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Record W2023019433 · doi:10.1177/0008417415577422

Enhancing student occupational therapists’ client-centred counselling skills

2015· article· en· W2023019433 on OpenAlexfundvenueno aff
Pamela Wener, Carolyn O. Bergen, Lisa G. Diamond-Burchuk, Cynthia Yamamoto, Alana E. Hosegood, James D. Staley

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsSession (web analytics)Occupational therapyRating scaleCornerstoneScale (ratio)PsychologyMedical educationMedicineApplied psychologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Client-centred practice is the cornerstone of the occupational therapy profession. However, there has been little focus on how to teach students to be client-centred practitioners while engaged in counselling. PURPOSE: The purpose of this study was to examine the impact of the use of a client-completed rating scale on student occupational therapists' client-centred counselling skills. METHOD: A time-series design was used to measure the changes in students' counselling skills over time. Demographic information was collected prior to time one. An online questionnaire was administered after study completion to explore students' experiences of using the Session Rating Scale. FINDINGS: The impact of using the Session Rating Scale as a measure of students' client-centred counselling skills performance significantly improved over time. Most students valued using the rating scale and would recommend its use for future students. IMPLICATIONS: The process of supporting students to learn how to engage clients in providing timely feedback and using this feedback to design treatment sets the stage for integration and application of client-centred practice.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.356
GPT teacher head0.517
Teacher spread0.161 · 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 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

Citations2
Published2015
Admission routes2
Has abstractyes

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