Analyzing Evidence on Interventions to Strengthen the Clinical Support for Midwifery Students in Clinical Placements: Protocol for a Systematic Scoping Review
Bibliographic record
Abstract
BACKGROUND: The benefits of clinical support are evident in various mentorship, preceptorship, or clinical supervision models. Poor collaboration between lecturers and clinical staff, lack of confidence about student support, large student intakes coupled with core demands create negative attitudes toward student supervision, and this poses a huge challenge to midwifery students who are expected to become competent in the process. OBJECTIVE: This study aims to identify and analyze interventions, strategies, and/or mechanisms in order to strengthen the clinical support for midwifery students in clinical practice areas from a global perspective. METHODS: This review will follow the Arksey and O'Malley framework (2005). The search strategy will include primary studies searched for in electronic databases such as EBSCOhost (CINAHL, MEDLINE, and Health Source: Nursing/Academic edition), PubMed, Google, and Google Scholar. Keywords such as "midwifery students," "midwifery education," and "clinical support" will be used to search for related articles. The search will include articles from the cited by search, as well as citations from the reference list of included articles. All title-screened articles will be exported to an EndNote library, and duplicate studies will be removed. Two independent reviewers will concurrently carry out the abstract and full-text article screening according to the eligibility criteria. Extracted data will highlight the aims, geographical setting, and level of training; intervention outcomes; and the most relevant and most significant findings. This review will also include a mixed methods quality appraisal check. A narrative summary of data extracted will be analyzed using content analysis. RESULTS: Interventions to strengthen the clinical support for midwifery students in practice will be extracted from this review, and data will be analyzed and extracted to develop a comprehensive guide or framework for clinical mentorship. As of August 2021, the electronic search, the data extraction, and the analysis have been completed. The results paper is expected to be published within the next 6 months. CONCLUSIONS: It is expected that this review will contribute to midwifery education by identifying quality evidence on clinical support interventions available to midwifery students globally, as well as best practice methods, procedures, or interventions that can be used to develop a midwifery mentorship training program. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29707.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.139 | 0.132 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.022 | 0.027 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.055 | 0.013 |
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 source (direct Gemma or distilled Codex), 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".