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BackgroundThe COVID-19 crisis and consequent confinement restrictions have caused significant psychosocial stress and reports of sleep complaints, which require early management, have increased during recent months. To help individuals concerned about their sleep, we developed a smartphone-based app called KANOPEE that allows users to interact with a virtual agent dedicated to autonomous screening and delivering digital behavioral interventions. ObjectiveOur objective was to assess the feasibility of this app, in terms of inclusion rate, follow-up rate, perceived trust and acceptance of the virtual agent, and effects of the intervention program, in the context of COVID-19 confinement in France. MethodsThe virtual agent is an artificial intelligence program using decision tree architecture and interacting through natural body motion and natural voice. A total of 2069 users aged 18 years and above downloaded the free app during the study period (April 22 to May 5, 2020). These users first completed a screening interview based on the Insomnia Severity Index (ISI) conducted by the virtual agent. If the users were positive for insomnia complaints (ISI score >14), they were eligible to join the 2-stage intervention program: (1) complete an electronic sleep diary for 1 week and (2) follow personalized sleep recommendations for 10 days. We collected and analyzed the following measures: sociodemographic information, ISI scores and sleep/wake schedules, and acceptance and trust of the agent. ResultsApproximately 76% (1574/2069) of the app users completed the screening interview with the virtual agent. The virtual agent was well accepted by 27.4% (431/1574) of the users who answered the acceptance and trust questionnaires on its usability, satisfaction, benevolence, and credibility. Of the 773 screened users who reported sleep complaints (ISI score >14), 166 (21.5%) followed Step 1 of the intervention, and only 47 of those (28.3%) followed Step 2. Users who completed Step 1 found that their insomnia complaints (baseline mean ISI score 18.56, mean ISI score after Step 1 15.99; P21) did not respond to either intervention. ConclusionsThese preliminary results suggest that the KANOPEE app is a promising solution to screen populations for sleep complaints and that it provides acceptable and practical behavioral advice for individuals reporting moderately severe insomnia.

Assessing chronotype is essential in clinical and research environments, but the Munich ChronoType Questionnaire (MCTQ), a widely utilised tool, is not available in French. Therefore, we carried out an observational monocentric study to validate the French MCTQ against the sleep diary for sleep schedules, the Morningness-Eveningness Questionnaire (MEQ) for chronotype, and polysomnography measures. We utilised the mid-sleep point on free days (MSF), adjusted for sleep debt (MSFsc), to gauge morningness/eveningness. The study included 80 participants (average age: 40.9 years, 50% female). The sleep schedules determined by the MCTQ and the sleep diary showed a high correlation. The MSFsc demonstrated a significant correlation with the MEQ, persisting even under sleep constraints such as an alarm on free days. The predictive accuracy was strong for a morning chronotype and moderate for an evening chronotype as assessed using the MEQ. In summary, the French MCTQ is a reliable tool for researchers and clinicians for assessing sleep schedules and chronotype in French-speaking populations. The MSFsc can effectively predict chronotype, even under sleep constraints. However, for the evening chronotype, self-assessment appears to be more accurate. The association with polysomnography measures enriches our understanding of the chronotype at the intersection of behaviour and physiology. [ABSTRACT FROM AUTHOR]

To assess the association between sleep irregularity, anxiety, and depression while controlling for other sleep dimensions and using a longitudinal design. Longitudinal cohort study which started in April 2020 during the first French lockdown in the general population. Follow-up questionnaires were completed in June 2020, a period without lockdown measures. Participants were asked about their sleep (regularity, duration, timing, complaints) and their anxiety (General Anxiety Disorder-7) and depressive (Patient Health Questionnaire-9) symptoms. A total of 3745 participants were included (mean age: 28.9 years) with 2945 women (78.6%). At baseline, 38.1% (1428) of participants reported irregular sleep timing, 23.8% (891) anxiety and 28.9% (1081) depressive symptoms. In cross-sectional analyses, irregular sleep timing was associated with a 2.5-fold higher likelihood of anxiety and a 4-fold higher likelihood of depressive symptoms compared to regular sleepers. Associations were not explained by the other sleep dimensions and persisted in a longitudinal analysis, with irregular sleep timing at baseline being associated with anxiety (OR = 3.27[1.58–6.76]) and depressive symptoms (OR = 3.45[1.66–7.19]) during follow-up. The results show a strong association between sleep irregularity and mental health. Furthers studies are needed to explore how sleep regularity could promote good mental health in non-clinical populations. [ABSTRACT FROM AUTHOR]

Healthcare workers often have irregular work schedules and experience significant stress, which can lead to poor sleep quality and frequent mental health issues, especially in the context of the COVID-19 pandemic. In this cross-sectional study, we aimed to assess the prevalence of poor sleep hygiene and mental health complaints among healthcare workers and examine their associations. We investigated participants' typical sleep–wake patterns on workdays and free days as indicators of sleep hygiene. Sleep efficiency and social jetlag were calculated as the ratio of mean sleep duration to time spent in bed, while sleep rebound was defined as the difference in mean sleep duration between workdays and free days. Social jetlag was determined as the difference in mid-sleep timing between workdays and free days, with mid-sleep defined as the midpoint between bedtime and wake-up time. Insomnia severity was assessed using the Insomnia Severity Index (ISI), daytime sleepiness using the Epworth Sleepiness Scale (ESS), and symptoms of anxiety and depression using the Patient Health Questionnaire 4 (PHQ-4). Fatigue was measured using a single item inspired by the Maslach Burnout Inventory (MBI). A total of 1562 participants (80.5% women, mean age 40.0 years) were included in the study. The results revealed that 25.9% of participants slept less than 6 h, 24.3% had a sleep efficiency of less than 85%, 27.3% experienced a sleep rebound of more than 2 h, and 11.5% reported a social jetlag exceeding 2 h. Additionally, 33.9% of participants reported insomnia, 45.1% reported excessive daytime sleepiness, 13.1% reported fatigue, 16.5% reported symptoms of depression, and 35.7% reported symptoms of anxiety. After adjustment, mean sleep duration and sleep efficiency were associated with most mental health complaints. Sleep rebound and social jetlag were associated with significant insomnia but not with anxiety or depression symptoms. Our findings underscore the high prevalence of poor sleep hygiene and mental health complaints among healthcare workers, exacerbated by the COVID-19 crisis. We advocate for the promotion of sleep health through behavioral sleep strategies to safeguard the well-being of healthcare professionals. [ABSTRACT FROM AUTHOR]

Objective Fully automated digital interventions show promise for disseminating evidence-based strategies to manage insomnia complaints. However, an important concept often overlooked concerns the extent to which users adopt the recommendations provided in these programs into their daily lives. Our objectives were evaluating users' adherence to the behavioral recommendations provided by an app, and exploring whether users' perceptions of the app had an impact on their adherence behavior. Material and methods Case series study of individuals completing a fully automated insomnia management program, conducted by a virtual agent, during December 2020 to September 2022. Primary outcome was self-reported adherence to the behavioral recommendations provided. Perceptions of the app and of the virtual agent were measured with the Acceptability E-Scale and ECA-Trust Questionnaire. Insomnia was evaluated with the Insomnia Severity Index at baseline (phase 1), after 7 days of sleep monitoring (phase 2) and post-intervention (phase 3). Results A total of 824 users were included, 62.7% female, mean age 51.85 (±12.55) years. Of them, 32.7% reported having followed at least one recommendation. Users' trust in the virtual agent and acceptance of the app were related to a pre-intervention effect in insomnia severity (phase 2). In turn, larger pre-intervention improvements predicted better adherence. Mediational analyses showed that higher levels of trust in the virtual agent and better acceptance of the app exerted statistically significant positive effects on adherence (β = 0.007, 95% CI, 0.001-0.017 and β = 0.003, 95% CI 0.0004-0.008, respectively). Discussion Users' adherence is motivated by positive perceptions of the app's features and pre-intervention improvements. Conclusions Determinants of adherence should be assessed, and targeted, to increase the impact of fully automated digital interventions. [ABSTRACT FROM AUTHOR]

The use of digital technologies is constantly growing around the world. The wider-spread adoption of digital technologies and solutions in the daily clinical practice in psychiatry seems to be a question of when, not if. We propose a synthesis of the scientific literature on digital technologies in psychiatry and discuss the main aspects of its possible uses and interests in psychiatry according to three domains of influence that appeared to us: 1) assist and improve current care: digital psychiatry allows for more people to have access to care by simply being more accessible but also by being less stigmatized and more convenient; 2) develop new treatments: digital psychiatry allows for new treatments to be distributed via apps, and practical guidelines can reduce ethical challenges and increase the efficacy of digital tools; and 3) produce scientific and medical knowledge: digital technologies offer larger and more objective data collection, allowing for more detection and prevention of symptoms. Finally, ethical and efficacy issues remain, and some guidelines have been put forth on how to safely use these solutions and prepare for the future. [ABSTRACT FROM AUTHOR]