Yale University School of Medicine, New Haven, CT, USA (LF, JRB, HC, SS).
VA Connecticut Healthcare System, West Haven, CT, USA (LF).
Med Decis Making. 2018 Jan;38(1):34-43. doi: 10.1177/0272989X17727002. Epub 2017 Aug 30.
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.
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.
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.
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.
确定 1）患者对药物信息是否存在不同的情感反应模式，以及 2）情感反应模式与服药意愿之间是否存在关联。
我们在受测者听取有关一种假设新药的益处和副作用描述时，实时测量他们的情绪。受测者使用手持反应系统上的一个拨号盘，从“非常好”到“非常差”来表示他们的感受。使用多时间序列的聚类分析统计方法来识别反应模式。受测者随后使用 7 分制李克特量表对他们服药的意愿进行评分。分析受测者的服药意愿评分与情感模式之间的关联。还进行了额外的分析，以探讨种族/民族在这些关联中的作用。
出现了情感反应的聚类，可以分为 4 种模式：对益处有“中度”积极反应，对副作用有消极反应（n=186）；对益处有“明显”积极反应，对副作用有消极反应（n=110）；感觉一直“良好”（n=58），感觉一直接近“中立”（n=33）。感觉良好的受测者服药意愿的平均（标准误差）为 4.72（0.20），而中度 3.76（0.11）、明显 3.68（0.14）和中立 3.62（0.26）的受测者则较低。表现出明显模式的黑人受测者比表现出明显模式的西班牙裔（P=0.0270）和白人受测者（P=0.0001）更不愿意服用药物。
患者对信息的情感反应模式聚类成特定的模式。反应因种族/民族而异，并与治疗意愿相关。最终，更好地了解患者对信息的反应可能有助于提供者开发改进的沟通方法。
