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Enregistrement W3211939572 · doi:10.2196/31634

Comparing Web-Based and In-Person Educational Workshops for Canadian Occupational Therapists and Understanding Their Learning Experiences: Mixed Methods Study

2021· article· en· W3211939572 sur OpenAlexaffvenueabout
Sung-Ha Kim, Ilana Bayer, Rebecca Gewurtz, Nadine Larivière, Lori Letts

Notice bibliographique

RevueJMIR Medical Education · 2021
Typearticle
Langueen
DomaineHealth Professions
ThématiqueOccupational Therapy Practice and Research
Établissements canadiensUniversité de SherbrookeMcMaster University
Organismes subventionnairesnon disponible
Mots-clésOccupational therapyPsychological interventionPsychologyPromotion (chess)Qualitative propertyMedical educationMeaning (existential)Qualitative researchMedicineApplied psychologyNursingComputer sciencePhysical therapyPsychotherapist

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: The Do-Live-Well (DLW) framework is an occupation-focused health promotion approach. Occupational therapists (OTs) have been interested in training opportunities regarding this framework. Traditionally, in-person continuing educational interventions are the main way that OTs obtain knowledge, but web-based learning has become popular among health care professionals. However, its effectiveness and learners' experience in web-based learning have not been well-studied in occupational therapy education. OBJECTIVE: This study aims to evaluate the effectiveness of the web-based and in-person educational DLW workshops for Canadian OTs and to understand their experiences in both workshop types. METHODS: An explanatory sequential mixed methods study design was used, where quantitative data were collected first, then qualitative data were used to explain the quantitative findings. A quasi-experimental design and interpretative description methodology were used in the quantitative and qualitative phases, respectively. RESULTS: Quantitative results were as follows: a total of 43 OTs completed pre-, post-, and follow-up evaluations (in-person group: 21/43, 49%; web-based group: 22/43, 51%). Practice settings of the participants varied, including geriatric, hospital, long-term, mental health, pediatric, and primary settings. The primary outcome was as follows: there were no statistically significant differences in knowledge changes at the 3 time points (P=.57 to P=.99) between the groups. In the web-based group, the knowledge scores at follow-up were lower compared with the posttest results, meaning that knowledge gain was reduced over time (P=.001). The secondary outcomes were as follows: there were statistically significant differences between the groups in factors influencing DLW adoption at posttest (P=.001) and in satisfaction with the workshop (P<.001) at posttest in favor of the in-person group. Qualitative results were as follows: a total of 18 OTs (9/18, 50% from each group) participated in an individual interview. Five themes were identified regarding learners' workshop experiences: relevance to their practices and interests may improve learning, a familiar learning environment may facilitate learning, synchronous in-person interaction is valuable in the learning process, ease of access to learning should be considered, and flexibility in web-based learning can be both beneficial and challenging. CONCLUSIONS: The quantitative results of this study reported no difference in knowledge acquisition between the in-person and web-based groups, indicating that web-based education is as effective as in-person workshops. However, participants' satisfaction with the workshop was statistically significantly higher for the in-person workshop. The qualitative findings described the participants' perceived benefits and challenges of each educational format. The participants in both the web-based and in-person workshop groups valued in-person interactions in learning, but the participants in the web-based workshop group expressed web-based learning lacked in-person-like interactions. Thus, adding synchronous in-person interactions to web-based learning may improve learners' educational experiences in web-based occupational therapy and continuing education.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,026
score de la tête « metaresearch » (Gemma)0,034
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,572
Score d'incertitude au seuil0,851

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0260,034
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0040,007
Études des sciences et des technologies0,0060,002
Communication savante0,0030,001
Science ouverte0,0030,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,227
Tête enseignante GPT0,558
Écart entre enseignants0,331 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

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

En bref

Citations16
Publié2021
Routes d'admission3
Résumé présentoui

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