Review

Measurement properties of the Epworth sleepiness scale☆

The objective of the present study was to validate the Short Version of French Sleepiness Scale for Adolescents (FSSA) with eight items (FSSA8).

A total of 384 adolescents, aged between 12 and 18 years, completed the FSSA8. These included 269 nonclinical adolescents and 115 adolescents admitted for overnight polysomnography and Multiple Sleep Latency Test (MSLT) because of suspected hypersomnia (85 patients with narcolepsy and 30 with other sleep disorders). Item response theory (IRT) assumptions were tested and psychometric properties were analysed. Matching on sex ratio and age was conducted to estimate concurrent criterion, diagnostic validity and cut-offs.

IRT assumptions were validated confirming the one-dimensionality of the FSSA8. The latent continuum sleepiness for which the scale and its items are reliable encompassed most of the clinical subjects. FSSA8 is weakly correlated with MSLT. Distribution of scores for the nonclinical group and the clinical group differed significantly; the FSSA8 had very good screening validity in sleep disorders. The cut-off was seven points.

The FSSA8 appeared to be more reliable for patients than for nonclinical participants and to be a good tool for screening excessive daytime sleepiness in sleep disorders.

La somnolence diurne est un indicateur important de la qualité et de la quantité du sommeil. Qu’il s’agisse de dépistage de pathologies rares comme l’hypersomnie ou de troubles plus fréquents comme le syndrome de retard de phase, la mesure de la somnolence est indispensable pour l’investigation clinique ou scientifique chez l’adolescent. A cette période de la vie, la somnolence diurne impacte les apprentissages, la scolarisation et le risque d’accidents sur la voie publique. L’objectif de cette étude est de tester les propriétés psychométriques de l’échelle française de la somnolence pour les adolescents (French Sleepiness Scale for Adolescents, FSSA) en vue de discriminer la somnolence normale et pathologique.

La version française de la FSSA a été adaptée pour correspondre aux versions étrangères (8 items). 384 adolescents, âgés entre 12 et 18 ans, ont renseigné la FSSA8 dont 269 hors-consultations et 115 lors d’une consultation hospitalière de sommeil avec polysomnographie et des tests itératifs de latence à l’endormissement (TILE, mesure objective de la somnolence diurne) dans le cadre d’une suspicion d’hypersomnie. 85 patients présentaient une narcolepsie et 30 d’autres troubles du sommeil. Les hypothèses de la théorie de la réponse aux items (i.e. Item Response Theory, IRT) ont été testé et les qualités psychométriques ont été analysées. Un appariement genre-âge a été réalisé pour estimer la validité diagnostique de l’échelle et pour déterminer des scores seuils.

Les hypothèses de l’IRT ont été validées confirmant la structure uni-factorielle de la FSSA8. L’échelle présente une bonne sensibilité et spécificité surtout pour les sujets cliniques bien qu’elle soit faiblement corrélée avec les mesures objectives de la somnolence (TILE). La distribution des scores pour le groupe non-clinique et le groupe clinique était significativement différente; la FSSA8 a une très bonne validité diagnostique pour les troubles du sommeil. Le seuil pathologique est de 7.

Le FSSA8 est un outil sensible dans le contexte de trouble du sommeil, et fiable pour le dépistage de la somnolence diurne excessive dans le cadre de pathologies du sommeil dans la population générale. Elle est cependant peu fiable chez les adolescents ne présentant aucun trouble du sommeil.

Vehicle automation allows drivers to disengage from driving causing a potential decline in their alertness. One of the major challenges of highly automated vehicles is to ensure a timely (with respect to safety and situation awareness) takeover in such conditions. For this purpose, the current study investigated the role of an in-vehicle digital voice-assistant (VA) in conditionally automated vehicles, offering spoken discourse relating specifically to contextual factors, such as the traffic situation and road environment. The study involved twenty-four participants, each taking two drives (counterbalanced): with VA and without VA, in a driving simulator. Participants were required to takeover vehicle control following the issuance of a takeover request (TOR) near the end of each drive. A parametric duration model was adopted to find the key factors determining takeover time (TOT). Paired comparisons showed higher alertness and higher active workload (mean NASA-TLX rating) during automation when accompanied by the VA. Paired t-test comparison of gaze behavior prior to takeover showed significantly higher instances of checking traffic signal, roadside objects, and the roadway during the drive with VA, indicating higher situation awareness. The parametric model indicated that the VA increased the likelihood of making a timely takeover by 39%. There was also some evidence suggesting that male drivers are likely to resume control 1.21 times earlier than female drivers. The study findings highlight the benefits of adopting a digital voice assistant to keep the drivers alert and aware about the recent traffic environment in partially automated vehicles.

Safety assessment among sleep-deprived drivers is a challenging research area with only a few sleep-related studies investigating safety performance during car-following. Therefore, this study aimed to measure the effects of partial sleep deprivation on driver safety during car-following. Fifty healthy male drivers with no prior history of any sleep-related disorders, drove the driving simulator in three conditions of varying sleep duration: a baseline (no sleep deprivation), test session (TS1) after one night of PSD (sleep ≤4.5 h/night) and TS2 after two consecutive nights of PSD. The reduced sleep in PSD sessions was monitored using an Actiwatch. Karolinska Sleepiness Scale was used to indicate loss of alertness among drivers. Each drive included a car-following task to measure longitudinal safety indicators based on speed and headway management: normalized time exposed to critical gap (TECG’), safety critical time headway and speed variability with respect to leading vehicle’s speed (SPV). Crash potential index (CPI) was also determined from deceleration rate of drivers during car-following and was found correlated with other indicators. Therefore, to determine the aggregate influence of PSD on safety during car-following, CPI was modelled in terms of TECG, SPV, THW and other covariates. All safety metrics were modelled using generalized mixed effects regression models. The results showed that compared to the baseline drive, critical time headway decreased by 0.65 and 1.08 times whereas speed variability increased by 1.34 and 1.28 times during the TS1 and TS2, respectively, both indicating higher crash risk. However, decrease in TECG’ by 64 % and 56 % during TS1 and TS2, respectively indicate compensatory measures to avoid risks due to sleep loss. A fractional regression model of crash potential revealed that low time-headway and higher speed variability and high time exposed to critical gap (TECG’) significantly contribute to higher CPI values indicating higher safety risk. Other covariates such as sleep duration, professional driving experience and history of traffic violations were also associated with safety indicators and CPI, however no significant effects of age were noticed in the study. The study findings present the safety indicators sensitive to rear-end crashes specifically under PSD conditions, which can be used in designing collisions avoidance systems and strategies to improve overall traffic safety.

OSA is found commonly in the elderly population (≥65 years old), and CPAP improves sleepiness and health-related quality of life (HRQoL) in the middle-aged population; however, data about its efficacy in elderly patients are unclear. The purpose of this study was to evaluate the efficacy of CPAP for sleepiness, HRQoL, mood, and cognition in elderly patients with OSA.

In elderly patients (≥65 years old) with OSA, is CPAP, compared with usual care or sham CPAP, effective at improving sleepiness, HRQoL, mood, and neurocognitive function?

We conducted a systematic review and meta-analysis of randomized controlled trials that included trials performed in elderly patients with OSA. As an intervention, we compared CPAP vs a control group. Two independent reviewers explored several databases; risk of bias (RoB) was evaluated with the Cochrane tool. Changes in sleepiness (Epworth Sleepiness Scale), HRQoL (Quebec Sleep Questionnaire), mood (Hospital Anxiety-Depression Scale), and neurocognitive tests after treatment were the outcomes. The meta-analysis was conducted according to the DerSimonian-Laird method, and the quality of evidence was rated according to the GRADE guidelines.

A total of 4 randomized controlled trials (680 participants) were included. RoB was high for performance and detection bias. CPAP was associated with a 2.62-point improvement in the Epworth Sleepiness Scale (1.93 to 3.30; I² = 52%). All domains of the Quebec Sleep Questionnaire were improved: hypersomnolence, 0.67 points (0.31 to 1.03; I² = 75%); diurnal symptoms, −0.71 points (−0.98 to −0.44; I² = 58%); nocturnal symptoms, 1.09 points (0.9 to 1.27; I² = 9%); emotions, 0.45 points (0.30 to 0.61; I² = 11%); and social interaction, 0.55 points (0.1 to 0.99; I² = 82%). CPAP also improved the Hospital Anxiety-Depression Scale depression domain, and there were reports of a slight improvement in neurocognitive tests. The quality of evidence was low and very low for all outcomes.

Although CPAP therapy reportedly results in important clinical differences in sleepiness, HRQoL, and mood and a slight improvement in neurocognitive tests, concerns regarding the RoB and quality of the evidence do not support the benefit in all patients.

PROSPERO ID CRD42019146947

This study aimed at modeling the Response Time (RT) and Total Braking Time (TBT) of drivers under Partial Sleep Deprivation (PSD). Fifty male participants drove the driving simulator in three experimental conditions: two test sessions and a baseline. The two test sessions were conducted after one and two nights of PSD (sleep = 4.25 ± 0.5 h), respectively. Sleep reduction was recorded using a wrist-worn Actiwatch. The baseline session was conducted after full rest (7-8 h sleep/day for a week). The order of test sessions and baseline was randomized. Each test included two hazard events: 1) pedestrians crossing a road and 2) parked vehicles merging into a roadway. Karolinska Sleepiness Scale (KSS) and Sleepiness Symptoms Questionnaire (SSQ) ratings were also recorded during each drive. Four separate models using parametric accelerated failure time (AFT) with Weibull distribution were developed for RT and TBT in the two events. The models were chosen with clustered heterogeneity to account for intra-group heterogeneity due to repeated measures across tests. In the case of pedestrians crossing event, RT increased by 10% in the first test session and no significant effect observed on RT in the second test session. The overall TBT reduced by 25% and 28% during the first and second PSD sessions, respectively. In the case of vehicle merging event, both response time and total braking time delayed by 44% and 17% respectively after PSD. Other factors such as age, experience, work-rest hours, KSS and SSQ rating, often exercising, approaching speed and braking force were also found significant in the analysis. The parametric AFT approach adopted in this study showed the change in ‘response time’ and ‘total braking time’ concerning the type of hazard scenario and partial sleep-deprivation.