US State and Territorial Indigenous Consultation Laws: A Potential Strategy to Improve the Social Determinants of Health.

OBJECTIVES: The United Nations (UN) has articulated the right to self-determination as a human right for Indigenous people; however, US states and territories have been slow to operationalize this aspect of the UN Declaration on the Rights of Indigenous Peoples. Indigenous consultation laws require all federal executive agencies to consult with tribal nations before implementing policies that have a "tribal implication," and these form the cornerstone of US efforts to implement the UN Declaration on the Rights of Indigenous Peoples. Despite these federal efforts, less is known about the degree to which state and territorial laws require consultation with Indigenous communities. METHODS: We reviewed all Indigenous consultation laws identified through a search of 50 US states, the District of Columbia, and 5 territories to provide a holistic picture of how jurisdictions have regulated Indigenous consultation efforts. RESULTS: Of the 56 states, 49 (87.5%) had at least 1 Indigenous consultation law; the remaining 7 jurisdictions had none. States engaged in Indigenous consultation in various ways, generally falling into 1 of 3 categories: (1) centralized consultation facilitated through an agency or department, (2) indirect consultation through a designated commission, and (3) fragmented Indigenous consultation through discrete laws. Important gaps were identified, including the lack of a definition for Indigenous consultation, the absence of an appeal process, and the need to train state officials on existing policies. CONCLUSIONS: The results provide a baseline on the degree to which US states and territories consult with Indigenous communities and can be used to identify gaps in US compliance with UN human rights mandates.

Physics-informed scaling laws for the performance of pitching foils in schooling configurations.

This study introduces novel physics-based scaling laws to estimate the propulsive performance of synchronously pitching foils in various schooling configurations. These relations are derived from quasi-steady lift-based and added mass forces. Hydrodynamic interactions among the schooling foils are considered through vortex-induced velocities imposed on them, constituting the ground effect. Generalized scaling equations are formulated for cycle-averaged coefficients of thrust and power. These equations encompass both the pure-pitching and induced velocity terms, capturing their combined effects. The equations are compared to computational results obtained from two-foil systems, exhibiting foil arrangements over a wide range of parameter space, including Strouhal number (0.15 ≤ St ≤ 0.4), pitching amplitude ([Formula: see text]) and phase difference ([Formula: see text]) at Re = 1000-10 000. The individual contributions of pure-pitching and induced velocity terms to propulsive performance elucidate that solely relying on the pure-pitching terms leads to inadequate estimation, emphasizing the significance of the induced velocity terms. The validity of the approach is further assessed by testing it with three-foil and five-foil configurations, which displays a collapse of estimated and measured results. This indicates that the scaling laws are applicable to multi-foil arrangements.

Rural and urban differences in marijuana use following passages of medical marijuana laws.

INTRODUCTION: Understanding differences in post-legalization patterns of marijuana between rural and urban environments has the potential to go a long way towards targeting intervention efforts aimed at reducing marijuana use disorders. METHODS: Data come from the National Survey on Drug Use and Health (NSDUH, 2015-2019, N = 210,392). Survey-weighted multivariable linear and logistic regression analyses were used to assess the relationship between key marijuana-related variables and the status of medical marijuana use in each state with interaction terms for rural versus urban status. RESULTS: Among the entire sample, the prevalence of marijuana abuse and dependence were 0.7% and 1.8%, respectively. Among marijuana users, the average number of days on which marijuana was used was 131.3 (SD = 136.3) days. Those living in states with legalized medical marijuana reported use on a greater number of days (B = 10.69; 95% CI: 5.26, 16.13) with frequency of use increasing as rurality increased, compared to a core based statistical area (CBSA) of ≥1 million: a CBSA of <1 million residents (B = 23.02; 95% CI: 17.38, 28.66) and non-CBSA (B = 37.62; 95% CI: 22.66, 52.58). We also observed lower odds of driving under the influence of marijuana in states where medical marijuana was legal (aOR = 0.86; 95% CI: 0.77, 0.95). CONCLUSION: We observed an increase in the frequency of marijuana use and a decrease in driving under the influence of marijuana in states with legalized medical marijuana use relative to those states where it remained illegal. We also observed key moderation based on rural-urban status. This body of results suggests that problematic marijuana use may be on the rise following the legalization of marijuana use, but also that corresponding protective attitudes exist.

The effects of rule changes in football-code team sports: a systematic review.

Rule changes within football-code team sports aim to improve performance, enhance player welfare, increase competitiveness, and provide player development opportunities. This manuscript aimed to review research investigating the effects of rule changes in football-code team sports. A systematic search of electronic databases (PubMed, ScienceDirect, CINAHL, MEDLINE, and SPORTDiscus) was performed to August 2023; keywords related to rule changes, football-code team sports, and activity type. Studies were excluded if they failed to investigate a football-code team sport, did not quantify the change of rule, or were review articles. Forty-six studies met the eligibility criteria. Four different football codes were reported: Australian rules football (n = 4), rugby league (n = 6), rugby union (n = 16), soccer (n = 20). The most common category was physical performance and match-play characteristics (n = 22). Evidence appears at a high risk of bias partly due to the quasi-experimental nature of included studies, which are inherently non-randomised, but also due to the lack of control for confounding factors within most studies included. Rule changes can result in unintended consequences to performance (e.g., longer breaks in play) and effect player behaviour (i.e., reduce tackler height in rugby) but might not achieve desired outcome (i.e., unchanged concussion incidence). Coaches and governing bodies should regularly and systematically investigate the effects of rule changes to understand their influence on performance and injury risk. It is imperative that future studies analysing rule changes within football codes account for confounding factors by implementing suitable study designs and statistical analysis techniques.

Symbiogenesis redicts the monism of the cosmos.

Symbiogenesis has been systematically exploited to understand consciousness as the aggregate of our physiology. The Symbiogenic mechanism for assimilation of factors in the environment formulates the continuum from inside the cell to the Cosmos, both consciousness and cosmology complying with the Laws of Nature. Since Symbiogenesis is 'constructive', whereas eliminating what threatens us is 'destructive', why do we largely practice Symbiogenesis? Hypothetically, Symbiogenesis recursively simulates the monism of our origin, recognizing 'something bigger than ourselves'. That perspective explains many heretofore unexplained aspects of consciousness, such as mind, epigenetic inheritance, physiology, behaviors, social systems, mathematics, the Arts, from an a priori perspective. Moreover, there is an energetic continuum from Newtonian to Quantum Mechanics, opening up to a novel way of understanding the 'true nature of our being', not as 'materialism', but instead being the serial homeostatic control of energy. The latter is consistent with the spirit of Claude Bernard and Walter B. Cannon's perspectives on physiology. Such a paradigm shift is overdue, given that materialism is causing the destruction of the Earth and ourselves.

The potential of developing high hepatic clearance drugs via controlled release: Lessons from Kirchhoff's Laws.

When a new molecular entity is predicted to exhibit high clearance in humans, pharmaceutical sponsors almost universally search for similar acting back-up compounds that will demonstrate low clearance. Here we show that, except for oral dosing, there can be marked advantages to developing and commercializing controlled release formulations of high clearance drugs, the expertise of readers of this journal. Our recent publications demonstrate that the universally held pharmacokinetic principle that drug delivery rate has no effect on measured drug clearance is not correct. Rather, we show that if clearance from the drug delivery site is markedly less than the iv bolus clearance of a drug, the in vivo drug clearance can be the drug delivery clearance controlled by the designed dosage form. This approach will be especially advantageous for high hepatic clearance drugs. These advantages include not being concerned with: a) saturable nonlinear kinetics, b) significant pharmacogenomic differences, c) drug-drug induction mechanisms, and d) in many cases drug-drug inhibition interactions. This is due to the ability of a drug sponsor to design clearance, independent of the pharmacokinetic characteristics for high clearance compounds, where clearance from the dosage form becomes the drug clearance from the patient. Recognition of this principle, as described here, results from our development of the use of Kirchhoff's Laws from physics to derive rate-defining clearance and rate constant elimination processes independent of differential equation derivations. The key message for readers of this journal is that high clearance drugs are potentially drugable through formulation design and should not be outright disregarded, since for such drugs the dose-corrected area under the curve can be increased if the release rate from the injection site is controlled and slow resulting in drug clearance from the body controlled by clearance from the dosage form. The concepts presented here describe previously unrecognized advantages of controlled release formulations.

Assessing risk for severe domestic violence and related homicides perpetrated by partners and in-laws: adapted danger assessments for women in abusive relationships in India.

Despite domestic violence and related homicides perpetrated by partners and/or in-laws being a significant public health problem in India, there are no reliable and valid instruments to identify and intervene with women in domestic violence relationships. Continued domestic violence can escalate to severe, near-lethal, or lethal violence or homicide. The Danger Assessment (DA) is a risk assessment instrument designed to assess the likelihood of severe, near-lethal, or lethal violence in abusive relationships. However, the DA is not designed to determine the risk of future severe, near-lethal, or lethal violence by in-laws. In-law abuse plays a significant role in domestic violence-related homicides in India and other countries with similar cultural norms. This study addressed this gap by developing the Danger Assessment for in-laws (DA-L) to assess risk from in-laws, alongside the Danger Assessment for Women in India (DA-WI) to assess risk from partners. The study also examined the psychometric properties of the DA-L and DA-WI. Longitudinal data from 150 women in India were used to measure the reliability and validity of the two versions of the DA. The original DA items and additional risk items were examined using relative risk ratios for their relationship with severe violence at three-month follow-ups. Predictive validity was tested with the receiver operating characteristic curve. The study resulted in reliable and valid measures (11 items DA-L and 26-items DA-WI) of risk. The versions of the DA can be useful for practitioners in India and those working with Indian women in the US and other countries. The DAs can be used for identifying women in domestic violence relationships who are at risk for future severe domestic violence and guide the provision of tailored safety plans.

The effect of vertical identification card laws on teenage tobacco and alcohol use.

We study the impact of vertical identification card laws, which changed the orientation of driver's licenses and state identification cards from horizontal to vertical for those under 21 years, on teenage tobacco and alcohol use. We study this question using four national datasets (pooled national and state Youth Risk Behavior Surveillance System, National Youth Tobacco Survey, Current Population Survey to Tobacco Use Supplements, and Behavioral Risk Factor Surveillance System). We improve previous databases of vertical ID law implementation by using original archival research to identify the exact date of the law change. We estimate models using standard two-way fixed effects and stacked difference-in-differences that avoid bias from dynamic and heterogeneous treatment effects. Using data through 2021, we do not find evidence of reductions in teenage tobacco and alcohol use. While these laws reduce retail-based purchasing, they also increase social sourcing, thus leading to no net impact on use.

My Way to School Through a Camera Lens: Involving Children to Inform a Policy Recommendation on Active School Travel.

Active school travel (AST) is an effective approach for increasing children's physical activity and independent mobility, but policy supporting AST is lacking. This study aims to explore children's experiences of AST to inform a policy recommendation. Photovoice methodology with a qualitative approach was applied, with children taking pictures on their way to school. This was followed by focus groups where the children explored their experiences of AST based on their photos. The data were analyzed using qualitative content analysis. The results show that the children valued independent mobility and wanted to be involved in decisions about their travels; they also expressed feelings of increased responsibility and personal growth as a consequence. Although the children recognized areas of improvement regarding infrastructure, especially regarding heavy traffic that jeopardized travel safety, they continued using AST. Finally, the children talked about the value of the health and environmental benefits of AST. Opportunities for friendship, play, and making decisions about their own time were highlighted as important incentives. The benefits from AST are many for children, as well as for society. The result has informed policy recommendations for AST, and the children's input will be used to communicate the recommendations. Listening to the voices of children could be a steppingstone toward forming future healthy mobility initiatives. In that process, it is key to include children's perspectives when formulating the AST policy for successful adoption and implementation.

Using qualitative system dynamics modeling to understand overdose bystander behavior in the context of Connecticut's Good Samaritan Laws and identify effective policy options.

BACKGROUND: Good Samaritan Laws are a harm reduction policy intended to facilitate a reduction in fatal opioid overdoses by enabling bystanders, first responders, and health care providers to assist individuals experiencing an overdose without facing civil or criminal liability. However, Good Samaritan Laws may not be reaching their full impact in many communities due to a lack of knowledge of protections under these laws, distrust in law enforcement, and fear of legal consequences among potential bystanders. The purpose of this study was to develop a systems-level understanding of the factors influencing bystander responses to opioid overdose in the context of Connecticut's Good Samaritan Laws and identify high-leverage policies for improving opioid-related outcomes and implementation of these laws in Connecticut (CT). METHODS: We conducted six group model building (GMB) workshops that engaged a diverse set of participants with medical and community expertise and lived bystander experience. Through an iterative, stakeholder-engaged process, we developed, refined, and validated a qualitative system dynamics (SD) model in the form of a causal loop diagram (CLD). RESULTS: Our resulting qualitative SD model captures our GMB participants' collective understanding of the dynamics driving bystander behavior and other factors influencing the effectiveness of Good Samaritan Laws in the state of CT. In this model, we identified seven balancing (B) and eight reinforcing (R) feedback loops within four narrative domains: Narrative 1 - Overdose, Calling 911, and First Responder Burnout; Narrative 2 - Naloxone Use, Acceptability, and Linking Patients to Services; Narrative 3 - Drug Arrests, Belief in Good Samaritan Laws, and Community Trust in Police; and Narrative 4 - Bystander Naloxone Use, Community Participation in Harm Reduction, and Cultural Change Towards Carrying Naloxone. CONCLUSIONS: Our qualitative SD model brings a nuanced systems perspective to the literature on bystander behavior in the context of Good Samaritan Laws. Our model, grounded in local knowledge and experience, shows how the hypothesized non-linear interdependencies of the social, structural, and policy determinants of bystander behavior collectively form endogenous feedback loops that can be leveraged to design policies to advance and sustain systems change.

Firearm Ownership: A Key Factor to Consider in Firearm Suicide Deaths in Children, Despite State Gun Laws.

INTRODUCTION: Firearm-related suicides among children present a significant public health concern and a tragic loss of young lives. This study explores the relationship between firearm-related suicides, gun ownership, and state-specific gun laws. METHODS: This retrospective cohort study collected data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research on children under 18 who died by firearm-related suicides between 2009 and 2016 in all 50 states and D.C. It also utilized data from the RAND State-Level Estimates of Household Firearm Ownership. The study focused on the rate of child firearm suicide deaths per 100,000 individuals. The key variable of interest was the percentage of guns owned per household in each state. Univariable analysis was conducted to examine the association between individual gun laws and child firearm suicide mortalities, while multivariable regression, adjusting for household gun ownership and significant firearm legislation, was employed to assess connection to child firearm suicide mortality. RESULTS: From 2009 to 2016, 3903 children died from firearm-related suicides in the United States. In our analysis, 15 out of 44 firearm laws were found to be associated with reducing the rates of firearm suicides among children (P < 0.05). However, multivariable regression showed that higher state gun ownership rates were the primary predictor of increased child fatalities from firearms, with children in such states being 325% more likely to die when analyzing handgun laws and 337% more likely when analyzing long gun laws, as indicated by coefficients of 4.25 and 4.37, respectively. No state laws alone notably improved death rates. CONCLUSIONS: Gun ownership has a stronger association with child suicide rates than state-specific gun laws. Given the weight of gun ownership, future research should prioritize comprehensive public health initiatives to prevent child firearm-related suicides.

Flow Behavior of Nanoparticle Agglomerates in a Fluidized Bed Simulated with Porous-Structure-Based Drag Laws.

Fluidization bed reactor is an attractive method to synthesize and process quantities of functional nanoparticles, due to the large gas-solid contact area and its potential scalability. Nanoparticles fluidize not individually but as a form of porous agglomerates with a typical porosity above 90%. The porous structure has a significant effect on the hydrodynamic behavior of a single nanoparticle agglomerate, but its influence on the flow behavior of nanoparticle agglomerates in a fluidized bed is currently unclear. In the present study, a drag model was developed to consider the porous structure effects of nanoparticle agglomerates by incorporating porous-structure-based drag laws in the Eulerian-Eulerian two-fluid model. Numerical simulations were performed from particulate to bubbling fluidization state to evaluate the applicability of porous-structure-based drag laws. Results obtained for the minimum fluidization and bubbling velocities, bed expansion ratio, and agglomerate dispersion coefficient show that, compared with the drag law of solid sphere, the porous-structure-based drag laws, especially the drag law of fractal porous spheres, provide a closer fit to the experimental data. This indicates that the pore structures have a great impact on gas-solid flow behavior of nanoparticle agglomerates, and the porous-structure-based drag laws are more suitable for describing flows in nanoparticle agglomerate fluidized beds.

Demographic characteristics and trends of cell phone use while driving citations in selected states in the United States, 2010-2020.

OBJECTIVE: Distracted driving is a leading cause of motor vehicle crashes, and cell phone use is a major source of in-vehicle distraction. Many states in the United States have enacted cell phone use laws to regulate drivers' cell phone use behavior to enhance traffic safety. Numerous studies have examined the effects of such laws on drivers' cell phone use behavior based on self-reported and roadside observational data. However, little was known about who actually violated the laws at the enforcement level. This study sought to uncover the demographic characteristics of drivers cited for cell phone use while driving and whether these characteristics changed over time since the enactment of cell phone laws. METHODS: We acquired useable traffic citation data for 7 states in the United States from 2010 to 2020 and performed descriptive and regression analyses. RESULTS: Male drivers were cited more for cell phone use while driving. Handheld and texting bans were associated with a greater proportion of cited drivers aged 40 and above, compared to texting-only bans. Trends in the citations issued based on drivers' age group following the enactment of different cell phone laws were also uncovered. The proportion of citations issued to drivers aged 60 and above increased over time but the temporal trend remained insignificant when population effect was considered. CONCLUSIONS: This study examined the demographic characteristics of drivers cited for cell phone use while driving in selected states with texting-only bans or handheld and texting bans. The results reveal policy-based differences in trends in the proportion of citations issued to drivers in different age groups.

Does an App a Day Keep the Doctor Away? AI Symptom Checker Applications, Entrenched Bias, and Professional Responsibility.

The growing prominence of artificial intelligence (AI) in mobile health (mHealth) has given rise to a distinct subset of apps that provide users with diagnostic information using their inputted health status and symptom information-AI-powered symptom checker apps (AISympCheck). While these apps may potentially increase access to health care, they raise consequential ethical and legal questions. This paper will highlight notable concerns with AI usage in the health care system, further entrenchment of preexisting biases in the health care system and issues with professional accountability. To provide an in-depth analysis of the issues of bias and complications of professional obligations and liability, we focus on 2 mHealth apps as examples-Babylon and Ada. We selected these 2 apps as they were both widely distributed during the COVID-19 pandemic and make prominent claims about their use of AI for the purpose of assessing user symptoms. First, bias entrenchment often originates from the data used to train AI systems, causing the AI to replicate these inequalities through a "garbage in, garbage out" phenomenon. Users of these apps are also unlikely to be demographically representative of the larger population, leading to distorted results. Second, professional accountability poses a substantial challenge given the vast diversity and lack of regulation surrounding the reliability of AISympCheck apps. It is unclear whether these apps should be subject to safety reviews, who is responsible for app-mediated misdiagnosis, and whether these apps ought to be recommended by physicians. With the rapidly increasing number of apps, there remains little guidance available for health professionals. Professional bodies and advocacy organizations have a particularly important role to play in addressing these ethical and legal gaps. Implementing technical safeguards within these apps could mitigate bias, AIs could be trained with primarily neutral data, and apps could be subject to a system of regulation to allow users to make informed decisions. In our view, it is critical that these legal concerns are considered throughout the design and implementation of these potentially disruptive technologies. Entrenched bias and professional responsibility, while operating in different ways, are ultimately exacerbated by the unregulated nature of mHealth.

α,ß,γ- Neutrosophic aggregation operators and their applications in the software site selection.

In this paper, we expended the concept of neutrosophic sets (NS) by introducing the idea α,ß,γ- neutrosophic set (α,ß,γ- NS). The existing models under conventional NSs, fail to adequately address the management of membership degree influence during the aggregation process. While the proposed framework manages the influence of membership degree (MD), indeterminacy membership degree (IMD), and non-membership degree (NMD) by incorporating parameters α, ß, and γ. Furthermore, we defined some fundamental operational laws for α,ß,γ- NSs and introduced a series of aggregation operators (AOs) to effectively combine α,ß,γ- neutrosophic information. Based on these AOs, a new Multiple Criteria Decision Making (MCDM) model is proposed for solving real-life decision-making (DM) challenges. An illustrative case study is presented to showcase the effectiveness of the proposed model in selecting an optimal location for a software office. The article concludes by validating the proposed model's authenticity and effectiveness through a comparative analysis with existing approaches.

Law compliance decision making for autonomous vehicles on highways.

As autonomous driving advances, autonomous vehicles will share the road with human drivers. This requires autonomous vehicles to adhere to human traffic laws under safe conditions. Simultaneously, when confronted with dangerous situations, autonomous driving should also possess the capability to deviate from traffic laws to ensure safety. However, current autonomous vehicles primarily prioritize safety and collision avoidance in their decision-making and planning. This may lead to misunderstandings and distrust from human drivers in mixed traffic flow, and even accidents. To address this, this paper proposes a decoupled hierarchical framework for compliance safety decision-making. The framework primarily consists of two layers: the decision-making layer and the motion planning layer. In the decision-making layer, a candidate behavior set is constructed based on the scenario, and a dual layer admission assessment is utilized to filter out unsafe and non-compliant behaviors from the candidate sets. Subsequently, the optimal behavior is selected as the decision behavior according to the designed evaluation metrics. The decision-making layer ensures that the vehicle can meet lane safety requirements and comply with static traffic laws. In the motion planning layer, the surrounding vehicles and the road are modeled as safety potential fields and traffic laws potential fields. Combining the optimal decision behavior, they are incorporated into the cost function of the model predictive control to achieve compliant and safe trajectory planning. The planning layer ensures that the vehicle meets trajectory safety requirements and complies with dynamic traffic laws under safe conditions. Finally, four typical scenarios are used to evaluate the effectiveness of the proposed method. The results indicate that the proposed method can ensure compliance in safe conditions while also temporarily deviating from traffic laws in emergency situations to ensure safety.

Range-limited Heaps' law for functional DNA words in the human genome.

Heaps' or Herdan-Heaps' law is a linguistic law describing the relationship between the vocabulary/dictionary size (type) and word counts (token) to be a power-law function. Its existence in genomes with certain definition of DNA words is unclear partly because the dictionary size in genome could be much smaller than that in a human language. We define a DNA word as a coding region in a genome that codes for a protein domain. Using human chromosomes and chromosome arms as individual samples, we establish the existence of Heaps' law in the human genome within limited range. Our definition of words in a genomic or proteomic context is different from other definitions such as over-represented k-mers which are much shorter in length. Although an approximate power-law distribution of protein domain sizes due to gene duplication and the related Zipf's law is well known, their translation to the Heaps' law in DNA words is not automatic. Several other animal genomes are shown herein also to exhibit range-limited Heaps' law with our definition of DNA words, though with various exponents. When tokens were randomly sampled and sample sizes reach to the maximum level, a deviation from the Heaps' law was observed, but a quadratic regression in log-log type-token plot fits the data perfectly. Investigation of type-token plot and its regression coefficients could provide an alternative narrative of reusage and redundancy of protein domains as well as creation of new protein domains from a linguistic perspective.

Reaching the ceiling? Empirical scaling behaviour for deep EEG pathology classification.

Machine learning techniques, particularly deep convolutional neural networks (ConvNets), are increasingly being used to automate clinical EEG analysis, with the potential to reduce the clinical burden and improve patient care. However, further research is required before they can be used in clinical settings, particularly regarding the impact of the number of training samples and model parameters on their testing error. To address this, we present a comprehensive study of the empirical scaling behaviour of ConvNets for EEG pathology classification. We analysed the testing error with increasing the training samples and model size for four different ConvNet architectures. The focus of our experiments is width scaling, and we have increased the number of parameters to up to 1.8 million. Our evaluation was based on two publicly available datasets: the Temple University Hospital (TUH) Abnormal EEG Corpus and the TUH Abnormal Expansion Balanced EEG Corpus, which together contain 10,707 training samples. The results show that the testing error follows a saturating power-law with both model and dataset size. This pattern is consistent across different datasets and ConvNet architectures. Furthermore, empirically observed accuracies saturate at 85%-87%, which may be due to an imperfect inter-rater agreement on the clinical labels. The empirical scaling behaviour of the test performance with dataset and model size has significant implications for deep EEG pathology classification research and practice. Our findings highlight the potential of deep ConvNets for high-performance EEG pathology classification, and the identified scaling relationships provide valuable recommendations for the advancement of automated EEG diagnostics.

Firearm-Related Juvenile Death Rates Correlate With Gun Ownership Rates, Measures of Guns in Circulation, and Leniency of Existing Firearm Laws Among U.S. States.

INTRODUCTION: Firearms now represent the leading cause of death in U.S. children. Therefore, this study aimed to determine if state-level rates of gun ownership, guns in circulation, and strictness of firearm-related laws are related to firearm-related mortality among both juveniles and overall populations. MATERIALS AND METHODS: State firearm mortality rates among the juvenile and overall populations were obtained from 2010 to 2020. The number of weapons registered with the Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF) and federal firearms licensees for each state were also recorded. Giffords Law Center Scorecard Rankings, a relative measure of the restrictiveness of each state's gun laws, were also collected. Unadjusted linear regressions modeled the relationships between firearm-associated mortality and ATF-registered weapons, federal firearm licensees, Giffords Center rankings, and gun ownership rates. Multivariable (adjusted) analyses were performed to control for poverty, unemployment, and poor mental health. RESULTS: Unadjusted analyses demonstrated that higher gun ownership rates and more lenient gun laws were associated with increased firearm-associated mortality among juveniles. Similarly, these measures as well as increased ATF-registered weapons and ATF federal firearm licensees were associated with increased firearm mortality in the overall population. In the adjusted analyses, more ATF-registered weapons, more ATF federal firearm licensees, higher gun ownership rates, and more lenient firearm laws were associated with increased firearm-related mortality in the overall population, while increased gun ownership and higher Giffords Center rankings were associated with increased firearm-associated mortality in the pediatric population. CONCLUSIONS: To reduce the toll of gun violence in the United States, policymakers should focus on implementing more restrictive firearm laws and reducing the prevalence of guns in their communities.

Using theoretical constraints and the TASI taxonomy to delineate predictably replicable findings.

The focus of the present article is not on failures to replicate but on the more optimistically framed and more fruitful question: What stable findings can be reproduced reliably and can be trusted by decision makers, managers, health agents, or politicians? We propagate the working hypothesis that a twofold key to stable and replicable findings lies in the existence of theoretical constraints and, no less important, in researchers' sensitivity to metatheoretical, auxiliary assumptions. We introduce a hierarchy of four levels of theoretical constraints-a priori principles, psychophysical, empirical, and modelling constraints-combined with the TASI taxonomy of theoretical, auxiliary, statistical, and inferential assumptions Trafimow, Journal for the Theory of Social Behaviour, 52, 37-48, (2022). Although theoretical constraints clearly facilitate stable and replicable research findings, TASI reminds us of various reasons why even perfectly valid hypotheses need not always be borne out. The presented framework should help researchers to operationalize conditions under which theoretical constraints render empirical findings most predictable.