College of Pharmacy, Seoul National University, Seoul, Republic of Korea.
Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Republic of Korea.
J Med Internet Res. 2023 Nov 29;25:e50152. doi: 10.2196/50152.
Patient medication reviews on social networking sites provide valuable insights into the experiences and sentiments of individuals taking specific medications. Understanding the emotional spectrum expressed by patients can shed light on their overall satisfaction with medication treatment. This study aims to explore the emotions expressed by patients taking phosphodiesterase type 5 (PDE5) inhibitors and their impact on sentiment.
This study aimed to (1) identify the distribution of 6 Parrot emotions in patient medication reviews across different patient characteristics and PDE5 inhibitors, (2) determine the relative impact of each emotion on the overall sentiment derived from the language expressed in each patient medication review while controlling for different patient characteristics and PDE5 inhibitors, and (3) assess the predictive power of the overall sentiment in explaining patient satisfaction with medication treatment.
A data set of patient medication reviews for sildenafil, vardenafil, and tadalafil was collected from 3 popular social networking sites such as WebMD, Ask-a-Patient, and Drugs.com. The Parrot emotion model, which categorizes emotions into 6 primary classes (surprise, anger, love, joy, sadness, and fear), was used to analyze the emotional content of the reviews. Logistic regression and sentiment analysis techniques were used to examine the distribution of emotions across different patient characteristics and PDE5 inhibitors and to quantify their contribution to sentiment.
The analysis included 3070 patient medication reviews. The most prevalent emotions expressed were joy and sadness, with joy being the most prevalent among positive emotions and sadness being the most prevalent among negative emotions. Emotion distributions varied across patient characteristics and PDE5 inhibitors. Regression analysis revealed that joy had the strongest positive impact on sentiment, while sadness had the most negative impact. The sentiment score derived from patient reviews significantly predicted patient satisfaction with medication treatment, explaining 19% of the variance (increase in R) when controlling for patient characteristics and PDE5 inhibitors.
This study provides valuable insights into the emotional experiences of patients taking PDE5 inhibitors. The findings highlight the importance of emotions in shaping patient sentiment and satisfaction with medication treatment. Understanding these emotional dynamics can aid health care providers in better addressing patient needs and improving overall patient care.
患者在社交网络平台上对药物的评价提供了个体使用特定药物的经验和情绪的有价值的见解。了解患者表达的情绪范围可以揭示他们对药物治疗的整体满意度。本研究旨在探索服用磷酸二酯酶 5（PDE5）抑制剂的患者表达的情绪及其对情绪的影响。
本研究旨在：（1）在不同患者特征和 PDE5 抑制剂下，确定患者药物评价中 6 种鹦鹉情绪的分布；（2）在控制不同患者特征和 PDE5 抑制剂的情况下，确定每种情绪对从每位患者药物评价中的语言表达得出的整体情绪的相对影响；（3）评估整体情绪在解释患者对药物治疗的满意度方面的预测能力。
从 WebMD、Ask-a-Patient 和 Drugs.com 这 3 个受欢迎的社交网络平台上收集了西地那非、伐地那非和他达拉非的患者药物评价数据。使用鹦鹉情绪模型（将情绪分为 6 个主要类别：惊喜、愤怒、爱、喜悦、悲伤和恐惧）来分析评价中的情绪内容。逻辑回归和情感分析技术用于检查不同患者特征和 PDE5 抑制剂下情绪的分布，并量化其对情绪的贡献。
分析共纳入 3070 份患者药物评价。表达最普遍的情绪是喜悦和悲伤，其中喜悦是积极情绪中最常见的，悲伤是消极情绪中最常见的。情绪分布因患者特征和 PDE5 抑制剂而异。回归分析显示，喜悦对情绪的积极影响最强，而悲伤的消极影响最大。从患者评价中得出的情绪评分显著预测了患者对药物治疗的满意度，在控制患者特征和 PDE5 抑制剂后，解释了 19%的方差（R 值增加）。
本研究深入了解了服用 PDE5 抑制剂的患者的情绪体验。研究结果强调了情绪在塑造患者情绪和对药物治疗的满意度方面的重要性。了解这些情绪动态可以帮助医疗保健提供者更好地满足患者的需求，从而改善整体患者护理。
