Christophe Lançon

Background/Objectives: Severe mental illnesses such as schizophrenia, major depressive disorder, and bipolar disorder are often accompanied by metabolic comorbidities. While the role of vitamins in physical health is well-established, their involvement in psychiatric disorders has garnered increasing attention in recent years. Methods: We conducted a cross-sectional analysis of 1003 patients diagnosed with severe mental illnesses. Vitamin D, B9, and B12 serum levels were measured, and deficiencies were defined using established clinical cutoffs. Multivariate regression analyses were performed to identify associations between vitamin deficiencies and clinical outcomes. Results: Our findings revealed that vitamin deficiencies were prevalent across all diagnostic groups, with particularly high rates in patients with schizophrenia and major depressive disorder. Vitamin D deficiency was significantly associated with worse psychiatric outcomes, including increased depressive symptoms (adjusted OR = 1.89, p = 0.018), lower Global Assessment of Functioning scores (adjusted OR = −0.18, p < 0.001), and higher rates of metabolic syndrome (adjusted OR = 1.97, p = 0.007). Folate and B12 deficiencies were also linked to greater psychiatric symptom severity and metabolic disturbances, including increased risks of obesity and dyslipidemia. Conclusions: Our study highlights the critical role of vitamins deficiencies in both psychiatric and metabolic health of patients with severe mental illnesses. These findings underscore the importance of routine screening and correction of these deficiencies as part of comprehensive care in psychiatric populations. The integration of nutritional interventions may offer a novel and holistic approach to improving both mental and physical health outcomes.

Background/Objectives: Modern therapeutic strategies incorporating virtual reality (VR) have emerged as potential treatments for generalized anxiety disorder (GAD), a prevalent and debilitating condition that is challenging to cure. This study aimed to evaluate the efficacy of VR combined with relaxation techniques in patients with GAD by comparing VR-based relaxation with standard mental imagery (MI) relaxation. Methods: Fifty-eight patients with GAD participated in a randomized comparative trial. Specific virtual environments were created using an inexpensive game engine/level editor (GLE). Psychometric scales and physiological instruments were employed to assess the effects of relaxation therapy on anxiety, depression, quality of life, presence within virtual environments and cybersickness. Results: Both the VR and MI groups demonstrated statistically significant improvements in anxiety, worry and mental quality of life scores. However, no significant differences were observed between the two groups in pre–post comparisons of psychometric scores. The VR group exhibited a noticeably higher protocol completion rate and a significant increase in heart rate variability during the therapy. The level of presence in the VR group was satisfactory and significantly correlated with physiological improvements and anxiety reduction, while cybersickness remained low. Participants’ preferences for specific virtual environments for relaxation are also discussed. Conclusions: These findings suggest that teaching and practicing relaxation in VR holds therapeutic potential for the treatment of GAD. Further research leveraging advanced VR sensory equipment and artificial intelligence agents is warranted to enhance therapeutic outcomes and explore additional applications.

While there is abundant literature on the benefits of Mindfulness-Based Interventions (MBI), data about factors associated with their Efficiency are scarce. Our study attempts to determine the moderators of efficacy and adherence in Mindfulness-Based Cognitive Therapy (MBCT) with a machine learning analysis. Seventy-six psychiatric outpatients at “university hospital mental health service” had a prescription for MBCT from their referring psychiatrist. They suffer from various psychiatric illnesses with depressive symptoms. They completed a battery of clinical, mindfulness, and psychological functioning self-report questionnaires before and after the MBCT intervention of 8 sessions. Changes (after minus before) in scores were used for efficacy. Scores before MBCT were used to study the adherent profile (8 sessions of MBCT) versus non-adherent patients (stopping MBCT before the eight sessions). For efficacy and adherence profiles, machine learning analysis based on the support vector machine (SMV) method was applied to complement classical statistical analyses. Results: For efficacy factors, the SVM analysis finds a two-dimensional profile of patients. The patients for whom MBCT is most effective are patients with a high Beck score (>25) and high trait mindfulness (FFMQ >90). The percentage of misclassified validation examples is 24.6 (LOO = 75.4). The model's sensitivity is 79.3%, and the specificity is 71.9%. For adherence factors, a three-dimensional model is found. The patients who perform the 8 sessions of the MBCT have a profile with high or low trait mindfulness, high or low bodily dissociation, and low self-compassion. The percentage of misclassified validation examples is 37.3 (LOO = 62.7). The model's sensitivity is 48.4%, and the specificity is 71.9%. These results provide preliminary evidence that the predictive power of machine learning may allow the designing of standard patient profiles, which can contribute to 3 more personalized care for patients with symptoms of depression and anxiety. Also, including more psychoeducation in MBCT programs can maximize clinical benefits and adherence to this therapy. However, further studies are needed to explore this topic in more detail.

Most patient-reported experience measures (PREMs) are paper-based, leading to a high burden for patients and care providers. The aim of this study was to (1) calibrate an item bank to measure patients’ experience of respect and dignity for adult patients with serious mental illnesses and (2) develop computerized adaptive testing (CAT) to improve the use of this PREM in routine practice. Patients with schizophrenia, bipolar disorder, and major depressive disorder were enrolled in this multicenter and cross-sectional study. Psychometric analyses were based on classical test and item response theories and included evaluations of unidimensionality, local independence, and monotonicity; calibration and evaluation of model fit; analyses of differential item functioning (DIF); testing of external validity; and finally, CAT development. A total of 458 patients participated in the study. Of the 24 items, 2 highly inter-correlated items were deleted. Factor analysis showed that the remaining items met the unidimensional assumption (RMSEA = 0.054, CFI = 0.988, TLI = 0.986). DIF analyses revealed no biases by sex, age, care setting, or diagnosis. External validity testing has generally supported our assumptions. CAT showed satisfactory accuracy and precision. This work provides a more accurate and flexible measure of patients’ experience of respect and dignity than that obtained from standard questionnaires.

The S-QoL 18 is a self-administered questionnaire that assesses quality of life (QoL) among individuals with schizophrenia. This study aims to validate the S-QoL 18 in bipolar and depressive disorders for a more widespread use in psychiatric settings. This study was conducted in a non-selected sample of individuals with bipolar and depressive disorders in the day hospital of a regional psychiatric academic hospital. Two-hundred and seventy-two stable outpatients with bipolar (n = 73) and recurrent and persistent depressive (n = 199) disorders were recruited over a 12 month-period. The S-QoL 18 was tested for construct validity, reliability, and external validity. The eight-factor structure of the S-QoL 18 was confirmed by confirmatory factor analysis (RMSEA = 0.075 (0.064–0.086), CFI = 0.972, TLI = 0.961). Internal consistency and reliability were satisfactory. External validity was confirmed via correlations between S-QoL 18 dimension scores, symptomatology, and functioning. The percentage of missing data for the eight dimensions did not exceed 5%. INFIT statistics were ranged from 0.7 to 1.2, ensuring that all items of the scale measured the same QoL concept. In conclusion, the S-QoL 18 appears to be a valid and reliable instrument for measuring QoL in patients with bipolar and depressive disorders. The S-QoL 18 may be used by healthcare professionals in clinical settings to accurately assess QoL in individuals with bipolar and depressive disorders, as well as in schizophrenia.

Background. Fasting interventions have shown effectiveness in alleviating stress, anxiety and depressive symptoms. However, no quantitative analysis has been carried out thus far. The objective was to determine the effectiveness of fasting interventions on stress, anxiety and depression and if these interventions were associated with increased or decreased fatigue/energy. Methods. Overall, 11 studies and 1436 participants were included in the quantitative analyses. Results. After limiting analyses to randomized controlled trials with low risk of bias, we found that fasting groups had lower anxiety (b = −0.508, p = 0.038), depression levels (b= −0.281, p = 0.012) and body mass index compared to controls without increased fatigue. There was no publication bias and no heterogeneity for these results. These interventions were safe, even in patients with type 2 diabetes. Conclusions. These results should be taken with a caveat. These results are preliminary and encouraging and fasting appears to be a safe intervention. Data are not sufficient to recommend one fasting intervention more than the others. No study was carried out in psychiatric populations and further trials should be carried out in these populations that may be good candidates for fasting interventions.

Background: Major depressive disorder (MDD) is among the most common psychiatric disorders. One-third of patients are usually unresponsive to several lines of treatment. This study aimed to describe the FondaMental French cohort of patients with treatment-resistant depression (TRD) and to estimate utility and healthcare resource use outcomes. Methods: Patients with TRD were evaluated prospectively over four years (baseline, 6, 12, 18, 24, 36 and 48 months) in a real-world clinical setting. Interim analyses focused on the first two consecutive years. Four MDD-related states (major depressive episode (MDE), response, remission, recovery) were defined based on the MADRS (Montgomery–Åsberg depression rating scale) and other clinical events. Health status was assessed with the EuroQol 5 Dimensions 5 Level (EQ-5D-5L) questionnaire. Utility values were estimated as preference measures that the patients assigned to their overall health status. Results: This study was based on 252 patients with TRD. The mean utility value by health state was 0.41, 0.63, 0.80, and 0.90, for MDE, response, remission, and recovery, respectively. At baseline, 59% of patients had an MADRS score of at least 28. Their baseline average utility value was lower compared to the other patients (0.43 versus 0.58, p < 0.001). This significant difference persisted at the following visits. The rate of patients in MDEs having at least one hospitalisation for depression or other reasons than depression was generally higher than that in the other health states. Conclusion: This study documented patterns in healthcare resource consumption, quality of life, and other characteristics in patients with TRD, both globally and by health state and depression severity.

Background and significance. There is a need to develop new hypothesis-driven treatment for both both major depression (MD) and schizophrenia in which the risk of depression is 5 times higher than the general population. Major depression has been also associated with poor illness outcomes including pain, metabolic disturbances, and less adherence. Conventional antidepressants are partly effective, and 44% of the subjects remain unremitted under treatment. Improving MD treatment efficacy is thus needed to improve the SZ prognosis. Microbiota-orientated treatments are currently one of the most promising tracks. Method. This work is a systematic review synthetizing data of arguments to develop microbiota-orientated treatments (including fecal microbiota transplantation (FMT)) in major depression and schizophrenia. Results. The effectiveness of probiotic administration in MD constitutes a strong evidence for developing microbiota-orientated treatments. Probiotics have yielded medium-to-large significant effects on depressive symptoms, but it is still unclear if the effect is maintained following probiotic discontinuation. Several factors may limit MD improvement when using probiotics, including the small number of bacterial strains administered in probiotic complementary agents, as well as the presence of a disturbed gut microbiota that probably limits the probiotics’ impact. FMT is a safe technique enabling to improve microbiota in several gut disorders. The benefit/risk ratio of FMT has been discussed and has been recently improved by capsule administration. Conclusion. Cleaning up the gut microbiota by transplanting a totally new human gut microbiota in one shot, which is referred to as FMT, is likely to strongly improve the efficacy of microbiota-orientated treatments in MD and schizophrenia and maintain the effect over time. This hypothesis should be tested in future clinical trials.