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Record W4291884886 · doi:10.3390/healthcare10081539

Exploring the Efficacy of a Virtual First Year Interprofessional Education Event

2022· article· en· W4291884886 on OpenAlexaff
Isdore Chola Shamputa, Boon Kek, Loretta Waycott, Tammie Fournier, Shaun McCarville, John Doucet, Derek Gaudet, Marc Nicholson

Bibliographic record

VenueHealthcare · 2022
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsNew Brunswick Community CollegeSaint John Regional HospitalUniversity of New Brunswick
Fundersnot available
KeywordsInterprofessional educationMedical educationCoronavirus disease 2019 (COVID-19)PsychologyHealth careMedicineNursing

Abstract

fetched live from OpenAlex

Interprofessional education (IPE) activities are utilized in health education programs to develop interprofessional collaboration (IPC) competencies. All first-year healthcare students at three postsecondary learning institutions attend a mandatory introductory IPE event annually. During the 2020/2021 academic year, the event was moved from a face-to-face activity to a virtual format due to the COVID-19 pandemic restrictions. This study examined whether the virtual IPE activity was effective in supporting the development of interprofessional competencies for first-year healthcare students. Two hundred and six students attended a synchronous didactic presentation on IPE competencies and discussed a simulated case in interprofessional groups of eight students and two faculty facilitators. The Interprofessional Collaborative Competency Attainment Survey (ICCAS) was used to measure the students’ opinions on interprofessional competencies. Paired t-tests were used to compare the pre- and post-scores. One hundred and nine (52.9% response rate) students completed the survey. Surveys from 99 students with matched pre- and post-scores were included in the study. The ICCAS competencies showed improvements (p < 0.05) in all of the students’ self-reported IPE competencies following the activity compared to before the training. Our findings indicate that the virtual IPE activity is effective in facilitating the development of IPC for first-year healthcare students.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.102
GPT teacher head0.456
Teacher spread0.354 · 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 teacher head, not a consensus.

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

Citations10
Published2022
Admission routes1
Has abstractyes

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