Children and Adolescents Psychological Distress Scale During COVID-19 Pandemic: Validation of a Psychometric Instrument (CONFEADO Study)

AIM AND OBJECT PURPOSE OF THE STUDY: In March 2020, the WHO declared a pandemic (COVID-19) due to the SARS-CoV-2 virus. In France, school closures and lockdowns were implemented. In this unprecedented context for French adolescents and children, the CONFEADO study surveyed children aged 9 to 18 years to assess their mental health, psychological distress, and resilience during and after the lockdown in relation to their living and housing conditions. To assess psychological distress, a psychometric tool (Children and Adolescent Psychological Distress Scale-CAPDS-10) was specifically designed for the research. This article presents the psychometric validity of the CAPDS-10. METHODS: This cross-sectional study collected data from June 9 to September 14, 2020, from children and adolescents (9 to 18 years of age) via an online questionnaire after sending it to a large network of partners. Psychological distress, resilience, and trait anxiety were assessed using the CAPDS-10, the Child and Youth Resilience Measure (CYRM), and the State-Trait Anxiety Inventory for Children (STAIC). The CAPDS-10 measured perceived psychological distress in the most recent 2 weeks (primary endpoint). The predictive power of the CAPDS-10 was determined by statistical analysis. We proceeded to a confirmatory factor analysis to validate the scale at a clinical level. We carried out a psychometric validation with a step to verify the uni-dimensionality of the scale (PCA analysis) and the calculation of convergent and divergent validity, correlation coefficient between items and subscales, Cronbach's alpha for reliability, determination of a cut-off score for the AUROC index. RESULTS: Three thousand and forty eight children and adolescents completed the CAPDS-10. Analysis confirmed a three-factor model (anxiety, depression, and aggressive behavior) (RMSEA = 0.072 [0.067; 0.077], CFI = 0.954), with a correlation coefficient between items >0.4. PCA analysis concluded that the scale is unidimensional. Reliability was satisfactory with Cronbach's alpha coefficients >0.7 (0.86). In addition, prediction was good with an AUROC index equal to 0.73 and a threshold score for severe distress greater than or equal to 19. CONCLUSION: The CAPDS-10 measures psychological distress over the most recent 2-week period with good psychometric qualities. It could be used in crisis or prevention contexts in the general population or in clinical settings

Evolution in French University Students' Mental Health One Month After the First COVID-19 Related Quarantine: Results From the COSAMe Survey

International audienceIntroduction The COVID-19 related quarantine had negative psychological effects among University students. Evidence from previous epidemics suggests that negative psychological effects of quarantine measures can last or even worsen after the quarantine lift. The objective of this study was to assess the evolution of students' mental health and to identify factors associated with mental health outcomes 1 month after the lift of the lockdown. Materials and Methods This repeated cross-sectional study collected data during the first quarantine in France (T1, N = 68,891) and 1 month after its lift (T2, N = 22,540), through an online questionnaire sent to all French University students. Using cross-sectional data, we estimated prevalence rates of suicidal thoughts, severe anxiety (State-Trait Anxiety Inventory, State subscale), depression (Beck Depression Inventory), and stress (Perceived Stress Scale) at T1 and T2. Using longitudinal data ( N = 6,346), we identified risk factors of poor mental health outcomes among sociodemographic characteristics, precariousness indicators, health-related data, information on the social environment, and media consumption, adjusting for baseline mental health status. Results We found lower prevalence rates of severe stress (21.7%), anxiety (22.1%), and depression (13·9%) one month after the quarantine compared to the quarantine period (24.8%, 27.5%, and 16.1%, respectively). The prevalence rate of suicidal thoughts increased from 11.4 to 13.2%. Regardless of the existence of symptoms during quarantine, four factors were systematically associated with poor mental health outcomes 1 month after the quarantine was lifted: female gender, a low feeling of integration before the quarantine period, a low quality of social ties during the quarantine, and a history of psychiatric follow-up. Conclusions The prevalence rates of severe stress, anxiety, and depression, although being lower than during the first lockdown, remained high after its lift. The prevalence rate of suicidal ideation increased. This stresses the need to consider the enduring psychological impact of the pandemic on students as a critical public health issue

Mental Health Symptoms of University Students 15 Months After the Onset of the COVID-19 Pandemic in France

International audienceImportance The Conséquences de la pandémie de COVID-19 sur la santé mentale des étudiants (COSAMe) survey was conducted among university students in France during the COVID-19 pandemic and found that although there was a slight decrease in anxiety, depression, and stress between the first lockdown (T1) and 1 month after it ended (T2), the prevalence of suicidal ideation had increased between these periods and 1 in 5 students had probable posttraumatic stress disorder (PTSD) at T2. These results emphasize the need to explore the long-term consequences of the COVID-19 pandemic. Objectives To measure the prevalence of mental health symptoms among university students in France 15 months after the first lockdown (T3) and to identify factors associated with outcomes. Design, Setting, and Participants This cross-sectional study reports data from the third measurement time of the repeated COSAMe survey, which took place from July 21 to August 31, 2021, through an online questionnaire sent to all French university students. Main Outcomes and Measures The prevalence of suicidal thoughts, PTSD (PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition] [PCL-5]), stress (Perceived Stress Scale), anxiety (State-Trait Anxiety Inventory), and depression (Beck Depression Inventory) at T3 were gender- and degree-standardized and compared with prevalence rates at T1 and T2. Multivariable logistic regression analyses identified risk factors. Results A total of 44 898 students completed the questionnaires. They were mainly women (31 728 [70.7%]), and the median (IQR) age was 19 (18-21) years. Standardized prevalence rates of stress, anxiety, depression, suicidal thoughts, and PTSD were 20.6% (95% CI, 20.2%-21.0%), 23.7% (95% CI, 23.3%-24.1%), 15.4% (95% CI, 15.1%-15.8%), 13.8% (95% CI, 13.5%-14.2%), and 29.8% (95% CI, 29.4%-30.2%), respectively. Compared with the decreased prevalence rates at T2, there was an increase at T3 for stress (2.5% increase), anxiety (13.9% increase), and depression (22.2% increase). The prevalence of suicidal ideation continued to increase from T1 (10.6%) to T3 (13.8%), and the prevalence of probable PTSD increased from 1 in 5 students to 1 in 3 students between T2 and T3. Female and nonbinary participants; participants without children and living in an urban area; and those with financial difficulties, a chronic condition, psychiatric history, COVID-19 history, social isolation, and low perceived quality of information received were at risk of all poor outcomes at T3 (eg, stress among women: adjusted OR, 2.18; 95% CI, 2.05-2.31; suicidal thoughts among nonbinary respondents: adjusted OR, 5.09; 95% CI, 4.32-5.99; anxiety among students with children: adjusted OR, 0.68; 95% CI, 0.56-0.81; depression among students living in a rural area: adjusted OR, 0.80; 95% CI, 0.75-0.85). Conclusions and Relevance These results suggest severe long-lasting consequences associated with the pandemic on the mental health of students. Prevention and care access should be a priority

A study on the relevance of generic word embeddings for sentence classification in hepatic surgery

International audienceWhile the fine-tuning process of extensive contextual language models often demands substantial computational capacity, utilizing generic pre-trained models in highly specialized domains can yield suboptimal results. This paper aims to explore an innovative approach to derive pertinent word embeddings tailored to a specific domain with limited computational resources (The introduced methodologies are tested within the domain of hepatic surgery, utilizing the French language.). This exploration takes place within a context where computational limitations prohibit the fine-tuning of large language models. A new embedding (referred to as FTW2V) that combines Word2Vec and FastText is introduced. This approach addresses the challenge of incorporating terms absent from Word2Vec’s vocabulary. Furthermore, a novel method is used to evaluate the significance of word embeddings within a specialized corpus. This evaluation involves comparing classification scores distributions of classifiers (Gradient Boosting) trained on word embeddings derived from benchmarked Natural Language Processing (NLP) models. As per this assessment technique, the FTW2V model, trained from scratch with limited computational resources, outperforms generic contextual models in terms of word embeddings quality. Additionally, a computationally efficient contextual model rooted in FTW2V is introduced. This modified model substitutes Gradient Boosting with a transformer and integrates Part Of Speech labels

Prevalence of and factors associated with post-traumatic stress disorder among French university students 1 month after the COVID-19 lockdown

International audienceAbstract The COVID-19 pandemic and quarantine measures have sparked debate regarding their traumatic nature. This cross-sectional study reports the prevalence rate of probable post-traumatic stress syndrome (PTSD) and associated factors among French university students. A total of 22,883 students completed the online questionnaire. The prevalence rate of probable PTSD, assessed using the PTSD Checklist for DSM-5, was 19.5% [19.0–20.0]. Female (1.32 [1.21–1.45]) or non-binary gender (1.76 [1.35–2.31]), exposure to a non-COVID-19-related traumatic event (3.37 [3.08–3.67]), having lived through quarantine alone (1.22 [1.09–1.37]), poor quality of social ties (2.38 [2.15–2.62]), loss of income (1.20 [1.09–1.31]), poor quality housing (1.90 [1.59–2.26]), low-quality of the information received (1.50 [1.35–1.66]) and a high level of exposure to COVID-19 (from 1.38 [1.24–1.54] to 10.82 [2.33–76.57] depending on the score) were associated with PTSD. Quarantine was considered potentially traumatic by 78.8% of the students with probable PTSD. These findings suggest the pandemic context and lockdown measures could have post-traumatic consequences, stimulating debate on the nosography of PTSD

Factors Associated With Mental Health Disorders Among University Students in France Confined During the COVID-19 Pandemic

International audienceAbstractImportance: The coronavirus disease 2019 (COVID-19) pandemic and quarantine measures have raised concerns regarding their psychological effects on populations. Among the general population, university students appear to be particularly susceptible to experiencing mental health problems.Objectives: To measure the prevalence of self-reported mental health symptoms, to identify associated factors, and to assess care seeking among university students who experienced the COVID-19 quarantine in France.Design, setting, and participants: This survey study collected data from April 17 to May 4, 2020, from 69 054 students living in France during the COVID-19 quarantine. All French universities were asked to send an email to their students asking them to complete an online questionnaire. The targeted population was approximately 1 600 000 students.Exposure: Living in France during the COVID-19 quarantine.Main outcomes and measures: The rates of self-reported suicidal thoughts, severe distress, stress, anxiety, and depression were assessed using the 22-item Impact of Events Scale-Revised, the 10-item Perceived Stress Scale, the 20-item State-Trait Anxiety Inventory (State subscale), and the 13-item Beck Depression Inventory, respectively. Covariates were sociodemographic characteristics, precariousness indicators (ie, loss of income or poor quality housing), health-related data, information on the social environment, and media consumption. Data pertaining to care seeking were also collected. Multivariable logistic regression analyses were performed to identify risk factors.Results: A total of 69 054 students completed the survey (response rate, 4.3%). The median (interquartile range) age was 20 (18-22) years. The sample was mainly composed of women (50 251 [72.8%]) and first-year students (32 424 [47.0%]). The prevalence of suicidal thoughts, severe distress, high level of perceived stress, severe depression, and high level of anxiety were 11.4% (7891 students), 22.4% (15 463 students), 24.7% (17 093 students), 16.1% (11 133 students), and 27.5% (18 970 students), respectively, with 29 564 students (42.8%) reporting at least 1 outcome, among whom 3675 (12.4%) reported seeing a health professional. Among risk factors identified, reporting at least 1 mental health outcome was associated with female gender (odds ratio [OR], 2.10; 95% CI, 2.02-2.19; P < .001) or nonbinary gender (OR, 3.57; 95% CI, 2.99-4.27; P < .001), precariousness (loss of income: OR, 1.28; 95% CI, 1.22-1.33; P < .001; low-quality housing: OR, 2.30; 95% CI, 2.06-2.57; P < .001), history of psychiatric follow-up (OR, 3.28; 95% CI, 3.09-3.48; P < .001), symptoms compatible with COVID-19 (OR, 1.55; 95% CI, 1.49-1.61; P < .001), social isolation (weak sense of integration: OR, 3.63; 95% CI, 3.35-3.92; P < .001; low quality of social relations: OR, 2.62; 95% CI, 2.49-2.75; P < .001), and low quality of the information received (OR, 1.56; 95% CI, 1.49-1.64; P < .001).Conclusions and relevance: The results of this survey study suggest a high prevalence of mental health issues among students who experienced quarantine, underlining the need to reinforce prevention, surveillance, and access to care

Facteurs associés à la résilience et à la santé mentale des enfants et des adolescents (9-16 ans) lors du confinement suite à la COVID-19 en France

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Facteurs associés à la résilience et à la santé mentale des enfants et des adolescents (9-16 ans) lors du confinement suite à la COVID-19 en France

International audienc

Facteurs associés à la résilience et à la santé mentale des enfants et des adolescents (9-16 ans) lors du confinement suite à la COVID-19 en France

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"Artificial intelligence": Which services, which applications, which results and which development today in clinical research? Which impact on the quality of care? Which recommendations?

International audienceArtificial intelligence (AI), beyond the concrete applications that have already become part of our daily lives, makes it possible to process numerous and heterogeneous data and knowledge, and to understand potentially complex and abstract rules in a manner human intelligence can but without human intervention. AI combines two properties, self-learning by the successive and repetitive processing of data as well as the capacity to adapt, that is to say the possibility for a scripted program to deal with multiple situations likely to vary over time. Roundtable experts confirmed the potential contribution and theoretical benefit of AI in clinical research and in improving the efficiency of patient care. Experts also measured, as is the case for any new process that people need to get accustomed to, its impact on practices and mindset. To maximize the benefits of AI, four critical points have been identified. The careful consideration of these four points conditions the technical integration and the appropriation by all actors of the life science spectrum: researchers, regulators, drug developers, care establishments, medical practitioners and, above all, patients and the civil society. 1st critical point: produce tangible demonstrations of the contributions of AI in clinical research by quantifying its benefits. 2nd critical point: build trust to foster dissemination and acceptability of AI in healthcare thanks to an adapted regulatory framework. 3rd critical point: ensure the availability of technical skills, which implies an investment in training, the attractiveness of the health sector relative to tech-heavy sectors and the development of ergonomic data collection tools for all health operators. 4th critical point: organize a system of governance for a distributed and secure model at the national level to aggregate the information and services existing at the local level. Thirty-seven concrete recommendations have been formulated which should pave the way for a widespread adoption of AI in clinical research. In this context, the French "Health data hub" initiative constitutes an ideal opportunity