Perceived helpfulness of alcohol protective behavioral strategies and consequence severity: A person-centered analysis.

Objective: College students report high rates of alcohol use and negative alcohol-related consequences (ARC). Many studies document that protective behavioral strategy (PBS) use is negatively associated with ARC. Few studies examine consequence severity and PBS helpfulness, both of which may provide nuance to this relationship. Participants and method: The current study used latent profile analysis to examine variability in PBS use, PBS helpfulness, ARC count, and ARC severity patterns among college students (n = 1156). We identified latent profiles and differences in alcohol use and drinking motives across profiles. Results: Three profiles best represented the data: (1) high PBS/low consequences, (2) moderate PBS/moderate consequences, (3) low PBS/high consequences. Conclusions: College students endorsing stronger drinking motives might be less likely to use and select helpful PBS and might experience more severe ARC. Results suggest that simple modifications to common measures can add depth of understanding and nuance to the examination of alcohol-related behaviors.

Assessing invariance of cannabis use motives by veteran status and binary gender identity among college students.

Student service members/veterans (SSM/V) are distinct from non-veteran students in a variety of ways, including in their cannabis use patterns and potentially their motives for cannabis use. Additionally, previous research has shown that men and women endorse different motives for their cannabis use. The present study was designed to assess whether a popular measure of cannabis use motives is invariant across veteran status and gender identity. Based on previous research, we hypothesized that cannabis motives would show invariance across SSM/V men, SSM/V women, non-veteran men, and non-veteran women (n = 1,011, SSM/V = 553) among those who indicated using cannabis at least once in their lifetime. Results from the four-group invariance testing procedure revealed metric invariance. This suggests that while the factor structure and factor loadings are invariant, there are differences at the intercept level for cannabis motives across groups. The same items load onto the same latent constructs and the strength of the items loading onto the latent factors was also the same across groups. The demonstrated invariance has implications for use in SSM/V and non-veteran clients. As this scale is brief, it could easily be used as a screening tool or used to guide intervention content.

Are Smaller Emergency Departments More Prone to Volume Variability?

INTRODUCTION: Daily patient volume in emergency departments (ED) varies considerably between days and sites. Although studies have attempted to define "high-volume" days, no standard definition exists. Furthermore, it is not clear whether the frequency of high-volume days, by any definition, is related to the size of an ED. We aimed to determine the correlation between ED size and the frequency of high-volume days for various volume thresholds, and to develop a measure to identify high-volume days. METHODS: We queried retrospective patient arrival data including 1,682,374 patient visits from 32 EDs in 12 states between July 1, 2018-June 30, 2019 and developed linear regression models to determine the correlation between ED size and volume variability. In addition, we performed a regression analysis and applied the Pearson correlation test to investigate the significance of median daily volumes with respect to the percent of days that crossed four volume thresholds ranging from 5-20% (in 5% increments) greater than each site's median daily volume. RESULTS: We found a strong negative correlation between ED median daily volume and volume variability (R2 = 81.0%; P < 0.0001). In addition, the four regression models for the percent of days exceeding specified thresholds greater than their daily median volumes had R2 values of 49.4%, 61.2%, 70.0%, and 71.8%, respectively, all with P < 0.0001. CONCLUSION: We sought to determine whether smaller EDs experience high-volume days more frequently than larger EDs. We found that high-volume days, when defined as days with a count of arrivals at or above certain median-based thresholds, are significantly more likely to occur in lower-volume EDs than in higher-volume EDs. To the extent that EDs allocate resources and plan to staff based on median volumes, these results suggest that smaller EDs are more likely to experience unpredictable, volume-based staffing challenges and operational costs. Given the lack of a standard measure to define a high-volume day in an ED, we recommend 10% above the median daily volume as a metric, for its relevance, generalizability across a broad range of EDs, and computational simplicity.

Decreased hospital admissions through emergency departments during the COVID-19 pandemic.

STUDY OBJECTIVE: Emergency Department (ED) visits decreased significantly in the United States during the COVID-19 pandemic. A troubling proportion of this decrease was among patients who typically would have been admitted to the hospital, suggesting substantial deferment of care. We sought to describe and characterize the impact of COVID-19 on hospital admissions through EDs, with a specific focus on diagnosis group, age, gender, and insurance coverage. METHODS: We conducted a retrospective, observational study of aggregated third-party, anonymized ED patient data. This data included 501,369 patient visits from twelve EDs in Massachusetts from 1/1/2019-9/9/2019, and 1/1/2020-9/8/2020. We analyzed the total arrivals and hospital admissions and calculated confidence intervals for the change in admissions for each characteristic. We then developed a Poisson regression model to estimate the relative contribution of each characteristic to the decrease in admissions after the statewide lockdown, corresponding to weeks 11 through 36 (3/11/2020-9/8/2020). RESULTS: We observed a 32% decrease in admissions during weeks 11 to 36 in 2020, with significant decreases in admissions for chronic respiratory conditions and non-orthopedic needs. Decreases were particularly acute among women and children, as well as patients with Medicare or without insurance. The most common diagnosis during this time was SARS-CoV-2. CONCLUSION: Our findings demonstrate decreased hospital admissions through EDs during the pandemic and suggest that several patient populations may have deferred necessary care. Further research is needed to determine the clinical and operational consequences of this delay.

Emergency physicians' active patient queues over the course of a shift.

OBJECTIVES: When emergency physicians see new patients in an ad libitum system, they see fewer patients as the shift progresses. However, it is unclear if this reflects a decreasing workload, as patient assessments often span many hours. We sought to investigate whether the size of a physician's queue of active patients similarly declines over a shift. METHODS: Retrospective cohort study, conducted over two years in three community hospitals in the Northeastern United States, with 8 and 9-h shifts. Timestamps of all encounters were recorded electronically. Generalized estimating equations were constructed to predict the number of active patients a physician concurrently managed per hour. RESULTS: We evaluated 64 physicians over a two-year period, with 9822 physician-shifts. Across all sites, physicians managed an increasing queue of active patients in the first several hours. This queue plateaued in the middle of the shift, declining in the final hours, independently of other factors. Physicians' queues of active patients increased slightly with greater volume and acuity, but did not affect the overall pattern of work. Similarly, working alone or with colleagues had little effect on the number of active patients managed. CONCLUSIONS: Emergency physicians in an ad libitum system tend to see new patients until reaching a stable roster of active patients. This pattern may help explain why physicians see fewer new patients over the course of a shift, should be factored into models of throughput, and suggests new avenues for evaluating relationships between physician workload, patient safety, physicians' well-being, and the quality of care.

Staffing and Provider Productivity in the Emergency Department.

Staffing and productivity are key concepts to understand when managing an emergency department. Provider productivity is not static, starts out high, and decreases throughout the shift in a stepwise manner. It is commonly measured by patients per hour or relative value units per hour, and is impacted by factors from the presence of residents to shift length. Appropriate staffing requires thorough understanding of the workforce and the variable patient demand of the department. Matching capacity to this demand potentially improves overall throughput and efficiency. Once knowledgeable about these factors, we provide a case study to showcase their application.

Comparing cannabis use motive item performance between American Indian and White youth.

OBJECTIVE: There is limited research on the motives for engaging in cannabis use for American Indian (AI) youth. The purpose of this study was to explore the differences in cannabis use motives between White and AI youth. METHOD: This study used data from youth living on or near reservations who currently use cannabis and identify as White (n = 156) or AI (n = 922). Students completed a survey containing a measure of cannabis use motives that included coping, recreation, and expansion motives. Eight items, four coping and four recreational/expansion, were evaluated using Item Response Theory. Multi-group analyses were conducted to assess the differences in item functioning between White and AI youth. RESULTS: Three of the four items in the four-item coping model and four items in the recreational/enhancement model exhibited meaningful differential item functioning (DIF). Results suggest that AI youth were more likely to endorse coping reasons for use while White youth were more likely to endorse recreational/expansion reasons for use. CONCLUSIONS: This study provides preliminary evidence that AI and White youth meaningfully differ in their likelihood to endorse coping, recreational, and expansion reasons for cannabis use. These findings highlight the importance of attending to differences between AI and White youth substance use motives, especially when developing culturally competent intervention and prevention strategies.

Risk and Protective Factors of Current Opioid Use Among Youth Living on or Near American Indian Reservations: An Application of Machine Learning.

Opioid use among youth, particularly among American Indian (AI) youth, is rising, resulting in a large number of accidental overdoses and deaths. In order to develop effective prevention strategies, we need to use exploratory data analysis to identify previously unknown predictors of opioid use among youth living on or near reservations. The present study is an application of Machine Learning, a type of exploratory data analysis, to the Our Youth, Our Future epidemiological survey (N = 6482) to determine salient risk and protective factors for past 30-day opioid use. The Machine Learning algorithm identified 11 salient risk and protective factors. Importantly, highest risk was conferred for those reporting recent cocaine use, having ever tried a narcotic other than heroin, and identifying as American Indian. Protective factors included never having tried opioids other than heroin, infrequent binge drinking, having fewer friends pressuring you to use illicit drugs, initiating alcohol use at a later age, and being older. This model explained 61% of the variance in the training sample and, on average, 24% of the variance in the bootstrapped samples. Taken together, this model identifies known predictors of 30-day opioid use, for example, recent substance use, as well as unknown predictors including being AI, Snapchat use, and peer encouragement for use. Notably, recent cocaine use was a more salient predictor of recent opioid use than lifetime opioid use.

Classes of drinking motives among American Indian youth drinkers.

Research exploring American Indian (AI) youth drinking motives and their relation to negative outcomes is critical due to higher rates of alcohol use and early exposure to intoxication in the population. The purpose of this study is to explore classes of drinking motives as they relate to heavy episodic drinking, perceived discrimination, religious importance, ethnic identity, and ethnic pride. This study is part of an ongoing epidemiologic and etiologic investigation of substance use among AI youth drinkers living on or near reservations (n = 1,934, Mage = 15.31). A latent class analysis (LCA) was conducted to discern latent classes of drinking motives. Once latent classes were identified, differences in perceived discrimination, ethnic pride, ethnic identity, religious importance, and heavy episodic drinking were tested. A 2-class solution provided the best overall model fit to the data. The higher coping and enhancement motive class was associated with significantly greater heavy episodic drinking, perceived discrimination, and ethnic identity compared with the low motive class. Further, the class structure did not differ between 7th and 8th graders and 9th-12th graders. Results indicate that among AI youth, the class with strong motives to drink for coping or enhancement had higher ethnic identity, greater risk of heavy episodic drinking, and greater perceived discrimination compared with the class with low motives. Future research should examine additional factors and stressors that may be associated with these classes of drinking motives and are unique to the AI population. (PsycINFO Database Record (c) 2019 APA, all rights reserved).