Creating interprofessional learning capacity in children's centres – description and evaluation of a pilot project
Bibliographic record
Abstract
Abstract Nationally, the promotion of interprofessional learning (IPL) at all levels is a key UK Government strategy aimed at improving communication, collaborative working and enhancing quality care for all service users. The development of interagency working through the provision of services for pre‐school children and their families within children's centres provides an ideal environment to promote interprofessional learning for pre‐registration health and social care students. A partnership project was established to develop new interprofessional practice learning placements for students completing social work and child branch nursing courses within two health and social care communities in a midland county and city in England. Following information on the aims and objectives of the project, children's centres opted in to participate. The Common Learning Programme North East Model for IPL was adopted as a template for managing the variability in numbers and timings for student placements. Workshops were provided to prepare IPL facilitators; students attended workshops and completed an IPL workbook as part of their learning experience. A total of 14 children's centres participated over the 2 years of the project. An action research framework was used to underpin the collection of evaluation data through questionnaires, telephone interviews and focus groups. All stakeholders were involved in workshop events to action plan for improvements following feedback from evaluations. All participating centres remained positive and encouraged other centres to participate. Problem areas highlighted and dealt with included the logistics involved in timing student placements; development and use of the IPL workbook; and ensuring enough IPL facilitators. A key factor contributing to the success of Creating Interprofessional Learning Capacity in Children's Centres has been effective partnership working with stakeholders from the higher education institutions, local authorities and the National Health Service. The benefits of IPL in providing students with an opportunity to develop into effective collaborative practitioners was recognised by those involved and resulted in a high level of commitment over the 2 years. Challenges remain and sustainability will always be an issue but gaining the ongoing commitment of all stakeholders within the children's centres themselves has been a key factor in the success of the project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".