Argelinda Baroni

Practitioner Review : The assessment of bipolar disorder in children and adolescents

BACKGROUND An increasing number of youth are being diagnosed with, and treated for, bipolar disorder (BD). Controversy exists about whether youth with non-episodic irritability and symptoms of attention deficit hyperactivity disorder (ADHD) should be considered to have a developmental presentation of mania. METHOD A selective review of the literature related to this question, along with recommendations to guide clinical assessment. RESULTS Data indicate differences between youth with episodic mania and those with non-episodic irritability in longitudinal diagnostic associations, family history, and pathophysiology. In youth with episodic mania, elation and irritability are both common during manic episodes. CONCLUSIONS In diagnosing mania in youth, clinicians should focus on the presence of episodes that consist of a distinct change in mood accompanied by concurrent changes in cognition and behavior. BD should not be diagnosed in the absence of such episodes. In youth with ADHD, symptoms such as distractibility and agitation should be counted as manic symptoms only if they are markedly increased over the youths baseline symptoms at the same time that there is a distinct change in mood and the occurrence of other associated symptoms of mania. Although different techniques for diagnosing comorbid illnesses have not been compared systematically, it appears most rational to diagnose co-occurring illnesses such as ADHD only if the symptoms of the co-occurring illness are present when the youth is euthymic.

Sleep Disturbances in Pediatric Bipolar Disorder: A Comparison between Bipolar I and Bipolar NOS

Introduction: The diagnosis of bipolar disorder (BD) in youths has been controversial, especially for the subtype BD not otherwise specified (BD-NOS). In spite of growing evidence that sleep is a core feature of BD, few studies characterize and compare sleep disturbances in youth with BD type I (BD-I) and BD-NOS. Sleep disturbances are frequently reported in clinical descriptions of children and adolescents with BD, however the reporting of the frequency and characteristics of sleep symptoms in youth with BD-NOS and BD-I during episodes remain poor. This study compares symptom of sleep disturbance as occurring in manic and depressive episodes in BD-I and BD-NOS youth using Kiddie-schedule for affective disorders and schizophrenia, present and lifetime version (K-SADS-PL) interview data. The study also addresses whether symptoms of sleep disturbance vary in different age groups. Materials and Methods: The sample consisted of 70 children and adolescent outpatients at an urban specialty clinic (42M/28F, 10.8 ± 3.6 years old) including 24 BD-I and 46 BD-NOS assessed using K-SADS-PL-parent interview. Results: Sleep disturbances including insomnia and decreased need for sleep were reported by 84.3% of the sample. Enuresis was diagnosed in 27% of sample. There were no significant differences in frequency of sleep symptoms between BD-I and BD-NOS. Regardless of BD subtype, current functioning was negatively correlated with decreased need for sleep but not insomnia, and regardless of BD subtype. Conclusion: The majority of youth with BD presents with sleep symptoms during mood episodes. BD-NOS presents with the same proportion of sleep symptoms as BD-I in our sample.

Fitbit Flex: an unreliable device for longitudinal sleep measures in a non-clinical population

Dear Editor, Clinicians and researchers are increasingly interested in employing tracking devices to measure activity and sleep, both of which are calculated via algorithms that use accelerometer data [1]. While polysomnography (PSG) is viewed as the gold standard for assessing sleep, it is costly, time-intensive, and intrusive. Actigraphy is often preferred in situations for which PSG is not indicated, such as naturalistic conditions or for prolonged observations—days to weeks. However, actigraphs are relatively expensive as well, making them unsuitable to monitor large samples. As such, activity-tracking devices have been proposed as an alternative. Several recent reports, including one by Montgomery-Downs [2] published in this journal, suggest that consumer-level devices might offer a valid and reliable alternative, as they are easy to use and relatively low in cost [2–4]. We are writing this letter to report our disappointing experience with Fitbit Flex to measure sleep in a non-clinical sample of college students. We utilized the Fitbit Flex to measure sleep parameters longitudinally in a sample of college students enrolled in an IRB-approved pilot study of their sleep. One hundred and seven college students consented to monitor their sleep by wearing a Fitbit Flex for 1 week at three time points—baseline (September 2014), post-intervention (November 2014), and 3month follow-up (February 2015). Prior to baseline data collection, trained research staff taught the college students how to use the Fitbit Flex using a standardized protocol. The students also watched a video tutorial that explained how to operate the device. Additionally, we provided students the link to view the online video tutorial should they need a reminder on how to operate the device. Despite these efforts, the devices failed to capture a significant amount of sleep data at baseline (see Fig. 1): only about 14 % of the Fitbit Flexes recorded sleep six or seven nights and nearly 35 % failed to record any nights of sleep. Hypothesizing that the lack of data collected was due to user error, we retrained the students using a modified approach. After showing them how to use the Fitbit, we then asked participants to demonstrate how to track their sleep, including how to determine via the device’s light and vibration patterns to which mode the device was set (i.e., if the device was in the sleep mode or not). Students received the Fitbit Flex only after they demonstrated correct use. We subsequently found even less data were collected than previously, with nearly 70 % failing to capture any sleep data (see Fig. 1) or activity data. Of note, the lack of both sleep and activity data indicates a device failure rather than participants’ misuse. Prior to each distribution, the devices were fully charged and synced, and they appeared to function appropriately as signaled by light and vibration patterns. Due to the poor data obtained at the first two time points, we canceled the third objective sleep assessment. We contacted the Fitbit company for technical support, but found them to be generally unresponsive and ultimately not able to rectify the situation. While prior studies comparing Fitbits to actigraphs have indicated that consumer-level devices might be a feasible alternative to actigraphs, especially in non-clinical populations, most of these investigations focused on performance over a limited time period of 1 or 2 days. We are aware of only one other study that tested the performance reliability of a Fitbit * Jess P. Shatkin jess.shatkin@nyumc.org

Stimulants, cognition and ADHD

Psychostimulants such as methylphenidate and amphetamine are the first-line pharmacologic treatments for Attention-Deficit/Hyperactivity Disorder (ADHD). They are considered prototypical cognitive enhancers but their effects on standard laboratory indices of cognitive function are modest when administered acutely, and even less substantial chronically. However, large-scale observational studies in patients with ADHD have detected stimulant-associated decreases of criminal acts, transportation accidents, slightly improved academic performance, and possible protection against drug abuse. These effects likely reflect modulation of broader domains such as emotional regulation and motivation which have been under-examined. Efforts to clarify the ontological relations between cognitive tasks and their underlying constructs should be incorporated into the Research Domain Criteria project and similar harmonization initiatives.

Impact of a sleep course on sleep, mood and anxiety symptoms in college students: A pilot study

ABSTRACT 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 < .001), perceived sleep latency (PSQI; p < .05), and circadian sleep phase (MEQ; p < .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 = .05) and anxiety (BAI; p < .05). Conclusions: These positive preliminary results indicate that focused education has the potential to improve sleep among college students.