Health Research Research Articles

Air quality, chemical mixtures, and local governance: findings from a national environmental health research program in Colombia

Air quality, chemical mixtures, and local governance: findings from a national environmental health research program in Colombia

Navigating Multifaceted Communication Channels in Disseminating Environmental Health Research: A Case Study of the PIPA Project

Navigating Multifaceted Communication Channels in Disseminating Environmental Health Research: A Case Study of the PIPA Project

The Ethnographic Interview: An Interdisciplinary Guide for Developing an Ethnographic Disposition in Health Research.

Interviews are central to the health ethnographers' toolkit. In this article, we offer a critical engagement with methodological literature coupled with reflective examples from our own research, in order to articulate the value of the ethnographic interview in health research. We contribute to literature on ethnographic interviews in two ways: by decoupling ethnographic interviews from the necessity of accompanying participant observation, and by outlining an ethnographic disposition towards interviewing. We define the seven key epistemic dispositions underpinning the ethnographic interview. These are humility, a readiness to revise core assumptions about a research topic, attentiveness to context, relationality, openness to complexity, an attention to ethnographic writing, and a consideration of the politics and history of the method. The strength of an epistemic understanding of the ethnographic interview is that it offers flexibility for developing a diverse array of interview techniques responsive to the needs of different research contexts and challenges. Ethnographic interviews, we show, contribute to the study of health through a richly explorative, responsive, contextualised, and reflexive approach.

Willingness to participate in a personalized health cohort – insights from the swiss health study pilot phase

BackgroundThis paper explores the feasibility of establishing a large-scale population-based cohort and biobank in Switzerland by assessing potential participants’ needs, expectations, and concerns about such an infrastructure providing information on health, lifestyle, and exposure trajectories, the development of disease, and risk factors over time.MethodsWe utilized a scenario-based questionnaire in the Swiss Health Study pilot phase (2020–2021), involving 1349 adults aged 20–69 from the cantons Vaud and Bern. We conducted descriptive statistics supported by R and qualitative content analysis of n = 374 open responses related to attitudes towards research.ResultsWe highlight the benefits and challenges of the scenario-based approach, discuss the sample represented in the pilot phase, and present implications for building a full cohort. We also report on participants’ attitudes towards and previous experience with health research. We analyze references regarding informed consent and feedback, attitudes towards the Swiss Health Study, and recommendations on improving its scope, design, and instruments. Results indicate a high interest (90%) in participating in a national health study, with 85% of a random population sample willing to join a long-term cohort. Only 43% were familiar with biobanks, and 44% preferred general consent. Trust was high for Swiss-based public research but lower for researchers from other countries or private sector. Over 95% expressed willingness to complete online questionnaires, undergo physical examination, and donate biosamples. Almost all participants wanted to know the outcomes of the medical tests (99.5%) and the exposure to environmental stressors (95%) from their study center visit. Preferred tools for monitoring sleep, physical activity, and diet were known smartphone apps with automatic data management.ConclusionOverall, the study reveals a positive attitude towards personalized health research, with a strong willingness to share data and samples. Key insights focus the meaning of informed consent for participation, the relevance of sampling and representativeness, as well as the significance and challenges of personalized feedback, especially regarding environmental health concerns. Findings emphasize participants’ supportive yet reflexive stances, underscoring the importance of aligning research values with individual values in personalized health research. These insights contribute valuable considerations for refining the scope, design, and instruments of future cohort studies.

Data sharing considerations to maximise use of pathogen biological and genomics resources data for public health.

Public sector data associated with health is a highly valuable resource with multiple potential end-users, from health practitioners, researchers, public bodies, policy makers and industry. Data for infectious disease agents is used for epidemiological investigations, disease tracking and assessing emerging biological threats. Yet, there are challenges in collating and re-using it. Data may be derived from multiple sources, generated and collected for different purposes. While public sector data should be open access, providers from public health settings or from agriculture, food or environment sources have sensitivity criteria to meet with ethical restrictions in how the data can be reused. Yet, sharable datasets need to describe the pathogens with sufficient contextual metadata for maximal utility, e.g. associated disease or disease potential and the pathogen source. As data comprises the physical resources of pathogen collections and potentially associated sequences, there is an added emerging technical issue of integration of 'omics 'big data'. Thus, there is a need to identify suitable means to integrate and safely access diverse data for pathogens. Established genomics alliances and platforms interpret and meet the challenges in different ways depending on their own context. Nonetheless, their templates and frameworks provide a solution for adaption to pathogen datasets.

Does an expanded allied health student training programme in regional New South Wales (Australia) result in a positive social return on investment? A protocol for a single-university education-based economic evaluation

Introduction20 years ago, health professional student placements in rural areas of Australia were identified as an important rural recruitment strategy and funding priority. Since then, there has been a growing...

Towards cross-application model-agnostic federated cohort discovery.

To demonstrate that 2 popular cohort discovery tools, Leaf and the Shared Health Research Information Network (SHRINE), are readily interoperable. Specifically, we adapted Leaf to interoperate and function as a node in a federated data network that uses SHRINE and dynamically generate queries for heterogeneous data models. SHRINE queries are designed to run on the Informatics for Integrating Biology & the Bedside (i2b2) data model. We created functionality in Leaf to interoperate with a SHRINE data network and dynamically translate SHRINE queries to other data models. We randomly selected 500 past queries from the SHRINE-based national Evolve to Next-Gen Accrual to Clinical Trials (ENACT) network for evaluation, and an additional 100 queries to refine and debug Leaf's translation functionality. We created a script for Leaf to convert the terms in the SHRINE queries into equivalent structured query language (SQL) concepts, which were then executed on 2 other data models. 91.1% of the generated queries for non-i2b2 models returned counts within 5% (or ±5 patients for counts under 100) of i2b2, with 91.3% recall. Of the 8.9% of queries that exceeded the 5% margin, 77 of 89 (86.5%) were due to errors introduced by the Python script or the extract-transform-load process, which are easily fixed in a production deployment. The remaining errors were due to Leaf's translation function, which was later fixed. Our results support that cohort discovery applications such as Leaf and SHRINE can interoperate in federated data networks with heterogeneous data models.

VIVALDI ASCOT and Ethnography Study: protocol for a mixed-methods longitudinal study to evaluate the impact of COVID-19 and other respiratory infection outbreaks on care home residents’ quality of life and psychosocial well-being

IntroductionOlder adults in care homes experienced some of the highest rates of mortality from SARS-CoV-2 globally and were subjected to strict and lengthy non-pharmaceutical interventions, which severely impacted their daily...

A versatile sample-delivery system for X-ray photoelectron spectroscopy of in-flight aerosols and free nanoparticles at MAX IV Laboratory.

Aerosol science is of utmost importance for both climate and public health research, and in recent years X-ray techniques have proven effective tools for aerosol-particle characterization. To date, such methods have often involved the study of particles collected onto a substrate, but a high photon flux may cause radiation damage to such deposited particles and volatile components can potentially react with the surrounding environment after sampling. These and many other factors make studies on collected aerosol particles challenging. Therefore, a new aerosol sample-delivery system dedicated to X-ray photoelectron spectroscopy studies of aerosol particles and gas molecules in-flight has been developed at the MAX IV Laboratory. The aerosol particles are brought from atmospheric pressure to vacuum in a continuous flow, ensuring that the sample is constantly renewed, thus avoiding radiation damage, and allowing measurements on the true unsupported aerosol. At the same time, available gas molecules can be used for energy calibration and to study gas-particle partitioning. The design features of the aerosol sample-delivery system and important information on the operation procedures are described in detail here. Furthermore, to demonstrate the experimental range of the aerosol sample-delivery system, results from aerosol particles of different shape, size and composition are presented, including inorganic atmospheric aerosols, secondary organic aerosols and engineered nanoparticles.

Two decades of the International Classification of Functioning, Disability and Health (ICF) in health research: a bibliometric analysis

Introduction: We conducted a twenty-year bibliometric analysis of scientific literature, focusing on the trends of The International Classification of Functioning, Disability and Health (ICF) use in health research. Methods: We retrieved 3’467 documents published between 2002 and 2022, sourced from the Web of Science Core Collection database. We used the Bibliometrix and VoSviewer tools for descriptive analyses and data visualization. Results: Our findings indicate a significant increase in ICF application since 2011, with an average annual growth rate of 13.19%. Prominent contributions were observed globally, with notable outputs from the U.S., Canada, Germany, the Netherlands, and Switzerland. The Ludwig Maximilian University Munich, Swiss Paraplegic Research, and McMaster University authored a quarter of the documents (24.6%). Collaboration networks of countries and institutions revealed robust partnerships, particularly between Germany and Switzerland. "Rehabilitation" was the most frequently occurring keyword, although a thematic shift towards epidemiology, aging, and health-related quality of life was observed post-2020. While rehabilitation remained the primary thematic focus, literature post-2020 highlighted epidemiology as a growing area of interest. Conclusions: A steady increase in ICF-based research mirrors the rising interest in a biopsychosocial and person-centered approach to healthcare. However, the literature is primarily produced by high-resource countries, with underrepresentation from low and middle-resource countries, suggesting an area of future research to address this discrepancy.

Participatory design in telehealth research: Practical case examples.

Participatory design (PD) is a methodology that emphasizes user participation in the design of new technologies to leverage change within organizations and services. PD originated in the computer science field in the 1970s and 1980s when new programs and technologies were developed to empower workers, by involving them in decisions that affected them. PD in health research has been proven to change clinical practice. Genuine user involvement that includes all stakeholders, and robust collaborations across sciences, sectors, and disciplines are basic elements of successful research to change clinical practice and to implement novel technical and organizational approaches. This paper summarizes seven case studies involving the use of PD in telehealth research. All cases presented promoted organizational changes supported by health information and communications technology, and have been implemented at either international, national, regional, or local levels. We describe how PD can be applied in health sciences and used to facilitate organizational changes, new perspectives, and new communications methods. The relevance and suitability of PD as a research design in health science is explained, and recommendations for conducting PD studies in telehealth research are presented. In PD, mutual learning and co-creation is facilitated. Consequently, learning from users, rather than studying them, corroborates our understanding and the emergence of new knowledge.

Policies and Indicators to Operationalize Structural Racism for Quantitative Health Research.

The field of structural racism is developing rapidly, with researchers moving from commentaries and review papers toward empirical research that aims to quantify the impact of exposure to structural racism on racial and ethnic inequities in health. Despite the increasing recognition of the impact of structural racism on health outcomes, its measurement in the empirical literature has focused on a limited set of area-based measures. This paper proposes two ways to expand the measurement of structural racism in public health research. First, by situating indicators of structural racism within the broader context of discriminatory policies that gave rise to racial and ethnic inequities, and second, by broadening the range of area-level indicators of structural racism beyond what has been used in the extant literature. The paper provides practical tools, including an extensive list of discriminatory federal policies, a list of common and novel indicators of structural racism across multiple domains, and an applied example showing how to connect policies and indicators of structural racism. These tools will aid researchers in developing a robust empirical evidence base to examine the role of structural racism in long-standing health inequities and advance quantitative research on the impact of structural racism on health inequities.

Assessing the Impact of Spatial and Temporal Variability in Fine Particulate Matter Pollution on Respiratory Health Outcomes in Asthma and COPD Patients

Ambient air pollution’s health impacts are well documented, yet the domestic environment remains underexplored. We aimed to compare indoor versus outdoor (I/O) air quality and estimate the association between indoor/ambient fine particulate matter (PM2.5) exposure and lung function in asthma and chronic obstructive pulmonary disease (COPD) patients. The study involved 24 h monitoring of PM2.5 levels indoors and outdoors, daily peak expiratory flow (PEF), and biweekly symptoms collection from five patients with asthma and COPD (average age of 50 years, 40% male) over a whole year. Data analysis was performed with linear mixed effect models for PEF and generalized estimating equations (GEE) for exacerbations. More than 5 million PM2.5 exposure and meteorological data were collected, demonstrating significant I/O PM2.5 ratio variability with an average ratio of 2.20 (±2.10). Identified indoor PM2.5 sources included tobacco use, open fireplaces, and cooking, resulting in average indoor PM2.5 concentrations of 63.89 μg/m3 (±68.41), significantly exceeding revised World Health Organization (WHO) guidelines. Analysis indicated a correlation between ambient PM2.5 levels and decreased PEF over 0-to-3-day lag, with autumn indoor exposure significantly impacting PEF and wheezing. The study underscores the need to incorporate domestic air quality into public health research and policy-making. A personalized approach is required depending on the living conditions, taking into account the exposure to particulate pollution.

Burden and social distribution of occupational psychosocial exposures in the United States workforce, 2022.

To characterize the burden and social distribution of occupational psychosocial exposures in the United States (US). We merged 2022 US employment and demographic data from the Current Population Survey (CPS) with occupational characteristic data from the Occupational Information Network (O*NET), wage data from the Occupational Employment and Wage Statistics Survey, and hours worked from the CPS, to estimate the number and proportion of US workers at risk of exposure to 19 psychosocial hazards. We additionally estimated the number and proportion of US workers over- or underrepresented in exposure burden. Of the exposures examined, US workers were most commonly employed in occupations with high time pressure (67.5 million US workers exposed; 43.2% US workers exposed), high emotional labor (57.1 million; 36.6%), and low wages (47.8 million; 30.6%). The burden of exposures was uneven across sociodemographic strata, attributable to occupational segregation. The full data set is available online at https://deohs.washington.edu/us-exposure-burden. Work-related psychosocial exposures are ubiquitous and should be considered in occupational and public health research, policy, and interventions to reduce the burden of disease and health inequities in the United States.

Impact of prior oral anticoagulation therapies on post-discharge outcomes after COVID-19: Results from aglobal federated health network analysis.

The impact of chronic oral anticoagulant (OACs) use on long-term post-discharge outcomes after coronavirus disease 2019 (COVID-19) hospitalisation remains unclear. Herein, we compared clinical outcomes up to 2-years after COVID-19 hospitalisation between patients on vitamin K antagonists (VKAs), direct-acting OACs (DOACs) and no OAC therapy. Data from TriNetX, a global federated health research network, were used. Adult patients on VKAs, DOACs or no OAC therapy at diagnosis of COVID-19 between 20 January 2020 and 31 December 2021, who were hospitalised for COVID-19, were included. The primary outcomes were all-cause mortality, ischaemic stroke/transient ischaemic attack (TIA)/systemic embolism (SE) and the composite of intracranial haemorrhage (ICH)/gastrointestinal bleeding, at 2 years after COVID-19 hospitalisation. We included 110,834 patients with COVID-19. Following propensity score matching (PSM), we identified a decreased mortality risk in DOAC-treated patients compared to the no OAC cohort (RR .808, 95% CI .751-.870). A higher risk of ischaemic stroke/TIA/SE was observed in VKA users compared to DOAC users (RR 1.100, 95% CI 1.020-1.220) and in VKA users compared to patients not taking OAC (RR 1.400, 95% CI 1.140-1.720). VKA use was associated with a greater risk of ICH/gastrointestinal bleeding than DOAC users (RR 1.198, 95% CI 1.066-1.347), while DOAC users had a lower risk compared to no OAC-treated patients (RR .840, 95% CI .754-.936). COVID-19 patients taking prior DOACs were associated with lower long-term mortality risk and ICH/gastrointestinal bleeding than patients not taking OAC. Compared to patients on DOACs, VKA users were associated with higher risks of mortality, ischaemic stroke/TIA/SE and ICH/gastrointestinal bleeding.

The Immigrant Mortality Advantage Among Over-65 Middle Eastern and North African Immigrants to the United States.

Immigrants to the United States often have longer life expectancies than their U.S.-born counterparts, however it is unclear whether a similar "immigrant advantage" exists for immigrants from the Middle East and North Africa (MENA). This study uses a novel machine-learning name classifier to offer one of the first national-level examinations of MENA mortality patterns by nativity in the United States. A recurrent neural network model was developed to identify MENA individuals based on given name and surname characteristics. The model was trained on more than 2.5 million mortality-linked social security records in the Berkeley Unified Numident Mortality Database (BUNMD). Mortality rates and life expectancy were estimated using a Gompertz distribution and maximum likelihood estimation, focusing on high-coverage years between 1988 and 2005 and deaths over age 65. Foreign-born MENA men over 65 showed a significant immigrant mortality advantage with a hazard ratio (HR) of 0.64 and an estimated 3.13 additional years of life expectancy at age 65 compared to U.S.-born counterparts. Foreign-born MENA women also exhibited an advantage, with a HR of 0.71 and an additional 2.24years of life expectancy at age 65. This study is one of the first national-level analyses of mortality outcomes among the over-65 MENA population in the United States, finding a MENA immigrant mortality advantage. The results suggest further research is needed to identify and disaggregate the MENA population in health research.

Study Protocol for a Cross-Sectional Survey on the Long-Term Impact of COVID-19 on Latino Health

ABSTRACT The COVID-19 pandemic has exacerbated the health inequities of Latinos nationwide. Latinos are 1.5 times more likely to get infected by SARS-CoV-2 than any other racial and ethnic groups and are 2.3 times more likely to be hospitalized from COVID-19 and 1.8 times to die from COVID-19. This research protocol aims to examine the effects of COVID-19 among a Latino population and identify social determinants of health that may contribute to increased susceptibility to COVID-19. The COVID-19 Latino Health Study consists of survey measures in nine domains: 1) demographic characteristics; 2) COVID-19 experiences; 3) food, diet, and sleep items; 4) quality of life; 5) health status; 6) smoking behaviors; 7) cancer health; 8) social capital; and 9) social connectedness. The study was conducted in English and Spanish. Respondents were recruited through social media websites (Twitter, Facebook, and Instagram), in-person community gatherings, and partnering with existing community-based organizations. A total of 869 respondents (522 English vs. 347 Spanish) participated in the cross-sectional study. Respondents were from 20 Spanish-speaking countries and territories of Latin America, with many individuals reporting a mixed Latino heritage. On average, Spanish-speaking respondents were 45 years old (SD = 14.4, range 18–87), with 40.6% (n = 141) and indicating an annual income of less than $20,000. At least 55% (n = 291) of Spanish-speaking respondents reported completing a GED or less. Comparatively, Latinos completing the survey in English were, on average, 30 years old (SD = 12.24, range 18–83), with 49.1% (n = 256) reporting income over $75,000. Furthermore, 57.5% (n = 300) of English respondents completed a bachelor’s degree or higher. This protocol explores the social determinants of health experienced by Latinos during the COVID-19 pandemic. We describe the data collection procedure and examine issues and challenges to conducting Latino health research during a pandemic.

Medical intelligence for anxiety research: Insights from genetics, hormones, implant science, and smart devices with future strategies

AbstractThis comprehensive review article embarks on an extensive exploration of anxiety research, navigating a multifaceted landscape that incorporates various disciplines, such as molecular genetics, hormonal influences, implant science, regenerative engineering, and real‐time cardiac signal analysis, all while harnessing the transformative potential of medical intelligence [medical + artificial intelligence (AI)]. By addressing fundamental research questions, this study investigated the molecular and hormonal foundations underlying anxiety disorders, shedding light on the intricate interplay of genetic and hormonal factors contributing to the etiology and progression of anxiety. Furthermore, this review delves into the emerging implications of biomaterials, defibrillators, and state‐of‐the‐art devices for anxiety research, elucidating their potential roles in diagnosis, treatment, and patient management. A pivotal contribution of this review is the development and exploration of an AI‐driven model for real‐time cardiac signal analysis. This innovative approach offers a promising avenue for enhancing the precision and timeliness of anxiety diagnosis and monitoring. Leveraging machine learning and AI techniques enables the accurate classification of persons with anxiety based on real‐time cardiac data, thereby ushering in a new era of personalized and data‐driven mental health care. Identifying emerging themes and knowledge gaps lays the foundation for future research directions and offers a roadmap for scholars and practitioners to navigate this intricate field. In conclusion, this comprehensive review serves as a vital resource, consolidating diverse perspectives and fostering a deeper understanding of anxiety disorders from biological, engineering, and technological standpoints, ultimately contributing to advancing mental health research and clinical practice.This article is categorized under: Application Areas > Health Care Application Areas > Science and Technology Technologies > Classification

Identifying interventions that improve medication safety & rational use of medicines in India

Background & objectives Medication-related harm is known to be the cause for about 1/10th of hospitalizations. Some estimates from India show that about 90 per cent of medicines consumed are inessential or irrational and contribute towards high out-of-pocket expenditure on health. In this context, the Indian Council of Medical Research in 2022 constituted a National Task Force (NTF) to explore possible solutions that could improve safe and rational use of medicines (SRUMs). The objective of this study was to identify research ideas in the field of SRUM through a survey of relevant stakeholders, and further to prioritize the research ideas using a pre-identified set of criteria. Methods The responses from the identified stakeholders were assessed using the Child Health and Nutrition Research Initiative method, which is an established research priority-setting methodology. First, the NTF asked for two to six research ideas from relevant Indian and global stakeholders on solutions to improve SRUM. The ideas were checked for duplicates, re-phrased where necessary and classified into various sub-themes. Subsequently, the research ideas were scored by Indian experts with relevant technical expertise using a pre-defined set of five criteria: innovativeness, effectiveness, translational value, answerability and applicability. Each research idea received from a stakeholder was assigned a score under each of the five criteria. The overall research priority score was calculated as a mean of all five criteria-specific scores and converted into a percentage. Results The final output of the prioritization process was a list of research ideas or questions, ranked by their scores. Total 209 unique ideas were received from 190 respondents, which were scored by 27 experts. The top three research topics on medication safety focused on cost-effective strategies for improving antimicrobial stewardship, safe use of poly-pharmacy in geriatric patients and drug take-back policy interventions. Regarding the rational use of medicine, the top three topics included testing mobile application-based antimicrobial stewardship interventions, development of diagnostics for antimicrobial resistance, and behavioural interventions. Interpretation & conclusions Several priority ideas found in this study also align with those of global priority, e.g., safe disposal practices and enhanced pharmacovigilance, rational use of medicines. Patient engagement, which underlines many of the top scoring ideas found in this study, is also inclined with the top research priorities reported by the WHO priority exercise on research into the safe use of medicines. However, to the best of our knowledge, this is the first such work from a low- and middle- income country on medication safety and rational use of medicines. The findings of this research priority-setting exercise can help to guide research for the development of policy-relevant and novel interventions to improve SRUM in India.

Reflecting on the quality of a methodologically pluralist evaluation of a large-scale Indigenous health research collaboration in Australia

BackgroundIndigenous communities worldwide lead calls for all evaluations of research, programmes and policies affecting their communities to reflect the values, priorities and perspectives of the Indigenous peoples and communities involved....