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Record W4409691988 · doi:10.5430/jnep.v15n5p56

Paid co-op models for health professional programs: A scoping review

2025· review· en· W4409691988 on OpenAlexvenueaboutno aff
Gabrielle Charron, Michelle Crick, Judy King, Valentina Ly, Kim Lortie, Sarah Leblond, Chantal Backman

Bibliographic record

VenueJournal of Nursing Education and Practice · 2025
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsHealth professionalsBusinessNursingMedicinePolitical scienceHealth care

Abstract

fetched live from OpenAlex

Background: Clinical learning is key for health professional students. As we face, worldwide, an aging healthcare workforce and widespread staff shortages, the urgency to adopt innovative and scalable models of clinical education has never been greater. These new approaches are essential not only to address the current capacity challenges but also to ensure the sustainability and quality of care, particularly as healthcare needs become more complex and patient populations continue to grow. Co-operative education (co-op) programs provide students with the opportunity to gain practical experiences in a clinical setting as part of their formal education while receiving some financial remuneration. Yet, little is known about the most effective ways to design, implement and evaluate these programs to best benefit patients, students, educational, and healthcare organizations. Our goal was to explore the available literature on paid co-op education models for students in health professional programs.Methods: We conducted a scoping review following the six stages of the Arskey and O’Malley’s scoping review framework and the PRISMA-ScR reporting format. This included defining the research question, developing the search strategy, conducting a two-step screening process, and performing data extraction and analysis of the included studies.Results: A total of 30 articles were included. Studies were from the United States (n = 14), the United Kingdom (n = 8), Canada (n = 4), Ireland (n = 2), New Zealand (n = 1) and Iran (n = 1). Most studies aimed to describe or evaluate the paid co-op programs (n = 12), or aimed to explore the experience of students, preceptors or faculty members who participated in a co-op program (n = 10). The studies included a wide range of healthcare professionals, including nursing (n = 21), pharmacy (n = 3), midwifery (n = 1), medicine (n = 1), occupational therapy (n = 1), audiology (n = 1), social work (n = 1), and a combination of occupational therapy, physiotherapy, and speech-language pathology (n = 1).Conclusions: The results of this scoping review contributed to the existing literature on paid co-op education programs for students in health professional programs. We explored the current state of these programs, the benefits and the challenges of these programs, and the potential directions for future planning, implementation, and research in this area. Health care leaders, program directors, clinical educators, and curriculum developers will be able to use these findings to inform future co-op programs that fosters mutual benefits for students, educational, and healthcare organizations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.116
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.030
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.116
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0260.030
Science and technology studies0.0020.002
Scholarly communication0.0070.006
Open science0.0030.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.879
GPT teacher head0.824
Teacher spread0.055 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2025
Admission routes2
Has abstractyes

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