The influence of neuropeptide Y (NPY) on the relationship between emotion regulation and mood-related pathology in survivors of childhood interpersonal trauma.

Neuropeptide Y (NPY) is a 36-amino acid peptide that is widely expressed throughout the limbic system. Recent evidence has highlighted NPY as a marker of resilience to posttraumatic psychopathology, which may be due to its association with neural regions involved with emotion regulation. This study examined whether plasma NPY levels moderated the relationship between emotion regulation and psychopathology in a sample of adult survivors of childhood interpersonal trauma, a population known to be at high risk for psychopathology. Adults exposed to an interpersonal criterion A trauma during childhood (N = 54) were recruited from an urban population at a midwestern medical center and completed a baseline study visit as part of a larger clinical trial. Participants gave a blood sample in order to assess circulating levels of NPY and answered questions related to emotion regulation and mood-related pathology. Results of a moderated multiple regression showed that the overall model was significant R2 = 0.26, F (5, 48) = 3.46, p < .01. Difficulties in emotion regulation was significantly predictive of psychopathology (unstandardized B = 0.032, p < .01), and this relationship was significantly moderated by levels of NPY (unstandardized B = -0.001, p < .05) such that the relationship between emotion regulation and psychopathology was weaker for those with higher levels of NPY. Results suggest that higher levels of NPY may lessen the association between emotion regulation and posttraumatic psychopathology in survivors of childhood interpersonal trauma. Further investigation of the contribution of NPY to psychopathology in this population is warranted. NCT: 02279290.

Brain derived neurotrophic factor and treatment outcomes among veterans attending an intensive treatment program for posttraumatic stress disorder.

Brain derived neurotrophic factor (BDNF) may play an important role in the success of treatment for posttraumatic stress disorder (PTSD). Pre- and post-treatment blood samples were analyzed for 40 veterans who completed a 3-week intensive outpatient treatment for PTSD. The treatment included Cognitive Processing Therapy, mindfulness, and yoga as core treatment components. PTSD symptoms were assessed at pre-treatment, post-treatment, and 3-month follow-up. Participants reported large decreases in PTSD symptoms from pre-to post-treatment (d = 1.46, p < 0.001) and pre-treatment to 3-month follow-up (d = 0.91, p < 0.001). Unexpectedly, participants demonstrated a decrease in BDNF from pre-to post-treatment (d = 0.64, p < 0.001). Changes in BDNF from pre-to post-treatment were not significantly associated with PTSD symptom improvement. However, higher levels of post-treatment BDNF were significantly associated with lower PTSD symptoms at 3-month follow-up (n = 27, r = -0.57, p = 0.002) and greater improvements in PTSD symptoms from pre-treatment to 3-month follow-up (n = 27, r = 0.50, p = 0.008). Higher levels of post-treatment BDNF may facilitate the long-term success of intensive PTSD treatment. Further research with larger samples is needed to evaluate the processes by which BDNF may affect consolidation of improvements after completion of PTSD treatment.

Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms Among Urban Homeless Youth: Mixed Methods Study Using Self-report and Smartphone Data.

BACKGROUND: Despite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new digital health intervention models for youth experiencing homelessness. Specifically, passive data collection (data collected without extra steps for a user) may provide insights into lived experience and user needs without putting an additional burden on youth experiencing homelessness to inform digital health intervention design. OBJECTIVE: The objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among youth experiencing homelessness. Additionally, we further examined the relationship between usage and location as correlated with depression and posttraumatic stress disorder (PTSD) symptoms. METHODS: A total of 35 adolescent and young adult participants were recruited from the general community of youth experiencing homelessness for a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to 6 months. Of these participants, 19 had sufficient passive data to conduct analyses. At baseline, participants completed self-reported measures for depression (Patient Health Questionnaire-9 [PHQ-9]) and PTSD (PTSD Checklist for DSM-5 [PCL-5]). Behavioral features were developed and extracted from phone location and usage data. RESULTS: Almost all participants (18/19, 95%) used private networks for most of their noncellular connectivity. Greater Wi-Fi usage was associated with a higher PCL-5 score (P=.006). Greater location entropy, representing the amount of variability in time spent across identified clusters, was also associated with higher severity in both PCL-5 (P=.007) and PHQ-9 (P=.045) scores. CONCLUSIONS: Location and Wi-Fi usage both demonstrated associations with PTSD symptoms, while only location was associated with depression symptom severity. While further research needs to be conducted to establish the consistency of these findings, they suggest that the digital patterns of youth experiencing homelessness offer insights that could be used to tailor digital interventions.

Abnormal intestinal milieu in posttraumatic stress disorder is not impacted by treatment that improves symptoms.

Posttraumatic stress disorder (PTSD) is a psychiatric disorder, resulting from exposure to traumatic events. Current recommended first-line interventions for the treatment of PTSD include evidence-based psychotherapies, such as cognitive processing therapy (CPT). Psychotherapies are effective for reducing PTSD symptoms, but approximately two-thirds of veterans continue to meet diagnostic criteria for PTSD after treatment, suggesting there is an incomplete understanding of what factors sustain PTSD. The intestine can influence the brain and this study evaluated intestinal readouts in subjects with PTSD. Serum samples from controls without PTSD (n = 40) from the Duke INTRuST Program were compared with serum samples from veterans with PTSD (n = 40) recruited from the Road Home Program at Rush University Medical Center. Assessments included microbial metabolites, intestinal barrier, and intestinal epithelial cell function. In addition, intestinal readouts were assessed in subjects with PTSD before and after a 3-wk CPT-based intensive treatment program (ITP) to understand if treatment impacts the intestine. Compared with controls, veterans with PTSD had a proinflammatory intestinal environment including lower levels of microbiota-derived metabolites, such as acetic, lactic, and succinic acid, intestinal barrier dysfunction [lipopolysaccharide (LPS) and LPS-binding protein], an increase in HMGB1, and a concurrent increase in the number of intestinal epithelial cell-derived extracellular vesicles. The ITP improved PTSD symptoms but no changes in intestinal outcomes were noted. This study confirms the intestine is abnormal in subjects with PTSD and suggests that effective treatment of PTSD does not alter intestinal readouts. Targeting beneficial changes in the intestine may be an approach to enhance existing PTSD treatments.NEW & NOTEWORTHY This study confirms an abnormal intestinal environment is present in subjects with PTSD. This study adds to what is already known by examining the intestinal barrier and evaluating the relationship between intestinal readouts and PTSD symptoms and is the first to report the impact of PTSD treatment (which improves symptoms) on intestinal readouts. This study suggests that targeting the intestine as an adjunct approach could improve the treatment of PTSD.

The opioid use disorder core outcomes set (OUD-COS) for treatment research: findings from a Delphi consensus study.

BACKGROUND AND AIM: There is no gold-standard and considerable heterogeneity in outcome measures used to evaluate treatments for opioid use disorder (OUD) along the opioid treatment cascade. The aim of this study was to develop the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network (CTN) opioid use disorder core outcomes set (OUD-COS). DESIGN: Four-round, e-Delphi expert panel consensus study and plenary research group discussion and targeted consultation. SETTING: United States. PARTICIPANTS: A panel of 25 members including clinical practitioners, clinical researchers and administrative staff from the CTN, the network's affiliated clinical and community sites and the NIDA Centre for the CTN. MEASUREMENTS: From a pool of 24 candidate items in four domains (biomedical/disease status; behaviors, symptoms and functioning; opioid treatment cascade; and morbidity and mortality), the panel completed an on-line questionnaire to rank items with defined specification on a 9-point scale for importance, with a standard 70% consensus criterion. FINDINGS: After the fourth round of the questionnaire and subsequent discussion, consensus was reached for five outcomes: two patient-reported (global impression of improvement and incident non-fatal overdose); one clinician-reported (illicit/non-medical drug toxicology); and two from administrative records (duration of treatment and fatal opioid poisoning). CONCLUSIONS: An e-Delphi consensus study has produced the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network opioid use disorder core outcomes set (version 1) for opioid use disorder treatment efficacy and effectiveness research.

Expanding Access to Medications for Opioid Use Disorder Treatment Through Incentivized Continuing Education.

INTRODUCTION: Buprenorphine treatment for opioid use disorder (OUD) has positive outcomes including reducing opioid-related morbidity and mortality. In March 2018, 58 of 102 counties in Illinois lacked access to medication for OUD. METHODS: Rush University created a fellowship training program with financial incentives to help expand buprenorphine treatment in Illinois. Fellows first completed an online waiver course, then attended an in-person intensive training weekend, and finally participated in a 9-month webinar series. Demographic and prescribing data were collected from fellows, as well as a comparison group of providers outside the fellowship who only completed a waiver training. RESULTS: At the fellowship's end, 31 of 37 fellows (84%) reported they were actively prescribing buprenorphine. Of the 23 fellows who were not prescribing at the fellowship's beginning, 17 (74%) initiated prescribing by the end. Among the 16 nonfellowship subjects who only completed a waiver training, just two (13%) reported they were prescribing buprenorphine at the study period's end. DISCUSSION: Our study indicates that providers need more training beyond the waiver to initiate buprenorphine prescribing. When resources are available to address a health crisis such as OUD, this model offers an innovative mechanism for delivering continuing medical education that produces outcomes quickly.

External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients.

BACKGROUND AND AIMS: Unhealthy alcohol use (UAU) is one of the leading causes of global morbidity. A machine learning approach to alcohol screening could accelerate best practices when integrated into electronic health record (EHR) systems. This study aimed to validate externally a natural language processing (NLP) classifier developed at an independent medical center. DESIGN: Retrospective cohort study. SETTING: The site for validation was a midwestern United States tertiary-care, urban medical center that has an inpatient structured universal screening model for unhealthy substance use and an active addiction consult service. PARTICIPANTS/CASES: Unplanned admissions of adult patients between October 23, 2017 and December 31, 2019, with EHR documentation of manual alcohol screening were included in the cohort (n = 57 605). MEASUREMENTS: The Alcohol Use Disorders Identification Test (AUDIT) served as the reference standard. AUDIT scores ≥5 for females and ≥8 for males served as cases for UAU. To examine error in manual screening or under-reporting, a post hoc error analysis was conducted, reviewing discordance between the NLP classifier and AUDIT-derived reference. All clinical notes excluding the manual screening and AUDIT documentation from the EHR were included in the NLP analysis. FINDINGS: Using clinical notes from the first 24 hours of each encounter, the NLP classifier demonstrated an area under the receiver operating characteristic curve (AUCROC) and precision-recall area under the curve (PRAUC) of 0.91 (95% CI = 0.89-0.92) and 0.56 (95% CI = 0.53-0.60), respectively. At the optimal cut point of 0.5, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.66 (95% CI = 0.62-0.69), 0.98 (95% CI = 0.98-0.98), 0.35 (95% CI = 0.33-0.38), and 1.0 (95% CI = 1.0-1.0), respectively. CONCLUSIONS: External validation of a publicly available alcohol misuse classifier demonstrates adequate sensitivity and specificity for routine clinical use as an automated screening tool for identifying at-risk patients.

Investigating Unhealthy Alcohol Use As an Independent Risk Factor for Increased COVID-19 Disease Severity: Observational Cross-sectional Study.

BACKGROUND: Unhealthy alcohol use (UAU) is known to disrupt pulmonary immune mechanisms and increase the risk of acute respiratory distress syndrome in patients with pneumonia; however, little is known about the effects of UAU on outcomes in patients with COVID-19 pneumonia. To our knowledge, this is the first observational cross-sectional study that aims to understand the effect of UAU on the severity of COVID-19. OBJECTIVE: We aim to determine if UAU is associated with more severe clinical presentation and worse health outcomes related to COVID-19 and if socioeconomic status, smoking, age, BMI, race/ethnicity, and pattern of alcohol use modify the risk. METHODS: In this observational cross-sectional study that took place between January 1, 2020, and December 31, 2020, we ran a digital machine learning classifier on the electronic health record of patients who tested positive for SARS-CoV-2 via nasopharyngeal swab or had two COVID-19 International Classification of Disease, 10th Revision (ICD-10) codes to identify patients with UAU. After controlling for age, sex, ethnicity, BMI, smoking status, insurance status, and presence of ICD-10 codes for cancer, cardiovascular disease, and diabetes, we then performed a multivariable regression to examine the relationship between UAU and COVID-19 severity as measured by hospital care level (ie, emergency department admission, emergency department admission with ventilator, or death). We used a predefined cutoff with optimal sensitivity and specificity on the digital classifier to compare disease severity in patients with and without UAU. Models were adjusted for age, sex, race/ethnicity, BMI, smoking status, and insurance status. RESULTS: Each incremental increase in the predicted probability from the digital alcohol classifier was associated with a greater odds risk for more severe COVID-19 disease (odds ratio 1.15, 95% CI 1.10-1.20). We found that patients in the unhealthy alcohol group had a greater odds risk to develop more severe disease (odds ratio 1.89, 95% CI 1.17-3.06), suggesting that UAU was associated with an 89% increase in the odds of being in a higher severity category. CONCLUSIONS: In patients infected with SARS-CoV-2, UAU is an independent risk factor associated with greater disease severity and/or death.

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups.

OBJECTIVES: To assess fairness and bias of a previously validated machine learning opioid misuse classifier. MATERIALS & METHODS: Two experiments were conducted with the classifier's original (n = 1000) and external validation (n = 53 974) datasets from 2 health systems. Bias was assessed via testing for differences in type II error rates across racial/ethnic subgroups (Black, Hispanic/Latinx, White, Other) using bootstrapped 95% confidence intervals. A local surrogate model was estimated to interpret the classifier's predictions by race and averaged globally from the datasets. Subgroup analyses and post-hoc recalibrations were conducted to attempt to mitigate biased metrics. RESULTS: We identified bias in the false negative rate (FNR = 0.32) of the Black subgroup compared to the FNR (0.17) of the White subgroup. Top features included "heroin" and "substance abuse" across subgroups. Post-hoc recalibrations eliminated bias in FNR with minimal changes in other subgroup error metrics. The Black FNR subgroup had higher risk scores for readmission and mortality than the White FNR subgroup, and a higher mortality risk score than the Black true positive subgroup (P < .05). DISCUSSION: The Black FNR subgroup had the greatest severity of disease and risk for poor outcomes. Similar features were present between subgroups for predicting opioid misuse, but inequities were present. Post-hoc mitigation techniques mitigated bias in type II error rate without creating substantial type I error rates. From model design through deployment, bias and data disadvantages should be systematically addressed. CONCLUSION: Standardized, transparent bias assessments are needed to improve trustworthiness in clinical machine learning models.

External validation of an opioid misuse machine learning classifier in hospitalized adult patients.

BACKGROUND: Opioid misuse screening in hospitals is resource-intensive and rarely done. Many hospitalized patients are never offered opioid treatment. An automated approach leveraging routinely captured electronic health record (EHR) data may be easier for hospitals to institute. We previously derived and internally validated an opioid classifier in a separate hospital setting. The aim is to externally validate our previously published and open-source machine-learning classifier at a different hospital for identifying cases of opioid misuse. METHODS: An observational cohort of 56,227 adult hospitalizations was examined between October 2017 and December 2019 during a hospital-wide substance use screening program with manual screening. Manually completed Drug Abuse Screening Test served as the reference standard to validate a convolutional neural network (CNN) classifier with coded word embedding features from the clinical notes of the EHR. The opioid classifier utilized all notes in the EHR and sensitivity analysis was also performed on the first 24 h of notes. Calibration was performed to account for the lower prevalence than in the original cohort. RESULTS: Manual screening for substance misuse was completed in 67.8% (n = 56,227) with 1.1% (n = 628) identified with opioid misuse. The data for external validation included 2,482,900 notes with 67,969 unique clinical concept features. The opioid classifier had an AUC of 0.99 (95% CI 0.99-0.99) across the encounter and 0.98 (95% CI 0.98-0.99) using only the first 24 h of notes. In the calibrated classifier, the sensitivity and positive predictive value were 0.81 (95% CI 0.77-0.84) and 0.72 (95% CI 0.68-0.75). For the first 24 h, they were 0.75 (95% CI 0.71-0.78) and 0.61 (95% CI 0.57-0.64). CONCLUSIONS: Our opioid misuse classifier had good discrimination during external validation. Our model may provide a comprehensive and automated approach to opioid misuse identification that augments current workflows and overcomes manual screening barriers.

The impact of aversive context on early threat detection in trauma exposed individuals and associations with post-traumatic stress symptoms.

Introduction: Prolonged attentional bias to threat (AB) is associated with posttraumatic stress symptoms (PTSS). However, it is unclear whether this relationship extends to early threat detection (elicited by masked stimuli) and/or varies if AB is measured during an aversive context. Methods: Two trauma-exposed samples of either intervention-seekers (N = 50) or community members (N = 98) completed a masked dot-probe task to measure early AB to angry faces in safe vs. aversive contexts (i.e., during threat of aversive noises). Results: Linear mixed effects models showed that an aversive context increased the orienting responses in both samples; however, PTSS did not moderate these effects in either sample. Limitations: Sample size and heterogeneity of trauma-type may have impacted effect of PTSS on AB. Conclusion: These results highlight the importance of assessing AB in varying contexts and examining generalizability across populations. Given prior research, the results also suggest that increased AB in PTSS may only be present for later attentional processes rather than early threat detection, at least with behavioral methods.

Maintenance of treatment gains up to 12-months following a three-week cognitive processing therapy-based intensive PTSD treatment programme for veterans.

BACKGROUND: Intensive treatment programmes (ITPs) have shown promise for reducing PTSD and depression symptoms. It is still unknown whether treatment gains are maintained following completion. OBJECTIVE: This study examined whether veterans were able to maintain treatment gains for up to 12 months after an ITP for PTSD and whether reductions in negative posttrauma cognitions predicted treatment gain maintenance. METHODS: 209 veterans (62.7% male, mean age = 40.86 years) completed a 3-week, CPT-based ITP for PTSD. Participants' PTSD (PCL-5) and depression (PHQ-9) symptoms were assessed at pre-treatment, post-treatment, and at 3-, 6-, and 12-month follow-up timepoints. RESULTS: Despite small symptom increases from post-treatment to 3-month follow-up, significant and clinically meaningful reductions in PTSD and depression symptoms were reported from intake to 12 months follow-up (averaging >18 points on the PCL-5 and >6 points on the PHQ-9; d = 1.28, and d = 1.18, respectively). Greater reductions in negative posttrauma cognitions during treatment were associated with lower PTSD (p <.001) and depression (p =.005) severity at follow-up. Most veterans who completed the aftercare survey followed treatment recommendations and reported seeing a mental health provider at 3-, 6-, and 12-months post-treatment. Aftercare treatment did not significantly predict whether veterans maintained treatment gains at follow-up. CONCLUSIONS: Overall maintenance of treatment gains long-term suggests veterans may be able to apply skills acquired during the ITP following treatment. These findings further support the feasibility and effectiveness of intensive, trauma-focused, evidence-based therapy delivery.

Antecedentes: Los programas de tratamiento intensivos (ITPs por sus siglas en inglés) han mostrado ser promisorios para reducir el TEPT y los síntomas depresivos. Se desconoce aún si las ganancias del tratamiento se mantienen después de la finalización. Este estudio examinó si los veteranos fueron capaces de mantener las ganancias del tratamiento después de 12 meses de un ITP para TEPT y si las reducciones de las cogniciones negativas postrauma predijeron la mantención de las ganancias del tratamiento.Método: 209 veteranos (62,7% varones, edad media=40,86 años) completaron una ITP de 3 semana basado en CPT. Los síntomas de TEPT (PCL-5) y depresión (PHQ-9) de los participantes se evaluaron pre-tratamiento,post tratamiento y a los 3,6 y 12 meses de seguimiento.Resultados: A pesar de un pequeño aumento de los síntomas a los tres meses de seguimiento después de terminado el tratamiento, se reportaron reducciones clínicamente significativas e importantes en el TEPT y síntomas depresivos desde el inicio hasta los 12 meses de seguimiento (un promedio ˃18 puntos en el PCL-5 y ˃6 puntos en el PHQ-9; d=1.28, y d=1.18, respectivamente. Las mayores reducciones en las cogniciones negativas postrauma durante el tratamiento se asociaron con una menor severidad del TEPT (p˂ .001) y depresión (p=.005) en el seguimiento. La mayoría de los veteranos que completaron la encuesta de cuidados posteriores siguieron las recomendaciones del tratamiento e informaron haber visto a algún profesional de salud mental a los 3, 6 y 12 meses post-tratamiento. Los cuidados posteriores al tratamiento no predijeron significativamente si los veteranos mantenían las ganancias del tratamiento en el seguimiento.Conclusiones: el mantenimiento general de las ganancias del tratamiento a largo plazo sugiere que los veteranos pueden aplicar las habilidades adquiridas durante la PTI después del tratamiento.Estos hallazgos respaldan aún más la viabilidad y efectividad de la administración en forma intensiva de una terapia basada en la evidencia y centrada en el trauma.

The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records.

Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

Examining Insomnia During Intensive Treatment for Veterans with Posttraumatic Stress Disorder: Does it Improve and Does it Predict Treatment Outcomes?

Previous research has demonstrated that sleep disturbances show little improvement with evidence-based psychotherapy for posttraumatic stress disorder (PTSD); however, sleep improvements are associated with PTSD treatment outcomes. The goal of the current study was to evaluate changes in self-reported insomnia symptoms and the association between insomnia symptoms and treatment outcome during a 3-week intensive treatment program (ITP) for veterans with PTSD that integrated cognitive processing therapy (CPT), mindfulness, yoga, and other ancillary services. As part of standard clinical procedures, veterans (N = 165) completed self-report assessments of insomnia symptoms at pre- and posttreatment as well as self-report assessments of PTSD and depression symptoms approximately every other day during treatment. Most veterans reported at least moderate difficulties with insomnia at both pretreatment (83.0%-95.1%) and posttreatment (69.1-71.3%). Statistically significant reductions in self-reported insomnia severity occurred from pretreatment to posttreatment; however, the effect size was small, d = 0.33. Longitudinal mixed-effects models showed a significant interactive effect of Changes in Insomnia × Time in predicting PTSD and depression symptoms, indicating that patients with more improvements in insomnia had more positive treatment outcomes. These findings suggest that many veterans continued to struggle with sleep disruption after a 3-week ITP, and successful efforts to improve sleep could lead to better PTSD treatment outcomes. Further research is needed to establish how adjunctive sleep interventions can be used to maximize both sleep and PTSD outcomes.

Feasibility of a 3-week intensive treatment program for service members and veterans with PTSD.

OBJECTIVE: The purpose of the present study was to detail the patient flow and establish the feasibility of a brief 3-week intensive treatment program (ITP) for veterans with posttraumatic stress disorder (PTSD). METHOD: The present study examined data from 648 veterans referred to a non-Veterans Affairs ITP for PTSD from January 2016 to February 2018 to determine the flow of patients into and through the ITP and evaluate individuals' satisfaction with treatment. RESULTS: On average, 25.9 individuals contacted the ITP each month expressing interest in the program. A large proportion of individuals who completed an intake evaluation were accepted (72.2%) into the ITP. Of those accepted, 70.6% ultimately attended the ITP, and the vast majority of veterans who attended the ITP completed treatment (91.6%). Logistic regression results suggested that among veterans who were accepted to the program, those who were legally separated or divorced had significantly greater odds of attending the program compared to single veterans. Veterans were highly satisfied with the 3-week ITP and rated cognitive processing therapy components as the most helpful part of the program. CONCLUSIONS: The present study demonstrates that ITP formats for PTSD are of interest and acceptable to veterans, and this format allows individuals to receive high doses of evidence-based treatments in a short amount of time. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Evaluating patterns and predictors of symptom change during a three-week intensive outpatient treatment for veterans with PTSD.

BACKGROUND: Intensive delivery of evidence-based treatment for posttraumatic stress disorder (PTSD) is becoming increasingly popular for overcoming barriers to treatment for veterans. Understanding how and for whom these intensive treatments work is critical for optimizing their dissemination. The goals of the current study were to evaluate patterns of PTSD and depression symptom change over the course of a 3-week cohort-based intensive outpatient program (IOP) for veterans with PTSD, examine changes in posttraumatic cognitions as a predictor of treatment response, and determine whether patterns of treatment outcome or predictors of treatment outcome differed by sex and cohort type (combat versus military sexual trauma [MST]). METHOD: One-hundred ninety-one veterans (19 cohorts: 12 combat-PTSD cohorts, 7 MST-PTSD cohorts) completed a 3-week intensive outpatient program for PTSD comprised of daily group and individual Cognitive Processing Therapy (CPT), mindfulness, yoga, and psychoeducation. Measures of PTSD symptoms, depression symptoms, and posttraumatic cognitions were collected before the intervention, after the intervention, and approximately every other day during the intervention. RESULTS: Pre-post analyses for completers (N = 176; 92.1% of sample) revealed large reductions in PTSD (d = 1.12 for past month symptoms and d = 1.40 for past week symptoms) and depression symptoms (d = 1.04 for past 2 weeks). Combat cohorts saw a greater reduction in PTSD symptoms over time relative to MST cohorts. Reduction in posttraumatic cognitions over time significantly predicted decreases in PTSD and depression symptom scores, which remained robust to adjustment for autocorrelation. CONCLUSION: Intensive treatment programs are a promising approach for delivering evidence-based interventions to produce rapid treatment response and high rates of retention. Reductions in posttraumatic cognitions appear to be an important predictor of response to intensive treatment. Further research is needed to explore differences in intensive treatment response for veterans with combat exposure versus MST.

Characteristics of veterans and military service members who endorse causing harm, injury, or death to others in the military.

OBJECTIVE: The purpose of the present research was to examine the demographic and mental health characteristics of veterans and service members who endorsed having caused harm, injury, or death to another person on deployment, while taking these individuals' total number of other lifetime traumas into account. METHOD: Data for the present study were collected as part of the standard clinical evaluation for 228 treatment-seeking veterans and service members. RESULTS: Those who reported having caused harm, injury, or death to another person on deployment (22.4%) were more likely to be male, to have served in the Marines, to have served post 9/11, and to endorse other traumas commonly reported on deployment than those who did not endorse causing harm, injury, or death. Those who endorsed causing harm on deployment were less likely to have served in the Air Force, and to have experienced sexual assault than those who did not cause harm. Causing harm, injury, or death was associated with higher levels of posttraumatic stress disorder (PTSD), drug use, and expressive anger at the bivariate level, but was no longer associated with mental health problems after accounting for the number of other lifetime traumas. CONCLUSIONS: Examining the role of causing harm in isolation may lead to false conclusions. Clinicians and researchers should assess for veterans' and service members' entire trauma histories. (PsycINFO Database Record

Exploring the potential of technology-based mental health services for homeless youth: A qualitative study.

Homelessness has serious consequences for youth that heighten the need for mental health services; however, these individuals face significant barriers to access. New models of intervention delivery are required to improve the dissemination of mental health interventions that tailor these services to the unique challenges faced by homeless youth. The purpose of this study was to better understand homeless youths' use of technology, mental health experiences and needs, and willingness to engage with technology-supported mental health interventions to help guide the development of future youth-facing technology-supported interventions. Five focus groups were conducted with 24 homeless youth (62.5% female) in an urban shelter. Youth were 18- to 20-years-old with current periods of homelessness ranging from 6 days to 4 years. Transcripts of these focus groups were coded to identify themes. Homeless youth reported using mobile phones frequently for communication, music, and social media. They indicated a lack of trust and a history of poor relationships with mental health providers despite recognizing the need for general support as well as help for specific mental health problems. Although initial feelings toward technology that share information with a provider were mixed, they reported an acceptance of tracking and sharing information under certain circumstances. Based on these results, we provide recommendations for the development of mental health interventions for this population focusing on technology-based treatment options. (PsycINFO Database Record

Ethical challenges in developing drugs for psychiatric disorders.

As the classification of mental disorders advances towards a disease model as promoted by the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC), there is hope that a more thorough neurobiological understanding of mental illness may allow clinicians and researchers to determine treatment efficacy with less diagnostic variability. This paradigm shift has presented a variety of ethical issues to be considered in the development of psychiatric drugs. These challenges are not limited to informed consent practices, industry funding, and placebo use. The consideration for alternative research models and quality of research design also present ethical challenges in the development of psychiatric drugs. The imperatives to create valid and sound research that justify the human time, cost, risk and use of limited resources must also be considered. Clinical innovation, and consideration for special populations are also important aspects to take into account. Based on the breadth of these ethical concerns, it is particularly important that scientific questions regarding the development of psychiatric drugs be answered collaboratively by a variety of stakeholders. As the field expands, new ethical considerations will be raised with increased focus on genetic markers, personalized medicine, patient-centered outcomes research, and tension over funding. We suggest that innovation in trial design is necessary to better reflect practices in clinical settings and that there must be an emphasized focus on expanding the transparency of consent processes, regard for suicidality, and care in working with special populations to support the goal of developing sound psychiatric drug therapies.

A Pilot Study of Tailored Cognitive-Behavioral Resilience Training for Trauma Survivors With Subthreshold Distress.

This pilot study evaluated the feasibility, acceptability, and preliminary effectiveness of tailored cognitive-behavioral resilience training (TCBRT) for trauma-exposed individuals with a variety of subsyndromal psychological symptoms. TCBRT is a brief, flexible intervention that allows individuals to select the areas they wish to target using common cognitive-behavioral change principles. There were 14 individuals (78.6% female) who were recruited from a major medical center and enrolled in the 5-session intervention. There were 12 (85.7%) who completed all TCBRT sessions, and 2 (14.3%) who dropped out after 3 sessions. All participants reported that they received benefit from, were engaged in, and were satisfied with the intervention. Of the 12 with postintervention data, 5 of the participants demonstrated reliable increases in resilience and 6 demonstrated reliable decreases in anxiety. These improvements appeared to be maintained at 2-month follow-up; of the 11 participants with follow-up data, 5 demonstrated reliable increases in resilience and 6 demonstrated reliable decreases in anxiety. Our findings suggested that TCRBT was acceptable to trauma-exposed individuals with varying types of subthreshold distress.