PANDEM-Source, a tool to collect or generate surveillance indicators for pandemic management: a use case with COVID-19 data.

Introduction: PANDEM-Source (PS) is a tool to collect and integrate openly available public health-related data from heterogeneous data sources to support the surveillance of infectious diseases for pandemic management. The tool may also be used for pandemic preparedness by generating surveillance data for training purposes. It was developed as part of the EU-funded Horizon 2020 PANDEM-2 project during the COVID-19 pandemic as a result of close collaboration in a consortium of 19 partners, including six European public health agencies, one hospital, and three first responder organizations. This manuscript describes PS's features and design to disseminate its characteristics and capabilities to strengthen pandemic preparedness and response. Methods: A requirement-gathering process with EU pandemic managers in the consortium was performed to identify and prioritize a list of variables and indicators useful for surveillance and pandemic management. Using the COVID-19 pandemic as a use case, we developed PS with the purpose of feeding all necessary data to be displayed in the PANDEM-2 dashboard. Results: PS routinely monitors, collects, and standardizes data from open or restricted heterogeneous data sources (users can upload their own data). It supports indicators and health resources related data from traditional data sources reported by national and international agencies, and indicators from non-traditional data sources such as those captured in social and mass media, participatory surveillance, and seroprevalence studies. The tool can also calculate indicators and be used to produce data for training purposes by generating synthetic data from a minimal set of indicators to simulate pandemic scenarios. PS is currently set up for COVID-19 surveillance at the European level but can be adapted to other diseases or threats and regions. Conclusion: With the lessons learnt during the COVID-19 pandemic, it is important to keep building capacity to monitor potential threats and develop tools that can facilitate training in all the necessary aspects to manage future pandemics. PS is open source and its design provides flexibility to collect heterogeneous data from open data sources or to upload end users's own data and customize surveillance indicators. PS is easily adaptable to future threats or different training scenarios. All these features make PS a unique and valuable tool for pandemic management.

Predictors of users' adherence to a fully automated digital intervention to manage insomnia complaints.

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 (ß = 0.007, 95% CI, 0.001-0.017 and ß = 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.

From improved sleep regularity to reduced sleep complaints and mental health conditions: a population-based interventional study using a smartphone-based virtual agent.

STUDY OBJECTIVES: To explore the effect of sleep regularity on sleep complaints and mental health conditions (i.e. insomnia, fatigue, anxiety, and depressive symptoms) in a population-based interventional study using a smartphone-based virtual agent. METHODS: A populational cohort based on the Kanopée application, which provided interactions with a virtual companion to collect data on sleep and make personalized recommendations to improve sleep over 17 days. A pre-intervention sleep diary and interview were used for cross-sectional analysis (n = 2142), and a post-intervention sleep diary and interview were used for longitudinal analysis (n = 732). The intra-individual mean (IIM) and standard deviation (ISD) of total sleep time (TST) were calculated to measure sleep quantity and sleep regularity. RESULTS: The mean age at baseline was 49 years, 65% were female, 72% reported insomnia, 58% fatigue, 36% anxiety, and 17% depressive symptoms. Before the intervention, irregular and short sleep was associated with a higher likelihood of insomnia (Relative risk [RR] = 1.26 [1.21-1.30] for irregular TST and RR = 1.19 [1.15-1.23] for short TST), fatigue, anxiety, and depressive symptoms. After the intervention, the IIM of the TST increased while the ISD of the TST and sleep complaints and mental health conditions decreased. More regular TST was associated with reduced insomnia and depressive symptoms (RR = 1.33 [1.10-1.52] and RR = 1.55 [1.13-1.98], respectively). CONCLUSIONS: Our results reveal a longitudinal association between sleep regularity and sleep complaints and mental health conditions. Policymakers, health professionals, and the general population should be aware that, beyond its positive effect on sleep health, regular sleep could promote mental health.

The Craving-Manager smartphone app designed to diagnose substance use/addictive disorders, and manage craving and individual predictors of relapse: a study protocol for a multicenter randomized controlled trial.

Background: The rate of individuals with addiction who are currently treated are low, and this can be explained by barriers such as stigma, desire to cope alone, and difficulty to access treatment. These barriers could be overcome by mobile technologies. EMI (Ecological Momentary Intervention) is a treatment procedure characterized by the delivery of interventions (messages on smartphones) to people in their daily lives. EMI presents opportunities for treatments to be available to people during times and in situations when they are most needed. Craving is a strong predictor of relapse and a key target for addiction treatment. Studies using Ecological Momentary Assessment (EMA) method have revealed that, in daily life, person-specific cues could precipitate craving, that in turn, is associated with a higher probability to report substance use and relapse in the following hours. Assessment and management of these specific situations in daily life could help to decrease addictive use and avoid relapse. The Craving-Manager smartphone app has been designed to diagnose addictive disorders, and assess and manage craving as well as individual predictors of use/relapse. It delivers specific and individualized interventions (counseling messages) composed of evidence-based addiction treatments approaches (cognitive behavioral therapy and mindfulness). The Craving-Manager app can be used for any addiction (substance or behavior). The objective of this protocol is to evaluate the efficacy of the Craving-Manager app in decreasing use (of primary substance(s)/addictive behavior(s)) over 4 weeks, among individuals on a waiting list for outpatient addiction treatment. Methods/design: This multicenter double-blind randomized controlled trial (RCT) will compare two parallel groups: experimental group (full interventional version of the app, 4 weeks, EMA + EMI), versus control group (restricted version of the app, 4 weeks, only EMA). Two hundred and seventy-four participants will be recruited in 6 addiction treatment centers in France. Discussion: This RCT will provide indication on how the Craving-Manager app will reduce addictive use (e.g., better craving management, better stimulus control) in both substance and behavioral addictions. If its efficacy is confirmed, the app could offer the possibility of an easy to use and personalized intervention accessible to the greatest number of individuals with addiction. Clinical Trial Registration: ClinicalTrials.gov: NCT04732676.

Exposure to Disinfectants and Cleaning Products and Respiratory Health of Workers and Children in Daycares: The CRESPI Cohort Protocol.

Although cleaning tasks are frequently performed in daycare, no study has focused on exposures in daycares in relation to respiratory health. The CRESPI cohort is an epidemiological study among workers (n~320) and children (n~540) attending daycares. The purpose is to examine the impact of daycare exposures to disinfectants and cleaning products (DCP) on the respiratory health of workers and children. A sample of 108 randomly selected daycares in the region of Paris has been visited to collect settled dust to analyze semi-volatile organic compounds and microbiota, as well as sample indoor air to analyze aldehydes and volatile organic compounds. Innovative tools (smartphone applications) are used to scan DCP barcodes in daycare and inform their use; a database then matches the barcodes with the products' compositions. At baseline, workers/parents completed a standardized questionnaire, collecting information on DCP used at home, respiratory health, and potential confounders. Follow-up regarding children's respiratory health (monthly report through a smartphone application and biannual questionnaires) is ongoing until the end of 2023. Associations between DCP exposures and the respiratory health of workers/children will be evaluated. By identifying specific environments or DCP substances associated with the adverse respiratory health of workers and children, this longitudinal study will contribute to the improvement of preventive measures.

Efficacy of a Smartphone-Based Virtual Companion to Treat Insomniac Complaints in the General Population: Sleep Diary Monitoring Versus an Internet Autonomous Intervention.

(1) Background: Insomnia is the most prevalent sleep disorder worldwide and cognitive behavioral therapy is the front-line treatment. Digital health technologies have a role to play in screening and delivering interventions remotely and without the need for human intervention. The KANOPEE app, which provides a screening and behavioral intervention for insomnia symptoms through an interaction with a virtual agent, showed encouraging results in previous studies during and after the COVID-19 lockdown, but has not yet been evaluated in a controlled study. This study aims at comparing the benefits of KANOPEE, a smartphone application dealing with insomnia complaints, with another application proposing an electronic sleep diary named "My Sleep Diary". The acceptance and potential benefits of these digital solutions are tested in real-life settings (i.e., without soliciting human medical resources) and in the general population. (2) Methods: Subjects were included if they downloaded one of the apps between December 2020 and October 2021, and were of legal age. Both apps were available on downloading platforms in France. Primary outcome was Insomnia Severity Index (ISI), and secondary outcomes were total sleep time (TST), sleep efficiency (SE) and wake time after sleep onset (WASO). (3) Results: A total of 535 users completed the intervention with KANOPEE and 489 users completed My Sleep Diary, both for 17 days. KANOPEE users improved their ISI score significantly more than sleep diary users (interaction Time*Group: F(2,2002) = 17.3, p < 0.001). Similar results were found for nocturnal sleep parameters (TST) (KANOPEE users gained 48 min of sleep after intervention, while My Sleep Diary users gained only 16 min of sleep), and particularly in the population with moderate to severe initial sleep complaints (F(4,1980) = 8.9, p < 0.001). Other sleep markers (SE and WASO) were significantly improved in the KANOPEE users compared to the sleep diary ones (p < 0.001). (4) Conclusions: KANOPEE provides significantly greater benefits than an electronic sleep diary regarding reduction of insomnia complaints and estimated nocturnal sleep characteristics in a self-selected sample of the general population. Population with the most severe initial ISI score (≥15) benefited the most from the KANOPEE App compared to filling up a simple sleep diary.

Association between household cleaning product profiles evaluated by the Ménag'Score® index and asthma symptoms among women from the SEPAGES cohort.

OBJECTIVE: Considering household disinfectants and cleaning products (HDCP) as mixture of ingredients, rather than each ingredient individually, might help in characterizing their role in asthma. We investigated the association between HDCP and asthma, using the recently developed Ménag'Score®, a health risk assessment score based on exhaustive ingredient lists of HDCP. METHODS: The study is based on 103 female volunteers of the SEPAGES cohort (2014-2019), with repeated data (up to 3 collection times, 200 observations). HDCP use was assessed from a barcode-based smartphone application linked with an ingredient database. The Ménag'score® risks for health and environment were computed for each weekly used HDCP from their exhaustive ingredient data (from A: no known risk to E: highest risk). The association between the use of HDCP with a poor Ménag'score® (D or E; overall, health, environment scores) and asthma symptoms, was estimated by generalized estimating equations models adjusted for age, BMI and smoking status. RESULTS: Participants were on average 33 years old, 11% smoked and 20% had at least one asthma symptom. The Ménag'score® was computed for 540 HDCP scanned by participants. Weekly use of HDCP with a poor Ménag'score®-health (around 60% of the participants) was associated with a higher risk of asthma symptoms (OR 3.13, 95% CI [1.32-7.43]). No association was observed for the Ménag'score®-environment. CONCLUSION: The use of HDCP with a poor Ménag'score®-health was associated with asthma symptoms. The results support the use of the Ménag'score®-health to further evaluate the health risks of HDCP in observational studies and as a potential public health tool.

Smartphone-based virtual agents and insomnia management: A proof-of-concept study for new methods of autonomous screening and management of insomnia symptoms in the general population.

Insomnia is the most frequent sleep disorder, and the COVID-19 crisis has massively increased its prevalence in the population, due to psychosocial stress or direct viral contamination. KANOPEE_2 is a smartphone-based application that provides interactions with a virtual agent to autonomously screen and alleviate insomnia symptoms through an intervention programme giving personalized advices regarding sleep hygiene, relaxation techniques and stimulus-control. In this proof-of-concept study, we tested the effects of KANOPEE_2 among users from all over the country (France) who downloaded the app between 1 June and 26 October 2020 (to focus on effects after the end of COVID-19 confinement). Outcome measures include insomnia severity (Insomnia Severity Index) and sleep/wake schedules measured by a sleep diary. One-thousand and thirty-four users answered the screening interview (Mage  = 43.76 years; SD = 13.14), and 108 completed the two-step programme (Mage  = 46.64 years; SD = 13.63). Of those who answered the screening, 42.8% did not report sleep complaints, while 57.2% presented mild-to-severe insomnia symptoms. At the end of the intervention, users reported significantly fewer sleep complaints compared with the beginning of the intervention (Insomnia Severity Indexbeginning  = 13.58; Insomnia Severity Indexend  = 11.30; p < 0.001), and significantly increased their sleep efficiency (sleep efficiencybeginning  = 76.46%; sleep efficiencyend  = 80.17%; p = 0.013). KANOPEE_2 is a promising solution both to provide autonomous evaluation of individuals' sleep hygiene and reduce insomnia symptoms over a brief and simple intervention. These results are very encouraging for addressing the issue of insomnia management in people exposed to major psychosocial stress and the consequences of COVID-19 infection.

Effectiveness and Acceptance of a Smartphone-Based Virtual Agent Screening for Alcohol and Tobacco Problems and Associated Risk Factors During COVID-19 Pandemic in the General Population.

Background: During the current COVID-19 pandemic, alcohol, and tobacco are the most available substances for managing stress and can induce a risk of addiction. KANOPEE is a smartphone application available to the general population using an embodied conversational agent (ECA) to screen for experiences of problems with alcohol/tobacco use and to provide follow-up tools for brief intervention. Objectives: This study aimed to determine if the smartphone KANOPEE application could identify people at risk for alcohol and/or tobacco use disorders in the context of the current COVID-19 pandemic, to assess adherence to a 7-day follow-up use diary, and to evaluate trust and acceptance of the application. Methods: The conversational agent, named Jeanne, interviewed participants about perceived problems with the use of alcohol and tobacco since the pandemic and explored risk for tobacco and alcohol use disorder with the five-item Cigarette Dependence Scale (CDS-5) and "Cut Down, Annoyed, Guilty, Eye-opener" (CAGE) questionnaire and experience of craving for each substance. Descriptive, univariate, and multivariate analyses were performed to specify personalized associations with reporting a problem with alcohol/tobacco use; descriptive analysis reported the experience with the intervention and acceptance and trust in the application. Results: From April 22 to October 26, 2020, 1,588 French participants completed the KANOPEE interview, and 318 answered the acceptance and trust scales. Forty-two percent of tobacco users and 27% of alcohol users reported problem use since the pandemic. Positive screening with CDS-5 and CAGE and craving were associated with reported problem use (p < 0.0001). Lockdown period influenced alcohol (p < 0.0005) but not tobacco use (p > 0.05). Eighty-eight percent of users reported that KANOPEE was easy to use, and 82% found Jeanne to be trustworthy and credible. Conclusion: KANOPEE was able to screen for risk factors for substance use disorder (SUD) and was acceptable to users. Reporting craving and being at risk for SUD seem to be early markers to be identified. Alcohol problem use seems to be more reliant on contextual conditions such as confinement. This method is able to offer acceptable, brief, and early intervention with minimal delay for vulnerable people.

Comparison of a Barcode-Based Smartphone Application to a Questionnaire to Assess the Use of Cleaning Products at Home and Their Association with Asthma Symptoms.

Household disinfectant and cleaning products (HDCPs) assessment is challenging in epidemiological research. We hypothesized that a newly-developed smartphone application was more objective than questionnaires in assessing HDCPs. Therefore, we aimed to compare both methods, in terms of exposure assessments and respiratory health effects estimates. The women of the SEPAGES birth cohort completed repeated validated questionnaires on HDCPs and respiratory health and used an application to report HDCPs and scan products barcodes, subsequently linked with an ingredients database. Agreements between the two methods were assessed by Kappa coefficients. Logistic regression models estimated associations of HDCP with asthma symptom score. The 101 participants (18 with asthma symptom score ≥1) scanned 617 different products (580 with available ingredients list). Slight to fair agreements for sprays, bleach and scented HDCP were observed (Kappa: 0.35, 0.25, 0.11, respectively). Strength of the associations between HDCP and asthma symptom score varied between both methods but all odds ratios (OR) were greater than one. The number of scanned products used weekly was significantly associated with the asthma symptom score (adjusted-OR [CI 95%]: 1.15 [1.00-1.32]). This study shows the importance of using novel tools in epidemiological research to objectively assess HDCP and therefore reduce exposure measurement errors.

Smartphone-Based Virtual Agents to Help Individuals With Sleep Concerns During COVID-19 Confinement: Feasibility Study.

BACKGROUND: The 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. OBJECTIVE: Our 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. METHODS: The 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. RESULTS: Approximately 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; P<.001) and nocturnal sleep quality improved significantly after 1 week. Users who completed Step 2 also showed an improvement compared to the initial measures (baseline mean ISI score 18.87, mean ISI score after Step 2 14.68; P<.001). Users that were most severely affected (ISI score >21) did not respond to either intervention. CONCLUSIONS: These 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.

Trust and acceptance of a virtual psychiatric interview between embodied conversational agents and outpatients.

Virtual agents have demonstrated their ability to conduct clinical interviews. However, the factors influencing patients' engagement with these agents have not yet been assessed. The objective of this study is to assess in outpatients the trust and acceptance of virtual agents performing medical interviews and to explore their influence on outpatients' engagement. In all, 318 outpatients were enroled. The agent was perceived as trustworthy and well accepted by the patients, confirming the good engagement of patients in the interaction. Older and less-educated patients accepted the virtual medical agent (VMA) more than younger and well-educated ones. Credibility of the agent appeared to main dimension, enabling engaged and non-engaged outpatients to be classified. Our results show a high rate of engagement with the virtual agent that was mainly related to high trust and acceptance of the agent. These results open new paths for the future use of VMAs in medicine.

Event-Related Electrodermal Response to Stress: Results From a Realistic Driving Simulator Scenario.

OBJECTIVE: The study goal was to test whether induced stress during driving could be measured at the event level through electrodermal activity responses. BACKGROUND: Stress measured in simulation scenarios could thus far show an overall change in the stress state, but not be well attributed to acute stressful events. Driving simulator scenarios that induce stress measurable at the event level in realistic situations are thus warranted. As such, acute stress reactions can be measured in the context of changing situational factors such as fatigue, substance abuse, or medical conditions. METHOD: Twelve healthy female participants drove the same route numerous times in a driving simulator, each time with different random traffic events occurring throughout. During one of the scenarios, unknown to the participants, 10 programmed neutral traffic events occurred, whereas in another scenario, at the same location, 10 stressful events occurred. RESULTS: Electrodermal response results showed both effects of scenario type and of events. The amplitude of the electrodermal response was significantly correlated with subjective stress experience. CONCLUSION: We conclude that our developed ecological driving simulation scenarios can be used to induce and measure stress at the event level. APPLICATION: The developed simulator scenarios enable us to measure stress reactions in driving situations at the time when the event actually happens. With these scenarios, we can measure how situational factors, such as fatigue or substance abuse, can change immediate stress reactions when driving. We can further measure more specifically how induced driving stress can affect physical and mental functioning afterward.

Evaluation of a virtual agent to train medical students conducting psychiatric interviews for diagnosing major depressive disorders.

BACKGROUND: A psychiatric diagnosis involves the physician's ability to create an empathic interaction with the patient in order to accurately extract semiology (i.e., clinical manifestations). Virtual patients (VPs) can be used to train these skills but need to be evaluated in terms of accuracy, and to be perceived positively by users. METHODS: We recruited 35 medical students who interacted in a 35-min psychiatric interview with a VP simulating major depressive disorders. Semiology extraction, verbal and non-verbal empathy were measured objectively during the interaction. The students were then debriefed to collect their experience with the VP. RESULTS: The VP was able to simulate the conduction of a psychiatric interview realistically, and was effective to discriminate students depending on their psychiatric knowledge. Results suggest that students managed to keep an emotional distance during the interview and show the added value of emotion recognition software to measure empathy in psychiatry training. Students provided positive feedback regarding pedagogic usefulness, realism and enjoyment in the interaction. LIMITATIONS: Our sample was relatively small. As a first prototype, the measures taken by the VP would need improvement (subtler empathic questions, levels of difficulty). The face-tracking technique might induce errors in detecting non-verbal empathy. CONCLUSION: This study is the first to simulate a realistic psychiatric interview and to measure both skills needed by future psychiatrists: semiology extraction and empathic communication. Results provide evidence that VPs are acceptable by medical students, and highlight their relevance to complement existing training and evaluation tools in the field of affective disorders.

How sleep problems contribute to simulator sickness: Preliminary results from a realistic driving scenario.

Virtual reality and simulation tools enable us to assess daytime functioning in environments that simulate real life as close as possible. Simulator sickness, however, poses a problem in the application of these tools, and has been related to pre-existing health problems. How sleep problems contribute to simulator sickness has not yet been investigated. In the current study, 20 female chronic insomnia patients and 32 female age-matched controls drove in a driving simulator covering realistic city, country and highway scenes. Fifty percent of the insomnia patients as opposed to 12.5% of controls reported excessive simulator sickness leading to experiment withdrawal. In the remaining participants, patients with insomnia showed overall increased levels of oculomotor symptoms even before driving, while nausea symptoms further increased after driving. These results, as well as the realistic simulation paradigm developed, give more insight on how vestibular and oculomotor functions as well as interoceptive functions are affected in insomnia. Importantly, our results have direct implications for both the actual driving experience and the wider context of deploying simulation techniques to mimic real life functioning, in particular in those professions often exposed to sleep problems.

Development and validation of a virtual agent to screen tobacco and alcohol use disorders.

BACKGROUND: Substance use disorders are under-detected and not systematically diagnosed or screened for by primary care. In this study, we present the acceptability and validity of an Embodied Conversational Agent (ECA) designed to screen tobacco and alcohol use disorder, in individuals who did not seek medical help for these disorders. METHODS: Individuals were included from June 2016 to May 2017 in the Outpatient Sleep Clinic of the University Hospital of Bordeaux. DSM-5 diagnoses of tobacco and alcohol use disorders were assessed by human interviewers. The ECA interview integrated items from the Cigarette Dependence Scale-5 (CDS-5) for tobacco use disorder screening, and the "Cut Down, Annoyed, Guilty, Eye-opener" (CAGE) questionnaire for alcohol use disorder screening. Paper version of CDS-5 and CAGE questionnaires and acceptability questionnaire was also self-administered. RESULTS: Of the 139 participants in the study (mean age 43.0 [SD = 13.7] years), 71 were women, and 68 were men. The ECA was well accepted by the patients. Paper self-administered CDS-5 and CAGE scores had a strong agreement with the ECA (p < 0.0001). The Receiver Operating Characteristic (ROC) analysis of the ECA interview showed AUC of 0.97 (95% CI, 0.93-1.0) and 0.84 (95% CI, 0.69-0.98) for CDS-5 and CAGE respectively with p-value <0.0001. CONCLUSIONS: This ECA was acceptable and valid to screen tobacco or alcohol use disorder among patients not requesting treatment for addiction. The ECA could be used in hospitals and potentially in primary care settings to help clinicians to better screen their patients for alcohol and tobacco use disorders.

Development of a bar code-based exposure assessment method to evaluate occupational exposure to disinfectants and cleaning products: a pilot study.

OBJECTIVE: Healthcare workers are highly exposed to various types of disinfectants and cleaning products. Assessment of exposure to these products remains a challenge. We aimed to investigate the feasibility of a method, based on a smartphone application and bar codes, to improve occupational exposure assessment among hospital/cleaning workers in epidemiological studies. METHODS: A database of disinfectants and cleaning products used in French hospitals, including their names, bar codes and composition, was developed using several sources: ProdHyBase (a database of disinfectants managed by hospital hygiene experts), and specific regulatory agencies and industrial websites. A smartphone application has been created to scan bar codes of products and fill a short questionnaire. The application was tested in a French hospital. The ease of use and the ability to record information through this new approach were estimated. RESULTS: The method was tested in a French hospital (7 units, 14 participants). Through the application, 126 records (one record referred to one product entered by one participant/unit) were registered, majority of which were liquids (55.5%) or sprays (23.8%); 20.6% were used to clean surfaces and 15.9% to clean toilets. Workers used mostly products with alcohol and quaternary ammonium compounds (>90% with weekly use), followed by hypochlorite bleach and hydrogen peroxide (28.6%). For most records, information was available on the name (93.7%) and bar code (77.0%). Information on product compounds was available for all products and recorded in the database. CONCLUSION: This innovative and easy-to-use method could help to improve the assessment of occupational exposure to disinfectants/cleaning products in epidemiological studies.

[Virtual doctors and e-health]. / Médecins virtuels et e-santé.

One of the challenges of e-health will be to give concrete form to personalised therapeutic solutions using connected objects, information and decision-making systems, and patient management behavioural programmes. Developed to improve the empathetic relationship with patients, virtual companions are the subject of research programmes.

Virtual human as a new diagnostic tool, a proof of concept study in the field of major depressive disorders.

Embodied Conversational Agents (ECAs) are promising software to communicate with patients but no study has tested them in the diagnostic field of mental disorders. The aim of this study was 1) to test the performance of a diagnostic system for major depressive disorders (MDD), based on the identification by an ECA of specific symptoms (the MDD DSM 5 criteria) in outpatients; 2) to evaluate the acceptability of such an ECA. Patients completed two clinical interviews in a randomized order (ECA versus psychiatrist) and filled in the Acceptability E-scale (AES) to quantify the acceptability of the ECA. 179 outpatients were included in this study (mean age 46.5 ± 12.9 years, 57.5% females). Among the 35 patients diagnosed with MDD by the psychiatrist, 14 (40%) patients exhibited mild, 12 (34.3%) moderate and 9 (25.7%) severe depressive symptoms. Sensitivity increased across the severity level of depressive symptoms and reached 73% for patients with severe depressive symptoms, while specificity remained above 95% for all three severity levels. The acceptability of the ECA evaluated by the AES was very good (25.4). We demonstrate here the validity and acceptability of an ECA to diagnose major depressive disorders. ECAs are promising tools to conduct standardized and well-accepted clinical interviews.