Heterogeneity in comorbidity between major depressive disorder and generalized anxiety disorder and its clinical consequences

Transdiagnostic association between subjective insomnia and depressive symptoms in major psychiatric disorders

In psychiatric disorders, comorbid depressive symptoms are associated with clinically important issues such as reduced quality of life, a poor prognosis, and increased suicide risk. Previous studies have found a close relationship between insomnia and depressive symptoms in major depressive disorder (MDD), and that actively improving insomnia heightens the improvement of depressive symptoms. This study aimed to investigate whether the association between insomnia and depressive symptoms is also found in other psychiatric disorders besides MDD. The subjects were 144 patients with MDD (n = 71), schizophrenia (n = 25), bipolar disorder (n = 22), or anxiety disorders (n = 26). Sleep status was assessed subjectively and objectively using the Athens Insomnia Scale (AIS) and sleep electroencephalography (EEG), respectively. Sleep EEG was performed using a portable EEG device. Depressive symptoms were assessed using the Beck Depression Inventory. Subjective insomnia, as defined by the AIS, was associated with depressive symptoms in all disorders. Moreover, in schizophrenia, a relation between depressive symptoms and insomnia was also found by objective sleep assessment methods using sleep EEG. Our findings suggest that the association between subjective insomnia and depressive symptoms is a transdiagnostic feature in major psychiatric disorders. Further studies are needed to clarify whether therapeutic interventions for comorbid insomnia can improve depressive symptoms in major psychiatric disorders, similar to MDD.

Anxiety and Depression Signs Among Adolescents in 26 Low- and Middle-Income Countries: Prevalence and Association With Functional Difficulties

PURPOSE

The aim of this study is to describe the occurrence of signs of depression and anxiety among adolescents from 26 low- and middle-income countries and explore the extent to which these are associated with difficulties across other functional domains.

METHODS

We analyzed randomly selected, nationally representative data from 26 countries with a total sample size of 123,975 adolescents aged 10-17 years. Data on functional difficulties, including signs of depression and anxiety, were collected by the Child Functioning Module, an instrument validated to identify the population of children with disabilities through household surveys. We estimated percentages and 95% confidence intervals of adolescents with difficulties across 11 domains of functioning, and of signs of depression and/or anxiety. We used multinomial regressions to estimate the association between difficulties in the different domains and having signs of depression only, signs of anxiety only, and signs of both depression and anxiety, relative to not presenting signs of depression or anxiety.

RESULTS

In total, 5.5% of adolescents were reported to have had signs of anxiety, 3.1% signs of depression, and 2.3% co-occurring signs of anxiety and depression. Compared to adolescents without functional difficulties, those with difficulties in one or more domains were three times more likely to have signs of depression and anxiety. The likelihood of presenting signs of depression only or signs of both depression and anxiety was significantly higher across all domains, and the highest among adolescent with difficulties to self-care and communicating. The likelihood of presenting signs of anxiety only was significantly higher across all domains except seeing and hearing, and the highest among adolescent with difficulties communicating and accepting changes.

DISCUSSION

Adolescents with functional difficulties in all domains analyzed, across different contexts, are more likely to experience depression and anxiety signs than those without such difficulties. Increasing the availability of population-level data on adolescent functional difficulties, including those related to depression and anxiety, is important in promoting inclusivity, participation, and the right of children to equal opportunities.

Childhood trauma and its impact on depressive and anxiety symptomatology in adulthood: A 6-year longitudinal study

BACKGROUND

Childhood trauma (CT) is a risk factor for depressive and anxiety disorders. However, whether CT is more strongly linked to specific clinical features of these disorders remains inconclusive. The current study comprehensively examined cross-sectional and longitudinal associations between CT and depressive/anxiety symptomatology in a large adult sample with current and remitted depressive and/or anxiety disorders.

METHODS

Baseline (n = 1803), 2-year (n = 1735), 4-year (n = 1585), and 6-year follow-up (n = 1475) data from the Netherlands Study of Depression and Anxiety were used. CT (emotional neglect, emotional/physical/sexual abuse) was assessed at baseline, while depressive/anxiety symptomatology with relevant dimensions (e.g., mood/cognitive, melancholic, general distress, and somatic depression) was assessed at each wave using self-reported questionnaires. Linear regressions and linear mixed models determined cross-sectional and longitudinal associations.

RESULTS

Individuals with CT, especially, severe CT, compared to those without CT, had significantly higher scores in overall depressive symptomatology (Cohen's d = 0.674), mood/cognitive depression (d = 0.691), melancholic depression (d = 0.587), general distress (d = 0.561), and somatic depression severity (d = 0.549). Differences were lower, but still highly significant for anxiety (d = 0.418), worry (d = 0.362), and fear/phobic symptomatology (d = 0.359). Effects were consistent across CT types and maintained over six years.

LIMITATIONS

Retrospectively-reported CT.

CONCLUSIONS

CT is a risk factor for depressive and anxiety symptomatology across all dimensions and enduring over multiple years. Screening for CT is essential to identify individuals at risk for more severe and chronic manifestations of affective disorders.

Are subtypes of affective symptoms differentially associated with change in cognition over time: A latent class analysis

BACKGROUND

In the absence of disease-modifying treatments, identifying potential psychosocial risk factors for dementia is paramount. Depression and anxiety have been identified as potential risk factors. Studies however have yielded mixed findings, lending possibility to the fact that potential constellations of co-occurring depression and anxiety symptoms may better explain the link between affective symptoms and cognitive decline.

METHODS

Data from participants (aged 50 and above) of the PROTECT study was used. Latent Class Analysis (LCA) was conducted on 21,684 participants with baseline anxiety and depression measures. Multiple linear regressions models, using a subset of these participants (N = 6136) who had complete cognition data at baseline and at 2-year follow-up, were conducted to assess for associations between class membership and longitudinal changes in cognition.

RESULTS

The LCA identified a 5-class solution: "No Symptoms", "Sleep", "Sleep and Worry", "Sleep and Anhedonia", and "Co-morbid Depression and Anxiety". Class membership was significantly associated with longitudinal change in cognition. Furthermore, this association differed across different cognitive measures.

LIMITATIONS

Limitations included significant attrition and a generally healthy sample which may impact generalisability.

CONCLUSIONS

Substantial heterogeneity in affective symptoms could explain previous inconsistent findings concerning the association between affective symptoms and cognition. Clinicians should not focus solely on total symptom scores on a single affective domain, but instead on the presence and patterns of symptoms (even if sub-clinical) on measures across multiple affective domains. Identifying particular subgroups that are at greater risk of poor cognitive outcomes may support targeted prevention work.

A Patient Stratification Approach to Identifying the Likelihood of Continued Chronic Depression and Relapse Following Treatment for Depression

Background: Subgrouping methods have the potential to support treatment decision making for patients with depression. Such approaches have not been used to study the continued course of depression or likelihood of relapse following treatment. Method: Data from individual participants of seven randomised controlled trials were analysed. Latent profile analysis was used to identify subgroups based on baseline characteristics. Associations between profiles and odds of both continued chronic depression and relapse up to one year post-treatment were explored. Differences in outcomes were investigated within profiles for those treated with antidepressants, psychological therapy, and usual care. Results: Seven profiles were identified; profiles with higher symptom severity and long durations of both anxiety and depression at baseline were at higher risk of relapse and of chronic depression. Members of profile five (likely long durations of depression and anxiety, moderately-severe symptoms, and past antidepressant use) appeared to have better outcomes with psychological therapies: antidepressants vs. psychological therapies (OR (95% CI) for relapse = 2.92 (1.24–6.87), chronic course = 2.27 (1.27–4.06)) and usual care vs. psychological therapies (relapse = 2.51 (1.16–5.40), chronic course = 1.98 (1.16–3.37)). Conclusions: Profiles at greater risk of poor outcomes could benefit from more intensive treatment and frequent monitoring. Patients in profile five may benefit more from psychological therapies than other treatments.

Failure to Identify Robust Latent Variables of Positive or Negative Valence Processing Across Units of Analysis

BACKGROUND

The heterogeneous nature of mood and anxiety disorders highlights a need for dimensionally based descriptions of psychopathology that inform better classification and treatment approaches. Following the Research Domain Criteria approach, this investigation sought to derive constructs assessing positive and negative valence domains across multiple units of analysis.

METHODS

Adults with clinically impairing mood and anxiety symptoms (N = 225) completed comprehensive assessments across several units of analysis. Self-report assessments included nine questionnaires that assess mood and anxiety symptoms and traits reflecting the negative and positive valence systems. Behavioral assessments included emotional reactivity and distress tolerance tasks, during which skin conductance and heart rate were measured. Neuroimaging assessments included fear conditioning and a reward processing task. The latent variable structure underlying these measures was explored using sparse Bayesian group factor analysis.

RESULTS

Group factor analysis identified 11 latent variables explaining 31.2% of the variance across tasks, none of which loaded across units of analysis or tasks. Instead, variance was best explained by individual latent variables for each unit of analysis within each task. Post hoc analyses 1) showed associations with small effect sizes between latent variables that were derived separately from functional magnetic resonance imaging and self-report data and 2) showed that some latent variables are not directly related to individual valence system constructs.

CONCLUSIONS

The lack of latent structure across units of analysis highlights challenges of the Research Domain Criteria approach and suggests that while dimensional analyses work well to reveal within-task features, more targeted approaches are needed to reveal latent cross-modal relationships that could illuminate psychopathology.

A dimensional approach to the neuronal correlates of anxiety, depression, and perfectionism: A transdiagnostic dissociation of error-related brain activity

Transdiagnostic approaches such as the Research Domain Criteria (RDoC) highlight the importance of addressing psychopathological constructs dimensionally, since comorbidity and heterogeneity represent prevalent issues in the available categorical diagnosis. The current study analyses distinct internalizing dimensions of depression and anxiety, and the transdiagnostic feature of perfectionism on the modulation of error-related brain activity (i.e., ERN). A sample of 125 participants completed self-reported measures of anxiety, depression, and perfectionism, and performed two versions of the Flanker Task (performance monitoring and sustained-threat) during an EEG recording. In the broad internalizing dimensions, anxiety predicted increased ERN amplitudes when controlling for the shared variance with depression and perfectionism. The narrower dimensions of anxiety and depression revealed a dissociative effect: cognitive anxiety explained blunted ERN amplitudes, while the physiological signs of anxiety and depression predicted increased amplitudes. For perfectionism, no significant results were found. Exploratory analyses further revealed that the Error Positivity component (Pe) was reduced in anxiety and physiological depression. We conclude that anxiety features emerge as the main explanation for the altered patterns of error monitoring in a transdiagnostic sample. Since anxiety is expected to co-occur with other disorders, the current findings suggest that altered patterns of error monitoring will be a transdiagnostic feature of various internalizing and anxiety-related disorders.

The importance of identifying functional Val158Met polymorphism in catechol-O- Methyltransferase when assessing MRI-based volumetric measurements in major depressive disorder

Many studies have shown volumetric differences in the hippocampus between COMT gene polymorphisms and other studies have shown differences between depressed patients and controls; yet, few studies have been completed to identify the volumetric differences when taking both factors into consideration. Using voxel-based morphology (VBM) we investigated, in major depressive disorder (MDD) patients and healthy controls, the relationship between COMT gene polymorphism and volumetric abnormalities. Data from 60 MDD patients and 25 healthy controls were included in this study. Volumetric measurements and genotyping of COMTval158met polymorphism were conducted to determine its impact on gray matter volume (GMV) in the hippocampus and amygdala using a Met dominant model (Val/Val vs Met/Val & Met/Met). In the analysis, a significant difference in the right hippocampus (p = 0.015), right amygdala (p = 0.003) and entire amygdala (p = 0.019) was found between the interaction of diagnosis and genotype after MRI scanner, age and sex correction. Healthy controls (HC) with the Met dominant genotype exhibited a larger right hippocampal, right amygdalar and entire amydgalar volume than MDD patients with the Met dominant genotype. Conversely, HC with the Val/Val genotype displayed a lower right hippocampal, right amygdalar and entire amygdalar volume than their MDD counterparts. This study shows that COMT polymorphism and depression may have a confounding effect on neuroimaging studies.

Latent variable mixture modelling and individual treatment prediction

Understanding which groups of patients are more or less likely to benefit from specific treatments has important implications for healthcare. Many personalised medicine approaches in mental health employ variable-centred approaches to predicting treatment response, yet person-centred approaches that identify clinical profiles of patients can provide information on the likelihood of a range of important outcomes. In this paper, we discuss the use of latent variable mixture modelling and demonstrate its use in the application of a patient profiling algorithm using routinely collected patient data to predict outcomes from psychological treatments. This validation study analysed data from two services, which included n = 44,905 patients entering treatment. There were different patterns of reliable recovery, improvement and clinical deterioration from therapy, across the eight profiles which were consistent over time. Outcomes varied between different types of therapy within the profiles: there were significantly higher odds of reliable recovery with High Intensity therapies in two profiles (32.5% of patients) and of reliable improvement in three profiles (32.2% of patients) compared with Low Intensity treatments. In three profiles (37.4% of patients) reliable recovery was significantly more likely if patients had CBT vs Counselling. The developments and potential application of latent variable mixture approaches are further discussed.

Double-blind placebo controlled trial of the anxiolytic effects of a standardized Echinacea extract

Earlier studies suggested that specific Echinacea preparations might decrease anxiety. To further study the issue, we performed a double blind, placebo controlled trial with a standardized Echinacea angustifolia root extract. Participants were volunteers scoring above 45 points on the state or on the trait subscale of the State Trait Anxiety Inventory (STAI). They were treated with 40 mg Echinacea or with placebo tablets twice daily for 7 days followed by a 3 week-long washout period. Participants were also administered the Beck Depression Inventory (BDI) and the Perceived Stress Scale (PSS). In the Echinacea group, state anxiety scores decreased by approximately 11 points by the end of the treatment period, whereas the decrease was around 3-points in the placebo group (p< 0.01). The effect maintained over the washout period. The difference from placebo was significant from the 7th day of treatment throughout. Changes were less robust with trait anxiety scores, but the preparation performed better than placebo in patients with high baseline anxiety. Neither BDI nor PSS scores were affected by the treatments. Adverse effects were rare and mild, and all were observed in the placebo group. These findings suggest that particular Echinacea preparations have significant beneficial effects on anxiety in humans.

Gene × Environment Interaction in Developmental Disorders: Where Do We Stand and What's Next?

Although the field of psychiatry has witnessed the proliferation of studies on Gene × Environment (G×E) interactions, still limited is the knowledge we possess of G×E interactions regarding developmental disorders. In this perspective paper, we discuss why G×E interaction studies are needed to broaden our knowledge of developmental disorders. We also discuss the different roles of hazardous versus self-generated environmental factors and how these types of factors may differentially engage with an individual's genetic background in predicting a resulting phenotype. Then, we present examplar studies that highlight the role of G×E in predicting atypical developmental trajectories as well as provide insight regarding treatment outcomes. Supported by these examples, we explore the need to move beyond merely examining statistical interactions between genes and the environment, and the motivation to investigate specific genetic susceptibility and environmental contexts that drive developmental disorders. We propose that further parsing of genetic and environmental components is required to fully understand the unique contribution of each factor to the etiology of developmental disorders. Finally, with a greater appreciation of the complexities of G×E interaction, this discussion will converge upon the potential implications for clinical and translational research.

Latent comorbid depression and anxiety symptoms across sex and race/ethnic subgroupings in a national epidemiologic study

The heterogeneity of mood and anxiety disorders has been widely documented and epidemiologic studies have found different prevalence rates for psychiatric disorders across subgroups (i.e. sex and race/ethnic). The current study compares the latent class structure across sex and race/ethnic groups to determine group differences in these latent class configurations. This study utilized data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample from the United States (N = 43,093). First, latent class analyses (LCAs) were used to assess subtypes of symptoms of depression and anxiety that characterize a latent class structure for the population represented by NESARC. Second, group LCAs were conducted across sex and race/ethnicity to compare the latent class structure across these groups. The results suggest a 7-class model is the best fit for the population as well as for the male, non-Hispanic White, and Black subgroups. Females fit best an 11-class model, Hispanics a 5-class model and Asian and American Indian subgroups a 4-class model. These results indicate that subgroups of sex and race/ethnicity do not share the same latent construct for symptoms of anxiety and depression. Understanding the variability in the presentation of comorbid mood and anxiety across subgroups has the potential to inform person-centered approaches to care as well as targeted and multicultural interventions to improve population health.

Prospective Investigation of the Contrast Avoidance Model of Generalized Anxiety and Worry

The factors that maintain generalized anxiety disorder (GAD) symptoms and worry over time are not entirely clear. The Contrast Avoidance Model (CAM) postulates that individuals at risk for pathological worry and GAD symptoms uniquely fear emotional shifts from neutral or positive emotions into negative emotional states, and consequently use worry to maintain negative emotion in order to avoid shifts or blunt the effect of negative contrasts. This model has received support in laboratory experiments, but has not been investigated prospectively in the naturalistic context of daily life. The present study tested the CAM in a longitudinal experience sampling study with a subclinical sample. Participants selected to represent a broad range of symptoms (N = 92) completed baseline measures of GAD and depression symptoms, and eight weekly assessments of worry, experiences of negative emotional contrasts during their worst event of the week, and situation-specific negative emotion. Consistent with the CAM, GAD symptoms prospectively predicted higher endorsement of negative contrast experiences as worst events, independent of depression symptoms. Unsurprisingly, higher negative contrasts predicted higher negative emotion. However, both higher baseline GAD symptoms and weekly worry uniquely moderated (reduced) this relationship, providing consistent support for the idea that worry may blunt the emotional effects of contrasts. Depression symptoms did not have the same moderating effect. These findings support the CAM in an ecologically valid context.

Latent class analysis of need descriptors within an Irish youth mental health early intervention program toward a typology of need

AIM

Significant overlap and comorbidity has been demonstrated among young people with mental health problems. This paper examined demographic characteristics, heterogeneity of need descriptors and services provided among young people (12-25 years) engaging in brief interventions at Jigsaw in the Republic of Ireland.

METHOD

Between 1 January 2013 and 31 December 2013, a total of 2571 young people sought help from 1 of 10 Jigsaw sites. Of these, 1247 engaged in goal-focused brief interventions, typically consisting of one to six face-to-face sessions. Descriptive statistics were used to summarize social and demographic factors. Latent class analysis was used to cluster young people into relevant typologies of presenting issues. Multinomial logistic regression was then performed to determine significant predictors of class membership.

RESULTS

The most common age of young people was 16. More women (59.6%) than men engaged in brief interventions, 56% attended school, 74% lived with their family of origin or with one parent, and 54.2% came from families where parents were married. Using established fit criteria, four relevant typologies emerged: Developmental (26.8%), Comorbid (15.8%), Anxious (42.7%) and Externalising (14.6%). Predictors varied by class membership, but general family problems and lack of adult support emerged as the strongest predictors for all classes.

CONCLUSION

This study demonstrated that the mental health needs of young people in Ireland are significant and diverse. Because Jigsaw favours a more descriptive approach to problem identification, the four typologies suggest a need to determine program capacity in engaging youth with heterogeneous presenting issues and to tailor brief interventions to each group's clinical profiles.

Network analysis of depression and anxiety symptom relationships in a psychiatric sample

BACKGROUND

Researchers have studied psychological disorders extensively from a common cause perspective, in which symptoms are treated as independent indicators of an underlying disease. In contrast, the causal systems perspective seeks to understand the importance of individual symptoms and symptom-to-symptom relationships. In the current study, we used network analysis to examine the relationships between and among depression and anxiety symptoms from the causal systems perspective.

METHOD

We utilized data from a large psychiatric sample at admission and discharge from a partial hospital program (N = 1029, mean treatment duration = 8 days). We investigated features of the depression/anxiety network including topology, network centrality, stability of the network at admission and discharge, as well as change in the network over the course of treatment.

RESULTS

Individual symptoms of depression and anxiety were more related to other symptoms within each disorder than to symptoms between disorders. Sad mood and worry were among the most central symptoms in the network. The network structure was stable both at admission and between admission and discharge, although the overall strength of symptom relationships increased as symptom severity decreased over the course of treatment.

CONCLUSIONS

Examining depression and anxiety symptoms as dynamic systems may provide novel insights into the maintenance of these mental health problems.

Comorbid Anxiety and Depressive Symptoms in Children and Adolescents: A Systematic Review and Analysis

BACKGROUND

A large and extensive body of research has examined comorbid anxiety and depression in adults. Children and adolescents also frequently present with comorbid anxiety and depression; however, research and treatment require unique environmental and neurodevelopmental considerations in children. As a result, our understanding of comorbid anxiety and depression in children and adolescents is limited.

OBJECTIVE

The goal of this systematic review was to examine the current literature focused on comorbid anxiety and depression in children and adolescents. The review included theoretical conceptualizations as well as diagnostic, neurobiological, prevention, and treatment considerations. In addition, a proposed algorithm for the treatment of comorbid anxiety and depression in children/adolescents is provided.

METHODS

This systematic literature review included 3 discrete searches in Ovid SP Medline, PsycInfo, and PubMed.

RESULTS

The review included and synthesized 115 articles published between 1987 and 2015. The available evidence suggests that anxiety and depression are common in clinical populations of children and adolescents, and that comorbidity is likely underestimated in children and adolescents. Children and adolescents with comorbid anxiety and depression have unique presentations, greater symptom severity, and treatment resistance compared with those who have either disease in isolation. A dimensional approach may be necessary for the future development of diagnostic strategies and treatments for this population. Nascent neuroimaging work suggests that anxiety and depression each represents a distinct neurobiological phenotype.

CONCLUSIONS

The literature that is currently available suggests that comorbid anxiety and depression is a common presentation in children and adolescents. This diagnostic picture underscores the importance of comprehensive dimensional assessments and multimodal evidence-based approaches given the high disease severity. Future research on the neurobiology and the treatment of these common clinical conditions is warranted.

CLASSIFICATION OF ANXIETY DISORDERS COMORBID WITH MAJOR DEPRESSION: COMMON OR DISTINCT INFLUENCES ON RISK?

BACKGROUND

Anxiety and depression display frequent comorbidity. Individuals with comorbid disorders also often have more extreme symptomatology than those with single disorders. This correlation between comorbidity and severity poses an interesting question: Are comorbid forms of anxiety and depression essentially just more severe versions of the pure disorders?

METHODS

In a large major depression (MD) case-control sample of individuals from the China, Oxford and VCU Experimental Research on Genetic Epidemiology project, we examined the patterns of lifetime anxiety comorbidity (including generalized anxiety disorder--GAD, panic disorder, and five phobia subtypes) among MD cases (N = 5,864) in this population. Binary and multinomial logistic regression was used to estimate associations between risk factors and outcomes including MD as well as latent class membership, which were compared using continuation ratios.

RESULTS

We found a five-class solution to fit best, and each resulting class had a distinct pattern of association with the tested risk factors. The use of continuation ratios suggests that a class characterized by high endorsement of GAD is comparable to a more severely affected "pure MD" group. The other three classes (characterized by agoraphobia, various specific phobias, and by high endorsement of all comorbid anxiety disorders, respectively) appear to differ meaningfully from MD alone.

CONCLUSIONS

Risk for MD resulting from environmental and psychosocial factors may also predispose individuals to GAD, and less consistently, other anxiety disorders. Presentations of MD with certain phobias display distinguishably different patterns of risk, however, and are therefore likely qualitatively distinct.

One-year trajectories of depression and anxiety symptoms in older patients presenting in general practice with musculoskeletal pain: A latent class growth analysis

OBJECTIVE

Distinguishing transient from persistent anxiety and depression symptoms in older people presenting to general practice with musculoskeletal pain is potentially important for effective management. This study sought to identify distinct post-consultation depression and anxiety symptom trajectories in adults aged over 50years consulting general practice for non-inflammatory musculoskeletal pain.

METHODS

Self-completion questionnaires, containing measures of anxiety and depressive symptoms, age, gender, pain status, coping and social status were mailed within 1week of the consultation and at 3, 6 and 12months. Latent class growth analysis was used to identify anxiety and depression symptoms trajectories, which were ascertained with cut-off score ≥8 on Hospital Anxiety and Depression Scale subscales. Associations between baseline characteristics and cluster membership were examined using multivariate multinomial logistic regression analysis (the 3-step approach).

RESULTS

Latent class growth analyses determined a 3-cluster anxiety model (n=499) and a 3-cluster depression model (n=501). Clusters identified were: no anxiety problem (44.1%), persistent anxiety problem (33.9%) and transient anxiety symptoms (22.2%); no depression problem (74.1%), persistent depression problem (22.0%) and gradual depression symptom recovery (4.0%). Widespread pain, interference with valued activities, coping by increased behavioral activities, catastrophizing, perceived lack of instrumental support, age ≥70years, being female, and performing manual/routine work were associated with anxiety and/or depression clusters.

CONCLUSIONS

Older people with non-inflammatory musculoskeletal pain are at high risk of persistent anxiety and/or depression problems. Biopsychosocial factors, such as pain status, coping strategies, instrumental support, performing manual/routine work, being female and age ≥70years, may help identify patients with persistent anxiety and/or depression.

Empirically derived subtypes of serious emotional disturbance in a large adolescent sample

PURPOSE

The heterogeneity of serious emotional disturbance has been thoroughly documented among adolescents with nationally representative data derived from structured interviews, although use of these interviews may not be feasible within the context of brief and self-administered school surveys. This study seeks to identify distinct subtypes of serious emotional disturbance in a large school-based sample.

METHODS

A total of 108,736 students fully completed the K6 scale that was included on the 2012 Kentucky Incentives for Prevention Survey. Latent class analysis was used to derive subtypes of serious emotional disturbance among students receiving a positive screen (n = 15,147). To determine significant predictors of class membership, adjusted rate ratios and 95 % confidence intervals were calculated using multinomial logistic regression.

RESULTS

A four-class model was the most parsimonious, with four distinct subtypes emerging that varied by both symptom type and severity: comorbid moderate severity, comorbid high severity, anxious moderate severity, and depressed high severity. Age, gender, race/ethnicity, family structure, substance use, antisocial behavior, role impairments, and peer victimization were significant predictors of class membership, although the magnitude of these effects was stronger for the two high severity groups.

CONCLUSIONS

Our results suggest heterogeneity of serious emotional disturbance by both symptom type and severity. Prevention programs may benefit by shifting focus from specific disorders to the core features of serious emotional disturbance, including psychological distress, high comorbidity, and role impairments.

Factors of psychological distress: clinical value, measurement substance, and methodological artefacts

PURPOSE

Psychometric models and statistical techniques are cornerstones of research into latent structures of specific psychopathology and general mental health. We discuss "pivot points" for future research efforts from a psychometric epidemiology perspective, emphasising sampling and selection processes of both indicators that guide data collection as well as samples that are confronted with them.

METHOD

First, we discuss how a theoretical model of psychopathology determines which empirical indicators (questions, diagnoses, etc.) and modelling methods are appropriate to test its implications. Second, we deal with how different research designs introduce different (co-)variances between indicators, potentially leading to a different understanding of latent structures. Third, we discuss widening the range of statistical models available within the "psychometrics class": the inclusion of categorical approaches can help to enlighten the debate on the structure of psychopathology and agreement on a minimal set of models might lead to greater convergence between studies. Fourth, we deal with aspects of methodology that introduce spurious (co-)variance in latent structure analysis (response styles, clustered data) and differential item functioning to gather more detailed information and to guard against over-generalisation of results, which renders assessments unfair.

CONCLUSIONS

Building on established insights, future research efforts should be more explicit about their theoretical understanding of psychopathology and how the analysis of a given indicator-respondent set informs this theoretical model. A coherent treatment of theoretical assumptions, indicators, and samples holds the key to building a comprehensive account of the latent structures of different types of psychopathology and mental health in general.

Racial and ethnic differences in depressive subtypes and access to mental health care in the United States

OBJECTIVES

Racial and ethnic minorities in the U.S. underutilize mental health service for mood disorders. This study sought to identify depressive subtypes associated with low use of mental health services across racial and ethnic groups based on a large, nationally representative sample of adults in the U.S.

METHODS

Based on latent class analysis, we identified the latent profile of depressive symptoms among those who endorsed lifetime depressed mood or anhedonia in the 2001-2002 National Epidemiological Survey on Alcohol and Related Condition (302 Asian Americans; 8602 Whites; 2266 Blacks; 2254 Hispanics). Proportions and types of lifetime mental health service use across depressive symptom subtypes were assessed and compared across the racial and ethnic categories.

RESULTS

A four class model of depressive subtypes was examined across race and ethnicity ("mild," "cognitive," "psychosomatic," and "severe"). Asian Americans, blacks, and Hispanics with "severe" subtype of depression had significantly lower odds of mental health service use compared to whites with "severe" subtype of depression. While Asian Americans did not have higher proportion of "psychosomatic" subtype than other race and ethnic groups, Asian Americans with "cognitive" subtype of depression significantly underused mental health services compared to Asian Americans with "psychosomatic" subtype of depression (Odds ratio:0.34, 95% Confidence interval:0.13,0.91).

LIMITATION

We were unable to account for heterogeneity of the subethnic group compositions based on country of origin and other socio-demographic factors.

CONCLUSIONS

A targeted outreach intervention to raise awareness among Asian Americans, blacks, and Hispanics with "severe" subtype and Asian Americans with "cognitive" subtype of depression may reduce disparity in mental health service utilization across racial and ethnic groups.

Adolescent subthreshold-depression and anxiety: psychopathology, functional impairment and increased suicide risk

BACKGROUND

 Subthreshold-depression and anxiety have been associated with significant impairments in adults. This study investigates the characteristics of adolescent subthreshold-depression and anxiety with a focus on suicidality, using both categorical and dimensional diagnostic models.

METHODS

 Data were drawn from the Saving and Empowering Young Lives in Europe (SEYLE) study, comprising 12,395 adolescents from 11 countries. Based on self-report, including Beck Depression Inventory-II (BDI-II), Zung Self-Rating Anxiety Scale (SAS), Strengths and Difficulties Questionnaire (SDQ) and Paykel Suicide Scale (PSS) were administered to students. Based on BDI-II, adolescents were divided into three groups: nondepressed, subthreshold-depressed and depressed; based on the SAS, they were divided into nonanxiety, subthreshold-anxiety and anxiety groups. Analyses of Covariance were conducted on SDQ scores to explore psychopathology of the defined groups. Logistic regression analyses were conducted to explore the relationships between functional impairments, suicidality and subthreshold and full syndromes.

RESULTS

 Thirty-two percent of the adolescents were subthreshold-anxious and 5.8% anxious, 29.2% subthreshold-depressed and 10.5% depressed, with high comorbidity. Mean scores of SDQ of subthreshold-depressed/anxious were significantly higher than the mean scores of the nondepressed/nonanxious groups and significantly lower than those of the depressed/anxious groups. Both subthreshold and threshold-anxiety and depression were related to functional impairment and suicidality.

CONCLUSIONS

Subthreshold-depression and subthreshold-anxiety are associated with an increased burden of disease and suicide risk. These results highlight the importance of early identification of adolescent subthreshold-depression and anxiety to minimize suicide. Incorporating these subthreshold disorders into a diagnosis could provide a bridge between categorical and dimensional diagnostic models.

A Monte Carlo investigation of factors influencing latent class analysis: an application to eating disorder research

OBJECTIVE

Latent class analysis (LCA) has frequently been used to identify qualitatively distinct phenotypes of disordered eating. However, little consideration has been given to methodological factors that may influence the accuracy of these results.

METHOD

Monte Carlo simulations were used to evaluate methodological factors that may influence the accuracy of LCA under scenarios similar to those seen in previous eating disorder research.

RESULTS

Under these scenarios, the aBIC provided the best overall performance as an information criterion, requiring sample sizes of 300 in both balanced and unbalanced structures to achieve accuracy proportions of at least 80%. The BIC and cAIC required larger samples to achieve comparable performance, while the AIC performed poorly universally in comparison. Accuracy generally was lower with unbalanced classes, fewer indicators, greater or nonrandom missing data, conditional independence assumption violations, and lower base rates of indicator endorsement.

DISCUSSION

These results provide critical information for interpreting previous LCA research and designing future classification studies.

PREDICTING LATENT CLASS SCORES FOR SUBSEQUENT ANALYSIS

Latent class regression models relate covariates and latent constructs such as psychiatric disorders. Though full maximum likelihood estimation is available, estimation is often in three steps: (i) a latent class model is fitted without covariates; (ii) latent class scores are predicted; and (iii) the scores are regressed on covariates. We propose a new method for predicting class scores that, in contrast to posterior probability-based methods, yields consistent estimators of the parameters in the third step. Additionally, in simulation studies the new methodology exhibited only a minor loss of efficiency. Finally, the new and the posterior probability-based methods are compared in an analysis of mobility/exercise.

Admixture analysis of age at onset in major depressive disorder

OBJECTIVES

This study aimed to determine the distributions of the age at onset (AAO) in patients with major depressive disorder (MDD) using admixture analysis and to determine the clinical differences between subgroups with different AAO.

METHODS

Participants were administered the Mini-International Neuropsychiatric Interview to obtain clinical data. Admixture analysis was performed using the STATA module DENORMIX to identify subgroups characterized by differences in AAO.

RESULTS

The best fit model was the three-component model with the following means, standard deviations and proportions: 14.60 (3.75) years (49.1%), 29.15 (6.75) years (34.1%) and 46.96 (6.06) years (16.8%) (χ(2)=3.64, 2 df, P=.162). The three subgroups were divided by AAO of 22 and 40. After controlling for duration of illness, there were no significant differences between the three AAO subgroups in terms of gender and psychiatric family history. However, the early-onset subgroup was significantly more likely to report being single compared to the intermediate- and late-onset groups. The proportion of individuals meeting criteria for lifetime comorbid panic disorders and obsessive-compulsive disorder did not differ significantly between the AAO groups. However, the early-onset group reported a higher incidence of attention-deficit/hyperactivity disorder (5.1% vs. 1.7% and 1.2%, P=.086), although this was not statistically significant.

CONCLUSIONS

Our study identified three characteristically different AAO subgroups in individuals suffering from MDD. The subgroups may reflect different underlying neurobiological mechanisms involved.

Culture and the anxiety disorders: recommendations for DSM-V

BACKGROUND

The anxiety disorders specified in the fourth edition, text revision, of The Diagnostic and Statistical Manual (DSM-IV-TR) are identified universally in human societies, and also show substantial cultural particularities in prevalence and symptomatology. Possible explanations for the observed epidemiological variability include lack of measurement equivalence, true differences in prevalence, and limited validity or precision of diagnostic criteria. One central question is whether, through inadvertent "over-specification" of disorders, the post-DSM-III nosology has missed related but somewhat different presentations of the same disorder because they do not exactly fit specified criteria sets. This review canvases the mental health literature for evidence of cross-cultural limitations in DSM-IV-TR anxiety disorder criteria.

METHODS

Searches were conducted of the mental health literature, particularly since 1994, regarding cultural or race/ethnicity-related factors that might limit the universal applicability of the diagnostic criteria for six anxiety disorders.

RESULTS

Possible mismatches between the DSM criteria and the local phenomenology of the disorder in specific cultural contexts were found for three anxiety disorders in particular. These involve the unexpectedness and 10-minute crescendo criteria in Panic Disorder; the definition of social anxiety and social reference group in Social Anxiety Disorder; and the priority given to psychological symptoms of worry in Generalized Anxiety Disorder. Limited evidence was found throughout, particularly in terms of neurobiological markers, genetic risk factors, treatment response, and other DSM-V validators that could help clarify the cross-cultural applicability of criteria.

CONCLUSIONS

On the basis of the available data, options and preliminary recommendations for DSM-V are put forth that should be further evaluated and tested.