Electroencephalography findings in menstrually-related mood disorders: A critical review.

The female reproductive years are characterized by fluctuations in ovarian hormones across the menstrual cycle, which have the potential to modulate neurophysiological and behavioral dynamics. Menstrually-related mood disorders (MRMDs) comprise cognitive-affective or somatic symptoms that are thought to be triggered by the rapid fluctuations in ovarian hormones in the luteal phase of the menstrual cycle. MRMDs include premenstrual syndrome (PMS), premenstrual dysphoric disorder (PMDD), and premenstrual exacerbation (PME) of other psychiatric disorders. Electroencephalography (EEG) non-invasively records in vivo synchronous activity from populations of neurons with high temporal resolution. The present overview sought to systematically review the current state of task-related and resting-state EEG investigations on MRMDs. Preliminary evidence indicates lower alpha asymmetry at rest being associated with MRMDs, while one study points to the effect being luteal-phase specific. Moreover, higher luteal spontaneous frontal brain activity (slow/fast wave ratio as measured by the delta/beta power ratio) has been observed in persons with MRMDs, while sleep architecture results point to potential circadian rhythm disturbances. In this review, we discuss the quality of study designs as well as future perspectives and challenges of supplementing the diagnostic and scientific toolbox for MRMDs with EEG.

Screening for affective dysregulation in school-aged children: relationship with comprehensive measures of affective dysregulation and related mental disorders.

Affective dysregulation (AD) is characterized by irritability, severe temper outbursts, anger, and unpredictable mood swings, and is typically classified as a transdiagnostic entity. A reliable and valid measure is needed to adequately identify children at risk of AD. This study sought to validate a parent-rated screening questionnaire, which is part of the comprehensive Diagnostic Tool for Affective Dysregulation in Children (DADYS-Screen), by analyzing relationships with comprehensive measures of AD and related mental disorders in a community sample of children with and without AD. The sample comprised 1114 children aged 8-12 years and their parents. We used clinical, parent, and child ratings for our analyses. Across all raters, the DADYS-Screen showed large correlations with comprehensive measures of AD. As expected, correlations were stronger for measures of externalizing symptoms than for measures of internalizing symptoms. Moreover, we found negative associations with emotion regulation strategies and health-related quality of life. In receiver operating characteristic (ROC) analyses, the DADYS-Screen adequately identified children with AD and provided an optimal cut-off. We conclude that the DADYS-Screen appears to be a reliable and valid measure to identify school-aged children at risk of AD.

Executive function in children with disruptive mood dysregulation disorder compared to attention-deficit/hyperactivity disorder and oppositional defiant disorder, and in children with different irritability levels.

Addressing current challenges in research on disruptive mood dysregulation disorder (DMDD), this study aims to compare executive function in children with DMDD, children with attention-deficit/hyperactivity disorder (ADHD), and children with oppositional defiant disorder (ODD). We also explore associations between irritability, a key DMDD characteristic, and executive function in a clinical sample regardless of diagnosis. Our sample include children (6-12 years) referred to child psychiatric clinics. Measures of daily-life (parent-reported questionnaire) and performance-based (neuropsychological tasks) executive function were applied. Identifying diagnoses, clinicians administered a standardized semi-structured diagnostic interview with parents. Irritability was assessed by parent-report. First, we compared executive function in DMDD (without ADHD/ODD), ADHD (without DMDD/ODD), ODD (without DMDD/ADHD) and DMDD + ADHD (without ODD). Second, we analyzed associations between executive function and irritability using the total sample. In daily life, children with DMDD showed clinically elevated and significantly worse emotion control scores compared to children with ADHD, and clinically elevated scores on cognitive flexibility compared to norm scores. Children with DMDD had significantly less working memory problems than those with ADHD. No differences were found between DMDD and ODD. Increased irritability was positively associated with emotional dyscontrol and cognitive inflexibility. For performance-based executive function, no diagnostic differences or associations with irritability were observed. We discuss how, in daily life, children with high irritability-levels get overwhelmed by feelings without accompanying regulatory capacities.

Mood Disorder Severity and Subtype Classification Using Multimodal Deep Neural Network Models.

The subtype diagnosis and severity classification of mood disorder have been made through the judgment of verified assistance tools and psychiatrists. Recently, however, many studies have been conducted using biomarker data collected from subjects to assist in diagnosis, and most studies use heart rate variability (HRV) data collected to understand the balance of the autonomic nervous system on statistical analysis methods to perform classification through statistical analysis. In this research, three mood disorder severity or subtype classification algorithms are presented through multimodal analysis of data on the collected heart-related data variables and hidden features from the variables of time and frequency domain of HRV. Comparing the classification performance of the statistical analysis widely used in existing major depressive disorder (MDD), anxiety disorder (AD), and bipolar disorder (BD) classification studies and the multimodality deep neural network analysis newly proposed in this study, it was confirmed that the severity or subtype classification accuracy performance of each disease improved by 0.118, 0.231, and 0.125 on average. Through the study, it was confirmed that deep learning analysis of biomarker data such as HRV can be applied as a primary identification and diagnosis aid for mental diseases, and that it can help to objectively diagnose psychiatrists in that it can confirm not only the diagnosed disease but also the current mood status.

Interictal Dysphoric Disorder: A disorder with distinct nosography or atypical symptomatology of mood disorders in people with epilepsy? Results from a systematic review.

INTRODUCTION: Mood disorders are the most frequent comorbidities in people with epilepsy. The term Interictal Dysphoric Disorder (IDD) has been used to describe a condition where at least three out of eight symptoms must be present for diagnosis. Symptoms are grouped into three symptom clusters of four "labile depressive" symptoms (anergia, depressed mood, insomnia, and pain), two "labile affective" symptoms (anxiety and fear), and two specific symptoms (euphoric moods and paroxysmal irritability), which are described and can be present in people with epilepsy. There is debate about whether IDD is a distinct disease, or if it is simply a special manifestation of mood disorders in epilepsy. For instance, it may represent an atypical presentation of depression in this population. METHODS: We conducted a systematic review of the literature in 3 databases with the terms "Interictal Dysphoric Disorder" and "mood disorder". A total of 130 articles were selected and, after removing the duplicated applying eligibility criteria, 12 articles were included. RESULTS: Six articles showed positive evidence for the validation of IDD as an independent nosological entity; in contrast, five articles reported inconclusive findings regarding the question; one explicitly questioned significant differences between IDD and mood disorders as nosological constructs. The data available and presented in this systematic review is insufficient to confirm IDD as a distinct diagnostic category. Nevertheless, it is worth noting other researchers have found some validity in this concept, highlighting the strong connection between mood disorders and epilepsy. CONCLUSION: Further research in this area is needed, and additional systematic reviews focusing on other aspects of the construct, such as neurobiological mechanisms, may prove to be helpful.

Subjective quality of life factorial structure across mental disorders: should we switch to assessing dimensions?

A two-factor structure of subjective quality of life (SQoL) was established for patients with schizophrenia with the dimensions being 'Life and Health' and 'Living Environment'. This study investigated whether the same structure applies in patients with mood and anxiety disorders and, if so, whether the dimension scores differ between the three diagnostic groups. SQoL data of 1366 patients with mood and 419 patients with anxiety disorders obtained on the Manchester Short Assessment of Quality of Life (MANSA) were retrieved from 3 multisite studies. We performed Confirmatory Factor Analyses (CFAs) based on the MANSA SQoL items of each diagnostic sample. Next, through a series of Kruskal-Wallis and Mann-Whitney tests, we compared the scores of the two factors across patients with mood disorders, anxiety disorders and schizophrenia. The two CFAs showed adequate fit of the two-factor structure across mood and anxiety disorders. The dimension scores on 'Life and Health' differed significantly between all three diagnostic groups. They were lowest in patients with anxiety disorders, higher in patients with mood disorders and highest in patients with schizophrenia. However, on the 'Living Environment' dimension, patients with mood disorders had significantly higher scores than patients with schizophrenia, whilst patients with anxiety disorders did not differ significantly from either other group. The findings suggest that a two-factor structure of SQoL applies across mental disorders. The two dimensions vary across diagnostic groups in different ways. Assessing two dimensions of SQoL may provide more specific and relevant information than global scores.

Chronic Pain and Mood Disorders Are Not Barriers to Symptom Improvement Under Collaborative Co-managed Care (C3).

OBJECTIVES: Patients with comorbid chronic pain and mood disorders have more severe gastrointestinal disease and higher healthcare expenses than their peers. We sought to determine whether management under our innovative Collaborative Co-Managed Care (C3) general gastroenterology care model improved outcomes. METHODS: Patient questionnaires completed by outpatients at our GI Motility Center were analyzed alongside demographic information to determine predictors of response to treatment based on adequate relief of gastrointestinal symptoms and improvement in quality of life. RESULTS: These comorbidities did not significantly impair response and may be associated with improved response under our model. CONCLUSIONS: The C3 general gastroenterology care model anchors on setting expectations and team-based communication and improves outcomes of, and access to, care.

Type D Personality as a Marker of Poorer Quality of Life and Mood Status Disturbances in Patients with Skin Diseases: A Systematic Review.

Type D personality is characterized by social inhibition and negative affectivity. Poorer outcomes and worse quality of life have been linked to type D personality in patients with a variety of non-dermatological diseases. Despite increasing evidence of the importance of type D personality in skin diseases, there are no reviews on this subject. The aim of this review is to summarize the current evidence regarding type D personality and skin diseases. A systematic search was performed using Medline and Web of Science databases from inception to 11 October 2022. Studies addressing the presence of type D personality, its associated factors, its impact on the outcomes of the disease or the quality of life of the patients were included in the systematic review. A total of 20 studies, including 3,124 participants, met the eligibility criteria and were included in the review. Acne, hidradenitis suppurativa, psoriasis, melanoma, atopic dermatitis, chronic spontaneous urticaria and pruritic disorders were the main diseases assessed. Type D personality was more frequent among patients with skin diseases than among controls. Type D personality was found to be associated with poorer quality of life and higher rates of psychological comorbidities in patients with skin diseases. In conclusion, type D personality appears to be a marker of patients with increased risk of poorer quality of life and higher rates of psychological comorbidities. Screening for type D personality in specialized dermatology units might be beneficial to identify patients who are more psychologically vulnerable to the consequences of chronic skin diseases.

Affectivity in danish patients with emotional disorders: assessing the validity of the Positive and Negative Affect Schedule (PANAS).

BACKGROUND: The Positive and Negative Affect Schedule (PANAS) was designed to measure trait positive affect (PA) and trait negative affect (NA). METHODS: The Danish PANAS was administered to outpatients with depression and anxiety disorders. Internal consistency was assessed using Cronbach's alpha and McDonald's omega and factorial structure was evaluated using confirmatory factor analysis (CFA). Convergent validity was evaluated by means of correlations with the negative affectivity and the detachment domain of the Personality Inventory for DSM-5 Short Form (PID-5-SF), the Hamilton Anxiety Rating Scale 6 (HARS-6) and the Hamilton Depression Rating Scale 6 (HDRS-6). RESULTS: PANAS Scores of 256 patients were analyzed. Cronbach's alpha and McDonald's omega showed good internal consistency for both the PA score (alpha = .84 and omega = .89) and the NA score (alpha = .86 and omega = .90). CFA analysis confirmed a structure with two factors corresponding to the PA and NA factors. PA was negatively correlated with the detachment domain of PID-5 (r = -.47), HARS-6 (r = -.15) and HDRS-6 (r = -.37). NA was positively correlated with PID-5-SF negative affectivity domain (r = .43), HARS-6 (r = .51) and HDRS-6 (r = .52). DISCUSSION: The Danish PANAS has promising internal consistency and construct validity, which are comparable to other studies of the instrument.

Navigating young minds: reliability and validity of the Greek version of kiddie - schedule for affective disorders and schizophrenia - present and lifetime DSM-5 version (K-SADS-PL-GR-5).

BACKGROUND: The Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (K-SADS-PL) is one of the most popular semi-structured psychiatric interviews for children and adolescents. Its latest DSM-5 version (K-SADS-PL DSM-5) has only recently been adapted and validated in various languages. In the present study, we aimed to investigate the reliability and validity of the Greek version of the K-SADS-PL DSM-5. METHODS: A total of 137 patients consecutively referred for admission, aged 7-17, were included. The K-SADS-PL DSM-IV was translated and adapted to correspond to DSM-5 categories. Convergent and divergent validity were assessed against two self-report rating scales, Children's Depression Inventory (CDI) and Screen for Child Anxiety Related Emotional Disorders (SCARED). Inter-rater reliability was calculated exclusively for instances where a diagnosis involved three or more patients. RESULTS: Our findings revealed good to excellent inter-rater reliability and good to excellent consensual validity across most psychiatric diagnoses, except for panic disorder. Diagnostic efficiency, measured by sensitivity, specificity, positive and negative predictive values, consistently showed high specificity and negative predictive validity across all diagnostic categories. CONCLUSIONS: These findings support the applicability of the Greek version of the K-SADS-PL DSM-5 as a reliable and valid diagnostic tool in Greek-speaking populations.

Accuracy of the Arabic HCL - 32 and MDQ in detecting patients with bipolar disorder.

BACKGROUND: Studies about the two most used and validated instruments for the early detection of Bipolar Disorder (BD), the 32 - item Hypomania Checklist (HCL - 32) and the Mood Disorder Questionnaire (MDQ), are scarce in non-Western countries. This study aimed to explore the reliability, factor structure, and criterion validity of their Arabic versions in a sample of Tunisian patients diagnosed with mood disorders. METHODS: The sample included 59 patients with BD, 86 with unipolar Major Depressive Disorder (MDD) and 281 controls. Confirmatory factor analysis was applied to show that a single global score was an appropriate summary measure of the screeners in the sample. Receiver Operating Characteristic analysis was used to assess the capacity of the translated screeners to distinguish patients with BD from those with MDD and controls. RESULTS: Reliability was good for both tools in all samples. The bifactor implementation of the most reported two-factor model had the best fit for both screeners. Both were able to distinguish patients diagnosed with BD from putatively healthy controls, and equally able to distinguish patients diagnosed with BD from patients with MDD. CONCLUSION: Both screeners work best in excluding the presence of BD in patients with MDD, which is an advantage in deciding whether or not to prescribe an antidepressant.

Absconding among admitted patients with bipolar affective disorder diagnosis in Uganda.

BACKGROUND: Hospitalization is often necessary for individuals with Bipolar affective Disorder (BAD) during severe manic or depressive episodes, as well as for stabilizing treatment regimens. However, a significant proportion of patients admitted for treatment of BAD abscond or leave the hospital without permission during their stay. In addition, patients managed for BAD may have unique characteristics that might force them into absconding. For example, the high prevalence of co-morbid substance use disorder - craving to use substances, suicidal behaviors - attempts to die by suicide, and cluster B personality disorders - characterized by impulsive acts. It is, therefore, essential to understand the factors contributing to absconding among patients with BAD, to facilitate designing strategies for preventing and managing this behavior. METHOD: This study was based on a retrospective chart review of the inpatients diagnosed with BAD at a tertiary psychiatry facility in Uganda from January 2018 to December 2021. RESULTS: Approximately 7.8% of those with BAD absconded from the hospital. The likelihood of absconding among those with BAD increased with the use of cannabis [adjusted odds ratio (aOR) = 4.00, 95% confidence interval (CI) = 1.22-13.09, p-value = 0.022] and having mood lability [aOR = 2.15, 95% CI = 1.10-4.21, p-value = 0.025]. However, receiving psychotherapy during the admission (aOR = 0.44, 95 CI = 0.26-0.74, p-value = 0.002) and treatment with haloperidol (aOR = 0.39, 95% CI = 0.18-0.83, p-value = 0.014) reduced the likelihood of absconding. CONCLUSION: Absconding among patients with BAD is common in Uganda. Those with symptoms of affective lability and those with comorbid cannabis use tend to abscond more, while those who receive haloperidol and psychotherapy are less likely to abscond.

Developing Empirical Latent Profiles of Impulsive Aggression and Mood in Youths across Three Outpatient Samples.

OBJECTIVE: Aggression with impulsivity and reactivity (AIR) may distinguish a subset of youth from those with attention problems, rule-breaking behavior, or mood disorders, potentially with differential treatment response. Yet, DSM-5 and ICD-10 do not include an AIR diagnosis. Thus, we empirically grouped youths into profiles based on AIR, manic, depressive, rule-breaking, and self-harm behaviors; examined which profiles replicated across three samples; and characterized profile sets on demographic and clinical features. METHOD: After harmonizing data from three samples (n = 679, n = 392, n = 634), Latent Profile Analysis (LPA) assigned youth to profiles based on caregiver-reported measures of AIR, manic, depressive, rule-breaking, and self-harm behaviors. Profiles from each sample were grouped into sets based on profile similarity. Analyses tested differences in diagnoses, sex, and race, age, functioning, and mood severity. RESULTS: Eight-profile solutions fit best. Seven profiles replicated across samples: high AIR and self-harm, lower depressive and manic scores; high AIR, manic symptoms, and self-harm; high depression symptoms; three smaller sets with high manic and depressive symptoms and moderate AIR; and two high rates of bipolar diagnoses and family bipolar history. Two sets were high on both AIR and mood symptoms, were the most impaired, and had the highest comorbidity. CONCLUSIONS: Analyses support an empirical definition of AIR, separate from mood disorders. Profile sets distinguished by level of AIR and mood symptoms differed in demographic and diagnostic characteristics as well as functioning. Importantly, a set emerged with high AIR but low mood indicators and with high rates of ADHD and ODD, but not mood disorder.

Behavioral Apophenia and Dimensions of Psychoticism in Adolescents with and without Mood Disorders.

Apophenia is the tendency to falsely detect meaningful relationships and may indicate susceptibility to more extreme expressions on the psychotic spectrum. This pilot investigated the fragmented ambiguous object task (FAOT), a new measure designed to assess apophenia behaviorally in a sample of adolescents with and without mood disorders using an image recognition task. Our primary hypothesis was that increased image recognition would be associated with PID-5 psychoticism. Participants were 33 (79% female) adolescents with (n = 18) and without (n = 15) mood disorders. Consistent with predictions, increased recognition of ambiguous images correlated positively with psychoticism. There was also moderate evidence for long-term stability of FAOT apophenia scores over time (mean interval of approximately 10 months). These findings offer preliminary evidence that the FAOT may be reflective of underlying psychoticism in our target population.

Digital Phenotyping for Mood Disorders: Methodology-Oriented Pilot Feasibility Study.

BACKGROUND: In the burgeoning area of clinical digital phenotyping research, there is a dearth of literature that details methodology, including the key challenges and dilemmas in developing and implementing a successful architecture for technological infrastructure, patient engagement, longitudinal study participation, and successful reporting and analysis of diverse passive and active digital data streams. OBJECTIVE: This article provides a narrative rationale for our study design in the context of the current evidence base and best practices, with an emphasis on our initial lessons learned from the implementation challenges and successes of this digital phenotyping study. METHODS: We describe the design and implementation approach for a digital phenotyping pilot feasibility study with attention to synthesizing key literature and the reasoning for pragmatic adaptations in implementing a multisite study encompassing distinct geographic and population settings. This methodology was used to recruit patients as study participants with a clinician-validated diagnostic history of unipolar depression, bipolar I disorder, or bipolar II disorder, or healthy controls in 2 geographically distinct health care systems for a longitudinal digital phenotyping study of mood disorders. RESULTS: We describe the feasibility of a multisite digital phenotyping pilot study for patients with mood disorders in terms of passively and actively collected phenotyping data quality and enrollment of patients. Overall data quality (assessed as the amount of sensor data obtained vs expected) was high compared to that in related studies. Results were reported on the relevant demographic features of study participants, revealing recruitment properties of age (mean subgroup age ranged from 31 years in the healthy control subgroup to 38 years in the bipolar I disorder subgroup), sex (predominance of female participants, with 7/11, 64% females in the bipolar II disorder subgroup), and smartphone operating system (iOS vs Android; iOS ranged from 7/11, 64% in the bipolar II disorder subgroup to 29/32, 91% in the healthy control subgroup). We also described implementation considerations around digital phenotyping research for mood disorders and other psychiatric conditions. CONCLUSIONS: Digital phenotyping in affective disorders is feasible on both Android and iOS smartphones, and the resulting data quality using an open-source platform is higher than that in comparable studies. While the digital phenotyping data quality was independent of gender and race, the reported demographic features of study participants revealed important information on possible selection biases that may result from naturalistic research in this domain. We believe that the methodology described will be readily reproducible and generalizable to other study settings and patient populations given our data on deployment at 2 unique sites.

Diagnostic instruments for the assessment of disruptive mood dysregulation disorder: a systematic review of the literature.

Disruptive mood dysregulation disorder (DMDD) involves non-episodic irritability and frequent severe temper outbursts in children. Since the inclusion of the diagnosis in the DSM-5, there is no established gold-standard in the assessment of DMDD. In this systematic review of the literature, we provide a synopsis of existing diagnostic instruments for DMDD. Bibliographic databases were searched for any studies assessing DMDD. The systematic search of the literature yielded K = 1167 hits, of which n = 110 studies were included. The most frequently used measure was the Kiddie Schedule for Affective Disorders and Schizophrenia DMDD module (25%). Other studies derived diagnostic criteria from interviews not specifically designed to measure DMDD (47%), chart review (7%), clinical diagnosis without any specific instrument (6%) or did not provide information about the assessment (9%). Three structured interviews designed to diagnose DMDD were used in six studies (6%). Interrater reliability was reported in 36% of studies (ranging from κ = 0.6-1) while other psychometric properties were rarely reported. This systematic review points to a variety of existing diagnostic measures for DMDD with good reliability. Consistent reporting of psychometric properties of recently developed DMDD interviews, as well as their further refinement, may help to ascertain the validity of the diagnosis.

Validation of the Italian version of the clinician affective reactivity index (CL-ARI).

INTRODUCTION: Irritability represents a transdiagnostic symptom in youths, which can become a predictor of long-term psychosocial adversity. Yet, few tools investigate this symptom in childhood. The aim of this study was to evaluate the psychometric properties of the CL-ARI in an Italian population, analyzing the correlations between irritability and other pathological constructs. MATERIALS AND METHODS: A cross-sectional study was carried out in a Child Neuropsychiatry Unit in Rome. A transdiagnostic sample of 67 youths aged 7-17 years, which underwent to a psychodiagnostic evaluation, was administered by a clinician with the translated version of the CL-ARI, along with tools exploring irritability and other constructs (depressive symptoms, anxiety, global impairment in functioning). RESULTS: The most frequent diagnosis obtained by the psychodiagnostic evaluation was anxiety disorder, followed by disruptive mood dysregulation disorder (DMDD) and no diagnosis. Cronbach's alpha values revealed good internal consistency for the total score (0.86), as well as for the score of each subscale of the tool (0.81 for temper outbursts, 0.89 for irritable mood, 0.71 for impairment). Test-retest reliability showed excellent values (ICC 0.89 to 0.98), and criterion validity exhibited good correlation among the sub-scales and between each sub-scale and the total score. Finally, positive correlations were found between total scores of the parent and the child interview, and between the CL-ARI, the measure of DMDD severity (CGI) and of depressive symptoms (CDI 2). CONCLUSIONS: These data confirmed that the CL-ARI is a promising tool designed to intercept irritability, with good psychometric properties. Further research on the assessment of irritability is critical and thus encouraged.

The prevalence of self-harm and mental disorders among individuals with intellectual disabilities.

OBJECTIVE: Mental health disorders are prevalent among individuals with intellectual disabilities (ID). However, there is a lack of research on the impact of concomitant autism spectrum disorders (ASD) or attention deficit hyperactivity disorder (ADHD) on the mental health within this population. We aimed to investigate the prevalence of mental health disorders and registered healthcare visits due to self-harm among individuals with ID. METHOD: We used administrative data for all healthcare with at least one recorded diagnosis of mental health disorder or self-harm during 2007-2017 among people with a diagnosis of Down syndrome (DS; n = 1298) and with ID without DS (IDnonDS; n = 10,671) using the rest of the population in Stockholm Region (n = 2,048,488) for comparison. RESULTS: The highest odds ratios for a mental health disorder were present in females with IDnonDS (9.01) followed by males with IDnonDS (8.50), compared to the general population. The ORs for self-harm among individuals with IDnonDS were high (8.00 for females and 6.60 for males). There were no registered cases of self-harm among individuals with DS. The prevalence of an anxiety or affective disorder was higher among individuals with ID including DS with concomitant ASD or ADHD. Neighbourhood socio-economic status was associated with a lower occurrence of mental health disorders and self-harm in wealthier areas for all outcomes and for all groups. CONCLUSIONS: Self-harm and psychiatric comorbidities were common among individuals with ID without DS with an attenuated difference among those with concomitant ASD or ADHD, which calls for attention.

Research and Diagnostic Algorithmic Rules (RADAR) for mood disorders, recurrence of illness, suicidal behaviours, and the patient's lifetime trajectory.

The top-down Diagnostic and Statistical Manual/International Statistical Classification of Diseases categories of mood disorders are inaccurate, and their dogmatic nature precludes both deductive (as indisputable) and inductive (as top-down) remodelling of case definitions. In trials, psychiatric rating scale scores employed as outcome variables are invalid and rely on folk psychology-like narratives. Using machine learning techniques, we developed a new precision nomothetic model of mood disorders with a recurrence of illness (ROI) index, a new endophenotype class, namely Major Dysmood Disorder (MDMD), characterised by increased ROI, a more severe phenome, and more disabilities. Nonetheless, our previous studies did not compute Research and Diagnostic Algorithmic Rules (RADAR) to diagnose MDMD and score ROI, lifetime (LT), and current suicidal behaviours, as well as the phenome of mood disorders. Here, we provide rules to compute bottom-up RADAR scores for MDMD, ROI, LT and current suicidal ideation and attempts, the phenome of mood disorders, and the lifetime trajectory of mood disorder patients from a family history of mood disorders and substance abuse to adverse childhood experiences, ROI, and the phenome. We also demonstrate how to plot the 12 major scores in a single RADAR graph, which displays all features in a two-dimensional plot. These graphs allow the characteristics of a patient to be displayed as an idiomatic fingerprint, allowing one to estimate the key traits and severity of the illness at a glance. Consequently, biomarker research into mood disorders should use our RADAR scores to examine pan-omics data, which should be used to enlarge our precision models and RADAR graph.

The relationship between mood disorder diagnosis and experiencing an unmet health-care need in Canada: findings from the 2014 Canadian Community Health Survey.

BACKGROUND: Despite Canada's universal health-care system, millions of Canadians experience unmet health-care needs (UHCN). People with mood disorders may be at higher risk of UHCN due to barriers such as stigma and gaps in health-care services. AIM: We aimed to examine the relationship between having a diagnosed mood disorder and experiencing UHCN using a recent, nationally representative survey. METHODS: Using the 2014 Canadian Community Health Survey, we used multivariate logistic regression to estimate the association between mood disorder and UHCN in the past 12 months, adjusting for sociodemographic variables and health status. RESULTS: Among 52,825 respondents, 11.8% reported UHCN. Respondents with a diagnosed mood disorder were more likely to report UHCN [adjusted odds ratio (OR) 1.61, 95% confidence interval (CI) 1.38, 1.89]. Among respondents with a regular doctor, people with mood disorders were still more likely to report UHCN (OR 1.63, 95% CI 1.38, 1.93). Sensitivity analyses using propensity score and missing data imputation approaches resulted in similar estimates. CONCLUSIONS: Adults diagnosed with a mood disorder are more likely to report UHCN in the past year, even those with a regular doctor. Our findings suggest that barriers beyond physician attachment may impact access to care for people with mood disorders.