Identifying tripartite relationship among cortical thickness, neuroticism, and mood and anxiety disorders.

The number of young adults seeking help for emotional distress, subsyndromal-syndromal mood/anxiety symptoms, including those associated with neuroticism, is rising and can be an early manifestation of mood/anxiety disorders. Identification of gray matter (GM) thickness alterations and their relationship with neuroticism and mood/anxiety symptoms can aid in earlier diagnosis and prevention of risk for future mood and anxiety disorders. In a transdiagnostic sample of young adults (n = 252;177 females; age 21.7 ± 2), Hypothesis (H) 1:regularized regression followed by multiple regression examined relationships among GM cortical thickness and clinician-rated depression, anxiety, and mania/hypomania; H2:the neuroticism factor and its subfactors as measured by NEO Personality Inventory (NEO-PI-R) were tested as mediators. Analyses revealed positive relationships between left parsopercularis thickness and depression (B = 4.87, p = 0.002), anxiety (B = 4.68, p = 0.002), mania/hypomania (B = 6.08, p ≤ 0.001); negative relationships between left inferior temporal gyrus (ITG) thickness and depression (B = - 5.64, p ≤ 0.001), anxiety (B = - 6.77, p ≤ 0.001), mania/hypomania (B = - 6.47, p ≤ 0.001); and positive relationships between left isthmus cingulate thickness (B = 2.84, p = 0.011), and anxiety. NEO anger/hostility mediated the relationship between left ITG thickness and mania/hypomania; NEO vulnerability mediated the relationship between left ITG thickness and depression. Examining the interrelationships among cortical thickness, neuroticism and mood and anxiety symptoms enriches the potential for identifying markers conferring risk for mood and anxiety disorders and can provide targets for personalized intervention strategies for these disorders.

Cannabis use and mood disorders: a systematic review.

Background: Problematic cannabis use is highly prevalent among people with mood disorders. This underscores the need to understand the effects of cannabis and cannabinoids in this population, especially considering legalization of recreational cannabis use. Objectives: We aimed to (1) systematically evaluate cross-sectional and longitudinal studies investigating the interplay between cannabis use, cannabis use disorder (CUD), and the occurrence of mood disorders and symptoms, with a focus on major depressive disorder (MDD) and bipolar disorder (BD) and; (2) examine the effects of cannabis on the prognosis and treatment outcomes of MDD and BD. Methods: Following PRISMA guidelines, we conducted an extensive search for English-language studies investigating the potential impact of cannabis on the development and prognosis of mood disorders published from inception through November 2023, using EMBASE, PsycINFO, PubMed, and MEDLINE databases. Results: Our literature search identified 3,262 studies, with 78 meeting inclusion criteria. We found that cannabis use is associated with increased depressive and manic symptoms in the general population in addition to an elevated likelihood of developing MDD and BD. Furthermore, we observed that cannabis use is linked to an unfavorable prognosis in both MDD or BD. Discussion: Our findings suggest that cannabis use may negatively influence the development, course, and prognosis of MDD and BD. Future well-designed studies, considering type, amount, and frequency of cannabis use while addressing confounding factors, are imperative for a comprehensive understanding of this relationship. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023481634.

Comparing psychological versus pharmacological treatment in emotional disorders: A network analysis.

Transdiagnostic group cognitive behavioural therapy (TD-GCBT) is more effective in improving symptoms and severity of emotional disorders (EDs) than treatment as usual (TAU; usually pharmacological treatment). However, there is little research that has examined the effects of these treatments on specific symptoms. This study used Network Intervention Analysis (NIA) to investigate the direct and differential effects of TD-GCBT + TAU and TAU on specific symptoms of anxiety and depression. Data are from a multicentre randomised clinical trial (N = 1061) comparing TD-GCBT + TAU versus TAU alone for EDs. The networks included items from the PHQ-9 (depression) and GAD-7 (anxiety) questionnaire and mixed graphical models were estimated at pre-treatment, post-treatment and 3-, 6- and 12-month follow-up. Results revealed that TD-GCBT + TAU was associated with direct effects, mainly on several anxiety symptoms and depressed mood after treatment. New direct effects on other depressive symptoms emerged during the follow-up period promoted by TD-GCBT compared to TAU. Our results suggest that the improvement of anxiety symptoms after treatment might precipitate a wave of changes that favour a decrease in depressive symptomatology. NIA is a methodology that can provide fine-grained insight into the likely pathways through which treatments exert their effects.

Infant microbes and metabolites point to childhood neurodevelopmental disorders.

This study has followed a birth cohort for over 20 years to find factors associated with neurodevelopmental disorder (ND) diagnosis. Detailed, early-life longitudinal questionnaires captured infection and antibiotic events, stress, prenatal factors, family history, and more. Biomarkers including cord serum metabolome and lipidome, human leukocyte antigen (HLA) genotype, infant microbiota, and stool metabolome were assessed. Among the 16,440 Swedish children followed across time, 1,197 developed an ND. Significant associations emerged for future ND diagnosis in general and for specific ND subtypes, spanning intellectual disability, speech disorder, attention-deficit/hyperactivity disorder, and autism. This investigation revealed microbiome connections to future diagnosis as well as early emerging mood and gastrointestinal problems. The findings suggest links to immunodysregulation and metabolism, compounded by stress, early-life infection, and antibiotics. The convergence of infant biomarkers and risk factors in this prospective, longitudinal study on a large-scale population establishes a foundation for early-life prediction and intervention in neurodevelopment.

Driver's Licensure and Driving Outcomes Among Youths With Mood Disorders.

Importance: Mood disorders are prevalent among adolescents and young adults, and their onset often coincides with driving eligibility. The understanding of how mood disorders are associated with youth driving outcomes is limited. Objective: To examine the association between the presence of a mood disorder and rates of licensing, crashes, violations, and suspensions among adolescents and young adults. Design, Setting, and Participants: This cohort study was conducted among New Jersey residents who were born 1987 to 2000, age eligible to acquire a driver's license from 2004 to 2017, and patients of the Children's Hospital of Philadelphia network within 2 years of licensure eligibility at age 17 years. The presence of a current (ie, ≤2 years of driving eligibility) mood disorder was identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Rates of licensure and driving outcomes among youths who were licensed were compared among 1879 youths with and 84 294 youths without a current mood disorder from 2004 to 2017. Data were analyzed from June 2022 to July 2023. Main Outcomes and Measures: Acquisition of a driver's license and first involvement as a driver in a police-reported crash and rates of other adverse driving outcomes were assessed. Survival analysis was used to estimate adjusted hazard ratios (aHRs) for licensing and driving outcomes. Adjusted rate ratios (aRRs) were estimated for driving outcomes 12 and 48 months after licensure. Results: Among 86 173 youths (median [IQR] age at the end of the study, 22.8 [19.7-26.5] years; 42 894 female [49.8%]), there were 1879 youths with and 84 294 youths without a mood disorder. A greater proportion of youths with mood disorders were female (1226 female [65.2%]) compared with those without mood disorders (41 668 female [49.4%]). At 48 months after licensure eligibility, 75.5% (95% CI, 73.3%-77.7%) and 83.8% (95% CI, 83.5%-84.1%) of youths with and without mood disorders, respectively, had acquired a license. Youths with mood disorders were 30% less likely to acquire a license than those without a mood disorder (aHR, 0.70 [95% CI, 0.66-0.74]). Licensed youths with mood disorders had higher overall crash rates than those without mood disorders over the first 48 months of driving (137.8 vs 104.8 crashes per 10 000 driver-months; aRR, 1.19 [95% CI, 1.08-1.31]); licensed youths with mood disorders also had higher rates of moving violations (aRR, 1.25 [95% CI, 1.13-1.38]) and license suspensions (aRR, 1.95 [95% CI, 1.53-2.49]). Conclusions and Relevance: This study found that youths with mood disorders were less likely to be licensed and had higher rates of adverse driving outcomes than youths without mood disorders. These findings suggest that opportunities may exist to enhance driving mobility in this population and elucidate the mechanisms by which mood disorders are associated with crash risk.

Mood variability during adolescent development and its relation to sleep and brain development.

Mood swings, or mood variability, are associated with negative mental health outcomes. Since adolescence is a time when mood disorder onset peaks, mood variability during this time is of significant interest. Understanding biological factors that might be associated with mood variability, such as sleep and structural brain development, could elucidate the mechanisms underlying mood and anxiety disorders. Data from the longitudinal Leiden self-concept study (N = 191) over 5 yearly timepoints was used to study the association between sleep, brain structure, and mood variability in healthy adolescents aged 11-21 at baseline in this pre-registered study. Sleep was measured both objectively, using actigraphy, as well as subjectively, using a daily diary self-report. Negative mood variability was defined as day-to-day negative mood swings over a period of 5 days after an MRI scan. It was found that negative mood variability peaked in mid-adolescence in females while it linearly increased in males, and average negative mood showed a similar pattern. Sleep duration (subjective and objective) generally decreased throughout adolescence, with a larger decrease in males. Mood variability was not associated with sleep, but average negative mood was associated with lower self-reported energy. In addition, higher thickness in the dorsolateral prefrontal cortex (dlPFC) compared to same-age peers, suggesting a delayed thinning process, was associated with higher negative mood variability in early and mid-adolescence. Together, this study provides an insight into the development of mood variability and its association with brain structure.

Comparing nurses attending a specialised mental health programme with and without substance use disorder: a retrospective, observational study in Spain.

OBJECTIVES: To analyse the differences between nurses with and without substance use disorders (SUDs) admitted to a specialised mental health programme. DESIGN: Retrospective, observational study. SETTING: Specialised mental health treatment programme for nurses in Catalonia, Spain. PARTICIPANTS: 1091 nurses admitted to the programme from 2000 to 2021. INTERVENTIONS: None. PRIMARY AND SECONDARY OUTCOMES: Sociodemographic, occupational and clinical variables were analysed. Diagnoses followed Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision criteria. RESULTS: Most nurses admitted to the programme were women (88%, n=960) and came voluntarily (92.1%, n=1005). The mean age at admission was 45 (SD=10.4) years. The most common diagnoses were adjustment disorders (36.6%, n=399), unipolar mood disorders (25.8%, n=282), anxiety disorders (16.4%, n=179) and SUDs (13.8%, n=151). Only 19.2% (n=209) of the sample were hospitalised during their first treatment episode. After multivariate analysis, suffering from a SUD was significantly associated with being a man (OR=4.12; 95% CI 2.49 to 6.82), coming after a directed referral (OR=4.55; 95% CI 2.5 to 7.69), being on sick leave at admission (OR=2.21; 95% CI 1.42 to 3.45) and needing hospitalisation at the beginning of their treatment (OR=12.5; 95% CI 8.3 to 20). CONCLUSIONS: Nurses with SUDs have greater resistance to voluntarily asking for help from specialised mental health treatment programmes and have greater clinical severity compared with those without addictions. SUDs are also more frequent among men. More actions are needed to help prevent and promote earlier help-seeking behaviours among nurses with this type of mental disorder.

Neuropathic pain and mood disorders in earthquake survivors with peripheral nerve injuries.

Background and purpose:

        Natural disasters, such as earthquakes, frequently result in mood disorders among affected individuals. It is established that neuropathic pain arising from traumatic neuropathies is also linked to mood disorders. This study investigates the influence of neuropathic pain on the development of mood disorders in earthquake survivors with peripheral nerve injuries, following the earthquake centered in Kahramanmaras on February 6, 2023. Additionally, we aim to assess the electro­physiological aspects of neuropathic injuries in these survivors.

The study comprised 46 earth-quake survivors with electrophysiologically confirmed peripheral nerve injuries, with 39 trauma-free survivors serving as the control group. Neuropathic pain, anxiety and depression were assessed using the Douleur Neuropathique 4 (DN4) questionnaire and the Hospital Anxiety and Depression Scale (HADS).

Our findings revealed that the ulnar and peroneal nerves were the most commonly injured structures. Among the survivors with peripheral nerve injury, 31 out of 46 (67%) were found to experience neuropathic pain. Furthermore, plexopathy and multiple extremity injuries were associated with more severe neuropathic pain. However, there was no significant difference in anxiety and depression scores between the two groups and neuropathic pain was found to have no independent effect.

The study indicates that the intensity of neuropathic pain varies based on the localization and distribution of peripheral nerve injuries. However, the presence of peripheral nerve damage or neuropathic pain was not directly associated with HADS scores, suggesting that mood disorders following disasters may have multifactorial causes beyond physical trauma.

Perfectionistic Self-Presentation and Psychopathology: A Systematic Review and Meta-Analysis.

Decades of research implicate perfectionism as a risk factor for psychopathology. Most research has focused on trait perfectionism (i.e., needing to be perfect), but there is a growing focus on perfectionistic self-presentation (PSP) (i.e., the need to seem perfect). The current article reports the results of a meta-analysis of previous research on the facets of PSP and psychopathology outcomes (either clinical diagnoses of psychiatric disorders or symptoms of these disorders). A systematic literature search retrieved 30 relevant studies (37 samples; N = 15,072), resulting in 192 individual effect-size indexes that were analysed with random-effect meta-analysis. Findings support the notion of PSP as a transdiagnostic factor by showing that PSP facets are associated with various forms of psychopathology, especially social anxiety, depression, vulnerable narcissism and-to lesser extent-grandiose narcissism and anorexia nervosa. The results indicated that there both commonalities across the three PSP and some unique findings highlighting the need to distinguish among appearing perfect, avoiding seeming imperfect and avoiding disclosures of imperfections. Additional analyses yielded little evidence in the results across studies including undergraduates, community samples and clinical samples. Our discussion includes a focus on factors and processes that contribute to the association between PSP and psychopathology.

The effect of lavender on mood disorders associated with the use of combined oral contraceptives (COCs): a triple-blinded randomized controlled trial.

BACKGROUND: The use of contraceptive methods is influenced by their effectiveness, availability, and minimal side effects. OCPs are one of the most effective and widely used methods of pregnancy prevention worldwide. This method not only prevents pregnancy but also helps prevent and treat other diseases. One of the main reasons for discontinuing this method is the emotional disturbances associated with its use. Lavender is an evergreen, fragrant plant that has gained significant attention for its anti-anxiety effects. This study was conducted to investigate the effect of lavender essential oil capsules on mood disorders during the use of COCs. METHODS: This triple-blinded clinical trial was conducted on 60 married women (aged 15-49 years old) who were consumers of COCs, referring to 26 health centers in Tabriz, Iran. The participants were randomly assigned to either the intervention (consuming one gelatin capsule containing 80 mg LEO daily) or control (consuming one placebo capsule daily) group. The intervention continued for 56 days. Scores for positive and negative were determined using the Positive and Negative Affect Schedule (PANAS) questionnaire; and for stress, depression, and anxiety were measured using the DASS-21 questionnaire on day's 28th and 56th post-intervention. Data analysis was conducted using the t-test and ANOVA with repeated measures, and a p-value of < 0.05 was considered significant for all analyses. RESULTS: A statistically significant difference was observed in mood disorders, stress, and depression between women receiving LEO or placebo. The consumption of LEO increased the positive mood on day 28 [MD (95% CI): 4.5 (2.1 to 7.0), p = 0.001] and day 56 [5.9 (3.4 to 8.3), p < 0.001] while decreased the negative mood on day 28 [MD (95% CI): -3.5 (-5.3 to -1.3), p < 0.001] and day 56 [-4.3 (-6.3 to -2.2), p < 0.001], stress on day 28 [MD (95% CI): -4.9 (-7.1 to -2.8), p = 0.001] and day 56 [-5.3 (-7.6 to -3.1), p < 0. 001], and depression on day 28 [MD (95% CI): -3.0 (-4.9 to 1.1), p = 0.003] and day 56 [-3.1 (-5.0 to 1.2), p = 0.002]. There was no statistically significant difference between the two groups in terms of anxiety. CONCLUSIONS: The consumption of LEO with COCs improved mood disorders and reduced stress and depression. The use of hormonal contraceptives and mood changes should be considered by providers. Therefore, regarding the possibility of mood changes, it is expected that appropriate counseling and education will be provided to women who consume COC., providing appropriate solutions, including the simultaneous use of LEO.

Anxiety symptoms preceding suicide: A Swedish nationwide record review.

BACKGROUND: The literature on the relationship between anxiety and suicidal behaviors is limited and findings are mixed. This study sought to determine whether physicians noted anxiety symptoms and suicidality in their patients in the weeks and months before suicide. METHODS: Data were derived from a nationwide medical record review of confirmed suicides in Sweden in 2015. Individuals with at least one documented physician consultation in any health care setting during 12 months before suicide (N = 956) were included. Clinical characteristics were compared between decedents with and without a notation of anxiety symptoms. Odds ratios were calculated to estimate associations between anxiety symptoms and suicidality in relation to suicide proximity. RESULTS: Anxiety symptoms were noted in half of individuals 1 week before suicide. Patients with anxiety were characterized by high rates of depressive symptoms, ongoing substance use issues, sleeping difficulties, and fatigue. After adjustment for mood disorders, the odds of having a notation of elevated suicide risk 1 week before death were doubled in persons with anxiety symptoms. Associations were similar across time periods (12 months - 1 week). Two-thirds had been prescribed antidepressants at time of death. LIMITATIONS: Data were based on physicians' notations which likely resulted in underreporting of anxiety depending on medical specialty. Records were not available for all decedents. CONCLUSIONS: Anxiety symptoms were common in the final week before suicide and were accompanied by increases in documented elevated suicide risk. Our findings can inform psychiatrists, non-psychiatric specialists, and GPs who meet and assess persons with anxiety symptoms.

Suicide risk after discharge from in-patient psychiatric care: A 15-year retrospective cohort study of individual patient data.

BACKGROUND: Suicide rates are known to be increased in patients after discharge from in-patient psychiatric treatment. However, evidence on risk factors for suicide within this patient group are contradictory. Thus, this study aims to investigate suicide after discharge from a sizeable psychiatric care facility to determine associated risk factors. METHODS: Data on individual patient level from a 15-year single-centre cohort were linked to data from the national death registry and cumulative incidence rates were calculated applying competing risk models. Independent variables included the patients' sex, age at admission, diagnosis, and length of admission. For each of these factors, subdistribution hazards ratios were calculated using a Fine-Gray model. RESULTS: In our sample of 18,425 discharges, when using patients with the diagnosis of substance-use-disorders as a comparator, a significant increase in hazard of post-discharge suicide for male sex (SHR = 1.67;p = 0.037) as well as the discharge diagnoses of affective disorders (SHR = 3.56;p = 0.017) and neurotic stress and somatoform disorders (SHR = 3.73;p = 0.024) were found. Interestingly, the hazard of suicide significantly decreased in more recent discharges (SHR = 0.93;p = 0.006). No statistically significant association of the length of admission with the suicide risk was found (SHR = 0.98;p = 0.834). LIMITATIONS: Suicides may have been mis-identified as natural death in the national death register. CONCLUSION: Male sex and distinct diagnoses were associated with an increased risk for suicide after discharge from a psychiatric care institution. The markedly increased suicide risk within this patient collective highlights the need for the development of tools to assess suicidal behaviour in this group of patients reliably.

The Mood and Resilience in Offspring (MARIO) project: a longitudinal cohort study among offspring of parents with and without a mood disorder.

BACKGROUND: One of the most robust risk factors for developing a mood disorder is having a parent with a mood disorder. Unfortunately, mechanisms explaining the transmission of mood disorders from one generation to the next remain largely elusive. Since timely intervention is associated with a better outcome and prognosis, early detection of intergenerational transmission of mood disorders is of paramount importance. Here, we describe the design of the Mood and Resilience in Offspring (MARIO) cohort study in which we investigate: 1. differences in clinical, biological and environmental (e.g., psychosocial factors, substance use or stressful life events) risk and resilience factors in children of parents with and without mood disorders, and 2. mechanisms of intergenerational transmission of mood disorders via clinical, biological and environmental risk and resilience factors. METHODS: MARIO is an observational, longitudinal cohort study that aims to include 450 offspring of parents with a mood disorder (uni- or bipolar mood disorders) and 100-150 offspring of parents without a mood disorder aged 10-25 years. Power analyses indicate that this sample size is sufficient to detect small to medium sized effects. Offspring are recruited via existing Dutch studies involving patients with a mood disorder and healthy controls, for which detailed clinical, environmental and biological data of the index-parent (i.e., the initially identified parent with or without a mood disorder) is available. Over a period of three years, four assessments will take place, in which extensive clinical, biological and environmental data and data on risk and resilience are collected through e.g., blood sampling, face-to-face interviews, online questionnaires, actigraphy and Experience Sampling Method assessment. For co-parents, information on demographics, mental disorder status and a DNA-sample are collected. DISCUSSION: The MARIO cohort study is a large longitudinal cohort study among offspring of parents with and without mood disorders. A unique aspect is the collection of granular data on clinical, biological and environmental risk and resilience factors in offspring, in addition to available parental data on many similar factors. We aim to investigate the mechanisms underlying intergenerational transmission of mood disorders, which will ultimately lead to better outcomes for offspring at high familial risk.

Neurocognitive correlates of metabolic dysregulation in individuals with mood disorders: a systematic review and meta-analysis.

Individuals with mood disorders are predisposed to metabolic dysfunction, while those with metabolic dysregulation such as diabetes and obesity experience more severe depressive symptoms. Both metabolic dysfunction and mood disorders are independently associated with cognitive deficits. Therefore, given their close association, this study aimed to explore the association between metabolic dysfunction in individuals with mood disorders in relation to cognitive outcomes. A comprehensive search comprised of these three domains was carried out; a random-effects meta-analysis pooling mean cognitive outcomes was conducted (PROSPERO ID: CRD42022295765). Sixty-three studies were included in this review; 26 were synthesized in a quantitative meta-analysis. Comorbid metabolic dysregulation was associated with significantly lower global cognition among individuals with mood disorders. These trends were significant within each mood disorder subgroup, including major depressive disorder, bipolar disorder, and self-report depression/depressive symptoms. Type 2 diabetes was associated with the lowest cognitive performance in individuals with mood disorders, followed by peripheral insulin resistance, body mass index ⩾25 kg/m2, and metabolic syndrome. Significant reduction in scores was also observed among individual cognitive domains (in descending order) of working memory, attention, executive function, processing speed, verbal memory, and visual memory. These findings demonstrate the detrimental effects of comorbid metabolic dysfunction in individuals with mood disorders. Further research is required to understand the underlying mechanisms connecting mood disorders, metabolism, and cognition.

Resting-state effective connectivity is systematically linked to reappraisal success of high- and low-intensity negative emotions.

Emotion regulation is a process by which individuals modulate their emotional responses to cope with different environmental demands, for example, by reappraising the emotional situation. Here, we tested whether effective connectivity of a reappraisal-related neural network at rest is predictive of successfully regulating high- and low-intensity negative emotions in an emotion-regulation task. Task-based and resting-state functional magnetic resonance imaging (rs-fMRI) data of 28 participants were collected using ultra-high magnetic field strength at 7 Tesla during three scanning sessions. We used spectral dynamic causal modeling (spDCM) on the rs-fMRI data within brain regions modulated by emotion intensity. We found common connectivity patterns for both high- and low-intensity stimuli. Distinctive effective connectivity patterns in relation to low-intensity stimuli were found from frontal regions connecting to temporal regions. Reappraisal success for high-intensity stimuli was predicted by additional connections within the vlPFC and from temporal to frontal regions. Connectivity patterns at rest predicting reappraisal success were generally more pronounced for low-intensity stimuli, suggesting a greater role of stereotyped patterns, potentially reflecting preparedness, when reappraisal was relatively easy to implement. The opposite was true for high-intensity stimuli, which might require a more flexible recruitment of resources beyond what is reflected in resting state connectivity patterns. Resting-state effective connectivity emerged as a robust predictor for successful reappraisal, revealing both shared and distinct network dynamics for high- and low-intensity stimuli. These patterns signify specific preparatory states associated with heightened vigilance, attention, self-awareness, and goal-directed cognitive processing, particularly during reappraisal for mitigating the emotional impact of external stimuli. Our findings hold potential implications for understanding psychopathological alterations in brain connectivity related to affective disorders.

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.

Developing and Implementing a Web-Based Branching Logic Survey to Support Psychiatric Crisis Evaluations of Individuals With Developmental Disabilities: Qualitative Study and Evaluation of Validity.

BACKGROUND: Individuals with developmental disabilities (DD) experience increased rates of emotional and behavioral crises that necessitate assessment and intervention. Psychiatric disorders can contribute to crises; however, screening measures developed for the general population are inadequate for those with DD. Medical conditions can exacerbate crises and merit evaluation. Screening tools using checklist formats, even when designed for DD, are too limited in depth and scope for crisis assessments. The Sources of Distress survey implements a web-based branching logic format to screen for common psychiatric and medical conditions experienced by individuals with DD by querying caregiver knowledge and observations. OBJECTIVE: This paper aims to (1) describe the initial survey development, (2) report on focus group and expert review processes and findings, and (3) present results from the survey's clinical implementation and evaluation of validity. METHODS: Sources of Distress was reviewed by focus groups and clinical experts; this feedback informed survey revisions. The survey was subsequently implemented in clinical settings to augment providers' psychiatric and medical history taking. Informal and formal consults followed the completion of Sources of Distress for a subset of individuals. A records review was performed to identify working diagnoses established during these consults. RESULTS: Focus group members (n=17) expressed positive feedback overall about the survey's content and provided specific recommendations to add categories and items. The survey was completed for 231 individuals with DD in the clinical setting (n=161, 69.7% men and boys; mean age 17.7, SD 10.3; range 2-65 years). Consults were performed for 149 individuals (n=102, 68.5% men and boys; mean age 18.9, SD 10.9 years), generating working diagnoses to compare survey screening results. Sources of Distress accuracy rates were 91% (95% CI 85%-95%) for posttraumatic stress disorder, 87% (95% CI 81%-92%) for anxiety, 87% (95% CI 81%-92%) for episodic expansive mood and bipolar disorder, 82% (95% CI 75%-87%) for psychotic disorder, 79% (95% CI 71%-85%) for unipolar depression, and 76% (95% CI 69%-82%) for attention-deficit/hyperactivity disorder. While no specific survey items or screening algorithm existed for unspecified mood disorder and disruptive mood dysregulation disorder, these conditions were caregiver-reported and working diagnoses for 11.7% (27/231) and 16.8% (25/149) of individuals, respectively. CONCLUSIONS: Caregivers described Sources of Distress as an acceptable tool for sharing their knowledge and insights about individuals with DD who present in crisis. As a screening tool, this survey demonstrates good accuracy. However, better differentiation among mood disorders is needed, including the addition of items and screening algorithm for unspecified mood disorder and disruptive mood dysregulation disorder. Additional validation efforts are necessary to include a more geographically diverse population and reevaluate mood disorder differentiation. Future study is merited to investigate the survey's impact on the psychiatric and medical management of distress in individuals with DD.

Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS).

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Multilevel analysis of positive emotional induction: Which is the role of gender and valence on cognitive control processes?

How emotions are processed affects people's cognition and behavior. One of the most used measures to study the physiological component of emotions is heart rate (HR), where greater HR variation (range) implies greater emotional processing. Several investigations established the importance of gender modulation of these processes due to the different cultural treatment given to emotions among genders. However, very heterogeneous results are reported today, and few studies incorporated these parameters when investigating emotion modulation of cognitive processes according to individual factors. The present work consists of two studies. In a pilot study, 97 young adults, through the Self-Assessment Manikin (SAM), ranged the valence and arousal to select two positive and neutral videos. The second study analyses the role of gender and valence in the variation of subjective (SAM) and physiological (HR) indicators of emotional processing associated with performance in two cognitive tasks (Stroop and Tower of London) under two different emotional conditions. Participants were 60 adults, who were randomly assigned to positive or neutral video visualization, and their HR was registered. There was a tendency for women to have higher HR during positive videos than in neutral. While the subjective reports indicated variances in the appraisal of the videos, the heart rate did not exhibit differences across the experimental conditions. Few studies integrate emotional and cognitive components, and include physiological and subjective measures of emotional processing. These findings illustrate the importance of including various measures of emotional and cognitive processing.