Improve Data Collection Research Articles

Lethal Force Usage by Law Enforcement Officers Against Hispanics, 2011-2020.

Most research on lethal force by law enforcement officers (LEOs) has focused on firearm deaths by LEOs among certain racial groups (e.g., African Americans). Specifically, not much is known about LEOs-induced lethal injuries among Hispanics. The purpose of this study was to characterize LEOs induced fatal injuries, the methods used, among various demographic groups of Hispanics, and the years of potential life lost before the age of 80 years due to lethal force by LEOs. Data from the Web-Based Injury Statistics Query and Reporting System (WISQARS) were analyzed for the years 2011-2020. LEOs killed 1,158 Hispanics; most were males (96.2%) with the majority being shot (89.9%). Two-thirds (66.9%) of those killed were Hispanics 20-39 years of age and from the Western U.S. These Hispanic deaths resulted in 53,320 YPLLs. Males and those ages 20-39 years lost the most YPLLs. The rate of fatal encounters with LEOs for Hispanics grew by 44.4% over the decade, with the highest rate in 2020. Mitigation of unnecessary Hispanic deaths by LEOs needs to include changes in law enforcement agency policies, hiring practices for LEOs, improved data collection for LEOs use of lethal force, improved mental healthcare and training for LEOs, use of less lethal strategies for citizen control by law enforcement, deference education for all young adults, and long-term changes in social forces that have created and maintained disenfranchised communities of color.

Evaluating adaptive management frameworks for data-limited crustacean fisheries

Crustacean fisheries represent an increasingly important contribution to global landings, food security and economic growth, especially in developing countries. However, many productive and valuable crustacean fisheries in Asian countries are characterized by limited data availability, scientific capacity, and fisheries management. Adaptive management frameworks, which use past and emerging information to provide stock status information and management advice, have been touted as particularly applicable for managing capacity- and data-limited fisheries because they employ methods that can improve data collection and result in evaluations of stock and ecosystem status with varying levels of data and capacity. Here, we examined the application of three adaptive fisheries management frameworks (FISHE, FishPath, and DLMtool) to three typical Asian crustacean fisheries that offered contrasting data types and availability, governance, and management and socio-economic contexts. Our aim was to evaluate their suitability for crustacean fisheries and identify particular data and modeling needs and management gaps in these fisheries. We found that while each of the frameworks could effectively recommend suitable monitoring, assessment, and management options given particular contextual factors, there were also limitations with each approach. For example, FISHE took a more wholistic view of ecosystem and fisheries heath, while the other frameworks were more focused on particular aspects of management such as stock assessment (FishPath) and management strategy evaluation (MSE; DLMtool). Applications of each approach also highlighted particular challenges in collecting commercial catch data due to limited monetary investment and poorly designed monitoring programs, which further hindered the implementation of catch and effort limits. The three frameworks also shared common challenges when applied to crustacean species, mainly associated with misalignment with the unique life-histories of crustaceans compared to finfish. By comparing the outputs of the three frameworks, we highlighted their respective strengths and weaknesses and propose an integrated framework that incorporates elements of each of the three frameworks. This integration offers a more comprehensive adaptive roadmap tailored to crustacean fisheries, which involves a mix of qualitative and quantitative approaches that could be applied depending on contextual factors and capacities. To further improve the applicability of adaptive frameworks to crustacean fisheries, we suggest considering crustacean's unique life history and the effects of climate change and other environmental factors, strengthening participatory processes, and balancing socio-economic and ecological objectives.

Strategies to Operationalize Health Equity in Island Area Health Departments.

Strategies to Operationalize Health Equity in Island Area Health Departments.

Best Practices for Addressing the Health Needs of the LGBTQ+ Community in Oncology Care

Patients with cancer in the LGBTQ+ community experience worse health outcomes when compared with their non-LGBTQ+ peers because of a variety of factors, including stigma, underrepresentation in research, lack of support, and implicit bias on the part of clinicians. For generations, many LGBTQ+ people have feared disclosing their identity to providers, leading to gaps in care and even higher mortality. As more people are identifying as members of the LGBTQ+ community, it’s crucial for providers to recognize them appropriately in healthcare, take steps such as acknowledging chosen names and pronouns, and provide care free from judgment. In today’s political climate, members of this community are facing increasing scrutiny, challenges, and barriers to accessing safe and affirming care. Providers can do their part to improve health outcomes among LGBTQ+ people by making their practices known as safe and affirming spaces, working to increase inclusivity in oncology care and improving data collection.

265P UCATS: A national specialist service for integration of gender affirming and oncological care in transgender patients with breast cancer

The transgender population face inequalities throughout the cancer pathway. Much of this stems from a lack of access to specialist knowledge of gender-affirming care and how it intersects with cancer. Breast cancer care in particular presents challenges for both patients and clinicians given the interaction with sex hormones , potential to exacerbate dysphoria and differing management in cisgender men vs. cisgender women. Breast cancer risk remains of concern in trans people. The best estimate of breast cancer incidence is trans men and non-binary people assigned female at birth (TMNB) is only 5 times less than in cisgender women. In trans women and non-binary people assigned male at birth (TFNB) the incidence is only 3 times less than in cisgender women. However cancer registries in most countries fail to accurately record gender identity and trans status. In response to this need, we established the UK Cancer and Transition Service (UCATS), a national multidisciplinary team meeting and clinic where any transgender patient with active or historical cancer can access specialist advice and support. This was coproduced with patient and public involvement and input from a specialist cancer charity. We discuss 6 cases of breast cancer in TMNB where cancer and gender-affirming care were mutually impacted by each other. Two of these lead to the establishment of UCATS and a further 4 were managed by the service. Challenges experienced by patients and clinicians included access to satisfactory reconstructive options, access to and management of gender-affirming hormones, and choice of anti-oestrogenic therapy. We recommend introduction similar services internationally and inclusion of gender identity and trans status in cancer registries to improve data collection on cancer risk. Further research is required on the use of gender-affirming hormones in hormone receptor-positive breast cancer in adjuvant and metastatic settings.

A Systematic Review of the ESG Strategy Literature and Future Outlook

This review investigates the importance of ESG factors in determining the long-term development and investment performance of companies, and identifies existing challenges and future directions in ESG strategy research. Through a comprehensive review and analysis of the existing literature on ESG strategy, the study highlights the key findings, implications, and future research directions in this field. The research underscores that incorporating ESG factors into corporate strategies enhances overall performance and contributes to sustainable development, while also revealing various implementation challenges such as difficulties in quantifying ESG factors and navigating diverse ESG criteria and assessment systems. This study presents an interdisciplinary approach to address ESG strategy research challenges, emphasizing the importance of harmonizing ESG standards and leveraging new technologies for improved data collection and analysis. The review acknowledges the limitations in current ESG strategy research, and suggests future research directions focusing on addressing these limitations, identifying suitable ESG evaluation criteria, and exploring the integration of new technologies in ESG investment. The findings stress the need for senior leadership support, establishment of a systematic framework, and effective communication with stakeholders for successful ESG strategy implementation, ultimately ensuring long-term competitiveness and sustainability for organizations.

Operationalization of a multidimensional sex/gender concept for quantitative environmental health research and implementation in the KORA study: Results of the collaborative research project INGER.

In environmental health research, sex and gender are not yet adequately considered. There is a need to improve data collection in population-based environmental health studies by comprehensively surveying sex/gender-related aspects according to gender theoretical concepts. Thus, within the joint project INGER we developed a multidimensional sex/gender concept which we aimed to operationalize and to test the operationalization for feasibility. In an iterative process, we created questionnaire modules which quantitatively captured the requirements of the INGER sex/gender concept. We deployed it in the KORA cohort (Cooperative Health Research in the Region of Augsburg, Germany) in 2019 and evaluated response and missing rates. The individual sex/gender self-concept was surveyed via a two-step approach that asked for sex assigned at birth and the current sex/gender identity. Additionally, we used existing tools to query internalized sex/gender roles and externalized sex/gender expressions. Adapted to the KORA population, we asked for discrimination experiences and care and household activities contributing to explain structural sex/gender relations. Further intersectionality-related social categories (e.g., socio-economic position), lifestyle and psychosocial factors were covered through data available in KORA. We could not identify appropriate tools to assess the true biological sex, sexual orientation and ethnic/cultural identity, which have yet to be developed or improved. The response-rate was 71%, the evaluation of 3,743 questionnaires showed a low missing rate. Prevalence of marginalized groups regarding sex/gender identity and definable by experiences of discrimination was very low. We have shown how the multidimensional INGER sex/gender concept can be operationalized according to an European and North American understanding of sex/gender for use in quantitative research. The questionnaire modules proved feasible in an epidemiologic cohort study. Being a balancing act between theoretical concepts and its quantitative implementation our operationalization paves the way for an adequate consideration of sex/gender in environmental health research.

Standardized reporting of pulmonary transfusion complications: Development of a model reporting form and flowchart.

Pulmonary complications of blood transfusion, including transfusion-related acute lung injury (TRALI), transfusion-associated circulatory overload (TACO), and transfusion-associated dyspnea, are generally underdiagnosed and under-reported. The international TRALI and TACO definitions have recently been updated. Currently, no standardized pulmonary transfusion reaction reporting form exists and most of the hemovigilance forms have not yet incorporated the updated definitions. We developed a harmonized reporting form, aimed at improved data collection on pulmonary transfusion reactions for hemovigilance and research purposes by developing a standardized model reporting form and flowchart. Using a modified Delphi method among an international, multidisciplinary panel of 24 hemovigilance experts, detailed recommendations were developed for a standardized model reporting form for pulmonary complications of blood transfusion. Two Delphi rounds, including scoring systems, took place and several subsequent meetings were held to discuss issues and obtain consensus. Additionally, a flowchart was developed incorporating recently published redefinitions of pulmonary transfusion reactions. In total, 17 participants completed the first questionnaire (70.8% response rate) and 14 participants completed the second questionnaire (58.3% response rate). According to the results from the questionnaires, the standardized model reporting form was divided into various subcategories: general information, patient history and transfusion characteristics, reaction details, investigations, treatment and supportive care, narrative, and transfused product. In this article, we present the recommendations from a global group of experts in the hemovigilance field. The standardized model reporting form and flowchart provide an initiative that may improve data collected to address pulmonary transfusion reactions.

Maximizing University Talent Potential through Improved Data Collection and Multimedia Management

Maximizing University Talent Potential through Improved Data Collection and Multimedia Management

Dental Infection Requiring Hospitalisation Is a Public Health Problem in Australia: A Systematic Review Demonstrating an Urgent Need for Published Data

Background: The aim of this systematic review was to analyse the published literature on dental infections leading to hospitalisations in Australia. It was hoped that understanding the patterns and trends would form a basis for improved preventive and management policies. Methods: An electronic search was performed using Web of Science, Medline via Ovid and Google Scholar. Inclusion and exclusion criteria were applied. The included studies were analysed for demographics, aetiology, management, length of hospital stay and outcome of dental infections requiring hospitalisation. Results: Nine retrospective studies were eligible for inclusion. A total of 2196 cases of dental infections leading to hospitalisations were reported, with a male predominance (55-67%). Mental health issues, illicit substance abuse and immunosuppression were the main associated comorbidities (up to 58%). Dental caries (59-90%) and pericoronitis (10-19%) were the leading causes of dental infections. Empirical antibiotics were utilised in up to 75% of cases prior to hospital presentation. Six mortalities were reported. Conclusions: The available published data show that dental infection is a significant public health problem. However, only general conclusions were possible due to the variably small sample size and data collection that was inconsistent and incomplete across studies. Improved data collection is required to develop policies for prevention and management.

Exploring the feasibility of establishing a core set of sexual, reproductive, maternal, newborn, child, and adolescent health indicators in humanitarian settings: results from a multi-methods assessment in Jordan

BackgroundReliable and rigorously collected sexual, reproductive, maternal, newborn, child, and adolescent health (SRMNCAH) data in humanitarian settings is often sparse and variable in quality across different humanitarian settings. To address this gap in data quality, the World Health Organization (WHO) developed a core set of indicators for monitoring and evaluating SRMNCAH services and outcomes in humanitarian settings, and assessed their feasibility in the field in Jordan, in addition to three other countries; with the goal of aggregating information from global consultations and field-level assessments to reach consensus on a set of core SRMNCAH indicators for services and outcome evaluation in humanitarian settings among WHO global partners.MethodsThe feasibility assessment in Jordan focused on the following constructs: relevance/usefulness, feasibility of measurement, systems and resources, and ethical issues. The multi-methods assessment included five components; a desk review, key informant interviews, focus group discussions, facility assessments, and observational sessions.ResultsFindings suggest that there is widespread support among regional, national, as well as global stakeholders for developing a core list of SRMNCAH indicators for monitoring and evaluation of services and outcomes in humanitarian settings in Jordan. There are numerous resources and data collection systems that could be leveraged, built upon, and improved to ensure the feasibility of collecting this proposed set of indicators. However, the data collection load requested from donors, the national government, international and UN agencies, coordination/cluster systems must be better harmonized, standardized, and less burdensome.ConclusionsDespite stakeholder support in developing a core set of indicators, this would only be useful if it has the buy-in from the international community. Greater harmonization and coordination, alongside increased resource allocation, would improve data collection efforts and allow stakeholders to meet indicators’ reporting requirements.

Examining injury trends in parcel delivery drivers in the United States: Challenges and opportunities.

Growth of e-commerce has caused a vast increase in parcel delivery, which raises concern for safety of drivers and other road users as more deliveries take place. This project analyzes injury/illness and fatality trends among workers with delivery-related NAICS codes using three major sources of occupational hazard data in the United States: the Survey of Occupational Illnesses and Injuries, the Census of Fatal Occupational Injuries, and the Industrial Tracking Application. Descriptive statistics were employed to illustrate trends over time as well as to highlight opportunities for improved data collection and dissemination. The number of injuries to drivers has risen sharply over the past decade. Some of this increase appears due to growth of this industry, but increasing overall rates suggest the industry is becoming more hazardous. While nonfatal injuries were typically caused by continuous workplace exposures (e.g., repetitive strain, contact with object/equipment), fatalities were almost exclusively caused by transportation incidents. Additionally, crucial aspects of these trends are difficult or impossible to analyze given the current data landscape. Observed trends reinforce earlier calls for additional scrutiny of working conditions that threaten drivers. Injuries caused by transportation incidents are likely more severe than others and highlight the danger the transportation system poses to drivers and others. Current data collection and dissemination processes offer room to improve in terms of understanding how to prevent future injuries.

Data-Driven Tracking Control for Multi-Agent Systems With Unknown Dynamics via Multithreading Iterative Q-Learning

This article addresses the tracking control problem of multiagent systems (MASs) with unknown dynamics. First, by designing a compensator, an augmented neighborhood error system is proposed. Then, a multithreading iterative <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -learning algorithm is developed, which can transform the tracking control problem into the optimal regulation of the augmented error system. In this algorithm, the agent controller is multithread, which consists of thread unit, global unit, and replay buffer. The thread unit is used to create the thread to collect the transitions with different control policies, which can reduce data relativity and improve data collection speed and exploration capability. The replay buffer is used to store the generated transitions. The global unit is used to generate the control policy. Moreover, the convergence analysis of the proposed algorithm is given, which shows that the neighborhood error converges to zero and the tracking control problem can be solved. Finally, the numerical example not only verifies the effectiveness of the obtained results but also shows the proposed algorithm performs better than the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -iterative algorithm.

Optimizing naloxone distribution to prevent opioid overdose fatalities: results from piloting the Systems Analysis and Improvement Approach within syringe service programs

BackgroundOpioid overdose fatalities are preventable with timely administration of naloxone, an opioid antagonist, during an opioid overdose event. Syringe service programs have pioneered naloxone distribution for potential bystanders of opioid overdose. The objective of this study was to pilot test a multi-component implementation strategy—the systems analysis and improvement approach for naloxone (SAIA-Naloxone)—with the goal of improving naloxone distribution by syringe service programs.MethodsTwo syringe service programs participated in a 6-month pilot of SAIA-Naloxone, which included (1) analyzing program data to identify gaps in the naloxone delivery cascade, (2) flow mapping to identify causes of attrition and brainstorm programmatic changes for improvement, and (3) conducting continuous quality improvement to test and assess whether modifications improve the cascade. We conducted an interrupted time series analysis using 52 weeks of data before and 26 weeks of data after initiating SAIA-Naloxone. Poisson regression was used to evaluate the association between SAIA-Naloxone and the weekly number of participants receiving naloxone and number of naloxone doses distributed.ResultsOver the course of the study, 11,107 doses of naloxone were distributed to 6,071 participants. Through SAIA-Naloxone, syringe service programs prioritized testing programmatic modifications to improve data collection procedures, proactively screen and identify naloxone-naïve participants, streamline naloxone refill systems, and allow for secondary naloxone distribution. SAIA-Naloxone was associated with statistically significant increases in the average number of people receiving naloxone per week (37% more SPP participants; 95% CI, 12% to 67%) and average number of naloxone doses distributed per week (105% more naloxone doses; 95% CI, 79% to 136%) beyond the underlying pre-SAIA-Naloxone levels. These initial increases were extended by ongoing positive changes over time (1.6% more SSP participants received naloxone and 0.3% more naloxone doses were distributed in each subsequent week compared to the weekly trend in the pre-SAIA Naloxone period).ConclusionsSAIA-Naloxone has strong potential for improving naloxone distribution from syringe service programs. These findings are encouraging in the face of the worsening opioid overdose crisis in the United States and support testing SAIA-Naloxone in a large-scale randomized trial within syringe service programs.

Assistive technology access in longitudinal datasets: a global review.

Functional limitations become more prevalent as populations age, emphasising an increasingly urgent need for assistive technology (AT). Critical to meeting this need trajectory is understanding AT access in older ages. Yet few publications examine this from a longitudinal perspective. This review aims to identify and collate what data exist globally, seeking all population-based cohorts and repeated cross-sectional surveys through the Maelstrom Research Catalogue (searched May 10, 2022) and the Disability Data Report (published 2022), respectively. Datasets incorporating functional limitations modules and question(s) dedicated to AT, with a wave of data collection since 2009, were included. Of 81 cohorts and 202 surveys identified, 47 and 62 meet inclusion criteria, respectively. Over 40% of cohorts were drawn from high-income countries which have already experienced significant population ageing. Cohorts often exclude participants based on pre-existing support needs. For surveys, Africa is the most represented region (40%). Globally, 73% of waves were conducted since 2016. 'Use' is the most collected AT access indicator (69% of cohorts and 85% of surveys). Glasses (78%) and hearing aids (77%) are the most represented AT. While gaps in data coverage and representation are significant, collating existing datasets highlights current opportunities for analyses and methods for improving data collection across the sector.

An Information Management Model for Addressing Residents’ Complaints through Artificial Intelligence Techniques

Construction companies usually record customer complaints as unstructured texts, resulting in unsuitable information to understand defect occurrences. Moreover, complaint databases are often manually classified, which is time-consuming and error-prone. However, previous studies have not provided guidance on how to improve customer complaint data collection and analysis. This research aims to devise an information management model for customer complaints in residential projects. Using Design Science Research, a study was undertaken at a Brazilian residential building company. Multiple sources of evidence were used, including interviews, participant observations, and analysis of an existing database. Natural language processing (NLP) was used to build a word menu for customers to lodge a complaint. Moreover, a recommendation system was proposed based on machine learning (ML) and hierarchical defect classification. The system was designed to indicate which defects should be investigated during inspections. The main outcome of this investigation is an information management model that provides an effective classification system for customer complaints, supported by artificial intelligence (AI) applications that improve data collection, and introduce some degree of automation to warranty services. The main theoretical contribution of the study is the use of advanced data management approaches for managing complaints in residential building projects, resulting in the combination of inputs from technical and customer perspectives to support decision-making.

Social determinants of health derived from people with opioid use disorder: Improving data collection, integration and use with cross-domain collaboration and reproducible, data-centric, notebook-style workflows.

Deriving social determinants of health from underserved populations is an important step in the process of improving the well-being of these populations and in driving policy improvements to facilitate positive change in health outcomes. Collection, integration, and effective use of clinical data for this purpose presents a variety of specific challenges. We assert that combining expertise from three distinct domains, specifically, medical, statistical, and computer and data science can be applied along with provenance-aware, self-documenting workflow tools. This combination permits data integration and facilitates the creation of reproducible workflows and usable (reproducible) results from the sensitive and disparate sources of clinical data that exist for underserved populations.

Ailing neurosurgical services in rural Africa

Ailing neurosurgical services in rural Africa

A Comprehensive Review of Mathematical Modeling Approaches for Analysing Human Reproductive Dynamics in North East India

North East India, characterized by its ethnic diversity and varied socio-economic conditions, encounters distinct reproductive health challenges driven by early marriage, cultural norms, and disparities in healthcare access. Early marriage contributes to early childbearing and affects fertility rates. Diverse cultural practices among the region's numerous ethnic groups shape family planning decisions and contraceptive use, while limited access to quality healthcare services exacerbates maternal and child health issues. This review paper examines how mathematical modeling can provide a structured approach to understanding these complex dynamics. The application of age-structured and fertility transition models is analysed to track demographic trends and shifts in fertility. Additionally, advanced modeling techniques, such as stochastic and agent-based models, are used to account for variability and simulate different scenarios. The review also evaluates data collection methods for accurate modeling and the processes of calibration and validation. The findings underscore the effectiveness of these models in capturing regional reproductive trends and highlight the need for improved data collection and the integration of local cultural and socio-economic factors into models to enhance their accuracy and relevance. By combining quantitative models with qualitative insights, this review aims to offer actionable recommendations for developing public health strategies and policies tailored to the specific needs of North East India.​

Evidence from ClinicalTrials.gov on the growth of Digital Health Technologies in neurology trials

Digital Health Technologies (DHTs) such as connected sensors offer particular promise for improving data collection and patient empowerment in neurology research and care. This study analyzed the recent evolution of the use of DHTs in trials registered on ClinicalTrials.gov for four chronic neurological disorders: epilepsy, multiple sclerosis, Alzheimer’s, and Parkinson’s disease. We document growth in the collection of both more established digital measures (e.g., motor function) and more novel digital measures (e.g., speech) over recent years, highlighting contexts of use and key trends.