Faculty Bibliography

OBJECTIVE: To examine the impact of a sleep course on sleep-related behaviors, mood, and anxiety in college students. PARTICIPANTS: Participants were 145 students enrolled in either the sleep course (n = 70) or a psychology course (n = 75); data were collected in September 2014, November 2014, and February 2015. METHODS: Sleep characteristics and symptoms of depression and anxiety were assessed using validated questionnaires and sleep logs. Linear, logistic and proportional odds regression models were used to test course effects. RESULTS: In November, sleep course students reported significant differences in sleep hygiene (SHI; p<0.001), perceived sleep latency (PSQI; p<0.05), and circadian sleep phase (MEQ; p<0.05), compared to controls. In February, the sleep course students maintained most of the aforementioned gains and reported fewer symptoms of depression (CES-D; p = 0.05) and anxiety (BAI; p<0.05). CONCLUSIONS: These positive preliminary results indicate that focused education has potential to improve sleep among college students.

In the current investigation, we compared and evaluated the effects of two intervention procedures, a modified chin prompt and reclined seating, on the liquid expulsion of 2 children with feeding disorders. For both participants, expulsion decreased to clinically meaningful levels when we added the modified chin prompt or reclined seating to a treatment package consisting of differential reinforcement of acceptance, nonremoval of the cup, and re-presentation. We discuss possible mechanisms underlying the effects of the 2 interventions and areas for future research.

Concerns regarding reproducibility of resting-state functional magnetic resonance imaging (R-fMRI) findings have been raised. Little is known about how to operationally define R-fMRI reproducibility and to what extent it is affected by multiple comparison correction strategies and sample size. We comprehensively assessed two aspects of reproducibility, test-retest reliability and replicability, on widely used R-fMRI metrics in both between-subject contrasts of sex differences and within-subject comparisons of eyes-open and eyes-closed (EOEC) conditions. We noted permutation test with Threshold-Free Cluster Enhancement (TFCE), a strict multiple comparison correction strategy, reached the best balance between family-wise error rate (under 5%) and test-retest reliability/replicability (e.g., 0.68 for test-retest reliability and 0.25 for replicability of amplitude of low-frequency fluctuations (ALFF) for between-subject sex differences, 0.49 for replicability of ALFF for within-subject EOEC differences). Although R-fMRI indices attained moderate reliabilities, they replicated poorly in distinct datasets (replicability < 0.3 for between-subject sex differences, < 0.5 for within-subject EOEC differences). By randomly drawing different sample sizes from a single site, we found reliability, sensitivity and positive predictive value (PPV) rose as sample size increased. Small sample sizes (e.g., < 80 [40 per group]) not only minimized power (sensitivity < 2%), but also decreased the likelihood that significant results reflect "true" effects (PPV < 0.26) in sex differences. Our findings have implications for how to select multiple comparison correction strategies and highlight the importance of sufficiently large sample sizes in R-fMRI studies to enhance reproducibility. Hum Brain Mapp 00:000-000, 2017. (c) 2017 Wiley Periodicals, Inc.

A systematic review with meta-analyses was performed to: 1) quantify the association between ADHD and risk of unintentional physical injuries in children/adolescents ("risk analysis"); 2) assess the effect of ADHD medications on this risk ("medication analysis"). We searched 114 databases through June 2017. For the risk analysis, studies reporting sex-controlled odds ratios (ORs) or hazard ratios (HRs) estimating the association between ADHD and injuries were combined. Pooled ORs (28 studies, 4,055,620 individuals without and 350,938 with ADHD) and HRs (4 studies, 901,891 individuals without and 20,363 with ADHD) were 1.53 (95% CI=1.40,1.67) and 1.39 (95% CI=1.06,1.83), respectively. For the medication analysis, we meta-analysed studies that avoided the confounding-by-indication bias [four studies with a self-controlled methodology and another comparing risk over time and groups (a "difference in differences" methodology)]. The pooled effect size was 0.879 (95% CI=0.838,0.922) (13,254 individuals with ADHD). ADHD is significantly associated with an increased risk of unintentional injuries and ADHD medications have a protective effect, at least in the short term, as indicated by self-controlled studies.