Relative to White women, African American/Black women are at an increased risk of breast cancer mortality. Early detection of breast cancer through mammography screening can mitigate mortality risks; however, screening rates are not ideal. Consequently, there is a need to better understand factors associated with adherence to breast cancer screening guidelines to inform interventions to increase mammography use, particularly for groups at elevated mortality risk. This study used the Andersen Behavioral Model of Health Services Use to examine factors associated with adherence to National Comprehensive Cancer Network breast cancer screening guidelines amongst 919 African American, church-going women from Houston, Texas. Logistic regression analyses measured associations between breast cancer screening adherence over the preceding 12 months (adherent or non-adherent) and predisposing (i.e., age, education, and partner status), enabling (i.e., health insurance status, annual household income, employment status, patient-provider communication, and social support), and need (i.e., personal diagnosis of cancer, family history of cancer, and risk perception) factors, separately and conjointly. Older age (predisposing: OR = 1.015 (1.007–1.023)), having health insurance and ideal patient–provider communication (enabling: OR = 2.388 (1.597–3.570) and OR = 1.485 (1.080–2.041)), and having a personal diagnosis of cancer (need: OR = 2.244 (1.058–4.758)) were each associated with greater odds of screening adherence. Only having health insurance and ideal patient-provider communication remained significantly associated with screening adherence in a conjoint model; cancer survivorship did not moderate associations between predisposing/enabling factors and screening adherence. Overall, results suggest that interventions which are designed to improve mammography screening rates amongst African American women might focus on broadening health insurance coverage and working to improve patient–provider communication. Implications for multi-level intervention approaches, including the role of churches in their dissemination, are proposed.

Tobacco use is exceedingly high among individuals receiving care for opioid addiction, but not commonly addressed by clinicians in treatment settings. Taking Texas Tobacco Free (TTTF) is a comprehensive tobacco-free workplace (TFW) program that builds treatment centers’ capacity to address tobacco use with evidence-based tobacco cessation policies and practices. Here, we examine the process and outcomes of TTTF’s implementation within 7 opioid addiction centers. Program goals were structured according to the RE-AIM framework. Pre- and post-implementation data were collected from client facing and non-client facing employees to assess changes in education, training receipt, knowledge, and intervention behaviors, relative to program goals. Centers reported tobacco screenings conducted and nicotine replacement therapy (NRT) delivered through 6 months post-implementation. Overall, 64.56% of employees participated in TTTF-delivered tobacco education, with a 54.9% gain in tobacco control and treatment knowledge (p < 0.0001), and significant increases in exposure to education about tobacco use and harms among individuals with opioid use disorder (p = 0.0401). There were significant gains in clinicians’ receipt of training in 9/9 tobacco education areas (ps ≤ 0.0118). From pre- to post-implementation, there were mean increases in the use of the 5A’s (ask, advise, assess, assist, and arrange) and other evidence-based interventions for tobacco cessation, with statistically significant gains seen in NRT provision/referral (p < 0.0001). Several program goals were achieved or exceeded; however, 100% center participation in specialized clinical trainings was among notable exceptions. One program withdrew due to competing pandemic concerns; all others implemented comprehensive TFW policies. Overall, TTTF may have improved participating opioid treatment centers’ capacity to address tobacco use, although study limitations, including lower post-implementation evaluation response rates, suggest that results require replication in other opioid addiction treatment settings.

Individuals with behavioral health conditions account for 50% of annual smoking-related deaths, yet rarely receive tobacco dependence treatment within local mental health authorities (LMHAs). As lack of training and knowledge are key barriers to providing tobacco dependence treatment, Taking Texas Tobacco-Free (TTTF) developed an iterative, 4–6-months train-the-trainer program to embed expertise and delivery of sustained education on tobacco-free workplace policies and practices in participating centers. We explore the employee “champions’” train-the-trainer program experiences using a community of practice (CoP) model to identify key contributors to successful program implementation. Across 3 different LMHAs, we conducted semi-structured individual and group interviews online at 2 time points. We interviewed each champion twice (except for 1 champion who dropped out between measurements); pre-implementation (3 group interviews; N = 4 + 4 + 3 = 11 champions); post-implementation (7 individual interviews and 1 group interview; 7 + 3 = 10 champions). Therefore, 11 champions participated in pre- and post-implementation interviews from July 2020–May 2021. Guided by an iterative, thematic analysis and constant comparison process, we inductively coded and summarized data into themes. Five factors contributed to successful program implementation: value of peer support/feedback; building knowledge, champion confidence, and program ownership; informative curriculum, adaptable to targeted populations; staying abreast of current tobacco/nicotine research and products; and TTTF team responsiveness and practical coaching/assistance. Champions reported the TTTF train-the-trainer program was successful and identified attitudes and CoP processes that effectively built organizational capacity and expertise to sustainably address tobacco dependence. Study findings can guide other agencies in implementing sustainable tobacco-free training programs.

Despite prior successful implementation of Taking Texas Tobacco Free (TTTF), an evidence-based tobacco-free workplace program, in local mental health authorities (LMHAs), post-implementation employee attrition necessitated continuing education on tobacco-free policies and tobacco treatment practices. Here, we report on the outcomes of a train-the-trainer program which trained “champions” to deliver tobacco cessation education at their LMHAs. Three LMHAs participated in program implementation via 10 champions, iteratively trained and coached by TTTF. Measures administered evaluated four goals: (1) increase champions’ self-efficacy in delivering trainings, (2) achieve program fidelity via TTTF staff evaluation of trainer effectiveness and knowledge increases among attending employees, (3) achieve stakeholder program acceptability, and (4) achieve program adoption via an increase in follow-up trainings. Champions’ self-efficacy increased throughout TTTF training. TTTF staff ratings of champion-led trainings met the targeted range for trainer effectiveness; employees had a 28.71% knowledge increase over baseline post-training (p < 0.001). Employees rated champions’ training delivery “very good” to “excellent”, on average; both champions and employees were, on average, “satisfied” to “extremely satisfied” with the curriculum and training received. There was an increase over baseline in trainings delivered during follow-up, and trainings increased in length and topic coverage. Ultimately, the train-the-trainer program achieved the intended goals, although not all changes were statistically significant, likely at least partially attributable to small sample sizes. Overall, these results suggest that TTTF’s train-the-trainer program was successful in its delivery and intention to build capacity for the provision of in-house tobacco education trainings to behavioral health employees/providers. However, further evaluation in additional settings, with more champions, et cetera, is necessary to validate these findings, ensure their replicability, link program implementation with reduced patient tobacco use rates, and assess long-term sustainability.

Background: World Health Organization Grade 2 meningiomas (G2Ms) often recur and resist therapies. Grade 2 meningiomas with histopathological necrosis have been associated with worse local control (LC) after radiation therapy, but the drivers and biomarkers of radiation resistance in G2Ms remain unknown. Methods: We performed genetic sequencing and histopathological analysis of 113 G2Ms and investigated the role of genetic and microenvironmental factors on clonogenic survival after ionizing radiation. We performed transcriptional profiling of our in vitro model and 18 human G2M tumors by bulk RNA sequencing as well as 8 G2Ms by single nuclei RNA sequencing. Results: NF2 loss-of-function (LOF) mutations were associated with necrosis in G2Ms (P = .0127). Tumors with NF2 mutation and necrosis had worse post-radiation LC compared to NF2 wildtype tumors without necrosis (P = .035). Under hypoxic conditions, NF2 knockdown increased radiation resistance in vitro (P < .001). Bulk RNA sequencing revealed NF2- and hypoxia-specific changes and a 50-gene set signature specific to radiation-resistant, NF2 knockdown, and hypoxic cells, which distinguished NF2 mutant/necrotic patient G2Ms by unsupervised clustering. Enrichment analysis revealed downregulation of apoptosis pathway genes and upregulation of proliferation-associated genes and genes normally downregulated after UV radiation exposure in NF2-mutant/necrotic tumor cells, which were validated with functional assays. Conclusions: NF2 LOF in the setting of hypoxia confers radiation resistance through transcriptional programs that reduce apoptosis and promote proliferation. These pathways may identify tumors resistant to radiation and represent therapeutic targets that in the future could improve LC in patients with radiation resistant G2Ms.

BACKGROUND AND OBJECTIVES: The body of neurosurgical literature has grown exponentially with publication rates increasing year-over-year. Manual screening of abstracts for systematic review creation and guideline formation has become an arduous process because of the mass of literature. Natural Language Processing, namely, large language models (LLMs), has shown promise in automating the abstract screening process. We evaluated whether Gemini Pro and ChatGPT, two LLM, can automate the screening of abstracts for a guideline created by the Congress of Neurological Surgeons. METHODS: We developed novel pipelines using Gemini Pro and ChatGPT-4o-mini to screen abstracts for guideline creation. We tested our pipeline using abstracts generated from the EMBASE search term provided in a Congress of Neurological Surgeons guideline on Chiari I malformations for a single population, intervention, comparison, and outcome question. We used only two inclusion/exclusion criteria and inputted a simplified version of the research question investigated. RESULTS: Of the 1764 abstracts generated from the search, 22 were manually chosen to be relevant for guideline creation. Using Gemini Pro, 1043 articles were correctly excluded and only 1 was incorrectly excluded, resulting in a sensitivity of 95% and a specificity of 60%. Using ChatGPT-4o-mini, 1066 articles were correctly excluded, but only 4 articles were correctly included, resulting in a sensitivity of 18% and a specificity of 95%. Both pipelines completed the screening process in under 1 hour. CONCLUSION: We have developed novel LLM pipelines to automate abstract screening for neurosurgical guideline creation. This technology can reduce the time necessary for abstract screening processes from several weeks to a few hours. While further validation is required, this process could pave the way for evidence-based guidelines to be continuously updated in real time across medical fields.