Faculty Bibliography

BACKGROUND: Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review. SCOPE AND METHODOLOGY: We first propose a neuroeconomic model of the decision-making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self-referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes. FINDINGS AND CONCLUSION: Based on clinical insights and considering each of the decision-making stages in turn, we outline disorder-specific hypotheses about impaired decision making in four childhood disorders: attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk-averse, and self-deprecating. A survey of current empirical indications related to these disorder-specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research.

OBJECTIVE: Impulsivity and inattention related to attention deficit hyperactivity disorder (ADHD) may increase food intake and, consequently, weight gain. However, findings on the association between obesity/overweight and ADHD are mixed. The authors conducted a meta-analysis to estimate this association. METHOD: A broad range of databases was searched through Aug. 31, 2014. Unpublished studies were also obtained. Study quality was rated with the Newcastle-Ottawa Scale. Random-effects models were used. RESULTS: Forty-two studies that included a total of 728,136 individuals (48,161 ADHD subjects; 679,975 comparison subjects) were retained. A significant association between obesity and ADHD was found for both children (odds ratio=1.20, 95% CI=1.05-1.37) and adults (odds ratio=1.55, 95% CI=1.32-1.81). The pooled prevalence of obesity was increased by about 70% in adults with ADHD (28.2%, 95% CI=22.8-34.4) compared with those without ADHD (16.4%, 95% CI=13.4-19.9), and by about 40% in children with ADHD (10.3%, 95% CI=7.9-13.3) compared with those without ADHD (7.4%, 95% CI=5.4-10.1). The significant association between ADHD and obesity remained when limited to studies 1) reporting odds ratios adjusted for possible confounding factors; 2) diagnosing ADHD by direct interview; and 3) using directly measured height and weight. Gender, study setting, study country, and study quality did not moderate the association between obesity and ADHD. ADHD was also significantly associated with overweight. Individuals medicated for ADHD were not at higher risk of obesity. CONCLUSIONS: This study provides meta-analytic evidence for a significant association between ADHD and obesity/overweight. Further research should address possible underlying mechanisms and the long-term effects of ADHD treatments on weight in individuals with both ADHD and obesity.

INTRODUCTION: Our aim was to assess differences in movement measures in attention-deficit/hyperactivity disorder (ADHD) vs. typically developing (TD) controls. METHODS: We performed meta-analyses of published studies on motion measures contrasting ADHD with controls. We also conducted a case-control study with children/adolescents (n=61 TD, n=62 ADHD) and adults (n=30 TD, n=19 ADHD) using the McLean motion activity test, semi-structured diagnostic interviews and the behavior rating inventory of executive function and Conners (parent, teacher; self) rating scales. RESULTS: Meta-analyses revealed medium-to-large effect sizes for actigraph (standardized mean difference [SMD]: 0.64, 95% confidence interval (CI): 0.43, 0.85) and motion tracking systems (SDM: 0.92, 95% CI: 0.65, 1.20) measures in differentiating individuals with ADHD from controls. Effects sizes were similar in studies of children/adolescents ([SMD]: 0.75, 95% CI: 0.50, 1.01) and of adults ([SMD]: 0.73, 95% CI: 0.46, 1.00). In our sample, ADHD groups differed significantly in number of head movements (p=0.02 in children; p=0.002 in adults), displacement (p=0.009/p<0.001), head area (p=0.03/p<0.001), spatial complexity (p=0.06/p=0.02) and temporal scaling (p=0.05/p=0.04). Mean effect sizes were non-significantly larger (d=0.83, 95% CI: 0.20, 1.45) in adults vs. children/adolescents with ADHD (d=0.45, 95% CI: 0.08, 0.82). In the concurrent go/no-go task, reaction time variability was significantly greater in ADHD (p<0.05 in both age groups) than controls. CONCLUSIONS: Locomotor hyperactivity remains core to the construct of ADHD even in adults. Our results suggest that objective locomotion measures may be particularly useful in evaluating adults with possible ADHD.

STUDY OBJECTIVES: To evaluate the frequency, severity, and associations of symptoms of attention-deficit/hyperactivity disorder (ADHD) in children with narcolepsy with and without cataplexy. DESIGN: Cross-sectional survey. SETTING: Four French national reference centers for narcolepsy. PATIENTS: One hundred eight consecutively referred children aged younger than 18 y with narcolepsy, with (NwC, n = 86) or without cataplexy (NwoC, n = 22), and 67 healthy controls. INTERVENTIONS: The participants, their families, and sleep specialists completed a structured interview and questionnaires about sleep, daytime sleepiness, fatigue, and ADHD symptoms (ADHD-rating scale based upon Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision [DSM-IV-TR] symptoms), and use of psychostimulants for the treatment of narcolepsy (administered in 68.2%). Polysomnographic measures were collected. MEASUREMENTS AND RESULTS: Clinically significant levels of ADHD symptoms were found in 4.8% of controls compared with 35.3% in patients with NwoC (P < 0.001) and 19.7% in patients with NwC (P < 0.01). Total ADHD scores were 6.4 (95% confidence interval [CI]: 4.5, 9.0) in controls compared with 14.2 (95% CI: 10.6, 18.9; P < 0.001), in patients with NwoC and 12.2 (95% CI: 9.8, 15.3; P < 0.01) in patients with NwC; subscores of inattention and hyperactivity/impulsivity were also significantly higher in both narcolepsy groups compared with controls. No difference was found between the NwC and NwoC groups for any ADHD measure. ADHD symptom severity was associated with increased levels of sleepiness, fatigue, and insomnia. Compared with the 34 untreated patients, the 73 patients treated with psychostimulants (modafinil in 91%) showed a trend toward lower narcolepsy symptoms but not lower ADHD symptoms. CONCLUSIONS: Pediatric patients with narcolepsy have high levels of treatment-resistant ADHD symptoms. The optimal treatment for ADHD symptoms in these patients warrants further evaluation in longitudinal intervention studies.

BACKGROUND: Although melatonin is increasingly used for sleep disturbances in children with neurodevelopmental disorders, evidence on effective dose and impact on specific types of sleep disturbance is limited. METHOD: We assessed 45 children (35 males, mean age: 6.3 +/- 1.7 years) with neurodevelopmental disorders (n = 29: intellectual disability; n = 9: autism spectrum disorder; n = 7: attention-deficit/hyperactivity disorder) and sleep disturbances, treated with melatonin (mean duration: 326 days) with doses increased according to response. RESULTS: Thirty-eight percent of children responded to low (2.5-3 mg), 31% to medium (5-6 mg) and 9% to high doses (9-10 mg) of melatonin, with a significant increase in total hours of sleep/night, decreased sleep onset delay and decreased number of awakenings/night (all: p = 0.001), as measured with sleep diaries. No serious adverse events were reported. CONCLUSIONS: Melatonin is generally effective and safe in children with neurodevelopmental conditions. Increasing above 6 mg/night adds further benefit only in a small percentage of children.

BACKGROUND: Prior follow-up studies of attention-deficit/hyperactivity disorder (ADHD) ascertained ADHD cases in clinical samples mostly from North America but rarely from European countries. They have provided a good deal of information about the persistence of ADHD and its impairments, but the degree to which these results generalize to population samples and to other countries is not certain. Prior studies have also not assessed predictors of new-onset ADHD in youth without ADHD. METHOD: At baseline, 7,912 of 18 million telephone numbers were randomly selected from throughout France from October 2, 2008, through December 11, 2008. Among 4,186 eligible families, 1,012 (24.2%) were successfully recruited at baseline, when a telephone interview was administered to all families about a child in the 6- to 12-year age range. Four years later, we attempted to recruit the entire sample to assess the persistence of ADHD and its impairments and the emergence of new associated conditions. RESULTS: 86.5% of the families assessed at baseline were followed-up (N = 875). Participants who were and were not interviewed at follow-up did not differ on any clinical or demographic features. At follow-up, the prevalence of full or subthreshold ADHD was 65.8% for ADHD participants and 9.8% for those not having ADHD at baseline. Among the children who were not diagnosed with ADHD at baseline, 3.4% were diagnosed with ADHD at follow-up. Both the persistence of ADHD and new onsets of ADHD were significantly predicted by several baseline clinical features and by having a family history of ADHD (all P values < .05). CONCLUSIONS: We replicated prior predictors of ADHD's persistence and provide new data about predictors of new ADHD onsets in the population. Our data about subthreshold ADHD support a dimensional conceptualization of the disorder and address the potential clinical utility of a subthreshold diagnostic category.

Objective: To assess group-differences in movement measures in published studies contrasting Attention-Deficit/Hyperactivity Disorder (ADHD) vs. controls. Background: ADHD diagnoses continue to be completely based on clinical history, which is subjective and subject to recall bias. In response, investigators have proposed incorporating objective measures such as locomotor activity which can be measured with actigraphy or with a high spatial and temporal resolution infrared camera. In May 2014, the United States Food and Drug Administration cleared an example of the latter, the Qb-Test, as a device to be used in supporting the diagnosis of ADHD. A review of the literature did not reveal any prior meta-analyses of such data. Methods: We performed a systematic review and meta-analysis of published studies on motion measures contrasting individuals diagnosed with ADHD and healthy controls. Two authors reviewed a total of 89 abstracts culled from an initial search of 356. After applying inclusion and exclusion criteria, 13 papers were included in our analyses of actigraphy and five papers in analyses of motion tracking systems. Results: The combined sample sizes were 406 patients with ADHD versus 359 controls with actigraphy data and 164 patients with ADHD versus 156 controls with motion tracking system data. Meta-analyses revealed medium effect sizes for actigraphy (standardized mean difference [SMD]: 0.64, 95 % CI: 0.43, 0.85) and large effects for motion tracking systems (SMD: 0.92, 95 % CI: 0.65, 1.20) in differentiating individuals with ADHD from controls. Conclusions: When measured objectively, locomotor hyperactivity robustly differentiates groups of patients with ADHD from healthy controls. Inclusion of objective locomotion measures is likely to be useful in circumstances in which ancillary information is not available, such as when evaluating adults with possible ADHD. However, even the relatively large effect sizes reported to date are unlikely to yield clinically actionable information for individual patients on their own. How to best incorporate such objective data in the diagnostic process remains unclear