[What do virtual reality tools bring to child and adolescent psychiatry?] / Qu'apportent les outils de réalité virtuelle en psychiatrie de l'enfant et l'adolescent ?

Virtual reality is a relatively new technology that enables individuals to immerse themselves in a virtual world. It offers several advantages including a more realistic, lifelike environment that may allow subjects to "forget" they are being assessed, allow a better participation and an increased generalization of learning. Moreover, the virtual reality system can provide multimodal stimuli, such as visual and auditory stimuli, and can also be used to evaluate the patient's multimodal integration and to aid rehabilitation of cognitive abilities. The use of virtual reality to treat various psychiatric disorders in adults (phobic anxiety disorders, post-traumatic stress disorder, eating disorders, addictions…) and its efficacy is supported by numerous studies. Similar research for children and adolescents is lagging behind. This may be particularly beneficial to children who often show great interest and considerable success on computer, console or videogame tasks. This article will expose the main studies that have used virtual reality with children and adolescents suffering from psychiatric disorders. The use of virtual reality to treat anxiety disorders in adults is gaining popularity and its efficacy is supported by various studies. Most of the studies attest to the significant efficacy of the virtual reality exposure therapy (or in virtuo exposure). In children, studies have covered arachnophobia social anxiety and school refusal phobia. Despite the limited number of studies, results are very encouraging for treatment in anxiety disorders. Several studies have reported the clinical use of virtual reality technology for children and adolescents with autistic spectrum disorders (ASD). Extensive research has proven the efficiency of technologies as support tools for therapy. Researches are found to be focused on communication and on learning and social imitation skills. Virtual reality is also well accepted by subjects with ASD. The virtual environment offers the opportunity to administer controlled tasks such as the typical neuropsychological tools, but in an environment much more like a standard classroom. The virtual reality classroom offers several advantages compared to classical tools such as more realistic and lifelike environment but also records various measures in standardized conditions. Most of the studies using a virtual classroom have found that children with Attention Deficit/Hyperactivity Disorder make significantly fewer correct hits and more commission errors compared with controls. The virtual classroom has proven to be a good clinical tool for evaluation of attention in ADHD. For eating disorders, cognitive behavioural therapy (CBT) program enhanced by a body image specific component using virtual reality techniques was shown to be more efficient than cognitive behavioural therapy alone. The body image-specific component using virtual reality techniques boots efficiency and accelerates the CBT change process for eating disorders. Virtual reality is a relatively new technology and its application in child and adolescent psychiatry is recent. However, this technique is still in its infancy and much work is needed including controlled trials before it can be introduced in routine clinical use. Virtual reality interventions should also investigate how newly acquired skills are transferred to the real world. At present virtual reality can be considered a useful tool in evaluation and treatment for child and adolescent disorders.

Association between reported sleep need and sleepiness at the wheel: comparative study on French highways between 1996 and 2011.

OBJECTIVE: To investigate the evolution over 15 years of sleep schedules, sleepiness at the wheel and driving risk among highway drivers. METHODS: Comparative survey including questions on usual sleep schedules and before the trip, sleepiness at the wheel, the Epworth sleepiness scale, Basic Nordic Sleep Questionnaire (BNSQ) and a travel questionnaire. RESULTS: 80% of drivers stopped by the highway patrol agreed to participate in both studies with a total of 3545 drivers in 2011 and 2196 drivers in 1996 interviewed. After standardisation based on sex, age and mean annual driving distance, drivers in 2011 reported shorter sleep time on week days (p<0.0001), and week-ends (p<0.0001) and shorter optimal sleep time (p<0.0001) compared to 1996 drivers. There were more drivers sleepy at the wheel in 2011 than in 1996 (p<0.0001) and 2.5 times more drivers in 2011 than in 1996 had an Epworth sleepiness score >15 indicating severe sleepiness. CONCLUSIONS: Even if drivers in 2011 reported good sleep hygiene prior to a highway journey, drivers have reduced their mean weekly sleep duration over 15 years and have a higher risk of sleepiness at the wheel. Sleep hygiene for automobile drivers remains an important concept to address.

Reliability of simulator driving tool for evaluation of sleepiness, fatigue and driving performance.

STUDY OBJECTIVE: To compare the impact of extended wakefulness (i.e., sleepiness) and prolonged driving (i.e., fatigue) at the wheel in simulated versus real-life driving conditions. DESIGN: Participants drove on an INRETS-MSIS SIM2 simulator in a research laboratory or an open French highway during 3 nocturnal driving sessions. A dose-response design of duration of nocturnal driving was used: a 2 h short driving session (3-5 AM), a 4 h intermediate driving session (1-5 AM) and an 8 h long driving session (9 PM-5 AM). PARTICIPANTS: Two groups of healthy male drivers (20 for simulated driving and 14 drivers for real driving; mean age±SD=22.3±1.6 years), free of sleep disorders. MEASUREMENTS: Number of inappropriate line crossings, self-rated fatigue and sleepiness were recorded in the last hour of driving sessions to control the effects of prior waking time and time of day. RESULTS: Compared to the daytime reference session, both simulated and real driving performance were affected by a short nocturnal driving session (P<.05 and P<.001, respectively). Extension of nocturnal driving duration affected simulated performance nonlinearly and more severely than that of real driving (P<.001). Compared to the daytime reference session, short nocturnal simulated and real driving sessions increased self-perceived fatigue and sleepiness. Real and simulated driving conditions had an identical impact on fatigue and sleepiness during extended periods of nocturnal driving. CONCLUSIONS: In healthy subjects, the INRETS-MSIS SIM2 simulator appropriately measures driving impairment in terms of inappropriate line crossings related to extended wakefulness but has limitations to measure the impact of extended driving on drivers' performance.

Is there a link between alertness and fatigue in patients with traumatic brain injury?

OBJECTIVES: Many patients with traumatic brain injury (TBI) report chronic fatigue, and previous studies showed a potential relationship between sleepiness and fatigue in these patients. Our study first looked at the impact of objective and subjective sleepiness on fatigue in patients with TBI. We then investigated how fatigue could affect driving performance in these patients. METHODS: Nocturnal polysomnography, the Fatigue Severity Scale (FSS), the Epworth Sleepiness Scale (ESS), and five 40-minute maintenance of wakefulness tests (MWT) were collected in 36 patients with TBI. Fitness to drive was assessed in a subsample of 22 patients compared to 22 matched controls during an hour simulated driving session. RESULTS: In patients with TBI, FSS, ESS, and mean MWT scores (+/-SD) were 27 +/- 10, 8 +/- 4, and 35 +/- 7 minutes vs 15 +/- 2.5, 5 +/- 3, and 37 +/- 5 minutes in controls. Patients with TBI reported more chronic fatigue (W = 99, p < 0.001) than controls, and, unlike in controls, the level of chronic fatigue was correlated to their MWT scores. Patients' driving performances were worse than the controls' (W = 79, p < 0.001). The best predictive factors of driving performance were fatigue scores and body mass index (multiple R = 0.458, 41.8% of explained variance). CONCLUSION: In patients with TBI, chronic fatigue is significantly related to subjective and objective levels of alertness, even though these levels are not highly pathologic. This might suggest that a small level of sleepiness (i.e., MWT scores between 33 and 39 minutes) worsens fatigue in these patients. Chronic fatigue and body mass index could predict driving simulator performance in patients with TBI.

Effect of fatigue on performance measured by a driving simulator in automobile drivers.

OBJECTIVE: To identify risk factors of performance decrement in automobile drivers. METHODS: 114 drivers (age <30 years, n=57; age > or =30 years, n=57) who stopped at a rest stop area on a freeway were recruited for the study. They filled out a questionnaire on their journey, sleep/wake patterns and performed a 30-min test on a driving simulator. The test evaluates, by computerized analysis, the lateral deviation of a virtual car from an appropriate trajectory on a virtual road. A sex/age matched control group was recruited in the community. Control subjects were studied at the same time of day as the index case driver. Controls had normal sleep wake schedule, absence of long driving and performed the same driving test. RESULTS: Drivers performed significantly worse than controls on the driving test. Age and duration of driving were the main factors associated with decreased performance. CONCLUSION: Our driving simulator can identify fatigue generated by driving but results must be considered in relation with age of subjects.