Potential Disparities Research Articles

Spatial spillover effects of the digital economy on the green total factor productivity of China’s manufacturing industry

The rapid expansion of the digital economy has garnered significant attention because of its potential to drive high-quality advancement in traditional sectors, particularly manufacturing. This study examines the spatial dynamics and potential spatial disparities between the digital economy and green total factor productivity (GTFP) in China’s manufacturing sector. We utilize a novel set of indicators to assess the advancement of the digital economy during Chinese provinces and apply spatial econometric models to investigate its spatial influence on GTFP. The main research content and conclusions of this study are as follows. (1) By employing a novel index system to quantify the digital economy’s advancement level within the manufacturing sector across various provinces in China, and utilizing it as the primary explanatory variable, the index system demonstrates significant efficacy in empirical analysis and is both scientifically robust and methodologically sound. (2) Using the spatial Dubin model, this study analyzes the spatial effects of the digital economy on the GTFP of the manufacturing sector and finds that it has a dominant positive spatial spillover effect on the GTFP of the manufacturing industry nationwide. (3) The results show that the effects of digital economy advancement on GTFP in the manufacturing industry have a positive spatial spillover effect in the eastern and central area, whereas it is negative in the western area. This study extends the applicability of the new economic geography and imperfect competition theories to the digital economy era, thereby contributing to these academic fields. Moreover, it introduces a novel analytical framework for assessing the digital economy’s influence on manufacturing advancement. The findings provide valuable insights and policy recommendations for fostering the development of the digital economy advancement across diverse regions in China.

Meta-analysis of mutational site-specificity and concordance/discordance characteristics of myeloid sarcoma.

6583 Background: Myeloid sarcoma (MS) is an atypical, extramedullary manifestation of acute myeloid leukemia. Next-generation sequencing (NGS) studies have explored mutational profiles of MS tumor sites and bone marrow (BM) samples. However, site-specific molecular patterns and mutational concordance/discordance between MS sites and BM remain unclear. Methods: Relevant studies about MS retrieved from a Pubmed search (1999-2023) with information about MS site involvement and NGS data were included. With R software, a meta-analysis (MA) of descriptive data, MS tumor site, mutations, and mutational concordance/discordance was performed to obtain pooled prevalence estimates using the Freeman-Tukey double arcsine transformation, inverse variance, and random effects model. MA of median age was pooled using the methods of McGrath et al. (2023). Meta-regression (MR) was performed with mixed-effects model. Chi-square test was used for statistical analysis of categorical variables. Results: 87 patients with MS from 10 studies were identified. Median age was 53 years (95% confidence interval [CI]: 48-56), and MS was more common in males (pooled estimate of 67%, 95% CI: 54.8-78.5). Skin was the most common site involved in MS with random effects pooled estimate of prevalence of 39.4% (95% CI: 20.8-59.3), followed by lymph node (10.1%, 95% CI: 1.8-21.8), bone (5%, 95% CI: 0.2-13.3), and soft tissue (2.4%, 95% CI: 0-9.5). Pooled estimates of most common mutated genes were NPM1 (20.3%, 95% CI: 6.2-38), FLT3 (18.3%, 95% CI: 5.5-34.6), TP53 (8.4%, 95% CI: 1.8-17.7), NRAS(6.6%, 95% CI: 0.9-15.4), and IDH2 (4.3% 95% CI: 0-13.4). NPM1 (13/34), FLT3 (7/34), and IDH2 (6/28) were enriched in cutaneous MS. KIT was exclusively enriched in non-cutaneous MS (8/53) compared to cutaneous MS (0/34) (p = 0.017). Although the prevalence of small bowel MS was low (n = 3), FLT3 was mutated in all cases (p < 0.01). Comparing MS tumor site to BM, pooled prevalence of mutation concordance was similar to discordance (49.8% [95% CI: 34.4-65.1] and 50.2% [95% CI: 34.9-65.6], respectively). Most common concordant mutations were FLT3 (5/28) and NRAS (5/28). NPM1 and FLT3 were most common discordant mutations and enriched in MS tumor sites (p < 0.01 and p < 0.05, respectively). NPM1 was a discordant mutation in MS tumor site only. Univariate MR of cutaneous MS found no significant influence from male sex and mutational concordance/discordance. Multivariate MR showed significant interaction with males and mutational discordance toward cutaneous MS (p < 0.01). Conclusions: Our meta-analysis highlights potential site-specific and mutational disparities in MS. Knowledge about such differences may allow the use of targeted therapies against different molecular aberrations, emphasizing the need to sequence both BM and MS sites. Findings suggesting interaction of male sex and mutational discordance in cutaneous MS needs further validation.

Characterization of social determinants of health in patients considered for participation in treatment clinical trials at a community cancer center serving the Great Plains.

e13704 Background: Avera Cancer Institute, a community-based cancer network comprised of six rural cancer centers in SD and MN, provides care to a five-state region in the upper mid-west covering 72,000 square miles and offers several clinical trials to patients to offer access to advanced treatment for malignancies. Malignances are known to disproportionally affect patients that are older, rural, minorities, and have lower socioeconomic status, which are all less likely to enroll into clinical trials. Methods: Patients evaluated for participation in clinical trials from 2018-2022 were identified in an institutional database. Trial type was designated as either a treatment or nontreatment trial. Status of trial involvement was designated between enrolled or screened. Their demographic information was obtained from the electronic health record (EHR). Demographic information obtained from the EHR includes race, ethnicity, language spoken, gender, employment status, insurance type, and if they live in an urban or rural area as defined by the US Census Bureau. Clinical trial portfolio during this time includes trials for breast, gynecological, gastrointestinal, lung, and hematologic malignancies. Results: 4,397 patients were considered for participation in a clinical trial at our institution in the studied timeframe. Of these patients, 1887 were screened for treatment trials and of that group, 773 were enrolled. 35% of participants considered for clinical trials were from urban areas while 65% considered were rural. 48% of the urban population ultimately were enrolled on a clinical trial while 44% of rural population participated. Participants who lived in an urban area 25-50 miles from our study site had an enrollment rate of 49% compared to rural enrollment of 33%, from 50-100 miles rates of 53% and 37%, from 100-250 miles rates of 29% and 41%, and from greater than 250 miles rates of 44% and 33%, respectively. 99.5% of the population was non-Hispanic, 97% were White, and 99% were English speaking. 74% of the total population were female and 26% were male. Females had an enrollment rate of 51% while males had an enrollment of 29%. Patients with no insurance enrolled in trial 62% compared to 36% of those with commercial insurance The average national Area Deprivation Index percentile for screened patients was 57 vs 59 for enrolled patients. Conclusions: This retrospective study demonstrates a greater likelihood for females, urban patients, and white, English-speaking patients to enroll into clinical trials. Our data also demonstrate a preference for uninsured patients to enroll into clinical trials, possibly due to the financial benefits they may provide. Further directions include comparing our patients considered for clinical trials to all patients treated at our institution to identify potential disparities in care.

How does local context matter? Assessing the heterogeneous impact of electric vehicle incentive policies in China

This study reassesses the effectiveness of electric vehicle (EV) incentive policies in China and explores potential disparities in policy impact across different local contexts. Initially, employing panel data analysis, it evaluates policy effectiveness using data from 80 Chinese pilot cities spanning 2010 to 2022. Subsequently, cities are stratified based on varying income levels, traffic conditions, population density, and administrative hierarchy to facilitate an in-depth examination of the heterogeneous impacts of EV policies. Additionally, the Difference-in-Differences (DID) estimation method is employed to scrutinize the dynamic effects of these policies over time, enhancing the credibility of the panel model results. The findings reveal that purchase subsidies, parking benefits, driving privileges, and charging infrastructure have significant positive impacts on EV market share. Specifically, financial incentives are more effective in low-income, low-traffic, low-density cities, as well as in provincial capital cities while driving privileges are more suitable for high-income, high-traffic, and high-density areas. This study also finds that usage-phase policies increasingly drive EV adoption over time, offsetting the negative impact of subsidy reductions. The results of this study hold substantial implications for policymakers, providing insights to design context-based EV policies tailored to specific local conditions.

The COVID-19 impact on STEMI disparities

ST-segment elevation myocardial infarction (STEMI) is a significant source of morbidity and mortality. Despite guideline-driven management and increased awareness of social determinants of health, there are persistent disparities in diagnosis, management, and outcomes. The coronavirus disease 2019 (COVID-19) pandemic has greatly affected emergency department visitation, conditions and throughput. The aim of this study was to find any potential health disparities in patients who presented with STEMI during the COVID-19 pandemic by reviewing STEMI care data from April to September 2019 (pre-pandemic) and April to September 2020 (during the pandemic) for our hospital system.Patients with STEMI within 12 h of presentation were included in this study, and subdivided by age, gender, and race/ethnicity. We compared the turnaround times between emergency department arrival to intervention (electrocardiogram or catheterization) within the patient subgroups to find any notable differences. No statistically significant changes in turnaround times during either study period were found based on age, gender, or race/ethnicity for the STEMI interventions despite shifts in emergency department resources during the pandemic. This study helped assess the status quo in STEMI intervention for our health system and serves as a baseline for us to monitor gaps in care or areas of improvement. As healthcare systems institute new measures to promote equitable care, such as improving the accuracy of demographic data capture, establishing a baseline is an essential first step in evaluating the impact of these measures.

Intermittent fasting as a dietary intervention with potential sexually dimorphic health benefits.

Intermittent fasting (IF) has proven to be a feasible dietary intervention for the wider population. The recent increase in IF clinical trials highlights its potential effects on health, including changes in body composition, cardiometabolic status, and aging. Although IF may have clinical applications in different populations, studies suggest there may be sex-specific responses in parameters such as body composition or glucose and lipid metabolism. Here, the existing literature on IF clinical trials is summarized, the application of IF in both disease prevention and management is discussed, and potential disparities in response to this type of diet between men and women are assessed. Moreover, the potential mechanisms that may be contributing to the sexually dimorphic response, such as age, body composition, tissue distribution, or sex hormones are investigated. This review underscores the need to further study these sex-specific responses to IF to define the most effective time frames and length of fasting periods for men and women. Tailoring IF to specific populations with a personalized approach may help achieve its full potential as a lifestyle intervention with clinical benefits.

M3KGR: A momentum contrastive multi-modal knowledge graph learning framework for recommendation

In recent years, there has been a discernible upswing in the utilization of knowledge graphs within recommender systems. This heightened interest in knowledge graphs stems from their ability to vividly illustrate relationships between items through augmented attribute representations. Scholars have endeavored to incorporate multi-modal data, encompassing texts and images, into knowledge graphs, albeit with restricted success. These efforts primarily hinge on image models for extracting visual representations and text models for extracting textual representations, prompting apprehensions regarding potential disparities between the two modalities. Moreover, the current approaches for computing node similarities using multi-modal information have not witnessed noteworthy progress or enhancements.Momentum Contrastive Multi-Modal Knowledge Graph Learning Framework for Recommendation (M3KGR) proposed in this paper aims to enhance the utilization of multi-modal data. Specifically, we leverage the existing CLIP model to simultaneously extract textual and visual representations of an entity, thus overcoming the challenge of integrating multi-modal information. Additionally, we introduce a multi-modal enhanced attention technique to further enhance the performance of the graph attention network. Furthermore, we introduce Momentum Contrast to mitigate the common issues of data sparsity and noise in recommender systems. Our comprehensive experiments conducted on three real datasets demonstrate that our model enhances the efficacy of multi-modal knowledge graphs in recommender systems by fully leveraging the potential of multi-modal data. The implementation of our model will be available at https://github.com/KlaineWei/M3KGR.

Insurance Disparities in Patient Outcomes and Healthcare Resource Utilization Following Neonatal Intraventricular Hemorrhage

Within the field of pediatric neurosurgery, insurance status has been shown to be associated with surgical delay, longer time to referral, and longer hospitalization in epilepsy treatment, myelomeningocele repair, and spasticity surgery.1,2 The aim of this study was to investigate the association of insurance status with inpatient adverse events, length of stay, and costs for newborns diagnosed with intraventricular hemorrhage (IVH). A retrospective cohort study was performed using the 2016-2019 National Inpatient Sample database. Patients with a primary diagnosis of IVH were identified using ICD-10-CM diagnostic and procedural codes. Patients were categorized based on insurance status: Medicaid or Private Insurance (PI). Multivariate logistic regression analyses were used to identify the impact of insurance status on extended LOS (defined as >75th percentile of LOS) and exorbitant cost (defined as >75th percentile of cost). Demographics differed significantly between groups, with the majority of newborns in the PI cohort being White (Medicaid: 35.8% vs PI: 60.3%, p<0.001) and the majority of Medicaid patients being in the 0-25th quartile of household income (Medicaid: 40.9% vs PI: 12.9%, p<0.001). While insurance status was not independently associated with increased odds of extended LOS or exorbitant cost, Medicaid patients had a greater mean LOS and total cost of admission than PI patients. Demographic characteristics, mean LOS, and mean total cost differed significantly between Medicaid and PI patients, indicating potential disparities based on insurance status. However, insurance status was not independently associated with increased healthcare utilization, necessitating further research in this area of study.

Translation, cultural adaptation, and validation of Numerical Pain Rating Scale and Global Rating of Change in Tibetan musculoskeletal trauma patients

Tibetan-speaking patients seeking care in predominantly Mandarin-speaking healthcare settings frequently face communication barriers, leading to potential disparities and difficulties in accessing care. To address this issue, we translated, culturally adapted, and validated the Numerical Pain Rating Scale (NPRS) and the Global Rating of Change (GRoC) into Tibetan (NPRS-Tib and GRoC-Tib), aiming to facilitate cross-linguistic and cross-cultural interactions while examining potential challenges in the adaptation process. Using standard translation-backward translation methods, expert review, pilot testing, and validation through a cross-sectional study with a short-term longitudinal component, we engaged 100 Tibetan patients with musculoskeletal trauma for psychometric validation, including 37 women (aged 22–60 years, mean age 39.1 years). The NPRS-Tib and GRoC-Tib exhibited outstanding psychometric properties, with an Intraclass Correlation Coefficient (ICC) of 0.983 for NPRS-Tib indicating superb test–retest reliability, and expert review confirming good content validity for both instruments. A Spearman's correlation coefficient (Rho) of -0.261 (P = 0.0087) revealed a significant, albeit weak, correlation between changes in NPRS-Tib scores and GRoC-Tib scores. The adaptation process also presented notable challenges, including translation discrepancies from translators' diverse backgrounds and levels of expertise, ambiguity in scale options, and the lack of established tools for criterion validity assessment in Tibetan.

A STUDY ON BRAND PREFERENCE OF MOBILE PHONES IN SELECTED CITIES OF KARNATAKA

The purpose of this research is to examine the complexities of customer choices in the mobile phone industry in Karnataka, with a specific emphasis on certain towns within the state. The comprehension of brand preference has significant importance for mobile phone makers and marketers, since it exerts a direct impact on customer choices and buying behaviours. Moreover, with the implementation of this study in certain urban areas, our objective is to unveil potential regional disparities and intricacies in consumer conduct and inclinations. These findings might provide significant perspectives for the development of focused marketing tactics. The elements that affect consumers brand preferences regarding mobile phone brands in few select locations of Karnataka were determined in this study.

Reporting of Child Maltreatment During the COVID-19 Pandemic in a Southern State in the United States.

COVID-19-related stay-at-home orders (SAHOs) created an immediate physical barrier between children and professionals such as pediatricians and teachers, who are often first to identify and report signs of child maltreatment. Our objective was to determine how the SAHO in a southern state was associated with reports of child maltreatment and whether this association was modified by sociodemographic characteristics. We linked data on reports of child maltreatment from a southern state in the United States from October 1, 2018, through September 30, 2020, to data from the US Census Bureau to obtain data on county-level socioeconomic characteristics. We fit a segmented regression model to evaluate changes in reports before and after the SAHO, March 20, 2020. We evaluated potential disparities by child age, case and allegation severity, and socioeconomic characteristics. Of 374 885 hotline calls, 276 878 (73.9%) were made before the SAHO and 98 007 (26.1%) after it. Although an immediate decrease in reports of child maltreatment occurred on the day of the SAHO, the rates of reporting within socioeconomic groups started increasing thereafter. While we found no significant change in the overall rate of change in hotline calls after versus before the SAHO (0.23; 95% CI, -0.11 to 0.58), stratified analyses indicate that the rates at which reporting increased varied by education level, health insurance coverage, median annual household income, and unemployment. Evaluating these trends is important for policy makers and practitioners to understand how policies enforced during the pandemic influence child maltreatment reporting and how these policies may affect reporting differently across socioeconomic groups.

Technological Perception with Rural and Urban Differentiation and Its Influence on the Quality of Life of Older People with Age-Related Macular Degeneration

The past decade has seen a global increase in population age, especially in developed countries, where aging involves visual diseases such as age-related macular degeneration (AMD), which severely affect quality of life (QoL) and mental health, as well as increase isolation and care costs. This study investigated how persons with AMD perceive the impact of technology use on their QoL, focusing on potential disparities between urban and rural contexts in Spain. Using a cross-sectional observational design, data from the 2020 National Statistics Institute’s Disability, Personal Autonomy, and Dependency Situations Survey were analyzed, focusing on QoL aspects based on the WHO items of the WHOQOL-100 scale. The results revealed a generally positive perception of technology among participants, with urban residents perceiving technology’s positive impact more favorably. Sex discrepancies in technology perception were also observed, as women exhibited a more positive outlook on technology’s influence on QoL. The analysis of QoL aspects, such as ‘Visibility’, ‘Learning’, ‘Mobility’, and ‘Domestic life’, highlighted distinct challenges faced by rural and urban populations, underscoring the importance of context-specific approaches in technology interventions. However, these perceptions were intertwined with comorbidities, which can exacerbate AMD-related issues. Furthermore, this study explored the role of technology in enhancing QoL among older adults with AMD, examining how it influences daily activities and independence, particularly in the context of AMD management. This study concluded that developing more-inclusive policies tailored to the specific needs of persons with AMD, with special attention to environmental and sex differences, is imperative to enhance the positive impact of technology on their QoL.

Trilaciclib dosage in Chinese patients with extensive-stage small cell lung cancer: a pooled pharmacometrics analysis.

This study aimed to analyze potential ethnic disparities in the dose-exposure-response relationships of trilaciclib, a first-in-class intravenous cyclin-dependent kinase 4/6 inhibitor for treating chemotherapy-induced myelosuppression in patients with extensive-stage small cell lung cancer (ES-SCLC). This investigation focused on characterizing these relationships in both Chinese and non-Chinese patients to further refine the dosing regimen for trilaciclib in Chinese patients with ES-SCLC. Population pharmacokinetic (PopPK) and exposure-response (E-R) analyses were conducted using pooled data from four randomized phase 2/3 trials involving Chinese and non-Chinese patients with ES-SCLC. PopPK analysis revealed that trilaciclib clearance in Chinese patients was approximately 17% higher than that in non-Chinese patients with ES-SCLC. Sex and body surface area influenced trilaciclib pharmacokinetics in both populations but did not exert a significant clinical impact. E-R analysis demonstrated that trilaciclib exposure increased with a dosage escalation from 200 to 280 mg/m2, without notable changes in myeloprotective or antitumor efficacy. However, the incidence of infusion site reactions, headaches, and phlebitis/thrombophlebitis rose with increasing trilaciclib exposure in both Chinese and non-Chinese patients with ES-SCLC. These findings suggest no substantial ethnic disparities in the dose-exposure-response relationship between Chinese and non-Chinese patients. They support the adoption of a 240-mg/m2 intravenous 3-day or 5-day dosing regimen for trilaciclib in Chinese patients with ES-SCLC.

Comparative Analysis of S&amp;P 500 and NASDAQ Indices: A Machine Learning Approach to Understanding Differential Market Sensitivities and Growth Stock Dynamics

This paper delves into the implementation of a Walking Forward Machine Learning Model designed for the construction and forecasting of portfolios comprised of randomly selected stocks from the S&amp;P 500 and NASDAQ indices. The primary objective of the study is to scrutinize the attributes of technology stocks, specifically assessing whether they exhibit characteristics typical of growth stocks. Furthermore, the research aims to discern potential disparities in predictive characteristics between technology stocks and standard equities. The passage elucidates the research methodology, encompassing data collection, model establishment, and evaluation processes, along with insights into the intricacies of portfolio construction. The empirical findings shed light on the model's efficacy in predicting stock returns and its aptitude in crafting investment portfolios. The concluding remarks underscore the significance of adjusting the model's learning rate in accordance with the distinct traits of various markets, emphasizing the need for a nuanced approach to enhance its overall generalization performance. This study contributes valuable insights into optimizing machine learning models for effective portfolio management in dynamic financial markets.

Role of information sources in adherence to COVID-19-related safety measures among college students in the USA

Objective During the COVID-19 pandemic, information sources such as public officials, national/international media, social media, public health agencies, college/university officials, etc., played a vital role in adherence to safety measures, including hygiene practices, social distancing, and mask-wearing. We analyze the role of trusted sources of information in adherence to safety measures and explore potential disparities among US college students during the pandemic. Methods We analyze Healthy Minds Study (HMS) 2020–2021 COVID Module data and utilize multivariable logistic regressions controlling for sociodemographic and COVID-19-related factors. Subgroup analyses were conducted by gender, citizenship status, race, and educational level. Results Significant differences were found in adherence to safety measures when information was received from different sources. Demographic subgroups within the college student population depended on different sources of COVID-19-related information. Adherence to COVID-19-related safety measures also differed by demographic characteristics. Conclusion This analysis supports the necessity for targeted health-related messaging among US college students.

Sexual minority identifiers and their perception of illicit drug use risks in the US: Results from a National Survey

PurposeThis study examined the relationship between sexual identities and perception of risks associated with illicit drug use among a nationally representative sample of US adults. MethodsWe analyzed data from five waves of the National Survey on Drug Use and Health (NSDUH, 2015–2019), with 205,418 adult participants. Six survey questions assessing participants’ perceptions of the risks associated with illicit drug use (LSD, heroin, and cocaine) were subjected to principal component analysis. Sex-stratified ordered logistic regressions were used to explore potential disparities in perceptions regarding the risk associated with illicit drug use among sexual minority identifiers. ResultsAmong male participants, approximately 11.3% and 1.8% of them perceived illicit drug use as moderate and low risks, respectively. About 6.0% of female participants perceived illicit drug use as moderate risk, and 1.1% of female participants perceived it as low risk. The sex-stratified regression models demonstrated that participants who identified as lesbian/gay or bisexual all had higher odds of reporting low perception of illicit drug use risks as compared to their heterosexual counterparts (all p < 0.01). ConclusionsIllicit drug use prevention strategies should consider risk perception disparities by sexual minority populations.

Lifetime prevalence and correlates of colorectal cancer screening among low-income U.S. Veterans.

The Veterans Health Administration (VHA) is the largest integrated healthcare system in the U.S. While preventive healthcare services are high priority in the VHA, low-income U.S. Veterans experience adverse life circumstances that may negatively impact their access to these services. This study examined lifetime prevalence as well as demographic, socioeconomic, military-specific, and clinical correlates of colorectal cancer (CRC) screening among low-income U.S. Veterans ≥ 50years of age. Cross-sectional data on 862 participants were analyzed from the 2021-2022 National Veteran Homeless and Other Poverty Experiences study. Overall, 55.3% (95% confidence interval [CI] 51.3-59.3%) reported ever-receiving CRC-screening services. In a multivariable logistic regression model, never-receivers of CRC screening were twice as likely to reside outside of the Northeast, and more likely to be married (odds ratio [OR] = 1.86, 95% CI 1.02, 3.37), have BMI < 25kg/m2 [vs. 25- < 30kg/m2] (OR = 1.75, 95% CI 1.19, 2.58), or ≥ 1 chronic condition (OR = 1.46, 95% CI 1.06, 2.02). Never-receivers of CRC screening were less likely to be female (OR = 0.53, 95% CI 0.29, 0.96), aged 65-79y [vs. ≥ 80y] (OR = 0.61, 95% CI 0.40, 0.92), live in 5 + member households (OR = 0.33, 95% CI 0.13, 0.86), disabled (OR = 0.45, 0.22, 0.92), with purchased health insurance (OR = 0.56, 95% CI 0.33, 0.98), or report alcohol-use disorder (OR = 0.10, 95% CI 0.02, 0.49) and/or HIV/AIDS (OR = 0.28, 95% CI 0.12, 0.68). Nearly 55% of low-income U.S. Veterans reported ever screening for CRC. Variations in CRC-screening behaviors according to veteran characteristics highlight potential disparities as well as opportunities for targeted behavioral interventions.

Digital transformation and the DIY artist: Balancing artistic integrity and economic sustainability in the digital domain

This study investigates the evolving role of do-it-yourself (DIY) artists in the context of digital transformation, analyzing the delicate balance between maintaining artistic integrity and achieving economic sustainability in the contemporary music industry. By exploring the innovative use of digital platforms, the research highlights the need to foster innovation and ensure sustainable growth as part of a pivotal strategy for these artists. The findings emphasize the complexities and challenges presented by digital platforms, particularly in terms of diverse groups and the potential disparity between artistic and commercial pressures. Drawing from global DIY music scenes, the study underlines the importance of expanding income sources, fostering community-driven growth, and prioritizing genuine artist–fan interactions. The results offer invaluable insights for independent musicians, industry stakeholders, and digital platform developers, emphasizing the interrelationship between artistry, identity, and sustainability in the digital domain.

Disparities in Trend of Renal Cell Carcinoma Mortality in the United States.

Renal cell carcinoma (RCC) accounts for 90% of malignant neoplasms of the kidney. In this report, the CDC WONDER database was accessed to retrieve age-adjusted mortality data from 1999 to 2020 due to RCC, defined as ICD-10 Code: C64 Malignant neoplasm of kidney except renal pelvis, for various demographics to investigate trends and potential disparities. In 2020, the overall age-adjusted mortality rate (AAMR) due to RCC in the USA was 42.4 per 1,000,000. The average annual percent change (AAPC) for the USA from 1999 to 2020 was -0.6%. Notably, in 2020, men had a higher AAMR than women, 63.9 compared to 25.7, and a significant difference in AAPC trend was identified between men (-0.5%) and women (-1.0%). When investigating trends according to race in 2020, the Asian population displayed the lowest AAMR at 18.9. When determining AAPC from 1999 to 2020 according to race group, the American Indian group demonstrated the greatest decline in AAPC at -1.3%, followed by the Black (-1.2%) and White populations (-0.5%). The Asian population did not exhibit a significant AAPC. Moreover, the rates between these three groups were statistically significantly different- indicating disparities in trend based on race. This investigation assesses the AAMR for different demographic groups of the USA population to identify disparities and guide resource allocation strategies.

FAIRER PRIORITISATION OF THOSE WAITING FOR PRIMARY HIP ARTHROPLASTY: RESULTS FROM THE PRIORITISATION OF THOSE AWAITING HIP AND KNEE ARTHROPLASTY (PATHWAY) STUDY

Given the prolonged waits for hip arthroplasty seen across the U.K. it is important that we optimise priority systems to account for potential disparities in patient circumstances and impact. We set out to achieve this through a two-stage approach. This included a Delphi-study of patient and surgeon preferences to determine what should be considered when determining patient priority, followed by a Discrete Choice Experiment (DCE) to decide relative weighting of included attributes.The study was conducted according to the published protocol ([https://boneandjoint.org.uk/article/10.1302/2633-1462.310.BJO-2022-0071](https://boneandjoint.org.uk/article/10.1302/2633-1462.310.BJO-2022-0071)). The Delphi study was performed online over 3 rounds with anonymous ranking and feedback. Included factors were voted as either Consensus in, Consensus out, or No Consensus• following an established scoring criterion. A final consensus meeting determined the prioritisation factors (and their levels) to be included in the DCE. The DCE was then conducted using an online platform, with surgeons performing 18 choice sets regarding which merited greater priority between two hypothetical patients. Results were collated and analysed using multinomial logit regression analysis (MNL).For the Delphi study there were 43 responses in the first round, with a subsequent 91% participation rate. Final consensus inclusion was achieved for Pain; Mobility/Function; Activities of Daily Living; Inability to Work/Care; Length of Time Waited; Radiological Severity and Mental Wellbeing. 70 individuals subsequently contributed to the DCE, with radiological severity being the most significant factor (Coefficient 2.27 \[SD 0.31\], p&lt;0.001), followed by pain (Coefficient 1.08 \[SD 0.13\], p&lt;0.001) and time waited (Coefficient for 1-month additional wait 0.12 \[SD 0.02\], p&lt;0.001). The calculated trade-off in waiting time for a 1-level change in pain (e.g., moderate to severe pain) was 9.14 months.These results present a new method of determining comparative priority for those on primary hip arthroplasty waiting lists. Evaluation of potential implementation in clinical practice is now required.