Network analysis of distress, suicidality, and resilience in a treatment seeking sample of first responders

Columbia-Suicide Severity Rating Scale (C-SSRS) Reveals High Rates of Suicidality in 602 Patients With Cleft and Craniofacial Conditions

INTRODUCTION

Little is known about rates of suicidal ideation and behavior among youth with cleft lip and/or palate (CLP) and other craniofacial conditions.

METHODS

Records of patients ages 6 and older who were administered the Columbia-Suicide Severity Rating Scale (C-SSRS) Lifetime Version during routine multidisciplinary cleft or craniofacial team visits between 2019 and 2023 were examined. Demographics information, C-SSRS data, and diagnoses were assessed with statistics including t tests, the Fisher exact test, and odds ratios.

RESULTS

A total of 1140 C-SSRS questionnaires across 602 (433 CLP and 169 craniofacial) patients with an average age of 11.2±3.7 years were included. Eighty-four (13.6%) patients endorsed lifetime suicidal ideation, 9 (1.5%) had at least one instance of suicidal behavior, 30 (5.0%) endorsed nonsuicidal self-injury, and 2 (0.3%) engaged in self-injurious behavior. Compared with CLP, those with other craniofacial conditions had similar odds of endorsing suicidal ideation and behavior (P≥0.05). Compared with those with isolated cleft palates, CLP had greater odds of endorsing suicidal ideation and behavior, though those differences were not significant (P≥0.05). Incidence of suicidality was unchanged before, during, and after the COVID-19 pandemic (P≥0.05). Dividing patients by sex or insurance type revealed no difference in suicidality (P≥0.05).

CONCLUSION

Patients with CLP and craniofacial conditions have a high incidence of suicidal ideation and behavior, though levels are similar between these groups. Suicidality in these patients was not negatively impacted by the COVID-19 pandemic. Early identification of safety risks and psychosocial challenges through regular screening can facilitate connection with appropriate clinical interventions.

Mapping PTSD, depression, and anxiety: A network analysis of co-occurring symptoms in treatment-seeking first responders

First responders are at high risk for a range of co-occurring mental health conditions due to their repeated exposure to traumatic events. When first responders present for treatment, their complex presentation of symptoms including posttraumatic stress disorder (PTSD), depression, and generalized anxiety disorder (GAD) can prove challenging to differentiate for clinical purposes. Network analysis provides a means to identify the nuanced associations between the symptoms of these conditions and to identify groups of related symptoms. In this study, a treatment-seeking sample of first responders (N = 432) completed self-report measures of PTSD, depression, and GAD. Network analysis was used to identify symptom clusters within the sample. Our cross-sectional data yielded six empirically distinct communities: depression symptoms, GAD symptoms, and four communities comprising PTSD symptoms - intrusion and avoidance; irritability and aggression; negative affect; and arousal and sleep. Network associations underscore the heterogeneity of PTSD and also highlight overlapping and diverging symptoms of depression and GAD. These findings are discussed within the context of existing research on first responders, and recommendations for further study and treatment interventions are provided.

Validation of the PCL-5, PHQ-9, and GAD-7 in a Sample of Veterans

OBJECTIVE

Veterans can present at nongovernment (Department of Defense, Department of Veterans Affairs) mental health agencies with complex symptom constellations that frequently include posttraumatic stress disorder, depression, and generalized anxiety. To date, no veteran study has validated these measures on a treatment-seeking sample of veterans outside the DoD and VA.

METHODS

We used a treatment-seeking sample of veterans ( N = 493) to validate measures that assess these constructs (PTSD Checklist 5, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7).

RESULTS

The seven-factor posttraumatic stress disorder hybrid configuration was the best fit. The best fitting model of the depression measure was a two-factor structure, cognitive-affective, and somatic depression. The measure of generalized anxiety was a unidimensional model.

LIMITATIONS

Follow-up studies should validate these measures on nontreatment-seeking discharged veterans.

CONCLUSIONS

We interpret these findings within the veteran scholarship and explore clinical implications for providers.

The effect of intolerance of uncertainty on anxiety and depression, and their symptom networks, during the COVID-19 pandemic

Individuals vary in their ability to tolerate uncertainty. High intolerance of uncertainty (the tendency to react negatively to uncertain situations) is a known risk factor for mental health problems. In the current study we examined the degree to which intolerance of uncertainty predicted depression and anxiety symptoms and their interrelations across the first year of the COVID-19 pandemic. We examined these associations across three time points (May 2020 - April 2021) in an international sample of adults (N = 2087, Mean age = 41.13) from three countries (UK, USA, Australia) with varying degrees of COVID-19 risk. We found that individuals with high and moderate levels of intolerance of uncertainty reported reductions in depression and anxiety symptoms over time. However, symptom levels remained significantly elevated compared to individuals with low intolerance of uncertainty. Individuals with low intolerance of uncertainty had low and stable levels of depression and anxiety across the course of the study. Network analyses further revealed that the relationships between depression and anxiety symptoms became stronger over time among individuals with high intolerance of uncertainty and identified that feeling afraid showed the strongest association with intolerance of uncertainty. Our findings are consistent with previous work identifying intolerance of uncertainty as an important risk factor for mental health problems, especially in times marked by actual health, economic and social uncertainty. The results highlight the need to explore ways to foster resilience among individuals who struggle to tolerate uncertainty, as ongoing and future geopolitical, climate and health threats will likely lead to continued exposure to significant uncertainty.