Diagnosis Of Mood Disorder Research Articles

Exploring Macroscopic and Microscopic Fluctuations of Elicited Facial Expressions for Mood Disorder Classification

In the clinical diagnosis of mood disorder, a large proportion of patients with bipolar disorder (BD) are misdiagnosed as having unipolar depression (UD). Generally, long-term tracking is required for patients with BD to conduct an appropriate diagnosis by using traditional diagnosis tools. A one-time diagnosis system for facilitating diagnosis procedures is thus highly desirable. Accordingly, in this study, the facial expressions of patients with BD, patients with UD, and healthy controls elicited by emotional video clips were used for conducting mood disorder classification; the classification was performed by exploring the temporal fluctuation characteristics among the three groups. First, macroscopic facial expressions characterized by action units (AUs) were applied for describing the temporal transformation of muscles. Modulation spectrum analysis was applied to extract short-term intensity variations in the AUs. An interval-based multilayer perceptron (MLP) neural network was then used to classify mood disorder on the basis of the detected AU intensities. Moreover, motion vectors (MVs) were employed to describe subtle changes in facial expressions in the microscopic view. Eight basic orientations of MV change were considered for representing microfluctuation. Wavelet decomposition was then applied to extract entropy and energy features in different frequency bands. A long short-term memory model was finally used to model long-term variations for conducting mood disorder classification. A decision-level fusion approach was conducted on the combined results of macroscopic and microscopic facial expressions. For evaluating the described methods, the facial expressions elicited from the 36 subjects (12 from each of the BD, UD, and control groups) were used in 12-fold cross-validation experiments. Approaches for macroscopic and microscopic expressions achieved classification accuracies of 63.9 and 66.7 percent, respectively, and the accuracy of the fusion approach reached 72.2 percent. The results indicate that macroscopic and microscopic view descriptors are complementary to each other and helpful for conducting mood disorder classification.

Physical Activity Health Communication for Adults With Mood Disorders in the United States.

Using national representative data, this study sought to examine receipt of physical activity communication and counseling among adults with mood disorders in comparison to the general population in the United States. The sample consisted of adult primary-care visits in the National Hospital Ambulatory Medical Care and National Ambulatory Medical Care Surveys. Multivariable logistic regression was used to examine the relationship between mental health status and receipt of physical activity communication and counseling. Overall, less than 20% of visits included physical activity communication and counseling. Controlling for covariates, visits for adults with a mood disorder diagnosis were associated with an increased odds of including physical activity communication and counseling, odds ratio = 1.25, 95% confidence interval = [1.08, 1.45]. Although adults with mood disorders were more likely to receive physical activity communication and counseling, most primary-care visits for adults in the United States did not include physical activity communication and counseling.

Long-Term Retention in an Outpatient Behavioral Health Clinic With Buprenorphine.

Despite high comorbidity between substance use disorders and other mental health diagnoses, there is a paucity of literature on buprenorphine treatment outcomes in outpatient mental health settings. This study aimed to identify rates and predictors of outpatient buprenorphine treatment retention in a Behavioral Health Clinic (BHC). This retrospective cohort study of adults on buprenorphine used multiple logistic regression to identify clinical and demographic factors associated with 1- and 2-year treatment retention and buprenorphine adherence. Of 321 subjects, 169 (52.6%) were retained in treatment for at least 1 year; 114 (35.5%) were retained for 2 years or more. Buprenorphine adherence was 95.8% and 97.3% for 1- and 2-year retention groups, respectively. Predictors of 1-year retention included benzodiazepine co-prescription (adjusted odds ratio [AOR] = 2.4; 95% CI [1.30, 4.55]), having a diagnosis of other mood disorder (AOR = 3.4; [1.95, 5.98]), or nicotine use disorder (AOR = 2.4; [1.35, 4.27]). Predictors of 2-year retention included female gender (AOR = 2.1; [1.16, 3.73]), having a diagnosis of depressive disorder (AOR = 4.6; [1.49, 14.29]), other mood disorder (AOR = 3.6; [1.88, 6.88]), or nicotine use disorder (AOR = 2.0; [1.13, 3.52]). During the study period, 52.7% and 35.5% of BHC patients treated with buprenorphine were retained for 1 and 2 years, respectively, comparable to the studies performed within primary care. Providing buprenorphine treatment within mental health clinics may serve patients who are already engaged with mental health providers but are reluctant to start new treatment within another treatment setting. Identifying common predictors of retention can help determine which patients require additional substance use treatment support. (Am J Addict 2019;28:339-346).

Patients With Mood Disorders Require Higher Doses of Buprenorphine for Management of Opiate Use Disorder [35Q

INTRODUCTION: The purpose of this study is to compare differences in buprenorphine doses needed to treat Opiate Use Disorder (OUD) in patients with and without mood disorders. METHODS: This is a retrospective cohort study of pregnant women treated at Indiana University with OUD. IRB approval was obtained from Indiana University School of Medicine. Charts were obtained via prescription medication search. Patients were included if they had at least one outpatient visit with our center during pregnancy and delivered within the Indiana University Health system. Charts were reviewed for maternal demographics, medical history, prescription use, and delivery data. RESULTS: 266 patients were treated and 171 patients had a mood disorder: 148 with depression, 130 with anxiety, and 19 with post-traumatic stress disorder (PTSD). Over 40% of the patients had a history of dual diagnoses. Patients with a history of depression or anxiety required a higher dose of buprenorphine during pregnancy (p=0.0217, p=0.0165) compared to those without a history of mood disorder. There was no significant difference in dose in those with PTSD versus those without mood disorder. In those with a diagnosis of mood disorder, there was no difference in buprenorphine dose between women on medication versus those not on medication for depression, anxiety, and PTSD. CONCLUSION: Patients with a mood disorder require higher doses of buprenorphine compared to patients without a mood disorder. Treatment of depression, anxiety or PTSD did not show a difference in buprenorphine dose versus no treatment when a mood disorder was diagnosed.

Risk and associated factors for a future schizophrenia diagnosis after an index diagnosis of unspecified psychotic disorder: A population-based study

A significant minority of unspecified psychosis presentations progress to schizophrenia. Clinical risk factors can inform targeted referral to specialized treatment programs, but few population studies have examined this. In this study, we used health administrative data for a population-based cohort from Manitoba, Canada to characterize the risk and identify vulnerable subgroups for a future diagnosis of schizophrenia after a diagnosis of unspecified psychotic disorder. Individuals aged 13–60 years with an inpatient or outpatient diagnosis of unspecified psychotic disorder between April 1, 2007 and March 31, 2012, and without any prior diagnosis of schizophrenia or related disorder, were identified (N = 3, 289). The primary outcome was a diagnosis of schizophrenia recorded after the index diagnosis of unspecified psychotic disorder and before March 31, 2015. Adjusted hazard ratios were computed controlling for age, sex, urbanicity, income, prior diagnosis of unspecified psychotic disorder, provider making the diagnosis, prior 12-month psychiatric hospitalization, and prior 12-month diagnoses of mood, anxiety, substance use, or personality disorders, and substance-induced psychosis. A classification tree identified vulnerable subgroups. The cumulative risk of a future diagnosis of schizophrenia was 26% during the follow-up period (mean 4.5 years), with a mean time to diagnosis of 2.0 years. The most vulnerable subgroup was diagnosed by a psychiatrist, younger than 27 years, without a mood or anxiety disorder, male, and residing in a low-income neighborhood; the rate of a subsequent schizophrenia diagnosis was 61.2%. These results support that identification of specific sociodemographic and clinical factors can help clinicians counsel and intervene with those at highest risk.

Cell-Coupled Long Short-Term Memory With L -Skip Fusion Mechanism for Mood Disorder Detection Through Elicited Audiovisual Features.

In early stages, patients with bipolar disorder are often diagnosed as having unipolar depression in mood disorder diagnosis. Because the long-term monitoring is limited by the delayed detection of mood disorder, an accurate and one-time diagnosis is desirable to avoid delay in appropriate treatment due to misdiagnosis. In this paper, an elicitation-based approach is proposed for realizing a one-time diagnosis by using responses elicited from patients by having them watch six emotion-eliciting videos. After watching each video clip, the conversations, including patient facial expressions and speech responses, between the participant and the clinician conducting the interview were recorded. Next, the hierarchical spectral clustering algorithm was employed to adapt the facial expression and speech response features by using the extended Cohn-Kanade and eNTERFACE databases. A denoizing autoencoder was further applied to extract the bottleneck features of the adapted data. Then, the facial and speech bottleneck features were input into support vector machines to obtain speech emotion profiles (EPs) and the modulation spectrum (MS) of the facial action unit sequence for each elicited response. Finally, a cell-coupled long short-term memory (LSTM) network with an L -skip fusion mechanism was proposed to model the temporal information of all elicited responses and to loosely fuse the EPs and the MS for conducting mood disorder detection. The experimental results revealed that the cell-coupled LSTM with the L -skip fusion mechanism has promising advantages and efficacy for mood disorder detection.

Health-care providers' perspectives on factors influencing return-to-work after surgery for nontraumatic conditions of the upper extremity

Study DesignThis study is a descriptive survey. IntroductionHealth care providers (HCPs) are key stakeholders who facilitate workers’ return to work (RTW) following upper extremity surgery. Hand therapists play a major role in this process, yet we do not know if and/or how their perspectives differ from other HCPs. Purpose of the StudyThis study examined HCPs’ opinion on factors that influence RTW after surgery for nontraumatic upper extremity conditions and whether HCPs from different disciplines differed in their opinion. MethodsHCPs (occupational therapists, physiotherapists, hand therapists, exercise physiologists, psychologists, surgeons, and general practitioners) completed a survey rating 50 factors on a worker’s ability to RTW. Each factor was scored using a 5-point Likert scale from “not” to “extremely” influential, which was later dichotomised. Agreement was indicated at 75%. The level of disagreement between disciplines was examined. ResultsRespondents (n = 787) identified 20 factors being influential on RTW. They are (in order from highest to lowest) poor pain coping (the highest, >85% of respondents), postoperative psychological state, RTW self-efficacy, employer/supervisor’s support, employer’s unwillingness for job modification, recovery expectations, job satisfaction, suitable duties availability, whether the job can be modified, and mood disorder diagnosis. There was agreement that two factors do not influence RTW, gender, and preemployment medical assessment. There was disagreement (P < .05) between HCP disciplines on six factors (obesity, comorbidities, doctors’ RTW recommendation, diagnosis, fitness, income). There were no consistent patterns with respect to which professions disagreed across all six factors. Hand therapists differed from the other disciplines for three of the factors including diagnosis, comorbidities, and doctor’s recommendation for RTW. DiscussionThe factors that stakeholders agreed as having the greatest influence were mainly related to the worker (pain and psychological factors) and the workplace and are amenable to RTW interventions. ConclusionInterventions facilitating RTW and future research should consider the factors identified by HCPs in this study.

The reliability and clinical utility of ICD-11 schizoaffective disorder: A field trial

A major goal for the revision of the International Classification of Diseases and Related Health Problems, Tenth Edition (ICD-10) is to increase the clinical utility of the diagnostic system. Schizoaffective disorder has a history of poor diagnostic reliability due to the similarities and overlap in symptoms that it shares with other disorders, especially primary psychotic and mood disorders. The present study was part of the case-controlled field trials for ICD-11 and examines how the proposed changes for schizoaffective disorder may improve differential diagnosis and diagnostic accuracy. Clinicians from around the globe (n = 873) were provided with either ICD-10 or ICD-11 diagnostic guidelines and asked to apply them to case vignettes comparing schizoaffective disorder to schizophrenia and mood disorders with psychotic symptoms. Participants were asked to respond to follow-up diagnostic questions to determine which components of the diagnostic guidelines affected diagnostic accuracy. Overall, clinicians showed small improvements in accurately diagnosing vignettes using ICD-11 over ICD-10. Results suggest the discrepancy in diagnosing schizoaffective disorder is related primarily to the presence of mood symptoms and discrepancies about whether those symptoms are more consistent with schizoaffective disorder or a mood disorder diagnosis. Continuing to identify ways to more accurately capture this symptom picture will be important in the future as well as systematic efforts to educate clinicians about differential diagnosis.

Associations among diet, the gastrointestinal microbiota, and negative emotional states in adults

ABSTRACT Objective: Habitual diet impacts mood and the human gastrointestinal (GI) microbiota. Yet, studies infrequently control for diet when evaluating associations between mood and GI microbiota. Accordingly, we aimed to investigate relationships among diet, GI microbiota, and mood in adults without mood disorders by conducting a cross-sectional examination of dietary intake, subjective emotional state, and fecal microbial taxa abundances. Methods: Adults (N = 133; 25–45 years of age) without physician-diagnosed mood disorders were studied. Fecal DNA was extracted, and the V4 region of the 16S rRNA gene was sequenced. Sequences were analyzed using QIIME2. Subjective mood state was assessed using the 42-item Depression, Anxiety, and Stress Scale (DASS-42). Habitual dietary intake was measured with the National Cancer Institute's Diet History Questionnaire II, and diet quality was evaluated with the 2010 Healthy Eating Index (HEI). Results: Relationships were observed between 28 bacterial taxa and DASS-42 scores. Sex-dependent associations were observed among 21 bacterial taxa and DASS-42 scores, including an inverse relationship between Anxiety scale scores and Bifidobacterium in females and an inverse relationship between Depression scale scores and Lactobacillus in males. HEI total fruit and dairy components were inversely associated with Depression and Stress scales, respectively. Conclusions: These results suggest GI microbes are related to mood in adults without diagnosed mood disorders and that these relationships differ by sex and are influenced by dietary fiber intake. Incorporating dietary intake data in gut-microbiota-brain studies may help clarify the roles of specific microbes and dietary components in mental health symptoms.

High Frequency of Bipolar Disorder Comorbidity in Medical Inpatients

Objective: Bipolar disorder is a severe, disabling, and recurring disorder. Some studies have shown that the frequency of bipolar disorder in patients with medical diseases is higher than healthy controls. The aim of this study was to investigate the frequency of bipolar disorders in medically ill patients hospitalized in Iranian general hospitals. Method : In this cross sectional study, 697 inpatients (342 men, 49.1%) from different wards of 3 general hospitals, with the mean age of 39.3+-10, were enrolled in the study using nonprobability sampling. Demographic questionnaire, Mood Disorder Questionnaire (MDQ) and Bipolar Spectrum Diagnostic Scale (BSDS) were used. Inclusion criteria were as follow: informed consent, age 18-65 years, ability to speak Persian, and having at least middle school education. Results: The frequency of bipolar disorder was 12.1% and 20.8% based on BSDS and MDQ, respectively. The results of both tests were positive in 7.9% of hospitalized patients. The frequency of bipolar mood disorder was significantly higher in single patients and in those with comorbidity of alcohol and substance use disorders. Conclusion: Considering the high frequency of bipolar mood disorders in hospitalized medically ill patients and its probable effects on compliance and prognosis, early screening, diagnosis, and treatment of bipolar mood disorders is important in these patients.

83 Catatonia in a 17-year-old Male Patient with Bipolar Disorder, a Case Study

AbstractStudy Objective(s)Catatonia is not only present in adults; children &amp; adolescents can suffer from catatonia but are often misdiagnosed. A study by Ghaziuddin, Dhossche and Marcotte (2012) found that 18 of the 101 child and adolescent patients had symptoms of catatonia, but only 2 actually had been given a diagnosis by their providers.Method17-year-old male who was recently discharged from the inpatient psychiatric unit with the diagnosis of Major Depressive Disorder. His discharge medication was bupropion XL 150mg daily. Within 10 days of his discharge, he was back to the emergency room with worsening anxiety and manic symptoms. At the emergency room, patient’s sister reported that he was acting differently within the last 3–4 days, and making statements that he can save the world that everyone was talking about him. He was also speaking faster than usual, having decreased need for sleep. He reported hearing voices, seeing things. Patient was admitted again, and was given diagnosis of Bipolar Mood Disorder, type I, manic phase, with psychosis. He was started on divalproex 500mg bid for mood stabilization. His Bupropion was discontinued. Gradually his Divalproex was increased to 750mg bid. During his hospital stay he developed lack of spontaneous speech, sluggish responses to questions with automatic answers such as “I don’t know”. He also developed very sluggish motor movements. There was negativism. He needed one on one support for his daily activities of living, needed step by step instructions for all ADLs.All the test results were negative including EEG, MRI and CT scan of the brain. Bush Francis catatonia rating scale was done and he scored 15. Lorazepam Challenge Test was performed, and the scale was repeated after the patient was given an IM dose of 2mg of Lorazepam, and he scored 2. At this point catatonia diagnosis was confirmed. He was started on scheduled doses of Lorazepam, gradually his Lorazepam dose was increased up to 9mg per day. His catatonia responded to Lorazepam treatment.Results17 year old male who initially hospitalized for symptoms of MDD and discharged with antidepressant, came back to the ER within 10 day with symptoms of mania with psychosis. During in-patient’s 2nd in-patient stay he developed catatonia, which was promptly diagnosed and appropriately treated with Lorazepam.ConclusionsCatatonia can happen in children &amp; adolescents with mood disorders, or with other psychiatric or medical conditions. Timely diagnosis and treatment is very crucial to avoid poor outcome, especially because treatment options for catatonia are well understood; Benzodiazepines, electroconvulsive therapy and reduction or discontinuation of antipsychotics are successful in the treatment of catatonia (Ghaziuddin, Dhossche and Marcotte, 2012).

77 Long-term Valbenazine Treatment in Patients with Schizophrenia/Schizoaffective Disorder or Mood Disorder and Tardive Dyskinesia

AbstractBackgroundPatients treated with antipsychotics, regardless of psychiatric diagnosis, are at risk for developing tardive dyskinesia (TD), a potentially debilitating drug-induced movement disorder. Valbenazine (INGREZZA; VBZ) is a novel vesicular monoamine transporter 2 (VMAT2) inhibitor approved to treat TD in adults. Data from KINECT 4 (NCT02405091) were analyzed to evaluate the long-term effects of VBZ in adults with schizophrenia/schizoaffective disorder (SZD) or mood disorder (MD) and moderate or severe TD.MethodsKINECT 4 included open-label treatment (48weeks) followed by washout (4weeks). Entry requirements included: moderate or severe TD, qualitatively assessed at screening by a blinded, external reviewer; DSM diagnosis of SZD or MD; psychiatric stability (Brief Psychiatric Rating Scale score &lt;50). Stable concomitant psychiatric medications were allowed. Dosing was initiated at 40mg, with escalation to 80mg at Wk4 if participants had a Clinical Global Impression of Change-TD score of ≥3 (minimally improved to very much worse) and tolerated 40mg. A reduction to 40mg was allowed if 80mg was not tolerated (80/40mg); participants unable to tolerate 40mg were discontinued. Safety was the primary focus, but the Abnormal Involuntary Movement Scale (AIMS) total score (sum of items 1–7) was used to evaluate changes in TD. Mean changes from baseline (BL) in AIMS total score (rated by on-site investigators) were analyzed descriptively. Safety assessments included treatment-emergent adverse events (TEAEs) and psychiatric scales (Positive and Negative Syndrome Scale [PANSS], Calgary Depression Scale for Schizophrenia [CDSS], Montgomery-Åsberg Depression Rating Scale [MADRS], Young Mania Rating Scale [YMRS], and Columbia-Suicide Severity Rating Scale [C SSRS]).ResultsOf 163 participants in the analyses, 103 completed the study. Adverse events (n=26) was the most common reason for discontinuation. Analyses included 119 participants with SZD (40mg=37; 80mg=76; 80/40mg=6) and 44 with MD (40mg=8; 80mg=31; 80/40mg=5). At Wk48, mean improvements from BL in AIMS total score were: SZD (40mg, –10.1; 80mg,–10.7); MD (40mg, 10.2; 80mg: –11.6). AIMS total scores at Wk52 (end of washout) indicated a return toward BL levels. Compared to SZD, the MD subgroup had a higher incidence of any TEAE (84% vs 61% [all doses]) but fewer TEAEs leading to discontinuation (7% vs 18%). Urinary tract infection was the most common TEAE in the MD subgroup (18%); somnolence and headache were most common in the SZD subgroup (7% each). Psychiatric status remained stable from BL to Wk48: SZD (PANSS positive, –0.7, PANSS negative, –0.6; CDSS, –0.7); MD (MADRS, –0.3; YMRS, –0.3). Most participants (95%) had no change in C-SSRS score during the study.ConclusionSustained and clinically meaningful TD improvements were observed with VBZ, regardless of primary psychiatric diagnosis. VBZ was generally well tolerated and no notable changes in psychiatric status were observed.Funding Acknowledgements: Supported by Neurocrine Biosciences, Inc.

Exploring Comorbidity Within Mental Disorders Among a Danish National Population

ImportanceIndividuals with mental disorders often develop comorbidity over time. Past studies of comorbidity have often restricted analyses to a subset of disorders and few studies have provided absolute risks of later comorbidity.ObjectivesTo undertake a comprehensive study of comorbidity within mental disorders, by providing temporally ordered age- and sex-specific pairwise estimates between the major groups of mental disorders, and to develop an interactive website to visualize all results and guide future research and clinical practice.Design, Setting, and ParticipantsThis population-based cohort study included all individuals born in Denmark between January 1, 1900, and December 31, 2015, and living in the country between January 1, 2000, and December 31, 2016. The analyses were conducted between June 2017 and May 2018.Main Outcomes and MeasuresDanish health registers were used to identify mental disorders, which were examined within the broad 10-level International Statistical Classification of Diseases and Related Health Problems, 10th Revision, subchapter groups (eg, codes F00-F09 and F10-F19). For each temporally ordered pair of disorders, overall and lagged hazard ratios and 95% CIs were calculated using Cox proportional hazards regression models. Absolute risks were estimated using competing risks survival analyses. Estimates for each sex were generated.ResultsA total of 5 940 778 persons were included in this study (2 958 293 men and 2 982 485 women; mean [SD] age at beginning of follow-up, 32.1 [25.4] years). They were followed up for 83.9 million person-years. All mental disorders were associated with an increased risk of all other mental disorders when adjusting for sex, age, and calendar time (hazard ratios ranging from 2.0 [95% CI, 1.7-2.4] for prior intellectual disabilities and later eating disorders to 48.6 [95% CI, 46.6-50.7] for prior developmental disorders and later intellectual disabilities). The hazard ratios were temporally patterned, with higher estimates during the first year after the onset of the first disorder, but with persistently elevated rates during the entire observation period. Some disorders were associated with substantial absolute risks of developing specific later disorders (eg, 30.6% [95% CI, 29.3%-32.0%] of men and 38.4% [95% CI, 37.5%-39.4%] of women with a diagnosis of mood disorders before age 20 years developed neurotic disorders within the following 5 years).Conclusions and RelevanceComorbidity within mental disorders is pervasive, and the risk persists over time. This study provides disorder-, sex-, and age-specific relative and absolute risks of the comorbidity of mental disorders. Web-based interactive data visualization tools are provided for clinical utility.

Evaluation of the diagnostic continuity of unspecified mood disorder

Objective: According to ICD-10, the diagnosis of unspecified mood disorder (UMD), coded ‘F39,’ is used when there is insufficient or contradictory information about the patient and the symptoms of mood disorder are not sufficient to diagnose a specific mood disorder. Information about the frequency, diagnostic validity and continuity of this diagnosis is unsatisfactory. Therefore, we aimed to evaluate the prevalence and diagnostic continuity of this diagnosis among individuals diagnosed with UMD in our outpatient clinic. Method: Included in the study were patients who presented to the psychiatry outpatient unit for the first time between January 2011 and December 2017, were diagnosed with mood disorder code ‘F39’ at the first admission, and presented at least three times in different periods (n=48). Outpatient unit records were evaluated retrospectively and the data were analyzed with SPSS version 19.0. Results: The mean follow-up period of 48 patients included in the study was 14.4±13.9 months. The final diagnoses of the patients after follow-up were UMD (42%), depressive disorder (25%), bipolar disorder (17%), and anxiety disorder (10%). It was found that the duration of the follow-up for individuals diagnosed with UMD was significantly shorter than for those with a different diagnosis. No significant difference was found between final diagnoses in terms of age, gender, level of education, and marital status. Conclusion: UMD has less diagnostic stability than other mood disorders. Therefore, longer follow-up durations are needed in patients with UMD, and it is crucial to reconsider the diagnosis during follow-up. Further studies with larger samples are needed to elucidate the stability of UMD.

Treating Illness Distress in Chronic Illness

Abstract. Cognitive-behavioral therapy (CBT) is an evidence-based treatment for depression and anxiety recommended for those with and without physical long-term conditions (LTCs). However, the cognitive-behavioral mechanisms targeted in CBT protocols are based on empirical cognitive-behavioral models of depression and anxiety. In these models, emotions are conceptualized as primary mental health disorders rather than a reaction to the challenges of living with a LTC commonly referred to as illness distress. This raises important clinical questions with theoretical implications. These include: Is the experience of illness distress conceptually distinct from primary mental health diagnoses of anxiety and mood disorder? Are there unique cognitive-behavioral mechanisms related to illness self-management, which should be incorporated into CBT for illness distress? How can illness self-management interventions be embedded within existing CBT protocols for depression and anxiety? To address these questions, we distinguish between primary mental health disorders and illness distress conceptually and explore the impact of this on tailored treatment planning and engagement. Second, we review how health psychology theoretical models can help to inform modifications of existing cognitive-behavioral treatments for anxiety and depression to better support the needs of individuals experiencing illness distress. Third, we provide examples of how to embed processes important for illness self-management including, illness cognitions and adherence, alongside existing CBT techniques. The mechanisms and intervention techniques discussed may help to inform the development of integrated CBT treatments for illness distress for future hypothesis testing in comparative effectiveness trials.

Understanding Mood Disorders in Children.

Mood disorders include all types of depression and bipolar disorder, and mood disorders are sometimes called affective disorders. We will discuss newly developing two issues in affective disorders in children and adolescents. Those are the new diagnostic challenges using neuroimaging techniques in affective disorders and the introduction of disruptive mood dysregulation disorder (DMDD). During the 1980s, mental health professionals began to recognize symptoms of mood disorders in children and adolescents, as well as adults. However, children and adolescents do not necessarily have or exhibit the same symptoms as adults. It is more difficult to diagnose mood disorders in children, especially because children are not always able to express how they feel. Child mental health professionals believe that mood disorders in children and adolescents remain one of the most underdiagnosed mental health problems. We are currently trying to introduce the new diagnostic technique-machine learning in children and adolescents with MDD. We will discuss the current progress in the clinical application of machine learning for MDD. After that, we would also discuss a new challenging diagnosis-DMDD. We are still suffering from a lack of evidence when trying to treat the patients with DMDD. In addition, there are some debates about the diagnostic validity of DMDD. We will explain the current situation of DMDD studies and the future directions in the study of DMDD.

Gender differences in mental health and substance use disorders and related healthcare services utilization.

Pathological gambling often co-occurs with other psychiatric disorders. Gender differences in treatment-seeking behaviors among patients with pathological gambling diagnosis remain poorly understood. This study assessed gender differences in healthcare services utilization in patients seeking treatment for pathological gambling, substance use, and mental health co-occurring conditions. Study data were derived from a representative sample of the Massachusetts All Payers Claims Database for the period 2009-2013. Descriptive analyses were performed by gender using group t-tests and Pearson's chi-square tests. Bootstrap analysis was used to account for skewed distribution of healthcare services utilization data. Multiple linear regressions were used to evaluate the association between healthcare services utilization and gender while controlling for patient's age, county, and ICD-9-CM diagnosis codes. Over two-thirds of the patients were males. Moreover, two in five patients seeking treatment had pathological gambling as principal or primary diagnosis. Females had a significantly greater number of three or more co-occurring psychiatric conditions than males. Having a diagnosis of episodic mood disorder, neurotic disorder, or adjustment reaction significantly increased the utilization of healthcare services for both genders. Females had a greater utilization of healthcare services than males for the same psychiatric diagnosis. Healthcare services utilization significantly varies by gender and type of mental health and substance use diagnosis. There are significant differences by gender in the utilization of healthcare services for the same psychiatric disorders. There is a need to address gender differences in psychiatric conditions and their related healthcare needs. (Am J Addict 2019;28:9-15).

Race and gender differences in attitudes toward help seeking among marginalized young adults with mood disorders: A mixed-methods investigation.

Race and gender differences in help seeking are well-established; however, reasons for these differences are less clear. This study examined race and gender differences in two potential contributors-perceptions of illness and attitudes toward treatment-in a sample of marginalized young adults. Interviews were conducted with young adults (age 18-25) with prior involvement in public systems of care and mood disorder diagnoses (n = 60). A quantitative interview assessed illness perceptions and attitudes followed by a qualitative interview focused on perceptions of mental illness and treatment. Analyses examined quantitative differences across four race/gender subgroups-White women (n = 13), White men (n = 6), women of color (n = 27), and men of color (n = 14), then qualitative results were reviewed for a subset of cases (n = 30) to understand differences revealed in the quantitative analyses. Women of color had lower scores on illness understanding compared to other groups and men of color had lower scores on chronicity. Attitudes including propensity toward help seeking and stigma resistance were lowest in men of color, followed by women of color. Qualitative findings supported that men of color viewed their symptoms as less chronic and managed symptoms by changing their mindset rather than formal treatments. White participants talked more about their illnesses as chronic conditions and spoke more positively of treatment. Race/gender differences were identified, particularly in relation to views of mental illness and stigma. Messaging that highlights independence and strength in relation to managing symptoms may be particularly important for young people of color. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Inflammatory gene expression in adipose tissue according to diagnosis of anxiety and mood disorders in obese and non-obese subjects

Psychiatric disorders have been widely reported to be associated with systemic inflammation upregulation and adiposity. However, there are no data that link adipose tissue inflammation to these mental disorders. The analysis of adipokines and inflammation-related markers in adipose tissue could help to elucidate the potential association between obesity and mental health. An observational study was conducted in samples of patients consisting of non-obese and obese subjects, who were diagnosed with anxiety or mood disorders. Gene expression of adiponectin (ADIPOQ), leptin (LEP) and inflammatory markers (IL6, IL1B, TNF, CCL2, CSF3, ITGAM, and PLAUR) were determined in visceral (VAT) and subcutaneous (SAT) adipose tissues. Our results showed that the gene expression of adipokines and inflammation-related markers was higher in the VAT and SAT of obese subjects compared with non-obese subjects. Regarding mental disorders, all the inflammatory genes in the VAT were significantly higher in non-obese subjects with anxiety or mood disorders than in subjects without mental disorders, except for TNF and ITGAM. Additionally, IL6 expression was significantly lower in SAT. In contrast, obese patients diagnosed with anxiety or mood disorders only showed significantly lower expression levels of IL1B in VAT and ADIPOQ in SAT when compared with obese subjects without mental disorders. These data suggest the potential involvement of VAT inflammation in anxiety and mood disorders, involving complex mechanisms which are strongly affected by obesity.

Early Menopause Is a Risk Factor for Postmenopausal Depression in Healthy Women, But Are Depressive Episodes a Risk Factor for Early Menopause?

Background: This study investigated whether age of menopause in bipolar women is different from that in healthy women and if there is a relationship between age at menopause and previous depressive episodes. Methods: We consecutively evaluated 86 euthymic and postmenopausal women who were older than 33 years and were diagnosed with bipolar disorder according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). The healthy control group comprised 100 individuals of similar age. After the diagnostic interview, bipolar patients completed the Mood Disorders Diagnosis and Follow-Up Form (SKIP-TURK). Results: Age at menopause in bipolar women was earlier than that of the controls (P = 0.001). Age at menopause correlated with age of onset of bipolar disorder (r = 0.453). A strong inverse correlation was found between the age of menopause and total duration of depressive episodes (r = -0.542). Conclusion: Early-onset bipolar disorder is associated with early ages of menopause. Age at menopause seems to be related to duration of depressive period. Considering the effects of hypoestrogenemia on ischemic heart diseases and cognitive impairment, it is important that the risk which is already high for both situations should be reduced, and depressive periods should be prevented. J Clin Gynecol Obstet. 2018;7(3-4):69-71 doi: https://doi.org/10.14740/jcgo504w