Risk factors for suicide reattempt: a systematic review and meta-analysis.

BACKGROUND: Suicide is one of the main external causes of death worldwide. People who have already attempted suicide are at high risk of new suicidal behavior. However, there is a lack of information on the risk factors that facilitate the appearance of reattempts. The aim of this study was to calculate the risk of suicide reattempt in the presence of suicidal history and psychosocial risk factors and to estimate the effect of each individual risk factor. METHODS: This systematic review and meta-analysis were conducted following the PRISMA-2020 guidelines. Studies on suicide reattempt that measured risk factors were searched from inception to 2022. The risk factors studied were those directly related to suicide history: history of suicide prior to the index attempt, and those that mediate the transition from suicidal ideation to attempt (alcohol or drug misuse, impulsivity, trauma, and non-suicidal self-injury). RESULTS: The initial search resulted in 11 905 articles. Of these, 34 articles were selected for this meta-analysis, jointly presenting 52 different effect sizes. The pooled effect size across the risk factors was significant (OR 2.16). Reattempt risk may be increased in presence of any of the following risk factors: previous history, active suicidal ideation, trauma, alcohol misuse, and drug misuse. However, impulsivity, and non-suicidal self-injury did not show a significant effect on reattempt. CONCLUSION: Most of the risk factors traditionally associated with suicide are also relevant when talking about suicide reattempts. Knowing the traits that define reattempters can help develop better preventive and intervention plans.

Sleep-wake variations of electrodermal activity in bipolar disorder.

BACKGROUND: Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities. METHODS: We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h. Fifteen EDA features were inferred by mixed-effect models for repeated measures considering sleep state, group and covariates. RESULTS: Thirteen EDA feature models were significantly influenced by sleep state, notably including phasic peaks (p < 0.001). During wakefulness, phasic peaks showed different values for mania (M [SD] = 6.49 [5.74, 7.23]), euthymia (5.89 [4.83, 6.94]), HC (3.04 [1.65, 4.42]), and depression (3.00 [2.07, 3.92]). Four phasic features during wakefulness better discriminated between HC and mania or euthymia, and between depression and euthymia or mania, compared to sleep. Mixed symptoms, average skin temperature, and anticholinergic medication affected the models, while sex and age did not. CONCLUSION: EDA measured from awake recordings better distinguished between BD states than sleep recordings, when controlled by confounders.

Emotion dysregulation in bipolar disorder compared to other mental illnesses: a systematic review and meta-analysis.

People with bipolar disorder (BD) often present emotion dysregulation (ED), a pattern of emotional expression interfering with goal-directed behavior. ED is a transdiagnostic construct, and it is unclear whether it manifests itself similarly in other conditions, such as major depressive disorder (MDD) or borderline personality disorder (BPD), or has specific features in BD. The present systematic review and meta-analysis explored ED and adopted emotion regulation (ER) strategies in BD compared with other psychiatric conditions. PubMed/MEDLINE, EMBASE, Scopus, and PsycINFO databases were systematically searched from inception to April 28th, 2022. Studies implementing validated instruments assessing ED or ER strategies in BD and other psychiatric disorders were reviewed, and meta-analyses were conducted. Twenty-nine studies yielding multiple comparisons were included. BD was compared to MDD in 20 studies (n = 2451), to BPD in six studies (n = 1001), to attention deficit hyperactivity disorder in three studies (n = 232), to anxiety disorders in two studies (n = 320), to schizophrenia in one study (n = 223), and to post-traumatic stress disorder in one study (n = 31). BD patients did not differ from MDD patients in adopting most adaptive and maladaptive ER strategies. However, small-to-moderate differences in positive rumination and risk-taking behaviors were observed. In contrast, patients with BPD presented an overall higher degree of ED and more maladaptive ER strategies. There were insufficient data for a meta-analytic comparison with other psychiatric disorders. The present report further supports the idea that ED is a transdiagnostic construct spanning a continuum across different psychiatric disorders, outlining specific clinical features that could represent potential therapeutic targets.

Correlation between emotion dysregulation and mood symptoms of bipolar disorder: A systematic review and meta-analysis.

BACKGROUND: Emotion dysregulation (ED) is a transdiagnostic construct characterized by difficulties regulating intense emotions. People with bipolar disorder (BD) are more likely to show ED and use maladaptive emotion regulation strategies than adaptive ones. However, little is known about whether ED in BD is a trait or it is rather an epiphenomenon of mood symptoms. METHODS: We conducted a systematic review and meta-analysis of the evidence across major literature databases reporting correlations between measures of emotion regulation (overall ED and different emotion regulation strategies) and measures of depressive and (hypo)manic symptoms in BD from inception until April 12th, 2022. RESULTS: Fourteen studies involving 1371 individuals with BD were included in the qualitative synthesis, of which 11 reported quantitative information and were included in the meta-analysis. ED and maladaptive strategies were significantly higher during periods with more severe mood symptoms, especially depressive ones, while adaptive strategies were lower. CONCLUSION: ED significantly correlates with BD symptomatology, and it mainly occurs during mood alterations. ED may be a target for specific psychotherapeutic and pharmacological treatments, according to precision psychiatry. However, further studies are needed, including patients with mood episodes and longitudinal design, to provide more robust evidence and explore the causal direction of the associations.

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies.

BACKGROUND: Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution. OBJECTIVE: We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers. METHODS: Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores. RESULTS: Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=-2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible. CONCLUSIONS: The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising but suggest the need to adapt and enhance the smartphone-based solution to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.

Evaluating the Effect of a Telepsychiatry Educational Program on the Awareness, Knowledge, Attitude, and Skills of Telepsychiatry Among Spanish Psychiatrists during COVID-19 Pandemic.

Introduction: The COVID-19 pandemic has renewed the interest in telepsychiatry as a way to help psychiatrists care for their patients, but mental health providers' unfamiliarity and concerns may impede implementation of such services. This study aimed to determine the effect of an online educational intervention on awareness, knowledge, attitude, and skills (AKAS) of telepsychiatry among psychiatrists. Methods: The study used a pre-post-test design to compare AKAS of telepsychiatry among psychiatrists participating in an online course of practical telepsychiatry. The telemedicine AKAS questionnaire adapted to telepsychiatry was applied before and after the educational intervention, during the months of October to December 2020. Results: Responses from 213 participants were analyzed before the educational intervention and from 152 after it. The knowledge showed by Spanish psychiatrists before the educational intervention was good in 61% of participants, fair in 37%, and inadequate in 2%. With respect to attitudes toward telepsychiatry, 62% self-reported a high attitude, 33% moderate, and 5% low. With regard self-reported skills, 57% of the participating psychiatrists were highly skilled or experts, 22% moderately skilled, and 9% unskilled in handling telepsychiatry equipment. Despite the high baseline values, the educational intervention significantly improved psychiatrists' awareness, knowledge and attitudes toward telepsychiatry although not their skills. Conclusions: Online course of practical telepsychiatry was effective although future editions need to improve its focus on skills. This educational intervention represents an effort to promote the implementation of telepsychiatry as a health care alternative.

Consensus on nomenclature for clinical staging models in bipolar disorder: A narrative review from the International Society for Bipolar Disorders (ISBD) Staging Task Force.

OBJECTIVES: Clinical staging is widely used in medicine to map disease progression, inform prognosis, and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well-defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking. METHODS: Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders. RESULTS: Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at-risk status and subthreshold stages, and to various clinical stages of BD as it is currently diagnosed. CONCLUSION: The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light.

Trajectories of suicidal ideation after first-episode psychosis: a growth mixture modeling approach.

OBJECTIVE: The period immediately after the onset of first-episode psychosis (FEP) may present with high risk for suicidal ideation (SI) and attempts, although this risk may differ among patients. Thus, we aimed to identify trajectories of SI in a 2-years follow-up FEP cohort and to assess baseline predictors and clinical/functional evolution for each trajectory of SI. METHODS: We included 334 FEP participants with data on SI. Growth mixture modeling was used to identify trajectories of SI. Putative sociodemographic, clinical, and cognitive predictors of the distinct trajectories were examined using multinomial logistic regression. RESULTS: We identified three distinct trajectories: Non-SI trajectory (85.53% sample), Improving SI trajectory (9.58%), and Worsening SI trajectory (6.89%). Multinomial logistic regression model revealed that greater baseline pessimistic thoughts, anhedonia, and worse perceived family environment were associated with higher baseline SI followed by an Improving trajectory. Older age, longer duration of untreated psychosis, and reduced sleep predicted Worsening SI trajectory. Regarding clinical/functional evolution, individuals within the Improving SI trajectory displayed moderate depression at baseline which ameliorated during the study period, while the Worsening SI subgroup exhibited persistent mild depressive symptoms and greater functional impairment at follow-up assessments. CONCLUSION: Our findings delineated three distinct trajectories of SI among participants with FEP, one experiencing no SI, another in which SI might depend on acute depressive symptomatology, and a last subset where SI might be associated with mild but persistent clinical and functional impairments. These data provide insights for the early identification and tailored treatment of suicide in this at-risk population.

The interplay between acute bacterial skin and skin structure infections and depression: a vicious circle of major clinical importance.

PURPOSE OF REVIEW: Previous studies suggest an association between depression and increased risk of various type of infections, including acute bacterial skin and skin structure infections (ABSSSI). Here, we review the latest advancement in our understanding of immunity in patients with depression and its relevance to disease management and diagnosis, with a special focus on patients suffering from ABSSSI. RECENT FINDINGS: Recent studies have highlighted the role of hypothalamic-pituitary-adrenal axis, neuro-endocrine stress signaling pathways and behavioral attitudes (substance abuse and homelessness) in the pathogenesis of infections in depressed patients. Furthermore, acute bacterial infections, in turn, have emerged as a possible risk for depression development because of different mechanisms including antibiotic-driven changes in the microbiota. SUMMARY: Recent evidences have emphasized the threat that comanagement of depression and infection pose to infectious disease physician and psychiatrist. Depressed patients with ABSSSI must be closely monitored for drug side-effects, drug-drug interactions, toxicity, and adequate compliance. New management strategies including new long-acting antibiotics (e.g., dalbavancin) are welcome.

Bipolar disorder.

Bipolar disorder is a recurrent chronic disorder characterised by fluctuations in mood state and energy. It affects more than 1% of the world's population irrespective of nationality, ethnic origin, or socioeconomic status. Bipolar disorder is one of the main causes of disability among young people, leading to cognitive and functional impairment and raised mortality, particularly death by suicide. A high prevalence of psychiatric and medical comorbidities is typical in affected individuals. Accurate diagnosis of bipolar disorder is difficult in clinical practice because onset is most commonly a depressive episode and looks similar to unipolar depression. Moreover, there are currently no valid biomarkers for the disorder. Therefore, the role of clinical assessment remains key. Detection of hypomanic periods and longitudinal assessment are crucial to differentiate bipolar disorder from other conditions. Current knowledge of the evolving pharmacological and psychological strategies in bipolar disorder is of utmost importance.

Cognitive Impairment in Bipolar Disorder: Treatment and Prevention Strategies.

Over the last decade, there has been a growing appreciation of the importance of identifying and treating cognitive impairment associated with bipolar disorder, since it persists in remission periods. Evidence indicates that neurocognitive dysfunction may significantly influence patients' psychosocial outcomes. An ever-increasing body of research seeks to achieve a better understanding of potential moderators contributing to cognitive impairment in bipolar disorder in order to develop prevention strategies and effective treatments. This review provides an overview of the available data from studies examining treatments for cognitive dysfunction in bipolar disorder as well as potential novel treatments, from both pharmacological and psychological perspectives. All these data encourage the development of further studies to find effective strategies to prevent and treat cognitive impairment associated with bipolar disorder. These efforts may ultimately lead to an improvement of psychosocial functioning in these patients.

Gut Microbiota, Bacterial Translocation, and Interactions with Diet: Pathophysiological Links between Major Depressive Disorder and Non-Communicable Medical Comorbidities.

BACKGROUND: Persistent low-grade immune-inflammatory processes, oxidative and nitrosative stress (O&NS), and hypothalamic-pituitary-adrenal axis activation are integral to the pathophysiology of major depressive disorder (MDD). The microbiome, intestinal compositional changes, and resultant bacterial translocation add a new element to the bidirectional interactions of the gut-brain axis; new evidence implicates these pathways in the patho-aetiology of MDD. In addition, abnormalities in the gut-brain axis are associated with several chronic non-communicable disorders, which frequently co-occur in individuals with MDD, including but not limited to irritable bowel syndrome (IBS), chronic fatigue syndrome (CFS), obesity, and type 2 diabetes mellitus (T2DM). METHODS: We searched the PubMed/MEDLINE database up until May 1, 2016 for studies which investigated intestinal dysbiosis and bacterial translocation (the 'leaky gut') in the pathophysiology of MDD and co-occurring somatic comorbidities with an emphasis on IBS, CFS, obesity, and T2DM. RESULTS: The composition of the gut microbiota is influenced by several genetic and environmental factors (e.g. diet). Several lines of evidence indicate that gut-microbiota-diet interactions play a significant pathophysiological role in MDD and related medical comorbidities. Gut dysbiosis and the leaky gut may influence several pathways implicated in the biology of MDD, including but not limited to immune activation, O&NS, and neuroplasticity cascades. However, methodological inconsistencies and limitations limit comparisons across studies. CONCLUSIONS: Intestinal dysbiosis and the leaky gut may constitute a key pathophysiological link between MDD and its medical comorbidities. This emerging literature opens relevant preventative and therapeutic perspectives.

Antipsychotic switching in bipolar disorders: a systematic review.

With the increasingly widespread use of antipsychotics in bipolar disorder (BD), switching among these agents and between antipsychotics and mood stabilizers has become more common, in particular, since the introduction of the novel atypical antipsychotics with mood stabilizer properties. This systematic review aims to provide a comprehensive update of the current literature in BD about the switching of antipsychotics, among them and between them and mood stabilizers, in acute and maintenance treatment. We conducted a comprehensive, computerized literature search using terms related to antipsychotic switching in BD in the PubMed/Medline, PsycINFO, CINAHL database; the Cochrane Library and; the Clinicaltrials.gov web up to January 9th, 2013 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search returned 4160 articles. After excluding duplications, reviews, case reports and studies that did not fulfil the selection criteria, 8 studies were included. Not only have few articles on antipsychotic switching been published but also recruitment in most studies included mixed samples of patients. In general, antipsychotic switching, regardless of the route of drug administration, was well tolerated and no interference was shown in antipsychotic effectiveness during the interchange of drugs. Metabolic improvement was perceived when the switch involved antipsychotics with a low metabolic risk profile. The evidence-base for antipsychotic switching in BD is scant, and little controlled data is available. Switch from quetiapine to lithium and from risperidone to olanzapine has proven successful. Switching to antipsychotics with low metabolic risk had some positive impact on several safety measures. In stabilized patients, the plateau cross-taper switch may be preferred.

The functioning assessment short test (FAST): Clinically meaningful response threshold in patients with major depressive disorder receiving antidepressant treatment.

BACKGROUND: Functional impairment is common in patients with major depressive disorder (MDD). The Functioning Assessment Short Test (FAST) provides a detailed clinician-rated assessment of functioning across multiple aspects of daily life. This study aimed to establish clinically relevant response thresholds for the FAST in patients with MDD receiving antidepressant treatment. METHODS: Data were derived from three 8-week clinical trials of antidepressant therapy in patients with MDD that included assessment of functioning using the FAST as a pre-specified endpoint. The minimal clinically important difference (MCID) and threshold for response in terms of change in FAST total score were determined using anchor-based methods. RESULTS: After 8 weeks of antidepressant treatment, the mean reduction in FAST total score in patients considered clinically minimally improved (Clinical Global Impression-Improvement [CGII] score of 3) was 7-9 points (~20 % reduction). The threshold for functional response (reduction in FAST total score from baseline in patients with a CGI-I score of ≤2 at week 8) was 16-19 points (~50 % reduction). The threshold for functional response was higher in patients with MDD and comorbid generalized anxiety disorder than in those with MDD alone (mean reduction in FAST total score at 8 weeks: 26 points [63 %]). LIMITATIONS: Short-term studies. CONCLUSIONS: These results provide further validation of the FAST for assessing functioning in patients with MDD. In patients with MDD, the suggested MCID for FAST total score is 7-9 points and the proposed threshold for response is a reduction from baseline of approximately 50 %.

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. OBJECTIVE: In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. METHODS: We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. RESULTS: SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. CONCLUSIONS: We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number.

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.

Exploring Clinical Subgroups of Participants with Major Depressive Disorder that may Benefit from Adjunctive Minocycline Treatment.

Objective: : To explore illness-related factors in patients with major depressive disorder (MDD) recipients of adjunctive minocycline (200 mg/day) treatment. The analysis included participants experiencing MDD from a 12-week, double blind, placebo-controlled, randomized clinical trial (RCT). Methods: : This is a sub-analysis of a RCT of all 71 participants who took part in the trial. The impact of illness chronicity (illness duration and number of depressive episodes), systemic illness (endocrine, cardiovascular and obesity), adverse effects and minocycline were evaluated as change from baseline to endpoint (12-week) using ANCOVA. Results: : There was a consistent but statistically non-significant trend on all outcomes in favour of the use of adjunctive minocycline for participants without systemic illness, less illness chronicity, and fewer adverse effects. Conclusion: : Understanding the relationship between MDD and illness chronicity, comorbid systemic illness, and adverse effects, can potentially better characterise those individuals who are more likely to respond to adjunctive anti-inflammatory medications.

Anxious and depressive symptoms and health-related quality of life in a cohort of people who recently attempted suicide: A network analysis.

BACKGROUND: Suicide is an international health concern with immeasurable impact from the perspective of human and social suffering. Prior suicide attempts, anxious and depressive symptoms, and relatively lower health-related quality of life (HRQoL) are among the most replicated risk factors for suicide. Our goal was to visualize the distribution of these features and their interconnections with use of a network analysis approach in individuals who recently attempted suicide. METHODS: Individuals with a recent suicide attempt were recruited from nine University Hospitals across Spain as part of the SURVIVE cohort study. Anxious and depressive symptoms, and perceived HRQoL were included in the network analysis. Network structures were estimated with the EBICglasso model. Centrality measures and bridge symptoms connecting communities were explored. Subnetworks comparing younger and older individuals, and women and men were analyzed. RESULTS: A total of 1106 individuals with a recent suicide attempt were included. Depressed mood was the symptom with the greatest influence in the overall network, followed by anxiety symptoms such as feeling nervous, worrying, restless, and having difficulties to relax. Perceived general health was associated with increased suicidal ideation in the whole sample. Older people showed a specific connection between perceived general health and depressed mood. LIMITATIONS: The cross-sectional design does not allow determination of established causality. CONCLUSIONS: Depressed mood was the core network's symptom and, therefore, an important target in the management and prevention of suicide. HRQoL had more influence on the network of older populations, in which it should be a primary focus.

Cognitive reserve moderates the relationship between childhood maltreatment, objective and subjective cognition, and psychosocial functioning in individuals with first-episode psychosis.

OBJECTIVE: This study aimed to assess the relationship between childhood maltreatment (CM), objective and subjective cognition, and psychosocial functioning in adults with first-episode psychosis (FEP) by examining the moderating role of cognitive reserve (CR). A secondary objective was to explore whether unique CM subtypes (physical and/or emotional abuse, sexual abuse, physical and/or emotional neglect) were driving this relationship. METHOD: Sixty-six individuals with FEP (Mage = 27.3, SD = 7.2 years, 47% male) completed a comprehensive neuropsychological test battery, the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA), the Functioning Assessment Short Test (FAST), the Childhood Trauma Questionnaire (CTQ), and the Cognitive Reserve Assessment Scale in Health (CRASH). Linear regression analyses were conducted to evaluate the interaction effect of CR between CM and cognitive and psychosocial variables, controlling for age, sex, and social desirability (CTQ-denial-minimization). RESULTS: In adults with FEP overall CM interacted with CR to predict COBRA-subjective cognitive complaints, but not neurocognitive or psychosocial functioning. Sexual abuse and physical neglect interacted with CR to predict verbal memory. Most of the CM subtypes interacted with CR to predict FAST-leisure time, whereas only emotional neglect interacted with CR to predict FAST-interpersonal relationships. Overall, greater CR was related to better functioning. CONCLUSIONS: The current results indicate that associations between specific CM subtypes, subjective and objective cognition, and psychosocial domains are moderated through CR with greater functioning. Early interventions focused on CR seeking to improve cognitive and psychosocial outcomes, with emphasis on improving subjective cognitive functions would be beneficial for individuals with FEP and CM. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Psychiatric profiles in suicidal attempters: Relationships with suicide behaviour features.

BACKGROUND: Suicide constitutes a major health concern worldwide, being a significant contributor of death, globally. The diagnosis of a mental disorder has been extensively linked to the varying forms of suicidal ideation and behaviour. The aim of our study was to identify the varying diagnostic profiles in a sample of suicide attempters. METHODS: A sample of 683 adults (71.3% females, 40.10±15.74 years) admitted at a hospital emergency department due to a suicide attempt was recruited. Latent class analysis was used to identify diagnostic profiles and logistic regression to study the relationship between comorbidity profile membership and sociodemographic and clinical variables. RESULTS: Two comorbidity profiles were identified (Class I: low comorbidity class, 71.3% of attempters; Class II: high comorbidity class, 28.7% of attempters). Class I members were featured by the diagnosis of depression and general anxiety disorder, and low comorbidity; by contrast, the high comorbidity profile was characterized by a higher probability of presenting two or more coexisting psychiatric disorders. Class II included more females, younger, with more depressive symptoms and with higher impulsivity levels. Moreover, Class II members showed more severe suicidal ideation, higher number of suicide behaviours and a greater number of previous suicide attempts (p<.01, for all the outcomes), compared to Class I members. CONCLUSIONS: Psychiatric profiles may be considered for treatment provision and personalized psychiatric treatment in suicidal attempters as well as tackle suicide risk.