Bored to death: Artificial Intelligence research reveals the role of boredom in suicide behavior.

Background: Recent advancements in Artificial Intelligence (AI) contributed significantly to suicide assessment, however, our theoretical understanding of this complex behavior is still limited. Objective: This study aimed to harness AI methodologies to uncover hidden risk factors that trigger or aggravate suicide behaviors. Methods: The primary dataset included 228,052 Facebook postings by 1,006 users who completed the gold-standard Columbia Suicide Severity Rating Scale. This dataset was analyzed using a bottom-up research pipeline without a-priory hypotheses and its findings were validated using a top-down analysis of a new dataset. This secondary dataset included responses by 1,062 participants to the same suicide scale as well as to well-validated scales measuring depression and boredom. Results: An almost fully automated, AI-guided research pipeline resulted in four Facebook topics that predicted the risk of suicide, of which the strongest predictor was boredom. A comprehensive literature review using APA PsycInfo revealed that boredom is rarely perceived as a unique risk factor of suicide. A complementing top-down path analysis of the secondary dataset uncovered an indirect relationship between boredom and suicide, which was mediated by depression. An equivalent mediated relationship was observed in the primary Facebook dataset as well. However, here, a direct relationship between boredom and suicide risk was also observed. Conclusion: Integrating AI methods allowed the discovery of an under-researched risk factor of suicide. The study signals boredom as a maladaptive 'ingredient' that might trigger suicide behaviors, regardless of depression. Further studies are recommended to direct clinicians' attention to this burdening, and sometimes existential experience.

[WHEN MEDICATIONS ARE NOT ENOUGH - NEUROFEEDBACK AS A COMPLEMENTARY TREATMENT FOR POST-TRAUMATIC STRESS DISORDER - A CASE REPORT].

INTRODUCTION: Neurofeedback (NF) therapy is brain training using operant conditioning including real-time displays of brain activity to teach people how to regulate their brain function. We would like to present a treatment for a patient who experienced severe traumatic events on 7/10 including physical injury accompanied by difficulty sleeping for two months, nightmares, intrusive thoughts, difficulties in emotional regulation and difficulty in concentrating. Due to the complexity and difficulties in emotional regulation accompanied by severe sleep disturbances, it was decided to treat with medication in combination with neurofeedback. After several training sessions in addition to pharmaceutical treatment, significant relaxation was observed, there was an improvement in concentration and the patient was able to return to his work and normal social functioning. In addition, intrusive thoughts decreased in intensity and frequency.

Amygdala-derived-EEG-fMRI-pattern neurofeedback for the treatment of chronic post-traumatic stress disorder. A prospective, multicenter, multinational study evaluating clinical efficacy.

We conducted a prospective, single arm, multisite, multinational, open label trial assessing the safety and efficacy of a novel amygdala derived neurofeedback treatment, designated Amygdala-Derived-EFP, for chronic PTSD. Participants, including veterans and civilians, underwent screening, training, 15 neurofeedback sessions over 8 weeks and; baseline, termination (8 weeks) and 3 month post treatment assessments with validated measures. The primary endpoint was more than 50 % of the participants demonstrating a Minimally Clinically Important Difference (MCID) defined as a 6-point reduction, on the Clinician Administered PTSD Scale (CAPS-5) total score at 3 months. Secondary measures included the PCL-5, ERQ, PHQ-9, and CGI. Statistical analyses were performed using SAS®V9.4. The primary endpoint was met, with a CAPS-5 MCID response rate of 66.7 %. The average reduction in CAPS-5 total scores at 3 month follow up was 13.5 points, more than twice the MCID. Changes from baseline in CAPS-5, PCL-5, PHQ-9 scores at 8 weeks and the 3 month follow-up demonstrated statistically significant improvements in response and; demonstrated effect sizes ranging from 0.46 to 1.07. Adverse events were mild and resolved after treatment. This study builds on prior research demonstrating similar outcomes using amygdala-derived neurofeedback. Positive attributes of this therapy include monitoring by non-physician personnel, affordability, accessibility, and tolerability.

Social Media Images Can Predict Suicide Risk Using Interpretable Large Language-Vision Models.

Background: Suicide, a leading cause of death and a major public health concern, became an even more pressing matter since the emergence of social media two decades ago and, more recently, following the hardships that characterized the COVID-19 crisis. Contemporary studies therefore aim to predict signs of suicide risk from social media using highly advanced artificial intelligence (AI) methods. Indeed, these new AI-based studies managed to break a longstanding prediction ceiling in suicidology; however, they still have principal limitations that prevent their implementation in real-life settings. These include "black box" methodologies, inadequate outcome measures, and scarce research on non-verbal inputs, such as images (despite their popularity today).Objective: This study aims to address these limitations and present an interpretable prediction model of clinically valid suicide risk from images.Methods: The data were extracted from a larger dataset from May through June 2018 that was used to predict suicide risk from textual postings. Specifically, the extracted data included a total of 177,220 images that were uploaded by 841 Facebook users who completed a gold-standard suicide scale. The images were represented with CLIP (Contrastive Language-Image Pre-training), a state-of-the-art deep-learning algorithm, which was utilized, unconventionally, to extract predefined interpretable features (eg, "photo of sad people") that served as inputs to a simple logistic regression model.Results: The results of this hybrid model that integrated theory-driven features with bottom-up methods indicated high prediction performance that surpassed common deep learning algorithms (area under the receiver operating characteristic curve [AUC] = 0.720, Cohen d = 0.82). Further analyses supported a theory-driven hypothesis that at-risk users would have images with increased negative emotions and decreased belongingness.Conclusions: This study provides a first proof that publicly available images can be leveraged to predict validated suicide risk. It also provides simple and flexible strategies that could enhance the development of real-life monitoring tools for suicide.

[COPING WITH THE UNSEEN WOUNDS TO EVALUATE THE HANDICAPS CAUSED BY PTSD].

INTRODUCTION: Post-Traumatic Stress Disorder (PTSD) has been clinically known for over 3500 years, but due to political and financial reasons it was referred to by many names, to put the blame for its existence on the weakness of the victim instead of the abnormal hazards of war. Since it entered the DSM-3 as a specific illness entity (1980), the research and treatment methods grew tremendously, yet the way to diagnosis, understanding how the illness affects the victim, his family members and surrounding were left behind. Diagnosis of PTSD is largely based on the subjective reports of the victim. Talking about the trauma goes often in contradiction with the disorders' related feelings of avoidance, shame and guilt. On the other hand, the patient needs the recognition of his illness so that he can be compensated. These aspects lead to under- and over-diagnosis in many cases. Adding to the oddities of the illness in its diagnosis are the chronicity but wavy tendencies of the clinical picture (such as getting worse near the date of the trauma or when the terror rises) and the option of late onset PTSD etc.. One can understand the gaps between the suffering of the victims and the recognition of their handicap level.

[SLEEP MONITORING FOR PREDICTION OF MAJOR DEPRESSION RECURRENCE IN PATIENTS AT HIGH RISK - A PROSPECTIVE STUDY].

INTRODUCTION: Objective: To examine the feasibility of sleep monitoring using an innovative wearable technology, as a predictive tool for MDE (major depressive episode) recurrence in high risk patients.

Working in corona-designated departments in a fortified underground hospital: Concerns about corona and predictors of job burnout.

Background: In August 2020 during Israel's second COVID-19 wave Rambam Medical Center opened the Sammy Ofer Fortified Underground Emergency Hospital. This was declared a regional Corona center in the north of Israel, receiving the most severe Corona patients from the region. Alongside the advanced inpatient capacity and technology within the underground facility, there was a severe shortage of trained medical and paramedical staff, as well as harsh working conditions. The current study examined the implications and effects of working in an underground facility on healthcare workers, focusing on emotion regulation tendencies and profession as predictors of job burnout. Methods: Seventy-six healthcare workers, who had worked in the underground hospital for a minimum continuous period of 2 weeks during the peak of the COVID-19 pandemic, and a control group of 40 healthcare workers from northern Israel were asked to fill out an online survey administered via Qualtrics (total sample 116). The survey comprised six questionnaires: a demographic survey questionnaire; a COVID-19 concerns questionnaire; a psychological distress questionnaire (DASS, Depression Anxiety Stress Scale); trait worry (PSWQ; Penn State Worry Questionnaire); emotion regulation (ERQ, Emotion Regulation Questionnaire), and burnout (SMBM, Shirom - Melamed Burnout Measure). Results: Independent-samples t-tests revealed no significant differences in psychological distress or burnout between Rambam Underground hospital workers and the control group. Conversely, COVID-19 concern scores were significantly different in the two groups, the Rambam hospital workers showing less concern (M = 2.9, SD = 0.73) than the control group (M = 3.47, SD = 0.76) [t (114) = -3.974, p < 0.001]. Hierarchical linear regression analysis identified the significant predictors of burnout among healthcare workers. Participants' profession (physician), psychological distress (total DASS score), and a personality trait of worry were statistically significant predictors for job burnout (p = 0.028, p < 0.001, p = 0.023, respectively). Concerns about COVID-19 marginally predicted job burnout (p = 0.09). Group (underground vs. control) and emotion regulation tendencies did not predict burnout. Conclusion: The two groups showed no significant differences in psychological distress nor in burnout. Being a physician, having an intrinsic trait of being overly worried and experiencing psychological distress were significant predictors for job burnout among healthcare workers, regardless of work environment (underground vs. control).

Familial clustering of psychiatric disorders and low IQ.

BACKGROUND: Although the ICD and DSM differentiate between different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case-control, sibling study examining familial clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014. METHODS: We identified all cases with autism spectrum disorder (ASD, N = 2128), severe intellectual disability (ID, N = 9572), attention-deficit hyperactive disorder (ADHD) (N = 3272), psychotic (N = 7902), mood (N = 9704), anxiety (N = 10 606), personality (N = 24 816), or substance/alcohol abuse (N = 791) disorders, and low IQ (⩾2 SDs below the population mean, N = 31 186). Non-CNS control disorders were adolescents with Type-1 diabetes (N = 2427), hernia (N = 29 558) or hematological malignancies (N = 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk (RRR) of the sibling of a case having the same (within-disorder RRR) or a different (across-disorder RRR) disorder. RESULTS: Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53 [95% confidence interval (CI): 9.23-14.40] for ASD to 2.93 (95% CI: 2.80-3.07) for personality disorders. The median across-disorder RRR between any pair of psychiatric disorders was 2.16 (95% CI: 1.45-2.43); the median RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93-1.98). There was no consistent increase in across-disorder RRRs between the non-CNS disorders and psychiatric disorders and/or low IQ. CONCLUSION: These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.

Prefrontal Cortex Brain Activation During Texting and Walking: A Functional Near-Infrared Spectroscopy Feasibility Study.

Texting while walking is an increasingly common, potentially dangerous task but its functional brain correlates have yet to be reported. Therefore, we evaluated prefrontal cortex (PFC) activation patterns during single- and dual-task texting and walking in healthy adults. Thirteen participants (29-49 years) walked under single- and dual-task conditions involving mobile phone texting or a serial-7s subtraction task, while measuring PFC activation (functional near-infrared spectroscopy) and behavioral task performance (inertial sensors, mobile application). Head lowering during texting increased PFC activation. Texting further increased PFC activation, and decreased gait performance similarly to serial-7 subtraction. Our results support the key role of executive control in texting while walking.

Personality disorders and cause-specific mortality: a nationwide study of 2 million adolescents.

BACKGROUND: Personality disorders are prevalent in 6-10% of the population, but their risk for cause-specific mortality is unclear. The aim of the study was to assess the association between personality disorders diagnosed in late adolescence and all-cause as well as cause-specific (cardiovascular-related, external-related) mortality. METHODS: We performed a longitudinal study on a historical prospective cohort based on nationwide screening prior to recruitment to the Israeli army. The study participants were 16-19-year-old persons who attended the army screening (medical and cognitive, including screening for psychiatric disorders) between 1967 and 2006. Participants were followed from 1967 till 2011. RESULTS: The study included 2 051 606 subjects, of whom 1 229 252 (59.9%) were men and 822 354 (40.1%) were women, mean age 17.36 years. There were 55 508 (4.5%) men and 8237 (1.0%) women diagnosed with personality disorders. The adjusted hazard ratio (HRs) for coronary, stroke, cardiovascular, external-related causes and all-cause mortality among men with personality disorders were 1.34 (1.03-1.74), 1.82 (1.20-2.76), 1.45 (1.23-1.71), 1.41 (1.30-1.53) and 1.44 (1.36-1.51), respectively. The absolute rate difference for all-cause mortality was 56.07 and 13.19 per 105 person-years among men and women, respectively. Among women with personality disorders, the adjusted HRs for external-related causes and all-cause mortality were 2.74 (1.87-4.00) and 2.01 (1.56-2.58). Associations were already evident within 10 years of follow-up. CONCLUSIONS: Personality disorder in late adolescence is associated with increased risk of cardiovascular, external- and all-cause mortality. Increased cardiovascular mortality is evident before the age of 40 years and may point to the importance of lifestyle education already in youth.

Post-SSRI Sexual Dysfunction (PSSD): Biological Plausibility, Symptoms, Diagnosis, and Presumed Risk Factors.

INTRODUCTION: Post-SSRI sexual-dysfunction (PSSD) is an iatrogenic syndrome, the underlying neurobiological mechanisms of which are unclear. Symptom onset follows cessation of serotonergic antidepressants i.e. Selective Serotonin and Norepinephrine Reuptake Inhibitors (SSRI's, SNRI's), and Tricyclic antidepressants (TCA's). PSSD symptoms include genital anesthesia, erectile dysfunction and orgasmic/ejaculatory anhedonia, and should be differentiated from depression-related sexual-dysfunction. Recently, accumulated data of numerous case-reports suggest additional non-sexual symptoms including, anhedonia, apathy, and blunted affect. PSSD gained official recognition after the European medical agency concluded that PSSD is a medical condition that persists after discontinuation of SSRI's and SNRI's. OBJECTIVE: To review possible underlying neurobiological mechanisms of this syndrome, update information on the pathophysiology, present a list of potential risk-factors and discuss potential management options for PSSD. METHODS: Extensive literature review on the main symptom-patterns of this disorder was undertaken using PubMed. It includes introductory explications of relevant neurobiology with the objective of generating hypothesis. RESULTS: Precipitating factors for PSSD include previous exposure to certain drugs, genetic predisposition, psychological stress or chemical stressful reaction to antidepressants along pre-existing medical conditions affecting neuroplasticity. Different theories have been proposed to explain the pathophysiology of PSSD: epigenetic gene expression, dopamine-serotonin interactions, serotonin neurotoxicity and hormonal changes. The diagnosis of PSSD is achieved by excluding all other etiologies of sexual-dysfunction. Treatment is challenging, and many strategies have been suggested without definitive outcomes. We offer the contours of a future neurobiological research agenda, and propose several underlying mechanisms for the various symptoms of PSSD which could be the foundation for a future treatment algorithm. CONCLUSION: There is a need for well-designed neurobiological research in this domain, as well as in the prevalence, pathophysiology, and treatment of PSSD. Practitioners should be alert to the distinctive features of PSSD. Misdiagnosing this syndrome might lead to harmful treatments including reinstatement of medications which generated PSSD. Sexual Medicine Reviews. Peleg LC, Rabinovitch D, Lavie Y, et al. Post-SSRI Sexual Dysfunction (PSSD): Biological Plausibility, Symptoms, Diagnosis, and Presumed Risk Factors. Sex Med Rev 2022;10:91-98.

Trends in Psychiatric Emergency Department Visits in Northern Israel During the COVID-19 Outbreak.

Background: During the spread of coronavirus disease (COVID-19), mandatory quarantines increased social isolation and anxiety, with inevitable consequences on mental health and health seeking behavior. We wished to estimate those trends. Methods: We examined all psychiatric visits to the emergency department (ED) during March, April 2020, compared to identical months in 2018, 2019. We evaluated both number and nature of referrals. Results: Throughout the years, psychiatric referrals comprised about 5% of the total number of ED visits. In March-April 2020, 30% decreases were observed in overall ED visits and in psychiatric referrals in the ED. Compared to 2018-2019, in 2020, the proportions of these diagnoses were higher: anxiety disorders (14.5 vs. 5.4%, p < 0.001), personality disorders (6.7 vs. 3.2%, p = 0.001), psychosis (9.5 vs. 6.7%, p = 0.049), post-traumatic stress disorder (3.2 vs. 1.5%, p = 0.023). Compared to 2018-2019, in 2020, proportions were lower for adjustment disorder (5.8 vs. 8.9%, p = 0.036) and for consultation regarding observation (11.7 vs. 31.6%, p < 0.001). Differences were not observed between 2018-2019 and 2020 in the proportions of other diagnoses including suicide and self-harm disorders. Referrals concerning suicide and self-harm in a rural hospital and community clinic were 30% lower in the COVID-19 lockdown than in the same months in 2018, 2019. Conclusion: Psychiatric ED visits decreased by the same proportion as overall visits to the ED, apparently driven by fears of COVID-19. Referrals relating suicidality and self-harm shown nominal decrease, but their proportioned share remained constant. Increased anxiety and delayed care may eventually lead to increased mental health needs.

Sleep Monitoring Using WatchPAT Device to Predict Recurrence of Major Depression in Patients at High Risk for Major Depression Disorder Recurrence: A Case Report.

Background: Major depressive disorders are strongly correlated with alterations in sleep pattern and architecture, including changes in the Rapid Eye Movement (REM) phase. However, it is still unknown whether sleep alterations precede other depression-related symptoms, particularly in patients with recurrent depressive episodes at relapse risk. Case Presentation: We initiated a study aimed at examining the value of ambulatory sleep monitoring using a WatchPAT device, in predicting recurrence of Major depression. Depression was assessed monthly with the Beck Depression Inventory version II (BDI-II). Here we present the case of a 63 years old woman, with a history of recurrent depressive episodes. AT the time of recruitment, she was asymptomatic, she experienced recurrence of Major depression 3 months into the study. We observed a significant reduction of the Rem Latency parameters 5 weeks prior to BDI-II score increase, reflecting major depressive episode recurrence. Conclusion: Though our results are preliminary, they suggest that ambulatory sleep monitoring can be used as a simple and accessible tool, predicting recurrence of Major Depressive episodes in patients at high risk, thus enabling early treatment intervention.

Machine learning-based diagnosis support system for differentiating between clinical anxiety and depression disorders.

In light of the need for objective mechanism-based diagnostic tools, the current research describes a novel diagnostic support system aimed to differentiate between anxiety and depression disorders in a clinical sample. Eighty-six psychiatric patients with clinical anxiety and/or depression were recruited from a public hospital and assigned to one of the experimental groups: Depression, Anxiety, or Mixed. The control group included 25 participants with no psychiatric diagnosis. Participants performed a battery of six cognitive-behavioral tasks assessing biases of attention, expectancies, memory, interpretation and executive functions. Data were analyzed with a machine-learning (ML) random forest-based algorithm and cross-validation techniques. The model assigned participants to clinical groups based solely on their aggregated cognitive performance. By detecting each group's unique performance pattern and the specific measures contributing to the prediction, the ML algorithm predicted diagnosis classification in two models: (I) anxiety/depression/mixed vs. control (76.81% specificity, 69.66% sensitivity), and (II) anxiety group vs. depression group (80.50% and 66.46% success rates in classifying anxiety and depression, respectively). The findings demonstrate that the cognitive battery can be utilized as a support system for psychiatric diagnosis alongside the clinical interview. This implicit tool, which is not based on self-report, is expected to enable the clinician to achieve increased diagnostic specificity and precision. Further, this tool may increase the confidence of both clinician and patient in the diagnosis by equipping them with an objective assessment tool. Finally, the battery provides a profile of biased cognitions that characterizes the patient, which in turn enables more fine-tuned, individually-tailored therapy.

Resting mononuclear cell NR3C1 and SKA2 expression levels predict blunted cortisol reactivity to combat training stress among elite army cadets exposed to childhood adversity.

Childhood adversity (CA) may alter reactivity to stress throughout life, increasing risk for psychiatric and medical morbidity, yet long-term correlates of milder CA levels among high functioning healthy adolescents are less studied. The current study examined the prevalence and impact of CA exposure among a cohort of healthy motivated elite parachute unit volunteers, prospectively assessed at rest and at the height of an intensive combat-simulation exposure. We found significantly reduced gene expression levels in resting mononuclear cell nuclear receptor, subfamily 3, member 1 (NR3C1), and its transactivator spindle and kinetochore-associated protein 2 (SKA2), that predict blunted cortisol reactivity to combat-simulation stress among CA exposed adolescents. Long-term alterations in endocrine immune indices, subjective distress, and executive functions persist among healthy high functioning adolescents following milder CA exposure, and may promote resilience or vulnerability to later real-life combat exposure.

Electronic Media Abstinence in Sabbath Observant Jews: A Comparison Between the Weekday and Sabbath.

BACKGROUND: Dependence on technology and electronic media devices (EMDs) is a significant phenomenon of modern life with many people experiencing adverse symptoms during abstention. Orthodox Jews abstain from using all forms of EMDs for 25 consecutive hours every week on the Sabbath but do not appear to experience significant adverse reactions during this abstention. OBJECTIVES: To better examine whether Sabbath observant Jews experience fewer and less severe adverse symptoms while abstaining from EMDs on the Sabbath compared to weekdays. METHODS: Ten Sabbath observant Jews abstained from using all forms of EMDs for 25 hours on a Sabbath and again on a weekday. At the end of each 25-hour period participants completed a 12-item Likert-type scale self-assessment of 1-5, once as a report of their condition at 10:00 and again after 25 hours of abstaining. The authors compared the mean results of Sabbath and weekday using Wilcoxon signed ranks test. P ≤ 0.05 was considered significant. RESULTS: Overall, discomfort on Sabbath was less than on weekdays. A statistically significant decrease on the Sabbath was found at both the 10:00 reporting time and after 25 hours in anxiety, restlessness, thoughts and plans of using devices, and overall difficulty to abstain. Significance was found for feelings of not knowing what to do with time (10:00) and moodiness and irritability, being drawn to devices, and cravings achieved significance (after 25 hours). CONCLUSIONS: Sabbath observant Jews reported statistically significant less adverse reactions while abstaining from EMDs on the Sabbath compared to on a weekday.

Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study.

Traumatic brain injury (TBI) is often characterized by alterations in brain connectivity. We explored connectivity alterations from a network perspective, using graph theory, and examined whether injury severity affected structural connectivity and modulated the association between brain connectivity and cognitive deficits post-TBI. We performed diffusion imaging network analysis on chronic TBI patients, with different injury severities and healthy subjects. From both global and local perspectives, we found an effect of injury severity on network strength. In addition, regions which were considered as hubs differed between groups. Further exploration of graph measures in the determined hub regions showed that efficiency of six regions differed between groups. An association between reduced efficiency in the precuneus and nonverbal abstract reasoning deficits (calculated using actual pre-injury scores) was found in the controls but was lost in TBI patients. Our results suggest that disconnection of network hubs led to a less efficient network, which in turn may have contributed to the cognitive impairments manifested in TBI patients. We conclude that injury severity modulates the disruption of network organization, reflecting a "dose response" relationship and emphasize the role of efficiency as an important diagnostic tool to detect subtle brain injury specifically in mild TBI patients.

Changes in the dynamic network structure of PTSD symptoms pre-to-post combat.

BACKGROUND: Combat exposure is associated with elevated risk for post-traumatic stress disorder (PTSD). Despite considerable research on PTSD symptom clustering, it remains unknown how symptoms of PTSD re-organize following combat. Network analysis provides a powerful tool to examine such changes. METHODS: A network analysis approach was taken to examine how symptom networks change from pre- to post-combat using longitudinal prospective data from a cohort of infantry male soldiers (Mage = 18.8 years). PTSD symptoms measured using the PTSD Checklist (PCL) were assessed after 6 months of combat training but before deployment and again after 6 months of combat (Ns = 910 and 725 at pre-deployment and post-combat, respectively). RESULTS: Stronger connectivity between PTSD symptoms was observed post-combat relative to pre-deployment (global strength values of the networks were 7.54 pre v. 7.92 post; S = .38, p < 0.05). Both the re-experiencing symptoms cluster (1.92 v. 2.12; S = .20, p < 0.03) and the avoidance symptoms cluster (2.61 v. 2.96; S = .35, p < 0.005) became more strongly inter-correlated post-combat. Centrality estimation analyses revealed that psychological reaction to triggers was central and linked the intrusion and avoidance sub-clusters at post-combat. The strength of associations between the arousal and reactivity symptoms cluster remained stable over time (1.85 v. 1.83; S = .02, p = .92). CONCLUSIONS: Following combat, PTSD symptoms and particularly the re-experiencing and avoidance clusters become more strongly inter-correlated, indicating high centrality of trigger-reactivity symptoms.

Understanding the association between advanced paternal age and schizophrenia and bipolar disorder.

BACKGROUND: Previous studies reported an association between advanced paternal age at birth and increased risk for schizophrenia and bipolar disorder. While some hypothesize that this association is caused by de-novo mutations in paternal spermatozoa, others cite factors associated with psycho-social characteristics of fathers who have children at a late age. This study aims to test these hypotheses. METHODS: A historical-prospective, population-based cohort study, performed by linking the Israeli Draft Board Registry and the Israeli National Psychiatric Hospitalization Registry (N = 916 439; 4488 with schizophrenia, 883 with bipolar disorder). Odds ratios (OR) and two-sided 95% confidence intervals (CI) were calculated by logistic regression models, using paternal age as predictor and risk for later hospitalizations for schizophrenia or bipolar disorder as outcome measure. Models were first fitted unadjusted, then adjusted for paternal age at birth of the first child. RESULTS: In the unadjusted model, offspring of fathers aged 45 and above at birth had increased risk of schizophrenia (OR = 1.71, 95% CI 1.49-1.99) and bipolar disorder (OR = 1.63, 95% CI 1.16-2.24). However, taking into account paternal age at birth of first child, advanced paternal age was no longer associated with increased risk of schizophrenia (OR = 0.60, 95% CI 0.48-0.79) or bipolar disorder (OR = 1.03, 95% CI 0.56-1.90). CONCLUSIONS: Controlling for paternal age at birth of the first offspring, advanced paternal age does not predict increased risk for schizophrenia or bipolar disorder. These data indicate that the association between advanced paternal age and having an offspring with schizophrenia and bipolar disorder is likely due to psychos-social factors, or common genetic variation associated with delayed initial fatherhood.

[ISRAELI MILITARY PSYCHIATRY: CHALLENGES AND ACHIEVEMENTS].

INTRODUCTION: In this article, we have attempted to summarize the achievements and the challenges of the mental health department (MHD) of the IDF Medical Core from the past four decades, since its initiation. We approach this wide scope question through the investigation of the MHD according to the perspective of its main fields of endeavor. These domains are widely arrayed. In this paper, we chose to focus on the following: the unique training of the mental health officers; the initial psychological screening of soldiers - from recruitment to discharge; the mental health treatment of soldiers and officers, and the life-time treatment of combat post traumatic (PTSD) patients; the development of combat PTSD diagnosis, treatment and prevention; the continuous prevention of soldiers' suicides; the prevention of psychiatric hospitalizations; and the participation of the MHD in research and in the development of new treatment modalities. In the writing of this paper we relied on the accumulative experience of the MHD and the historic perspective of the last four commanders of the Mental Health Department of the IDF.