fda批准的处方数字疗法的用户评论的情感和主题分析:一项混合方法的真实世界证据研究。

IF 1 Q3 MEDICINE, GENERAL & INTERNAL
Cureus Pub Date : 2025-05-23 eCollection Date: 2025-05-01 DOI:10.7759/cureus.84710
Shaheen E Lakhan
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A rules-based sentiment classifier was applied based on user star ratings, and thematic content analysis was conducted using a hybrid natural language processing and manual coding approach. Reviews were grouped by app and platform, and dominant themes were extracted using unsupervised topic modeling. Results Of the 13 PDTs identified, seven had publicly accessible user reviews, yielding a dataset of 247 unique entries: AspyreRx, EndeavorRx, Regulora, Rejoyn, reSET, reSET-O, and Stanza. Sentiment classification revealed that 25.1% of reviews were positive, 12.6% neutral, and 62.3% negative. Thematic analysis identified six recurrent themes, including pediatric benefit and engagement, rewards and incentives, access and activation barriers, technical issues, emotional reactions and cost sensitivity, and boredom and frustration. 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引用次数: 0

摘要

处方数字疗法(PDTs)是fda批准的、有证据支持的、基于智能手机的干预措施。虽然临床试验在受控条件下建立了疗效,但在现实世界环境中的患者体验仍然缺乏特征。应用商店评论虽然是非正式的,但却提供了反映用户情绪、用户粘性障碍和感知利益的潜在现实证据来源。目的结合定量情感分类和定性主题分析,通过对公开应用商店评论的混合方法分析,表征fda批准的pdt的真实用户体验。方法通过FDA的De Novo或510(k)途径鉴定FDA批准的pdt。我们使用结构化抓取工具从苹果App Store和b谷歌Play Store收集评论。采用基于用户星级的基于规则的情感分类器,采用自然语言处理和人工编码相结合的方法进行主题内容分析。根据应用和平台对评论进行分组,并使用无监督主题建模提取主导主题。结果在确定的13个pdt中,有7个具有可公开访问的用户评论,产生了247个独特条目的数据集:AspyreRx, orrx, Regulora, rejyn, reSET, reSET- o和Stanza。情绪分类显示,25.1%的评论是正面的,12.6%是中性的,62.3%是负面的。专题分析确定了六个反复出现的主题,包括儿科福利和参与、奖励和激励、获取和激活障碍、技术问题、情绪反应和成本敏感性、无聊和沮丧。虽然负面情绪总体上更为普遍,但一些产品,特别是玖宁和玖宁,获得了有意义的感知益处和治疗价值报告。注意到公司的转型已经破坏了一些pdt的历史回顾数据的连续性。App store评论为pdt提供了丰富的、以用户为中心的RWE和见解来源。它们强调了在临床试验中通常没有捕捉到的访问、可用性和信任的维度。将这些反馈整合到上市后评估中,可以为未来基于软件的治疗方法的设计、监管和报销提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment and Thematic Analysis of User Reviews for FDA-Cleared Prescription Digital Therapeutics: A Mixed-Methods Real-World Evidence Study.

Background Prescription digital therapeutics (PDTs) are FDA-cleared, evidence-backed, smartphone-based interventions. While clinical trials establish efficacy under controlled conditions, the patient experience in real-world settings remains poorly characterized. App store reviews, though informal, offer a potential source of real-world evidence (RWE) reflecting user sentiment, barriers to engagement, and perceived benefit. Objective To characterize the real-world user experience of FDA-cleared PDTs through a mixed-methods analysis of publicly available app store reviews, combining quantitative sentiment classification with qualitative thematic analysis. Methods FDA-cleared PDTs via FDA's De Novo or 510(k) pathways were identified. Reviews were collected from the Apple App Store and Google Play Store using structured scraping tools. A rules-based sentiment classifier was applied based on user star ratings, and thematic content analysis was conducted using a hybrid natural language processing and manual coding approach. Reviews were grouped by app and platform, and dominant themes were extracted using unsupervised topic modeling. Results Of the 13 PDTs identified, seven had publicly accessible user reviews, yielding a dataset of 247 unique entries: AspyreRx, EndeavorRx, Regulora, Rejoyn, reSET, reSET-O, and Stanza. Sentiment classification revealed that 25.1% of reviews were positive, 12.6% neutral, and 62.3% negative. Thematic analysis identified six recurrent themes, including pediatric benefit and engagement, rewards and incentives, access and activation barriers, technical issues, emotional reactions and cost sensitivity, and boredom and frustration. While negative sentiment was more prevalent overall, several products, particularly Rejoyn and EndeavorRx, received meaningful reports of perceived benefit and therapeutic value. Company transitions were noted to have disrupted the continuity of historical review data of some PDTs. Conclusions App store reviews provide a rich, user-centered source of RWE and insights for PDTs. They highlight dimensions of access, usability, and trust not typically captured in clinical trials. Integrating such feedback into post-market evaluation may inform future design, regulation, and reimbursement of software-based therapeutics.

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