Decisional Needs of Veterans With Mild Traumatic Brain Injury Initiating Treatment for Insomnia Disorder and Obstructive Sleep Apnea.

OBJECTIVE: We sought to elicit key informant (KI) perspectives regarding decisional needs of Veterans with mild traumatic brain injury (mTBI) who are initiating insomnia disorder and obstructive sleep apnea (OSA) treatment within the Veterans Health Administration (VHA) Polytrauma/TBI System of Care (PSC). Specifically, we sought to understand: (1) information regarding treatment options that Veterans with mTBI require in order to make an informed decision; and (2) values used to guide decision-making (ie, personally meaningful aspects of the decision used to compare treatment options). SETTING: Nationwide VHA PSC sites. PARTICIPANTS: Clinicians included VHA providers and policymakers involved in the management of mTBI and/or sleep disorders in the VHA PSC (n = 29). Veterans included those with a clinician-confirmed mTBI who received care for insomnia disorder and/or OSA within the past year (n = 20). DESIGN: Semi-structured interviews with the 49 KIs were recorded and transcribed verbatim. Themes were identified using a descriptive and interpretive approach to qualitative analysis. MAIN MEASURES: Not applicable. RESULTS: Informational needs identified by both KI groups included information regarding outcomes and downsides of treatment, accessible delivery, treatment candidates, description of diagnosis, and level of commitment. Values used to guide decision-making for both insomnia disorder and OSA treatment included benefits, downsides, and availability of treatments. Values used to decide on insomnia treatments alone included time commitment, intrinsic management of sleep, beliefs regarding mental health treatment, and time course of benefit. Values used to decide on OSA treatment alone included intrusiveness of the treatment, appearance, and impact on bed partners. CONCLUSIONS: The current study revealed the decisional needs of Veterans with mTBI who are initiating sleep disorder treatment. Findings can inform the development of decision aids and other efforts aimed at promoting patient-centered management of comorbid mTBI and sleep disorders, thereby improving care quality and clinical outcomes.

Factors Influencing Adherence to Insomnia and Obstructive Sleep Apnea Treatments among Veterans with Mild Traumatic Brain Injury.

OBJECTIVE: To understand factors influencing adherence to recommended treatment for insomnia and obstructive sleep apnea (OSA) among Veterans with mild traumatic brain injury (mTBI). METHOD: Semi-structured interviews (n = 49) with 29 clinical stakeholders and 20 Veterans were conducted. Clinical stakeholders included Veterans Health Administration providers and policymakers involved in the management of mTBI and/or sleep disorders. Veterans included those with a clinician-confirmed mTBI with a recent history of insomnia disorder and/or OSA treatment. Themes were identified using a Descriptive and Interpretive approach. RESULTS: Barriers to sleep disorder treatment adherence included factors associated with the patient (e.g., negative appraisal of treatment benefit), intervention (e.g., side effects), health conditions (e.g., cognitive challenges), health care system (e.g., limited availability of care), and socioeconomic status (e.g., economic instability). Similarly, facilitators of adherence included patient- (e.g., positive appraisal of treatment benefit), intervention- (e.g., flexible delivery format), condition- (e.g., accommodating cognitive impairments), health care system- (e.g., access to adherence support), and socioeconomic-related factors (e.g., social support). CONCLUSIONS: Interviews revealed the multi-faceted nature of factors influencing adherence to sleep disorder treatment among Veterans with mTBI. Findings can inform the development of novel interventions and care delivery models that meet the complex needs of this population.

Factors influencing shared decision-making for insomnia and obstructive sleep apnea treatment among Veterans with mild traumatic brain injury.

STUDY OBJECTIVES: We elicited perspectives of clinical stakeholders and Veterans regarding barriers and facilitators to implementing shared decision-making (SDM) for comorbid mild traumatic brain injury (mTBI) and sleep disorders in the Veterans Health Administration. We also compared the perspectives of clinical stakeholders and Veterans regarding determinants of SDM. METHODS: Semistructured interviews were conducted with 29 clinical stakeholders and 20 Veterans (n = 49). Clinical stakeholders included Veterans Health Administration providers and policymakers involved in the management of mTBI and/or sleep disorders (insomnia disorder, obstructive sleep apnea). Veterans included those with a clinician-confirmed mTBI who received care for insomnia disorder and/or obstructive sleep apnea within the past year. Themes were identified using a descriptive and interpretive approach to qualitative analysis. We compared results across clinical stakeholders and Veterans. RESULTS: Barriers to implementing SDM were identified by both groups at the patient (eg, mTBI sequalae), provider (eg, deprioritization of Veteran preferences), encounter (eg, time constraints), and facility levels (eg, reduced care access). Similarly, both groups identified facilitators at the patient (eg, enhanced trust), provider (eg, effective communication), encounter (eg, decision support), and facility levels (eg, mitigating access barriers). Integrated services and provider discontinuity were factors identified by clinical stakeholders and Veterans alone, respectively. CONCLUSIONS: Our study revealed factors shaping the implementation of SDM at the levels of the patient, provider, encounter, and facility. Findings can inform the development of strategies aimed at implementing SDM for comorbid mTBI and sleep disorders, promoting patient-centered care and enhancing clinical outcomes. CITATION: Kinney AR, Brenner LA, Nance M, et al. Factors influencing shared decision-making for insomnia and obstructive sleep apnea treatment among Veterans with mild traumatic brain injury. J Clin Sleep Med. 2024;20(5):801-812.

Longitude-based time zone partitions and rates of suicide.

BACKGROUND: Increasing evidence suggests that conditions with decreased morning and increased evening light exposure, including shift work, daylight-saving time, and eveningness, are associated with elevated mortality and suicide risk. Given that the alignment between the astronomical, biological, and social time varies across a time zone, with later-shifted daylight exposure in the western partition, we hypothesized that western time zone partitions would have higher suicide rates than eastern partitions. METHODS: United States (U.S.) county-level suicide and demographic data, from 2010 to 2018, were obtained from a Centers for Disease Control database. Using longitude and latitude, counties were sorted into the western, middle, or eastern partition of their respective time zones, as well as the northern and southern halves of the U.S. Linear regressions were used to estimate the associations between suicide rates and time zone partitions, adjusting for gender, race, ethnicity, age group, and unemployment rates. RESULTS: Data were available for 2872 counties. Across the U.S., western partitions had statistically significantly higher rates of suicide compared to eastern partitions and averaged up to two additional yearly deaths per 100,000 people (p < .001). LIMITATIONS: Ecological design and limited adjustment for socioeconomic factors. CONCLUSIONS: To our knowledge, this is the first study of the relationship between longitude-based time zone partitions and suicide. The results were consistent with the hypothesized elevated suicide rates in the western partitions, and concordant with previous reports on cancer mortality and transportation fatalities. The next step is to retest the hypothesis with individual-level data, accounting for latitude, photoperiodic changes, daylight-saving time, geoclimatic variables, physical and mental health indicators, as well as socioeconomic adversity and protection.

COVID-19 and Lifetime Experiences of Trauma, Moral Injury, and Institutional Betrayal Among Healthcare Providers.

OBJECTIVE: The aim of the study is to increase understanding regarding healthcare provider experiences with psychological trauma, moral injury, and institutional betrayal, both over the lifetime and during the COVID-19 pandemic. METHODS: The study employed a cross-sectional design to understand traumatic experiences, moral injury, and institutional betrayal among medical and mental health providers. Participants were asked to identify an index trauma, and experiences were coded qualitatively using categories for traumatic events, moral injury, and institutional betrayal. RESULTS: Results revealed that experiences of trauma, moral injury, and institutional betrayal were common in relation to the pandemic, as were prepandemic histories of traumatic exposures. Findings indicate that trauma exposure was a work hazard for healthcare providers during the pandemic, which could result in negative long-term mental health outcomes. CONCLUSIONS: Future research is needed to explore potential long-term negative outcomes among healthcare providers.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta.

Carbohydrate chains are ubiquitous in the complex molecular processes of life. These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. High-resolution structures of protein-glycoligand complexes reveal the atomic details necessary to understand this level of molecular recognition and inform application-focused scientific and engineering pursuits. When experimental challenges hinder high-throughput determination of quality structures, computational tools can, in principle, fill the gap. In this work, we introduce GlycanDock, a residue-centric protein-glycoligand docking refinement algorithm developed within the Rosetta macromolecular modeling and design software suite. We performed a benchmark docking assessment using a set of 109 experimentally determined protein-glycoligand complexes as well as 62 unbound protein structures. The GlycanDock algorithm can sample and discriminate among protein-glycoligand models of native-like structural accuracy with statistical reliability from starting structures of up to 7 Å root-mean-square deviation in the glycoligand ring atoms. We show that GlycanDock-refined models qualitatively replicated the known binding specificity of a bacterial carbohydrate-binding module. Finally, we present a protein-glycoligand docking pipeline for generating putative protein-glycoligand complexes when only the glycoligand sequence and unbound protein structure are known. In combination with other carbohydrate modeling tools, the GlycanDock docking refinement algorithm will accelerate research in the glycosciences.

PyRosetta Jupyter Notebooks Teach Biomolecular Structure Prediction and Design.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of sixteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

Novel sampling strategies and a coarse-grained score function for docking homomers, flexible heteromers, and oligosaccharides using Rosetta in CAPRI rounds 37-45.

Critical Assessment of PRediction of Interactions (CAPRI) rounds 37 through 45 introduced larger complexes, new macromolecules, and multistage assemblies. For these rounds, we used and expanded docking methods in Rosetta to model 23 target complexes. We successfully predicted 14 target complexes and recognized and refined near-native models generated by other groups for two further targets. Notably, for targets T110 and T136, we achieved the closest prediction of any CAPRI participant. We created several innovative approaches during these rounds. Since round 39 (target 122), we have used the new RosettaDock 4.0, which has a revamped coarse-grained energy function and the ability to perform conformer selection during docking with hundreds of pregenerated protein backbones. Ten of the complexes had some degree of symmetry in their interactions, so we tested Rosetta SymDock, realized its shortcomings, and developed the next-generation symmetric docking protocol, SymDock2, which includes docking of multiple backbones and induced-fit refinement. Since the last CAPRI assessment, we also developed methods for modeling and designing carbohydrates in Rosetta, and we used them to successfully model oligosaccharide-protein complexes in round 41. Although the results were broadly encouraging, they also highlighted the pressing need to invest in (a) flexible docking algorithms with the ability to model loop and linker motions and in (b) new sampling and scoring methods for oligosaccharide-protein interactions.