P099 Personality predictors of engagement with self-reports in sleep-disordered young adults

Abstract Introduction Young adults are vulnerable to sleep disturbance and associated daytime impairment, yet the interplay between sleep and daytime function over time is poorly understood in young adults with sleep disorders. This may be because traditional measures of sleep-related impairment are difficult to employ longitudinally at high frequency. To address this limitation, we described engagement with a mobile app-based “check-in” to monitor daytime function in young adults with sleep disorders. We also considered personality predictors of initial and total engagement. Methods As part of a larger type-1 effectiveness-implementation study, participants could voluntarily download Hoap, a smartphone-based application containing a brief daily check-in for self-reporting daytime function. Big Five personality dimensions were derived using the NEO-Personality Inventory. We used a hurdle model with a negative binomial count component to determine if personality domain scores predict (i) the odds of downloading Hoap and, subsequently, (ii) the total number of daily self-reports made during the 90-day monitoring period. Results Of the 64 participants (38 female; [mean(±SD)] age = 25(±5) yrs), 33 voluntarily downloaded Hoap. In those that did, mean number of daily self-reports was 10.5(±15.5). Trait agreeableness (OR[95%CI] =1.12[1.03, 1.23]) and age (1.17[1.03, 1.34]) were the only predictors of downloading Hoap. No personality or demographic variables predicted number of daily self-reports in the model’s negative binomial component. Discussion Young adults with sleep disorders may struggle to engage with daily self-report check-ins for daytime function. Strategies that incentivise engagement are likely required in this vulnerable population to help better understand the sleep-functioning interplay over extended periods.