Veterans' 12-month PTSD and depression outcomes following 2- and 3-week intensive cognitive processing therapy-based treatment.

Background: Growing evidence indicates that daily delivery of evidence-based PTSD treatments (e.g. Cognitive Processing Therapy (CPT)), as part of intensive PTSD treatment programmes (ITPs), is feasible and effective. Research has demonstrated that a 2-week CPT-based ITP can produce equivalent outcomes to a 3-week ITP, suggesting shorter treatment can also be highly effective. However, the extent to which ITP length and composition impact longer-term outcomes needs further study.Objective: We examined whether PTSD and depression symptoms 3-, 6-, and 12-months following completion of a 2-week ITP could be considered non-inferior, or equivalent, to those of a 3-week ITP.Method: Data from 638 veterans who participated in a 2-week CPT-based ITP were evaluated against 496 veterans who participated in a 3-week CPT-based ITP. A Bayes factor approach was used to examine whether PTSD and depression severity outcomes of the 2-week ITP could be considered equivalent to the 3-week ITP.Results: Participants across both ITPs reported large PTSD (d = 0.98) and moderate to large depression symptom reductions (d = 0.69) from baseline to 12-month follow-up. The PTSD and depression symptom reductions seen in the 2-week ITP were determined to be equivalent to those of the 3-week ITP.Conclusions: Low follow-up completion was a limitation. Future research might replicate the present findings using samples with greater follow-up rates and explore whether adjunctive services impact other relevant constructs, such as quality of life and functioning.

This study demonstrated that intensive PTSD treatment programmes for veterans can produce large and lasting PTSD and depression symptoms reductions.A 2-week intensive PTSD treatment programme that offered 37 fewer clinical hours was just as effective as a 3-week programme for veterans, with lasting symptom improvement up to 12 months after treatment.The 2-week programme focused primarily on individual Cognitive Processing Therapy delivered twice per day whereas the 3-week programme combined individual and group CPT and had a much larger number of adjunctive services.

A latent profile analysis of moral emotions following moral transgressions.

OBJECTIVE: Moral transgressions (MTs), events that violate one's moral code, are associated with the moral emotions of guilt and shame. However, there may be different patterns by which people experience guilt and shame that affect distress following MTs. METHOD: Undergraduates (N = 1371) exposed to an MT completed self-report assessments. This study used latent profile analysis (LPA) to examine profiles based on guilt cognitions, internalized shame, and distress in relation to a reported MT. Cognitive flexibility, years since the MT, and deliberate and intrusive rumination were examined as variables to determine how these factors predicted profile membership. RESULTS: Results from the LPA revealed a three-profile solution: a low moral distress profile (n = 1002), a moderate moral distress profile (n = 262), and a shame prominent profile (n = 107). Results indicated that higher levels of deliberate and intrusive rumination and lower levels of cognitive flexibility significantly increased the likelihood of belonging to the moderate moral distress or shame prominent profiles compared to the low moral distress profile. Higher levels of intrusive rumination and lower levels of cognitive flexibility also significantly increased the likelihood of belonging to the shame prominent profile over the moderate distress profile. CONCLUSION: Three different profiles emerged, with the shame prominent profile being driven primarily by internalized shame. Results suggest that intrusive rumination and cognitive inflexibility are risk factors to experiencing adverse responses to MTs.

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.

Posttraumatic cognition change trajectories in veterans with PTSD who completed an intensive Cognitive Processing Therapy treatment program.

Negative posttraumatic cognitions (NPCs) have been linked to symptoms of PTSD and are an important target of cognitive behavioral treatments for PTSD, including Cognitive Processing Therapy (CPT). Yet to be explored are the different change trajectories of NPCs during CPT. Knowledge of such change trajectories could elucidate common NPC change processes within CPT and their relationship to PTSD symptom severity. We examined NPC change trajectories in a group of 443 veterans who completed a 2-week intensive CPT program. We identified four NPC trajectory groups termed start high end high, start high end moderate, start moderate end low, and start low end low. Most of the groups showed an increase in NPCs at the midpoint of treatment before ultimately decreasing. As predicted, baseline PTSD symptom severity predicted change trajectory group membership. Also, NPC change trajectories were associated with PTSD severity at the end of treatment such that individuals in smaller NPC change groups had higher PTSD symptoms at the end of treatment, and vice versa. Clinicians can use this knowledge to make predictions of a particular client's NPC change trajectory and set expectations for what progress in treatment may look like, including normalizing increases in NPCs from the start of treatment.

Treating a common comorbidity: Pain outcomes following a 3-week cognitive processing therapy-based intensive treatment for posttraumatic stress disorder address.

Posttraumatic stress disorder (PTSD) commonly co-occurs with pain and has been implicated in the maintenance of chronic pain. However, limited research has examined whether intervening for PTSD can hinder or optimize treatment outcomes for co-occurring pain and PTSD. In the present study, we examined changes in pain, PTSD, and depressive symptoms among 125 veterans completing a 3-week cognitive processing therapy (CPT)-based intensive treatment program (ITP) for PTSD. We also explored whether pretreatment pain interference predicted changes in PTSD and depressive symptom severity and whether larger changes in pain interference over the course of treatment were associated with larger changes in PTSD and depressive symptom severity. Linear mixed models revealed that participants' pain interference decreased throughout treatment, d = 0.15, p = .039. Higher levels of pretreatment pain interference were associated with higher PTSD, p = .001, and depressive symptom severity, p = .014, over time. Larger reductions in pain interference corresponded to more improvement in PTSD symptoms, ß = -.03; p < .001, but not depressive symptoms. These findings indicate that ITPs for PTSD can reduce pain interferences, albeit to a small degree, and that reductions in pain interference can contribute to reductions in PTSD symptom severity. Future studies should examine which treatment components contribute to larger changes in symptom severity for veterans with co-occurring pain and PTSD.

Predicting suicidal ideation 3 months following intensive posttraumatic stress disorder treatment.

OBJECTIVE: This study examined whether posttraumatic stress disorder (PTSD) symptom change during a 3- and 2-week intensive treatment program (ITP)-based in cognitive processing therapy was predictive of reduced suicidal ideation (SI) following treatment. METHOD: Veterans completed either a 3-week (n = 274, Mage = 42.35, SD = 9.43, 64.23% male, 65.33% White) or 2-week (n = 177, Mage = 42.90, SD = 9.81, 57.63% male, 66.67% White) ITP and self-reported PTSD, depression, and SI symptoms prior to, during, and 3 months following treatment. RESULTS: Mixed-effects-based two-stage location scale models assessed change in both overall PTSD severity over the course of the 3- and 2-week ITPs, as well as how this change predicted 3-month follow-up SI. Veterans in both programs reported moderate reductions in SI from baseline to posttreatment (3 weeks: d = 0.49; 2 weeks: d = 0.48). Of the 210 veterans across both programs who endorsed at least some SI at baseline, two-thirds (65.24%) reported reductions in SI posttreatment; three-quarters (74.45%) of these maintained posttreatment SI at 3-month follow-up that was lower than baseline levels. CONCLUSIONS: Both baseline SI and greater individual improvement in PTSD symptom severity during the ITPs were associated with lower SI at 3-month follow-up. Overall, study findings suggest that veterans with PTSD who also endorse SI can be successfully treated using the intensive delivery format and are likely to experience a reduction in SI both during and following treatment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Using the Personalized Advantage Index to determine which veterans may benefit from more vs. less comprehensive intensive PTSD treatment programs.

Background: Intensive PTSD treatment programs (ITPs) are highly effective but tend to differ greatly in length and the number of adjunctive services that are provided in conjunction with evidence-based PTSD treatments. Individuals' treatment response to more or less comprehensive ITPs is poorly understood.Objective: To apply a machine learning-based decision-making model (the Personalized Advantage Index (PAI)), using clinical and demographic factors to predict response to more or less comprehensive ITPs.Methods: The PAI was developed and tested on a sample of 747 veterans with PTSD who completed a 3-week (more comprehensive; n = 360) or 2-week (less comprehensive; n = 387) ITP.Results: Approximately 12.32% of the sample had a PAI value that suggests that individuals would have experienced greater PTSD symptom change (5 points) on the PTSD Checklist for DSM-5 in either a more- or less comprehensive ITP. For individuals with the highest 25% of PAI values, effect sizes for the amount of PTSD symptom change between those in their optimal vs. non-optimal programs was d = 0.35.Conclusions: Although a minority was predicted to have benefited more from a program, there generally was not a substantial difference in predicted outcomes. Less comprehensive and thus more financially sustainable ITPs appear to work well for most individuals with PTSD.

A Personalized Advantage Index (PAI) was developed for a 3-week (more comprehensive) and a 2-week (less comprehensive) intensive PTSD treatment program to predict treatment responses.Using the PAI, approximately 12% of the sample was predicted to have experienced meaningfully greater in another program than the one in which they participated.Findings suggest a less comprehensive and more financially sustainable 2-week intensive PTSD treatment program would work well for most veterans in the present study.

Report From a Multidisciplinary Symposium on the Future of Living Kidney Donor Transplantation.

Virtually all clinicians agree that living donor renal transplantation is the optimal treatment for permanent loss of kidney function. Yet, living donor kidney transplantation has not grown in the United States for more than 2 decades. A virtual symposium gathered experts to examine this shortcoming and to stimulate and clarify issues salient to improving living donation. The ethical principles of rewarding kidney donors and the limits of altruism as the exclusive compelling stimulus for donation were emphasized. Concepts that donor incentives could save up to 40 000 lives annually and considerable taxpayer dollars were examined, and survey data confirmed voter support for donor compensation. Objections to rewarding donors were also presented. Living donor kidney exchanges and limited numbers of deceased donor kidneys were reviewed. Discussants found consensus that attempts to increase living donation should include removing artificial barriers in donor evaluation, expansion of living donor chains, affirming the safety of live kidney donation, and assurance that donors incur no expense. If the current legal and practice standards persist, living kidney donation will fail to achieve its true potential to save lives.

Using machine learning to predict sudden gains in intensive treatment for PTSD.

Sudden gains have been found in PTSD treatment across samples and treatment modality. Sudden gains have consistently predicted better treatment response, illustrating clear clinical implications, though attempts to identify predictors of sudden gains have produced inconsistent findings. To date, sudden gains have not been examined in intensive PTSD treatment programs (ITPs). This study explored the occurrence of sudden gains in a 3-week and 2-week ITP (n = 465 and n = 235), evaluated the effect of sudden gains on post-treatment and follow-up PTSD severity while controlling for overall change, and used three machine learning algorithms to assess our ability to predict sudden gains. We found 31% and 19% of our respective samples experienced a sudden gain during the ITP. In both ITPs, sudden gain status predicted greater PTSD symptom improvement at post-treatment (t2 W=-8.57, t3 W=-14.86, p < .001) and at 3-month follow-up (t2 W=-3.82, t3 W=-5.32, p < .001). However, the effect for follow-up was no longer significant after controlling for total symptom reduction across the ITP (t2 W=-1.59, t3 W=-0.32, p > .05). Our ability to predict sudden gains was poor (AUC <.7) across all three machine learning algorithms. These findings demonstrate that sudden gains can be detected in intensive treatment for PTSD, though their implications for treatment outcomes may be limited. Moreover, despite the use of three machine-learning methods across two fairly large clinical samples, we were still unable to identify variables that accurately predict whether an individual will experience a sudden gain during treatment. Implications for clinical application of these findings and for future studies are discussed.

Examining trauma cognition change trajectories among initial PTSD treatment non-optimal responders: a potential avenue to guide subsequent treatment selection.

BACKGROUND: Despite their general effectiveness, 14-50% of individuals do not fully respond to evidence-based treatments for posttraumatic stress disorder (PTSD). Although changes in negative posttrauma cognitions (NPCs) are considered a likely PTSD treatment mechanism, less is known about how NPCs change among individuals who continue to be symptomatic following treatment (non-optimal responders). OBJECTIVE: The objective of this study was to examine NPC change trajectories among individuals who were determined to be non-optimally responsive to intensive PTSD treatment. METHOD: Using a 3-week Cognitive Processing Therapy-based intensive PTSD treatment sample (ITP; N = 243), the present study examined the number of distinct NPC change trajectories among non-optimal responders via Group Based Trajectory Modeling and assessed predictors of non-optimal responders' NPC change trajectory membership. Analyses were replicated in a separate 2-week ITP sample (N = 215). RESULTS: In both non-optimal responder samples, two trajectories emerged; a no NPC change group which represented those with an overall lack of NPC change throughout treatment and an NPC change group which represented those with an overall reduction of NPCs occurring primarily later in treatment. Changes in PTSD symptom severity during treatment was the only consistent predictor of NPC change trajectory group membership among treatment non-optimal responders across ITPs. CONCLUSIONS: Findings suggest NPC change among non-optimal responders is nuanced and may inform subsequent intervention selection, resulting in testable hypotheses for future research.

Throughout intensive PTSD treatment, non-optimal responders exhibited two distinct negative posttrauma cognition change trajectories: (1) no change, and (2) slow change.Changes in PTSD symptom severity during treatment consistently predicted non-optimal responders' trajectory of change in negative posttrauma cognitions.Additional research is needed to explore how nuances of negative posttrauma cognition change may inform subsequent treatment intervention in initial non-optimal responders.

Demonstration of Hong-Ou-Mandel interference in an LNOI directional coupler.

Interference between single photons is key for many quantum optics experiments and applications in quantum technologies, such as quantum communication or computation. It is advantageous to operate the systems at telecommunication wavelengths and to integrate the setups for these applications in order to improve stability, compactness and scalability. A new promising material platform for integrated quantum optics is lithium niobate on insulator (LNOI). Here, we realise Hong-Ou-Mandel (HOM) interference between telecom photons from an engineered parametric down-conversion source in an LNOI directional coupler. The coupler has been designed and fabricated in house and provides close to perfect balanced beam splitting. We obtain a raw HOM visibility of (93.5 ± 0.7) %, limited mainly by the source performance and in good agreement with off-chip measurements. This lays the foundation for more sophisticated quantum experiments in LNOI.

'Undoing a knot': a qualitative study of massed 1-week Cognitive Processing Therapy.

Introduction: Intensive or massed Cognitive Processing Therapy (CPT) for posttraumatic stress disorder (PTSD) has been found to result in significant PTSD symptom reductions. However, few studies to date have used qualitative approaches to systematically evaluate client reflections about massed treatment approaches for PTSD. To address this gap, the present study aimed to improve our understanding of trauma survivors' reflections following the completion of 1-week CPT.Method: We conducted semi-structured interviews with seven trauma survivors within 3-months of the completion of 1-week CPT. We used the scissor-and-sort technique to identify themes and subthemes in the qualitative data.Results: Using the scissor-and-sort technique, we generated five main themes and associated subthemes from the data. The main themes were: (a) tangible skills, (b) feasibility, (c) therapeutic process, (d) symptom presentation, and (e) treatment expectations.Conclusion: Collectively, our results suggested that 1-week CPT was feasible and led to changes in PTSD symptoms and improved cognitive and affective coping skills.

Scant research has examined client reflections about massed treatment approaches for PTSD.Among participants who completed a semi-structured interview about their experiences with 1-week CPT for PTSD, we generated five themes: (a) tangible skills, (b) feasibility, (c) therapeutic process, (d) symptom presentation, and (e) treatment expectations.Collectively, our results suggested that 1-week CPT was feasible and led to changes in PTSD symptoms and improved cognitive and affective coping skills.

More is not always better: 2 weeks of intensive cognitive processing therapy-based treatment are noninferior to 3 weeks.

OBJECTIVE: Although there is mounting evidence that massed treatment for PTSD is both feasible and effective, many questions remain about the optimal length of intensive treatment programs (ITPs), as well as the role of adjunctive services, such as psychoeducation, mindfulness, and yoga. Our setting recently transitioned from a three-week ITP to a two-week program. Adjunctive services were reduced, but the amount of individual CPT between programs remained similar. The present study examined the effectiveness of a two-week ITP based on twice daily individual CPT sessions and evaluated the program's noninferiority to an established three-week ITP using a Bayesian analytical approach. METHOD: Bayesian linear mixed regression models were used to explore PTSD and depression changes over time, as well as predictors of change. Noninferiority of the two-week ITP to a three-week ITP was also established using a Bayes factor approach. RESULTS: Results indicate that program participants change meaningfully in both PTSD and depression severity over the course of treatment, and that changes in posttraumatic cognitions predict subsequent changes in these outcomes. Further, the two-week ITP can be considered noninferior to the three-week ITP in both clinical outcomes and overall satisfaction. CONCLUSIONS: In the context of intensive PTSD treatment, the content of the ITP appears to matter more than its overall length. Shorter programs have the potential to increase access and treatment capacity. Our findings demonstrate the importance of continuous and rigorous program evaluation. Limitations as well as future directions for research, such as identifying the most effective treatment components, are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Posttraumatic stress disorder and depression residual symptoms among veterans and service members who completed a 3-week cognitive processing therapy-based intensive treatment program.

OBJECTIVE: While previous studies have documented that evidence-based treatments for posttraumatic stress disorder (PTSD) are efficacious, treatment completers often continue to experience residual symptoms. However, no studies to date have assessed residual symptoms following intensive treatment programs (ITPs) for PTSD, which combine evidence-based PTSD treatment along with adjunctive interventions. The present study examined residual symptoms of PTSD and depression in 482 veterans and service members who completed a 3-week Cognitive Processing Therapy-based ITP. METHOD: Residual symptoms were examined at posttreatment and 3 months following ITP completion. Frequency analyses and logistic regressions were conducted to discern the presence of residual symptoms among (a) the total sample and (b) participants who did and did not experience clinically meaningful change in PTSD symptom severity over the course of treatment. RESULTS: Study results indicated that the majority of participants (80%-87%) reported some PTSD and depression residual symptoms at ITP completion, which commonly continued to be endorsed at 3 months following ITP completion. At both treatment completion and 3 months following treatment, participants who experienced clinically meaningful changes during the ITP exhibited statistically lower odds of PTSD and depression residual symptoms as compared to participants who did not experience clinically meaningful changes. However, regardless of whether clinically meaningful changes in PTSD symptoms were experienced, participants most commonly endorsed residual symptoms in the hyperarousal cluster of PTSD and general depression symptoms at high rates. CONCLUSIONS: Findings suggest the need to further examine functional impairment and coping skill use associated with these long-standing residual symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Moving toward precision PTSD treatment: predicting veterans' intensive PTSD treatment response using continuously updating machine learning models.

BACKGROUND: Considerable heterogeneity exists in treatment response to first-line posttraumatic stress disorder (PTSD) treatments, such as Cognitive Processing Therapy (CPT). Relatively little is known about the timing of when during a course of care the treatment response becomes apparent. Novel machine learning methods, especially continuously updating prediction models, have the potential to address these gaps in our understanding of response and optimize PTSD treatment. METHODS: Using data from a 3-week (n = 362) CPT-based intensive PTSD treatment program (ITP), we explored three methods for generating continuously updating prediction models to predict endpoint PTSD severity. These included Mixed Effects Bayesian Additive Regression Trees (MixedBART), Mixed Effects Random Forest (MERF) machine learning models, and Linear Mixed Effects models (LMM). Models used baseline and self-reported PTSD symptom severity data collected every other day during treatment. We then validated our findings by examining model performances in a separate, equally established, 2-week CPT-based ITP (n = 108). RESULTS: Results across approaches were very similar and indicated modest prediction accuracy at baseline (R2 ~ 0.18), with increasing accuracy of predictions of final PTSD severity across program timepoints (e.g. mid-program R2 ~ 0.62). Similar findings were obtained when the models were applied to the 2-week ITP. Neither the MERF nor the MixedBART machine learning approach outperformed LMM prediction, though benefits of each may differ based on the application. CONCLUSIONS: Utilizing continuously updating models in PTSD treatments may be beneficial for clinicians in determining whether an individual is responding, and when this determination can be made.

The role of time since trauma on treatment outcomes of veterans in two intensive posttraumatic stress disorder treatment programs.

Research on the impact of time since trauma (TST) on posttraumatic stress disorder (PTSD) treatment outcomes lacks consensus and has not been examined in cognitive processing therapy (CPT)-based intensive PTSD treatment programs (ITPs). Furthermore, little is known about how TST impacts other trauma-related outcomes, such as depressive symptoms and negative posttrauma cognitions. We examined whether TST predicted severity and changes in PTSD and depressive symptoms and negative posttrauma cognitions, controlling for trauma type (combat or military sexual trauma), age, sex, and race, in two separate samples of veterans with PTSD who completed 2-week (n = 132) or 3-week (n = 407) CPT-based ITPs. In the 3-week sample, PTSD symptom reduction differed based on TST; however, these differences lacked clinical significance, TST x Time R2 b = .002, and were not replicated in the 2-week sample, R2 b < .001. TST did not significantly predict depressive symptoms, R2 b = .005, or negative posttrauma cognition severity or changes, R2 b = .002, in the 3-week sample. In the 2-week sample, linear mixed-effects models indicated that TST also did not significantly predict PTSD or depressive symptoms, R2 b s < .001, or negative posttrauma cognition severity or changes, R2 b s = .002. These findings suggest that TST is not a clinically relevant predictor of PTSD symptoms, depressive symptoms, or negative posttrauma cognitions among individuals engaged in CPT-based ITPs. Future research should investigate the association between TST and trauma-related outcomes in more trauma type- and age-diverse samples within different intensive treatment settings.

Evaluating changes in negative posttrauma cognition as a mechanism of PTSD severity changes in two separate intensive treatment programs for veterans.

BACKGROUND: A wealth of evidence has illustrated that reductions in negative posttrauma cognitions (NPCs) predict improvement in posttraumatic stress disorder (PTSD) symptoms during treatment. Yet, the specific temporal arrangement of changes in these constructs is less well understood. This study examined the temporal association between NPC changes and PTSD symptom changes in two distinct intensive PTSD treatment samples. METHODS: Data from 502 veterans who completed a 3-week CPT-based intensive PTSD treatment program was used to test the extent to which lagged NPC measurement predicted the next occurring PTSD severity measurement using linear mixed effects regression models. PTSD severity was assessed every other day during treatment. NPCs were assessed at three treatment timepoints. A second sample of 229 veterans who completed a 2-week CPT-based intensive PTSD treatment program was used to replicate these findings. RESULTS: Across both intensive PTSD treatment programs, NPCs generally increased from intake the end of the first treatment week, which was followed by gradual decreases in NPCs throughout the rest of both programs. Change in NPCs during both the 3-week (b = .21, p < .001, R2 = .38) and the 2-week programs (b = 0.20, p < .001, R2 = .24) were significant predictors of change in PTSD symptom severity. However, the reverse was true as well, with change in PTSD severity predicting latter change in NPCs during both the 3-week (b = 1.51, p < .001, R2 = .37) and 2-week (b = 1.37, p < .001, R2 = .33) programs, further raising questions about temporality of the association between NPCs and PTSD symptom severity during treatment. CONCLUSIONS: The present study demonstrated that changes in NPCs may not temporally precede changes in PTSD symptom severity in PTSD treatment samples. Instead, we observed earlier PTSD symptom changes and a bidirectional association between the two constructs across both samples. Clinically, the study supports the continued focus on NPCs as an important treatment target as they are an important indicator of successful PTSD treatment, even if they may not be a direct mechanism of treatment-based changes in PTSD severity. Future research should attempt to identify alternative mechanisms of change in CPT.

Changes in guilt cognitions in intensive PTSD treatment among veterans who experienced military sexual trauma or combat trauma.

Unresolved trauma-related guilt has been identified as a factor that can intensify posttraumatic stress disorder PTSD symptomology and is associated with many negative mental health outcomes. Evidence-based treatments, such as Cognitive Processing Therapy (CPT), have been shown to successfully reduce trauma-related guilt. However, less is known about how trauma-related guilt cognitions change over the course of PTSD treatment and, more specifically, intensive PTSD treatments. The current study examined whether guilt cognitions (i.e., hindsight bias/responsibility, insufficient justification, wrongdoing) changed over the course of a 3-week CPT-based intensive treatment program (ITP), whether guilt cognition changes predicted PTSD and depression symptom reductions over time, and whether guilt cognition changes and their association with PTSD and depression symptom changes differed based on whether they worked on combat trauma or military sexual trauma. Data were collected from 360 veterans enrolled in a 3-week ITP. Results from linear mixed effects models suggested that trauma-related guilt cognitions reduced significantly over the course of treatment (ps < .001), changes in wrongdoing (p = .032) and hindsight bias/responsibility (p = .003) were significant predictors of PTSD symptom reductions and hindsight bias/responsibility (p = .032) was the only significant predictor of depression symptom reduction. Overall differences in guilt cognitions over time based on cohort type were only significant for insufficient justification (p = .001). These findings suggest that changes in hindsight bias/responsibility demonstrated the largest effect size (d = 0.1.14), implying that hindsight bias/responsibility may be one of the most important guilt cognitions to target. This study also highlights the importance of the relationship between trauma-related guilt and PTSD and depression symptoms. Future research should examine whether changes in guilt cognitions precede changes in PTSD and depression symptoms, and if addressing certain types of guilt cognitions is more important to achieving PTSD and depression symptom reductions.

Digital Screening and Automated Resource Identification System to Address COVID-19-Related Behavioral Health Disparities: Feasibility Study.

BACKGROUND: Digital mental health (DMH) tools use technology (eg, websites and mobile apps) to conveniently deliver mental health resources to users in real time, reducing access barriers. Underserved communities facing health care provider shortages and limited mental health resources may benefit from DMH tools, as these tools can help improve access to resources. OBJECTIVE: This study described the development and feasibility evaluation of the Emotional Needs Evaluation and Resource Guide for You (ENERGY) System, a DMH tool to meet the mental health and resource needs of youth and their families developed in the context of the COVID-19 pandemic. The ENERGY System offers a brief assessment of resource needs; problem-solving capabilities; and symptoms of depression, anxiety, trauma, and alcohol and substance use followed by automated, personalized feedback based on the participant's responses. METHODS: Individuals aged ≥15 years were recruited through community partners, community events, targeted electronic health record messages, and social media. Participants completed screening questions to establish eligibility, entered demographic information, and completed the ENERGY System assessment. Based on the participant's responses, the ENERGY System immediately delivered digital resources tailored to their identified areas of need (eg, relaxation). A subset of participants also voluntarily completed the following: COVID-19 Exposure and Family Impact Survey (CEFIS) or COVID-19 Exposure and Family Impact Survey Adolescent and Young Adult Version (CEFIS-AYA); resource needs assessment; and feedback on their experience using the ENERGY System. If resource needs (eg, housing and food insecurity) were endorsed, lists of local resources were provided. RESULTS: A total of 212 individuals accessed the ENERGY System link, of which 96 (45.3%) completed the screening tool and 86 (40.6%) received resources. Participant responses on the mental health screening questions triggered on average 2.04 (SD 1.94) intervention domains. Behavioral Activation/Increasing Activities was the most frequently launched intervention domain (56%, 54/96), and domains related to alcohol or substance use were the least frequent (4%, 4/96). The most frequently requested support areas were finances (33%, 32/96), transportation (26%, 25/96), and food (24%, 23/96). The CEFIS and CEFIS-AYA indicated higher than average impacts from the pandemic (ie, average scores >2.5). Participants were satisfied with the ENERGY System overall (65%, 39/60) as well as the length of time it took to answer the questions (90%, 54/60), which they found easy to answer (87%, 52/60). CONCLUSIONS: This study provided initial support for the feasibility of the ENERGY System, a DMH tool capable of screening for resource and mental health needs and providing automated, personalized, and free resources and techniques to meet the identified needs. Future studies should seek direct feedback from community members to further improve the ENERGY System and its dissemination to encourage use.

Projecting the Economic Impact of Compensating Living Kidney Donors in the United States: Cost-Benefit Analysis Demonstrates Substantial Patient and Societal Gains.

OBJECTIVES: The aim of this study was to show how the US government could save approximately 47 000 patients with chronic kidney failure each year from suffering on dialysis and premature death by compensating living kidney donors enough to completely end the kidney shortage. METHODS: Supply and demand analysis was used to estimate the number of donated kidneys needed to end the kidney shortage and the level of compensation required to encourage this number of donations. These results were then input into a detailed cost-benefit analysis to estimate the economic value of kidney transplantation to (1) the average kidney recipient and their caregiver, (2) taxpayers, and (3) society in general. RESULTS: We estimate half of patients diagnosed with kidney failure each year-approximately 62 000 patients-could be saved from suffering on dialysis and premature death if they could receive an average of 1½ kidney transplants. However, currently there are only enough donated kidneys to save approximately 15 000 patients. To encourage sufficient donations to save the other 47 000 patients, the government would have to compensate living kidney donors approximately $77 000 (±50%) per donor. The value of transplantation to an average kidney recipient (and caregiver) would be approximately $1.5 million, and the savings from the recipient not needing expensive dialysis treatments would be approximately $1.2 million. CONCLUSIONS: This analysis reveals the huge benefit that compensating living kidney donors would provide to patients with kidney failure and their caregivers and, conversely, the huge cost that is being imposed on these patients and their families by the current legal prohibition against such compensation.