Objective: To determine if 1) patients have distinct affective reaction patterns to medication information, and 2) whether there is an association between affective reaction patterns and willingness to take medication.
Methods: We measured affect in real time as subjects listened to a description of benefits and side effects for a hypothetical new medication. Subjects moved a dial on a handheld response system to indicate how they were feeling from "Very Good" to "Very Bad". Patterns of reactions were identified using a cluster-analytic statistical approach for multiple time series. Subjects subsequently rated their willingness to take the medication on a 7-point Likert scale. Associations between subjects' willingness ratings and affect patterns were analyzed. Additional analyses were performed to explore the role of race/ethnicity regarding these associations.
Results: Clusters of affective reactions emerged that could be classified into 4 patterns: "Moderate" positive reactions to benefits and negative reactions to side effects ( n = 186), "Pronounced" positive reactions to benefits and negative reactions to side effects ( n = 110), feeling consistently "Good" ( n = 58), and feeling consistently close to "Neutral" ( n = 33). Mean (standard error) willingness to take the medication was greater among subjects feeling consistently Good 4.72 (0.20) compared with those in the Moderate 3.76 (0.11), Pronounced 3.68 (0.14), and Neutral 3.62 (0.26) groups. Black subjects with a Pronounced pattern were less willing to take the medication compared with both Hispanic ( P = 0.0270) and White subjects ( P = 0.0001) with a Pronounced pattern.
Conclusion: Patients' affective reactions to information were clustered into specific patterns. Reactions varied by race/ethnicity and were associated with treatment willingness. Ultimately, a better understanding of how patients react to information may help providers develop improved methods of communication.
Keywords: affect; decision making; risk perceptions.