MétaCan
Menu
Back to cohort
Record W2804974192 · doi:10.22230/jripe.2018v8n1a264

Health Professions Students' Teamwork Before and After an Interprofessional Education Co-Curricular Experience

2018· article· en· W2804974192 on OpenAlexvenueno aff
Shelley C. Mishoe, Kimberly Adams Tufts, Leigh A. Diggs, James D. Blando, Denise M Claiborne, Johanna M. Hoch, Martha Walker

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsTeamworkInterprofessional educationHealth professionsMedical educationExperiential learningPsychologySocializationScale (ratio)LicensureHealth careMedicineNursingPedagogySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Background: Effective interprofessional collaboration may positively impact clinical outcomes, patient satisfaction, and cost effectiveness. However, educational silos and discipline-specific socialization have reinforced each health profession’s independent values, attitudes, and problem-solving approaches.Methods and Findings: Students’ (N = 376) attitudes about teamwork were measured with the Interprofessional Attitudes Scale, Teamwork, Roles, and Responsibilities subscale using a pretest-posttest design. Experiential learning strategies and a case study approach were used to introduce students to the roles and responsibilities of the students’ disciplines. There was a positive mean difference in pretest-posttest measures (p < .001) with a moderate effect size (r = .27).Conclusions: Providing opportunities for pre-licensure health sciences students to understand the roles and responsibilities of other disciplines through IPE co-curricular learning can enhance positive attitudes toward teamwork.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.608
Teacher spread0.553 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Research in Interprofessional Practice and EducationSame topicInterprofessional Education and CollaborationFrench-language works237,207