Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Cognitive therapies are developed on the principle that specific cognitive appraisals are key determinants in the development and maintenance of mental health disorders. It is likely that particular appraisals of the coronavirus pandemic will have explanatory power for subsequent mental health outcomes in the general public. To enable testing of this hypothesis we developed a questionnaire assessing coronavirus-related cognitions.

12 285 participants completed online a 46-item pool of cognitions about coronavirus and six measures of different mental health problems. The sample was randomly split into derivation and validation samples. Exploratory factor analyses determined the factor structure, selection of items, and model fit in the derivation sample. Confirmatory factor analysis (CFA) then tested this model in the validation sample. Associations of the questionnaire with mental health outcomes were examined.

The 26-item, seven-factor, Oxford Psychological Investigation of Coronavirus Questionnaire [TOPIC-Q] was developed. CFA demonstrated a good model fit (χ2 = 2108.43, df = 278, p < 0.001, comparative fit index (CFI) = 0.950, Tucker−Lewis index (TLI) = 0.942, root mean square error of approximation (RMSEA) = 0.033, standardized root mean square residual (SRMR) = 0.038). The factors were: cognitions about (1) safety and vulnerability, (2) negative long-term impact, (3) having the virus, (4) spreading the virus, (5) social judgment, (6) negative self, and (7) being targeted. The questionnaire explained significant variance in depression (45.8%), social anxiety (37.3%), agoraphobia (23.2%), paranoia (27.3%), post-traumatic stress disorder (57.1%), and panic disorder (31.4%). Cognitions about negative long-term impact had the greatest explanatory power across disorders.

TOPIC-Q provides a method to assess appraisals of the pandemic, which is likely to prove helpful both in longitudinal studies assessing mental health outcomes and in delivery of psychological therapy.

The neurodevelopmental model of psychosis was established over 30 years ago; however, the developmental influence on psychotic symptom expression – how age affects clinical presentation in first-episode psychosis – has not been thoroughly investigated.

Using generalized additive modeling, which allows for linear and non-linear functional forms of age-related change, we leveraged symptom data from a large sample of antipsychotic-naïve individuals with first-episode psychosis (N = 340, 12–40 years, 1–12 visits), collected at the University of Pittsburgh from 1990 to 2017. We examined relationships between age and severity of perceptual and non-perceptual positive symptoms and negative symptoms. We tested for age-associated effects on change in positive or negative symptom severity following baseline assessment and explored the time-varying relationship between perceptual and non-perceptual positive symptoms across adolescent development.

Perceptual positive symptom severity significantly decreased with increasing age (F = 7.0, p = 0.0007; q = 0.003) while non-perceptual positive symptom severity increased with age (F = 4.1, p = 0.01, q = 0.02). Anhedonia severity increased with increasing age (F = 6.7, p = 0.00035; q = 0.0003), while flat affect decreased in severity with increased age (F = 9.8, p = 0.002; q = 0.006). Findings remained significant when parental SES, IQ, and illness duration were included as covariates. There were no developmental effects on change in positive or negative symptom severity (all p > 0.25). Beginning at age 18, there was a statistically significant association between severity of non-perceptual and perceptual symptoms. This relationship increased in strength throughout adulthood.

These findings suggest that as maturation proceeds, perceptual symptoms attenuate while non-perceptual symptoms are enhanced. Findings underscore how pathological brain–behavior relationships vary as a function of development.

Research on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population.

Lambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017.

We found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73–12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60–4.87), chronic pain and depression (HR 4.14; 95% CI 3.69–4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36–4.95).

Our results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.

Higher cognitive ability is associated with favourable health characteristics. The relation between ability and alcohol consumption, and their interplay with other health characteristics, is unclear. We aimed to assess the relationship between cognitive ability and alcohol consumption and to assess whether alcohol consumption relates differently to health characteristics across strata of ability.

For 63 120 Norwegian males, data on cognitive ability in early adulthood were linked to midlife data on alcohol consumption frequency (times per month, 0–30) and other health characteristics, including cardiovascular risk factors and mental distress. Relations were assessed using linear regression and reported as unstandardised beta coefficients [95% confidence interval (CI)].

The mean ± s.d. frequency of total alcohol consumption in the sample was 4.0 ± 3.8 times per month. In the low, medium, and high group of ability, the frequencies were 3.0 ± 3.3, 3.7 ± 3.5, and 4.7 ± 4.1, respectively. In the full sample, alcohol consumption was associated with physical activity, heart rate, fat mass, smoking, and mental distress. Most notably, each additional day of consumption was associated with a 0.54% (0.44–0.64) and 0.14% (0.09–0.18) increase in the probability of current smoking and mental distress, respectively. In each strata of ability (low, medium, high), estimates were 0.87% (0.57–1.17), 0.48% (0.31–0.66) and 0.49% (0.36–0.62) for current smoking, and 0.44% (0.28–0.60), 0.10% (0.02–0.18), and 0.09% (0.03–0.15) for mental distress, respectively.

Participants with low cognitive ability drink less frequently, but in this group, more frequent alcohol consumption is more strongly associated with adverse health characteristics.

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Recent research has emphasized the importance of within-person transactions between situational perceptions and borderline symptomatology. The current study extends current evidence by evaluating a broad range of situational perceptions and their transactions with borderline symptomatology across both private and professional contexts. Additionally, it explores whether early experiences of parental harsh punishment and emotional support during childhood, two well-established etiological factors in developmental theories of borderline symptomatology, influence the effect of daily situation perception in adulthood on borderline symptom presentation.

N = 131 young adults (Mage = 20.97, s.d.age = 1.64) completed end-of-day diaries of their borderline symptoms and perceptions of the home and school or work environment for 14 days. During their mid-childhood, reports of maternal strategies of harsh punishment and emotional support were collected.

Findings revealed that on the same day, borderline symptoms were associated with more negative and stressful, and less positive perceptions of both the private and professional context. Additionally, borderline symptoms predicted more negative and stressful perceptions of school/work on subsequent days. Finally, while early harsh punishment predicted overall increases in daily borderline symptoms 10 years later, emotionally supportive parenting in childhood predicted decreases in borderline symptom expression in less positive and more stressful contexts.

The current study points to the importance of managing BPD symptoms to reduce subsequent negative perceptions of the environment, and also indicates the relevance of exploring adult person-situation processes based on early parenting experiences.

Deficits in emotional intelligence (EI) were detected in patients with bipolar disorder (BD), but little is known about whether these deficits are already present in patients after presenting a first episode mania (FEM). We sought (i) to compare EI in patients after a FEM, chronic BD and healthy controls (HC); (ii) to examine the effect exerted on EI by socio-demographic, clinical and neurocognitive variables in FEM patients.

The Emotional Intelligence Quotient (EIQ) was calculated with the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). Performance on MSCEIT was compared among the three groups using generalized linear models. In patients after a FEM, the influence of socio-demographic, clinical and neurocognitive variables on the EIQ was examined using a linear regression model.

In total, 184 subjects were included (FEM n = 48, euthymic chronic BD type I n = 75, HC n = 61). BD patients performed significantly worse than HC on the EIQ [mean difference (MD) = 10.09, standard error (s.e.) = 3.14, p = 0.004] and on the understanding emotions branch (MD = 7.46, s.e. = 2.53, p = 0.010). FEM patients did not differ from HC and BD on other measures of MSCEIT. In patients after a FEM, EIQ was positively associated with female sex (β = −0.293, p = 0.034) and verbal memory performance (β = 0.374, p = 0.008). FEM patients performed worse than HC but better than BD on few neurocognitive domains.

Patients after a FEM showed preserved EI, while patients in later stages of BD presented lower EIQ, suggesting that impairments in EI might result from the burden of disease and neurocognitive decline, associated with the chronicity of the illness.

Attention-deficit/hyperactivity disorder (ADHD) is a developmental condition that often persists into adulthood with extensive negative consequences on quality of life. Despite emerging evidence indicating the genetic basis of ADHD, investigations into the familial expression of latent neurocognitive traits remain limited.

In a group of adult ADHD probands (n = 20), their unaffected first-degree relatives (n = 20) and typically developing control participants (n = 20), we assessed endophenotypic alterations in the default mode network (DMN) connectivity during resting-state functional magnetic resonance imaging in relation to cognitive performance and clinical symptoms. In an external validation step, we also examined the dimensional nature of this neurocognitive trait in a sample of unrelated healthy young adults (n = 100) from the Human Connectome Project (HCP).

The results illustrated reduced anti-correlations between the posterior cingulate cortex/precuneus and right middle frontal gyrus that was shared between adult ADHD probands and their first-degree relatives, but not with healthy controls. The observed connectivity alterations were linked to higher ADHD symptoms that was mediated by performance in a sustained attention task. Moreover, this brain-based neurocognitive trait dimensionally explained ADHD symptom variability in the HCP sample.

Alterations in the default mode connectivity may represent a dimensional endophenotype of ADHD, hence a significant aspect of the neuropathophysiology of this disorder. As such, brain network organisation can potentially be employed as an important neurocognitive trait to enhance statistical power of genetic studies in ADHD and as a surrogate efficacy endpoint in the development of novel pharmaceuticals.

Military personnel deployed to combat and peacekeeping missions are exposed to high rates of traumatic events. Accumulating evidence suggests an important association between deployment and the development of other mental health symptoms beyond post-traumatic stress disorder.

This study examined the prevalence of agoraphobia, anxiety, depression, and hostility symptoms in a cohort of Dutch ISAF veterans (N = 978) from pre-deployment up to 10 years after homecoming. The interaction of potential moderating factors with the change in mental health symptoms relative to pre-deployment was investigated at each time point.

The probable prevalence of agoraphobia, anxiety, depression, and hostility symptoms significantly increased over time to respectively 6.5, 2.7, 3.5, and 6.2% at 10 years after deployment. Except for hostility symptoms, the probable prevalence at 10 years after deployment was the highest compared to all previous follow-up assessments. Importantly, less perceived social support after returning from deployment was found as a risk factor for all different mental health symptoms. Unit support was not associated with the development of mental health problems.

This study suggests a probable broad and long-term impact of deployment on the mental health of military service members. Due to the lack of a non-deployed control group, causal effects of deployment could not be demonstrated. Continued effort should nevertheless be made in the diagnosis and treatment of a wide range of mental health symptoms, even a decade after deployment. The findings also underscore the importance of social support after homecoming and its potential for the prevention of long-term mental health problems.

The scale of the global mental health burden indicates the inadequacy not only of current treatment options, but also the pace of the standard treatment development process. The ‘leapfrog’ trial design is a newly-developed simple Bayesian adaptive trial design with potential to accelerate treatment development. A first leapfrog trial was conducted to provide a demonstration and test feasibility, applying the method to a low-intensity internet-delivered intervention targeting anhedonia.

At the start of this online, single-blind leapfrog trial, participants self-reporting depression were randomized to an initial control arm comprising four weeks of weekly questionnaires, or one of two versions of a four-week cognitive training intervention, imagery cognitive bias modification (imagery CBM). Intervention arms were compared to control on an ongoing basis via sequential Bayesian analyses, based on a primary outcome of anhedonia at post-intervention. Results were used to eliminate and replace arms, or to promote them to become the control condition based on pre-specified Bayes factor and sample size thresholds. Two further intervention arms (variants of imagery CBM) were added into the trial as it progressed.

N = 188 participants were randomized across the five trial arms. The leapfrog methodology was successfully implemented to identify a ‘winning’ version of the imagery CBM, i.e. the version most successful in reducing anhedonia, following sequential elimination of the other arms.

The study demonstrates feasibility of the leapfrog design and provides a foundation for its adoption as a method to accelerate treatment development in mental health. Registration: clinicaltrials.gov, NCT04791137.

Adverse childhood experiences (ACEs) increase the risk of mental health difficulties in general, but the link to panic disorder (PD) has received comparatively little attention. There are no data for the magnitudes between ACEs and PD. This systematic review and meta-analysis estimated the overall, as well as the subgroups, odds ratio of having PD in adults who report ACEs, compared to adults who do not.

The study was pre-registered on PROSPERO [CRD42018111506] and the database was searched in June 2021. In order to overcome the violation of independent assumptions due to multiple estimations from the same samples, we utilized a robust variance estimation model that supports meta-analysis for clustered estimations. Accordingly, an advanced method relaxing the distributional and asymptotic assumptions was used to assess publication bias and sensitivity.

The literature search and screening returned 34 final studies, comprising 192,182 participants. Ninety-six estimations of 20 types of ACEs were extracted. Pooled ORs are: overall 2.2, CI (1.82–2.58), sexual abuse 1.92, CI (1.37–2.46), physical abuse 1.71, CI (1.37–2.05), emotional abuse 1.61, CI (0.868–2.35), emotional neglect 1.53, CI (0.756–2.31), parental alcoholism 1.83, CI (1.24–2.43), and parental separation/loss 1.82, CI (1.14–2.50). No between-group difference was identified by either sociolegal classification (abuse, neglect, household dysfunction) or threat-deprivation dimensions (high on threat, high on deprivation and mixed).

There are links of mild to medium strength between overall ACEs and PD as well as individual ACEs. The homogeneous effect sizes across ACEs either suggest the effects of ACEs on PD are comparable, or raised the question whether the categorical or dimensional approaches to classifying ACEs are the definitive ways to conceptualize the impact of ACEs on later mental health.

We need to better understand the frequency and predictors of opioid use disorder (OUD) after first opioid prescription (OP).

We followed 1 516 392 individuals from the Swedish population born 1980–2000, from 1 July 2007, until 31 Dec 2017. We examined putative risk predictors with univariable and multivariable Cox Models and the potential causal effects of predictors by propensity score and co-sibling analyses.

Of the individuals in our cohort, 24.8% (375 404) received a first OP, of whom 3034 (0.90%) developed a subsequent first OUD. The hazard ratio (HR) (± 95% CIs) for OUD after OP equaled 7.10 (6.75–7.46), with a mean time to onset of 3.41 (2.39) years. The strongest putative risk factors for development of OUD after OP were prior psychiatric and substance use disorders, criminal behavior, parental divorce/death, poor school performance, current community deprivation, divorce, and male sex. Few predictors differed across sexes. OP renewal was associated with a HR of 3.66 (3.41–3.93) for OUD. Co-sibling and propensity score analyses suggested that at least a moderate proportion of the risk factor-OUD association was likely causal. A risk score to predict OUD after OP had an AUC of 0.85, where nearly 60% of cases scoring in the top decile.

In a general population sample, an OP represents a substantial risk factor for subsequent OUD. Many of the risk factors for OUD after OP can be readily assessed at the time of potential OP, permitting clinicians to evaluate the risk of iatrogenic OUD.

Recent well-powered genome-wide association studies have enhanced prediction of substance use outcomes via polygenic scores (PGSs). Here, we test (1) whether these scores contribute to prediction over-and-above family history, (2) the extent to which PGS prediction reflects inherited genetic variation v. demography (population stratification and assortative mating) and indirect genetic effects of parents (genetic nurture), and (3) whether PGS prediction is mediated by behavioral disinhibition prior to substance use onset.

PGSs for alcohol, cannabis, and nicotine use/use disorder were calculated for Minnesota Twin Family Study participants (N = 2483, 1565 monozygotic/918 dizygotic). Twins' parents were assessed for histories of substance use disorder. Twins were assessed for behavioral disinhibition at age 11 and substance use from ages 14 to 24. PGS prediction of substance use was examined using linear mixed-effects, within-twin pair, and structural equation models.

Nearly all PGS measures were associated with multiple types of substance use independently of family history. However, most within-pair PGS prediction estimates were substantially smaller than the corresponding between-pair estimates, suggesting that prediction is driven in part by demography and indirect genetic effects of parents. Path analyses indicated the effects of both PGSs and family history on substance use were mediated via disinhibition in preadolescence.

PGSs capturing risk of substance use and use disorder can be combined with family history measures to augment prediction of substance use outcomes. Results highlight indirect sources of genetic associations and preadolescent elevations in behavioral disinhibition as two routes through which these scores may relate to substance use.

The goal of the present study was to investigate the association between PTSD and the onset of hypertension in previously normotensive individuals in a population living in the stressful environment of the urban slums while controlling for risk factors for cardiovascular disease (CVD).

Participants were 320 normotensive individuals who lived in slums and were attending a family doctor program. Measurements included a questionnaire covering sociodemographic characteristics, clinical status and life habits, the Posttraumatic Stress Disorder Checklist – Civilian Version, and the Beck Depression Inventory. Incident hypertension was defined as the first occurrence at the follow-up review of the medical records of (1) systolic blood pressure of 140 mm Hg or higher or diastolic blood pressure of 90 mm Hg or higher, (2) the participant started taking antihypertensive medication, or (3) a new diagnosis of hypertension made by a physician. Differences in sociodemographic, clinical, and lifestyle characteristics between hypertensive and non-hypertensive individuals were compared using the χ2 and t tests. Multivariate Cox proportional hazards models were used to calculate hazard ratios (HR) and 95% confidence intervals (CI).

Six variables – age, educational level, body mass, smoking, diabetes, and PTSD diagnosis – showed a statistically significant (p ≤ 0.20) association with the hypertensive status. In the Cox regression, only PTSD diagnosis was significantly associated with incident hypertension (multivariate HR = 1.94; 95% CI 1.11–3.40).

The present findings highlight the importance of considering a diagnostic hypothesis of PTSD in the prevention and treatment of cardiovascular diseases.