Antipsychotics are widely used in the treatment of major depressive disorder (MDD), but there has been no comprehensive meta-analytic assessment that examined their use as monotherapy and adjunctive therapy.

A systematic review and a meta-analysis were conducted on randomized placebo-controlled trials (RCTs) that reported on the efficacy and safety/tolerability of antipsychotics for the treatment of adults with MDD. Data of both monotherapy and adjunctive antipsychotic use were extracted, but analyzed separately using a random-effects model. Co-primary outcomes were study-defined-treatment response and intolerability-related discontinuation. We also illustrated the risk/benefit balance of antipsychotics for MDD, using two-dimensional graphs representing the primary efficacy and safety/tolerability outcome. Secondary outcomes included psychopathology, remission, all-cause-discontinuation, inefficacy-related discontinuation, and adverse events.

Forty-five RCTs with 12 724 patients were included in the analysis. In monotherapy (studies = 13, n = 4375), amisulpride [1.99 (1.55–2.55)], sulpiride [1.50 (1.03–2.17)], and quetiapine [1.48 (1.23–1.78)] were significantly superior to placebo regarding treatment response. However, intolerability-related discontinuations were significantly higher compared to placebo with amisulpride and quetiapine. In adjunctive therapy (studies = 32, n = 8349), ziprasidone [1.80 (1.07–3.04)], risperidone [1.59 (1.19–2.14)], aripiprazole [1.54 (1.35–1.76)], brexpiprazole [1.41 (1.21–1.66)], cariprazine [1.27 (1.07–1.52)], and quetiapine [1.23 (1.08–1.41)] were significantly superior to placebo regarding treatment response. However, of these antipsychotics that were superior to placebo, only risperidone was equivalent to placebo regarding discontinuation due to intolerability, while the other antipsychotics were inferior.

Results suggest that there are significant differences regarding the risk/benefit ratio among antipsychotics for MDD, which should inform clinical care.

In older populations disturbed 24-h activity rhythms, poor sleep, and depressive symptoms are often lingering and co-morbid, making treatment difficult. To improve insights into these commonly co-occurring problems, we assessed the bidirectional association of sleep and 24-h activity rhythms with depressive symptoms in middle-aged and elderly persons.

In 1734 participants (mean age: 62.3 ± 9.3 years, 55% women) from the prospective Rotterdam Study, 24-h activity rhythms and sleep were estimated with actigraphy (mean duration: 146 ± 19.6 h), sleep quality with the Pittsburgh Sleep Quality Index, and depressive symptoms with the Center for Epidemiological Studies Depression scale. Repeated measures were available for 947 participants (54%) over a median follow-up of 6 years (interquartile range = 5.6–6.3). Linear-mixed models were used to assess temporal associations of 24-h activity rhythms and sleep with depressive symptoms in both directions.

High 24-h activity rhythm fragmentation (IV) (B = 1.002, 95% confidence interval (CI) = 0.641–1.363), long time in bed (TIB) (B = 0.111, 95% CI = 0.053–0.169), low sleep efficiency (SE) (B = −0.015, 95% CI = −0.020 to −0.009), long sleep onset latency (SOL) (B = 0.009, 95% CI = 0.006–0.012), and low self-rated sleep quality (B = 0.112, 95% CI = 0.0992–0.124) at baseline were associated with increasing depressive symptoms over time. Conversely, more depressive symptoms at baseline were associated with an increasing 24-h activity rhythm fragmentation (B = 0.002, 95% CI = 0.001–0.003) and TIB (B = 0.009, 95% CI = 0.004–0.015), and a decreasing SE (B = −0.140, 95% CI = −0.196 to −0.084), SOL (B = 0.013, 95% CI = 0.008–0.018), and self-rated sleep quality (B = 0.193, 95% CI = 0.171–0.215) over time.

This study demonstrates a bidirectional association of 24-h activity rhythms, actigraphy-estimated sleep, and self-rated sleep quality with depressive symptoms over a time frame of multiple years in middle-aged and elderly persons.

To characterize the association between the protracted biopsychosocial coronavirus disease 2019 (COVID-19) pandemic exposures and incident suicide attempt rates.

Data were from a nationally representative cohort based on electronic health records from January 2013 to February 2021 (N = 852 233), with an interrupted time series study design. For the primary analysis, the effect of COVID-19 pandemic on incident suicide attempts warranting in-patient hospital treatment was quantified by fitting a Poisson regression and modeling the relative risk (RR) and the corresponding 95% confidence intervals (CIs). Scenarios were forecast to predict attempted suicide rates at 10 months after social mitigation strategies. Fourteen sensitivity analyses were performed to test the robustness of the results.

Despite the increasing trend in the unexposed interval, the interval exposed to the COVID-19 pandemic was statistically significant (p < 0.001) associated with a reduced RR of incident attempted suicide (RR = 0.63, 95% CI 0.52–0.78). Consistent with the primary analysis, sensitivity analysis of sociodemographic groups and methodological factors were statistically significant (p < 0.05). No effect modification was identified for COVID-19 lockdown intervals or COVID-19 illness status. All three forecast scenarios at 10 months projected a suicide attempt rate increase from 12.49 (7.42–21.01) to 21.38 (12.71–35.99).

The interval exposed to the protracted mass social trauma of the COVID-19 pandemic was associated with a lower suicide attempt rate compared to the unexposed interval. However, this trend is likely to reverse 10 months after lifting social mitigation policies, underscoring the need for enhanced implementation of public health policy for suicide prevention.

Maternal Rheumatoid Arthritis (RA) is suggested to increase the risk of Autism Spectrum Disorder (ASD) in the offspring, mainly through inflammation/autoimmunity, but the association is unclear. A prospective population-based cohort study was implemented to examine the association between maternal RA and offspring ASD.

We included all children born alive in Sweden from 1995 to 2015, followed up through 2017. Diagnoses of ASD and RA were clinically ascertained from National Patient Register. We quantified the association by hazard ratios (HR) and two-sided 95% confidence intervals (CI), from Cox regression after detailed adjustment for potential confounders. We examined RA serostatus, etiological subgroups and the timing of exposure. To closer examine the underlying mechanism for the association, we included a negative control group for RA, arthralgia, with similar symptomology as RA but free from inflammation/autoimmunity.

Of 3629 children born to mothers with RA, 70 (1.94%) were diagnosed with ASD, compared to 28 892 (1.92%) of 1 503 908 children born to mothers without RA. Maternal RA before delivery was associated with an increased risk of offspring ASD (HR = 1.43, 95% CI 1.11–1.84), especially for seronegative RA (HR = 1.61, 95% CI 1.12–2.30). No similar association was observed for paternal RA, maternal sisters with RA, or RA diagnosed after delivery. Maternal arthralgia displayed as high risks for offspring ASD as did maternal RA (HR = 1.41, 95% CI 1.24–1.60).

In Sweden, maternal RA before delivery was associated with an increased risk of offspring ASD. The comparable association between maternal arthralgia and ASD risk suggests other pathways of risk than autoimmunity/inflammation, acting jointly or independently of RA.

Certain treatments have demonstrated acute efficacy for binge-eating disorder (BED) but there is a dearth of controlled research examining pharmacotherapies as maintenance treatments for responders to initial interventions. This gap in the literature is particularly critical for pharmacotherapy for BED which is associated with relapse following discontinuation. The current study tested the efficacy of naltrexone/bupropion maintenance treatment amongst responders to acute treatments for BED.

Prospective randomized double-blind placebo-controlled single-site trial, conducted August 2017–December 2021, tested naltrexone/bupropion as maintenance treatment for responders to acute treatments with naltrexone/bupropion and/or behavioral weight-loss therapy for BED with comorbid obesity. Sixty-six patients (84.8% women, mean age 46.9, mean BMI 34.9 kg/m2) who responded to acute treatments were re-randomized to placebo (N = 34) or naltrexone/bupropion (N = 32) for 16 weeks; 86.3% completed posttreatment assessments. Mixed models and generalized estimating equations comparing maintenance treatments (naltrexone/bupropion v. placebo) included main and interactive effects of acute treatments.

Intention-to-treat binge-eating remission rates following maintenance treatments were 50.0% (N = 17/34) for placebo and 68.8% (N = 22/32) for naltrexone/bupropion. Placebo following response to acute treatment with naltrexone/bupropion was associated with significantly decreased probability of binge-eating remission, increased binge-eating frequency, and no weight loss. Naltrexone/bupropion following response to acute treatment with naltrexone/bupropion was associated with good maintenance of binge-eating remission, low binge-eating frequency, and significant additional weight loss.

Adult patients with BED with co-occurring obesity who have good responses to acute treatment with naltrexone/bupropion should be offered maintenance treatment with naltrexone/bupropion.

Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.

A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.

Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.

These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.

Adverse childhood experiences (ACEs) and genetic liability are important risk factors for depression and inflammation. However, little is known about the gene−environment (G × E) mechanisms underlying their aetiology. For the first time, we tested the independent and interactive associations of ACEs and polygenic scores of major depressive disorder (MDD-PGS) and C-reactive protein (CRP-PGS) with longitudinal trajectories of depression and chronic inflammation in older adults.

Data were drawn from the English longitudinal study of ageing (N~3400). Retrospective information on ACEs was collected in wave3 (2006/07). We calculated a cumulative risk score of ACEs and also assessed distinct dimensions separately. Depressive symptoms were ascertained on eight occasions, from wave1 (2002/03) to wave8 (2016/17). CRP was measured in wave2 (2004/05), wave4 (2008/09), and wave6 (2012/13). The associations of the risk factors with group-based depressive-symptom trajectories and repeated exposure to high CRP (i.e. ⩾3 mg/L) were tested using multinomial and ordinal logistic regression.

All types of ACEs were independently associated with high depressive-symptom trajectories (OR 1.44, 95% CI 1.30–1.60) and inflammation (OR 1.08, 95% CI 1.07–1.09). The risk of high depressive-symptom trajectories (OR 1.47, 95% CI 1.28–1.70) and inflammation (OR 1.03, 95% CI 1.01–1.04) was also higher for participants with higher MDD-PGS. G×E analyses revealed that the associations between ACEs and depressive symptoms were larger among participants with higher MDD-PGS (OR 1.13, 95% CI 1.04–1.23). ACEs were also more strongly related to inflammation in participants with higher CRP-PGS (OR 1.02, 95% CI 1.01–1.03).

ACEs and polygenic susceptibility were independently and interactively associated with elevated depressive symptoms and chronic inflammation, highlighting the clinical importance of assessing both ACEs and genetic risk factors to design more targeted interventions.

The sense of ‘loss of control’ (LOC), or a feeling of being unable to stop eating or control what or how much one is eating, is the most salient aspect of binge eating. However, the neural alterations that may contribute to this experience and eating behavior remain poorly understood.

We used functional near-infrared spectroscopy (fNIRS) to measure activation in the prefrontal cortices of 23 women with bulimia nervosa (BN) and 23 healthy controls (HC) during two tasks: a novel go/no-go task requiring inhibition of eating responses, and a standard go/no-go task requiring inhibition of button-pressing responses.

Women with BN made more commission errors on both tasks. BN subgroups with the most severe LOC eating (n = 12) and those who felt most strongly that they binge ate during the task (n = 12) showed abnormally reduced bilateral ventromedial prefrontal cortex (vmPFC) and right ventrolateral prefrontal cortex (vlPFC) activation associated with eating-response inhibition. In the entire BN sample, lower eating-task activation in right vlPFC was related to more frequent and severe LOC eating, but no group differences in activation were detected on either task when this full sample was compared with HC. BN severity was unrelated to standard-task activation.

Results provide initial evidence that diminished PFC activation may directly contribute to more severe eating-specific control deficits in BN. Our findings support vmPFC and vlPFC dysfunction as promising treatment targets, and indicate that eating-specific tasks and fNIRS may be useful tools for identifying neural mechanisms underlying dysregulated eating.

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.

There is substantial variation in patient symptoms following psychological therapy for depression and anxiety. However, reliance on endpoint outcomes ignores additional interindividual variation during therapy. Knowing a patient's likely symptom trajectories could guide clinical decisions. We aimed to identify latent classes of patients with similar symptom trajectories over the course of psychological therapy and explore associations between baseline variables and trajectory class.

Patients received high-intensity psychological treatment for common mental health problems at National Health Service Improving Access to Psychological Therapies services in South London (N = 16 258). To identify trajectories, we performed growth mixture modelling of depression and anxiety symptoms over 11 sessions. We then ran multinomial regressions to identify baseline variables associated with trajectory class membership.

Trajectories of depression and anxiety symptoms were highly similar and best modelled by four classes. Three classes started with moderate-severe symptoms and showed (1) no change, (2) gradual improvement, and (3) fast improvement. A final class (4) showed initially mild symptoms and minimal improvement. Within the moderate-severe baseline symptom classes, patients in the two showing improvement as opposed to no change tended not to be prescribed psychotropic medication or report a disability and were in employment. Patients showing fast improvement additionally reported lower baseline functional impairment on average.

Multiple trajectory classes of depression and anxiety symptoms were associated with baseline characteristics. Identifying the most likely trajectory for a patient at the start of treatment could inform decisions about the suitability and continuation of therapy, ultimately improving patient outcomes.

Wellbeing has a fundamental role in determining life expectancy and major depressive disorder (MDD) is one of the main modulating factors of wellbeing. This study evaluated the modulators of wellbeing in individuals with lifetime recurrent MDD (RMDD), single-episode MDD (SMDD) and no MDD in the UK Biobank.

Scores of happiness, meaningful life and satisfaction about functioning were condensed in a functioning-wellbeing score (FWS). We evaluated depression and anxiety characteristics, neuroticism-related traits, physical diseases, lifestyle and polygenic risk scores (PRSs) of psychiatric disorders. Other than individual predictors, we estimated the cumulative contribution to FWS of each group of predictors. We tested the indirect role of neuroticism on FWS through the modulation of depression manifestations using a mediation analysis.

We identified 47 966, 21 117 and 207 423 individuals with lifetime RMDD, SMDD and no MDD, respectively. Depression symptoms and personality showed the largest impact on FWS (variance explained ~20%), particularly self-harm, worthlessness feelings during the worst depression, chronic depression, loneliness and neuroticism. Personality played a stronger role in SMDD. Anxiety characteristics showed a higher effect in SMDD and no MDD groups. Neuroticism played indirect effects through specific depressive symptoms that modulated FWS. Physical diseases and lifestyle explained only 4–5% of FWS variance. The PRS of MDD showed the largest effect on FWS compared to other PRSs.

This was the first study to comprehensively evaluate the predictors of wellbeing in relation to the history of MDD. The identified variables are important to identify individuals at risk and promote wellbeing.

Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment.

US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data.

Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06–1.43) and 1.18 (1.02–1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01–1.25) and 1.16 (1.04–1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03–1.31)]. No other associations were statistically significant.

Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Catatonia, a severe neuropsychiatric syndrome, has few studies of sufficient scale to clarify its epidemiology or pathophysiology. We aimed to characterise demographic associations, peripheral inflammatory markers and outcome of catatonia.

Electronic healthcare records were searched for validated clinical diagnoses of catatonia. In a case–control study, demographics and inflammatory markers were compared in psychiatric inpatients with and without catatonia. In a cohort study, the two groups were compared in terms of their duration of admission and mortality.

We identified 1456 patients with catatonia (of whom 25.1% had two or more episodes) and 24 956 psychiatric inpatients without catatonia. Incidence was 10.6 episodes of catatonia per 100 000 person-years. Patients with and without catatonia were similar in sex, younger and more likely to be of Black ethnicity. Serum iron was reduced in patients with catatonia [11.6 v. 14.2 μmol/L, odds ratio (OR) 0.65 (95% confidence interval (CI) 0.45–0.95), p = 0.03] and creatine kinase was raised [2545 v. 459 IU/L, OR 1.53 (95% CI 1.29–1.81), p < 0.001], but there was no difference in C-reactive protein or white cell count. N-Methyl-d-aspartate receptor antibodies were significantly associated with catatonia, but there were small numbers of positive results. Duration of hospitalisation was greater in the catatonia group (median: 43 v. 25 days), but there was no difference in mortality after adjustment.

In the largest clinical study of catatonia, we found catatonia occurred in approximately 1 per 10 000 person-years. Evidence for a proinflammatory state was mixed. Catatonia was associated with prolonged inpatient admission but not with increased mortality.

Young people are most vulnerable to suicidal behaviours but least likely to seek help. A more elaborate study of the intrinsic and extrinsic correlates of suicidal ideation and behaviours particularly amid ongoing population-level stressors and the identification of less stigmatising markers in representative youth populations is essential.

Participants (n = 2540, aged 15–25) were consecutively recruited from an ongoing large-scale household-based epidemiological youth mental health study in Hong Kong between September 2019 and 2021. Lifetime and 12-month prevalence of suicidal ideation, plan, and attempt were assessed, alongside suicide-related rumination, hopelessness and neuroticism, personal and population-level stressors, family functioning, cognitive ability, lifetime non-suicidal self-harm, 12-month major depressive disorder (MDD), and alcohol use.

The 12-month prevalence of suicidal ideation, ideation-only (no plan or attempt), plan, and attempt was 20.0, 15.4, 4.6, and 1.3%, respectively. Importantly, multivariable logistic regression findings revealed that suicide-related rumination was the only factor associated with all four suicidal outcomes (all p < 0.01). Among those with suicidal ideation (two-stage approach), intrinsic factors, including suicide-related rumination, poorer cognitive ability, and 12-month MDE, were specifically associated with suicide plan, while extrinsic factors, including coronavirus disease 2019 (COVID-19) stressors, poorer family functioning, and personal life stressors, as well as non-suicidal self-harm, were specifically associated with suicide attempt.

Suicide-related rumination, population-level COVID-19 stressors, and poorer family functioning may be important less-stigmatising markers for youth suicidal risks. The respective roles played by not only intrinsic but also extrinsic factors in suicide plan and attempt using a two-stage approach should be considered in future preventative intervention work.

Adolescence is characterized by profound change, including increases in negative emotions. Approximately 84% of American adolescents own a smartphone, which can continuously and unobtrusively track variables potentially predictive of heightened negative emotions (e.g. activity levels, location, pattern of phone usage). The extent to which built-in smartphone sensors can reliably predict states of elevated negative affect in adolescents is an open question.

Adolescent participants (n = 22; ages 13–18) with low to high levels of depressive symptoms were followed for 15 weeks using a combination of ecological momentary assessments (EMAs) and continuously collected passive smartphone sensor data. EMAs probed negative emotional states (i.e. anger, sadness and anxiety) 2–3 times per day every other week throughout the study (total: 1145 EMA measurements). Smartphone accelerometer, location and device state data were collected to derive 14 discrete estimates of behavior, including activity level, percentage of time spent at home, sleep onset and duration, and phone usage.

A personalized ensemble machine learning model derived from smartphone sensor data outperformed other statistical approaches (e.g. linear mixed model) and predicted states of elevated anger and anxiety with acceptable discrimination ability (area under the curve (AUC) = 74% and 71%, respectively), but demonstrated more modest discrimination ability for predicting states of high sadness (AUC = 66%).

To the extent that smartphone data could provide reasonably accurate real-time predictions of states of high negative affect in teens, brief ‘just-in-time’ interventions could be immediately deployed via smartphone notifications or mental health apps to alleviate these states.

Co-occurring psychiatric disorders are common in autism, with previous studies suggesting 54–94% of autistic individuals develop a mental health condition in their lifetime. Most studies have looked at clinically-recruited cohorts, or paediatric cohorts followed into adulthood, with less known about the autistic community at a population level. We therefore studied the prevalence of co-occurring psychiatric and neurological conditions in autistic individuals in a national sample.

This retrospective case-control study utilised the SAIL Databank to examine anonymised whole population electronic health record data from 2001 to 2016 in Wales, UK (N = 3.6 million). We investigated the prevalence of co-occurring psychiatric and selected neurological diagnoses in autistic adults' records during the study period using International Classification of Diseases-10 and Read v2 clinical codes compared to general population controls matched for age, sex and deprivation

All psychiatric conditions examined were more common amongst adults with autism after adjusting for age, sex and deprivation. Prevalence of attention-deficit hyperactivity disorder (7.00%), bipolar disorder (2.50%), obsessive-compulsive disorder (3.02%), psychosis (18.30%) and schizophrenia (5.20%) were markedly elevated in those with autism, with corresponding odds ratios 8.24–10.74 times the general population. Depression (25.90%) and anxiety (22.40%) were also more prevalent, with epilepsy 9.21 times more common in autism.

We found that a range of psychiatric conditions were more frequently recorded in autistic individuals. We add to understanding of under-reporting and diagnostic overshadowing in autism. With increasing awareness of autism, services should be cognisant of the psychiatric conditions that frequently co-occur in this population.

Exposure to trauma is common and can have a profoundly negative impact on mental health. Interventions based on trauma-focused cognitive behavioural therapy have shown promising results to facilitate recovery. The current trial evaluated whether a novel, scalable and digital early version of the intervention, Condensed Internet-Delivered Prolonged Exposure (CIPE), is effective in reducing post-traumatic stress symptoms.

A single-site randomised controlled trial with self-referred adults (N = 102) exposed to trauma within the last 2 months. The participants were randomised to 3 weeks of CIPE or a waiting list (WL) for 7 weeks. Assessments were conducted at baseline, week 1–3 (primary endpoint), week 4–7 (secondary endpoint) and at 6-month follow-up. The primary outcome measure was PTSD Checklist for DSM-5 (PCL-5).

The main analysis according to the intention-to-treat principle indicated statistically significant reductions in symptoms of post-traumatic stress in the CIPE group as compared to the WL group. The between-group effect size was moderate at week 3 (bootstrapped d = 0.70; 95% CI 0.33–1.06) and large at week 7 (bootstrapped d = 0.83; 95% CI 0.46–1.19). Results in the intervention group were maintained at the 6-month follow-up. No severe adverse events were found.

CIPE is a scalable intervention that may confer early benefits on post-traumatic stress symptoms in survivors of trauma. The next step is to compare this intervention to an active control group and also investigate its effects when implemented in regular care.