Front Public Health

OBJECTIVE: To examine the relationship between young adults' labor force participation and depression in the context of the COVID-19 pandemic. DESIGN SETTING PARTICIPANTS: Data come from the nationally-representative EPICOV cohort study set up in France, and were collected in 2020 and 2021 (3 waves of online or telephone interviews: 02/05/2020-12/06/2020; 26/10/2020-14/12/2020; 24/06/2021-09/08/2021) among 2,217 participants aged 18-30 years. Participants with prior mental health disorder (n = 50) were excluded from the statistical analyses. RESULTS: Using Generalized Estimating Equation (GEE) models controlled for participants' socio-demographic and health characteristics and weighted to be nationally-representative, we found that compared to young adults who were employed, those who were studying or unemployed were significantly more likely to experience depression assessed using the PHQ-9 (multivariable ORs, respectively: OR: 1.29, 95% CI 1.05-1.60 and OR: 1.50, 1.13-1.99). Stratifying the analyses by age, we observed that unemployment was more strongly associated with depression among participants 25-30 years than among those who were 18-24 years (multivariable ORs, respectively, 1.78, 95% CI 1.17-2.71 and 1.41, 95% CI 0.96-2.09). Being out of the labor force was, to the contrary, more significantly associated with depression among participants 18-24 years (multivariable OR: 1.71, 95% CI 1.04-2.82, vs. 1.00, 95% CI 0.53-1.87 among participants 25-30 years). Stratifying the analyses by sex, we found no significant differences in the relationships between labor market characteristics and depression (compared to participants who were employed, multivariable ORs associated with being a student: men: 1.33, 95% CI 1.01-1.76; women: 1.19, 95% CI 0.85-1.67, multivariable ORs associated with being unemployed: men: 1.60, 95% CI 1.04-2.45; women: 1.47, 95% CI 1.01-2.15). CONCLUSIONS AND RELEVANCE: Our study shows that in addition to students, young adults who are unemployed also experience elevated levels of depression in the context of the COVID-19 pandemic. These two groups should be the focus of specific attention in terms of prevention and mental health treatment. Supporting employment could also be a propitious way of reducing the burden of the COVID-19 pandemic on the mental health of young adults.Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic: ORCHESTR

Examining the Theoretical Framework of Behavioral Activation for Major Depressive Disorder: Smartphone-Based Ecological Momentary Assessment Study.

BACKGROUND: Behavioral activation (BA), either as a stand-alone treatment or as part of cognitive behavioral therapy, has been shown to be effective for treating depression. The theoretical underpinnings of BA derive from Lewinsohn et al's theory of depression. The central premise of BA is that having patients engage in more pleasant activities leads to them experiencing more pleasure and elevates their mood, which, in turn, leads to further (behavioral) activation. However, there is a dearth of empirical evidence about the theoretical framework of BA. OBJECTIVE: This study aims to examine the assumed (temporal) associations of the 3 constructs in the theoretical framework of BA. METHODS: Data were collected as part of the "European Comparative Effectiveness Research on Internet-based Depression Treatment versus treatment-as-usual" trial among patients who were randomly assigned to receive blended cognitive behavioral therapy (bCBT). As part of bCBT, patients completed weekly assessments of their level of engagement in pleasant activities, the pleasure they experienced as a result of these activities, and their mood over the course of the treatment using a smartphone-based ecological momentary assessment (EMA) application. Longitudinal cross-lagged and cross-sectional associations of 240 patients were examined using random intercept cross-lagged panel models. RESULTS: The analyses did not reveal any statistically significant cross-lagged coefficients (all P>.05). Statistically significant cross-sectional positive associations between activities, pleasure, and mood levels were identified. Moreover, the levels of engagement in activities, pleasure, and mood slightly increased over the duration of the treatment. In addition, mood seemed to carry over, over time, while both levels of engagement in activities and pleasurable experiences did not. CONCLUSIONS: The results were partially in accordance with the theoretical framework of BA, insofar as the analyses revealed cross-sectional relationships between levels of engagement in activities, pleasurable experiences deriving from these activities, and enhanced mood. However, given that no statistically significant temporal relationships were revealed, no conclusions could be drawn about potential causality. A shorter measurement interval (eg, daily rather than weekly EMA reports) might be more attuned to detecting potential underlying temporal pathways. Future research should use an EMA methodology to further investigate temporal associations, based on theory and how treatments are presented to patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02542891, https://clinicaltrials.gov/ct2/show/NCT02542891; German Clinical Trials Register, DRKS00006866, https://tinyurl.com/ybja3xz7; Netherlands Trials Register, NTR4962, https://www.trialregister.nl/trial/4838; ClinicalTrials.Gov, NCT02389660, https://clinicaltrials.gov/ct2/show/NCT02389660; ClinicalTrials.gov, NCT02361684, https://clinicaltrials.gov/ct2/show/NCT02361684; ClinicalTrials.gov, NCT02449447, https://clinicaltrials.gov/ct2/show/NCT02449447; ClinicalTrials.gov, NCT02410616, https://clinicaltrials.gov/ct2/show/NCT02410616; ISRCTN registry, ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725

A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood.

BACKGROUND: Although major depressive disorder (MDD) is characterized by a pervasive negative mood, research indicates that the mood of depressed patients is rarely entirely stagnant. It is often dynamic, distinguished by highs and lows, and it is highly responsive to external and internal regulatory processes. Mood dynamics can be defined as a combination of mood variability (the magnitude of the mood changes) and emotional inertia (the speed of mood shifts). The purpose of this study is to explore various distinctive profiles in real-time monitored mood dynamics among MDD patients in routine mental healthcare. METHODS: Ecological momentary assessment (EMA) data were collected as part of the cross-European E-COMPARED trial, in which approximately half of the patients were randomly assigned to receive the blended Cognitive Behavioral Therapy (bCBT). In this study a subsample of the bCBT group was included (n = 287). As part of bCBT, patients were prompted to rate their current mood (on a 1-10 scale) using a smartphone-based EMA application. During the first week of treatment, the patients were prompted to rate their mood on three separate occasions during the day. Latent profile analyses were subsequently applied to identify distinct profiles based on average mood, mood variability, and emotional inertia across the monitoring period. RESULTS: Overall, four profiles were identified, which we labeled as: (1) "very negative and least variable mood" (n = 14) (2) "negative and moderate variable mood" (n = 204), (3) "positive and moderate variable mood" (n = 41), and (4) "negative and highest variable mood" (n = 28). The degree of emotional inertia was virtually identical across the profiles. CONCLUSIONS: The real-time monitoring conducted in the present study provides some preliminary indications of different patterns of both average mood and mood variability among MDD patients in treatment in mental health settings. Such varying patterns were not found for emotional inertia

Effect of Sleep Disturbance Symptoms on Treatment Outcome in Blended Cognitive Behavioral Therapy for Depression (E-COMPARED Study): Secondary Analysis.

BACKGROUND: Sleep disturbance symptoms are common in major depressive disorder (MDD) and have been found to hamper the treatment effect of conventional face-to-face psychological treatments such as cognitive behavioral therapy. To increase the dissemination of evidence-based treatment, blended cognitive behavioral therapy (bCBT) consisting of web-based and face-to-face treatment is on the rise for patients with MDD. To date, no study has examined whether sleep disturbance symptoms have an impact on bCBT treatment outcomes and whether it affects bCBT and treatment-as-usual (TAU) equally. OBJECTIVE: The objectives of this study are to investigate whether baseline sleep disturbance symptoms have an impact on treatment outcomes independent of treatment modality and whether sleep disturbance symptoms impact bCBT and TAU in routine care equally. METHODS: The study was based on data from the E-COMPARED (European Comparative Effectiveness Research on Blended Depression Treatment Versus Treatment-as-Usual) study, a 2-arm, multisite, parallel randomized controlled, noninferiority trial. A total of 943 outpatients with MDD were randomized to either bCBT (476/943, 50.5%) or TAU consisting of routine clinical MDD treatment (467/943, 49.5%). The primary outcome of this study was the change in depression symptom severity at the 12-month follow-up. The secondary outcomes were the change in depression symptom severity at the 3- and 6-month follow-up and MDD diagnoses at the 12-month follow-up, assessed using the Patient Health Questionnaire-9 and Mini-International Neuropsychiatric Interview, respectively. Mixed effects models were used to examine the association of sleep disturbance symptoms with treatment outcome and treatment modality over time. RESULTS: Of the 943 patients recruited for the study, 558 (59.2%) completed the 12-month follow-up assessment. In the total sample, baseline sleep disturbance symptoms did not significantly affect change in depressive symptom severity at the 12-month follow-up (β=.16, 95% CI -0.04 to 0.36). However, baseline sleep disturbance symptoms were negatively associated with treatment outcome for bCBT (β=.49, 95% CI 0.22-0.76) but not for TAU (β=-.23, 95% CI -0.50 to 0.05) at the 12-month follow-up, even when adjusting for baseline depression symptom severity. The same result was seen for the effect of sleep disturbance symptoms on the presence of depression measured with Mini-International Neuropsychiatric Interview at the 12-month follow-up. However, for both treatment formats, baseline sleep disturbance symptoms were not associated with depression symptom severity at either the 3- (β=.06, 95% CI -0.11 to 0.23) or 6-month (β=.09, 95% CI -0.10 to 0.28) follow-up. CONCLUSIONS: Baseline sleep disturbance symptoms may have a negative impact on long-term treatment outcomes in bCBT for MDD. This effect was not observed for TAU. These findings suggest that special attention to sleep disturbance symptoms might be warranted when MDD is treated with bCBT. Future studies should investigate the effect of implementing modules specifically targeting sleep disturbance symptoms in bCBT for MDD to improve long-term prognosis

Programmes de soins en psychiatrie : état des savoirs, regards sur les pratiques

International audienceLa loi du 5 juillet 2011 a introduit la possibilité de soins ambulatoires sans consentement dans le cadre de programmes de soins. Un premier bilan statistique réalisé par l’Irdes fait apparaître qu’en 2015 près de 37 000 personnes auraient été prises en charge selon cette modalité de soin, soit 40 % des personnes ayant reçu des soins sans consentement cette année-là

Les programmes de soins en psychiatrie : quelles évaluations pour quelles évolutions ?

International audienceLes modalités de soins sans consentement ambulatoires soulèvent des enjeux tant cliniques que juridiques, éthiques et sociaux. Quels bénéfices attend-on de ces dispositifs, pour la personne, sur le plan clinique, mais aussi sur le plan de sa trajectoire de soins ou de son insertion sociale ? S’y ajoute-t-il des attentes pour la société, en termes de réduction de conduites jugées « problématiques »

Using the Personalized Advantage Index for Individual Treatment Allocation to Blended Treatment or Treatment as Usual for Depression in Secondary Care

A variety of effective psychotherapies for depression are available, but patients who suffer from depression vary in their treatment response. Combining face‐to‐face therapies with internet‐ based elements in the sense of blended treatment is a new approach to treatment for depression. The goal of this study was to answer the following research questions: (1) What are the most important predictors determining optimal treatment allocation to treatment as usual or blended treatment? and (2) Would model‐determined treatment allocation using this predictive information and the personalized advantage index (PAI)‐approach result in better treatment outcomes? Bayesian model averaging (BMA) was applied to the data of a randomized controlled trial (RCT) comparing the efficacy of treatment as usual and blended treatment in depressive outpatients. Pre‐ treatment symptomatology and treatment expectancy predicted outcomes irrespective of treatment condition, whereas different prescriptive predictors were found. A PAI of 2.33 PHQ‐9 points was found, meaning that patients who would have received the treatment that is optimal for them would have had a post‐treatment PHQ‐9 score that is two points lower than if they had received the treatment that is suboptimal for them. For 29% of the sample, the PAI was five or greater, which means that a substantial difference between the two treatments was predicted. The use of the PAI approach for clinical practice must be further confirmed in prospective research; the current study supports the identification of specific interventions favorable for specific patients

Eur Child Adolesc Psychiatry

Children's screen time increased as a result of the COVID-19 pandemic. In the summer of 2021, we explored the association between high screen time over a period of one year since May 2020 and behavioural problems among children and adolescents. The data were derived from the French EpiCov cohort study, collected in spring 2020, autumn 2020, and spring 2021. Participants (N = 1089) responded to online or telephone interviews about one of their children aged 3 to 14 years. Screen time was categorized as high if the daily mean screen time exceeded recommendations at each collection time. The Strengths and Difficulties Questionnaire (SDQ) was completed by parents to identify internalizing (emotional or peer problems) and externalizing (conduct problems or hyperactivity/inattention) behaviours in their children. Among the 1,089 children, 561 (51.5%) were girls, the average age was 8.6 years (SD 3.7). Internalizing behaviours: High screen time was not associated with internalizing behaviours (OR [95% CI] 1.20 [0.90-1.59]) or emotional symptoms (1.00 [0.71-1.41]) while it was associated with peer problems (1.42 [1.04-1.95]). Externalizing behaviours: High screen time was associated with externalizing problems (1.63 [1.01-2.63]) and conduct problems (1.91 [1.15-3.22]) only among older children aged 11 to 14 years. No association with hyperactivity/inattention was found. In a French cohort, exploration of persistent high screen time in the first year of the pandemic and behaviour difficulties in Summer 2021 resulted in mixed findings according to behaviour's type and children's age. These mixed findings warrant further investigation into screen type and leisure/school screen use to enhance future pandemic responses appropriate for children.Epidémiologie environnementale du COVID-19 en Guyane française: combiner eDNA et biogéographie pour prédire les futurs pics épidémique

Suicidal ideation following self-reported COVID-19-like symptoms or serology-confirmed SARS-CoV-2 infection in France: A propensity score weighted analysis from a cohort study

International audienceBackground A higher: risk of suicidal ideation associated with self-report of : Coronavirus Disease 2019 (COVIDAU -19)-like: symptoms}or COVID COVID-19 19} infection has been observed }CoronavirusDisease in cross-sectional 2019}atfirstmenti studies, but evidence from longitudinal studies remains limited. The aims of this study were 2-fold: (1) to explore if self-reported COVID-19-like symptoms in 2020 were associated with suicidal ideation in 2021; (2) to explore if the association also existed when using a biological marker of Severe Acute Respiratory Syndrome Coronavirus 2 (SARSAU -CoV-2): infection in}SARS CoV 2020. Methods and findings AAU total: PLOSstyle of 52,050 participants from the ; French EpiCov cohort were included (median: followup time = 13.7 months). In terms of demographics, 53.84% were women, 60.92% were over 45 years old, 82.01% were born in mainland France from parents born in mainland France, and 59.38% completed high school. COVID-19-like symptoms were defined as participant report of a sudden loss of taste/smell or fever alongside cough, shortness of breath, or chest oppression, between February and November 2020. Symptoms were self-reported at baseline in May 2020 and at the first follow-up in Autumn 2020. Serology-confirmed SARS-CoV-2 infection in 2020 was derived from Spike protein ELISA test screening in dried-blood-spot samples. Samples were collected from October 2020 to March 2021, with 94.4% collected in 2020. Suicidal ideation since December 2020 was self-reported at the second follow-up in Summer 2021. Associations of self-reported COVID-19-like symptoms and serology-confirmed SARS-CoV-2 infection in 2020 with suicidal ideation in 2021 were ascertained using modified Poisson regression models, weighted by inverse probability weights computed from propensity scores. Among the 52,050 participants, 1.68% [1.54% to 1.82%] reported suicidal ideation in 2021, 9.57% [9.24% to 9.90%] had a serology-confirmed SARS-CoV-2 infection in 2020, and 13.23% [12.86% to 13.61%] reported COVID-19-like symptoms in 2020. Self-reported COVID-19-like symptoms in 2020 were associated with higher risks of later suicidal ideation in 2021 (Relative Riskipw [95AU % CI]: Pleasenotethatallinstancesof = 1.43 [1.20 to 1.69]), while}CI serol- 95%}hav ogy-confirmed SARS-CoV-2 infection in 2020 was not (RRipw = 0.89 [0.70 to 1.13]). Limitations of this study include the use of a single question to assess suicidal ideation, the use of self-reported history of mental health disorders, and limited generalizability due to attrition bias. Conclusions Self-reported COVID-19-like symptoms in 2020, but not serology-confirmed SARS-CoV-2 infection in 2020, were associated with a higher risk of subsequent suicidal ideation in 2021. The exact role of SARS-CoV-2 infection with respect to suicide risk has yet to be clarified. Including mental health resources in COVID-19-related settings could encourage symptomatic individuals to care for their mental health and limit suicidal ideation to emerge or worsen