Does format matter? A naturalistic study of digital and provider-led cognitive behavioral therapy for insomnia implemented in a healthcare system.

OBJECTIVES: Cognitive Behavioral Therapy for Insomnia (CBTi) is a first-line treatment for a prevalent and impairing disorder. Digital CBTi programs increase access to internet-based self-directed care. However, the clinical effect of offering different forms of CBTi in a healthcare setting is not clearly understood. This study examines treatment engagement and clinical outcomes for individuals referred to either digital or provider-led CBTi. METHODS: Over two years, providers at a Veterans Health Administration (VHA) facility referred patients to digital CBTi with telephone coaching support or traditional provider-led CBTi. Characteristics of those referred, proportions engaging in and completing treatment, as well as insomnia severity were compared among those referred to each format. RESULTS: Providers referred 139 individuals to digital CBTi, 340 to provider-led CBTi, and 14 to both formats. Individuals referred to digital CBTi were older with less severe insomnia. Despite lower levels of program engagement and completion in the digital CBTi cohort, measures of insomnia symptom change were similar between the groups. CONCLUSIONS: This is the first study to evaluate both digital and provider-led evidence-based treatments for insomnia disorder simultaneously deployed in a healthcare setting. While engagement in digital CBTi lagged that for provider-led CBTi, offering both formats may expand access to different groups, while fostering similar outcomes.

Implementing a Multi-Disciplinary, Evidence-Based Resilience Intervention for Moral Injury Syndrome: Systemic Barriers and Facilitators.

Moral injury syndrome (MIS) is a mental health (MH) problem that substantially affects resilience; the presence of MIS reduces responsiveness to psychotherapy and increases suicide risk. Evidence-based treatment for MIS is available; however, it often goes untreated. This project uses principles of the Consolidated Framework for Implementation Research (CFIR) to assess barriers and facilitators to the implementation of Building Spiritual Strength (BSS), a multi-disciplinary treatment for MIS. Interviews were conducted with chaplains and mental health providers who had completed BSS facilitator training at six sites in the VA. Data were analyzed using the Hamilton Rapid Turnaround method. Findings included multiple facilitators to the implementation of BSS, including its accessibility and appeal to VA chaplains; leadership by VA chaplains trained in the intervention; and effective collaboration between the chaplains and mental health providers. Barriers to the implementation of BSS included challenges in engaging mental health providers and incorporating them as group leaders, veterans' lack of familiarity with the group format of BSS, and the impact of the COVID-19 pandemic. Results highlight the need for increased trust and collaboration between VA chaplains and mental health providers in the implementation of BSS and treatment of MIS.

GPAW: An open Python package for electronic structure calculations.

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

Rationale, design, and protocol for a hybrid type 1 effectiveness-implementation trial of a proactive smoking cessation electronic visit for scalable delivery via primary care: the E-STOP trial.

BACKGROUND: Cigarette smoking remains the leading cause of preventable disease and death in the United States. Primary care offers an ideal setting to reach adults who smoke cigarettes and improve uptake of evidence-based cessation treatment. Although U.S. Preventive Services Task Force Guidelines recommend the 5As model (Ask, Advise, Assess, Assist, Arrange) in primary care, there are many barriers to its implementation. Automated, comprehensive, and proactive tools are needed to overcome barriers. Our team developed and preliminarily evaluated a proactive electronic visit (e-visit) delivered via the Electronic Health Record patient portal to facilitate evidence-based smoking cessation treatment uptake in primary care, with promising initial feasibility and efficacy. This paper describes the rationale, design, and protocol for an ongoing Hybrid Type I effectiveness-implementation trial that will simultaneously assess effectiveness of the e-visit intervention for smoking cessation as well as implementation potential across diverse primary care settings. METHODS: The primary aim of this remote five-year study is to examine the effectiveness of the e-visit intervention vs. treatment as usual (TAU) for smoking cessation via a clinic-randomized clinical trial. Adults who smoke cigarettes are recruited across 18 primary care clinics. Clinics are stratified based on their number of primary care providers and randomized 2:1 to either e-visit or TAU. An initial baseline e-visit gathers information about patient smoking history and motivation to quit, and a clinical decision support algorithm determines the best evidence-based cessation treatment to prescribe. E-visit recommendations are evaluated by a patient's own provider, and a one-month follow-up e-visit assesses cessation progress. Main outcomes include: (1) cessation treatment utilization (medication, psychosocial cessation counseling), (2) reduction in cigarettes per day, and (3) biochemically verified 7-day point prevalence abstinence (PPA) at six-months. We hypothesize that patients randomized to the e-visit condition will have better cessation outcomes (vs. TAU). A secondary aim evaluates e-visit implementation potential at patient, provider, and organizational levels using a mixed-methods approach. Implementation outcomes include acceptability, adoption, fidelity, implementation cost, penetration, and sustainability. DISCUSSION: This asynchronous, proactive e-visit intervention could provide substantial benefits for patients, providers, and primary care practices and has potential to widely improve reach of evidence-based cessation treatment. TRIAL REGISTRATION: NCT05493254.

Pynta─An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics.

Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. We present Pynta, a workflow software for automating the calculation of surface and gas-surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.

Lithium Use for Suicide Prevention, Revisited.

The literature on lithium's role in suicide prevention is rife with competing interpretations and diverging opinions, in part stemming from the complexity of the underlying literature base. Conclusions that lithium unequivocally offers suicide prevention benefits do not appear warranted based on the strength of existing studies. Given the evidence along with the indisputable risks associated with lithium (especially in overdose), and the need for sustained therapeutic dosing to achieve any theoretical antisuicide benefit, it seems evident that any potential role for lithium in suicide prevention is far narrower than originally hypothesized. As such, the goal of this article is to provide an evidence-informed, therapeutic risk management approach to clinical decision-making concerning the use of lithium for suicide prevention to ensure that such prescribing is done in a patient-centered fashion that mitigates, to the extent possible, the potential risks of lithium use. This includes a review of potential justifications for not employing lithium for suicide prevention, given the recommendations in the existing guidelines. Clinicians should approach this clinical decision in an individualized fashion with full consideration of the potential risks associated with lithium use and availability, as well as potential alternative treatment options. An individualized risk/benefit analysis must also take into consideration the presence of comorbid conditions; the acuity of suicide risk, and any history of self-directed violence, with special attention to suicide attempts via overdose; treatment adherence, past and present; the presence and/or strength of a therapeutic relationship; and other viable treatment options.

Sella, an Open-Source Automation-Friendly Molecular Saddle Point Optimizer.

We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, for example, through the addition of dummy atoms. Additionally, the algorithm supports constrained optimization using the null-space sequential quadratic programming formalism. Our algorithm determines the direction of the reaction coordinate through iterative diagonalization of the Hessian matrix and does not require evaluation of the full Hessian matrix. Geometry optimization steps are chosen using the restricted step partitioned rational function optimization method, and displacements are realized using a high-performance geodesic stepping algorithm. This results in a robust and efficient optimization algorithm suitable for use in automated frameworks. We have implemented our algorithm in Sella, an open-source software package designed to optimize atomic systems to saddle point structures. We also introduce a new benchmark test comprising 500 molecular structures that approximate saddle point geometries and show that our saddle point optimization algorithm outperforms the algorithms implemented in several leading electronic structure theory packages.

Geometry optimization speedup through a geodesic approach to internal coordinates.

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

The Implementation and Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia in Primary Care: A Pilot Study.

Background: Digital interventions delivering Cognitive Behavioral Therapy for insomnia (Digital CBTi) may increase utilization of effective care for a common and serious condition. A low-intensity implementation strategy may facilitate digital CBTi use in healthcare settings. This pilot study assessed the feasibility of implementing a digital CBTi in Veterans Health Administration (VA) primary care through iterative modifications to a low-intensity implementation strategy, while evaluating clinical outcomes of a specific digital CBTi program. Methods: A self-directed digital CBTi was implemented in the primary care clinics of a single VA facility using a cohort trial design that iteratively modified an implementation strategy over three 8-month phases. The phase 1 implementation strategy included (1) provider education; (2) point-of-care information via pamphlets; and (3) provider referral to digital CBTi through phone calls or messages. Phases 2 and 3 maintained these activities, while (1) adding a clinic-based coach who performed initial patient education and follow-up support contacts, (2) providing additional recruitment pathways, and (3) integrating the referral mechanism into provider workflow. Implementation outcomes included provider adoption, patient adoption, and acceptability. Clinical outcomes (insomnia severity, depression severity, and sedative hypnotic use) were compared among enrollees at baseline and 10 weeks. Results: Across all phases 66 providers (48.9%) made 153 referrals, representing 0.38% of unique clinic patients. Of referrals, 77 (50.3%) enrolled in the study, 45 (29.4%) engaged in the program, and 24 (15.7%) completed it. Provider and patient adoption did not differ meaningfully across phases. Among enrollees, digital CBTi was acceptable and the Insomnia Severity Index decreased by 4.3 points (t = 6.41, p < 0.001) and 13 (18.6%) reached remission. The mean number of weakly sedative-hypnotic doses decreased by 2.2 (35.5%) (t = 2.39, p < 0.02). Conclusions: Digital CBTi implementation in VA primary care is feasible using low-intensity implementation strategy, resulting in improved clinical outcomes for users. However, iterative implementation strategy modifications did not improve adoption.The trial was registered at clinicaltrials.gov (NCT03151083).

Accelerated Saddle Point Refinement through Full Exploitation of Partial Hessian Diagonalization.

Identification and refinement of first order saddle point (FOSP) structures on the potential energy surface (PES) of chemical systems is a computational bottleneck in the characterization of reaction pathways. Leading FOSP refinement strategies for modestly sized molecular systems require calculation of the full Hessian matrix, which is not feasible for larger systems such as those encountered in heterogeneous catalysis. For these systems, the standard approach to FOSP refinement involves iterative diagonalization of the Hessian, but this comes at the cost of longer refinement trajectories due to the lack of accurate curvature information. We present a method for incorporating information obtained by an iterative diagonalization algorithm into the construction of an approximate Hessian matrix that accelerates FOSP refinement. We measure the performance of our method with two established FOSP refinement benchmarks and find a 50% reduction on average in the number of gradient evaluations required to converge to a FOSP for one benchmark and a 25% reduction on average for the second benchmark.

Micki: A python-based object-oriented microkinetic modeling code.

We have developed a flexible, general-purpose microkinetic modeling code, Micki, to analyze complex, heterogeneously catalyzed chemical reactions based upon first-principles calculations. This Python-based code is modular and object oriented, framing the development of microkinetic models in familiar chemical terms. We also present novel approaches, incorporated into Micki, to describe diffusion limited reactions, multidentate bindings, thermodynamically consistent lateral interactions, and Brønsted-Evans-Polanyi estimates of changes in barrier heights. Micki has built-in modules for subsequent analysis of microkinetic models, including degree of rate control and rate order. As a demonstration of the power and flexibility of the code, we build a microkinetic model for the water-gas shift reaction and compare to previously published experimental results and microkinetic models, showing that Micki can quantitatively reproduce experimental turnover frequencies with minimal empirical optimization.

Beliefs and Attitudes About the Dissemination and Implementation of Internet-Based Self-Care Programs in a Large Integrated Healthcare System.

Behavioral intervention technologies (BITs) are online programs or mobile applications that deliver behavioral health interventions for self-care. The dissemination and implementation of such programs in U.S. healthcare systems has not been widely undertaken. To better understand these phenomena, we explored perspectives on BIT deployment in the Veterans Health Administration. Interviews from 20 providers, administrators, and policy makers were analyzed using qualitative methods. Eight themes were identified including the use of traditional healthcare delivery models, strategies for technology dissemination and implementation, internet infrastructure, leadership, health system structure, regulations, and strategic priorities. This research suggests policy, funding, and strategy development initiatives to promote the implementation and dissemination of BITs.

Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

Behavioral intervention technologies (BITs) are websites, software, mobile apps, and sensors designed to help users address or change behaviors, cognitions, and emotional states. BITs have the potential to transform health care delivery, and early research has produced promising findings of efficacy. BITs also favor new models of health care delivery and provide novel data sources for measurement. However, there are few examples of successful BIT implementation and a lack of consensus on as well as inadequate descriptions of BIT implementation measurement. The aim of this viewpoint paper is to provide an overview and characterization of implementation outcomes for the study of BIT use in routine practice settings. Eight outcomes for the evaluation of implementation have been previously described: acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability. In a proposed recharacterization of these outcomes with respect to BIT implementation, definitions are clarified, expansions to the level of analysis are identified, and unique measurement characteristics are discussed. Differences between BIT development and implementation, an increased focus on consumer-level outcomes, the expansion of providers who support BIT use, and the blending of BITs with traditional health care services are specifically discussed. BITs have the potential to transform health care delivery. Realizing this potential, however, will hinge on high-quality research that consistently and accurately measures how well such technologies have been integrated into health services. This overview and characterization of implementation outcomes support BIT research by identifying and proposing solutions for key theoretical and practical measurement challenges.

Computer-based self-help therapy: A qualitative analysis of attrition.

The impact of computer-based cognitive-behavioral self-help therapy programs is limited by high attrition. This study explored reactions to computer-based cognitive-behavioral self-help therapy use among individuals not completing a full treatment course. Individuals receiving outpatient substance use disorder treatment at a Veterans Health Administration clinic who enrolled in a study implementing a computer-based cognitive-behavioral self-help therapy for insomnia, but subsequently dropped out prior to completion, were interviewed. Reactions to use and reasons for attrition were explored through thematic analysis of interviews. Among barriers to use, themes of competing demands, personal attributes, the computer-based format of computer-based cognitive-behavioral self-help therapies, and negative experiences with the specific program used were identified. Among facilitators of use, themes of personal support, the computer-based cognitive-behavioral self-help therapy format, and personal attributes were identified. Recommendations for future implementation efforts to include additional person-to-person contact during computer-based cognitive-behavioral self-help therapy participation were made. These themes may be employed to develop strategies for computer-based cognitive-behavioral self-help therapy implementation in order to maximize program engagement and completion.

Implementing Internet-Based Self-Care Programs in Primary Care: Qualitative Analysis of Determinants of Practice for Patients and Providers.

BACKGROUND: Access to evidence-based interventions for common mental health conditions is limited due to geographic distance, scheduling, stigma, and provider availability. Internet-based self-care programs may mitigate these barriers. However, little is known about internet-based self-care program implementation in US health care systems. OBJECTIVE: The objective of this study was to identify determinants of practice for internet-based self-care program use in primary care by eliciting provider and administrator perspectives on internet-based self-care program implementation. METHODS: The objective was explored through qualitative analysis of semistructured interviews with primary care providers and administrators from the Veterans Health Administration. Participants were identified using a reputation-based snowball design. Interviews focused on identifying determinants of practice for the use of internet-based self-care programs at the point of care in Veterans Health Administration primary care. Qualitative analysis of transcripts was performed using thematic coding. RESULTS: A total of 20 physicians, psychologists, social workers, and nurses participated in interviews. Among this group, internet-based self-care program use was relatively low, but support for the platform was assessed as relatively high. Themes were organized into determinants active at patient and provider levels. Perceived patient-level determinants included literacy, age, internet access, patient expectations, internet-based self-care program fit with patient experiences, interest and motivation, and face-to-face human contact. Perceived provider-level determinants included familiarity with internet-based self-care programs, changes to traditional care delivery, face-to-face human contact, competing demands, and age. CONCLUSIONS: This exploration of perspectives on internet-based self-care program implementation among Veterans Health Administration providers and administrators revealed key determinants of practice, which can be used to develop comprehensive strategies for the implementation of internet-based self-care programs in primary care settings.

The atomic simulation environment-a Python library for working with atoms.

The atomic simulation environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple 'for-loop' construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

Multimodal Neuroimaging of Frontolimbic Structure and Function Associated With Suicide Attempts in Adolescents and Young Adults With Bipolar Disorder.

OBJECTIVE: Bipolar disorder is associated with high risk for suicidal behavior that often develops in adolescence and young adulthood. Elucidation of involved neural systems is critical for prevention. This study of adolescents and young adults with bipolar disorder with and without a history of suicide attempts combines structural, diffusion tensor, and functional MR imaging methods to investigate implicated abnormalities in the morphology and structural and functional connectivity within frontolimbic systems. METHOD: The study had 26 participants with bipolar disorder who had a prior suicide attempt (the attempter group) and 42 participants with bipolar disorder without a suicide attempt (the nonattempter group). Regional gray matter volume, white matter integrity, and functional connectivity during processing of emotional stimuli were compared between groups, and differences were explored for relationships between imaging modalities and associations with suicide-related symptoms and behaviors. RESULTS: Compared with the nonattempter group, the attempter group showed significant reductions in gray matter volume in the orbitofrontal cortex, hippocampus, and cerebellum; white matter integrity in the uncinate fasciculus, ventral frontal, and right cerebellum regions; and amygdala functional connectivity to the left ventral and right rostral prefrontal cortex. In exploratory analyses, among attempters, there was a significant negative correlation between right rostral prefrontal connectivity and suicidal ideation and between left ventral prefrontal connectivity and attempt lethality. CONCLUSIONS: Adolescent and young adult suicide attempters with bipolar disorder demonstrate less gray matter volume and decreased structural and functional connectivity in a ventral frontolimbic neural system subserving emotion regulation. Among attempters, reductions in amygdala-prefrontal functional connectivity may be associated with severity of suicidal ideation and attempt lethality.

Psychopharmacologic Services for Homeless Veterans: Comparing Psychotropic Prescription Fills Among Homeless and Non-Homeless Veterans with Serious Mental Illness.

Using national Veterans Health Administration (VHA) administrative data, this study evaluated differences in psychotropic medication use between homeless and non-homeless adults with serious mental illness (SMI) who used VHA services in 2010. The adjusted mean number of psychotropic prescription fills associated with homeless individuals were identified using regression models adjusted for socio-demographics, diagnoses, and use of health services. Of the 876,989 individuals with SMI using VHA services, 7.2 % were homeless at some time during 2010. In bivariate analysis, homeless individuals filled more psychotropic medication prescriptions compared with non-homeless individuals. However, after adjusting for potentially confounding variables, homeless individuals were found to have filled 16.2 % fewer prescriptions than non-homeless individuals when all psychotropics were analyzed together (F = 6947.1, p < .001) and for most individual classes of psychotropics. Greater use of residential/inpatient mental health services by the homeless was the most important single factor associated with filling more psychotropic prescriptions than non-homeless individuals.

Implementing Computer-Based Psychotherapy Among Veterans in Outpatient Treatment for Substance Use Disorders.

OBJECTIVE: Computer-based psychotherapy interventions (CBPIs) are increasingly offered as first-level access to evidence-based mental health treatment. However, their implementation has not been evaluated in public-sector outpatient settings. METHODS: An evidence-based CBPI for insomnia was implemented with provider and patient education sessions, on-site Internet access, and clinician telephone support. Persons receiving care at a Veterans Health Administration substance abuse treatment clinic were screened for chronic insomnia and offered CBPI access. The feasibility of this strategy was evaluated in a pre-post design, which assessed engagement and completion rates, participant-reported acceptability, and clinical outcomes. RESULTS: Of 100 veterans referred, 51 enrolled in the program, of whom 22 (43%) completed all sessions, 13 (26%) partially completed the program, and 16 (31%) did not engage. There were no statistically significant differences between these three groups in baseline characteristics. In the total sample, Insomnia Severity Index (ISI) scores decreased (improved) by 32% (mean±SD of 6.3±6.2 points, t=6.82, df=44, p<.001). Veterans who completed all six sessions displayed clinically and statistically significant improvements on the ISI compared with those who did not engage, as shown in a regression analysis that controlled for baseline insomnia severity, time between assessments, and sedative-hypnotic medication use (F=3.87, df=4 and 40, p≤.004). Among all participants, 67% agreed that they would engage in another CBPI in the future. When questioned about potential barriers, 36% of the full sample endorsed a preference for face-to-face therapy. CONCLUSIONS: A strategy of brief provider and patient education, on-site Internet access, and telephone support was feasible and effective for implementing CBPIs in outpatient substance abuse treatment settings for veterans.

Technology Use and Interest in Computerized Psychotherapy: A Survey of Veterans in Treatment for Substance Use Disorders.

INTRODUCTION: This study examined interest in computerized psychotherapies (CPTs) and its relation to use of information technology among individuals receiving Veterans Health Administration (VHA) outpatient treatment. MATERIALS AND METHODS: Veterans receiving treatment in a VHA substance use disorder outpatient clinic completed a self-report questionnaire. The survey addressed recent experience using information technology and potential interest in using CPTs for symptoms/functional problems associated with substance use and mental health disorders. Demographic, diagnostic, and information technology use data were compared between those expressing interest in CPT and those not expressing an interest, as well as with nationally representative veteran data from the 2010 National Survey of Veterans (NSV). RESULTS: Of 151 respondents, 82% were interested in CPT for at least one problem, and 60% were interested for more than one. The most commonly selected CPTs were for substance use (46%), depression (45%), problem solving (43%), and insomnia (42%). None of the 23 measures of information technology use was associated with interest in CPTs. Compared with respondents not interested in any CPTs, those interested in CPT were older (t150=2.1, p=0.042) and more likely to be African American [χ(2)(1)=8.8, p=0.032], to have reported a drug use disorder [χ(2)(1)=4.2, p=0.041], and to have reported more than one substance use or psychiatric disorder [χ(2)(1)=8.5, p=0.014]. The majority of respondents reported use of Internet and e-mail (65% and 64%, respectively), proportions comparable to respondents to the NSV. CONCLUSIONS: Among veterans receiving outpatient substance use treatment, interest in CPT is high and unrelated to information technology use. Efforts to implement CPTs may interest this population.