Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death.

The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex.

Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31).

These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.

Ambulatory monitoring is gaining popularity in mental and somatic health care to capture an individual's wellbeing or treatment course in daily-life. Experience sampling method collects subjective time-series data of patients' experiences, behavior, and context. At the same time, digital devices allow for less intrusive collection of more objective time-series data with higher sampling frequencies and for prolonged sampling periods. We refer to these data as parallel data. Combining these two data types holds the promise to revolutionize health care. However, existing ambulatory monitoring guidelines are too specific to each data type, and lack overall directions on how to effectively combine them.

Literature and expert opinions were integrated to formulate relevant guiding principles.

Experience sampling and parallel data must be approached as one holistic time series right from the start, at the study design stage. The fluctuation pattern and volatility of the different variables of interest must be well understood to ensure that these data are compatible. Data have to be collected and operationalized in a manner that the minimal common denominator is able to answer the research question with regard to temporal and disease severity resolution. Furthermore, recommendations are provided for device selection, data management, and analysis. Open science practices are also highlighted throughout. Finally, we provide a practical checklist with the delineated considerations and an open-source example demonstrating how to apply it.

The provided considerations aim to structure and support researchers as they undertake the new challenges presented by this exciting multidisciplinary research field.

Imaging studies have shown that the subcallosal region (SCR) volume was decreased in patients with major depressive disorder (MDD). However, whether the volumetric reductions in the SCR are due to thinning of the cortex or a loss of surface area (SA) remains unclear. In addition, the relationship between cortical measurements of the SCR and age through the adult life span in MDD remains unclear.

We used a cross-sectional design from 114 individuals with MDD and 112 matched healthy control (HC) individuals across the adult life span (range: 18–74 years). The mean cortical volume (CV), SA and cortical thickness (CT) of the SCR were computed using cortical parcellation based on FreeSurfer software. Multivariate analyses of covariance models were performed to compare differences between the MDD and HC groups on cortical measurements of the SCR. Multiple linear regression models were used to test age-by-group interaction effects on these cortical measurements of the SCR.

The MDD had significant reductions in the CV and SA of the left SCR compared with HC individuals after controlling of other variables. The left SCR CV and SA reductions compared with matched controls were observed only in early adulthood patients. We also found a significant age-related CT reduction in the SCR both in the MDD and HC participants.

The SCR volume reduction was mainly driven by SA in MDD. The different trajectories between the CT and SA of the SCR with age may provide valuable information to distinguish pathological processes and normal ageing in MDD.

Varied longitudinal courses of suicidal ideation (SI) may be linked to unique sets of risk and protective factors.

A national probability sample of 2291 U.S. veterans was followed over four assessments spanning 7 years to examine how a broad range of baseline risk and protective factors predict varying courses of SI.

Most veterans (82.6%) denied SI at baseline and all follow-ups, while 8.7% had new onset SI, 5.4% chronic SI, and 3.3% remitted SI. Compared to the no-SI group, chronic SI was associated with childhood trauma, baseline major depressive and/or posttraumatic stress disorder (MDD/PTSD), physical health difficulties, and recent traumatic stressors. Remitted veterans had the highest risk of a prior suicide attempt (SA) compared to no-SI [relative risk ratio (RRR) = 3.31] and chronic SI groups (RRR = 4.65); and high rates of MDD/PTSD (RRR = 7.62). New onset SI was associated with recent stressors and physical health difficulties. All symptomatic SI groups reported decrements in protective factors, specifically, social connectedness, trait curiosity/exploration, and purpose in life.

Nearly one-in-five veterans reported SI over a 7-year period, most of whom evidenced new onset or remitted SI courses. Chronic and remitted SI may represent particularly high-risk SI courses; the former was associated with higher rates of prospective SA, and psychiatric and physical distress, and the latter with increased likelihood of prior SA, and isolation from social and mental health supports. Physical disability, MDD/PTSD, and recent stressors may be important precipitating or maintaining factors of SI, while social connectedness may be a key target for suicide prevention efforts.

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Higher levels of PTSD symptoms are present among trauma-exposed females v. males in adulthood; however, much less is known about the emergence of this sex difference during development.

In a multi-study sample of 7–18-year-olds (n = 3397), we examined the effect of sex and age on the severity of PTSD symptoms after a single incident trauma at 1 month (T1), and on symptom change after a natural recovery period of 3 (T2) and 6 months (T3). PTSD scores were harmonised across measurement types, and linear regressions were used to determine sex and age effects, adjusting for study level variance and trauma type.

A sex × age interaction was observed at T1 (p < 0.001) demonstrating that older age was associated with greater PTSD symptom severity in females (β = 0.008, p = 0.047), but less severe symptoms in males (β = −0.011, p = 0.014). The same pattern was observed at T2 and T3, with sex differences beginning to emerge by age 12 years. PTSD symptoms decreased naturally by ~25% at T2 with little further improvement by T3. Further, females showed a greater reduction in symptoms at T3 than males, although the same effect was not observed at T2.

Sex differences in PTSD symptoms become apparent during adolescence, due to opposing changes in susceptibility occurring in females and males with age. Understanding the factors contributing to these findings is likely to provide wider insight into sex-specific psychological vulnerability to trauma-related psychopathology.

The association between executive dysfunction, brain dysconnectivity, and inflammation is a prominent feature across major psychiatric disorders (MPDs), schizophrenia, bipolar disorder, and major depressive disorder. A dimensional approach is warranted to delineate their mechanistic interplay across MPDs.

This single site study included a total of 1543 participants (1058 patients and 485 controls). In total, 1169 participants underwent diffusion tensor and resting-state functional magnetic resonance imaging (745 patients and 379 controls completed the Wisconsin Card Sorting Test). Fractional anisotropy (FA) and regional homogeneity (ReHo) assessed structural and functional connectivity, respectively. Pro-inflammatory cytokine levels [interleukin (IL)-1β, IL-6, and tumor necrosis factor-α] were obtained in 325 participants using blood samples collected with 24 h of scanning. Group differences were determined for main measures, and correlation and mediation analyses and machine learning prediction modeling were performed.

Executive deficits were associated with decreased FA, increased ReHo, and elevated IL-1β and IL-6 levels across MPDs, compared to controls. FA and ReHo alterations in fronto-limbic-striatal regions contributed to executive deficits. IL-1β mediated the association between FA and cognition, and IL-6 mediated the relationship between ReHo and cognition. Executive cognition was better predicted by both brain connectivity and cytokine measures than either one alone for FA-IL-1β and ReHo-IL-6.

Transdiagnostic associations among brain connectivity, inflammation, and executive cognition exist across MPDs, implicating common neurobiological substrates and mechanisms for executive deficits in MPDs. Further, inflammation-related brain dysconnectivity within fronto-limbic-striatal regions may represent a transdiagnostic dimension underlying executive dysfunction that could be leveraged to advance treatment.

Duration of untreated psychosis (DUP) is an important measure of access to care as it predicts prognosis and treatment outcomes. Little is known about potential socioeconomic inequalities in DUP. The aim of this study was to investigate inequalities in DUP associated with socioeconomic deprivation in a national cohort in England.

We analysed a cohort of 887 patients with a first-episode in psychosis using the administrative Mental Health Services Dataset in England for 2012/13-2014/15. We used a Generalised Linear Model to account for non-linearity in DUP and looked at inequalities across the whole distribution of DUP using quantile regression.

The median DUP was 22 days (mean = 74 days) with considerable variations between and within the 31 hospital providers. We found evidence of significant inequalities regarding the level of socioeconomic deprivation. Patients living in the second, third and fourth deprived neighbourhood quintiles faced a 36, 24 and 31 day longer DUP than patients from the least deprived neighbourhoods. Inequalities were more prevalent in higher quantiles of the DUP distribution. Unemployment prolonged DUP by 40 days. Having been in contact with mental health care services prior to the psychosis start significantly reduced the DUP by up to 53 days.

Socioeconomic deprivation is an important factor in explaining inequalities in DUP. Policies to improve equitable access to care should particularly focus on preventing very long delays in treatment and target unemployed patients as well as people that have not been in contact with any mental health professional in the past.

Little is known about how conspiracy beliefs and health responses are interrelated over time during the course of the coronavirus disease 2019 (Covid-19) pandemic. This longitudinal study tested two contrasting, but not mutually exclusive, hypotheses through cross-lagged modeling. First, based on the consequential nature of conspiracy beliefs, we hypothesize that conspiracy beliefs predict an increase in detrimental health responses over time. Second, as people may rationalize their behavior through conspiracy beliefs, we hypothesize that detrimental health responses predict increased conspiracy beliefs over time.

We measured conspiracy beliefs and several health-related responses (i.e. physical distancing, support for lockdown policy, and the perception of the coronavirus as dangerous) at three phases of the pandemic in the Netherlands (N = 4913): During the first lockdown (Wave 1: April 2020), after the first lockdown (Wave 2: June 2020), and during the second lockdown (Wave 3: December 2020).

For physical distancing and perceived danger, the overall cross-lagged effects supported both hypotheses, although the standardized effects were larger for the effects of conspiracy beliefs on these health responses than vice versa. The within-person change results only supported an effect of conspiracy beliefs on these health responses, depending on the phase of the pandemic. Furthermore, an overall cross-lagged effect of conspiracy beliefs on reduced support for lockdown policy emerged from Wave 2 to 3.

The results provide stronger support for the hypothesis that conspiracy beliefs predict health responses over time than for the hypothesis that health responses predict conspiracy beliefs over time.