Identifying children and/or adolescents who are at highest risk for developing chronic depression is of utmost importance, so that we can develop more effective and targeted interventions to attenuate the risk trajectory of depression. To address this, the objective of this study was to identify young people with persistent depressive symptoms across adolescence and young adulthood and examine the prospective associations between factors and persistent depressive symptoms in young people.

We used data from 6711 participants in the Avon Longitudinal Study of Parents and Children. Depressive symptoms were assessed at 12.5, 13.5, 16, 17.5, 21 and 22 years with the Short Mood and Feelings Questionnaire, and we further examined the influence of multiple biological, psychological and social factors in explaining chronic depressive symptoms.

Using latent class growth analysis, we identified four trajectories of depressive symptoms: persistent high, persistent low, persistent moderate and increasing high. After applying several logistic regression models, we found that loneliness and feeling less connected at school were the most relevant factors for chronic course of depressive symptoms.

Our findings contribute with the identification of those children who are at highest risk for developing chronic depressive symptoms.

There is heterogeneity in the long-term trajectories of depressive symptoms among patients. To date, there has been little effort to inform the long-term trajectory of symptom change and the factors associated with different trajectories. Such knowledge is key to treatment decision-making in primary care, where depression is a common reason for consultation. We aimed to identify distinct long-term trajectories of depressive symptoms and explore pre-treatment characteristics associated with them.

A total of 483 patients from the PsicAP clinical trial were included. Growth mixture modeling was used to identify long-term distinct trajectories of depressive symptoms, and multinomial logistic regression models to explore associations between pre-treatment characteristics and trajectories.

Four trajectories were identified that best explained the observed response patterns: “recovery” (64.18%), “late recovery” (10.15%), “relapse” (13.67%), and “chronicity” (12%). There was a higher likelihood of following the recovery trajectory for patients who had received psychological treatment in addition to the treatment as usual. Chronicity was associated with higher depressive severity, comorbidity (generalized anxiety, panic, and somatic symptoms), taking antidepressants, higher emotional suppression, lower levels on life quality, and being older. Relapse was associated with higher depressive severity, somatic symptoms, and having basic education, and late recovery was associated with higher depressive severity, generalized anxiety symptoms, greater disability, and rumination.

There were different trajectories of depressive course and related prognostic factors among the patients. However, further research is needed before these findings can significantly influence care decisions.

Cerebral microvascular dysfunction may contribute to depression via disruption of brain structures involved in mood regulation, but evidence is limited. We investigated the association of retinal microvascular function, a proxy for microvascular function in the brain, with incidence and trajectories of clinically relevant depressive symptoms.

Longitudinal data are from The Maastricht Study of 5952 participants (59.9 ± 8.5 years/49.7% women) without clinically relevant depressive symptoms at baseline (2010–2017). Central retinal arteriolar equivalent and central retinal venular equivalent (CRAE and CRVE) and a composite score of flicker light-induced retinal arteriolar and venular dilation were assessed at baseline. We assessed incidence and trajectories of clinically relevant depressive symptoms (9-item Patient Health Questionnaire score ⩾10). Trajectories included continuously low prevalence (low, n = 5225 [87.8%]); early increasing, then chronic high prevalence (early-chronic, n = 157 [2.6%]); low, then increasing prevalence (late-increasing, n = 247 [4.2%]); and remitting prevalence (remitting, n = 323 [5.4%]).

After a median follow-up of 7.0 years (range 1.0–11.0), 806 (13.5%) individuals had incident clinically relevant depressive symptoms. After full adjustment, a larger CRAE and CRVE were each associated with a lower risk of clinically relevant depressive symptoms (hazard ratios [HRs] per standard deviation [s.d.]: 0.89 [95% confidence interval (CI) 0.83–0.96] and 0.93 [0.86–0.99], respectively), while a lower flicker light-induced retinal dilation was associated with a higher risk of clinically relevant depressive symptoms (HR per s.d.: 1.10 [1.01–1.20]). Compared to the low trajectory, a larger CRAE was associated with lower odds of belonging to the early-chronic trajectory (OR: 0.83 [0.69–0.99]) and a lower flicker light-induced retinal dilation was associated with higher odds of belonging to the remitting trajectory (OR: 1.23 [1.07–1.43]).

These findings support the hypothesis that cerebral microvascular dysfunction contributes to the development of depressive symptoms.

The aim of the study was to investigate longitudinal trajectories of change in anxiety and depression symptoms in Polish adolescents during the second year of the COVID-19 pandemic and after the outbreak of the war in Ukraine. Additionally, we aimed to identify risk/protective factors and outcomes associated with these trajectories.

We collected data in three waves between November 2021 and May 2022. Adolescents (N = 281 in the first wave) completed the Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7, the Filial Responsibility Scale for Youth, and questions related to the COVID-19 pandemic and war in Ukraine.

We identified three trajectories of depressive symptoms: resilient with low, stable symptoms (71% of participants), chronically elevated symptoms (11%), and acute symptoms followed by recovery (18%). We distinguished two trajectories of anxiety symptoms: resilient (75%) and chronic (25%). Non-resilient trajectories were predicted by higher levels of familial unfairness (perceived lack of equality and reciprocity in the family), relationship difficulties at school and at home, older age, and poor socioeconomic status. Chronic depressive and anxiety symptoms were associated with higher war-related concerns.

These findings can inform preventive and therapeutic interventions for at-risk adolescents to reduce negative long-term outcomes of social crises.

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

One hundred and twenty-six persons aged 18–85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Mental health problems are elevated in autistic individuals but there is limited evidence on the developmental course of problems across childhood. We compare the level and growth of anxious-depressed, behavioral and attention problems in an autistic and typically developing (TD) cohort.

Latent growth curve models were applied to repeated parent-report Child Behavior Checklist data from age 2–10 years in an inception cohort of autistic children (Pathways, N = 397; 84% boys) and a general population TD cohort (Wirral Child Health and Development Study; WCHADS; N = 884, 49% boys). Percentile plots were generated to quantify the differences between autistic and TD children.

Autistic children showed elevated levels of mental health problems, but this was substantially reduced by accounting for IQ and sex differences between the autistic and TD samples. There was small differences in growth patterns; anxious-depressed problems were particularly elevated at preschool and attention problems at late childhood. Higher family income predicted lower base-level on all three dimensions, but steeper increase of anxious-depressed problems. Higher IQ predicted lower level of attention problems and faster decline over childhood. Female sex predicted higher level of anxious-depressed and faster decline in behavioral problems. Social-affect autism symptom severity predicted elevated level of attention problems. Autistic girls' problems were particularly elevated relative to their same-sex non-autistic peers.

Autistic children, and especially girls, show elevated mental health problems compared to TD children and there are some differences in predictors. Assessment of mental health should be integrated into clinical practice for autistic children.

Our study aimed to (1) identify trajectories on different mental health components during a two-year follow-up of the COVID-19 pandemic and contextualise them according to pandemic periods; (2) investigate the associations between mental health trajectories and several exposures, and determine whether there were differences among the different mental health outcomes regarding these associations.

We included 5535 healthy individuals, aged 40–65 years old, from the Barcelona Brain Health Initiative (BBHI). Growth mixture models (GMM) were fitted to classify individuals into different trajectories for three mental health-related outcomes (psychological distress, personal growth and loneliness). Moreover, we fitted a multinomial regression model for each outcome considering class membership as the independent variable to assess the association with the predictors.

For the outcomes studied we identified three latent trajectories, differentiating two major trends, a large proportion of participants was classified into ‘resilient’ trajectories, and a smaller proportion into ‘chronic-worsening’ trajectories. For the former, we observed a lower susceptibility to the changes, whereas, for the latter, we noticed greater heterogeneity and susceptibility to different periods of the pandemic. From the multinomial regression models, we found global and cognitive health, and coping strategies as common protective factors among the studied mental health components. Nevertheless, some differences were found regarding the risk factors. Living alone was only significant for those classified into ‘chronic’ trajectories of loneliness, but not for the other outcomes. Similarly, secondary or higher education was only a risk factor for the ‘worsening’ trajectory of personal growth. Finally, smoking and sleeping problems were risk factors which were associated with the ‘chronic’ trajectory of psychological distress.

Our results support heterogeneity in reactions to the pandemic and the need to study different mental health-related components over a longer follow-up period, as each one evolves differently depending on the pandemic period. In addition, the understanding of modifiable protective and risk factors associated with these trajectories would allow the characterisation of these segments of the population to create targeted interventions.

This paper examined whether distinct life-course trajectories of psychological distress from adolescence to midlife were associated with poorer mental health outcomes during the pandemic.

We present a secondary analysis of two nationally representative British birth cohorts, the 1958 National Child Development Study (NCDS) and 1970 British Cohort Study (BCS70). We used latent variable mixture models to identify pre-pandemic longitudinal trajectories of psychological distress and a modified Poisson model with robust standard errors to estimate associations with psychological distress, life satisfaction and loneliness at different points during the pandemic.

Our analysis identified five distinct pre-pandemic trajectories of psychological distress in both cohorts. All trajectories with prior symptoms of psychological distress irrespective of age of onset, severity and chronicity were associated with a greater relative risk of poorer mental health outcomes during the pandemic and the probability of poorer mental health associated with psychological distress trajectories remained fairly constant. The relationship was not fully attenuated when most recent pre-pandemic psychological distress and other midlife factors were controlled for.

Whilst life-course trajectories with any prior symptoms of psychological distress put individuals at greater risk of poor mental health outcomes during the pandemic, those with chronic and more recent occurrences were at highest risk. In addition, prior poor mental health during the adult life-course may mean individuals are less resilient to shocks, such as pandemics. Our findings show the importance of considering heterogeneous mental health trajectories across the life-course in the general population in addition to population average trends.

The course of Bipolar Disorder (BD) is highly variable, with marked inter and intra-individual differences in symptoms and functioning. In this study, we identified illness trajectories across major clinical domains that could have etiological, prognostic, and therapeutic relevance.

Using the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we performed univariate and multivariate trajectory modeling of depressive symptoms, manic symptoms, and psychosocial functioning. Multinomial regression was performed to identify baseline variables associated with poor outcome trajectories.

Depressive symptoms predominated, with most subjects being found in trajectories characterized by various degrees of depressive symptoms and 13% of subjects being classified in a poor outcome ‘persistently depressed’ trajectory. Most subjects experienced few manic symptoms, although approximately 10% of subjects followed a trajectory of persistently manic symptoms. Trajectory analysis of psychosocial functioning showed impairment in most of the sample, with little improvement during follow up. Multi-trajectory analyses highlighted significant impairment in subjects with persistently mixed and persistently depressed trajectories of illness. In general, poor outcome trajectories were marked by lower educational attainment, higher unemployment and disability, and a greater likelihood of adverse clinical features (rapid cycling and suicide attempts) and comorbid diagnoses (anxiety disorders, PTSD, and substance abuse/dependence disorders).

Subjects with BD can be classified into several trajectories of clinically relevant domains that are prognostically relevant and show differing degrees of associations with a broad range of negative clinical risk factors. The highest level of psychosocial disability was found in subjects with chronic mixed and depressive symptoms, who show limited improvement despite guideline-based treatment.

The relationships between offspring depression profiles across adolescence and different timings of parental depression during the perinatal period remain unknown.

To explore different timings of maternal and paternal perinatal depression in relation to patterns of change in offspring depressive mood over a 14 year period.

Data were obtained from the Avon Longitudinal Study of Parents and Children (ALSPAC). Parental antenatal depression (ANTD) was assessed at 18 weeks gestation, and postnatal depression (PNTD) at 8 weeks postpartum. Population-averaged trajectories of offspring depressive symptoms were estimated using the Short Mood and Feelings Questionnaire (SMFQ) on nine occasions between 10 and 24 years of age.

Full data were available for 5029 individuals. Offspring exposed to both timings of maternal depression had higher depressive symptoms across adolescence compared with offspring not exposed to ANTD or PNTD, characterised by higher depressive symptoms at age 16 (7.07 SMFQ points (95% CI = 6.19, 7.95; P < 0.001)) and a greater rate of linear change (0.698 SMFQ points (95% CI = 0.47, 0.93; P = 0.002)). Isolated maternal ANTD and to a lesser extent PNTD were also both associated with higher depressive symptoms at age 16, yet isolated maternal PNTD showed greater evidence for an increased rate of linear change across adolescence. A similar pattern was observed for paternal ANTD and PNTD, although effect sizes were attenuated.

This study adds to the literature demonstrating that exposure to two timings of maternal depression (ANTD and PNTD) is strongly associated with greater offspring trajectories of depressive symptoms.

Oral histories from 9/11 responders to the World Trade Center (WTC) attacks provide rich narratives about distress and resilience. Artificial Intelligence (AI) models promise to detect psychopathology in natural language, but they have been evaluated primarily in non-clinical settings using social media. This study sought to test the ability of AI-based language assessments to predict PTSD symptom trajectories among responders.

Participants were 124 responders whose health was monitored at the Stony Brook WTC Health and Wellness Program who completed oral history interviews about their initial WTC experiences. PTSD symptom severity was measured longitudinally using the PTSD Checklist (PCL) for up to 7 years post-interview. AI-based indicators were computed for depression, anxiety, neuroticism, and extraversion along with dictionary-based measures of linguistic and interpersonal style. Linear regression and multilevel models estimated associations of AI indicators with concurrent and subsequent PTSD symptom severity (significance adjusted by false discovery rate).

Cross-sectionally, greater depressive language (β = 0.32; p = 0.049) and first-person singular usage (β = 0.31; p = 0.049) were associated with increased symptom severity. Longitudinally, anxious language predicted future worsening in PCL scores (β = 0.30; p = 0.049), whereas first-person plural usage (β = −0.36; p = 0.014) and longer words usage (β = −0.35; p = 0.014) predicted improvement.

This is the first study to demonstrate the value of AI in understanding PTSD in a vulnerable population. Future studies should extend this application to other trauma exposures and to other demographic groups, especially under-represented minorities.