Faculty Bibliography

We study regularized estimation in high-dimensional longitudinal classification problems, using the lasso and fused lasso regularizers. The constructed coefficient estimates are piecewise constant across the time dimension in the longitudinal problem, with adaptively selected change points (break points). We present an efficient algorithm for computing such estimates, based on proximal gradient descent. We apply our proposed technique to a longitudinal data set on Alzheimer's disease from the Cardiovascular Health Study Cognition Study. Using data analysis and a simulation study, we motivate and demonstrate several practical considerations such as the selection of tuning parameters and the assessment of model stability. While race, gender, vascular and heart disease, lack of caregivers, and deterioration of learning and memory are all important predictors of dementia, we also find that these risk factors become more relevant in the later stages of life.

Progressive muscle relaxation (PMR) is an under-utilized Level A evidence-based treatment for migraine prevention. We studied the feasibility and acceptability of smartphone application (app)-based PMR for migraine in a neurology setting, explored whether app-based PMR might reduce headache (HA) days, and examined potential predictors of app and/or PMR use. In this single-arm pilot study, adults with ICHD3 migraine, 4+ HA days/month, a smartphone, and no prior behavioral migraine therapy in the past year were asked to complete a daily HA diary and do PMR for 20 min/day for 90 days. Outcomes were: adherence to PMR (no. and duration of audio plays) and frequency of diary use. Predictors in the models were baseline demographics, HA-specific variables, baseline PROMIS (patient-reported outcomes measurement information system) depression and anxiety scores, presence of overlapping pain conditions studied and app satisfaction scores at time of enrollment. Fifty-one patients enrolled (94% female). Mean age was 39 ± 13 years. The majority (63%) had severe migraine disability at baseline (MIDAS). PMR was played 22 ± 21 days on average. Mean/session duration was 11 ± 7 min. About half (47%) of uses were 1+ time/week and 35% of uses were 2+ times/week. There was a decline in use/week. On average, high users (PMR 2+ days/week in the first month) had 4 fewer days of reported HAs in month 2 vs. month 1, whereas low PMR users (PMR < 2 days/week in the first month) had only 2 fewer HA days in month 2. PROMIS depression score was negatively associated with the log odds of using the diary at least once (vs. no activity) in a week (OR = 0.70, 95% CI = [0.55, 0.85]) and of doing the PMR at least once in a week (OR = 0.77, 95% CI = [0.68, 0.91]). PROMIS anxiety was positively associated with using the diary at least once every week (OR = 1.33, 95% CI = [1.09, 1.73]) and with doing the PMR at least once every week (OR = 1.14 [95% CI = [1.02, 1.31]). In conclusion, about half of participants used smartphone-based PMR intervention based upon a brief, initial introduction to the app. App use was associated with reduction in HA days. Higher depression scores were negatively associated with diary and PMR use, whereas higher anxiety scores were positively associated.