Work

Natural language processing in mixed-methods evaluation of a digital sleep-alcohol intervention for young adults

Year: 2024

Type: article

Abstract: We used natural language processing (NLP) in convergent mixed methods to evaluate young adults’ experiences with Call it a Night ( CIAN ), a digital personalized feedback and coaching sleep-alcohol intervention. Young adults with heavy drinking ( N = 120) were randomized to CIAN or controls ( A + SM : web-based advice + self-monitoring or A : advice; clinicaltrials.gov, 8/31/18, #NCT03658954). Most CIAN participants (72.0%) preferred coaching to control interventions. Control participants found advice more helpful than CIAN participants ( X 2 = 27.34, p < 0.001). Most participants were interested in sleep factors besides alcohol and appreciated increased awareness through monitoring. NLP corroborated generally positive sentiments ( M = 15.07(10.54)) and added critical insight that sleep (40%), not alcohol use (12%), was a main participant motivator. All groups had high adherence, satisfaction, and feasibility. CIAN ( Δ = 0.48, p = 0.008) and A + SM ( Δ = 0.55, p < 0.001) had higher reported effectiveness than A ( F (2, 115) = 8.45, p < 0.001). Digital sleep-alcohol interventions are acceptable, and improving sleep and wellness may be important motivations for young adults.

Source: npj Digital Medicine

DOI: 10.1038/s41746-024-01321-3