Diary analysis of an RCT: Natural language analyses of gamma-music-based intervention

چکیده

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 both music-listening and podcast-listening participants spent a similar amount of time engaging with intervention and, on average, described positively valenced experiences. Results suggest the importance of naturalistic data obtained from diary studies as a snapshot of ongoing interventions.