Evidence for a competitive relationship between executive functions and statistical learning.

The ability of the brain to extract patterns from the environment and predict future events, known as statistical learning, has been proposed to interact in a competitive manner with prefrontal lobe-related networks and their characteristic cognitive or executive functions. However, it remains unclear whether these cognitive functions also possess a competitive relationship with implicit statistical learning across individuals and at the level of latent executive function components. In order to address this currently unknown aspect, we investigated, in two independent experiments (NStudy1 = 186, NStudy2 = 157), the relationship between implicit statistical learning, measured by the Alternating Serial Reaction Time task, and executive functions, measured by multiple neuropsychological tests. In both studies, a modest, but consistent negative correlation between implicit statistical learning and most executive function measures was observed. Factor analysis further revealed that a factor representing verbal fluency and complex working memory seemed to drive these negative correlations. Thus, the antagonistic relationship between implicit statistical learning and executive functions might specifically be mediated by the updating component of executive functions or/and long-term memory access.

Differential associations between insight and quality-of-life dimensions among individuals with schizophrenia.

PURPOSE/OBJECTIVE: In schizophrenia, insight, the recognition that one has a medical illness that requires treatment, has long been related to deteriorated quality of life. Yet, insight and quality of life are broad constructs that encompass several dimensions. Here, we investigated differential associations between insight and quality-of-life dimensions using a psychological network approach. RESEARCH METHOD/DESIGN: We extracted data from the French network of rehabilitation centers REHABase (January 2016 to December 2022, N = 1,056). Our psychological network analysis modeled insight and quality of life as a network of interacting dimensions: three insight dimensions (awareness of illness, reattribution of symptoms to the disease, and recognition of treatment need) and eight quality-of-life dimensions (autonomy, physical and psychosocial well-being, relationships with family, friends and romantic partners, resilience, and self-esteem). RESULTS: Insight was negatively associated with quality of life. Our psychological network analysis revealed a strong negative association between awareness of disease and self-esteem. Both dimensions were the strongest nodes in the overall network. Our network analysis also revealed a significant but positive connection between recognition of treatment needs and resilience. CONCLUSION/IMPLICATIONS: While insight and quality of life are overall negatively associated, we found both negative and positive connections between insight and quality-of-life dimensions. The negative relationship between insight and quality of life may reflect the deleterious effects of diagnostic labeling on a patient's self-esteem. Yet, acknowledgment of treatment needs may have positive effects on quality of life and may promote recovery, perhaps because it emphasizes the need for support rather than labels and abnormalities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Contribution of socio-demographic and clinical characteristics to predict initial referrals to psychosocial interventions in patients with serious mental illness.

AIMS: Psychosocial rehabilitation (PSR) is at the core of psychiatric recovery. There is a paucity of evidence regarding how the needs and characteristics of patients guide clinical decisions to refer to PSR interventions. Here, we used explainable machine learning methods to determine how socio-demographic and clinical characteristics contribute to initial referrals to PSR interventions in patients with serious mental illness. METHODS: Data were extracted from the French network of rehabilitation centres, REHABase, collected between years 2016 and 2022 and analysed between February and September 2022. Participants presented with serious mental illnesses, including schizophrenia spectrum disorders, bipolar disorders, autism spectrum disorders, depressive disorders, anxiety disorders and personality disorders. Information from 37 socio-demographic and clinical variables was extracted at baseline and used as potential predictors. Several machine learning models were tested to predict initial referrals to four PSR interventions: cognitive behavioural therapy (CBT), cognitive remediation (CR), psychoeducation (PE) and vocational training (VT). Explanatory power of predictors was determined using the artificial intelligence-based SHAP (SHapley Additive exPlanations) method from the best performing algorithm. RESULTS: Data from a total of 1146 patients were included (mean age, 33.2 years [range, 16-72 years]; 366 [39.2%] women). A random forest algorithm demonstrated the best predictive performance, with a moderate or average predictive accuracy [micro-averaged area under the receiver operating curve from 'external' cross-validation: 0.672]. SHAP dependence plots demonstrated insightful associations between socio-demographic and clinical predictors and referrals to PSR programmes. For instance, patients with psychotic disorders were more likely to be referred to PE and CR, while those with non-psychotic disorders were more likely to be referred to CBT and VT. Likewise, patients with social dysfunctions and lack of educational attainment were more likely to be referred to CR and VT, while those with better functioning and education were more likely to be referred to CBT and PE. CONCLUSIONS: A combination of socio-demographic and clinical features was not sufficient to accurately predict initial referrals to four PSR programmes among a French network of rehabilitation centres. Referrals to PSR interventions may also involve service- and clinician-level factors. Considering socio-demographic and clinical predictors revealed disparities in referrals with respect to diagnoses, current clinical and psychological issues, functioning and education.

Mechanistic account of the left auditory cortex for tone-matching in schizophrenia: A pilot transcranial random noise stimulation (tRNS) sham-controlled study.

OBJECTIVE: Deficits in the ability to match tones following brief delay and their contribution to higher-order cognitive alterations have been repeatedly documented in schizophrenia. The aim was to explore if left fronto-temporal high-frequency transcranial random noise stimulation (hf-tRNS), with electrodes placed over brain regions involved in tone-matching would significantly modulate performances in participants with schizophrenia. METHODS: In a randomized, double-blind sham-controlled study, 10 participants with schizophrenia were allocated to receive ten sessions of either active or sham hf-tRNS. The anode was placed over the left prefrontal cortex and the cathode over the left temporoparietal junction. A tone-matching task was administered before and after the hf-tRNS. RESULTS: We calculated the changes in tone-matching performance before and after hf-tRNS session in each group. A significant between-group difference was observed for the difficult tone-matching conditions (W= 14.500, p = 0.032), with tone-matching improvement in the sham group and no improvement in the active group. DISCUSSION: hf-tRNS could disrupt the test-retest learning effect in the tone-matching task in individuals with schizophrenia. It is likely that this disruption resulted from cathodal-induced inhibition of the functional coupling between auditory cortical areas that correlates with tone-matching performance in patients. CONCLUSION: The findings contribute to our understanding of hf-tRNS effects on early auditory processing in schizophrenia.

Functioning, clinical severity, education and sex moderate the inverse relationship between insight and quality of life in patients with schizophrenia.

BACKGROUND: In schizophrenia, insight, the recognition that one has a medical illness that requires treatment, has long been related to deteriorated quality of life, a phenomenon that has been described as the "insight paradox". Here, we aimed to determine whether certain socio-demographic and clinical characteristics strengthen or weaken this negative relationship. METHODS: We used data from the French network of rehabilitation centers REHABase (N = 769). We explored mean differences in quality-of-life scores between patients with good insight vs. poor insight. We also explored modifying effects of socio-demographic and clinical characteristics (sex, education, age, functioning, clinical severity, duration of illness). RESULTS: Patients with good insight had a decreased quality-of-life total score. Similar effects were found for the following sub-dimensions of quality of life: autonomy, physical and psychological well-being, and self-esteem. The negative effect of insight on quality of life was attenuated for people who had >12 years of education and for people with a higher level of functioning. By contrast, the negative effect of insight on quality of life was accentuated in people with greater clinical severity. Functioning and clinical severity showed similar modifying effects for other quality-of-life dimensions: autonomy, physical and psychological well-being, and self-esteem. Finally, males demonstrated an increased negative association between insight and self-esteem. CONCLUSIONS: The relationship between insight and quality of life is moderated by socio-demographic and clinical circumstances. Future inquiries may utilize our findings by integrating socio-demographic and clinical factors in treatment programs designs to conjointly improve insight and quality of life.

Predictors of mental well-being over the first lockdown period due to the COVID-19 pandemic in France. A repeated cross-sectional study.

Introduction: Numerous studies have investigated the positive and negative effects of potential predictors of well-being during lockdowns due to COVID-19. Yet, little is known on whether these effects significantly changed with time spent in lockdown. In the current study, we described the association of mental well-being with a large number of background characteristics (e.g., socio-demographic or health-related factors), COVID-related factors, and coping strategies, over the duration of the first lockdown due to COVID-19 in France. Methods: A nationwide online survey was conducted over 7 of the 8 weeks of the 1st lockdown in France, i.e., from 25 March 2020 to 10 May 2020. The level of mental well-being was reported using the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). We also measured various background characteristics (e.g., age, sex, education, health issues), COVID-related factors (e.g., health and economic risks, agreement with lockdown), and coping strategies. Our analytical strategy enabled us to disentangle effects aggregated over the study period from those that linearly vary with time spent in lockdown. Results: Our final dataset included 18,957 participants. The level of mental well-being dropped gradually from the third to the eighth week of lockdown [49.7 (sd 7.9) to 45.5 (sd 10.6)]. Time in lockdown was associated with a decrease in well-being (for each additional 10 days of lockdown: B = -0.30, 95%CI: -0.62, -0.15). Factors that showed significantly negative and positive effects on well-being as time in lockdown progressed were (for each additional 10 days of lockdown): having current psychiatric problems (B = -0.37; 95%CI: -0.63, -0.04), worries about having access to personal protective equipment (B = -0.09; 95%CI: -0.18, -0.01), coping by having positive beliefs about the future of the pandemics (B = 0.29; 95%CI: 0.04, 0.62), being supported by neighbors (B = 0.24; 95%CI: 0.04, 0.44), and being involved in collective actions (B = 0.23; 95%CI: 0.04, 0.46). Discussion: Participants from our sample saw a drop in their mental well-being throughout the first period of COVID-19 lockdown. Policymakers should be mindful of factors contributing to greater deterioration of mental well-being over time, such as having current psychiatric issues. Promoting collective actions and local support from neighbors may alleviate the deterioration of mental well-being over time.

The neural signature of reality-monitoring: A meta-analysis of functional neuroimaging studies.

Distinguishing imagination and thoughts from information we perceived from the environment, a process called reality-monitoring, is important in everyday situations. Although reality monitoring seems to overlap with the concept of self-monitoring, which allows one to distinguish self-generated actions or thoughts from those generated by others, the two concepts remain largely separate cognitive domains and their common brain substrates have received little attention. We investigated the brain regions involved in these two cognitive processes and explored the common brain regions they share. To do this, we conducted two separate coordinate-based meta-analyses of functional magnetic resonance imaging studies assessing the brain regions involved in reality- and self-monitoring. Few brain regions survived threshold-free cluster enhancement family-wise multiple comparison correction (p < .05), likely owing to the small number of studies identified. Using uncorrected statistical thresholds recommended by Signed Differential Mapping with Permutation of Subject Images, the meta-analysis of reality-monitoring studies (k = 9 studies including 172 healthy subjects) revealed clusters in the lobule VI of the cerebellum, the right anterior medial prefrontal cortex and anterior thalamic projections. The meta-analysis of self-monitoring studies (k = 12 studies including 192 healthy subjects) highlighted the involvement of a set of brain regions including the lobule VI of the left cerebellum and fronto-temporo-parietal regions. We showed with a conjunction analysis that the lobule VI of the cerebellum was consistently engaged in both reality- and self-monitoring. The current findings offer new insights into the common brain regions underlying reality-monitoring and self-monitoring, and suggest that the neural signature of the self that may occur during self-production should persist in memories.

Basic auditory processing and its relationship with symptoms in patients with schizophrenia: A systematic review.

Processing of basic auditory features, one of the earliest stages of auditory perception, has been the focus of considerable investigations in schizophrenia. Although numerous studies have shown abnormalities in pitch perception in schizophrenia, other basic auditory features such as intensity, duration, and sound localization have been less explored. Additionally, the relationship between basic auditory features and symptom severity shows inconsistent results, preventing concrete conclusions. Our aim was to present a comprehensive overview of basic auditory processing in schizophrenia and its relationship with symptoms. We conducted a systematic review according to the PRISMA guidelines. PubMed, Embase, and PsycINFO databases were searched for studies exploring auditory perception in schizophrenia compared to controls, with at least one behavioral task investigating basic auditory processing using pure tones. Forty-one studies were included. The majority investigated pitch processing while the others investigated intensity, duration and sound localization. The results revealed that patients have a significant deficit in the processing of all basic auditory features. Although the search for a relationship with symptoms was limited, auditory hallucinations experience appears to have an impact on basic auditory processing. Further research may examine correlations with clinical symptoms to explore the performance of patient subgroups and possibly implement remediation strategies.

Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning.

Probabilistic sequence learning supports the development of skills and enables predictive processing. It remains contentious whether visuomotor sequence learning is driven by the representation of the visual sequence (perceptual coding) or by the representation of the response sequence (motor coding). Neurotypical adults performed a visuomotor sequence learning task. Learning occurred incidentally as it was evidenced by faster responses to high-probability than to low-probability targets. To uncover the neurophysiology of the learning process, we conducted both univariate analyses and multivariate pattern analyses (MVPAs) on the temporally decomposed EEG signal. Univariate analyses showed that sequence learning modulated the amplitudes of the motor code of the decomposed signal but not in the perceptual and perceptual-motor signals. However, MVPA revealed that all 3 codes of the decomposed EEG contribute to the neurophysiological representation of the learnt probabilities. Source localization revealed the involvement of a wider network of frontal and parietal activations that were distinctive across coding levels. These findings suggest that perceptual and motor coding both contribute to the learning of sequential regularities rather than to a neither-nor distinction. Moreover, modality-specific encoding worked in concert with modality-independent representations, which suggests that probabilistic sequence learning is nonunitary and encompasses a set of encoding principles.

Efficacy and auditory biomarker analysis of fronto-temporal transcranial direct current stimulation (tDCS) in targeting cognitive impairment associated with recent-onset schizophrenia: study protocol for a multicenter randomized double-blind sham-controlled trial.

BACKGROUND: In parallel to the traditional symptomatology, deficits in cognition (memory, attention, reasoning, social functioning) contribute significantly to disability and suffering in individuals with schizophrenia. Cognitive deficits have been closely linked to alterations in early auditory processes (EAP) that occur in auditory cortical areas. Preliminary evidence indicates that cognitive deficits in schizophrenia can be improved with a reliable and safe non-invasive brain stimulation technique called tDCS (transcranial direct current stimulation). However, a significant proportion of patients derive no cognitive benefits after tDCS treatment. Furthermore, the neurobiological mechanisms of cognitive changes after tDCS have been poorly explored in trials and are thus still unclear. METHOD: The study is designed as a randomized, double-blind, 2-arm parallel-group, sham-controlled, multicenter trial. Sixty participants with recent-onset schizophrenia and cognitive impairment will be randomly allocated to receive either active (n=30) or sham (n=30) tDCS (20-min, 2-mA, 10 sessions during 5 consecutive weekdays). The anode will be placed over the left dorsolateral prefrontal cortex and the cathode over the left auditory cortex. Cognition, tolerance, symptoms, general outcome and EAP (measured with EEG and multimodal MRI) will be assessed prior to tDCS (baseline), after the 10 sessions, and at 1- and 3-month follow-up. The primary outcome will be the number of responders, defined as participants demonstrating a cognitive improvement ≥Z=0.5 from baseline on the MATRICS Consensus Cognitive Battery total score at 1-month follow-up. Additionally, we will measure how differences in EAP modulate individual cognitive benefits from active tDCS and whether there are changes in EAP measures in responders after active tDCS. DISCUSSION: Besides proposing a new fronto-temporal tDCS protocol by targeting the auditory cortical areas, we aim to conduct a randomized controlled trial (RCT) with follow-up assessments up to 3 months. In addition, this study will allow identifying and assessing the value of a wide range of neurobiological EAP measures for predicting and explaining cognitive deficit improvement after tDCS. The results of this trial will constitute a step toward the use of tDCS as a therapeutic tool for the treatment of cognitive impairment in recent-onset schizophrenia. TRIAL REGISTRATION: ClinicalTrials.gov NCT05440955. Prospectively registered on July 1st, 2022.

Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach.

BACKGROUND: There is a lack of knowledge regarding the actionable key predictive factors of homelessness in psychiatric populations. Therefore, we used a machine learning model to explore the REHABase database (for rehabilitation database-n = 3416), which is a cohort of users referred to French psychosocial rehabilitation centers in France. METHODS: First, we analyzed whether the different risk factors previously associated with homelessness in mental health were also significant risk factors in the REHABase. In the second step, we used unbiased classification and regression trees to determine the key predictors of homelessness. Post hoc analyses were performed to examine the importance of the predictors and to explore the impact of cognitive factors among the participants. RESULTS:  First, risk factors that were previously found to be associated with homelessness were also significant risk factors in the REHABase. Among all the variables studied with a machine learning approach, the most robust variable in terms of predictive value was the nature of the psychotropic medication (sex/sex relative mean predictor importance: 22.8, σ = 3.4). Post hoc analyses revealed that first-generation antipsychotics (15.61%; p < 0.05 FDR corrected), loxapine (16.57%; p < 0.05 FWER corrected) and hypnotics (17.56%; p < 0.05 FWER corrected) were significantly associated with homelessness. Antidepressant medication was associated with a protective effect against housing deprivation (9.21%; p < 0.05 FWER corrected). CONCLUSIONS: Psychotropic medication was found to be an important predictor of homelessness in our REHABase cohort, particularly loxapine and hypnotics. On the other hand, the putative protective effect of antidepressants confirms the need for systematic screening of depression and anxiety in the homeless population.

Pregnancy, Mental Well-Being and Lockdown: A Nationwide Online Survey in France.

The objective of this study was to compare the mental well-being of French women who were and were not pregnant during the first COVID-19 pandemic lockdown. We performed a nationwide online quantitative survey including all women between 18 and 45 years of age during the second and third weeks of global lockdown (25 March-7 April 2020). The main outcome measure was mental well-being measured by the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). This study analysed 275 responses from pregnant women and compared them with those from a propensity score-matched sample of 825 non-pregnant women. In this French sample, the median WEMWBS score was 49.0 and did not differ by pregnancy status. Women living in urban areas reported better well-being, while those with sleep disorders or who spent more than an hour a day watching the news reported poorer well-being. During the first lockdown in France, women had relatively low mental well-being scores, with no significant difference between pregnant and non-pregnant women. More than ever, health-care workers need to find a way to maintain their support for women's well-being. Minor daily annoyances of pregnancy, such as insomnia, should not be trivialised because they are a potential sign of poor well-being.

Mental well-being in young people with psychiatric disorders during the early phase of COVID-19 lockdown.

BACKGROUND: Mental health and well-being were seriously impacted by the COVID-19 lockdown especially among young people and people with psychiatric disorders. This study aimed to identify factors associated with well-being in young people with psychiatric disorders, during early phase of COVID-19 lockdown in France. METHODS: A national cross-sectional online study started on the 8th day of COVID-19 lockdown in France (during March 25-30, 2020). We included young people aged from 16 to 29 who responded to the questionnaire, living and being confined in France, with past or current psychiatric treatment. The questionnaire was accessible online and explored demographics and clinical factors, well-being, stress, situation during lockdown. Well-being was measured by the Warwick-Edinburg Mental Well-Being Scale (WEMWBS). Simple and multiple linear regression analyses were carried out. RESULTS: 439 individuals were included with 262 (59.7%) previously treated and 177 (40.3%) currently treated. WEMWBS total score were 42.48 (9.05). Feeling of useful was the most affected dimension. Well-being was positively correlated with: currently working on site, physical activity, abilities to cope with difficulties, family and social supports (p<0.05). It was negatively correlated with: elevated stress level, anxious ruminations, dissatisfaction with information, difficulties to sleep or reorganize daily life, feeling supported by medicines (p<0.05). No individual factor was correlated with well-being. The stepwise linear multivariate model had simple R2 coefficient of determination of 0.535. CONCLUSION: In the specific population of young people with psychiatric disorders, factors associated with well-being at early stage of lockdown were mainly psychosocial and related to brutal disorganisation of daily life.

The central role of self-esteem in the quality of life of patients with mental disorders.

In psychiatry, recent years have seen a change of focus from a clinician- to a patient-centered perspective that emphasizes quality of life as a treatment target. As a complex construct, quality of life is composed of multiple dimensions that interact with one-another (e.g. physical and psychological well-being, relationships, autonomy, self-esteem). Here, we used data from the REHABase cohort, which includes N = 2180 patients from 15 psychosocial rehabilitation centers in France, to explore networks of quality-of-life dimensions among six psychiatric disorders: schizophrenia, neurodevelopmental, bipolar, depressive, anxiety, and personality disorders. Stronger connections (edges) involved the Self-Esteem dimension, such as Self-Esteem-Physical Well-Being, Self-Esteem-Autonomy, Self-Esteem-Psychological Well-Being, and Self-Esteem-Resilience. Self-esteem was also consistently retrieved as the most central node (the dimension with the most connections within each network). Between-group tests did not reveal any differences regarding network structure, overall connectivity, edge-weights, and nodes' centrality. Despite presenting with different symptom profiles, various psychiatric disorders may demonstrate similar inter-relationships among quality-of-life dimensions. In particular, self-esteem may have a crucial inter-connecting role in patients' quality of life. Our findings could support treatment programmes that specifically target self-esteem to improve patients' quality of life in a cost-effective way.

Ten Sessions of 30 Min tDCS over 5 Days to Achieve Remission in Depression: A Randomized Pilot Study.

Although transcranial Direct Current stimulation (tDCS) shows promise in the treatment of major depressive episodes, the optimal parameters and population to target remain unclear. We investigated the clinical interest of a 10 session tDCS regimen in patients with mild to severe treatment-resistant depression, in a pilot double-blind, randomized sham-controlled trial. tDCS was delivered over 5 consecutive days (two 30 min sessions per day separated by at least 2 h, 2 mA). The anode and cathode were placed over the left and the right dorsolateral prefrontal cortex, respectively. One month after tDCS, we observed significantly fewer patients who achieved remission (MADRS10 < 10) in the sham group (0 out of 18 patients) than in the active group (5 out of 21 patients; p = 0.05). However, no significant difference was observed between the groups regarding the mean scores of severity changes throughout the study period. Bifrontal add-on tDCS delivered twice per day over 5 days, in combination with antidepressant medication, can be a safe and suitable approach to achieve remission in patients with mild to severe treatment-resistant major depressive disorder. However, in regards to the pilot nature and limitations of the present study, further studies are needed before any frank conclusions can be made regarding the use of tDCS with the proposed parameters in clinical settings.

Efficacy and safety of topiramate for reducing impulsivity: A transdiagnostic systematic review and meta-analysis of a common clinical use.

Impulsivity is an important transdiagnostic feature of many psychiatric disorders, as well as a marker of poorer outcome. Topiramate is broadly used for reducing impulsivity in various neuropsychiatric disorders, but no systematic review or meta-analysis has ever explored whether evidence supports this clinical use. We conducted a systematic review and meta-analysis of the literature, using PubMed, PsycInfo and Cochrane databases. We included all studies assessing the efficacy of topiramate in adults with high levels of impulsivity, based on either psychometric or neuropsychological measures. Seven articles were included, involving 578 participants. Important heterogeneity in designs and quality features was observed. Topiramate lowered impulsivity levels in two of the studies that used the Barratt Impulsiveness Scale (BIS) (401 participants) and in one of the studies that used neuropsychological measures (63 participants). Four other studies found no effect of topiramate on impulsivity. A larger reduction in the BIS-11 overall score, with a mean difference of 2.57 (95% confidence interval -4.12 to -1.02), was found in the topiramate group than the placebo group using a random effects model. However, one study accounted for the major part (85.5%) of it, and most included studies presented a high risk of bias. The use of a self-assessment scale induced an additional risk of self-report bias. No clear-cut evidence was found for a transdiagnostic effectiveness of topiramate in reducing impulsivity levels. However, encouraging results were found in some specific disorders.

Neuroanatomical correlates of reality monitoring in patients with schizophrenia and auditory hallucinations.

BACKGROUND: Reality-monitoring process enables to discriminate memories of internally generated information from memories of externally derived information. Studies have reported impaired reality-monitoring abilities in schizophrenia patients with auditory hallucinations (AHs), specifically with an exacerbated externalization bias, as well as alterations in neural activity within frontotemporoparietal areas. In healthy subjects, impaired reality-monitoring abilities have been associated with reduction of the paracingulate sulcus (PCS). The current study aimed to identify neuroanatomical correlates of reality monitoring in patients with schizophrenia. METHODS: Thirty-five patients with schizophrenia and AHs underwent a reality-monitoring task and a 3D anatomical MRI scan at 1.5 T. PCS lengths were measured separately for each hemisphere, and whole-brain voxel-based morphometry analyses were performed using the Computational Anatomy Toolbox (version 12.6) to evaluate the gray-matter volume (GMV). Partial correlation analyses were used to investigate the relationship between reality-monitoring and neuroanatomical outcomes (PCS length and GMV), with age and intracranial volume as covariates. RESULTS: The right PCS length was positively correlated with reality-monitoring accuracy (Spearman's ρ = 0.431, p = 0.012) and negatively with the externalization bias (Spearman's ρ = -0.379, p = 0.029). Reality-monitoring accuracy was positively correlated with GMV in the right angular gyrus, whereas externalization bias was negatively correlated with GMV in the left supramarginal gyrus/superior temporal gyrus, in the right lingual gyrus and in the bilateral inferior temporal/fusiform gyri (voxel-level p < 0.001 and cluster-level p < 0.05, FDR-corrected). CONCLUSIONS: Reduced reality-monitoring abilities were significantly associated with shorter right PCS and reduced GMV in temporal and parietal regions of the reality-monitoring network in schizophrenia patients with AHs.

PLAN-e-PSY, a mobile application to improve case management and patient's functioning in first episode psychosis: protocol for an open-label, multicentre, superiority, randomised controlled trial.

INTRODUCTION: The prognosis of first episode psychosis (FEP), which is a severe disorder, can be notably impaired by patients' disengagement from healthcare providers. Coordinated specialty care with case management is now considered as the gold standard in this population, but there are still challenges for engagement with subsequent functional impairments. Youth-friendly and patient-centred clinical approaches are sought to improve engagement in patients with FEP. Mobile applications are widely used by young people, including patients with FEP, and can increase the youth friendliness of clinical tools. We hypothesise that a co-designed mobile application used during case management can improve functioning in patients with FEP as compared with usual case management practices. METHODS AND ANALYSIS: A mobile case management application for planning and monitoring individualised care objectives will be co-designed with patients, caregivers and health professionals in a recovery-oriented approach. The application will be compared with usual case management practices in a multicentre, two-arm and parallel groups clinical trial. Patients will be recruited by specialised FEP teams. Impact on functioning will be assessed using the Personal and Social Performance Scale; the variation between baseline and 12 months in each group (control and active) will be the primary outcome. ETHICS AND DISSEMINATION: This study has been approved by the Inserm Institutional Review Board IRB00003888 (Comité d'évaluation éthique de l'INSERM, reference number 20-647). The results of the study will be published in a peer-reviewed journal and presented at national and international conferences. We will also communicate the results to patients and family representatives' associations. An optimised version of the application will be then disseminated through the French FEP network (Transition Network). TRIAL REGISTRATION NUMBER: ClinicalTrials.gov: NCT04657380.

Correction: Global Changes and Factors of Increase in Caloric/Salty Food Intake, Screen Use, and Substance Use During the Early COVID-19 Containment Phase in the General Population in France: Survey Study.

[This corrects the article DOI: 10.2196/19630.].

Cognitive insight in individuals with an at-risk mental state for psychosis: A meta-analysis.

AIM: To compare cognitive insight abilities measured with the Beck Cognitive Insight Scale (BCIS) between individuals with an at-risk mental state (ARMS) and healthy controls. METHOD: Review and meta-analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RESULTS: A search for articles investigating cognitive insight in ARMS in the MEDLINE and ScienceDirect databases revealed five studies including 303 ARMS and 376 controls. Regarding BCIS subscales, ARMS individuals displayed significant higher scores for self-certainty than controls with a small-to-moderate effect size (ESg = 0.45 [0.23;0.67], P < .005), whereas no significant difference was observed for self-reflectiveness (ESg = -0.56 [-0.18;1.29], P = .14). No significant differences were observed between ARMS and controls for overall cognitive insight abilities as indexed by the BCIS composite score (ESg = -0.24 [-0.43;0.91], P = .45). CONCLUSIONS: Self-certainty abnormalities seem to predate the expression of full-blown psychotic episode and to be higher in ARMS than in healthy controls. By contrast, ARMS did not display abnormal self-reflectiveness and overall cognitive insight abilities.