Heterogeneity in 10-Year Course Trajectories of Moderate to Severe Major Depressive Disorder: A Danish National Register-Based Study

The working life expectancy of American adults experiencing depression

OBJECTIVES

To estimate the working life expectancies (WLE) of men and women with depression, examining depression by symptom trajectories from the late 20s to early 50s, and to estimate WLE by race/ethnicity and educational attainment.

METHODS

Data from 9206 participants collected from 1979 to 2018 in the US National Longitudinal Survey of Youth 1979 cohort were used. Depression was measured using the Center for Epidemiologic Studies Depression Scale Short Form at four time points (age 28-35, age 30-37, age 40, and age 50). Labor force status was measured monthly starting at age 30 until age 58-62. Depressive symptom trajectories were estimated using growth mixture modeling and multistate modeling estimated WLE from age 30-60 for each gender and depressive symptom trajectory.

RESULTS

Five latent symptom trajectories were established: a persistent low symptom trajectory (n = 6838), an episodic trajectory with high symptoms occurring before age 40 (n = 995), an episodic trajectory with high symptoms occurring around age 40 (n = 526), a trajectory with high symptoms occurring around age 50 (n = 570), and a persistent high symptom trajectory (n = 277). The WLE for men at age 30 was 30.3 years for the persistent low symptom trajectory, 22.8 years for the episodic before 40 trajectory, 19.6 years for the episodic around age 40 trajectory, 18.6 years for the episodic around age 50 trajectory, and 13.2 years for the persistent high symptom trajectory. Results were similar for women. WLE disparities between depression trajectories grew when stratified by race/ethnicity and education level.

CONCLUSIONS

Roughly a quarter of individuals experienced episodic depressive symptoms. However, despite periods of low depressive symptoms, individuals were expected to be employed ~5-17 years less at age 30 compared to those with low symptoms. Accessible employment and mental health disability support policies and programs across the working life course may be effective in maintaining work attachment and improving WLE among those who experience depression.

Predictive modeling of initiation and delayed mental health contact for depression

BACKGROUND

Depression is prevalent among Operation Enduring Freedom and Operation Iraqi Freedom (OEF/OIF) Veterans, yet rates of Veteran mental health care utilization remain modest. The current study examined: factors in electronic health records (EHR) associated with lack of treatment initiation and treatment delay; the accuracy of regression and machine learning models to predict initiation of treatment.

METHODS

We obtained data from the VA Corporate Data Warehouse (CDW). EHR data were extracted for 127,423 Veterans who deployed to Iraq/Afghanistan after 9/11 with a positive depression screen and a first depression diagnosis between 2001 and 2021. We also obtained 12-month pre-diagnosis and post-diagnosis patient data. Retrospective cohort analysis was employed to test if predictors can reliably differentiate patients who initiated, delayed, or received no mental health treatment associated with their depression diagnosis.

RESULTS

108,457 Veterans with depression, initiated depression-related care (55,492 Veterans delayed treatment beyond one month). Those who were male, without VA disability benefits, with a mild depression diagnosis, and had a history of psychotherapy were less likely to initiate treatment. Among those who initiated care, those with single and mild depression episodes at baseline, with either PTSD or who lacked comorbidities were more likely to delay treatment for depression. A history of mental health treatment, of an anxiety disorder, and a positive depression screen were each related to faster treatment initiation. Classification of patients was modest (ROC AUC = 0.59 95%CI = 0.586-0.602; machine learning F-measure = 0.46).

CONCLUSIONS

Having VA disability benefits was the strongest predictor of treatment initiation after a depression diagnosis and a history of mental health treatment was the strongest predictor of delayed initiation of treatment. The complexity of the relationship between VA benefits and history of mental health care with treatment initiation after a depression diagnosis is further discussed. Modest classification accuracy with currently known predictors suggests the need to identify additional predictors of successful depression management.

Risk of suicidal behavior in patients with major depression and bipolar disorder - A systematic review and meta-analysis of registry-based studies

Suicide is a health priority and one of the most common causes of death in mood disorders. One of the limitations of this type of research is that studies often establish rates of suicide behaviors in mood disorders by using diverse comparison groups or simply monitoring cohort of patients over a time period. In this registry-based systematic review, national registers were identified through searches in six academic databases, and information about the occurrence of suicide behaviors in mood disorders was systematically extracted. Odds ratios were subsequently calculated comparing rates of death by suicide in mood disorders in comparison with age and period matched rates of death by suicide in the general population obtained from country-wide national registers. The aim was to provide the most recent summary of epidemiological and clinical factors associated to suicide in mood disorders whilst calculating the likelihood of death by suicide in mood disorders in comparison with non-affected individuals according to national databases. The study follows the Preferred Reporting Guidelines for Systematic Reviews and Meta-analyses and was prespecify registered on Prospero (CRD42020186857). Results suggest that patients with mood disorders are at substantially increased risk of attempting and dying by suicide. Several epidemiological, clinical and social factors are reported to be associated with clinical populations at risk of suicide. Meta-analyses of completed deaths by suicide suggest that the likelihood for dying by suicide in mood disorders is 8.62 times higher in major depression and 8.66 times higher in bipolar disorder with higher number of untoward events in women compared to men in both conditions. The likelihood of dying by suicide in major depressive disorders is higher in the first year following discharge. Clinical guidelines might consider longer periods of monitoring following discharge from hospital. Overall, due to the higher risk of suicide in mood disorders, efforts should be made to increase detection and prevention whilst focusing on reducing risk in the most severe forms of illness with appropriate treatment to promote response and remission at the earliest convenience.

Childhood maltreatment and association with trajectories of depressive symptoms among older adults: a longitudinal study in China

OBJECTIVES

Childhood maltreatment has long-lasting effects on mental health. Existing evidence suggests that trajectories of depressive symptoms vary among individuals; however, little is known about how childhood maltreatment shapes these trajectory patterns. Therefore, this study investigated the impacts of childhood maltreatment on eight-year depressive trajectories among Chinese older adults.

METHOD

Five waves of longitudinal data from the China Health and Retirement Longitudinal Study were utilized. Growth Mixture Modelling was performed to identify distinct trajectories of depressive symptoms, and multinomial logistic regression was conducted to explore the associations between these trajectories and childhood maltreatment.

RESULTS

Four trajectories of depressive symptoms were identified: the 'no symptoms' class (61.83%), the 'increasing symptoms' class (14.49%), the 'decreasing symptoms' class (16.44%), and the 'chronic symptoms' class (7.24%). Older adults who experienced childhood physical abuse were more likely to be in the 'chronic symptoms' class than in the 'no symptoms' class, whereas emotional neglect did not show a significant association with three problematic trajectories.

CONCLUSION

This study provides empirical evidence that childhood physical abuse increases the likelihood of developing chronic depressive symptoms in later life. To mitigate this risk, it is crucial to institute comprehensive treatment plans that incorporate trauma-informed care principles, employ evidence-based therapies specifically designed to address the long-term effects of abuse, and prioritize regular screening and assessment of mental health among older adults.

Following the children of depressed parents from childhood to adult life: A focus on mood and anxiety disorders

Background

Parental depression increases risk for anxiety and depression in offspring. The transition from adolescence to adulthood is a common risk period for onset of such disorders. However, relatively few studies have considered development of these disorders from childhood to adulthood including multiple assessments during this transition period.

Method

Offspring of depressed parents aged 9-17 years at baseline were followed prospectively for 13 years (n = 337). Average length of follow-up was 16 months between the first and second waves, 13 months between the second and third, and 8 years between the third and fourth. Current (3-month) psychopathology was assessed at each wave using diagnostic interviews. We derived estimates of 3-month prevalence, age at first diagnosis, course and comorbidity of disorders. Social functioning in adult life was assessed at the final wave and we assessed how prior and current disorder impacted adult functioning.

Results

A quarter of young people met criteria for a mood disorder and a third for anxiety disorder at least once. Mood and anxiety disorder prevalence increased from 4.5% and 15.8% respectively in childhood (9-11 years) to 22.3% and 20.9% respectively by age 23-28. Increased prevalence across the transition from adolescence to adulthood was particularly marked in males, while prevalence increased earlier in adolescence in females. Age at first diagnosis varied widely (mood disorder mean = 16.5 years (range 9-26); anxiety disorder mean = 14.5 years (range 9-28)). Over half (52%) reported functional impairment in early adulthood, 31% harmful alcohol use, and 10% self-harm or a suicide attempt. Both previous and current mood or anxiety disorder were associated with functional impairment in early adulthood.

Conclusions

There is a prolonged risk period for mood and anxiety disorders in this group, with prevalence peaking in early adulthood. This highlights the need for prolonged vigilance and effective targeted interventions in the offspring of depressed parents.

Postpartum and non-postpartum depression: a population-based matched case-control study comparing polygenic risk scores for severe mental disorders

It remains inconclusive whether postpartum depression (PPD) and depression with onset outside the postpartum period (MDD) are genetically distinct disorders. We aimed to investigate whether polygenic risk scores (PGSs) for major mental disorders differ between PPD cases and MDD cases in a nested case-control study of 50,057 women born from 1981 to 1997 in the iPSYCH2015 sample in Demark. We identified 333 women with first-onset postpartum depression (PPD group), who were matched with 993 women with first-onset depression diagnosed outside of postpartum (MDD group), and 999 female population controls. Data on genetics and depressive disorders were retrieved from neonatal biobanks and the Psychiatric Central Research Register. PGSs were calculated from both individual-level genetic data and meta-analysis summary statistics from the Psychiatric Genomics Consortium. Conditional logistic regression was used to calculate the odds ratio (OR), accounting for the selection-related reproductive behavior. After adjustment for covariates, higher PGSs for severe mental disorders were associated with increased ORs of both PPD and MDD. Compared with MDD cases, MDD PGS and attention-deficit/hyperactivity disorder PGS were marginally but not statistically higher for PPD cases, with the OR of PPD versus MDD being 1.12 (95% CI: 0 .97-1.29) and 1.11 (0.97-1.27) per-standard deviation increase, respectively. The ORs of PPD versus MDD did not statistically differ by PGSs of bipolar disorder, schizophrenia, or autism spectrum disorder. Our findings suggest that relying on PGS data, there was no clear evidence of distinct genetic make-up of women with depression occurring during or outside postpartum, after taking the selection-related reproductive behavior into account.

Longitudinal Digital Mood Charting in Bipolar Disorder: Experiences with ChronoRecord Over 20 Years

INTRODUCTION

Longitudinal study is an essential methodology for understanding disease trajectories, treatment effects, symptom changes, and long-term outcomes of affective disorders. Daily self-charting of mood and other illness-related variables is a commonly recommended intervention. With the widespread acceptance of home computers in the early 2000s, automated tools were developed for patient mood charting, such as ChronoRecord, a software validated by patients with bipolar disorder. The purpose of this study was to summarize the daily mood, sleep, and medication data collected with ChronoRecord, and highlight some of the key research findings. Lessons learned from implementing a computerized tool for patient self-reporting are also discussed.

METHODS

After a brief training session, ChronoRecord software for daily mood charting was installed on a home computer and used by 609 patients with affective disorders.

RESULTS

The mean age of the patients was 40.3±11.8 years, a mean age of onset was 22±11.2 years, and 71.4% were female. Patients were euthymic for 70.8% of days, 15.1% had mild depression, 6.6% had severe depression, 6.6% had hypomania, and 0.8% had mania. Among all mood groups, 22.4% took 1-2 medications, 37.2% took 3-4 medications, 25.7 took 5-6 medications, 11.6% took 7-8 medications, and 3.1% took >8 medications.

CONCLUSION

The daily mood charting tool is a useful tool for increasing patient involvement in their care, providing detailed patient data to the physician, and increasing understanding of the course of illness. Longitudinal data from patient mood charting was helpful in both clinical and research settings.

Objective polysomnography-based sleep features and major depressive disorder subtypes in the general population

Insomnia and its opposite hypersomnia are part of the diagnostic criteria for major depressive disorder (MDD). However, no study has investigated whether the postulated sleep alterations in clinical subtypes of MDD are reflected in polysomnography (PSG)-derived objective sleep measures. The objective of this study was to establish associations between the melancholic, atypical and unspecified subtypes of MDD and objective PSG-based sleep features. This cross-sectional analysis included 1820 community-dwelling individuals who underwent PSG and a semi-structured psychiatric interview to elicit diagnostic criteria for MDD and its subtypes. Adjusted robust linear regression was used to assess associations between MDD subtypes and PSG-derived objective sleep measures. Current melancholic MDD was significantly associated with decreased absolute delta power and sleep efficiency and with increased wake after sleep onset. Remitted unspecified MDD was significantly associated with increased rapid eye movements density. No other significant associations were identified. Our findings reflect that some PSG-based sleep features differed in MDD subtypes compared with no MDD. The largest number of significant differences were observed for current melancholic MDD, whereas only rapid eye movements density could represent a risk factor for MDD as it was the only sleep measure that was also associated with MDD in remitted participants.

Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting

The risk of relapse after antidepressant medication (ADM) discontinuation is high. Predictors of relapse could guide clinical decision-making, but are yet to be established. We assessed demographic and clinical variables in a longitudinal observational study before antidepressant discontinuation. State-dependent variables were re-assessed either after discontinuation or before discontinuation after a waiting period. Relapse was assessed during 6 months after discontinuation. We applied logistic general linear models in combination with least absolute shrinkage and selection operator and elastic nets to avoid overfitting in order to identify predictors of relapse and estimated their generalisability using cross-validation. The final sample included 104 patients (age: 34.86 (11.1), 77% female) and 57 healthy controls (age: 34.12 (10.6), 70% female). 36% of the patients experienced a relapse. Treatment by a general practitioner increased the risk of relapse. Although within-sample statistical analyses suggested reasonable sensitivity and specificity, out-of-sample prediction of relapse was at chance level. Residual symptoms increased with discontinuation, but did not relate to relapse. Demographic and standard clinical variables appear to carry little predictive power and therefore are of limited use for patients and clinicians in guiding clinical decision-making.

The 10-year trajectories of auditory hallucinations among 496 patients with a first schizophrenia-spectrum disorder: Findings from the OPUS cohort

BACKGROUND

Auditory hallucinations represent a key diagnostic feature of schizophrenia and one of the most frequent and debilitating psychotic symptoms. However, little is known regarding their long-term trajectories.

METHODS

We included 496 patients with a first schizophrenia-spectrum disorder. Patients were at baseline and after one, two, five, and ten years asked for auditory hallucinations, scoring from 0 ("None") to 5 ("Severe: Voices occur often every day"). We performed latent class growth analyses to identify trajectories of auditory hallucinations and multinomial logistic regression analyses to estimate predictors of trajectory membership.

RESULTS

We identified three trajectories of auditory hallucinations. The Low-Decreasing class (77%) had the lowest mean score at baseline (mean score = 2.1). The score improved within the first year (mean score = 0.5) and stayed low (mean score = 0 after ten years). The High-Fluctuating class (10%) improved during the first two years from a mean score of 3.0 to 1.0, but increased after five and ten years (mean score = 2.4). The High-Increasing class (13%) started at a high level (mean score = 3.5), improved a little after one year (mean score = 3.0), but increased to a mean score of 4.8 after ten years. Alcohol misuse and longer duration of untreated psychosis were associated with increased odds of being in the High-Increasing compared to the Low-Decreasing class.

CONCLUSIONS

The majority of patients with schizophrenia-spectrum disorder improved on auditory hallucinations during the first ten years, but almost one out of four had a fluctuating course with 13% experiencing an increase to severe and daily auditory hallucinations after ten years.

Association between air pollution exposure and mental health service use among individuals with first presentations of psychotic and mood disorders: retrospective cohort study

BACKGROUND

Growing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset.

AIMS

To examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders.

METHOD

We identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008-2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods.

RESULTS

Following covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5-34%), 18% (95% CI 5-34%) and 11% (95% CI 3-19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25-38%), 31% (95% CI 24-37%), 7% (95% CI 4-11%) and 9% (95% CI 5-14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years.

CONCLUSIONS

Residential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.

Common and specific determinants of 9-year depression and anxiety course-trajectories: A machine-learning investigation in the Netherlands Study of Depression and Anxiety (NESDA)

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_pred) were calculated.

RESULTS

Low to high prediction correlations (ρ_pred: 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.

Trajectories of EBV DNA and identifying the potential long-term survivors in metastatic nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is highly incident in southern China. Distant metastasis is the leading cause of death in NPC patients. However, the phenotypical feature of this patient population is largely undefined. The current study aimed to categorize metastatic NPC patients into novel subgroups based on their EBV DNA trajectories. In this retrospective study, 446 eligible patients with metastatic NPC treated at Sun Yat-Sen University Cancer Center between 2012 and 2016 were analyzed. Using a mixture model analysis, we identified distinct trajectories based on longitudinal EBV DNA measurements. We evaluated their associations with metastatic NPC mortality using Cox regression analysis. The two-class trajectory model provided the best fit, in which 272 patients were classified as non-sustained EBV DNA class and 174 patients as sustained EBV DNA class. After a median follow-up of 60.8 months, the median OS was 61.7 months in the sustained EBV DNA clearance class versus 20.0 months in the non-sustained EBV DNA clearance class (P<0.001). Compared with patients in the non-sustained EBV DNA clearance class, patients in the sustained EBV DNA clearance class demonstrated superior PFS (HR, 3.238; 95% CI, 2.601-4.032; P<0.001). Forty-three patients experienced disease-free for longer than 36 months, defined as long-term survivors (LTS). Notably, 41 patients were presented in the sustained EBV DNA clearance class (95.3%), along with only 2 patients in the non-sustained EBV DNA clearance class. Collectively, we identified two EBV DNA trajectory sub-phenotypes of patients with metastatic NPC, providing more reliable survival information for physicians and patients during their informed decision-making process.

Postnatal Major Depressive Disorder in Australia: Inequalities and Costs of Healthcare to Individuals, Governments and Insurers

BACKGROUND

Perinatal mental health has pervasive impacts on the wellbeing of both the mother and child, affecting quality of life, bonding and attachment and cognitive development.

OBJECTIVES

The aim of this study was to (i) quantify the costs to government healthcare funders, private health insurers and individuals through out-of-pocket fees, of women with postnatal major depressive disorder (MDD); and (ii) identify any socioeconomic inequalities in health service use and costs amongst these women.

METHODS

A whole-of-population linked administrative dataset containing the clinical records and health service use for all births in the state of Queensland, Australia between 01 July 2012 and 30 June 2015 was used (n = 189,081). Postnatal MDD was classified according to ICD-10 code, with women hospitalised for MDD in the 12 months after birth classified as having 'postnatal MDD' (n = 728). Health service use and costs from birth to 12 months post-birth were included. Total costs included cost to government funders and private health insurers and out-of-pocket fees. Total costs and costs to different funders were compared for women with postnatal MDD and for women without an inpatient event for postnatal MDD, with unadjusted means presented. A generalised linear model was used to compare the difference in total costs, adjusting for key confounders. Costs to different funders and number of different services accessed were then compared for women with postnatal MDD by socioeconomic status, with unadjusted means presented.

RESULTS

The total costs from birth to 12 months post-birth were 636% higher for women with postnatal MDD than women without an inpatient event for postnatal MDD, after accounting for differences in private hospital use, mode of birth, clinical characteristics and socioeconomic status. Amongst women with postnatal MDD, the cost of all services accessed was higher for women of highest socioeconomic status than for women of lowest socioeconomic status (A$15,787.66 vs A$11,916.94). The cost of services for women of highest socioeconomic status was higher for private health insurers (A$8941.25 vs A$2555.26), but lower for public hospital funders (A$2423.39 vs A$6582.09) relative to women of lowest socioeconomic status. Outside of public hospitals, costs to government funders was higher for women of highest socioeconomic status (A$2766.80 vs A$1952.00). Women of highest socioeconomic status accessed more inpatient (8.2 vs 3.1) and specialist services (13.4 vs 5.5) and a higher proportion had access to psychiatric specialist care (39.7% vs 13.6%) and antidepressants (97.6% vs 93.8%).

CONCLUSION

MDD is costly to all funders of healthcare. Amongst women with MDD, there are large differences in the types of services accessed and costs to different funders based on socioeconomic status. There may be significant financial and structural barriers preventing equal access to care for women with postnatal MDD.

Association of remote traumatic brain injury and military employment with late-life trajectories of depressive symptom severity

BACKGROUND

Traumatic brain injury (TBI) and military service are common lifetime exposures among current older adults that may affect late-life mental health. The objective of the present study was to evaluate the association between TBI with loss of consciousness (LOC) and military employment and late-life depressive symptom severity trajectory.

METHODS

1445 males and 2096 females adults at least 65 years old without dementia or recent TBI were enrolled and followed biennially for up to 10 years in the Adult Changes in Thought study from Kaiser Permanente Washington in Seattle, Washington.

RESULTS

Using group-based trajectory modeling, we documented four distinct depressive symptom severity trajectories that followed a similar course in males and females (Minimal, Decreasing, Increasing, and Persistent). In multinomial regression analyses, TBI with LOC in males was associated with greater likelihood of Persistent versus Minimal depressive symptom severity compared to individuals without TBI (OR = 1.51, 95% CI: 1.01, 2.27; p=0.046). Males reporting past military employment had greater likelihood of Decreasing versus Minimal depressive symptom severity compared to individuals without past military employment (OR = 1.54, 95% CI: 1.03, 2.31; p=0.035). There was no association between TBI or military employment and depression trajectories in females, and no evidence of effect modification by age or between exposures.

LIMITATIONS

Lifetime history of TBI was ascertained retrospectively and may be subject to recall bias. Also, past military employment does not presuppose combat exposure.

CONCLUSIONS

Remote TBI and past military employment are relevant to late-life trajectories of depressive symptom severity in dementia-free older males.

Employment and earnings trajectories before and after sickness absence due to major depressive disorder: a nationwide case-control study

OBJECTIVES

To examine employment and earnings trajectories before and after the first sickness absence period due to major depressive disorder (MDD).

METHODS

All individuals (n=158 813) in Finland who had a first sickness absence period (lasting longer than 9 days) due to MDD between 2005 and 2015 were matched with one randomly selected individual of the same age and gender with no history of MDD. Employment status and earnings were measured using register-based data annually from 2005 to 2015. Generalised estimating equations were used to examine the trajectories of employment and earnings before and after MDD diagnosis in men and women separately.

RESULTS

Sickness absence due to MDD was associated with increased probability of non-employment during and after the year of the first sickness absence period. In men, but not in women, the probability of being employed was lower 5 years before the sickness absence period due to MDD. When compared with the individuals in the control group, men had around 34% and women 15% lower earnings 1 year, and 40% and 23%, respectively, 5 years, after the first sickness absence period due to MDD. More severe MDD and longer duration of sickness absence period were associated with lower probability of being employed.

CONCLUSIONS

Sickness absence due to MDD was associated with considerable reduction in employment and earnings losses. For men and individuals with more severe MDD, this reduction was before the first sickness period. This supports a reciprocal association between employment and earnings with MDD.

Mental Health Challenges of United States Healthcare Professionals During COVID-19

As COVID-19 continues to impact global society, healthcare professionals (HCPs) are at risk for a number of negative well-being outcomes due to their role as care providers. The objective of this study was to better understand the current psychological impact of COVID-19 on HCPs in the United States This study used an online survey tool to collect demographic data and measures of well-being of adults age 18 and older living in the United States between March 20, 2020 and May 14, 2020. Measures included anxiety and stress related to COVID-19, depressive symptoms, current general anxiety, health questions, tiredness, control beliefs, proactive coping, and past and future appraisals of COVID-related stress. The sample included 90 HCPs and 90 age-matched controls (M_age = 34.72 years, SD = 9.84, range = 23 – 67) from 35 states of the United States. A multivariate analysis of variance was performed, using education as a covariate, to identify group differences in the mental and physical health measures. HCPs reported higher levels of depressive symptoms, past and future appraisal of COVID-related stress, concern about their health, tiredness, current general anxiety, and constraint, in addition to lower levels of proactive coping compared to those who were not HCPs (p < 0.001, η² = 0.28). Within the context of this pandemic, HCPs were at increased risk for a number of negative well-being outcomes. Potential targets, such as adaptive coping training, for intervention are discussed.

Predicting individual clinical trajectories of depression with generative embedding

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Patients with major depressive disorder (MDD) show variable clinical trajectories.

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Generative embedding (GE) is used to predict clinical trajectories in MDD patients.

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GE classifies patients with chronic depression vs. fast remission with 79% accuracy.

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GE provides mechanistic interpretability and outperforms conventional measures.

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Proof-of-concept that illustrates the potential of GE for clinical prediction.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy – generative embedding (GE) – which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.

Clinical state tracking in serious mental illness through computational analysis of speech

Individuals with serious mental illness experience changes in their clinical states over time that are difficult to assess and that result in increased disease burden and care utilization. It is not known if features derived from speech can serve as a transdiagnostic marker of these clinical states. This study evaluates the feasibility of collecting speech samples from people with serious mental illness and explores the potential utility for tracking changes in clinical state over time. Patients (n = 47) were recruited from a community-based mental health clinic with diagnoses of bipolar disorder, major depressive disorder, schizophrenia or schizoaffective disorder. Patients used an interactive voice response system for at least 4 months to provide speech samples. Clinic providers (n = 13) reviewed responses and provided global assessment ratings. We computed features of speech and used machine learning to create models of outcome measures trained using either population data or an individual's own data over time. The system was feasible to use, recording 1101 phone calls and 117 hours of speech. Most (92%) of the patients agreed that it was easy to use. The individually-trained models demonstrated the highest correlation with provider ratings (rho = 0.78, p<0.001). Population-level models demonstrated statistically significant correlations with provider global assessment ratings (rho = 0.44, p<0.001), future provider ratings (rho = 0.33, p<0.05), BASIS-24 summary score, depression sub score, and self-harm sub score (rho = 0.25,0.25, and 0.28 respectively; p<0.05), and the SF-12 mental health sub score (rho = 0.25, p<0.05), but not with other BASIS-24 or SF-12 sub scores. This study brings together longitudinal collection of objective behavioral markers along with a transdiagnostic, personalized approach for tracking of mental health clinical state in a community-based clinical setting.

Stability of clinically relevant depression symptoms in old-age across 11 cohorts: a multi-state study

AIMS

To study the temporal dynamics of depression symptom episodes in old-age and the related influence of risk factors.

METHODS

Data from 41 362 old adults (54.61% women; mean age = 75.30, SD = 6.20) from the Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project were used. Depressive symptoms were followed over an 18-year period. A multi-state model, comprising three statuses (no depression, new clinically relevant episode of symptoms and episode persistence), was fitted. Multinomial regression was used to study the role of risk factors in status transition.

RESULTS

Almost 85% of participants showed no depression, but prevalence became lower over time (B = -0.25, P < 0.001). New episode point prevalence was over 5.30% with a significant probability of moving to persistence status (transition probability = 0.27). Episode persistence became evident in 9.86% of episode status transitions, with increasing rate over time (B = 0.54, P < 0.01). Loneliness was proven to be the strongest predictor of episode emergence (OR = 17.76) and persistence (OR = 5.93).

CONCLUSIONS

The course of depression tends to become chronic and unremitting in old-age. This study may help to plan interventions to tackle symptom escalation and risk factor influence.

Major depression subtypes are differentially associated with migraine subtype, prevalence and severity

Objective

Migraine and major depressive disorder show a high rate of comorbidity, but little is known about the associations between the subtypes of major depressive disorder and migraine. In this cross-sectional study we aimed at investigating a) the lifetime associations between the atypical, melancholic, combined and unspecified subtype of major depressive disorder and migraine with and without aura and b) the associations between major depressive disorder and its subtypes and the severity of migraine.

Methods

A total of 446 subjects with migraine (migraine without aura: n = 294; migraine with aura: n = 152) and 2511 controls from the population-based CoLaus/PsyCoLaus study, Switzerland, were included. Associations between major depressive disorder subtypes and migraine characteristics were tested using binary logistic or linear regression.

Results

Melancholic, combined and unspecified major depressive disorder were associated with increased frequency of migraine with aura, whereas only melancholic major depressive disorder was associated with increased frequency of migraine without aura. Lifetime and unspecified major depressive disorder were associated with severe migraine intensity among subjects with migraine with aura but not migraine without aura, while combined major depressive disorder was associated with higher migraine frequency independently from migraine subtype.

Conclusion

This study suggests that melancholic but not atypical major depressive disorder is associated with migraine and migraine subtypes. Future studies exploring pathophysiological mechanisms shared between melancholic depression and migraine are warranted.

Incidence of medically treated depression in Denmark among individuals 15-44 years old: a comprehensive overview based on population registers

OBJECTIVE

Examine the overall incidence of medically treated depression in Denmark among individuals 15-44 years old, and estimate the 5-year cumulative incidence of psychiatric hospital care among individuals treated first in non-hospital-based care.

METHODS

We followed all individuals born in Denmark between 1969 and 1998 from age 15 or 2006 (whichever came first) until first depression treatment; death; emigration; or December 31, 2013. Incidence rates were estimated using Poisson regression. Cumulative incidence of hospital care following treatment in non-hospital care was estimated using Kaplan-Meier curves.

RESULTS

In this sample of 2 014 760 individuals, incidence rates of depression in non-hospital and hospital-based care in 2012-2013 were 6.6 (95% Confidence Interval: 6.5-6.7) per 1000 person-years and 1.5 (95% CI: 1.5-1.6) per 1000 person-years, respectively. Overall, 85-90% of first medical treatment for depression took place outside of psychiatric hospitals, but a quarter (26.3%) of individuals treated for depression received hospital care initially or within 5 years. Incidence of hospital care was higher in women and younger individuals.

CONCLUSIONS

Most medical treatment for depression in Denmark takes place in non-hospital settings. Women and younger individuals are more likely to receive hospital care both initially and within 5 years after first antidepressant treatment.

Trajectories of depression and anxiety symptom change during psychological therapy

BACKGROUND

Forty-percent of the variance in psychological treatment outcomes is estimated to be explained by symptom change by the third treatment session. However, change may not be uniform across patient groups and symptom domains. This study aimed to identify subgroups of patients with different trajectories of depression and anxiety symptom change during psychological therapy and identify baseline patient characteristics associated with these trajectories.

METHODS

4394 patients attending two psychological treatment services completed sessional, self-report depression and anxiety measures. Trajectories of symptom change were investigated using latent class growth analysis. Multinomial logistic regression was used to explore associations between baseline patient characteristics and trajectory classes.

RESULTS

A number of distinct trajectories were identified. Anxiety symptom trajectories could be distinguished by the third treatment session, but for depression symptoms there was a class displaying limited change until session six followed by rapid improvement in symptoms thereafter. Compared to the non-responding trajectories, depression and anxiety trajectories indicating treatment response were associated with lower baseline severity, better social functioning and lower incidence of phobic anxiety, but not with medication prescription status.

LIMITATIONS

Data came from two services, so wider generalisability is unknown. Predictors were limited to data routinely collected in the services; unmeasured factors may have improved the prediction of trajectories.

CONCLUSIONS

Baseline characteristics and symptom change early in therapy can help identify different trajectories of symptom change. This knowledge could aid clinical decision making and help improve treatment outcomes. By ignoring distinct trajectories, clinicians may incorrectly consider patients as "not-on-track" and unnecessarily change or end therapy that would otherwise benefit patients.

Predictors of change in depressive symptoms over time: Results from the Australian Longitudinal Study on Women's Health

BACKGROUND

Depressive symptoms fluctuate over time, and are most common amongst women in early adulthood. Understanding predictors of changes in depressive symptoms among young women may inform health promotion and early intervention.

METHODS

Data were collected at three-yearly intervals from 2000 (Survey 2) to 2012 (Survey 6) from the Australian Longitudinal Study on Women's Health. The sample comprised 7663 women, aged 22-27 in 2000, who reported any indicator of poor mental health at any wave. Generalised linear mixed models identified predictors of change in depressive symptoms (CESD-10) over each three-year period.

RESULTS

Depressive symptoms reduced over time. In a fully adjusted model, greater reduction in symptoms was predicted by higher initial symptoms, time, higher social support, and higher self-rated general health. Slower reduction was predicted by lower education, difficulty managing on income, high or zero alcohol consumption, stress, and history of childhood sexual assault or partner violence. Motherhood predicted an increase in depressive symptoms at Survey 2 (2000), but a decrease at Survey 5 (2009).

LIMITATIONS

Although sampling was nationally representative, there is a slight bias towards Australian-born and more educated women. Further, although validated measures are used, all data are self-report.

CONCLUSIONS

Fluctuations in depressive symptoms among young women are related to fixed and time-varying factors spanning multiple health and social domains. A range of factors, including education and financial resources, promotion of positive social support systems, and encouragement of health promoting lifestyles, might serve to promote young women's mental health and thus to reduce pressure on clinical services.

Trajectories of depressive symptoms in the acute phase of psychosis: Implications for treatment

Depression is common in schizophrenia and associated with negative outcomes. Previous studies have identified heterogeneity in treatment response in schizophrenia. We aimed to investigate different trajectories of depression in patients suffering from psychosis and predictors of change in depressive symptoms during antipsychotic treatment. Two hundred and twenty-six patients >18 years acutely admitted due to psychosis were consecutively included and the follow-up was 27 weeks. The Calgary Depression Scale for Schizophrenia (CDSS) sum score was the primary outcome. Latent growth curve (LGCM) and Growth Mixture Models (GMM) were conducted. Predictors were the Positive sum score of the Positive and Negative Syndrome Scale for Schizophrenia (PANSS), Schizophrenia spectrum/non-spectrum psychoses, gender and being antipsychotic naive at inclusion. We found support for three depression-trajectories, including a high- (14.7%), a low depression-level (69.6%) class and a third depressed class quickly decreasing to a low level (15.7%). Change in CDSS was associated with change in PANSS positive score in all time intervals (4 weeks: b = 0.18, p < 0.001, 3 months: 0.21, p < 0.023, 6 months: 0.43, p < 0.001) and with a diagnosis within schizophrenia spectrum but not with antipsychotic naivety or gender. The schizophrenia-spectrum patients had less depressive symptoms at inclusion (-2.63, p < 0.001). In conclusion, an early responding and a treatment refractory group were identified. The treatment-refractory patients are candidates for enhanced anti-depressive treatment, for which current evidence is limited. The post-psychotic depression group was characterized by depressive symptoms in the acute phase as well. We could not identify differentiating characteristics of the depression trajectories.

Sex similarities and differences in risk factors for recurrence of major depression

BACKGROUND

Major depression (MD) occurs about twice as often in women as in men, but it is unclear whether sex differences subsist after disease onset. This study aims to elucidate potential sex differences in rates and risk factors for MD recurrence, in order to improve prediction of course of illness and understanding of its underlying mechanisms.

METHODS

We used prospective data from a general population sample (n = 653) that experienced a recent episode of MD. A diverse set of potential risk factors for recurrence of MD was analyzed using Cox models subject to elastic net regularization for males and females separately. Accuracy of the prediction models was tested in same-sex and opposite-sex test data. Additionally, interactions between sex and each of the risk factors were investigated to identify potential sex differences.

RESULTS

Recurrence rates and the impact of most risk factors were similar for men and women. For both sexes, prediction models were highly multifactorial including risk factors such as comorbid anxiety, early traumas, and family history. Some subtle sex differences were detected: for men, prediction models included more risk factors concerning characteristics of the depressive episode and family history of MD and generalized anxiety, whereas for women, models included more risk factors concerning early and recent adverse life events and socioeconomic problems.

CONCLUSIONS

No prominent sex differences in risk factors for recurrence of MD were found, potentially indicating similar disease maintaining mechanisms for both sexes. Course of MD is a multifactorial phenomenon for both males and females.

A Review on the General Stability of Mood Disorder Diagnoses Along the Lifetime

PURPOSE OF REVIEW

The purpose of this review is to review the most recent literature regarding diagnostic stability of mood disorders, focusing on epidemiological, clinical-psychopathological, and neurobiological data for unipolar and bipolar affective disorders.

RECENT FINDINGS

Unipolar depression follows a chronic course in at least half of all cases and presents a considerable diagnostic stability across all age ranges. Studies using latent class analysis are allowing improved profiling of depressive subtypes and assessment of their prevalence. Advances have been made in our understanding of the neurobiological underpinnings of depression, with data highlighting the roles of amyloid deposits, the ApoE4 allele, and atrophy of the anterior hippocampus or frontal cortex. The diagnostic instability of bipolar disorder is manifest in the early years, seen in both the extent of diagnostic delay and the high rate of diagnostic conversion from unipolar depression. Regarding disruptive mood dysregulation disorder, we have little data to date, but those which exist indicate a high rate of comorbidity and minimal diagnostic stability for this disorder. Diagnostic stability varies substantially among mood disorders, which would be related to the validity of current diagnostic categories and our diagnostic accuracy.

Number of illness episodes as predictor of residual symptoms in major depressive disorder

Notwithstanding major depressive disorder (MDD) is a recurring and chronic condition, relatively few variables have consistently been shown to predict its course. Residual depressive symptoms may be associated with disability and functional impairment but few studies evaluated clinical correlates associated with these symptoms and their impact on functioning after adjustment for potential confounders. Therefore, our study aimed to investigate factors associated with residual depressive symptoms and their impact on the course of MDD. The sample consisted of 210 consecutive MDD euthymic outpatients (67.6% females; mean age = 52.1 ± 15.5), admitted to the Section of Psychiatry, University of Genoa (Italy). Residuals depressive symptoms were significantly associated with female gender; use of short half-life benzodiazepines; longer duration of the current depressive episode; higher number of illness episodes; and higher duration of illness. Conversely, prior treatment with first-generation antipsychotics, later age of illness onset and first hospitalization were less frequently observed among patients with residual symptoms. After multivariate analyses, only duration of current illness episodes (ß = 0.003; p = <0.005) and substance abuse (ß = 0.042; p = <0.05) remained significantly associated with residual symptoms. Our findings indicate that residual depressive symptoms conferred a pernicious illness course in this specific cohort of MDD patients. Future trials mainly targeting these burdensome symptoms are warranted.

Variation in the 12-Month Treatment Trajectories of Children and Adolescents After a Diagnosis of Depression

IMPORTANCE

Depression during childhood and adolescence is heterogeneous. Treatment patterns are often examined in aggregate, yet there is substantial variability across individual treatment trajectories. Understanding this variability can help identify treatment gaps among youths with depression.

OBJECTIVE

To characterize heterogeneity in 12-month trajectories of psychotherapy and antidepressant treatment in youths with depression.

DESIGN, SETTING, AND PARTICIPANTS

This is a longitudinal-cohort study of youths 18 years or younger with a new diagnosis of depression and at least 12 months of follow-up following diagnosis, as determined from commercial insurance claims filed from 2007 to 2014. Latent class models were fit to summary measures of psychotherapy and antidepressant use in the 12 months following the index diagnosis. We examined variation in baseline health, health care utilization, and health outcomes across classes with similar patterns of psychotherapy and antidepressant use. Data analysis took place between June 2016 and March 2017.

MAIN OUTCOMES AND MEASURES

Psychotherapy and antidepressant use.

RESULTS

The cohort included 84 909 individuals with a mean (SD) age at index diagnosis of 15.0 (2.6) years, of whom 49 995 (59%) were female. Attention-deficit/hyperactivity disorder (n = 14 625; 17%) and anxiety (n = 12 358; 15%) were the most common comorbid diagnoses. During the assessment period, 59 023 individuals (70%) received psychotherapy at any point, and 33 997 individuals (40%) were dispensed antidepressants at any point. Eight classes with distinct treatment trajectories were identified, which we classified into 4 broad groups: 3 classes that received dual therapy (n = 18 710; 22%), 2 classes that received antidepressant monotherapy (n = 15 287; 18%), 2 classes that received psychotherapy monotherapy (n = 40 313; 48%) and 1 class that received no treatment (n = 10 599; 13%). The most common class received psychotherapy monotherapy (n = 35 243; 42%) and had the lowest incidence of attempted suicide (0.8 per 100 person-years [PY]) and inpatient hospitalization (3.5 per 100 PY) during the assessment period and postassessment period (0.5 per 100 PY and 1.3 per 100 PY, respectively). The group receiving dual therapy had the highest incidence of attempted suicide during the assessment period (4.7-7.1 per 100 PY, depending on the class) and postassessment period (1.5-1.7 per 100 PY).

CONCLUSIONS AND RELEVANCE

In our sample, 13% of youths received no treatment, and 18% received antidepressants without concomitant psychotherapy. Summary measures of treatment can mask informative patterns of psychotherapy and antidepressant use. Latent class analysis can be used to identify subgroups of individuals with similar treatment trajectories and help identify treatment gaps under current practice patterns.

Trajectories of suicidal ideation over 6 months among 482 outpatients with bipolar disorder

INTRODUCTION

Suicidal ideation occurs frequently among individuals with bipolar disorder; however, its course and persistence over time remains unclear. We aimed to investigate 6-months trajectories of suicidal ideation among adults with bipolar disorder.

METHODS

The Bipolar CHOICE study randomized 482 outpatients with bipolar disorder to 6 months of lithium- or quetiapine-based treatment including other psychotropic medications as clinically indicated. Participants were asked at 9 visits about suicidal ideation using the Concise Health Risk Tracking scale. We performed latent Growth Mixture Modelling analysis to empirically identify trajectories of suicidal ideation. Multinomial logistic regression analyses were applied to estimate associations between trajectories and potential predictors.

RESULTS

We identified four distinct trajectories. The Moderate-Stable group represented 11.1% and was characterized by constant suicidal ideation. The Moderate-Unstable group included 2.9% with persistent thoughts about suicide with a more fluctuating course. The third (Persistent-low, 20.8%) and fourth group (Persistent-very-low, 65.1%) were characterized by low levels of suicidal ideation. Higher depression scores and previous suicide attempts (non-significant trend) predicted membership of the Moderate-Stable group, whereas randomized treatment did not.

LIMITATIONS

No specific treatments against suicidal ideation were included and suicidal thoughts may persist for several years.

CONCLUSION

More than one in ten adult outpatients with bipolar disorder had moderately increased suicidal ideation throughout 6 months of pharmacotherapy. The identified predictors may help clinicians to identify those with additional need for treatment against suicidal thoughts and future studies need to investigate whether targeted treatment (pharmacological and non-pharmacological) may improve the course of persistent suicidal ideation.

Dual trajectories of breakfast eating and fruit and vegetable intake over a 5-year follow-up period among economically disadvantaged children: Gender differences

Breakfast eating (BE) seems to be cross-sectionally associated with fruit and vegetable intake (FVI). To date, gender differences in any codevelopment between BE and FVI, as well as their associated factors, have not been examined. The objectives of this study were (1) to identify dual trajectories of BE and FVI among economically disadvantaged boys and girls; and (2) to examine potential associated factors of identified dual trajectories by gender. Children from economically disadvantaged families were enrolled in this prospective multicity study of the Taiwan Database of Children and Youth in Poverty between July 6 and October 31, 2009 and followed up biannually (2009, 2011, and 2013). One thousand one children (50.2% girls, mean ages at each time point being 9.1, 11.2 and 13.1 years, respectively; 49.8% boys, 9.0, 11.0 and 13.0 years) who completed at least two of the three assessments were included. Dual trajectories of BE and FVI over a 5-year follow-up period were identified as the outcome variables of interest by using mainly group-based dual trajectory modeling. Nine potential associated factors were then examined using logistic regression models. Two distinct dual trajectories of BE and FVI were identified among the girls: longitudinally irregular (68.8%) and shift to irregular (31.2%). Two distinct dual trajectories of BE and FVI were identified among the boys: longitudinally irregular (90.2%) and consistently regular (9.8%). Age was the significantly associated factor for boys. The findings confirmed a heterogeneous codevelopment between BE and FVI that may indicate different underlying mechanisms. Most children with a longitudinally irregular BE pattern had a similar pattern of FVI. Future research should comprehensively explore the gender differences in the determinants of codevelopment between BE and FVI.

Trajectories of relapse in randomised, placebo-controlled trials of treatment discontinuation in major depressive disorder: an individual patient-level data meta-analysis

BACKGROUND

Understanding patterns of relapse in patients who respond to antidepressant treatment can inform strategies for prevention of relapse. We aimed to identify distinct trajectories of depression severity, assess whether similar or different trajectory classes exist for patients who continued or discontinued active treatment, and test whether clinical predictors of trajectory class membership exist using pooled data from clinical trials.

METHODS

We analysed individual patient data from four double-blind discontinuation clinical trials of duloxetine or fluoxetine versus placebo in major depression from before 2012 (n=1462). We modelled trajectories of relapse up to 26 weeks during double-blind treatment. Trajectories of depression severity, as measured by the Hamilton Depression Rating Scale score, were identified in the entire sample, and separately in groups in which antidepressants had been continued or discontinued, using growth mixture models. Predictors of trajectory class membership were assessed with weighted logistic regression.

FINDINGS

We identified similar relapse trajectories and two trajectories of stable depression scores in the normal range on active medication and on placebo. Active treatment significantly lowered the odds of membership in the relapse trajectory (odds ratio 0·47, 95% CI 0·37-0·61), whereas female sex (1·56, 1·23-2·06), shorter length of time with clinical response by 1 week (1·10, 1·06-1·15), and higher Clinical Global Impression score at baseline (1·28, 1·01-1·62) increased the odds. Overall, the protective effect of antidepressant medication relative to placebo on the risk of being classified as a relapser was about 13% (33% vs 46%).

INTERPRETATION

The existence of similar relapse trajectories on active medication and on placebo suggests that there is no specific relapse signature associated with antidepressant discontinuation. Furthermore, continued treatment offers only modest protection against relapse. These data highlight the need to incorporate treatment strategies that prevent relapse as part of the treatment of depression.

FUNDING

National Institutes of Health, the US Department of Veterans Affairs Alcohol Research Center, and National Center for Post-Traumatic Stress Disorder.

Longitudinal Patterns and Predictors of Depression Trajectories Related to the 2014 Occupy Central/Umbrella Movement in Hong Kong

OBJECTIVES

To examine the longitudinal patterns and predictors of depression trajectories before, during, and after Hong Kong's 2014 Occupy Central/Umbrella Movement.

METHODS

In a prospective study, between March 2009 and November 2015, we interviewed 1170 adults randomly sampled from the population-representative FAMILY Cohort. We used the Patient Health Questionnaire-9 to assess depressive symptoms and probable major depression. We investigated pre-event and time-varying predictors of depressive symptoms.

RESULTS

We identified 4 trajectories: resistant (22.6% of sample), resilient (37.0%), mild depressive symptoms (32.5%), and persistent moderate depression (8.0%). Baseline predictors that appeared to protect against persistent moderate depression included higher household income (odds ratio [OR] = 0.18; 95% confidence interval [CI] = 0.06, 0.56), greater psychological resilience (OR = 0.63; 95% CI = 0.48, 0.82), more family harmony (OR = 0.68; 95% CI = 0.56, 0.83), higher family support (OR = 0.80; 95% CI = 0.69, 0.92), better self-rated health (OR = 0.28; 95% CI = 0.16, 0.49), and fewer depressive symptoms (OR = 0.59; 95% CI = 0.43, 0.81).

CONCLUSIONS

Depression trajectories after a major protest are comparable to those after major population events. Health care professionals should be aware of the mental health consequences during and after social movements, particularly among individuals lacking social support.

Data-driven classification of bipolar I disorder from longitudinal course of mood

The Diagnostic and Statistical Manual of Mental Disorder (DSM) classification of bipolar disorder defines categories to reflect common understanding of mood symptoms rather than scientific evidence. This work aimed to determine whether bipolar I can be objectively classified from longitudinal mood data and whether resulting classes have clinical associations. Bayesian nonparametric hierarchical models with latent classes and patient-specific models of mood are fit to data from Longitudinal Interval Follow-up Evaluations (LIFE) of bipolar I patients (N=209). Classes are tested for clinical associations. No classes are justified using the time course of DSM-IV mood states. Three classes are justified using the course of subsyndromal mood symptoms. Classes differed in attempted suicides (P=0.017), disability status (P=0.012) and chronicity of affective symptoms (P=0.009). Thus, bipolar I disorder can be objectively classified from mood course, and individuals in the resulting classes share clinical features. Data-driven classification from mood course could be used to enrich sample populations for pharmacological and etiological studies.

'Big data' in mental health research: current status and emerging possibilities

PURPOSE

'Big data' are accumulating in a multitude of domains and offer novel opportunities for research. The role of these resources in mental health investigations remains relatively unexplored, although a number of datasets are in use and supporting a range of projects. We sought to review big data resources and their use in mental health research to characterise applications to date and consider directions for innovation in future.

METHODS

A narrative review.

RESULTS

Clear disparities were evident in geographic regions covered and in the disorders and interventions receiving most attention.

DISCUSSION

We discuss the strengths and weaknesses of the use of different types of data and the challenges of big data in general. Current research output from big data is still predominantly determined by the information and resources available and there is a need to reverse the situation so that big data platforms are more driven by the needs of clinical services and service users.