BackgroundAttempted suicide is the main risk factor for suicide and repeated suicide attempts. However, the evidence for follow-up treatments reducing suicidal behavior in these patients is limited. The objective of the present study was to evaluate the efficacy of the Attempted Suicide Short Intervention Program (ASSIP) in reducing suicidal behavior. ASSIP is a novel brief therapy based on a patient-centered model of suicidal behavior, with an emphasis on early therapeutic alliance.Methods and FindingsPatients who had recently attempted suicide were randomly allocated to treatment as usual (n = 60) or treatment as usual plus ASSIP (n = 60). ASSIP participants received three therapy sessions followed by regular contact through personalized letters over 24 months. Participants considered to be at high risk of suicide were included, 63% were diagnosed with an affective disorder, and 50% had a history of prior suicide attempts. Clinical exclusion criteria were habitual self-harm, serious cognitive impairment, and psychotic disorder. Study participants completed a set of psychosocial and clinical questionnaires every 6 months over a 24-month follow-up period.The study represents a real-world clinical setting at an outpatient clinic of a university hospital of psychiatry. The primary outcome measure was repeat suicide attempts during the 24-month follow-up period. Secondary outcome measures were suicidal ideation, depression, and health-care utilization. Furthermore, effects of prior suicide attempts, depression at baseline, diagnosis, and therapeutic alliance on outcome were investigated.During the 24-month follow-up period, five repeat suicide attempts were recorded in the ASSIP group and 41 attempts in the control group. The rates of participants reattempting suicide at least once were 8.3% (n = 5) and 26.7% (n = 16). ASSIP was associated with an approximately 80% reduced risk of participants making at least one repeat suicide attempt (Wald χ2 1 = 13.1, 95% CI 12.4–13.7, p < 0.001). ASSIP participants spent 72% fewer days in the hospital during follow-up (ASSIP: 29 d; control group: 105 d; W = 94.5, p = 0.038). Higher scores of patient-rated therapeutic alliance in the ASSIP group were associated with a lower rate of repeat suicide attempts. Prior suicide attempts, depression, and a diagnosis of personality disorder at baseline did not significantly affect outcome. Participants with a diagnosis of borderline personality disorder (n = 20) had more previous suicide attempts and a higher number of reattempts.Key study limitations were missing data and dropout rates. Although both were generally low, they increased during follow-up. At 24 months, the group difference in dropout rate was significant: ASSIP, 7% (n = 4); control, 22% (n = 13). A further limitation is that we do not have detailed information of the co-active follow-up treatment apart from participant self-reports every 6 months on the setting and the duration of the co-active treatment.ConclusionsASSIP, a manual-based brief therapy for patients who have re...

Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain’s intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2 × 2 × 2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test–retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905 ± 0.033 between-sessions; 0.885 ± 0.052 between-scanners) than ASL (0.545 ± 0.048; 0.575 ± 0.059). Nevertheless, ASL provided highly reproducible (0.955 ± 0.021; 0.970 ± 0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

Emergency personnel and rescue workers may be at a risk of posttraumatic stress symptoms (PTSS) due to exposure to trauma and work-related stressors. Though rescuers of different professions are often engaged in the same type of emergency, they have different tasks and responsibilities and receive different training in coping with traumatic events and stress; hence, we speculated that the salience of identified risk factors for PTSS vary across their respective professions. The present cross-sectional survey aimed to identify influencing variables on PTSS, well-being, and suicidal ideation that can act differently across professions of rescue workers and emergency personnel. In this anonymous online study, data from 1,002 rescue workers and emergency personnel in Switzerland, were collected: 499 police officers, 239 firefighters, 97 ambulance personnel, and 85 emergency and 82 psychiatric nurses. PTSS, coping strategies, well-being, suicidal ideation, previously experienced and work-related trauma, and self-efficacy were measured and analyzed using multiple regression and structural equation modeling (SEM). The prevalence of suspected posttraumatic stress disorder varied across the professions, ranged from 8% (firefighters) to 22% (psychiatric nurses), and was associated with psychological strain and suicidal ideation. The SEM showed that dysfunctional coping strategies, self-efficacy, previously experienced and work-related trauma, years on job, and female sex explained up to 78% of PTSS and that PTSS itself explained up to 68% of the psychological strain experienced in the different professions. Independent of the profession, dysfunctional coping such as alcohol use, avoidance, and distraction, as well as work-related trauma were the most robust predictors of PTSS. However, while self-efficacy was a risk factor for police officers, firefighters and ambulance personnel, it was a protective factor for emergency and psychiatric nurses. Furthermore, female sex was only a risk factor for ambulance personnel and emergency nurses. In agreement with prior research, emergency personnel and rescuers exhibited enhanced prevalence of PTSS and suspected PTSD, leading to significant psychological strain and suicidal ideation. However, risk factors varied across the professions. Thus, the development of profession-specific trainings to improve self-efficacy and coping with work-related stressors to reduce PTSS, and enhance quality of life, is needed for individuals in such high-risk professions.Clinical Trial Registration:ClinicalTrials.gov Nr. NCT03842553.

See Mayes (doi:) for a scientific commentary on this article.The hippocampus is thought to support only conscious memory, while neocortex supports both conscious and unconscious memory. Duss et al. show that amnesic patients with damage to the hippocampal–anterior thalamic axis exhibit a diminished form of unconscious encoding and retrieval, suggesting that certain forms of unconscious memory are hippocampus-dependent.

There are a growing number of neuroimaging methods that model spatio-temporal patterns of brain activity to allow more meaningful characterizations of brain networks. This paper proposes dynamic graphical models (DGMs) for dynamic, directed functional connectivity. DGMs are a multivariate graphical model with time-varying coefficients that describe instantaneous directed relationships between nodes. A further benefit of DGMs is that networks may contain loops and that large networks can be estimated. We use network simulations and human resting-state fMRI (N = 500) to investigate the validity and reliability of the estimated networks. We simulate systematic lags of the hemodynamic response at different brain regions to investigate how these lags potentially bias directionality estimates. In the presence of such lag confounds (0.4–0.8 s offset between connected nodes), our method has a sensitivity of 72%–77% to detect the true direction. Stronger lag confounds have reduced sensitivity, but do not increase false positives (i.e., directionality estimates of the opposite direction). In human resting-state fMRI, the default mode network has consistent influence on the cerebellar, the limbic and the auditory/temporal networks. We also show a consistent reciprocal relationship between the visual medial and visual lateral network. Finally, we apply the method in a small mouse fMRI sample and discover a highly plausible relationship between areas in the hippocampus feeding into the cingulate cortex. We provide a computationally efficient implementation of DGM as a free software package for R.