Anxiety, distress tolerance, and the relationship between complex posttraumatic stress disorder symptoms and alcohol use in veterans.

OBJECTIVES: Little is known about whether distress tolerance and anxiety mediate the relationship between comorbid complex posttraumatic stress disorder (CPTSD) and alcohol use among military veterans. Here, we investigated the contribution of distress tolerance and anxiety on the strength of the CPTSD and alcohol use association. We hypothesized that the impact of a two-factor model of CPTSD derived from subscale scores on the International Trauma Questionnaire (ITQ)-namely ITQ PTSD and ITQ Disturbances in Self Organization (DSO; e.g., issues with affective regulation/self-belief and shame)-on alcohol use severity would be mediated by anxiety but not by distress tolerance. METHODS: Participants included 403 community-dwelling United Kingdom (UK) veterans (91.64% male, Mage = 51.15 years, SD = 12.48) recruited as part of a larger, online study. RESULTS: Findings indicated that the influence of CPTSD symptoms on alcohol use severity was mediated by anxiety, not by distress tolerance, with greater relative impact due to ITQ DSO status than ITQ PTSD status. CONCLUSIONS: We identified the mediational influence of anxiety and distress tolerance on the association between CPTSD subscales and alcohol use in UK veterans. Interventions for anxiety may be adapted for reducing problematic alcohol use and the impact of CPTSD symptoms in veterans with comorbid PTSD and alcohol use disorder.

The network structure of mania symptoms differs between people with and without binge eating.

OBJECTIVES: People with bipolar disorder who also report binge eating have increased psychopathology and greater impairment than those without binge eating. Whether this co-occurrence is related to binge eating as a symptom or presents differently across full-syndrome eating disorders with binge eating is unclear. METHODS: We first compared networks of 13 lifetime mania symptoms in 34,226 participants from the United Kingdom's National Institute for Health and Care Research BioResource with (n = 12,104) and without (n = 22,122) lifetime binge eating. Second, in the subsample with binge eating, we compared networks of mania symptoms in participants with lifetime anorexia nervosa binge-eating/purging (n = 825), bulimia nervosa (n = 3737), and binge-eating disorder (n = 3648). RESULTS: People with binge eating endorsed every mania symptom significantly more often than those without binge eating. Within the subsample, people with bulimia nervosa most often had the highest endorsement rate of each mania symptom. We found significant differences in network parameter statistics, including network structure (M = 0.25, p = 0.001) and global strength (S = 1.84, p = 0.002) when comparing the binge eating with no binge-eating participants. However, network structure differences were sensitive to reductions in sample size and the greater density of the latter network was explained by the large proportion of participants (34%) without mania symptoms. The structure of the anorexia nervosa binge-eating/purging network differed from the bulimia nervosa network (M = 0.66, p = 0.001), but the result was unstable. CONCLUSIONS: Our results suggest that the presence and structure of mania symptoms may be more associated with binge eating as a symptom rather than any specific binge-type eating disorder. Further research with larger sample sizes is required to confirm our findings.

Rates and correlates of psychological distress and PTSD among persons with physical disabilities in Cambodia.

BACKGROUND: Compared to the general population, persons with disabilities are at increased risk of poor mental health. The aim of this study was to determine the rates and correlates of psychological distress and post-traumatic stress disorder (PTSD) among persons with physical disabilities in Cambodia. METHODS: From July to December 2021 data were collected as part of a mental health screening programme for persons with physical disabilities who access prosthetic and orthotic services. Psychological distress was measured using the Kessler-10 (K-10) and PTSD using the PC-PTSD-5. Bivariate and multiple linear regression analyses were conducted to identify factors associated with levels of psychological distress and PTSD among this population. RESULTS: Our study found a high prevalence of psychological distress and PTSD in this patient cohort. Of the 213 participants, 31.5% were likely to be experiencing mild to moderate psychological distress indicative of a mental health disorder, with 13.6% likely to have a severe mental health disorder. Sixty-five percent of patients reported experiencing PTSD symptoms, with forty-six percent meeting the criteria for probable PTSD. Psychological distress was associated with pathological worry, rumination, and facets of mindfulness. Rumination and pathological worry were found to be significant predictors of psychological distress. PTSD symptoms were associated with pathological worry but not facets of mindfulness or rumination. Facets of mindfulness and pathological worry were found to be significant predictors of PTSD. CONCLUSION: Integration of mental health services within the disability sector is required to address psychological distress and PTSD symptoms among people with physical disabilities in Cambodia. Health system interventions, such as screening, referral, and the training of health providers, need to be strengthened. Further studies focussing on the psychosocial determinants of mental health of persons with disabilities in Cambodia are required.

Risk and protective factors for new-onset binge eating, low weight, and self-harm symptoms in >35,000 individuals in the UK during the COVID-19 pandemic.

OBJECTIVE: The disruption caused by the COVID-19 pandemic has been associated with poor mental health, including increases in eating disorders and self-harm symptoms. We investigated risk and protective factors for the new onset of these symptoms during the pandemic. METHOD: Data were from the COVID-19 Psychiatry and Neurological Genetics study and the Repeated Assessment of Mental health in Pandemics Study (n = 36,715). Exposures were socio-demographic characteristics, lifetime psychiatric disorder, and COVID-related variables, including SARS-CoV-2 infection/illness with COVID-19. We identified four subsamples of participants without pre-pandemic experience of our outcomes: binge eating (n = 24,211), low weight (n = 24,364), suicidal and/or self-harm ideation (n = 18,040), and self-harm (n = 29,948). Participants reported on our outcomes at frequent intervals (fortnightly to monthly). We fitted multiple logistic regression models to identify factors associated with the new onset of our outcomes. RESULTS: Within each subsample, new onset was reported by: 21% for binge eating, 10.8% for low weight, 23.5% for suicidal and/or self-harm ideation, and 3.5% for self-harm. Shared risk factors included having a lifetime psychiatric disorder, not being in paid employment, higher pandemic worry scores, and being racially minoritized. Conversely, infection with SARS-CoV-2/illness with COVID-19 was linked to lower odds of binge eating, low weight, and suicidal and/or self-harm ideation. DISCUSSION: Overall, we detected shared risk factors that may drive the comorbidity between eating disorders and self-harm. Subgroups of individuals with these risk factors may require more frequent monitoring during future pandemics. PUBLIC SIGNIFICANCE: In a sample of 35,000 UK residents, people who had a psychiatric disorder, identified as being part of a racially minoritized group, were not in paid employment, or were more worried about the pandemic were more likely to experience binge eating, low weight, suicidal and/or self-harm ideation, and self-harm for the first time during the pandemic. People with these risk factors may need particular attention during future pandemics to enable early identification of new psychiatric symptoms.

Exploring the associations between auditory hallucinations and psychopathological experiences in 10,933 patient narratives: moving beyond diagnostic categories and surveys.

BACKGROUND: Previous research suggests that auditory hallucinations are prevalent within both the clinical and general populations. Yet, we know little about how these phenomena are associated with other psychopathology symptoms and experiences. The current study aids investigations towards preventing, predicting and more effectively responding to such distressing occurrences. There have been substantial efforts in the literature to propose models of auditory hallucination and attempts to verify them. However, many of these studies used survey methods that restrict the person's responses to a set of pre-defined criteria or experiences and do not allow exploration of potential important other symptoms beyond them. This is the first study to explore the correlates of auditory hallucination using a qualitative dataset consisting of unrestricted responses of patients about their lived experiences with mental illness. METHOD: The study used a dataset consisting of 10,933 narratives from patients diagnosed with mental illnesses. For analysis, the study used correlation on the text-based data. This approach is an alternative to the knowledge-based approach where experts manually read the narratives and infer the rules and relationships from the dataset. RESULT: This study found at least 8 correlates of auditory hallucination (small correlation coefficients), with the unusual ones being "pain." The study also found that auditory hallucinations were independent of obsessive thoughts and compulsive behaviours, and dissociation, in contrast with the literature. CONCLUSION: This study presents an innovative approach to explore the possible associations between symptoms without the restrictions of (or outside the confines of) traditional diagnostic categories. The study exemplified this by finding the correlates of auditory hallucination. However, any other symptom or experience of interest can be studied similarly. Potential future directions of these findings are discussed in the context of mental healthcare screening and treatment.

Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study.

BACKGROUND: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants. METHODS: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two). RESULTS: For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships. CONCLUSIONS: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies.

What we talk about when we talk about trauma: Content overlap and heterogeneity in the assessment of trauma exposure.

The accurate definition and assessment of trauma exposure is the foundation for replicable studies of mental health problems following trauma exposure. However, scales developed to assess trauma exposure might vary widely in terms of item content; overlap; and specifications of trauma intensity, frequency, duration, and timing. We compared eight frequently used self-report measures of trauma exposure to address content overlap and measurement heterogeneity. Combined, these measures assess 44 disparate exposures. Mean overlap across scales was moderate (M = 0.41, range: 0.25-0.48 across scales). Pairwise overlap between scales ranged from .19 to .59. We found 18 exposures (40.9%) that were included in one scale and three exposures (6.8%) that were included in all eight scales. Four of the included scales assess trauma frequency, five assess intensity or perceived danger, two assess duration, and four assess timing. The implications of measurement heterogeneity for clinical research as well as for comparability and replication of trauma-related research are discussed.

The Middle-Out Approach to reconceptualizing, assessing, and analyzing traumatic stress reactions.

Alternative models of traumatic stress and broader psychopathology have been proposed to address issues of heterogeneity, comorbidity, clinical utility, and equitable representation. However, systematic and practical methods and guidelines to organize and apply these models remain scarce. The Middle-Out Approach is a novel, integrative, contextually informed framework for organizing and applying existing empirical methods to evaluate current and alternative traumatic stress reactions. Rather than beginning to identify traumatic stress reactions from the top-down (i.e., disorder-first approach) or bottom-up (i.e., symptom-first approach), constructs are evaluated from the middle out (i.e., presentation-first approach), unconstrained by higher-order disorders or lower-order diagnostic symptoms. This approach provides innovation over previous methods at multiple levels, including the conceptualization of traumatic stress reactions as well as the type of assessments and data sources used and how they are used in statistical analyses. Conceptualizations prioritize the identification of middle-order phenotypes, representing person-centered clinical presentations, which are informed by the integration of multidimensional, transdiagnostic, and multimodal (e.g., psychosocial, physiological) assessments and/or data sources. Integrated data are then analyzed concurrently using person-centered statistical models to identify precise, discrete, and representative health outcomes within broader heterogeneous samples. Subsequent variable-centered analyses are then used to identify culturally sensitive and contextually informed correlates of phenotypes, their clinical utility, and the differential composition within and between broader traumatic stress reactions. Examples from the moral injury literature are used to illustrate practical applications that may increase clinical utility and the accurate representation of health outcomes for diverse individuals and communities.

A tri-directional examination of adolescent personality, perceived parenting, and economic and parental adversity contexts in influencing adolescent behavioral outcomes.

INTRODUCTION: Adolescent personality is consistently linked to behavioral strengths and difficulties. However, most of this work is limited in that it does not consider personality beyond the Big Five or economic or parental adversity contexts. The Tri-Directional Framework of Parent and Offspring Traits and Outcomes highlights the collective influence of personality, parenting, and context on offspring behavioral outcomes. METHODS: Parent and adolescent cross-sectional data were collected from 2019 to 2021 as part of the Parents and Children Together project in the United Kingdom. Adolescents (N = 310, 48.7% female) self-reported on Dark Triad traits, parenting, and behavior. Parents (N = 288, 46.9% mothers) self-reported on socioeconomic status and adverse childhood experiences. In two path analysis models, we examined: (1) adolescent Dark Triad, context, and their interactions as predictors of perceived maternal and paternal warmth, hostility, and control; and (2) adolescent Dark Triad, perceived parenting, context, and personality-parenting interactions as predictors of adolescent behavioral strengths and difficulties. RESULTS: Adolescent narcissistic traits were the strongest predictors of perceived maternal parenting, whereas adolescent psychopathy and Machiavellianism were the strongest predictors of perceived paternal parenting. Adolescent personality interacted with contextual factors in predicting parenting, but not with perceived parenting in predicting behavior. CONCLUSION: Adolescent Dark Triad traits, especially narcissism, and contextual factors are important for the parent-offspring relationship and developmental outcomes. We recommend that research move beyond assessing direct trait-outcome associations to examining how these associations operate in different environments.

Intimate Partner Sexual Violence, Gender, and Psychological Distress Among Northern Irish University Students.

While substantial prevalence rates of intimate partner sexual violence (IPSV) have been found among university students for decades in North America, there is a specific gap in published studies on this issue in the United Kingdom and Ireland. The present analysis used data from a larger survey study of students in one Northern Irish university. The analyses reported here were used to examine relationships among IPSV victims, gender (males and females only), unhealthy alcohol use, and psychological distress among university students (n = 654) since the age of 16 and during the previous year. The results of this study are consistent with previous research indicating that women (n = 248) experience IPSV more often than men (n = 37; 50% vs. 23%, respectively). Nonetheless, IPSV is experienced by both men and women with statistically significant associations with alcohol use, posttraumatic stress, depression, and generalized anxiety compared with those who did not report any IPSV experience.

What can we learn about the psychiatric diagnostic categories by analysing patients' lived experiences with Machine-Learning?

BACKGROUND: To deliver appropriate mental healthcare interventions and support, it is imperative to be able to distinguish one person from the other. The current classification of mental illness (e.g., DSM) is unable to do that well, indicating the problem of diagnostic heterogeneity between disorders (i.e., the disorder categories have many common symptoms). As a result, the same person might be diagnosed with two different disorders by two independent clinicians. We argue that this problem might have resulted because these disorders were created by a group of humans (APA taskforce members) who relied on more intuition and consensus than data. Literature suggests that human-led decisions are prone to biases, group-thinking, and other factors (such as financial conflict of interest) that can enormously influence creating diagnostic and treatment guidelines. Therefore, in this study, we inquire that if we prevent such human intervention (and thereby their associated biases) and use Artificial Intelligence (A.I.) to form those disorder structures from the data (patient-reported symptoms) directly, then can we come up with homogenous clusters or categories (representing disorders/syndromes: a group of co-occurring symptoms) that are adequately distinguishable from each other for them to be clinically useful. Additionally, we inquired how these A.I.-created categories differ (or are similar) from human-created categories. Finally, to the best of our knowledge, this is the first study, that demonstrated how to use narrative qualitative data from patients with psychopathology and group their experiences using an A.I. Therefore, the current study also attempts to serve as a proof-of-concept. METHOD: We used secondary data scraped from online communities and consisting of 10,933 patients' narratives about their lived experiences. These patients were diagnosed with one or more DSM diagnoses for mental illness. Using Natural Language Processing techniques, we converted the text data into a numeric form. We then used an Unsupervised Machine Learning algorithm called K-Means Clustering to group/cluster the symptoms.  RESULTS: Using the data mining approach, the A.I. found four categories/clusters formed from the data. We presented ten symptoms or experiences under each cluster to demonstrate the practicality of application and understanding. We also identified the transdiagnostic factors and symptoms that were unique to each of these four clusters. We explored the extent of similarities between these clusters and studied the difference in data density in them. Finally, we reported the silhouette score of + 0.046, indicating that the clusters are poorly distinguishable from each other (i.e., they have high overlapping symptoms). DISCUSSION: We infer that whether humans attempt to categorise mental illnesses or an A.I., the result is that the categories of mental disorders will not be unique enough to be able to distinguish one service seeker from another. Therefore, the categorical approach of diagnosing mental disorders can be argued to fall short of its purpose. We need to search for a classification system beyond the categorical approaches even if there are secondary merits (such as ease of communication and black-and-white (binary) decision making). However, using our A.I. based data mining approach had several meritorious findings. For example, we found that some symptoms are more exclusive or unique to one cluster. In contrast, others are shared by most other clusters (i.e., identification of transdiagnostic experiences). Such differences are interesting objects of inquiry for future studies. For example, in clear contrast to the traditional diagnostic systems, while some experiences, such as auditory hallucinations, are present in all four clusters, others, such as trouble with eating, are exclusive to one cluster (representing a syndrome: a group of co-occurring symptoms). We argue that trans-diagnostic conditions (e.g., auditory hallucinations) might be prime targets for symptom-level interventions. For syndrome-level grouping and intervention, however, we argue that exclusive symptoms are the main targets. CONCLUSION: Categorical approach to mental disorders is not a way forward because the categories are not unique enough and have several shared symptoms. We argue that the same symptoms can be present in more than one syndrome, although dimensionally different. However, we need additional studies to test this hypothesis. Future directions and implications were discussed.

Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants.

BACKGROUND: Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature. METHODS: Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890). RESULTS: Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios. CONCLUSION: Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies.

Disentangling the Symptom-Level Nuances in Comorbid Posttraumatic Stress Disorder and Problematic Alcohol Use in Northern Irish Military Veterans: A Network Analysis.

Posttraumatic stress disorder (PTSD) and alcohol use are highly prevalent among military veteran populations. Several theories have been proposed to account for the comorbidity between PTSD and problematic alcohol use, but research examining the symptom-level associations between the two is limited. The current study used network analysis to examine the associations between PTSD and problematic alcohol use. Data were collected through a cross-sectional survey of veterans of the United Kingdom Armed Forces living in Northern Ireland. The sample comprised 511 (91.2% male) veterans with a history of trauma exposure and current alcohol use. A network consisting of PTSD symptoms from the PTSD Checklist for DSM-5 (PCL-5) and items from the Alcohol Use Disorders Identification Test (AUDIT) was constructed, and the bridge centrality of all items was estimated to identify items with the highest number of associations and the strongest associations between the two constructs. The PTSD symptom "reckless behavior" (2.43) had the highest bridge centrality values and thus the strongest connections and most connections to the alcohol use items. For the alcohol use items, "not being able to stop drinking" (2.31) and "number of drinks" (1.24) demonstrated the strongest bridge connections to the PTSD items. These results highlight the role of specific PTSD symptoms involved in the interaction between PTSD and problematic alcohol use.

Factors associated with changing alcohol consumption during the first UK lockdown.

BACKGROUND: In response to COVID-19 there have been lockdowns and restrictions to hospitality services. Drinking behaviours often change in response to traumatic events and changes in the drinking environment, and this is influenced by a range of factors. This study explores self-reported changes in alcohol consumption in the third month of the UK lockdown, associations with socio-demographics factors and with COVID-19-related concerns, and mental health and wellbeing. METHODS: The COVID-19 Psychological Wellbeing Study was a longitudinal, online, three-wave survey of 1958 UK adults. Data were collected during the first UK lockdown; wave 1 launched 23 March 2020, wave 2 was 1 month after and wave 3 2 months after completion of wave 1A hierarchical multinomial regression model was estimated to investigate factors associated with changes in perceived alcohol consumption in the third month of the lockdown. RESULTS: The majority of participants reported changes in drinking (62%) with over one-third indicating increased consumption. Student status and worries about the financial implications of COVID-19 were associated with lower odds of decreased alcohol consumption. Those with above average income and those with children in the household had lower odds of increased alcohol consumption, while younger adults had higher odds of increased alcohol consumption. CONCLUSIONS: This study adds to the growing body of research showing changes in alcohol consumption behaviours during the COVID-19 lockdown restrictions, and identifies risk and protective factors which can aid in targeting intervention at those most in need of support.

Temporal trends in health worker social media communication during the COVID-19 pandemic.

During the COVID-19 pandemic, healthcare professionals are exposed to extreme hazards and workplace stressors. Social media postings by physicians and nurses related to COVID-19 from January 21 to June 1, 2020 were obtained from the Reddit website. Topic modeling via Latent Dirichlet Allocation (LDA) using a machine-learning approach was performed on 1723 documents, each posted in a unique Reddit discussion. We selected the optimal number of topics using a heuristic approach based on examination of the rate of perplexity change (RPC) across LDA models. A two-step multiple linear regression was done to identify differences across time and between nurses versus physicians. Prevalent topics included excessive workload, positive emotional expression and collegial support, anger and frustration, testing positive for COVID-19 and treatment, use of personal protective equipment, impacts on healthcare jobs, disruption of medical procedures, and general healthcare issues. Nurses' posts initially reflected concern about workload, personal danger, safety precautions, and emotional support to their colleagues. Physicians posted initially more often than nurses about technical aspects of the coronavirus disease, medical equipment, and treatment. Differences narrowed over time: nurses increasingly made technical posts, while physicians' posts increasingly were in the personal domain, suggesting a convergence of the professions over time.

Age and sex-related variability in the presentation of generalized anxiety and depression symptoms.

BACKGROUND: Generalized anxiety and depression are extremely prevalent and debilitating. There is evidence for age and sex variability in symptoms of depression, but despite comorbidity it is unclear whether this extends to anxiety symptomatology. Studies using questionnaire sum scores typically fail to address this phenotypic complexity. METHOD: We conducted exploratory and confirmatory factor analyses on Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) items to identify latent factors of anxiety and depression in participants from the Genetic Links to Anxiety and Depression Study (N = 35,637; 16-93 years). We assessed age- and sex-related variability in latent factors and individual symptoms using multiple logistic regression. RESULTS: Four factors of mood, worry, motor, and somatic symptoms were identified (comparative fit index [CFI] = 0.99, Tucker-Lewis Index [TLI] = 0.99, root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residuals [SRMR] = 0.04). Symptoms of irritability (odds ratio [OR] = 0.81) were most strongly associated with younger age, and sleep change (OR = 1.14) with older age. Males were more likely to report mood and motor symptoms (p < .001) and females to report somatic symptoms (p < .001). CONCLUSION: Significant age and sex variability suggest that classic diagnostic criteria reflect the presentation most commonly seen in younger males. This study provides avenues for diagnostic adaptation and factor-specific interventions.

Posttraumatic Stress Disorder Symptoms and Reckless Behaviors: A Network Analysis Approach.

Existing literature indicates a theoretical and empirical relation between engagement in reckless behaviors and posttraumatic stress disorder (PTSD). Thus, the DSM-5 revision of the PTSD nosology added a new "reckless or self-destructive behavior" (RSDB) symptom (Criterion E2). The current study applied a network analytic approach to examine the item-level relations among a range of reckless behaviors and PTSD symptom clusters. Participants were recruited from Amazon's Mechanical Turk (N = 417), and network analysis was conducted with 20 variables: six PTSD symptom clusters, corresponding to the hybrid model of PTSD (Armour et al., 2015) and excluding the externalizing behavior cluster (Community 1), and 14 items related to reckless behavior (Community 2). The results showed that the network associations were strongest within each construct (i.e., within PTSD and within reckless behaviors), although several bridge connections (i.e., between PTSD clusters and reckless behaviors) were identified. Most reckless behavior items had direct associations with one or more PTSD symptom clusters. The present findings support the existence of close relations between a variety of reckless behaviors and PTSD symptom clusters beyond their relations with DSM Criterion E2. The results provide testable hypotheses about the associations between specific reckless behaviors and PTSD symptom clusters, which may inform future research.

Making the transition: How finding a good job is a risky business for military Veterans in Northern Ireland.

Veterans transitioning from the military to civilian life may encounter difficulties in different domains of functioning. Most research in this area comes from the US and Israel, with Veterans in Northern Ireland (NI) in the United Kingdom, remaining an understudied population. This qualitative study aimed to examine the nature of transition experiences of NI Veterans by analyzing responses (N = 252) to an open-ended question related to the transition process, in a self-report survey. Thematic analysis highlighted both positive and negative experiences across high-level themes. These were related to (1a) how good the military life had been, (1b) the transition had been easy for some Veterans, and (1c) the skills gained in the military have been valuable; (2) it was hard to adjust to civilian life/still adjusting; (3) negative employment experiences; (4) lack of trust; (5) transitioning is hard in NI; and (6) inadequate support, post-service. The findings highlight that NI Veterans share some of the same challenges as other Veterans; however, the challenges in NI are compounded by ongoing security concerns and political tensions, which means living under the radar is a reality for many, making finding meaningful work and community integration difficult. The findings indicate that preparation for civilian life and the acculturation process needs to start many months before discharge. Perhaps more crucially, regiments should work closely with and support civilian employers to equip them to recognize and value the skills ex-Services Veterans can offer, and find a good fit for their skills within their organizations.

Comorbidity Patterns of Psychiatric Conditions in Canadian Armed Forces Personnel.

OBJECTIVE: Posttraumatic stress disorder (PTSD) is often accompanied by other mental health conditions, including major depressive disorder (MDD), substance misuse disorders, and anxiety disorders. The objective of the current study is to delineate classes of comorbidity and investigate predictors of comorbidity classes amongst a sample of Canadian Armed Forces (CAF) Regular Force personnel. METHODS: Latent class analyses (LCAs) were applied to cross-sectional data obtained between April and August 2013 from a nationally representative random sample of 6700 CAF Regular Force personnel who deployed to the mission in Afghanistan. RESULTS: MDD was the most common diagnosis (8.0%), followed by PTSD (5.3%) and generalized anxiety disorder (4.7%). Of those with a mental health condition, LCA revealed 3 classes of comorbidity: a highly comorbid class (8.3%), a depressed-only class (4.6%), and an alcohol use-only class (3.1%). Multinomial logit regression showed that women (adjusted relative risk ratio [ARRR] = 2.77; 95% CI, 2.13 to 3.60; P < 0.01) and personnel reporting higher trauma exposure (ARRR = 4.18; 95% CI, 3.13 to 5.57; P < 0.01) were at increased risk of membership in the comorbid class compared to those without a mental health condition. When compared to those with no mental health condition, experiencing childhood abuse increased the risk of being in any comorbidity class. CONCLUSIONS: Results provide further evidence to support screening for and treatment of comorbid mental health conditions. The role of sex, childhood abuse, and combat deployment in determining class membership may also prove valuable for clinicians treating military-related mental health conditions.

Assessing the existence of dissociative PTSD in sub-acute patients of whiplash.

Numerous studies investigating dissociative posttraumatic stress disorder (D-PTSD) have emerged. However, there is a lack of studies investigating D-PTSD following a wider range of traumatic exposure. Thus, the present study investigates D-PTSD using latent class analysis (LCA) in sub-acute patients of whiplash and associated risk factors. The results of LCA showed a three-class solution primarily distributed according to posttraumatic stress disorder (PTSD) symptom severity and thus no indication of D-PTSD. Dissociative symptoms, psychological distress (i.e. anxiety/depression), and pain severity significantly predicted PTSD severity. Combined, the results support the component model of dissociation and PTSD, while still stressing the importance of dissociative symptoms when planning treatment for PTSD.