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Drug use disorders (DUDs) represent a major global health challenge, leading to substantial morbidity and mortality, while also being compounded by social and structural barriers. In this study, we examined global epidemiological trends in DUDs over the past three decades to inform clinical and public health responses. We extracted data on the incidence, deaths, and disability-adjusted life years (DALYs) attributable to DUDs from the 2021 Global Burden of Diseases, Injuries, and Risk Factors Study between 1990 and 2021. Age-standardized incidence (ASIR), mortality (ASMR), and DALY rates per 100,000 population were calculated. The analysis focused on four DUDs—opioid, amphetamine, cocaine, and cannabis use disorders—and further stratified rates by sex, Socio-demographic Index (SDI), countries, and world regions. In 2021, there were 13.6 (95% UI, 11.6–15.7) million new cases, 137,278 (95% UI, 129,269–146,181) deaths, and 15.6 (95% UI, 12.8–18.1) million DALYs attributed to DUDs. Between 1990 and 2021, the ASIR decreased by 8.1%, while the ASMR and DALY rates rose by 30.8% and 14.8%, respectively. Opioid use disorder accounted for the highest ASIR (169.4 [95% UI, 145.1–195.0] per 100,000), ASMR (1.7 [95% UI, 1.6–1.8] per 100,000), and age-standardized DALY rate (191.0 [95% UI, 156.1–222.8] per 100,000) in 2021. Sex and geographical variations were notable, with males and world regions like high-income North America, Australasia, and Eastern/Western Europe showing disproportionately higher rates. Overall, these findings highlight rising mortality and morbidity rates despite a modest decline in incidence, underscoring the need for tailored public health interventions, advancing harm reduction programs, and expanding access to treatment.

Microbial species must compete for space and nutrients to persist in the gastrointestinal (GI) tract, and our understanding of the complex pathobiont-microbiota interactions is far from complete. Klebsiella pneumoniae , a problematic, often drug-resistant nosocomial pathogen, can colonize the GI tract asymptomatically, serving as an infection reservoir. To provide insight on how K. pneumoniae interacts with the resident gut microbiome, we conduct a transposon mutagenesis screen using a murine model of GI colonization with an intact microbiota. Among the genes identified were those encoding a type VI secretion system (T6SS), which mediates contact-dependent killing of gram-negative bacteria. From several approaches, we demonstrate that the T6SS is critical for K. pneumoniae gut colonization. Metagenomics and in vitro killing assays reveal that K. pneumoniae reduces Betaproteobacteria species in a T6SS-dependent manner, thus identifying specific species targeted by K. pneumoniae . We further show that T6SS gene expression is controlled by several transcriptional regulators and that expression only occurs in vitro under conditions that mimic the gut environment. By enabling K. pneumoniae to thrive in the gut, the T6SS indirectly contributes to the pathogenic potential of this organism. These observations advance our molecular understanding of how K. pneumoniae successfully colonizes the GI tract. Through metagenomics, Bray et al. identified Klebsiella pneumoniae interacting microbiota partners in the gut, and a transposon mutagenesis screen revealed a role for its T6SS in gut colonization, with t6ss transcription only occurring in vitro under GI-mimetic conditions.

Successful microbial colonization of the gastrointestinal (GI) tract hinges on an organism’s ability to overcome the intense competition for nutrients in the gut between the host and the resident gut microbiome. Enteric pathogens can exploit ethanolamine (EA) in the gut to bypass nutrient competition. However, Klebsiella pneumoniae ( K . pneumoniae ) is an asymptomatic gut colonizer and, unlike well-studied enteric pathogens, harbors two genetically distinct ethanolamine utilization ( eut ) loci. Our investigation uncovered unique roles for each eut locus depending on EA utilization as a carbon or nitrogen source. Murine gut colonization studies demonstrated the necessity of both eut loci in the presence of intact gut microbiota for robust GI colonization by K . pneumoniae . Additionally, while some Escherichia coli gut isolates could metabolize EA, other commensals were incapable, suggesting that EA metabolism likely provides K . pneumoniae a selective advantage in gut colonization. Molecular and bioinformatic analyses unveiled the conservation of two eut loci among K . pneumoniae and a subset of the related taxa in the K . pneumoniae species complex, with the NtrC-RpoN regulatory cascade playing a pivotal role in regulation. These findings identify EA metabolism as a critical driver of K . pneumoniae niche establishment in the gut and propose microbial metabolism as a potential therapeutic avenue to combat K . pneumoniae infections.

Background Homelessness is associated with health problems and with adverse childhood experiences (ACEs). The risk of chronic health conditions for homeless compared to housed youth, and how this risk interacts with ACEs remains unclear. This study investigated the relationship between ACEs, housing, and child health, and whether: 1) ACEs and health vary by housing context; 2) ACEs and homelessness confer independent health risks; and 3) ACEs interact with housing with regard to adolescent health. Methods Using data from 119,254 8th–11th graders, we tested independent and joint effects of ACEs and past-year housing status (housed, family homelessness, unaccompanied homelessness) on overall health and chronic health conditions, controlling for sociodemographic covariates. Results The prevalence of ACEs varied by housing status, with 34.1% of housed youth experiencing ≥1 ACE vs. 56.3% of family-homeless and 85.5% of unaccompanied-homeless youth. Health status varied similarly. Homelessness and ACEs were independently associated with low overall health and chronic health conditions, after adjusting for covariates. Compared to housed youth, both family-homeless youth and unaccompanied-homeless youth had increased odds of low overall health and chronic physical and/or mental health conditions. All ACE x housing-status interactions were significant (all p  < 0.001), such that ACE-related health risks were moderated by housing status. Conclusions ACEs and housing status independently predict health status during adolescence beyond other sociodemographic risks. Experiencing homelessness, whether unaccomapnied or with family, is associated with increased health risk, and every additional ACE increases this risk. Clinicians and health systems should advocate for policies that include stable housing as a protective factor.

Background Countries rely on out-of-pocket (OOP) spending to different degrees and employ varying techniques. The article examines trends in OOP spending in ten high-income countries since 2000, and analyzes their relationship to self-assessed barriers to accessing health care services. The countries are Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States. Methods Data from three sources are employed: OECD statistics, the Commonwealth Fund survey of individuals in each of ten countries, and country-specific documents on health care policies. Based on trends in OOP spending, we divide the ten countries into three groups and analyze both trends and access barriers accordingly. As part of this effort, we propose a conceptual model for understanding the key components of OOP spending. Results There is a great deal of variation in aggregate OOP spending per capita spending but there has been convergence over time, with the lowest-spending countries continuing to show growth and the highest spending countries showing stability. Both the level of aggregate OOP spending and changes in spending affect perceived access barriers, although there is not a perfect correspondence between the two. Conclusions There is a need for better understanding the root causes of OOP spending. This will require data collection that is broken down into OOP resulting from cost sharing and OOP resulting from direct payments (due to underinsurance and lacking benefits). Moreover, data should be disaggregated by consumer groups (e.g. income-level or health status). Only then can we better link the data to specific policies and suggest effective solutions to policy makers.

Social media platforms provide a valuable source of public health information, as one-third of US adults seek specific health information online. Many antitobacco campaigns have recognized such trends among youth and have shifted their advertising time and effort toward digital platforms. Timely evidence is needed to inform the adaptation of antitobacco campaigns to changing social media platforms. In this study, we conducted a content analysis of major antitobacco campaigns on Facebook using machine learning and natural language processing (NLP) methods, as well as a traditional approach, to investigate the factors that may influence effective antismoking information dissemination and user engagement. We collected 3515 posts and 28,125 associated comments from 7 large national and local antitobacco campaigns on Facebook between 2018 and 2021, including the Real Cost, Truth, CDC Tobacco Free (formally known as Tips from Former Smokers, where \"CDC\" refers to the Centers for Disease Control and Prevention), the Tobacco Prevention Toolkit, Behind the Haze VA, the Campaign for Tobacco-Free Kids, and Smoke Free US campaigns. NLP methods were used for content analysis, including parsimonious rule-based models for sentiment analysis and topic modeling. Logistic regression models were fitted to examine the relationship of antismoking message-framing strategies and viewer responses and engagement. We found that large campaigns from government and nonprofit organizations had more user engagements compared to local and smaller campaigns. Facebook users were more likely to engage in negatively framed campaign posts. Negative posts tended to receive more negative comments (odds ratio [OR] 1.40, 95% CI 1.20-1.65). Positively framed posts generated more negative comments (OR 1.41, 95% CI 1.19-1.66) as well as positive comments (OR 1.29, 95% CI 1.13-1.48). Our content analysis and topic modeling uncovered that the most popular campaign posts tended to be informational (ie, providing new information), where the key phrases included talking about harmful chemicals (n=43, 43%) as well as the risk to pets (n=17, 17%). Facebook users tend to engage more in antitobacco educational campaigns that are framed negatively. The most popular campaign posts are those providing new information, with key phrases and topics discussing harmful chemicals and risks of secondhand smoke for pets. Educational campaign designers can use such insights to increase the reach of antismoking campaigns and promote behavioral changes.

This study examines a common pedagogical approach whereby students view teacher feedback outside of class time. Facilitated through Moodle, it aimed to investigate not only the effect of written corrective feedback (WCF) on learning outcomes, but importantly, how frequently students review the feedback they receive. The study was conducted at a Japanese Women’s University in Tokyo (age: M = 19.6, SD = 0.6). Over a 15-week semester, students were required to write weekly homework assignments. These were then marked by the researcher and returned via Moodle, with students encouraged to read their feedback before attempting the next assignment. In line with existing research in the field, a no-WCF control group was compared against treatment groups that received indirect WCF with meta-linguistic explanations. Further to this, using an online system such as Moodle allowed the provision of linked grammar resource pages through basic HTML code embedded within the WCF itself. At the end of the semester student texts were analysed to measure improvement. When pre-test and post-tests were compared there were no significant differences within groups or between groups on measures of fluency and accuracy. However, what sets this study apart from others that have investigated student engagement, is the use of online activity logs which in combination with survey data allowed the investigation of actual study habits rather than merely those that are self-reported. The results of which give better insight and valid explanations for the outcomes of the study and call into question the efficacy of take-home feedback.

The Affordable Care Act's marketplaces present an important opportunity for expanding coverage but consumers face enormous challenges in navigating through enrollment and re-enrollment. We tested the effectiveness of a behaviorally informed policy tool--plan recommendations--in improving marketplace decisions. Data were gathered from a community sample of 656 lower-income, minority, rural residents of Virginia. We conducted an incentive-compatible, computer-based experiment using a hypothetical marketplace like the one consumers face in the federally-facilitated marketplaces, and examined their decision quality. Participants were randomly assigned to a control condition or three types of plan recommendations: social normative, physician, and government. For participants randomized to a plan recommendation condition, the plan that maximized expected earnings, and minimized total expected annual health care costs, was recommended. Primary data were gathered using an online choice experiment and questionnaire. Plan recommendations resulted in a 21 percentage point increase in the probability of choosing the earnings maximizing plan, after controlling for participant characteristics. Two conditions, government or providers recommending the lowest cost plan, resulted in plan choices that lowered annual costs compared to marketplaces where no recommendations were made. As millions of adults grapple with choosing plans in marketplaces and whether to switch plans during open enrollment, it is time to consider marketplace redesigns and leverage insights from the behavioral sciences to facilitate consumers' decisions.

Background Under the Affordable Care Act (ACA), millions of Americans have been enrolling in the health insurance marketplaces. Nearly 20% of them are tobacco users. As part of the ACA, tobacco users may face up to 50% higher premiums that are not eligible for tax credits. Tobacco users, along with the uninsured and racial/ethnic minorities targeted by ACA coverage expansions, are among those most likely to suffer from low health literacy – a key ingredient in the ability to understand, compare, choose, and use coverage, referred to as health insurance literacy. Whether tobacco users choose enough coverage in the marketplaces given their expected health care needs and are able to access health care services effectively is fundamentally related to understanding health insurance. However, no studies to date have examined this important relationship. Methods Data were collected from 631 lower-income, minority, rural residents of Virginia. Health insurance literacy was assessed by asking four factual questions about the coverage options presented to them. Adjusted associations between tobacco use and health insurance literacy were tested using multivariate linear regression, controlling for numeracy, risk-taking, discount rates, health status, experiences with the health care system, and demographics. Results Nearly one third (31%) of participants were current tobacco users, 80% were African American and 27% were uninsured. Average health insurance literacy across all participants was 2.0 (SD 1.1) out of a total possible score of 4. Current tobacco users had significantly lower HIL compared to non-users (−0.22, p  < 0.05) after adjustment. Participants who were less educated, African American, and less numerate reported more difficulty understanding health insurance ( p  < 0.05 each.) Conclusions Tobacco users face higher premiums for health coverage than non-users in the individual insurance marketplace. Our results suggest they may be less equipped to shop for plans that provide them with adequate out-of-pocket risk protection, thus placing greater financial burdens on them and potentially limiting access to tobacco cessation and treatment programs and other needed health services.

As coverage is expanded in health systems that rely on consumers to choose health insurance plans that best meet their needs, interest in whether consumers possess sufficient understanding of health insurance to make good coverage decisions is growing. The recent IJHPR article by Green and colleagues—examining understanding of supplementary health insurance (SHI) among Israeli consumers—provides an important and timely answer to the above question. Indeed, their study addresses similar problems to the ones identified in the US health care market, with two notable findings. First, they show that overall—regardless of demographic variables—there are low levels of knowledge about SHI, which the literature has come to refer to more broadly as “health insurance literacy.” Second, they find a significant disparity in health insurance literacy between different SES groups, where Jews were significantly more knowledgeable about SHI compared to their Arab counterparts. The authors’ findings are consistent with a growing body of literature from the U.S. and elsewhere, including our own, presenting evidence that consumers struggle with understanding and using health insurance. Studies in the U.S. have also found that difficulties are generally more acute for populations considered the most vulnerable and consequently most in need of adequate and affordable health insurance coverage. The authors’ findings call attention to the need to tailor communication strategies aimed at mitigating health insurance literacy and, ultimately, access and outcomes disparities among vulnerable populations in Israel and elsewhere. It also raises the importance of creating insurance choice environments in health systems relying on consumers to make coverage decisions that facilitate the decision process by using “choice architecture” to, among other things, simplify plan information and highlight meaningful differences between coverage options.