabilitation settings across Canada. RESULTS: Six overarching themes emerged: (1) relying on personal attributes to engage in practice improvement, (2) acting on factors that motivate and trigger EBP, (3) achieving better outcomes because of engagement in EBP, (4) using an adaptive decision-making process, (5) participating in professional activities that contribute to practice improvement, and (6) working in a practice area with a large body of evidence. CONCLUSIONS AND RELEVANCE: Expertise in stroke rehabilitation EBP appears to be a function of several personal attributes and habits of mind in addition to being influenced by a commitment to client-centered practice. Expertise requires a combination of deliberate effort and motivation to improve client outcomes, always in a context conducive to reflection, adaptation, and openness to innovation. Experts who model these traits and articulate the processes used to develop their expertise can be viewed as promising educational and continuing professional development resources. What This Article Adds: Expert evidence-based occupational therapists develop their expertise in this domain through commitment to client-centered practice, efforts toward honing this aspect of practice, and a willingness to innovate and adapt to challenging situations.

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)0.056
metaresearch head score (Gemma)0.109
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.109
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0170.032
Scholarly communication0.0210.018
Open science0.0030.019
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0030.001

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 head0.428
GPT teacher head0.550
Teacher spread0.122 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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