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Record W2064894183 · doi:10.3109/09638230903469244

Examining the effects of interprofessional education on mental health providers: Findings from an updated systematic review

2010· review· en· W2064894183 on OpenAlexaff
Enette Pauzé, Scott Reeves

Bibliographic record

VenueJournal of Mental Health · 2010
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity Health NetworkSt. Michael's HospitalUniversity of TorontoPublic Health Ontario
Fundersnot available
KeywordsCINAHLPsycINFOMental healthMEDLINEPopularityInterprofessional educationSystematic reviewPsychologyMedicineMedical educationHealth careNursingPsychiatryPsychological interventionSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Interprofessional education (IPE)'s popularity as an effective strategy to enhance the ability of health professionals to work in interprofessional teams has grown substantially over the past decade. AIMS: Building upon the work of Reeves ( 2001 ), this paper provides an updated systematic review of the effects of IPE on mental health providers delivering adult mental health care from 1967 to 1998. METHOD: A systematic review was undertaken to update an earlier review in this field. Three databases (Medline, CINAHL, and PsycINFO) were searched from January 1999 to December 2007, and 16 articles were included in the review. RESULTS: A triangulation approach was used to rate the quality of the evidence reported by the studies, and yielded the following article ratings: five good, five acceptable, four poor, and two unacceptable. Overall, the use of theory to inform IPE was limited. Methodologically, before-and-after study designs were most common, as were multiple data collection techniques. Few studies attributed negative/unintended consequences to IPE, or reported clear limitations to their approaches or findings. CONCLUSION: The review suggests an improvement in the methodological rigor in research designs, with a preference for mixed methods and outcomes measured at more complex levels.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.051
GPT teacher head0.505
Teacher spread0.455 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations34
Published2010
Admission routes1
Has abstractyes

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