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Enregistrement W6959765628 · doi:10.11575/prism/43872

Co-worker Assessment and Physician Multisource Feedback

2013· other· en· W6959765628 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity of Calgary · 2013
Typeother
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueGenetic and Environmental Crop Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeneralizability theoryFormative assessmentSpecialtyData collectionReliability (semiconductor)Variance (accounting)UnivariateConsistency (knowledge bases)Sample (material)

Résumé

récupéré en direct d'OpenAlex

Background: The College of Physicians and Surgeons of Alberta’s Physician Achievement Review program (PAR) uses questionnaire data from several sources, including co-workers, to provide formative feedback to physicians to promote quality improvement and continuing professional development within the profession. The PAR co-worker assessment questionnaires (CAQ) used in PAR were developed over more than a decade and not been psychometrically evaluated since then. The CAQs have not been reviewed either on their own or across the nine medical specialties which comprise PAR. Aim: The purpose of this study was to more fully understand the CAQs’ psychometric profile including an exploration of the interprofessional constructs being measured and any changes in performance scores over time. Method: A purposive sample of co-worker data from 1341 physicians across nine medical specialties in Alberta was evaluated. Secured PAR databases containing CAQ data (n = 9674) were accessed and analyzed using univariate and multivariate parametric techniques to: (a) evaluate the psychometric profile of the CAQ within and across specialty grouping; (b) to determine if physician characteristics and co-worker familiarity were associated with PAR performance scores; and (c) to evaluate if a difference existed between Time1 PAR feedback and Time2 PAR performance. Results: Internal consistency of all CAQs remains extremely high (i.e., > 0.90) suggesting a potential unidimensionality. Generalizability coefficients were not as robust as were originally reported. Variance components across the collection of CAQs indicated that opportunity for CAQ revision to improve its reliability is better directed at the processes associated with data collection (e.g., assessor selection practices) rather than revising questionnaire items. Principal components analyses were conducted as a variable reduction procedure. Each CAQ demonstrated a number of redundant questionnaire items (range: 5 to 11), and while the components structure remained similar to the factor structure published in the original research, component labeling was updated to reflect the CanMEDS competencies supporting interprofessional practice (i.e., communicator and collaborator). In the case of family physicians and pediatricians, a new component emerged reflecting the consolidation of the communicator and professional roles into one previously unidentified component labelled: good doctor. Several independent t-tests, ANOVA, and linear regression analyses were conducted providing evidence that certain physician characteristics together with co-worker familiarity were significant predictors of CAQ performance scores within speciality groupings. Different medical specialities were influenced differently by socio-demographic characteristics relative to CAQ scores; however, across all medical specialties co-worker familiarity demonstrated a significant positive linear relationship with CAQ scoring. Finally, significant increases and decreases in CAQ scores from Time1 to Time2 were found depending upon specialty grouping. Conclusion: The CAQ provides reliable data to physicians relative to interprofessional collaboration. Opportunity exists to improve the reliability of these tools by addressing unique variance components generated by the unbalanced nature of multisource feedback collection processes. Given the manner in which the tools were constructed, future revision efforts ought to include focus groups of specialty-specific co-workers seeking to illuminate how different clinical contexts influence what interprofessionality uniquely means within that specialty grouping.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,344
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,181
Écart entre enseignants0,173 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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