A Statistical Analysis of the Impact of Gun Ownership on Mass Shootings in the USA Between 2013 and 2022.

Mass shootings (incidents with four or more people shot in a single event, not including the shooter) are becoming more frequent in the United States, posing a significant threat to public health and safety in the country. In the current study, we intended to analyze the impact of state-level prevalence of gun ownership on mass shootings-both the frequency and severity of these events. We applied the negative binomial generalized linear mixed model to investigate the association between gun ownership rate, as measured by a proxy (i.e., the proportion of suicides committed with firearms to total suicides), and population-adjusted rates of mass shooting incidents and fatalities at the state level from 2013 to 2022. Gun ownership was found to be significantly associated with the rate of mass shooting fatalities. Specifically, our model indicated that for every 1-SD increase-that is, for every 12.5% increase-in gun ownership, the rate of mass shooting fatalities increased by 34% (p value < 0.001). However, no significant association was found between gun ownership and rate of mass shooting incidents. These findings suggest that restricting gun ownership (and therefore reducing availability to guns) may not decrease the number of mass shooting events, but it may save lives when these events occur.

Overestimation of Balance Ability Among Older Adults at Risk for Falls.

Objective: This study examined alignment of subjective balance confidence with Stopping Elderly Accidents, Deaths and Injuries (STEADI) fall risk. Methods: Cross-sectional analysis of 155 community-dwelling adults (60 + y/o) from 2016 to 2018 who completed a STEADI fall assessment. Descriptive statistics, Chi-Square analysis, and biserial point correlations were applied. Results: Adults who overestimate balance confidence, 55.6% (n = 50) reported a fall in the past year, 62.2% (n = 56) were worried about falling, 48.9% (n = 44) felt unsteady when standing/walking, and 70.0% (n = 63) had a score of ≥4 on the Stay Independent Questionnaire (SIQ). Physical performance for these adults were mean TUG score 10.9s (SD = 3.4), mean 30 second chair stands 10.8 (SD = 3.5), and mean 4-stage balance score 3.1 (SD = .76). Discussion: Older adults are more likely to overestimate their subjective balance confidence. Individuals are equally likely to have reported a fall in the past year if they were "at fall risk," regardless of their subjective balance confidence.

Analyzing the impact of state gun laws on mass shootings in the United States from 2013 to 2021.

OBJECTIVES: Mass shooting incidents have drastically increased in the United States in the last 10 years, with a disproportionate number of incidents occurring in some states. Gun laws vary greatly by state, but little research has been conducted to examine the association between the strength of state gun laws and mass shootings. This study aims to explore the aggregate effect of state gun laws on the rate of mass shooting incidents and fatalities. STUDY DESIGN: This was a cross-sectional time series. METHODS: This study applied the negative binomial generalized linear mixed model to assess the impact of state gun laws restrictiveness-as measured by the total number of active gun laws-on the rate of mass shooting incidents and fatalities. RESULTS: The restrictiveness of state gun laws was significantly associated with the rate of mass shooting fatalities; specifically, for every 1 standard deviation (SD) increase in the state gun law restrictiveness score (i.e. for every additional 27 gun laws in place), the rate of mass shooting fatalities was decreased by 24% (P-value <0.0001), controlling for other predictor variables in the model. However, no significant association was found between the restrictiveness of state gun laws and rate of mass shooting incidents. CONCLUSIONS: State gun laws may not decrease the number of mass shooting events, but they appear to help reduce the number of deaths when these mass shootings occur. Better data collection on mass shootings and further research on the impacts of specific gun laws are needed to help understand the effectiveness of gun laws and inform law-based interventions.

The Impacts of the COVID-19 Pandemic on Doctor of Physical Therapy Students: A National Survey.

INTRODUCTION: Since the lockdown in March 2020, the COVID-19 pandemic has inevitably affected all individuals across the world. The purpose of this study was to determine the perceived impacts of the pandemic on doctor of physical therapy (DPT) students and if there were any statistically significant differences based on minority status, gender, or class standing. REVIEW OF LITERATURE: Literature suggested that DPT students experienced negative impacts of the pandemic on academic success and mental health. However, there is a lack of comprehensive understanding of the perceived physical, mental, financial, and academic impacts of the COVID-19 pandemic by physical therapist students nationally. SUBJECTS: Convenience sampling was used to recruit all students enrolled in physical therapist programs in the United States. METHODS: The research design was a cross-sectional survey administered electronically using the Alchemer survey platform with 12 Likert scale items compiled in the physical, mental, financial, and academic domains. All items were designed to evaluate the perceived impacts of the pandemic on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). RESULTS: A total of 1,230 completed responses were received. The mean responses were 3.45 (SD 1.12), 3.48 (SD 0.92), 2.74 (SD 1.03), and 3.33 (SD 0.93) for the physical, mental, financial, and academic domains, respectively. No significant difference was found based on minority status. A statistically significant difference was found in the mental domain, with female students perceiving a more negative impact by the pandemic. First-year students reported a significantly higher negative impact in the physical domain compared with second-year students. The perceived impact in the academic domain was significantly higher for both first- and second-year students than third-year students. CONCLUSIONS: Developing and promoting access to campus and community resources to address the challenges caused by the COVID-19 pandemic is critical to facilitating student success during and after the pandemic.

Statistical inferences on nonconstant relative potency with quantal response data.

Relative potency is widely used in toxicological and pharmacological studies to characterize potency of chemicals. The relative potency of a test chemical compared to a standard chemical is defined as the ratio of equally effective doses (standard divided by test). This classical concept relies on the assumption that the two chemicals are toxicologically similar-that is, they have parallel dose-response curves on log-dose scale-and thus have constant relative potency. Nevertheless, investigators are often faced with situations where the similarity assumption is deemed unreasonable, and hence the classical idea of constant relative potency fails to hold; in such cases, simply reporting a single constant value for relative potency can produce misleading conclusions. Relative potency functions, describing relative potency as a function of the mean response (or other quantities), is seen as a useful tool for handling nonconstant relative potency in the absence of similarity. Often, investigators are interested in assessing nonconstant relative potency at a finite set of some specific response levels for various regulatory concerns, rather than the entire relative potency function; this simultaneous assessment gives rise to multiplicity, which calls for efficient statistical inference procedures with multiplicity adjusted methods. In this paper, we discuss the estimation of relative potency at multiple response levels using the relative potency function, under the log-logistic dose-response model. We further propose and evaluate three approaches to calculating multiplicity-adjusted confidence limits as statistical inference procedures for assessing nonconstant relative potency. Monte Carlo simulations are conducted to evaluate the characteristics of the simultaneous limits.

Severe Pain in Veteran Students.

BACKGROUND: Severe pain is prevalent in military veterans. Veteran students face significant challenges in attaining academic success. Understanding the impact of pain on learning of veteran students is very important to better advocate for veteran students and promote social responsibility and cultural competence. OBJECTIVE: The objective of the research was to determine pain in veteran students compared to nonveteran students. DESIGN: The research design was a cross-sectional non-experimental survey. METHODS: The survey included a total of 6 questions adapted from the National Health Interview Survey and was administered using SurveyGizmo. RESULTS: Veteran students are 4.3 times more likely to report severe pain than nonveteran students. 98.6% veteran students reported pain and 22.2% had severe pain. 25.0% of veteran students reported the ability to carry out daily work limited by pain. Only 4.2% of veteran students reported sufficient resources on campus helping them deal with pain, while 58.3% reported sufficient resources off campus. CONCLUSIONS: Veteran students had statistically significantly more severe pain. They were more limited by pain in carrying out daily work and reported fewer resources to help them cope with pain. The data can inform strategies for advocacy activities of physical therapists and assessment for culturally competent education.

Multiplicity-Adjusted Confidence Limits in Risk Assessment with Quantal Response Data.

In risk assessment, it is often desired to make inferences on the risk at certain low doses or on the dose(s) at which a specific benchmark risk (BMR) is attained. At times, [Formula: see text] dose levels or BMRs are of interest, and some form of multiplicity adjustment is necessary to ensure a valid [Formula: see text] simultaneous inference. Bonferroni correction is often employed in practice for such purposes. Though relative simple to implement, the Bonferroni strategy can suffer from extreme conservatism (Nitcheva et al., 2005; Al-Saidy et al., 2003). Recently, Kerns (2017) proposed the use of simultaneous hyperbolic and three-segment bands to perform multiple inferences in risk assessment under Abbott-adjusted log-logistic model with the dose level constrained to a given interval. In this paper, we present and compare methods for deriving multiplicity-adjusted upper limits on extra risk and lower bounds on the benchmark dose under Abbott-adjusted log-logistic model. Monte Carlo simulations evaluate the characteristics of the simultaneous limits. An example is given to illustrate the use of the methods.

A cellular automata model of bone formation.

Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model.

Simultaneous confidence bands for log-logistic regression with applications in risk assessment.

In risk assessment, it is often desired to make inferences on the low dose levels at which a specific benchmark risk is attained. Applications of simultaneous hyperbolic confidence bands for low-dose risk estimation with quantal data under different dose-response models (multistage, Abbott-adjusted Weibull, and Abbott-adjusted log-logistic models) have appeared in the literature. The use of simultaneous three-segment bands under the multistage model has also been proposed recently. In this article, we present explicit formulas for constructing asymptotic one-sided simultaneous hyperbolic and three-segment bands for the simple log-logistic regression model. We use the simultaneous construction to estimate upper hyperbolic and three-segment confidence bands on extra risk and to obtain lower limits on the benchmark dose by inverting the upper bands on risk under the Abbott-adjusted log-logistic model. Monte Carlo simulations evaluate the characteristics of the simultaneous limits. An example is given to illustrate the use of the proposed methods and to compare the two types of simultaneous limits at very low dose levels.