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Record W1182579564 · doi:10.22230/jripe.2015v5n1a189

Community service learning: an effective vehicle for interprofessional education

2015· article· en· W1182579564 on OpenAlexvenueno aff
Taline Dadian Infante, Lyda Arevalo-Flechas, Lark A. Ford, Norma S Partida, Norma S. Ketchum, Brad H. Pollock, Anthony J. Infante

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsInterprofessional educationMultidisciplinary approachFocus groupMedical educationTeamworkNursingService-learningMedicineHealth carePsychologyPopulationPedagogySociology

Abstract

fetched live from OpenAlex

Background Health professions students have limited exposure to each other during education and training, yet there are many expectations for interaction in the workplace as part of functioning health care teams. We reasoned that providing students an opportunity to work together in a service learning project under faculty supervision would enhance student knowledge and appreciation of each other’s disciplines and give them a better understanding of working together. Methods and Findings Teams of students from four disciplines (medicine, nursing, dentistry, dental hygiene) worked as volunteers with a unique population of transitional homeless families to develop individualized health and wellness plans. Pre- and post-participation surveys were used to measure changes in student perceptions of working in multi-disciplinary teams, and focus groups were used to identify strengths and weaknesses of the project and future directions. Conclusions Results showed positive predispositions to working with each other which were further enhanced by collaborative, interprofessional experience. Students’ confidence in working together in multidisciplinary teams and understanding of the training and expertise of other professions increased after participation and changes were statistically significant. Interprofessional education and community service-based learning may be a powerful combination for demonstrating the value of clinical teamwork to health professions 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)0.017
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.173
GPT teacher head0.620
Teacher spread0.446 · 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 designQualitative
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

Citations9
Published2015
Admission routes1
Has abstractyes

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