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Schizophrenia spectrum disorders (SSD) have been linked to oxidative stress (OS). Recent findings from our group show that serum free thiols (R-SH, sulfhydryl groups) can function as an accurate biomarker of systemic OS, since they are readily oxidized by reactive species (ROS), thereby serving as potent antioxidants. The aim of this study is to investigate if reduced R-SH levels can be demonstrated in recently diagnosed patients with SSD compared to healthy controls (HC).In this study, 102 patients with recently diagnosed SSD (< three years), and 42 HC were included. Levels of R-SH were quantified and studied for correlations with age, C-reactive protein (CRP) as proxy of inflammation as well as body mass index (BMI) and total cholesterol as indices of metabolic health.R-SH levels were significantly lower in patients when compared to HC. When correcting for age the difference was borderline significant (p=0.05). Moreover, R-SH correlated significantly with age (r = -0.29) and CRP (r = -0.29) in patients with SSD, but not in the HC.R-SH levels are reduced in SSD as compared to HC and correlate negatively with CRP and age in SSD. Future studies are required to further investigate R-SH and its role in SSD.

BackgroundInflammation and metabolic dysregulation are age-related physiological changes and are associated with depressive disorder. We tried to identify subgroups of depressed older patients based on their metabolic-inflammatory profile and examined the course of depression for these subgroups.MethodsThis clinical cohort study was conducted in a sample of 364 depressed older (⩾60 years) patients according to DSM-IV criteria. Severity of depressive symptoms was monitored every 6 months and a formal diagnostic interview repeated at 2-year follow-up. Latent class analyses based on baseline metabolic and inflammatory biomarkers were performed. Adjusted for confounders, we compared remission of depression at 2-year follow-up between the metabolic-inflammatory subgroups with logistic regression and the course of depression severity over 2-years by linear mixed models.ResultsWe identified a ‘healthy’ subgroup (n = 181, 49.7%) and five subgroups characterized by different profiles of metabolic-inflammatory dysregulation. Compared to the healthy subgroup, patients in the subgroup with mild ‘metabolic and inflammatory dysregulation’ (n = 137, 37.6%) had higher depressive symptom scores, a lower rate of improvement in the first year, and were less likely to be remitted after 2-years [OR 0.49 (95% CI 0.26–0.91)]. The four smaller subgroups characterized by a more specific immune-inflammatory dysregulation profile did not differ from the two main subgroups regarding the course of depression.ConclusionsNearly half of the patients with late-life depressions suffer from metabolic-inflammatory dysregulation, which is also associated with more severe depression and a worse prognosis. Future studies should examine whether these depressed older patients benefit from a metabolic-inflammatory targeted treatment.

BackgroundIt has been claimed that functional somatic syndromes share a common etiology. This prospective population-based study assessed whether the same variables predict new onsets of irritable bowel syndrome (IBS), chronic fatigue syndrome (CFS) and fibromyalgia (FM).MethodsThe study included 152 180 adults in the Dutch Lifelines study who reported the presence/absence of relevant syndromes at baseline and follow-up. They were screened at baseline for physical and psychological disorders, socio-demographic, psycho-social and behavioral variables. At follow-up (mean 2.4 years) new onsets of each syndrome were identified by self-report. We performed separate analyses for the three syndromes including participants free of the relevant syndrome or its key symptom at baseline. LASSO logistic regressions were applied to identify which of the 102 baseline variables predicted new onsets of each syndrome.ResultsThere were 1595 (1.2%), 296 (0.2%) and 692 (0.5%) new onsets of IBS, CFS, and FM, respectively. LASSO logistic regression selected 26, 7 and 19 predictors for IBS, CFS and FM, respectively. Four predictors were shared by all three syndromes, four predicted IBS and FM and two predicted IBS and CFS but 28 predictors were specific to a single syndrome. CFS was more distinct from IBS and FM, which predicted each other.ConclusionsSyndrome-specific predictors were more common than shared ones and these predictors might form a better starting point to unravel the heterogeneous etiologies of these syndromes than the current approach based on symptom patterns. The close relationship between IBS and FM is striking and requires further research.

Background: Given the strong relationship between depression and anxiety, there is an urge to investigate their shared and specific long-term course determinants. The current study aimed to identify and compare the main determinants of the 9-year trajectories of combined and pure depression and anxiety symptom severity. Methods: Respondents with a 6-month depression and/or anxiety diagnosis (n=1,701) provided baseline data on 152 sociodemographic, clinical and biological variables. Depression and anxiety symptom severity assessed at baseline, 2-, 4-, 6- and 9-year follow-up, were used to identify data-driven course-trajectory subgroups for general psychological distress, pure depression, and pure anxiety severity scores. For each outcome (class-probability), a Superlearner (SL) algorithm identified an optimally weighted (minimum mean squared error) combination of machine-learning prediction algorithms. For each outcome, the top determinants in the SL were identified by determining variable-importance and correlations between each SL-predicted and observed outcome ( ρ p r e d ) were calculated. Results: Low to high prediction correlations ( ρ p r e d : 0.41-0.91, median=0.73) were found. In the SL, important determinants of psychological distress were age, young age of onset, respiratory rate, participation disability, somatic disease, low income, minor depressive disorder and mastery score. For course of pure depression and anxiety symptom severity, similar determinants were found. Specific determinants of pure depression included several types of healthcare-use, and of pure-anxiety course included somatic arousal and psychological distress. Limitations: Limited sample size for machine learning. Conclusions: The determinants of depression- and anxiety-severity course are mostly shared. Domain-specific exceptions are healthcare use for depression and somatic arousal and distress for anxiety-severity course.

BACKGROUND: Research so far provided few clues on the order in which depressive symptoms typically remit during treatment. This study examined which depressive symptoms improve first, and whether symptoms changed before, simultaneous with, or after the core symptoms of depression (i.e., sad mood, loss of pleasure, and loss of interest).METHODS: Participants were 176 patients with Major Depressive Disorder (MDD) receiving outpatient treatment (a combination of pharmacotherapy and psychological interventions) for depression. Participants filled out the Inventory of Depressive Symptomatology - Self Report (IDS-SR) for 16 to 20 consecutive weeks. For each symptom, the timing of onset of a persistent improvement was determined for each single-subject separately.RESULTS: Which symptoms improved first differed markedly across patients. The core depression symptoms improved 1.5 to 2 times more often before (48% - 60%) than after (19% -28%) depressive cognitions ('view of myself' and 'view of the future'), anxiety symptoms ('feeling irritable' and 'feeling anxious / tense') and vegetative symptoms ('loss of energy', 'slowed down', and 'physical energy'). Only improvements in suicidal thoughts were more likely to occur before (46% - 48%) than after (29%) improvements in the depression core symptoms.LIMITATIONS: Not all 'core depression-non-core symptom' combinations could be tested because some symptoms did not improve in a sufficient number of patients.CONCLUSIONS: Which improvements mark the start of symptom remission differed between patients. Improvements in the core depression symptoms 'sad mood', 'loss of interest', and 'loss of pleasure' were more likely to occur before than after improvements in non-core symptoms.

We studied the association of early-life environmental and child factors with disruptive behaviors in children with autistic traits around age 7, in the Avon Longitudinal Study of Parents and Children (n = 6,401). Logistic regression with the least absolute shrinkage and selection operator indicated that disruptive behaviors were associated with prenatal smoking, no seafood-consumption during pregnancy, breech presentation at delivery, neonatal feeding problems, low social-economic situation, suboptimal preschool family environment, maternal depression, maternal antisocial behavior, male sex, and difficult child temperament. Compared to controls, male sex, maternal depression, and suboptimal preschool family environment were related to autistic traits without disruptive behaviors. Thus, there may be a difference in early-life factors related to autism spectrum disorder with and without disruptive behaviors.

Background With increasing age, symptoms of depression may increasingly overlap with age-related physical frailty and cognitive decline. We aim to identify late-life-related subtypes of depression based on measures of depressive symptom dimensions, cognitive performance, and physical frailty. Methods A clinical cohort study of 375 depressed older patients with a DSM-IV depressive disorder (acronym NESDO). A latent profile analysis was applied on the three subscales of the Inventory of Depressive Symptomatology, as well as performance in five cognitive domains and two proxies for physical frailty. For each class, we investigated remission, dropout, and mortality at 2-year follow-up as well as change over time of depressive symptom severity, cognitive performance, and physical frailty. Results A latent profile analysis model with five classes best described the data, yielding two subgroups suffering from pure depression (“mild” and “severe” depression, 55% of all patients) and three subgroups characterized by a specific profile of cognitive and physical frailty features, labeled as “amnestic depression,” “frail-depressed, physically dominated,” and “frail-depressed, cognitively dominated.” The prospective analyses showed that patients in the subgroup of “mild depression” and “amnestic depression” had the highest remission rates, whereas patients in both frail-depressed subgroups had the highest mortality rates. Conclusions Late-life depression can be subtyped by specific combinations of age-related clinical features, which seems to have prospective relevance. Subtyping according to the cognitive profile and physical frailty may be relevant for studies examining underlying disease processes as well as to stratify treatment studies on the effectiveness of antidepressants, psychotherapy, and augmentation with geriatric rehabilitation.

Experience sampling studies into daily-life affective reactivity indicate that depressed individuals react more strongly to both positive and negative stimuli than non-depressed individuals, particularly on negative affect (NA). Given the different mean levels of both positive affect (PA) and NA between patients and controls, such findings may be influenced by floor/ceiling effects, leading to violations of the normality and homoscedasticity assumptions underlying the used statistical models. Affect distributions in prior studies suggest that this may have particularly influenced NA-reactivity findings. Here, we investigated the influence of floor/ceiling effects on the observed PA- and NA-reactivity to both positive and negative events. Data came from 346 depressed, non-depressed, and remitted participants from the Netherlands Study of Depression and Anxiety (NESDA). In PA-reactivity analyses, no floor/ceiling effects and assumption violations were observed, and PA-reactivity to positive events, but not negative events, was significantly increased in the depressed and remitted groups versus the non-depressed group. However, NA-scores exhibited a floor effect in the non-depressed group and naively estimated models violated model assumptions. When these violations were accounted for in subsequent analyses, group differences in NA-reactivity that had been present in the naive models were no longer observed. In conclusion, we found increased PA-reactivity to positive events but no evidence of increased NA-reactivity in depressed individuals when accounting for violations of assumptions. The results indicate that affective-reactivity results are very sensitive to modeling choices and that previously observed increased NA-reactivity in depressed individuals may (partially) reflect unaddressed assumption violations resulting from floor effects in NA.

Background: Mismatch between need and mental healthcare (MHC) use (under-and overuse) has mainly been studied with cross-sectional designs, not accurately capturing patterns of persistence or change in clinical burden and MHC-use among persons with depressive and/or anxiety disorders. Aims: Determining and describing [mis]match of longitudinal trajectories of clinical burden and MHC-use. Methods: Six-year longitudinal burden and MHC-use data came from the Netherlands Study of Depression and Anxiety (n=2981). The sample was split into four subgroups: I) no clinical burden but constant MHC use, II) constant clinical burden but no MHC-use, III) changing clinical burden and MHC-use, and IV) healthy non-users. Within subgroups I)-III), specific clinical burden and MHC trajectories were identified (growth mixture modeling). The resulting classes’ associations with predisposing, enabling, and need factors were investigated (regression analysis). Results: Subgroups I-III revealed different trajectories. I) increasing MHC without burden (4.1%). II) slightly increasing (1.9%), strongly increasing (2.4%), and decreasing (9.5%) burden without MHC. III) increasing (41.4%) or decreasing (19.4%) burden and concurrently increasing MHC use (first underuse, then matched care), thus revealing delayed MHC-use. Only having suicidal ideation (p

BackgroundMultiple predictors have been associated with persistent somatic symptoms. However, previous studies problematically defined the persistence of symptoms, conflated participants' sex and gender, and focused on patient populations. Therefore, we studied associations between predictors, especially sex and gender, and longitudinal patterns of somatic symptoms in the general adult population. We also assessed whether predictors for persisting symptoms differ between sexes.MethodTo identify developmental trajectories of somatic symptoms, assessed by the SCL-90 SOM, we used latent class trajectory modeling in the Dutch Lifelines Cohort Study [N = 150 494; 58.6% female; median time to follow-up: 46.0 (min–max: 22.0–123.0) months]. To identify predictors of trajectories, we applied multiple logistic regression analyses. Predictors were measured by surveys at baseline and a composite gender index was previously developed.ResultsA five-class linear LCGA model fitted the data best: 93.7% of the population had a stable symptom trajectory, whereas 1.5% and 4.8% of the population had a consistently increasing or decreasing symptom trajectory, respectively. Female sex predicted severe, stable symptom severity (OR 1.74, 95% CI 1.36–2.22), but not increasing symptom severity (OR 1.15, 95% CI 0.99–1.40). Femininity was protective hereof (OR 0.60, 95% CI 0.44–0.82 and OR 0.66, 95% CI 0.51–0.85, respectively). Merely a few predictors of symptom severity, for instance hours of paid employment and physical functioning, differed in strength between sexes. Yet, effect sizes were small.ConclusionFemale sex and femininity predict symptom trajectories. No large sex differences in the strength of additional predictors were found, thus it may not be clinically useful to distinguish between predictors specific to male or female patients of persistent somatic symptoms.

Background: In longitudinal research, switching between diagnoses should be considered when examining patients with depression and anxiety. We investigated course trajectories of affective disorders over a nine-year period, comparing a categorical approach using diagnoses to a dimensional approach using symptom severity.Method: Patients with a current depressive and/or anxiety disorder at baseline (N = 1701) were selected from the Netherlands Study of Depression and Anxiety (NESDA). Using psychiatric diagnoses, we described 'consistently recovered,' 'intermittently recovered,' 'intermittently recurrent', and 'consistently chronic' at two-, four-, six-, and nine-year follow-up. Additionally, latent class growth analysis (LCGA) using depressive, anxiety, fear, and worry symptom severity scores was used to identify distinct classes.Results: Considering the categorical approach, 8.5% were chronic, 32.9% were intermittently recurrent, 37.6% were intermittently recovered, and 21.0% remained consistently recovered from any affective disorder at nine-year follow-up. In the dimensional approach, 66.6% were chronic, 25.9% showed partial recovery, and 7.6% had recovered.Limitations: 30.6% of patients were lost to follow-up. Diagnoses were rated by the interviewer and questionnaires were completed by the participant.Conclusions: Using diagnoses alone as discrete categories to describe clinical course fails to fully capture the persistence of affective symptoms that were observed when using a dimensional approach. The enduring, fluctuating presence of sub-threshold affective symptoms likely predisposes patients to frequent relapse. The commonness of subthreshold symptoms and their adverse impact on long-term prognoses deserve continuous clinical attention in mental health care as well further research.

Background: Personality and coping may be related to symptom severity and psychosocial functioning in patients with recent-onset psychosis. This study aimed to investigate associations of personality traits and coping strategies with concurrent and follow-up symptom severity and functioning in those patients, and identify whether coping mediates relations between personality and symptoms or functioning.Methods: At baseline, 527 recent-onset psychosis patients (73 % male, mean age = 28 years) received assessments on personality (Neuroticism-Extraversion-Openness – Five-Factor Inventory), coping (Utrecht Coping List), symptom severity (Positive And Negative Syndrome Scale) and psychosocial functioning (Global Assessment of Functioning Scale). Of those, 149 also received symptom and functioning assessments at follow-up. Multivariable linear regression analyses were performed to assess cross-sectional associations of personality and coping with symptoms and functioning at baseline. Longitudinal associations of baseline personality and coping with follow-up symptomatic remission and functioning were analyzed with multivariable linear and binary logistic regression analyses, respectively. Lastly, it was investigated whether coping mediated associations between personality and symptoms or functioning.Results: Higher baseline Agreeableness (B = -0.019, [95%CI: −0.031; −0.007]) and Neuroticism (B = -0.017, [95%CI: −0.028; −0.006]) were associated with lower concurrent symptom severity. Reassuring Thoughts were associated with better functioning at baseline (B = 0.833, [95%CI: 0.272; 1.393]). Neither personality nor coping were associated with follow-up symptomatic remission or functioning. Coping did not mediate associations between personality and symptoms or functioning.Conclusion: Only the coping strategy Reassuring Thoughts is associated with better baseline functioning in patients with recent-onset psychosis. Personality traits seem to have limited clinically relevant relations with symptom severity or functioning.

In the Original Publication Table 2 was incorrectly published. The correct table is given below.

Background A substantial percentage of depressed patients do not respond satisfactorily to conventional antidepressant treatment. This treatment resistant depression (TRD) may be partly related to inflammatory processes in the central nervous system. Accordingly, peripheral inflammatory markers might serve to predict treatment response with novel but still experimental forms of antidepressant treatment. Methods A literature search on treatment of TRD and inflammatory markers was performed using the PubMed/Medline database on November 8th 2018, and 95 articles were retrieved initially, which were subsequently screened and selected only when the inclusion and exclusion criteria were met. Results Ten studies were recruited. In five studies higher baseline interleukin-6 (IL-6) or C-reactive protein (CRP)/high-sensitivity-CRP (hsCRP) in blood predicted better response to medication with anti-inflammatory characteristics, such as ketamine and infliximab. One study found that higher IL-6 predicted worse response to antidepressant treatment in patients with TRD. No evidence was found for the predictive value of other inflammatory markers (e.g., Tumor Necrosis Factor-α, Interferon-γ). Limitations The number of available studies was limited; included studies showed considerable methodological variation and used different definitions for TRD. Conclusion The inflammatory markers IL-6 and CRP/hsCRP could hold promise as markers for the prediction of treatment response in TRD. Clearly, this field of research is still far from mature but it could pave the way for novel and efficacious treatments for at least the inflammatory type of TRD with more well-designed studies and more convincing results.

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of similar to 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

Background: The pathophysiology of numerous central nervous system disorders remains poorly understood. Biomarker research using cerebrospinal fluid (CSF) is a promising way to illuminate the neurobiology of neuropsychiatric disorders. CSF biomarker studies performed so far generally included patients with neurodegenerative diseases without an adequate control group. The Anaesthetic Biobank of Cerebrospinal fluid (ABC) was established to address this. The aims are to (I) provide healthy-control reference values for CSF-based biomarkers, and (II) to investigate associations between CSF-based candidate biomarkers and neuropsychiatric symptoms.& nbsp; & nbsp;Methods: In this cross-sectional study, we collect and store CSF and blood from adult patients undergoing spinal anaesthesia for elective surgery. Blood (20.5 mL) is collected during intravenous cannulation and CSF (10 mL) is aspirated prior to intrathecal local anaesthetic injection. A portion of the blood and CSF is sent for routine laboratory analyses, the remaining material is stored at & minus;80 ?. Relevant clinical, surgical and anaesthetic data are registered. A neurological examination and Montreal Cognitive Assessment (MoCA) are performed pre-operatively and a subset of patients fill in questionnaires on somatic and mental health (depression, anxiety and stress).& nbsp; Results: Four-hundred-fifty patients (58% male; median age: 56 years) have been enrolled in the ABC. The planned spinal anaesthetic procedure was not attempted for various reasons in eleven patients, in fourteen patients the spinal puncture failed and in twelve patients CSF aspiration was unsuccessful. A mean of 9.3 mL CSF was obtained in the remaining 413 of patients. Most patients had a minor medical history and 60% scored in the normal range on the MoCA (median score: 26).& nbsp; Conclusions: The ABC is an ongoing biobanking project that can contribute to CSF-based biomarker research. The large sample size with constant sampling methods and extensive patient phenotyping provide excellent conditions for future neuroscientific research.

This article was published in Psychological Medicine with spelling mistake in its title. In the original the word 'psychiatric' was misspelled as 'sychiatric'. This has now been updated. The publisher apologises for this error.

BACKGROUND: Childhood trauma (CT) is a risk factor for depressive and anxiety disorders. Although dysregulated biological stress systems may underlie the enduring effect of CT, the relation between CT and separate and cumulative activity of the major stress systems, namely, the hypothalamic-pituitary-adrenal (HPA)-axis, the immune-inflammatory system, and the autonomic nervous system (ANS), remains inconclusive.METHODS: In the Netherlands Study of Depression and Anxiety (NESDA, n = 2778), we determined whether self-reported CT (as assessed by the Childhood Trauma Interview) was associated with separate and cumulative markers of the HPA-axis (cortisol awakening response, evening cortisol, dexamethasone suppression test cortisol), the immune-inflammatory system (C-reactive protein, interleukin-6, tumor necrosis factor-α), and the ANS (heart rate, respiratory sinus arrhythmia, pre-ejection period) in adulthood.RESULTS: Almost all individuals with CT (n = 1330) had either current or remitted depressive and/or anxiety disorder (88.6%). Total-sample analyses showed little evidence for CT being significantly associated with the separate or cumulative stress systems' activity in adulthood. These findings were true for individuals with and without depressive and/or anxiety disorders. To maximize contrast, individuals with severe CT were compared to healthy controls without CT. This yielded slight, but significantly higher levels of cortisol awakening response (AUCg, β = .088, p = .007; AUCi, β = .084, p = .010), cumulative HPA-axis markers (β = .115, p = .001), C-reactive protein (β = .055, p = .032), interleukin-6 (β = .053, p = .038), cumulative inflammation (β = .060, p = .020), and cumulative markers across all systems (β = .125, p = .0003) for those with severe CT, partially explained by higher rates of smoking, body mass index, and chronic diseases.CONCLUSION: While our findings do not provide conclusive evidence on CT directly dysregulating stress systems, individuals with severe CT showed slight indications of dysregulations, partially explained by an unhealthy lifestyle and poorer health.

Background The Multidimensional Adolescent Functioning Scale (MAFS) is a 23-item, self-report questionnaire assessing psychosocial functioning in adolescents aged 12–17 years. It captures three domains of functioning: ‘general functioning’, ‘family-related functioning’, and ‘peer-related functioning’. The original English version has good psychometric properties. The aim of the current paper was to translate the MAFS to Dutch and to investigate the psychometric properties of this translation. Methods After translation, the Dutch MAFS was assessed in 397 adolescents aged 12–17 years, assessed at schools. Internal consistency, factor structure and correlations with other questionnaires assessing functioning, psychopathology and well-being were investigated. Results A hierarchical/bifactor model with a general factor that loads on all items (MAFS-general) and three group factors, loading respectively on the GF, FF and PF items, was found to describe the data best. Internal consistency of the MAFS total score (α = 0.87) was good and of the subscales (α = 0.74–0.80) acceptable. Comparable alphas were found in males and females. Correlations between MAFS subscales ranged from 0.33 to 0.43, indicating sufficient differentiation. The MAFS general factor score and group factor scores showed positive correlations with other measures of good functioning and well-being, and negative correlations with measures of psychopathology, supporting convergent and divergent validity. Conclusions The Dutch translation of the MAFS has adequate psychometric properties to assess three domains of functioning in adolescents from the general population aged 12–17 years. The MAFS is freely accessible in the Appendix and easy to administer.

Background Smartphones have become ubiquitous in China, offering a promising way to deliver mental health interventions; however, little is known about the current use and characteristics of smartphone apps for mental health. Objective The purpose of this study was to gain insight into mobile mental health apps available in China as of December 2018. Methods A systematic search was conducted to identify and evaluate the most downloaded apps from iOS and Android platforms. Apps were categorized according to their main purpose and downloaded to evaluate their content. Each app’s affiliation, cost, target users, information security, and evidence-based nature were evaluated. Results Of the 172 unique apps that were identified, there were 37 apps (21.5%) for psychological counseling, 50 apps (29.1%) for assessment, 12 apps (7.0%) to relieve stress, 24 apps (14.0%) for psychoeducation, and 49 (28.4%) multipurpose apps (ie, a combination of counseling and assessment). Most apps were developed for adults in the general population (166/172, 96.5%), rather than for psychiatric patients. App-based counseling was mostly provided by psychologists, and of the assessed apps, only 40% (70/172) used evidence-based scales to assess mental health problems such as anxiety or depressed mood. Guided meditation was used as the main technique in stress-relieving apps. Conclusions Many apps contained useful and evidence-based elements, such as good quality information, validated measurements, and useful meditation methods; however, for mobile apps to contribute significantly to mental health care in China, considerable challenges remain, including the need for more patient-focused apps that can actually take on the role of a health care provider. In addition, efficacy studies are needed.

BACKGROUND: Mental health problems during adolescence may create a problematic start into adulthood for affected individuals. Usually, categorical indicators of adolescent mental health issues (yes/no psychiatric disorder) are used in studies into long-term functional outcomes. This however does not take into account the full spectrum of mental health, nor does it consider the trajectory of mental health problem development over time. The aim of this study was twofold: (1) to identify distinct developmental trajectories of (co-occurring) internalizing and externalizing mental health symptoms over the course of adolescence (ages 11-19), and (2) to document the associations between these adolescent trajectories and economic, social, and health outcomes in young adulthood (age 22), unadjusted and adjusted for childhood functioning, putative confounders and current mental health.METHODS: Data were used from the Dutch TRAILS cohort study (subsample n = 1524, 47.3% males). Self-reported INT and EXT symptoms using the Youth/Adult Self Report were assessed four times (ages 11y, 13y, 16y, 19y). Adolescent mental health trajectories were estimated using Parallel-Processes Latent Class Growth Analyses. Self-reported economic, social, and health outcomes and parent-reported current mental health (using Adult Behaviour Checklist) were assessed at age 22. Multiple logistic regression analyses were performed to test associations between trajectories and outcomes.RESULTS: Four distinct trajectory classes were identified: (1) a normative class with decreasing-low INT+EXT symptoms (n = 460), (2) continuous moderately-high INT+EXT (n = 298), (3) continuous moderate, INT>EXT (n = 414), and (4) decreasing moderate, EXT>INT (n = 352). Compared to the normative class, the other three trajectories generally predicted less optimal early-adult outcomes, with the strongest effects observed for individuals with continuous moderate-high levels of both INT and EXT symptoms throughout adolescence. The associations largely remained after adjustment for pre-adolescent functioning, selected confounders and current mental health.CONCLUSIONS: Both adolescent trajectories and current mental health had substantial independent effects on early-adult functioning.

Auditory verbal hallucinations (AVH) can be transiently present in both clinical and healthy adolescent populations. It is not yet fully understood why AVH discontinue in some adolescents and persist in others. The aim of this explorative study is to investigate predictors of spontaneous discontinuation of distressing AVH in a school-based sample of adolescents. 1841 adolescents (mean age 12.4 years, 58% female) completed self-report questionnaires at baseline. The current study included 123 adolescents (7%; 63% female) who reported at least mild distressing AVH at baseline and completed follow-up measurements. LASSO analyses were used to uncover predictors of spontaneous discontinuation of distressing AVH. During follow-up, 43 adolescents (35%) reported having experienced distressing AVH during the last 12 months, while 80 adolescents did not. Spontaneous discontinuation of distressing AVH was predicted by never having used cannabis, parents not being divorced in the past year, never having been scared by seeing a deceased body, less prosocial behaviour, school grade repetition, having the feeling that others have it in for you, having anxiety when meeting new people, having lived through events exactly as if they happened before and having the feeling as if parts of the body have changed. No associations between spontaneous discontinuation of distressing AVH and age or ethnicity were found. Distressing AVH in non-clinical adolescents are mostly transient. Discontinuation was predicted up to a certain extent. However, several predictors were difficult to interpret and do not provide leads for preventive measures, except for discouraging cannabis use. Electronic supplementary material The online version of this article (10.1007/s00787-019-01393-7) contains supplementary material, which is available to authorized users.

Background Little is known about the public stigma on mental illness and mental health knowledge (MHK) in China, public stigma and low MHK can negatively affect patients’ health and increase the burden of mental disorders on society. This study aimed at investigating the rates of stigma and MHK, the correlates of stigma and MHK, and the association between MHK and stigma among a Chinese population. Methods The data is from the Tianjin Mental Health Survey (TJMHS), which involved a large and a representative sample of adult community residents in the Chinese municipality of Tianjin (n = 11,748). In a 12% random subsample (n = 1775) the Perceived Discrimination and Devaluation scale (PDD) and a Mental Health Knowledge Questionnaire (MHKQ) were administered. First, percentages of the responses to the individual items of the PDD and MHKQ were investigated. Second, sociodemographic correlates of PDD and MHK, and the association between stigma and MHK were investigated. Results We found that a sizable proportion of participants responded that others would hold a negative attitude towards (former) mental patients, especially with regard to engaging in closer personal relationships. Most people were not familiar about the causes, treatments and prevention of mental illness. Resident area, age, education level, Per capita family income and employment status were related to devaluation score and MHKQ score. MHK was negatively associated with public stigma. Conclusions There is room for improvement with regard to levels of public stigma and MHK in China. Providing psychoeducation to improve public MHK could also contribute to reduction of public stigma.

Many individuals with severe mental disorders have difficulties in vocational and social functioning, which are regarded the most important outcomes, together with clinical symptoms. To understand the underlying mechanisms, research is increasingly focused on factors influencing functional outcomes. One established association has been shown between cognition and community functioning with negative symptoms as a possible mediator. Although it has been shown that negative symptoms consist of two subdomains, thus far negative symptoms have been assessed as one unitary construct. This study considers for the first time subdomains of negative symptoms as putative mediators (expressive deficits, amotivation) of the association between cognition (neuro- and social cognition) and functional outcome (living situation, occupation, social functioning). We expected that specific subdomains of negative symptoms (e.g. amotivation) would mediate the effect of cognition on specific functional outcomes (e.g. social functioning) independently from illness duration. To assess this, we included two independent cohorts, consisting of participants with different illness duration. These two independent cohorts consisted of patients with a recent-onset psychotic disorder: PROGR-S (first time treated; N = 1129) and GROUP (illness duration preferably

Aims The mechanisms underlying both depressive and anxiety disorders remain poorly understood. One of the reasons for this is the lack of a valid, evidence-based system to classify persons into specific subtypes based on their depressive and/or anxiety symptomatology. In order to do this without a priori assumptions, non-parametric statistical methods seem the optimal choice. Moreover, to define subtypes according to their symptom profiles and inter-relations between symptoms, network models may be very useful. This study aimed to evaluate the potential usefulness of this approach. Methods A large community sample from the Canadian general population (N = 254 443) was divided into data-driven clusters using non-parametric k-means clustering. Participants were clustered according to their (co)variation around the grand mean on each item of the Kessler Psychological Distress Scale (K10). Next, to evaluate cluster differences, semi-parametric network models were fitted in each cluster and node centrality indices and network density measures were compared. Results A five-cluster model was obtained from the cluster analyses. Network density varied across clusters, and was highest for the cluster of people with the lowest K10 severity ratings. In three cluster networks, depressive symptoms (e.g. feeling depressed, restless, hopeless) had the highest centrality. In the remaining two clusters, symptom networks were characterised by a higher prominence of somatic symptoms (e.g. restlessness, nervousness). Conclusion Finding data-driven subtypes based on psychological distress using non-parametric methods can be a fruitful approach, yielding clusters of persons that differ in illness severity as well as in the structure and strengths of inter-symptom relationships.

Background: Studies have shown similar efficacy of different antidepressants in the treatment of depression.Method: Data of phase-2 and -3 clinical-trials for 16 antidepressants (levomilnacipran, desvenlafaxine, duloxetine, venlafaxine, paroxetine, escitalopram, vortioxetine, mirtazapine, venlafaxine XR, sertraline, fluoxetine, citalopram, paroxetine CR, nefazodone, bupropion, vilazodone), approved by the FDA for the treatment of depression between 1987 and 2016, were extracted from the FDA reviews that were used to evaluate efficacy prior to marketing approval, which are less liable to reporting biases. Meta-analytic Bayes factors, which quantify the strength of evidence for efficacy, were calculated. In addition, posterior pooled effect-sizes were calculated and compared with classical estimations.Results: The resulted Bayes factors showed that the evidence load for efficacy varied strongly across antidepressants. However, all tested drugs except for bupropion and vilazodone showed strong evidence for their efficacy. The posterior effect-size distributions showed variation across antidepressants, with the highest pooled estimated effect size for venlafaxine followed by paroxetine, and the lowest for bupropion and vilazodone.Limitations: Not all published trials were included in the study.Conclusions: The results illustrate the importance of considering both the effect size and the evidence-load when judging the efficacy of a treatment. In doing so, the currently employed Bayesian approach provided clear insights on top of those gained with traditional approaches.

Psychometric work on the widely used Depression Anxiety and Stress Scales (DASS) has mostly used classical psychometrics and ignored common internet-administered versions. Therefore, the present study used not only classical, but also modern psychometrics based on item response theory (IRT) to evaluate an internet-administered version of the DASS (Dutch translation). Internet-administered DASS data were collected as part of a large internet-based study in the Dutch adult population (n = 7972). Initially, external correlates (i.e. demographics other measures) and some classical psychometrics (internal consistency, convergent/divergent validity) of the DASS scales were evaluated. Next, IRT was used to investigate the scales' dimensionality, discrimination and item-functioning. Finally, the DASS depression scale was further investigated by linking it to the more clinically-oriented Quick Inventory of Depressive Symptomatology (QIDS) using item response theory (IRT). Initial classical psychometric analyses supported the scales' internal consistency (alpha = 0.94-0.98) and convergent/divergent validity. IRT analyses showed that each of the DASS scales was only suitable to measure variations in a very narrow and rather mild severity range. Linking the DASS depression scale with the QIDS also showed that the DASS depression scale discriminated best in the mild-moderate severity range, but not at higher severity levels that were covered by the QIDS. In conclusion, the scales of the internet-administered DASS show good internal consistency and validity. However, users should be aware that the scales discriminate best at mild-moderate severity ranges in the general population.

BackgroundTo effectively shape mental healthcare policy in modern-day China, up-to-date epidemiological data on mental disorders is needed. The objective was to estimate the prevalence, age-of-onset (AOO) and sociodemographic correlates of mental disorders in a representative household sample of the general population (age ⩾ 18) in the Tianjin Municipality in China.MethodsData came from the Tianjin Mental health Survey (TJMHS), which was conducted between July 2011 and March 2012 using a two-phase design. 11 748 individuals were screened with an expanded version of the General Health Questionnaire and 4438 subjects were selected for a diagnostic interview by a psychiatrist, using the Structured Clinical Interview for the Diagnostic and Statistical Manual – fourth edition (SCID).ResultsThe lifetime and 1-month prevalence of any mental disorder were 23.6% and 12.8%, respectively. Mood disorders (lifetime: 9.3%; 1-month: 3.9%), anxiety disorders (lifetime: 4.5% 1-month: 3.1%) and substance-use disorders (lifetime: 8.8%; 1-month: 3.5%) were most prevalent. The median AOO ranged from 25 years [interquartile range (IQR): 23–32] for substance-use disorders to 36 years (IQR: 24–50) for mood disorders. Not being married, non-immigrant status (i.e. local ‘Hukou’), being a farmer, having ConclusionResults from the current survey indicate that mental disorders are steadily reported more commonly in rapidly-developing urban China. Several interesting sociodemographic correlates were observed (e.g. male gender and non-immigrant status) that warrant further investigation and could be used to profile persons in need of preventive intervention.

BACKGROUND: Major depressive disorder (MDD) is characterized by high relapse/recurrence rates. Predicting individual patients' relapse/recurrence risk has proven hard, possibly due to course heterogeneity among patients. This study aimed to (1) identify homogeneous data-driven subgroups with different patterns of relapse/recurrence and (2) identify associated predictors.METHODS: For a year, we collected weekly depressive symptom ratings in 213 primary care MDD patients. Latent class growth analyses (LCGA), based on symptom-severity during the 24 weeks after no longer fulfilling criteria for the initial major depressive episode (MDE), were used to identify groups with different patterns of relapse/recurrence. Associations of baseline predictors with these groups were investigated, as were the groups' associations with 3- and 11-year follow-up depression outcomes.RESULTS: LCGA showed that heterogeneity in relapse/recurrence after no longer fulfilling criteria for the initial MDE was best described by four classes: "quick symptom decline" (14.0%), "slow symptom decline" (23.3%), "steady residual symptoms" (38.7%), and "high residual symptoms" (24.1%). The latter two classes showed lower self-esteem at baseline, and more recurrences and higher severity at 3-year follow-up than the first two classes. Moreover, the high residual symptom class scored higher on neuroticism and lower on extraversion and self-esteem at baseline. Interestingly, the steady residual symptoms and high residual symptoms classes still showed higher severity of depressive symptoms after 11 years.CONCLUSION: Some measures were associated with specific patterns of relapse/recurrence. Moreover, the data-driven relapse/recurrence groups were predictive of long-term outcomes, suggesting that patterns of residual symptoms could be of prognostic value in clinical practice.

Background: Researchers have tried to identify more homogeneous subtypes of major depressive disorder (MDD) with latent class analyses (LCA). However, this approach does no justice to the dimensional nature of psychopathology. In addition, anxiety and functioning-levels have seldom been integrated in subtyping efforts. Therefore, this study used a hybrid discrete-dimensional approach to identify subgroups with shared patterns of depressive and anxiety symptomatology, while accounting for functioning-levels.Methods: The Comprehensive International Diagnostic Interview (CIDI) 1.1 was used to assess previous-year depressive and anxiety symptoms in the Netherlands Mental Health Survey and Incidence Study-1 (NEMESIS 1; n=5583). The data were analyzed with factor analyses, LCA and hybrid mixed-measurement item response theory (MM-IRT) with and without functioning covariates. Finally, the classes' predictors (measured one year earlier) and outcomes (measured two years later) were investigated.Results: A 3-class MM-IRT model with functioning covariates best described the data and consisted of a 'healthy class' (74.2%) and two symptomatic classes ('sleep/energy' [13.4%]; 'mood/anhedonia' [12.4%]). Factors including older age, urbanicity, higher severity and presence of 1-year MDD predicted membership of either symptomatic class vs. the healthy class. Both symptomatic classes showed poorer 2-year outcomes (i.e. disorders, poor functioning) than the healthy class. The odds of MDD after two years were especially increased in the mood/anhedonia class.Limitations: Symptoms were assessed for the past year whereas current functioning was assessed.Conclusions: Heterogeneity of depression and anxiety symptomatology are optimally captured by a hybrid discrete-dimensional subtyping model. Importantly, accounting for functioning-levels helps to capture clinically relevant interpersonal differences.

BackgroundMild psychotic experiences are common in the general population. Although transient and benign in most cases, these experiences are predictive of later mental health problems for a significant minority. The goal of the present study was to perform examinations of the dimensional and discrete variations in individuals’ reporting of subclinical positive and negative psychotic experiences in a unique Dutch internet-based sample from the general population.MethodsPositive and negative subclinical psychotic experiences were measured with the Community Assessment of Psychic Experiences in 2870 individuals. First, the prevalence of these experiences and their associations with demographics, affect, psychopathology and quality of life were investigated. Next, latent class analysis was used to identify data-driven subgroups with different symptom patterns, which were subsequently compared on aforementioned variables.ResultsSubclinical psychotic experiences were commonly reported. Both positive and negative psychotic experiences were associated with younger age, more negative affect, anxiety and depression as well as less positive affect and poorer quality of life. Seven latent classes (‘Low psychotic experiences’, ‘Lethargic’, ‘Blunted’, ‘Distressed’, ‘Paranormal’, ‘Distressed_grandiose’ and ‘Distressed/positive psychotic experiences’) were identified that demonstrated both dimensional differences in the number/severity of psychotic experiences and discrete differences in the patterns of reported experiences.ConclusionSubclinical psychotic experiences show both dimensional severity variations and discrete symptom-pattern variations across individuals. To understand and capture all interindividual variations in subclinical psychotic experiences, their number, nature and context (co-occurrence patterns) should be considered at the same time. Only some psychotic experiences may lay on a true psychopathological psychosis continuum.

BackgroundIn search of empirical classifications of depression and anxiety, most subtyping studies focus solely on symptoms and do so within a single disorder. This study aimed to identify and validate cross-diagnostic subtypes by simultaneously considering symptoms of depression and anxiety, and disability measures.MethodA large cohort of adults (Lifelines, n = 73 403) had a full assessment of 16 symptoms of mood and anxiety disorders, and measurement of physical, social and occupational disability. The best-fitting subtyping model was identified by comparing different hybrid mixture models with and without disability covariates on fit criteria in an independent test sample. The best model's classes were compared across a range of external variables.ResultsThe best-fitting Mixed Measurement Item Response Theory model with disability covariates identified five classes. Accounting for disability improved differentiation between people reporting isolated non-specific symptoms [‘Somatic’ (13.0%), and ‘Worried’ (14.0%)] and psychopathological symptoms [‘Subclinical’ (8.8%), and ‘Clinical’ (3.3%)]. Classes showed distinct associations with clinically relevant external variables [e.g. somatization: odds ratio (OR) 8.1–12.3, and chronic stress: OR 3.7–4.4]. The Subclinical class reported symptomatology at subthreshold levels while experiencing disability. No pure depression or anxiety, but only mixed classes were found.ConclusionsAn empirical classification model, incorporating both symptoms and disability identified clearly distinct cross-diagnostic subtypes, indicating that diagnostic nets should be cast wider than current phenomenology-based categorical systems.

Background Failure to seek treatment for mental health disorders is a serious public health concern. Unfortunately, there is little insight into help-seeking and its associated factors in China which has undergone rapid economic development in the past 30 years and has an increasing prevalence of mental disorder. Therefore, this study aimed to (1) investigate help-seeking rates in healthcare and non-healthcare settings and (2) investigate the correlates of help-seeking behavior in a large Chinese survey. Methods Data came from the Tianjin Mental Health Survey (TJMHS), a representative sample of adult community residents in the Chinese municipality of Tianjin (n = 11,748). Of these, 1759 individuals had ≥1 axis-I diagnosis according to the Diagnostic and Statistical manual– fourth edition (DSM-IV) and were administered a Help-Seeking Questionnaire. Results 15.7% of patients reported that they had ever sought help during their entire lifetime before the interview, with 4.5% seeking help in mental healthcare, 3.2% in other healthcare and 8.1% in non-healthcare settings (e.g., family, friends, and spiritual advisor). Among help-seekers, the first help was mostly sought in non-healthcare settings (58.4%), followed by healthcare (27.5%) and mental healthcare settings (24.5%). Female gender, younger age, having 7–9 years vs 0–6 years of education, a low income, a psychotic disorder and having ≥2 disorders were associated with increased help-seeking. Older age, being married and having a psychotic or organic disorder were associated with increased help-seeking in healthcare vs. non-healthcare settings. Conclusion A small percentage of persons with mental disorders in the Tianjin region seek help and among those who do, variations in the types of help-seeking may be partially explained by demographic and clinical characteristics.

Previous studies have discouraged the use of the Cox proportional hazards (PH) model for traditional mediation analysis as it might provide biased results. Accelerated failure time (AFT) models have been proposed as an alternative for Cox PH models. In addition, the use of the potential outcomes framework has been proposed for mediation models with time-to-event outcomes. The aim of this paper is to investigate the performance of traditional mediation analysis and potential outcomes mediation analysis based on both the Cox PH and the AFT model. This is done by means of a Monte Carlo simulation study and the illustration of the methods using an empirical data set. Both the product-of-coefficients method of the traditional mediation analysis and the potential outcomes framework yield unbiased estimates with respect to their own underlying indirect effect value for simple mediation models with a time-to-event outcome and estimated based on Cox PH or AFT.

Background: In mental health research, functional recovery is increasingly valued as an important outcome in addition to symptomatic remission. Methods: Course types of functional limitations among depressed older patients and its relation with symptomatic remission were explored in a naturalistic cohort study (Netherlands Study of Depression in Older persons). 378 depressed older patients (≥60 years) and 132 non-depressed persons were included. Depressive disorders were assessed with Composite International Diagnostic Interview at baseline and two-year follow-up. Functional limitations were assessed every 6 months with the World Health Organization Disability Assessment II. Results: Depressed patients had more functional limitations compared to their non-depressed counterparts. Growth Mixture Modeling among depressed patients identified two trajectories of functional limitations, both starting at a high disability level. The largest subgroup (81.2%) was characterized by a course of high disability levels over time. The smaller subgroup (18.8%) had an improving course (functional recovery). After two years, the main predictor of functional recovery was the remission of depression. Among symptomatic remitted patients, female sex, higher level of education, higher gait speed, and less severe depression were associated with no functional recovery. Non-remitted patients without functional recovery were characterized by the presence of more chronic somatic diseases, a lower sense of mastery, and a higher level of anxiety. Conclusions: 1 in 5 depressed older patients have a course with functional recovery. Combining functional and symptomatic recovery points to a subgroup of older patients that might profit from more rigorous psychiatric treatment targeted at psychiatric comorbidity and a group of frail depressed older patients that might profit from integrated geriatric rehabilitation.

BACKGROUND Smartphones have become ubiquitous in China, offering a promising way to deliver mental health interventions; however, little is known about the current use and characteristics of smartphone apps for mental health. OBJECTIVE The purpose of this study was to gain insight into mobile mental health apps available in China as of December 2018. METHODS A systematic search was conducted to identify and evaluate the most downloaded apps from iOS and Android platforms. Apps were categorized according to their main purpose and downloaded to evaluate their content. Each app’s affiliation, cost, target users, information security, and evidence-based nature were evaluated. RESULTS Of the 172 unique apps that were identified, there were 37 apps (21.5%) for psychological counseling, 50 apps (29.1%) for assessment, 12 apps (7.0%) to relieve stress, 24 apps (14.0%) for psychoeducation, and 49 (28.4%) multipurpose apps (ie, a combination of counseling and assessment). Most apps were developed for adults in the general population (166/172, 96.5%), rather than for psychiatric patients. App-based counseling was mostly provided by psychologists, and of the assessed apps, only 40% (70/172) used evidence-based scales to assess mental health problems such as anxiety or depressed mood. Guided meditation was used as the main technique in stress-relieving apps. CONCLUSIONS Many apps contained useful and evidence-based elements, such as good quality information, validated measurements, and useful meditation methods; however, for mobile apps to contribute significantly to mental health care in China, considerable challenges remain, including the need for more patient-focused apps that can actually take on the role of a health care provider. In addition, efficacy studies are needed.

Background: Predicting the onset and course of mood and anxiety disorders is of clinical importance but remains difficult. We compared the predictive performances of traditional logistic regression, basic probabilistic machine learning (ML) methods, and automated ML (Auto-sklearn).Methods: Data were derived from the Netherlands Study of Depression and Anxiety. We compared how well multinomial logistic regression, a na?ve Bayes classifier, and Auto-sklearn predicted depression and anxiety diagnoses at a 2-, 4-, 6-, and 9-year follow up, operationalized as binary or categorical variables. Predictor sets included demographic and self-report data, which can be easily collected in clinical practice at two initial time points (baseline and 1-year follow up).Results: At baseline, participants were 42.2 years old, 66.5% were women, and 53.6% had a current mood or anxiety disorder. The three methods were similarly successful in predicting (mental) health status, with correct predictions for up to 79% (95% CI 75?81%). However, Auto-sklearn was superior when assessing a more complex dataset with individual item scores.Conclusions: Automated ML methods added only limited value, compared to traditional data modelling when predicting the onset and course of depression and anxiety. However, they hold potential for automatization and may be better suited for complex datasets.

Objective: Previously published findings from the DepreMI cohort suggested that both the course and the type of depressive symptoms following myocardial infarction (MI) are related to prognosis but did not examine both factors simultaneously. The aim of this reanalysis study was to assess whether MI patients can be empirically classified based on trajectories of cognitive/affective (CA) and somatic/affective (SA) symptoms, and whether these classes differentially predict adverse outcomes. Method: Patients with acute MI (n = 457) were recruited between 1997 and 2000 and provided (BDI-I) data at baseline, 3, 6 and 12 months. Parallel Processes latent class growth analysis was used to identify latent classes. Patients were followed up until 2007 for all-cause mortality and cardiovascular readmissions. Results: Three classes were identified: low severity = consistently low CA and SA (n = 316); somatic persistence = consistently low CA and high SA (n = 110); and overall persistence = high and increasing CA and SA (n = 31). After adjustment for gender and the Global Registry of Acute Coronary Events risk score, somatic persistence (hazard ratio [HR]: 1.86; 95% CI: 1.18 -2.94; p = .008) but not overall persistence (HR: 1.09.; 95% CI: 0.39-3.03; p = .87), predicted mortality compared with low severity. Classes were not predictive of nonfatal cardiovascular events. Conclusions: MI patient classes differed in severity and course of CA and SA depressive symptoms in the post-MI year. Only a class with persistent SA depressive symptoms was associated with increased mortality compared with patients with low severity. This is suggestive of different origins of SA depressive symptoms in MI patients that may explain the differential associations with mortality.

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. Although efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine-learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared with observed scores assessed 10-12 years after baseline. ML model prediction accuracy was also compared with that of conventional logistic regression models. Area under the receiver operating characteristic curve based on ML (0.63 for high chronicity and 0.71-0.76 for the other prospective outcomes) was consistently higher than for the logistic models (0.62-0.70) despite the latter models including more predictors. A total of 34.6-38.1% of respondents with subsequent high persistence chronicity and 40.8-55.8% with the severity indicators were in the top 20% of the baseline ML-predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML-predicted risk distribution. These results confirm that clinically useful MDD risk-stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

Autism traits are found at elevated rates in individuals with schizophrenia spectrum disorders, however, there is a lack of evidence regarding potential clinical impact. The current research aimed to examine potential associations between autism traits and symptoms of psychosis, social and role functioning, and quality of life. 99 individuals experiencing a first episode of psychosis took part in a cross-sectional interview and self-report questionnaire which assessed current symptoms of psychosis, autism traits, functioning, and quality of life. Participants were found to have a high level of autism traits. Higher autism traits were associated with poorer quality of life, functioning, and current psychotic symptoms. Receiver operating characteristic curve (ROC) analyses indicated that optimal AQ cut-off scores to predict severity of psychosis symptoms, functioning, and quality of life were lower than those used to suggest likely autism-spectrum diagnosis. Results suggest that autism traits are associated with poorer clinical presentation in first-episode psychosis populations, even in those whose traits fall below potentially diagnostic thresholds for autism. Psychosis services should be prepared to adequately address the needs of individuals with higher autism traits.