Greater adolescent tiredness is related to more emotional arousal during a hyperventilation task: An area under the curve approach

Assessing Area under the Curve as an Alternative to Latent Growth Curve Modeling for Repeated Measures Zero-Inflated Poisson Data: A Simulation Study

Researchers interested in the assessment of substance use trajectories, and predictors of change, have several data analysis options. These include, among others, generalized estimating equations and latent growth curve modeling. One difficulty in the assessment of substance use, however, is the nature of the variables studied. Although counting instances of use (e.g., the number of cigarettes smoked per day) would seem to be the best option, such data present difficulties in that the distribution of these variables is not likely normal. Count variables often follow a Poisson distribution, and when dealing with substance use in the general population, there is a preponderance of zeros (representing not using). As such, substance use counts may approximate a zero-inflated Poisson distribution. Unfortunately, analyses with zero-inflated Poisson random variables are not easily accommodated in many types of software and may be beyond access to most researchers. As such, an easier method would benefit researchers interested in assessing substance use change. The purpose of this study is to assess the area under the curve as an option when dealing with repeated measures data and contrast it to one popular method of longitudinal data analysis, latent growth curve modeling. Using a Monte Carlo simulation study with varying sample sizes, we found that the area under the curve performed well with different sample sizes and compared favorably to the performance of latent growth curve modeling, particularly when dealing with smaller sample sizes. The area under the curve may be a simpler alternative for researchers, especially when dealing with smaller sample sizes.

A double-blind, randomized, placebo-controlled test of the effects of cannabidiol on fear elicited by a 10% carbon dioxide-enriched air breathing challenge

OBJECTIVE

A single administration of cannabidiol (CBD) can reduce anxiety during social anxiety inductions. No study, however, has evaluated the impact of CBD on fear responding among humans.

METHOD

A double-blind, randomized, placebo-controlled trial was undertaken to address this gap in the literature. Specifically, the current study tested a single oral administration of CBD (either 150 mg, 300 mg, or 600 mg), compared to placebo, for reducing fear reactivity to a well-established 5-min administration of 10% carbon dioxide (CO2)-enriched air biological challenge. CBD was administered 90 min prior to the challenge. Participants were 61 healthy young adults who self-reported fear continuously during the challenge. Heart rate also was continuously monitored, and panic symptoms were self-reported using the Diagnostic Sensations Questionnaire immediately following the procedure.

RESULTS

Results indicated no effect of condition on self-reported fear, panic symptoms, or heart rate.

CONCLUSION

This is the first study to document that CBD does not reduce fear reactivity in humans, thereby representing an important extension to research on the effects of CBD.

Disparities in sleep duration among American children: effects of race and ethnicity, income, age, and sex

Children in the United States sleep less than the recommended amount and sleep deficiencies may be worse among disadvantaged children. Prior studies that compared sleep time in children of different race/ethnic groups mostly relied on questionnaires or were limited to small sample sizes. Our study takes advantage of the Adolescent Brain Cognitive Development study to compare total sleep time using a week of actigraphy data among American children (n = 4,207, 9 to 13 y old) of different racial/ethnic and income groups. We also assessed the effects of neighborhood deprivation, experience of discrimination, parent's age at child's birth, body mass index (BMI), and time the child fell asleep on sleep times. Daily total sleep time for the sample was 7.45 h and race/ethnicity, income, sex, age, BMI, were all significant predictors of total sleep time. Black children slept less than White children (∼34 min; Cohen's d = 0.95), children from lower income families slept less than those from higher incomes (∼16 min; Cohen's d = 0.44), boys slept less than girls (∼7 min; Cohen's d = 0.18), and older children slept less than younger ones (∼32 min; Cohen's d = 0.91); mostly due to later sleep times. Children with higher BMI also had shorter sleep times. Neither area deprivation index, experience of discrimination, or parent's age at child's birth significantly contributed to sleep time. Our findings indicate that children in the United States sleep significantly less than the recommended amount for healthy development and identifies significant racial and income disparities. Interventions to improve sleep hygiene in children will help improve health and ameliorate racial disparities in health outcomes.