Multi-Jurisdictional Evaluation of Sentinel City Virtual Simulation for Community Health Nursing Clinical Education
Bibliographic record
Abstract
Although positive learning outcomes have been documented for nursing students who participate in virtual simulation for community health nursing clinical education (Chircop & Cobbett, 2020), it is unknown whether learning outcomes of students using the same virtual simulation program are comparable across jurisdictions. Nine schools of nursing across Canada (Nova Scotia, Ontario, British Columbia) implemented and evaluated Sentinel City a virtual simulation program to complement the traditional community clinical, or as an alternative learning experience. A descriptive survey was used to carry out an evaluation of the use of Sentinel City and student learning outcomes. Quantitative data provided demographic statistics to describe the sample, compare student learning outcomes and perceptions of their learning experience and the qualitative data from open-ended questions provided detailed responses on the use of Sentinel City and its future recommendation. Data were analyzed using ANOVA (Welch statistic) to identify any significant differences among students from each jurisdiction in relation to their perception of the use of Sentinel City in meeting their course learning outcomes. Qualitative data from open-ended responses were analyzed using the six-step process outlined by Braun and Clarke (2006). The use of Sentinel City for community clinical learning in various Canadian jurisdictions positively contributed to achieving desired student learning outcomes. There are, however, significant differences among jurisdictions. Most of the students “agreed” that Sentinel City helped them achieve course learning outcomes. In all jurisdictions, most of the students indicated that they were “confident” and “very confident” in their knowledge about the community health nursing process, understanding of a population/community health assessment, understanding how to plan a population health intervention, and in their ability to integrate the five principles of primary health care into practice. Regarding their ability to apply a population health perspective (upstream thinking), most of the students were “confident” and “very confident”. Almost all students (93.62%) were confident and “very confident” in their ability to recognize health inequities indicating the highest level of confidence (Mean 4.38, SD 0.71). As educators, we found several advantages with the use of SC, including the ability to create controlled and standardized clinical learning experiences which contributes to fairness and quality of community clinical education. We recommend a robust orientation and professional development program for clinical instructors in community health nursing that is consistent with the new International Nursing Association for Clinical Simulation and Learning (2021) standards. The required expertise in community health nursing together with solid foundational knowledge of a simulation program for community health nursing and facilitation skills competence during pre- and de-briefing sessions are necessary for student success. One of our recommendations has been achieved with the recent release of Sentinel City Canada (https://www.sentinelu.com/events/sentinel-city-canada/). Overall, this cross-jurisdictional study revealed a flexibility with which Sentinel City® can be used or adapted as a teaching tool at different programs across Canadian jurisdictions and still contribute to the achievement of course learning outcomes.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".