Do Therapeutic Recreation Mental Health Clinical Placements Provide Educational Experiences to Pre‐Registration Student Nurses?: A Mixed Methods Systematic Review
Bibliographic record
Abstract
Clinical placements are a critical component in any pre-registration student nurse's skill development and play an influential role in career specialisation upon registration. However, students are reporting to feel anxious and under prepared attending clinical placements, especially within mental health settings. Such a concern was highlighted in the Australian Government's Productivity Commission into Mental Health (2020). With recommendations for clinical placements to occur in therapeutic recreation environments, allowing increased interactions between students and individuals with a lived experience. Hence, this mixed methods systematic review aims to explore the experiences of pre-registration student nurses completing their mental health clinical placement within a therapeutic recreation environment. Six databases were searched for the review; CINHAL, Medline, PsycINFO, Web of Science, Scopus and the ProQuest Dissertation and Theses database, yielding 10 214 articles. Data were imported to COVIDENCE for management and screening processes. Risk of bias was undertaken by two authors utilising the Joanna Briggs Institute's Critical Appraisal Checklist for qualitative and quasi-experimental studies and McGill's Mixed Methods Appraisal Tool 2018 Version for mixed methods studies. Data were extracted manually for the 13 included articles which met the review inclusion criteria. Following a thematic analysis of the extracted data, three themes emerged: an optimal learning environment, impact on stigmatising beliefs and influence on future career. Findings identified that therapeutic recreation environments pose numerous education benefits for pre-registration student nurses. It is apparent through an immersive mental health clinical placement; student nurses are able to increase their mental health understanding through the lens of those with lived experiences. Such environments challenge stigmatising beliefs held by students prior to clinical placements and can lead to an increased desire to pursue a career within the mental health speciality. This review offers an insight into the many benefits for pre-registration student nurses who complete their mental health clinical placements in therapeutic recreation environments, including reduced stigmatising beliefs, increased mental health knowledge and improved clinical confidence. Trial Registration: PROSPERO: CRD42023476280.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".