Objectives: Trust represents a key quality of strong clinician-patient relationships. Many have attempted to assess patient-reported trust. However, most trust measures suffer from ceiling effects, with no variability, making it not possible to examine predictors of trust and distrust. Rather than rely on patient reports, we created a codebook for instances of trust and distrust from actual patient-clinician encounters.
Methods: Three coders conducted a qualitative analysis of audio recordings among patient-cardiologist outpatient encounters.
Results: We identified trust and distrust based on vocal and verbal cues in the interactions. We found consistent patterns that indicated patient trust and distrust.
Conclusion: Overall, this work empirically validates a new more accurate measurement of trust for patient-doctor interactions.
Innovation: We are the first to use audio recordings to identify verbal markers of trust and distrust in patient-clinician interactions. From this work, others can code trust and distrust in recorded encounters rather than rely on self-report measures.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339236 | PMC |
| http://dx.doi.org/10.1016/j.pecinn.2023.100187 | DOI Listing |
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