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Record W1563241159 · doi:10.22230/jripe.2014v4n1a161

Introducing Interprofessional Education and Care Concepts in a Geriatric Multilevel Centre: Development and Introduction of a Toolkit for Staff and Students

2014· article· en· W1563241159 on OpenAlexfundvenueno aff
Faith Boutcher, David Conn, Margaret Mroziewicz, Lisa M Guttman Sokoloff

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsInterprofessional educationAttendanceTeamworkFocus groupHealth careMedical educationPsychologyMedicineNursingSociology

Abstract

fetched live from OpenAlex

Background: Although interprofessional education (IPE) is not new, there has been limited research in IPE focused on the care of older adults. The objective of this study was to develop and implement an interprofessional education and care (IPE/C) toolkit, to help staff and students understand and apply the concepts of IPE/C.Methods and Findings: Focus groups identified staff and students’ understanding of IPE/C and informed development of an IPE/C toolkit comprised of IPE/C tools and resources. Five clinical teams (N = 51) attended workshops that introduced the toolkit and educated teams about IPE/C. Focus group participants had heard of but had limited exposure to IPE/C. Responses to the Attitudes Toward Health Care Teams (ATHT) questionnaire indicated a positive trend on all questions; 2 questions in subscale 1 were statistically significant (p = .01 & p = .005), indicating a positive attitude toward teams and teamwork. Several limitations were identified, including inconsistent attendance at workshops, scheduling challenges, and limited physician participation.Conclusions: This pilot project provided baseline data on staff and students’ understanding of and attitudes toward IPE/C in a multilevel geriatric centre and demonstrated that an IPE/C toolkit delivered via team workshops can enhance healthcare team attitudes. Next steps include expanding the rollout to other teams and introducing the toolkit to all staff and 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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.541
Teacher spread0.497 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2014
Admission routes2
Has abstractyes

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