Diary Analysis of an RCT: Natural Language Analyses of Gamma-Music-Based Intervention.

Benjamin M Kubit, Corinna Parrish, Ziyan Zhao, Psyche Loui
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引用次数: 0

Abstract

Recent findings in Alzheimer's Disease research has suggested that light entrainment in the form of gamma-band (40 Hz) stimulation can ameliorate Alzheimer's-associated pathology and improve cognition. Here we report feasibility of a music-based intervention that is coupled with light entrainment in the gamma band, as well as a control intervention that pairs podcast listening with lights tuned to delta but not gamma band frequencies. We compare qualitative data from participant-maintained logbooks (diaries) and researcher notes using Natural Language Processing (NLP) methods, specifically word count and sentiment analysis, and show that while both music-listening and podcast-listening participants were able to complete the interventions, participants in the podcast intervention wrote more words in their logbooks. Results suggest the importance of naturalistic data obtained from diary studies as a snapshot of ongoing interventions.

一项随机对照试验的日记分析:基于音乐干预的自然语言分析。
阿尔茨海默病研究的最新发现表明,伽马波段(40赫兹)刺激形式的光携射可以改善阿尔茨海默病相关病理并改善认知。在这里,我们报告了一种基于音乐的干预的可行性,这种干预与伽马波段的光干扰相结合,以及一种对照干预,将播客收听与调到三角洲而不是伽马波段频率的灯光相结合。我们使用自然语言处理(NLP)方法,特别是字数统计和情感分析,比较了来自参与者维护的日志(日记)和研究人员笔记的定性数据,结果表明,虽然听音乐和听播客的参与者都能够完成干预,但播客干预的参与者在他们的日志中写了更多的单词。结果表明,从日记研究中获得的自然数据作为正在进行的干预措施的快照的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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