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.

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.

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.

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.

Sources of the increasing number of Vietnam era veterans with a diagnosis of PTSD using VHA services.

OBJECTIVE: Correlates of the sharp increase in Vietnam era veterans diagnosed as having posttraumatic stress disorder (PTSD) in the Veterans Health Administration (VHA) were examined. METHODS: Analyses compared receipt of a PTSD diagnosis and service-connected disability compensation in 2004-2006 and 2007-2009. RESULTS: Among Vietnam era veterans, the percentage with a PTSD diagnosis in 2007-2009 was 22.2% higher than the percentage with PTSD in 2004-2006; the percentage without PTSD was 6.2% higher than in 2004-2006. Of those with PTSD in 2007-2009, 22.6% were previous VHA service users newly diagnosed ("conversions"); only 12.8% were entirely new to VHA ("recents"). Rates of disability compensation among recents and conversions were almost two and three times higher, respectively, than among those without PTSD. CONCLUSIONS: The increase in Vietnam era veterans with PTSD is associated with more frequent "conversion" to PTSD among previous VHA users and receipt of disability compensation.

Use of second-generation antipsychotic agents for sleep and sedation: a provider survey.

OBJECTIVES: Anecdotal evidence suggests that second-generation antipsychotic agents are increasingly used to treat sleep problems. This study sought to quantify the proportion of new prescriptions for second-generation antipsychotic agents started for sleep/sedation and the correlates of such use. DESIGN: A cross-sectional survey of provider decision making at the time second-generation antipsychotic agents were prescribed, documenting the reasons for the medication, patient demographics, psychiatric and medical diagnoses, patient health characteristics, and provider background. SETTING: A single Veterans Affairs Medical Center over a 20-month period. PARTICIPANTS: Prescribers of second-generation antipsychotic agents. INTERVENTIONS: N/A. RESULTS: Seven hundred seven (32.2%) of 2,613 surveys indicated sleep/sedation was at least one reason for using a second-generation anti-psychotic agent, whereas for 266 (12.1%) it was the only reason. Quetiapine was most frequently prescribed overall as well as for sleep/sedation (47.0% and 73.6% respectively). Second-generation antipsychotic agent use for sleep/sedation was unrelated to sociodemographic characteristics, least likely in patients with schizophrenia or bipolar disorder, and most likely as a newly started second-generation antipsychotic agent. CONCLUSION: Sleep/sedation is a common reason given for new prescriptions of second-generation antipsychotic agents. Quetiapine is most frequently used for this purpose. A greater understanding of why providers use second-generation antipsychotic agents rather than safer and less costly alternatives for sleep problems may advance the development of interventions to reduce adverse effects.

Prescription of second-generation antipsychotics: responding to treatment risk in real-world practice.

OBJECTIVE: This study sought to determine the extent of providers' sensitivity to the presence of cardiometabolic disorders in the selection of second-generation antipsychotics. METHODS: As part of an academic detailing effort conducted between October 2007 and May 2009, all psychiatric providers at a single Veterans Affairs medical center completed a survey for every new prescription of an on-patent second-generation antipsychotic. The survey documented the drug prescribed, patients' sociodemographic data, psychiatric and comorbid diagnoses, and reasons for the prescription. The association between obesity, hypertension, hyperlipidemia, diabetes, and cardiovascular disease and the choice of antipsychotics with varying levels of cardiometabolic risk was evaluated. RESULTS: Data consisted of 2,613 surveys completed by 259 providers. Olanzapine, with high cardiometabolic risk, and quetiapine and risperidone, with moderate risk, accounted for 79% of prescriptions. There was a significant (p<.001) association between the second-generation antipsychotic prescribed and obesity, hyperlipidemia, and diabetes but not hypertension or cardiovascular disease. The proportion of patients receiving olanzapine was only slightly smaller, by an average of 4 percentage points, among patients with cardiometabolic disorders than among patients without cardiometabolic disorders. The proportion of patients receiving aripiprazole, with little or no cardiometabolic risk, was consistently higher, by an average of only 2 percentage points, among patients with a cardiometabolic disorder versus without one. CONCLUSIONS: Although this study found a statistically significant sensitivity by providers to cardiometabolic risk, this sensitivity was neither robust nor uniformly statistically significant. More research into how providers use medication risk information when making treatment decisions may help improve the quality of care.

Impact of a program encouraging the use of generic antipsychotics.

OBJECTIVE: Recent research suggests that second generation antipsychotics (SGAs) may be used more often than clinically warranted. An intervention consisting of academic detailing and a prescriber survey was employed to encourage the reduction of newly prescribed on-patent SGAs. DESIGN: Quasi-experimental quality improvement trial. METHODS: Academic detailing consisted of educational lectures and a pocket guide on the latest effectiveness, safety, and cost data for SGAs and first-generation antipsychotics. Detailing was coupled with a required 20-item survey of provider decision making completed prior to prescriptions for on-patent SGAs at a Veterans Health Administration medical center between October 2007 and May 2009. The survey identified the medication, treated diagnosis, comorbid psychiatric and medical diagnoses, reasons for the medication, prior medications, and provider professional status. The outcome was the number of new SGA prescriptions per month. RESULTS: The sample included 2176 surveys. The Spearman correlation between the number of prescriptions and the intervention month (range = 1-18) was 0.25 (P = .31), indicating no reduction. The most common medication prescribed was quetiapine (55.8%). The distributions of diagnoses were fairly even among schizophrenia, bipolar disorder, other affective disorders, and posttraumatic stress disorder (17.0, 28.2, 25.8, and 20.4%, respectively). The 3 most common reasons for prescribing an SGA were to improve efficacy (49.8%), reduce side effects (29.1%), and increase sleep or sedation (34.5%). CONCLUSIONS: Academic detailing coupled with a provider survey did not decrease the rate of new prescriptions for on-patent SGAs. Reasons for prescribing SGAs were not consistent with recent research findings regarding efficacy and side effects.

Minimum clinically important difference in the Positive and Negative Syndrome Scale with data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE).

CONTEXT: Establishing the minimum clinically important difference in the Positive and Negative Syndrome Scale (PANSS) is important to the interpretation of the research and clinical work conducted with this scale. METHOD: This study employed both anchor-based and distributive methods to estimate the minimum clinically important difference for the PANSS by using data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial, a large, multicenter trial for patients with schizophrenia. By using an equipercentile method, data from 1,442 individuals linked PANSS scores with both clinician and patient ratings on the Clinical Global Impressions scale (CGI). Data were also used to investigate the magnitude of the standard error of measurement (SEM), offering another estimate of the minimum clinically important difference. RESULTS: Cross-sectional, clinician-rated CGI-Severity of illness scores of 1 through 7 linked to PANSS scores of 32.4, 42.2, 57.5, 74.5, 93.0, 110.9, and 131.0, respectively. The minimum clinically important difference for PANSS scores using this scale equaled a 15.3-point (34.0%) change from baseline. A 1.96 SEM on the PANSS corresponded to a 16.5-point (36.2%) change from baseline. The minimum clinically important difference for a subsample with above-median baseline PANSS scores was 38% higher than a sample with lower baseline scores. With the patient-rated CGI as the anchor, PANSS scores were higher for CGI scores of 1 through 4, and the minimum clinically important difference was lower, 11.2 points (24.6%). CONCLUSION: Minimum clinically important difference estimates from a longer-term effectiveness trial were consistent with previous efforts from shorter-term efficacy trials. Minimum clinically important difference estimates can help clinicians and researchers design future studies and interpret treatment change in future research and clinical work.

Recent trends in the treatment of posttraumatic stress disorder and other mental disorders in the VHA.

OBJECTIVE: This study proposed to evaluate Veterans Health Administration (VHA) specialty mental health care workload for treating posttraumatic stress disorder (PTSD) and other mental disorders between 2005 and 2010 in comparison with results from 1997 to 2005. The 2005-2010 time frame represents a period of increased utilization of services by recently returning veterans and of program expansion within VHA. METHODS: VHA administrative databases were queried for all veterans receiving specialty mental health treatment annually between 2005 and 2010. Veterans were categorized by military service era (WWII or Korea, Vietnam, post-Vietnam, Persian Gulf War [including operations in Iraq and Afghanistan], and peacetime or other), diagnosis (PTSD or a non-PTSD mental disorder), and deployment to Iraq or Afghanistan. RESULTS: The total number of veterans served per year increased by 623,326 (117.6%) between 1997 and 2010. Veterans with PTSD increased at a greater rate since 2005 compared with veterans with other mental disorders. Vietnam veterans constituted a majority of all veterans treated for PTSD or for other mental disorders, and the number of Vietnam veterans treated for PTSD continues to grow. The number of visits per veteran with PTSD increased between 2006 and 2010, reversing previous trends. The rate of increase has been highest for Iraq and Afghanistan veterans. CONCLUSIONS: Both the number treated and treatment intensity have increased for veterans with PTSD who served in current conflicts, which might be expected, and in the Vietnam era, now 30 years past. A reversal of past declines in treatment intensity coincides with an increase in PTSD treatment funding and program expansion since 2005.

Smokeless tobacco use related to military deployment, cigarettes and mental health symptoms in a large, prospective cohort study among US service members.

AIMS: To characterize smokeless tobacco initiation and persistence in relation to deployment, combat, occupation, smoking and mental health symptoms. DESIGN: Prospective cohort, utilizing self-reported survey data from the Millennium Cohort Study. SETTING: US military service members in all branches including active duty, reserve and National Guard. PARTICIPANTS: Population-based sample of 45,272 participants completing both baseline (July 2001-June 2003; n = 77,047) and follow-up (June 2004-January 2006; n = 55,021) questionnaires (follow-up response rate = 71.4%). MEASUREMENTS: Self-reported smokeless tobacco initiation and persistence. FINDINGS: Over the study period, 72.4% did not deploy, 13.7% deployed without combat exposures and 13.9% deployed with combat exposures, while 1.9% were smokeless tobacco initiators and 8.9% were persistent users. The odds of initiation were greater for deployers with combat exposure [odds ratio (OR), 1.76; 95% confidence interval (CI), 1.49-2.09], deployers without combat exposure (OR, 1.31; 95% CI, 1.07-1.60) and those who deployed multiple times (OR, 1.67; 95% CI, 1.31-2.14), as well as in smoking recidivists/initiators (OR, 4.65; 95% CI, 3.82-5.66) and those reporting post-traumatic stress disorder symptoms (OR, 1.54; CI, 1.15-2.07). A similar pattern for higher odds of persistent use was observed for deployment and combat exposure, but not for smoking and mental health symptoms. Military occupation was not significantly associated with initiation or persistence. CONCLUSIONS: Deployment and combat exposure in the US military are associated with increased risk of smokeless tobacco initiation and persistence while smoking and symptoms of post-traumatic stress disorder increase the odds for initiation. Research is needed on aspects of military service amenable to the reduction or prevention of tobacco consumption.

Aircraft type and other risk factors for spinal disorders: data from 19,673 military cockpit aircrew.

INTRODUCTION: Many assume that exposure to flight in high-performance aircraft (HPA) or rotary wing aircraft (RWA) increases the risk of spinal disorders compared to other fixed wing aircraft (FWA). However, this association has yet to be confirmed. This study explores the relationship between flight in different aircraft and the development of lumbar and cervical spine disorders. METHODS: The flight records of 19,673 U.S. Air Force (USAF) cockpit aircrew officers were examined for entries with a spinal disorder diagnosis in an existing aircrew health information database. Univariate and multivariate analyses were employed to examine the association between aircraft type, other variables, and spinal disorders. RESULTS: In stratified analysis of HPA and FWA, but not RWA categories, statistically significant unadjusted associations were observed between flight hours and cervical [HPA: odds ratio (OR) = 2.80, FWA: OR = 4.73] and lumbar disorders (HPA: OR = 2.46, FWA: OR = 3.01). After adjustment for birth year in a stratified multivariate analysis, these associations were no longer statistically significant. In all three aircraft types, statistically significant adjusted associations were observed between older birth year category and both cervical (HPA: OR = 3.82, FWA: OR = 5.88) and lumbar disorders (HPA: OR = 4.16, RWA: OR = 2.96, FWA: OR = 2.39). DISCUSSION: The risk produced by exposure to HPA, RWA, or FWA as measured by flight hours may be overshadowed by that produced by birth year, which was the strongest predictor for spinal disorders in this study. Future endeavors should more closely examine the association between age and accrual of flight hours in various aircraft types in order to accurately direct preventive measures.