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

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.