OBJECTIVE:To study whether the insight described in psychosis also occurs in eating disorders (EDs), whether it differs between anorexia nervosa (AN) and bulimia nervosa (BN), and whether diagnosis-specific ED psychopathology mediates this relationship. METHODS:Cross-sectional baseline data from a prospective cohort of 103 day-hospital patients with AN or BN were analyzed. Standardized measures of insight, depressive symptoms, and ED psychopathology were administered. Exploratory factor analysis was conducted on depressive symptoms, followed by diagnosis-stratified correlation analyses between insight dimensions and depressive symptom factors. Mediation models were then applied to examine whether diagnosis-specific ED psychopathology accounted for significant associations. RESULTS:Three depressive dimensions were identified: emotional, apathetic, and self-critical, explaining 56.26% of the variance. In AN, affective distress was associated with poorer insight into hypothetical contradiction and treatment engagement, whereas negative self-cognitions where associated with better recognition and relabeling of ED pathology. In BN, depressive symptoms were associated with reduced insight into body weight concerns and treatment engagement. ED-specific psychopathology significantly mediated the relationship between depressive symptoms and insight in both AN and BN. CONCLUSION:These findings reveal that depressive symptoms and insight are associated in distinct patterns in anorexia and bulimia, and appear to be linked through different ED-specific psychopathological pathways. Highlighting these diagnosis-specific associations contributes to a more nuanced understanding of insight in EDs and underscores the need for tailored clinical approaches.

INTRODUCTION:Cognitive symptoms represent a significant and persistent challenge in patients with treatment-resistant depression (TRD), substantially impacting their functional outcomes. Deep brain stimulation (DBS) targeting the subcallosal cingulate gyrus (SCG) has shown clinical efficacy. Nonetheless, its long-term effects on cognition remains insufficiently researched. This study systematically evaluates cognitive outcomes following SCG-DBS over an extended follow-up period. METHODS:This retrospective, exploratory secondary analysis used longitudinal data from 12 TRD patients treated with SCG-DBS without a control group. Cognitive and clinical assessments were conducted pre-surgery and at long-term follow-up. Potential changes were examined using the Wilcoxon signed-rank test and its corresponding effect size (r), while Reliable Change Indices (RCIs) were applied to evaluate the statistical reliability of intra-subject cognitive changes. Spearman correlations explored associations between cognitive outcomes with clinical and functional ones. RESULTS:After a median follow-up of 5 years following SCG-DBS, TRD patients showed statistically significant improvements in immediate and delayed verbal memory (Wilcoxon's z = -2.28, p = .023, r = 0.66; Wilcoxon's z = -2.83, p = .005, r = 0.82, respectively), both reflecting large effect sizes. RCIs indicated reliable improvement in immediate (41.7% of patients) and in delayed (75%) verbal memory. Changes in verbal memory were not significantly correlated with clinical or functional improvements. CONCLUSIONS:These findings support the cognitive safety and benefits of SCG-DBS in individuals with TRD, particularly in verbal memory. However, further research is required to investigate the broader functional effects of SCG-DBS beyond the improvement of core clinical symptoms.

Major depressive disorder (MDD) is common and disabling, yet reported brain structural differences vary across studies. Here we performed a large vertex-wise (point-by-point) meta-analysis of cortical thickness and surface area using harmonized magnetic resonance imaging processing across 64 cohorts from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) MDD and Depression Imaging Research Consortium (DIRECT) consortia (5,736 patients; 6,538 controls). We show significantly lower cortical thickness in patients with MDD in multiple brain regions, including the inferior parietal, lateral occipital, superior parietal, medial and lateral orbitofrontal, anterior and posterior cingulate, and precentral gyri, with cortical surface area showing no significant differences. Effects were most pronounced in adults with acute depression, whereas adolescents showed no significant case-control differences. Antidepressant medication use at scanning was associated with more extensive thinning, although effect sizes remained modest (mostly |Cohen's d| < 0.20). This high-resolution, globally generalizable map can support studies of mechanisms and help evaluate structural markers of the clinical course and treatment response.

Cognitive dysfunction in major depressive disorder (MDD) often persists despite standard treatment. Integral cognitive remediation (INCREM) shows clinical efficacy, yet its molecular drivers remain poorly understood compared to supportive interventions like psychoeducation (PSYCHOED). In this exploratory study, we investigated whether circulating microRNAs (miRNAs) reflect the distinct biological trajectories of these interventions. We conducted a longitudinal analysis of 38 candidate miRNAs (previously validated in postmortem brain tissue of MDD individuals) in plasma from 22 patients with MDD participating in a randomized clinical trial who were assigned to 12 weeks of INCREM or PSYCHOED. Using bioinformatic pathway analyses (KEGG/GO), we identified non-overlapping miRNA profiles associated with each treatment. The INCREM response was characterized by a specific seven-miRNA signature (let-7b-3p, miR-100-5p, miR-129-5p, miR-135a-5p, miR-151a-5p, miR-4516, and miR-451a) targeting gene networks regulated in neuroplasticity, axon guidance, and synaptic transmission. These molecular changes mirrored significant objective cognitive improvements. Conversely, PSYCHOED induced a distinct profile (miR-126-5p and miR-195-5p) related to systemic cellular homeostasis and Wnt signaling, without objective cognitive gains. Our findings suggest that psychological therapies act as specific biological stimuli with distinct molecular targets. These circulating miRNA signatures provide preliminary evidence of neuroplasticity-related pathways as key drivers of cognitive recovery, offering potential blood-based biomarkers for precision psychiatry in MDD.

Abstract Elucidating the neurobiological basis of neurodevelopmental and psychiatric conditions (NDPCs) remains challenging because brain alterations vary within diagnoses and overlap across them. Whether diverse alterations follow a systematic organization that may reflect shared vulnerabilities remains unknown. Here, we assembled 10,135 individuals with schizophrenia, autism, bipolar, obsessive-compulsive, generalized anxiety, and major depressive disorders, and 11,998 reference participants across six continents through the ENIGMA consortium. Using normative modeling, we quantified individual deviations in cortical thickness, surface area, and subcortical volumes relative to lifespan reference trajectories (5 to 80 years). We show that structural deviations converged along cortical axes reflecting connectome organization, maturation, and cytoarchitectonic diversity. These axes mirrored typical population variation, but their expression differed across diagnoses and partly scaled with symptom severity. Even rare and highly individualized extreme deviations followed this organization, concentrating in densely connected regions. Finally, brain structural deviations overlapped substantially across diagnoses, while differences between them increased toward the association cortex. Together, we provide large-scale evidence that structural deviations across NDPCs are systematically constrained by the brain’s intrinsic architecture. This shared organization provides a framework for reconciling individual variability with transdiagnostic similarities and motivates an integrative, systems-level understanding of mental health.

Intensive Home Treatment for acute mental health crises has expanded internationally as a community-based alternative to inpatient admission. Despite its growing use, little is known about how informal carers experience supporting a relative during acute psychiatric decompensation at home-an emotionally demanding context marked by intensified responsibility and disruption of daily life. The aim of this study is to explore the lived experiences of informal caregivers providing support to a family member admitted to mental health Intensive Home Treatment using a reflexive thematic analysis within a constructivist orientation. The study adhered to the COREQ guidelines for qualitative research reporting. Data were collected using individual semi-structured interviews (n = 30) and one focus group (n = 8). The Stress Process Model informed the interview guide and acted as a sensitising lens; however, coding and theme development remained inductive. Three overarching themes and seven sub-themes captured the caregiving experience. Carers reported substantial physical, emotional, occupational and social consequences, including exhaustion, anxiety and marked disruption of daily routines. Their experiences combined distress with positive meaning making: strengthened bonds, feelings of usefulness and increased closeness coexisted with uncertainty, fear of relapse and difficulty managing unpredictable behaviours. Coping strategies included personal practices and external supports. All these findings suggest that caring during acute Intensive Home Treatment is meaningful yet highly demanding. Mental health professionals should systematically assess caregiver burden, support needs and coping resources, offering targeted interventions to enhance emotional well-being and sustain effective home-based psychiatric care.

The clinical and biological heterogeneity of major depressive disorder (MDD) may reflect the aggregation of different conditions with distinct pathologies under a single diagnostic label. Neuroanatomical heterogeneity in MDD was examined using a harmonized, age- and sex-matched sample from the ENIGMA MDD consortium (N = 5146; age range: 9-82 years; 64% female). Analyses of global neurostrucutral variability revealed greater cortical thickness heterogeneity in MDD compared with healthy controls (Cohen's d = -0.26). Regionally, increased variability in cortical thickness was most prominent in the cingulate (+6.1 to +6.6% more variation in MDD) and insular (+5.8%) cortices, as well as in the frontal (+5.7 to +6.8%) and temporal (+6.1 to +6.8%) lobes. Heterogeneity in cortical thickness was more pronounced among patients using antidepressant medication (Cohen's d = -0.39). Patient-specific analyses further showed that individuals with markedly increased cortical thickness variability (<5th percentile relative to the normative range) exhibited greater depressive symptom severity than those within the normative range (5th-95th percentile; Cohen's d = 0.19-0.36). Overall, the results indicate that neuroanatomical heterogeneity in MDD is primarily expressed in cortical thickness, offering refined insights into the neurobiological complexity of structural alterations associated with depression. These findings could guide future stratification efforts examining whether regionally confined changes in cortical thickness within areas of pronounced variability reflect clinically meaningful patient subgroups.

Background: Depressive symptoms cut across bipolar disorder (BD) and major depressive disorder (MDD), yet the extent to which the neurobiology of depressive severity is shared or diagnosis-specific is not well established. Progress is limited because multisite studies pool data from different depression rating scales, obscuring symptom-brain relationships. We used item response theory (IRT), which places these instruments on a single metric, to harmonise depressive symptom severity across five rating scales, and to identify shared and disorder-specific brain correlates of depression across BD and MDD.Methods: This cross-sectional mega-analysis of individual participant data from 52 international ENIGMA MDD and BD Working Group sites studied 11 999 individuals (6,789 healthy controls, 3,307 with BD, 1,903 with MDD) who had completed a depression measure and undergone T1-weighted MRI. We derived general and five symptom-specific IRT scores harmonised across five instruments (HDRS, MADRS, BDI-II, IDS, CES-D), and related them to cortical thickness, surface area, and subcortical volume, adjusting for age, sex, and global brain measures.Findings: Harmonising symptom scores strengthened brain-symptom associations beyond unharmonised total scores. Higher general depression severity was linked to lower cortical thickness, which strengthened after accounting for BD-MDD item-level differences. The disorders diverged: depressive severity was more tightly linked to subcortical structure, especially the hippocampus and thalamus, in MDD than BD, while BD showed lower cortical thickness across a wider cortical extent and more heterogeneous structural variability. Symptom dimensions diverged too: mood/motivational symptoms tracked cortical thickness in both disorders, while anxiety, cognitive-affective, and suicidal-ideation symptoms showed more disorder-specific subcortical and surface-area patterns.Interpretation: IRT harmonisation identified overlapping and disorder-specific associations between depressive severity and brain structure in BD and MDD, highlighting shared neurobiological features while demonstrating meaningful differences between disorders and supporting global efforts to integrate dimensional symptom measures across large-scale, multiscale studies.Funding: This work was supported by the US National Institute of Mental Health (R0I MH129742), including subaward SCON-00003343 awarded to Colm McDonald and Dara Cannon.

Desvenlafaxine, a serotonin-norepinephrine reuptake inhibitor, has demonstrated efficacy in improving affective symptoms of Major Depressive Disorder (MDD); however, its effects on associated cognitive and functional difficulties remain underexplored. This study seeks to assess the antidepressant effects of desvenlafaxine in patients with SSRI-resistant MDD, its impact on both objective and subjective cognitive performance, where cognitive improvements occur independently of clinical recovery or not, and its influence on psychosocial functioning. An observational case-control prospective study with 66 participants was conducted, including 26 patients with a current MDD episode, with an inadequate SSRI response, and with the prescription of desvenlafaxine as the next antidepressant therapeutic option, and 40 healthy controls. Sociodemographic, clinical, cognitive, and functional assessments were conducted both before and after a 12-week treatment period. Changes were analyzed using two tailed paired-samples t-tests, with Cohen’s d for effect sizes. Cognitive improvements were compared between the patients who achieved remission and those who did not. Patients showed significant improvements in depressive and anxiety symptoms, attention/working memory and processing speed, self-perceived cognitive difficulties and psychosocial functioning. Highlighting the fact these cognitive enhancements occurred independently of patients’ clinical improvement. The findings of this study focus on the therapeutic potential of desvenlafaxine, demonstrating its efficacy not only in ameliorating clinical and functional symptoms but also in addressing specific cognitive impairments in patients with depression. Further research is needed to elucidate the mechanisms underlying desvenlafaxine’s effects and optimize treatment strategies for individuals with MDD. NCT03432221 (clinical.trials.gov). Registration date: 08-01-2018.

This case study presents a 74-year-old woman with a 60-year history of anorexia nervosa (AN). Despite the long duration and severity of her illness, the patient achieved significant recovery through a multidisciplinary treatment approach. The treatment included a combination of nutritional therapy, psychotherapy, and pharmacotherapy, along with a strong emphasis on the patient's active involvement. Outcomes demonstrated substantial improvements in weight, mental health, and quality of life. This case highlights the importance of hope and perseverance in treating AN, even in cases considered difficult to manage. Findings suggest that an individualized and long-term approach, addressing both the physical and psychological aspects of the illness, may be crucial for achieving recovery in patients with chronic AN.

Importance:Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. Objective:To use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. Design setting and participants:A normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Main outcome measures:Z-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. Results:Z-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Conclusions and relevance:Our study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture. Key points: Question:Can z-scores derived from normative modelling shed light on the heterogeneous group-level findings of cortical thickness abnormalities in major depression and what characterises individuals at the extreme ends of cortical thickness abnormalities? Finding:We confirmed a large overlap in z-score distributions between depressed individuals and healthy controls and a heterogeneous spatial distribution of extreme z-deviations across brain regions across individual patients. Lower z-scores for cortical thickness were related to more severe clinical characteristics. Meaning:Our findings confirm the heterogeneity in individual variation in the location and extent of CT abnormalities across patients with MDD and stress the importance of individualised predictions when examining cortical thickness abnormalities.

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7012 participants from 31 sites (N = 2772 MDD and N = 4240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from other MRI modalities such as fMRI and DWI will lead to a higher performance in this diagnostic task.

INTRODUCTION:Individuals with major depressive disorder (MDD) and bipolar disorder (BD) frequently exhibit a disagreement between self-reported and objectively measured cognitive performance. Research suggests that these cognitive discrepancies may vary across disorders and are not exclusive to a specific diagnosis, potentially being influenced by clinical and sociodemographic factors. Overestimating cognitive abilities is associated with better psychosocial functioning in depression, whereas heightened sensitivity to cognitive deficits correlates with worse functioning. However, these phenomena remain underexplored in both depression and bipolar disorder. MATERIALS AND METHODS:We conducted a cross-sectional study of 200 participants, including 160 patients in full or partial clinical remission (94 with MDD and 66 with BD) and 40 healthy controls. Sociodemographic, clinical, and functional variables were collected, along with both subjective and objective cognitive measures. We conducted a multivariate binary logistic regression to identify factors associated with cognitive discrepancy patterns (under- vs overestimation). Finally, a two-way ANOVA tested the interaction between diagnosis and cognitive discrepancy patterns on psychosocial functioning. RESULTS:Patients with MDD tend to underestimate their cognitive abilities, while bipolar patients often overestimate theirs. Patients with higher depressive symptoms (B=-.045, p=.040) and higher intellectual level (B=-.241, p=<.001) report more subjective cognitive disturbances. Worse psychosocial functioning is not associated with underestimation but rather with the diagnosis itself (F=.63, p=.431), with bipolar disorder patients experiencing the most significant impact on daily functioning. CONCLUSIONS:Personalized cognitive assessments, integrating both objective and subjective measures, are of paramount importance to avoid generalizations and to accurately evaluate cognitive symptoms in patients with affective disorders.

Introduction: Obsessive-compulsive disorder (OCD) is a chronic condition where many patients remain symptomatic despite first-line treatments such as cognitive behavioural therapy and selective serotonin reuptake inhibitors. This randomised controlled trial evaluated mindfulness-based cognitive therapy (MBCT) efficacy as an augmentation strategy and its impact on brain functional connectivity. Methods: Sixty-eight participants with moderately symptomatic OCD were randomised into MBCT or treatment as usual (TAU). Clinical outcomes were evaluated using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the Obsessive-Compulsive Inventory, alongside other relevant secondary outcomes. Data were analysed using repeated-measures ANOVA to assess time * group effects. Neuroimaging functional measures (resting-state network connectivity) were collected before and after the intervention and analysed using independent component analysis. Results: Primary outcome: MBCT significantly reduced OCD symptoms compared to TAU (31.73% vs. 8.07% Y-BOCS reduction). Secondary outcomes: the MBCT group also experienced reductions in depressive symptoms, rumination, perceived stress, and quality of life. No significant post-treatment changes were observed in resting-state connectivity. However, baseline connectivity demonstrated significant predictive value, with lower connectivity in preselected networks of interest, including the fronto-striatal, salience, and default mode networks, associated with greater reductions in Y-BOCS scores. Conclusion: MBCT is an effective strategy for individuals with moderately symptomatic OCD who continue to experience symptoms despite prior gold-standard treatments. While no post-treatment changes in brain functional connectivity were observed, baseline connectivity patterns predicted symptom reduction, suggesting a neural basis for MBCT response.

The understanding of how antidepressant (AD) use is associated with brain structure in individuals with major depressive disorder (MDD) remains incomplete. We aimed to examine the association between AD medication use and brain morphology in relation to age and sex by pooling structural neuroimaging and clinical data from 32 cohorts within the ENIGMA-MDD working group. Interaction effects of group (2076 cases with current AD use (AD), 1495 cases not currently taking AD (nAD) and 5125 healthy controls (HC)) with age and sex, and main effects of group on regional brain structure (cortical surface area and thickness, and subcortical volume) were examined. Additionally, we examined the effect of AD type (SSRI, SNRI or mirtazapine) and duration of use on brain morphology. Younger individuals in the AD group showed lower bilateral middle temporal gyrus thickness compared to nAD and HC, but this was not seen in older individuals (crossover around 50 years). Lower hippocampal volume and thinner inferior temporal gyrus were shown in AD compared to nAD. These effects were independent of group differences in disease-course-related measures, but were driven by depressive symptom severity. Greater bilateral rostral anterior cingulate thickness was found in individuals older than approximately 40 years taking mirtazapine compared to individuals taking SSRIs or SNRIs. Evidence for subtle structural brain differences in temporal and limbic regions in individuals with MDD who currently use AD medication were found compared to those not currently taking AD medication. Future longitudinal studies are needed to determine the causality of these associations.

This cross-sectional study explores global and specific dimensions of insight in adults with eating disorders (EDs) in partial hospitalization and explores associations with clinical and psychological characteristics. Seventy-seven patients with EDs. were assessed using the Schedule for the Assessment of Insight in Eating Disorders (SAI-ED) which includes five domains: awareness of illness, awareness of symptoms, treatment engagement, subtotal, and total insight scores. Additional measures included the Beck Depression Inventory-II (BDI-II), Spielberger State-Trait Anxiety Inventory (STAI), and Eating Disorder Inventory (EDI) subscales for Drive for Thinness (DT), Interoceptive Awareness (IA), and Maturity Fears (MF). Multivariate regression analyses revealed that longer duration of illness and higher Drive for Thinness were positively associated with total insight, while higher depression scores were negatively associated. Awareness of illness was predicted by current body mass index (BMI) and Interoceptive Awareness; Awareness of Symptoms was associated with BMI and Maturity Fears; and Treatment Engagement was predicted by duration of illness, depression, and Maturity Fears. Findings indicate distinct relationships between specific insight dimensions and psychological characteristics in ED patients, highlighting the complex interplay of psychopathological factors influencing insight levels during partial hospitalization.

BACKGROUND:Anorexia nervosa (AN) is a severe and disabling disorder, with relapse rates as high as 50% after the first episode, posing a significant challenge for clinicians. Most therapies excessively focus on nourishment, resulting in temporary weight restoration but with no improvements in general well-being and quality of life. Radically Open Dialectical Behavior Therapy (RO-DBT) is a transdiagnostic treatment designed to address overcontrol, a key aspect in the functioning of patients with AN. To date, no clinical trial (CT) has shown its efficacy in these patients or evaluated its neurobiological mechanism of action. METHODS:A randomized CT in weight restored adult AN patients will be conducted, with one group receiving treatment as usual (TAU) and the other TAU plus RO-DBT, with the main outcome being quality of life. Secondary variables will include eating disorders (EDs) symptoms, overcontrol characteristics, autistic traits, and neuroimaging changes. DISCUSSION:The results will address a gap in knowledge regarding AN treatment, with the expectation that patients receiving TAU with RO-DBT will exhibit improved quality of life and experience fewer relapses at the one-year follow-up. This is the first study examining neuroimaging changes in RO-DBT to better understand its underlying mechanisms. TRIAL REGISTRATION:The study has been registered in ClinicalTrials.gov in September 22, 2023. It can be found in https://classic. CLINICALTRIALS:gov/ct2/show/NCT06050421 . TRIAL REGISTRATION NUMBER:NCT06050421.

This study aimed to evaluate the reliability and validity of the Spanish version of the Schedule for the Assessment of Insight in Eating Disorders (SAI-ED) and to explore the underlying structure of insight in patients with an eating disorder. A total of 103 patients diagnosed with anorexia nervosa or bulimia nervosa according to DSM-5 criteria were recruited from two specialized centers. Participants were assessed with the Spanish version of SAI-ED alongside the validated Spanish versions of the Brown Assessment of Beliefs Scale (BABS), and completed the Eating Attitudes Test-40 (EAT-40) and the Eating Disorder Inventory (EDI). Convergent and discriminant validity, internal consistency, inter-rater reliability and factor structure were analyzed. The Spanish version of the SAI-ED demonstrated good internal consistency (Cronbach’s alpha = 0.79), excellent inter-rater reliability (ICC = 0.92), and strong convergent validity with the BABS (rho = -0.57, p < 0.01). Discriminant validity was supported by non-significant correlations with the EDI-Perfectionism score (rho = -0.009, p = 0.929). Exploratory factor analysis revealed a three-factor structure capturing agreement on the need for treatment, awareness of eating disorder behaviors and awareness of body weight concerns. The Spanish version of the SAI-ED exhibits robust psychometric properties, confirming its validity and reliability for assessing insight in patients with eating disorders. The 3-factor structure underscores the complexity of insight in this population, emphasizing its clinical utility for tailoring treatment plans and optimizing intervention strategies. The study was registered at https://clinicaltrials.gov/ (NCT06177262). This study looked at how people with eating disorders understand their illness and treatment needs. We used a questionnaire called the SAI-ED to measure this kind of understanding, also known as "insight." We translated the SAI-ED into Spanish and tested it with 103 people diagnosed with anorexia or bulimia. The goal was to see if the Spanish version works well and gives reliable results. Our findings show that the Spanish SAI-ED is a useful and trustworthy tool. It helped us see that insight is not just one single thing. Instead, it has different parts: how much a person agrees they need treatment, how aware they are of their eating disorder behaviors, and how they see their body and weight. These results can help professionals better understand how each person experiences their illness and adjust treatment to fit their needs more closely. This kind of assessment may also support people in gaining more awareness of their difficulties and improve their motivation for recovery..

OBJECTIVE:To evaluate the feasibility and potential effectiveness of the Unified Protocol for Emotional Eating (UP-EE) in a group format. METHOD:Fifty-seven participants exhibiting high to severe emotional eating (EE) were assigned to an 8-week group intervention or to a control group receiving treatment as usual (TAU). EE (measured with the Dutch Eating Behavior Questionnaire) was the primary outcome, while state anxiety (State-Trait Anxiety Inventory [STAI-S]), depression (Beck Depression Inventory [BDI-II]) and perceived stress (Perceived Stress Scale [PSS-14]) were the secondary measures, assessed at baseline and post-intervention, or 8 weeks later in the control group. Satisfaction was measured via the Client Satisfaction Questionnaire (CSQ-8). Effectiveness was estimated using a linear mixed-effects model. RESULTS:The UP-EE received positive feedback and achieved an acceptable treatment retention. There were no significant differences regarding sociodemographic and clinical characteristics between groups. While both groups were not significantly different at the end of the intervention, the waitlist group worsened in anxiety, depression, and perceived stress, and showed only a slight improvement in EE. In contrast, the intervention group showed significant improvements across these variables, with a sharper decrease in EE. Results were consistent across both per-protocol and intention-to-treat analyses. CONCLUSIONS:A group UP-EE intervention is a feasible intervention. Future research should focus on a larger sample with a randomized controlled trial design and utilize measures of disordered eating to more clearly identify the superiority of the intervention over a comparison condition.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.