| Role | Learning Experience Designer / Evaluation Designer |
|---|---|
| Scope | Designed a measurement framework to evaluate whether the Shift Reset micro-practice protocol improves cognitive readiness and decision performance in high-pressure clinical environments. |
| Audience | Healthcare organizations implementing brief regulation or resilience interventions within clinical workflows. |
| Tools & Standards | Pre/Post self-report scales; scenario-based performance assessment; behavioral scoring rubric; LMS or xAPI data capture; basic statistical analysis. |
| Deliverables | Training impact measurement framework; pre/post check-in instrument; scenario performance rubric; data collection protocol; evaluation report template. |
Assess whether the Shift Reset micro-practice protocol improves clinicians’ cognitive readiness and emotional regulation during high-pressure clinical work, and whether these improvements translate into stronger decision performance in scenario-based tasks.
The evaluation focuses on immediate changes in regulation and task readiness, while avoiding measurement methods that could disrupt the calming effect of the protocol.
Because the purpose of the protocol is to down-regulate stress and restore attentional stability, the immediate post-session evaluation avoids quizzes or performance tests that could reintroduce cognitive pressure. Instead, the measurement focuses on perceived readiness to return to work and the practicality of completing the protocol within a clinical workflow.
| Metric | Method | Timing |
|---|---|---|
| Stress level | Brief self-rating (0–10) | Before VR / After VR |
| Focus | Brief self-rating (0–10) | Before VR / After VR |
| Mental Readiness | Brief self-rating (0–10) | Before VR / After VR |
| Ability to Return to Task | Brief Agreement Scale | After VR |
| Workflow Fit | Brief Agreement Scale | After VR |
| Completion Rate | Session Analytics | During Session |
This design captures immediate emotional and attentional change while also linking the intervention to downstream performance indicators.
All responses are recorded digitally through the training platform or associated data collection tool. Session completion and participation data are also captured to assess engagement and determine whether the protocol fits realistically within clinical workflows.
If organizations wish to explore whether improved regulation translates into performance outcomes, those measures can be collected later in a separate simulation or operational context, rather than immediately after the intervention.