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Enregistrement W4394158670 · doi:10.6084/m9.figshare.16531175

Online learning versus workshops: a rank minimized trial comparing the effect of two knowledge translation strategies designed to alter knowledge, readiness to change, and self-efficacy with respect to rehabilitation outcome measures

2021· dataset· en· W4394158670 sur OpenAlexaffabout
Mike Szekeres, Joy C. MacDermid

Notice bibliographique

RevueFigshare · 2021
Typedataset
Langueen
DomaineSocial Sciences
ThématiqueE-Learning and COVID-19
Établissements canadiensMcMaster UniversitySt Joseph's Health CareWestern University
Organismes subventionnairesnon disponible
Mots-clésOutcome (game theory)Knowledge translationRank (graph theory)RehabilitationPsychologyTranslation (biology)Computer sciencePhysical therapyPhysical medicine and rehabilitationKnowledge managementMedicineMathematics

Résumé

récupéré en direct d'OpenAlex

Traditional face-to-face learning is often replaced by virtual learning because it can be more feasible and cost-effective, and more recently due to the need for social distancing. The objective was to evaluate the effectiveness of two innovative knowledge translation (KT) interventions; in-person stakeholder-hosted, interactive, problem-based seminars (SHIPS) versus online problem-based tutorials (e-PBL) in changing knowledge, readiness to change, and self-efficacy with respect to the use of rehabilitation outcome measures. Physical and occupational therapists (<i>n</i> = 124) were recruited from four sites across Canada to participate in either an e-PBL or SHIPS. Evaluations of KT impact measured knowledge, self-efficacy to implement outcome measures in practice, and readiness to change. There were 112 participants who completed the study. Following the intervention, the mean knowledge scores for both groups improved, but there was greater improvement in participants who completed SHIPS. For self-efficacy and readiness to change, there was no significant difference between groups six months following the interventions. E-PBL was as good as a SHIPS for improving and retaining self-efficacy and readiness to change. Knowledge improved more with workshops than online delivery, while improvements in self-efficacy and readiness to change improved similarly regardless of delivery.Implications for RehabilitationThis study compared the relative efficacy of internet and workshop-based education, focusing specifically on the use of outcome measures in physical and occupational therapy practice.Improvements in the self-efficacy of rehabilitation professionals with respect to outcome measure use had lasting effects regardless of KT intervention type, as it was retained six months following the intervention.Results from this study show that online interventions may be as effective as face-to-face workshops for improving readiness to change and self-efficacy for using outcome measures in practice by rehabilitation professionals.This is valuable information given the recent global pandemic, the need for social distancing, and the potential for learning interventions to focus within the online environment in the future. This study compared the relative efficacy of internet and workshop-based education, focusing specifically on the use of outcome measures in physical and occupational therapy practice. Improvements in the self-efficacy of rehabilitation professionals with respect to outcome measure use had lasting effects regardless of KT intervention type, as it was retained six months following the intervention. Results from this study show that online interventions may be as effective as face-to-face workshops for improving readiness to change and self-efficacy for using outcome measures in practice by rehabilitation professionals. This is valuable information given the recent global pandemic, the need for social distancing, and the potential for learning interventions to focus within the online environment in the future.

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)0,002
score de la tête « metaresearch » (Gemma)0,018
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,087
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,018
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,183
Tête enseignante GPT0,423
Écart entre enseignants0,241 · 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
GenreJeu de données

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
Publié2021
Routes d'admission2
Résumé présentoui

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