Describing Learners’ Clinical Judgment Trajectory After Observing Expert Modeling Videos: A Mixed Methods Study

Published:September 02, 2022DOI:


      • Assigning expert-modeled simulation observations increased clinical judgment.
      • Asynchronous simulation observations helped low, medium, and high performers.
      • Observation reflections revealed differences in knowledge, thinking, and approach.
      • Time spent responding to prompts favorably influenced clinical judgment scores.



      Novice nurses have clinical judgment (CJ) deficiencies leading to errors.


      We used mixed methods to describe learners’ CJ trajectory after observing eight expert-modeled videos (EM) asynchronously over a semester. Learners responded to CJ prompts after observing EMs and were scored using Lasater Clinical Judgment Rubric (LCJR). Learners were assigned to low, medium, or high-performance groups based on cumulative LCJR rankings. Next, we analyzed whether background variables related to LCJR scores. Finally, we used Framework Method to describe characteristics of written responses for select low, medium, and high performers.


      Sixty-three junior-level nurses participated. Observing eight EMs increased CJ significantly over time, F (5.514, 341.858) = 24.18, p < .001, ηp2 = 0.28. Furthermore, all three performance groups significantly increased CJ over time. Longer time spent responding to prompts predicted whether learners were high versus low performers. Qualitative analysis revealed low, medium, and high performers nursing knowledge, thinking, and approach differs.


      Assigning EM observations and CJ prompts increased CJ development. Assigning EM observations and reflections allows educators to track CJ and overcome variable clinical experiences.


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