Objective: A challenging but main task for clinicians is to identify patients' concerns related to their medical conditions. The study aim was to validate a new coding scheme for identifying patients' cues and concerns.
Methods: 12 videotaped consultations between nurses and pain patients were coded according to the Verona Coding Scheme for Emotional Sequences (VR-CoDES). During a metainterview each patient watched his/her own video interview with the researcher to confirm or disconfirm the identified cues and concerns. A directive or an open format was applied. Quantitative and qualitative data analyses were performed.
Results: Patients' confirmation in relation to the coding gave a sensitivity of 0.95 and specificity of 0.99 in the directive format and a sensitivity of 0.99 and specificity of 0.70 applying the open format. Through a qualitative analysis 83% of researcher-identified cues and concerns were validated. 17% were not confirmed or uncertain.
Conclusion: The VR-CoDES seems to capture what are experienced as real concerns to patients, and proves to be a coding scheme with a high degree of ecological validity.
Practice implications: The VR-CoDES provides a valid framework for detecting patients' cues and concerns, and should be explored as a training tool to develop clinicians' empathic accuracy.
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