Health Research Research Articles

Maternal Sleep Quality and Executive Function are Associated with Perceptions of Infant Sleep.

This study examined the associations among maternal sleep quality, executive function, and perceptions of infant sleep in a sample of families recruited from human service and public health systems. Seventy-three mothers of infants 5-14 months old were included in the study. Mothers racially and ethnically identified as American Indian/Alaskan Native (4.1%), Asian (4.1%), Black/African American (12.3%), Latina (23.3%), more than one race (12.3%), Pacific Islander (1.4%), and White (42.5%). Mothers completed questionnaires assessing their own sleep (Pittsburgh Sleep Quality Index) and executive function (Behavior Rating Inventory of Executive Function) as well as their perceptions about their infant's sleep (Brief Infant Sleep Questionnaire). Results of the path analysis indicated significant direct effects among maternal sleep quality, executive function, and perceptions of infant sleep. Significant indirect effects were found such that poor maternal sleep quality was linked to poorer perceptions of infant sleep through maternal executive dysfunction, adjusting for infant sleep patterns, infant age, and maternal race and ethnicity. The current study highlights the potential role of maternal behavioral and cognitive factors in shaping mothers' perceptions about infant sleep. These findings support the need for health professionals and researchers to consider maternal sleep quality and executive function when addressing mothers' concerns about infant sleep.

Disparate outcomes in Hispanic patients with metabolic dysfunction-associated steatotic liver disease/steatohepatitis and type 2 diabetes: Large cohort study

BACKGROUND Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) are a growing health burden across a significant portion of the global patient population. However, these conditions seem to have disparate rates and outcomes between different ethnic populations. The combination of MASLD/MASH and type 2 diabetes increases the risk of hepatocellular carcinoma (HCC), and Hispanic patients experience the greatest burden, particularly those in South Texas. AIM To compare outcomes between Hispanic and non-Hispanic patients in the United States, while further focusing on the Hispanic population within Southeast Texas to determine whether the documented disparity in outcomes is a function of geographical circumstance or if there is a more widespread reason that all clinicians must account for in prognostic consideration. METHODS This cohort analysis was conducted with data obtained from TriNetX, LLC (“TriNetX”), a global federated health research network that provides access to deidentified medical records from healthcare organizations worldwide. Two cohort networks were used: University of Texas Medical Branch (UTMB) hospital and the United States national database collective to determine whether disparities were related to geographic regions, like Southeast Texas. RESULTS This study findings revealed Hispanics/Latinos have a statistically significant higher occurrence of HCC, type 2 diabetes mellitus, and liver fibrosis/cirrhosis in both the United States and the UTMB Hispanic/Latino groups. All-cause mortality in Hispanics/Latinos was lower within the United States group and not statistically elevated in the UTMB cohort. CONCLUSION This would appear to support that Hispanic patients in Southeast Texas are not uniquely affected compared to the national Hispanic population.

A qualitative narrative study of rescue and recovery workers responding to the terrorist bombing of Oklahoma City's Murrah Building.

Much of disaster mental health research uses quantitative methods, focusing on numerical prevalence, services, and outcomes. Qualitative methods can provide more detailed, rich, and spontaneous insights into personal disaster experiences, yielding important insights beyond deductive methods. This large-scale qualitative narrative study examined experiences of 181 OKC bombing rescue/recovery workers. Thematic narrative content of the bombing experience arose from personal accounts of the bomb blast by rescue/recovery workers proceeding chronologically from initial awareness and deployment to harrowing onsite search and rescue/recovery missions to the aftermath with reflections on the bombing. Beyond disaster recovery/rescue worker stories published in popular media, little other substantive published knowledge on this topic is available, and therefore this research study provides a wealth of new in-depth information that can provide guidance for policy and practice for disaster response.

Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants.

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

Reporting Conflicts of Interest and Funding in Health Care Guidelines: The RIGHT-COI&F Checklist.

Conflicts of interest (COIs) of contributors to a guideline project and the funding of that project can influence the development of the guideline. Comprehensive reporting of information on COIs and funding is essential for the transparency and credibility of guidelines. To develop an extension of the Reporting Items for practice Guidelines in HealThcare (RIGHT) statement for the reporting of COIs and funding in policy documents of guideline organizations and in guidelines: the RIGHT-COI&F checklist. The recommendations of the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network were followed. The process consisted of registration of the project and setting up working groups, generation of the initial list of items, achieving consensus on the items, and formulating and testing the final checklist. International collaboration. 44 experts. Consensus on checklist items. The checklist contains 27 items: 18 about the COIs of contributors and 9 about the funding of the guideline project. Of the 27 items, 16 are labeled as policy related because they address the reporting of COI and funding policies that apply across an organization's guideline projects. These items should be described ideally in the organization's policy documents, otherwise in the specific guideline. The remaining 11 items are labeled as implementation related and they address the reporting of COIs and funding of the specific guideline. The RIGHT-COI&F checklist requires testing in real-life use. The RIGHT-COI&F checklist can be used to guide the reporting of COIs and funding in guideline development and to assess the completeness of reporting in published guidelines and policy documents. The Fundamental Research Funds for the Central Universities of China.

COVID-19 Implications on Worksite Wellness Programming.

As multi-racial and multi-ethnic populations are anticipated to be 11.6% of the U.S. population by 2060, it is essential that public health research and practice find ways to effectively capture and reach these diverse groups. Single racial identification has been a norm in public health practice; however, this method has limitations for capturing the health of multi-racial and multi-ethnic individuals. Drawing on personal experience of the author and multi-disciplinary scholarship, this research commentary examines the limitations of single-race identification and how this influences the processes of racialization. The author provides important implications for public health research by suggesting more complex and effective ways to capture personal racial identification and racial perceptions and addresses how to reach multi-racial and multi-ethnic groups through public health interventions where individuals might identify with multiple cultural identities.

Reducing musculoskeletal disorders in iron ore mine operators: A fuzzy-based intervention approach.

This study focuses on evaluating the exposure to whole-body vibration (WBV) and association of musculoskeletal disorders (MSDs) with various risk factors among dumper operators in the mining industry. Despite the issue's significance, prior research has been limited. The study introduces a novel fuzzy-based approach for identifying, selecting, and prioritizing safety measures to mitigate MSD risks. Data collection comprised face-to-face interviews, anthropometric measurements, Rapid Upper Limb Assessment (RULA) scoring for posture assessment, and the Nordic Musculoskeletal questionnaire for assessment of MSD prevalence. Multiple linear and logistic regression models were used to analyse the contributing risk factors to MSDs and WBV exposure. These risk factors formed the basis for a practical approach to select appropriate safety measures based on fuzzy based aggregation method of expert's judgment aimed at mitigating the risk of MSDs. The results revealed that the risk factors such as poor work posture, WBV exposure and poor seat design were significantly associated with neck (adjusted odds ratio aOR = 4.81), upper limb and shoulder (aOR = 3.28), upper back (aOR = 5.09), and lower back pain (aOR = 3.67) at p < 0.05. Using these factors to formulate safety measures to reduce MSD risk, the minimization of sharp turns and abrupt changes in elevation in designing the haul roads, scheduled maintenance practices, and ergonomic seat design were found as important safety measures in this study. Our unique methodological approach in occupational health research could be highly beneficial for tailoring safety measures at the unit level with minimal effort.

Impact evaluation of a cash-plus programme for children with disabilities in the Xiengkhouang Province in Lao PDR: study protocol for a non-randomised controlled trial

IntroductionMore than 170 countries have implemented disability-targeted social protection programmes, although few have been rigorously evaluated. Consequently, a non-randomised controlled trial is being conducted of a pilot ‘cash-plus’ programme implemented...

“We might not have been in hospital, but we were frontline workers in the community”: a qualitative study exploring unmet need and local community-based responses for marginalised groups in Greater Manchester during the COVID-19 pandemic

BackgroundThe response to the COVID-19 pandemic saw a significant increase in demand for the voluntary, community, faith and social enterprise (VCFSE) sector to provide support to local communities. In Greater Manchester (GM), the VCFSE sector and informal networks provided health and wellbeing support in multiple ways, culminating in its crucial supportive role in the provision of the COVID-19 vaccination rollout across the GM city region. However, the support provided by the VCFSE sector during the pandemic remains under-recognised. The aims of the study were to: understand the views and experiences of marginalised communities in GM during the COVID-19 pandemic; explore how community engagement initiatives played a role during the pandemic and vaccine rollout; assess what can be learnt from the work of key stakeholders (community members, VCFSEs, health-system stakeholders) for future health research and service delivery.MethodsThe co-designed study utilised a participatory approach throughout and was co-produced with a Community Research Advisory Group (CRAG). Focus groups and semi-structured interviews were conducted remotely between September-November 2021, with 35 participants from local marginalised communities, health and care system stakeholders and VCFSE representatives. Thematic framework analysis was used to analyse the data.ResultsLocal communities in GM were not supported sufficiently by mainstream services during the course of the COVID-19 pandemic, resulting in increased pressure onto the VCFSE sector to respond to local communities’ need. Community-based approaches were deemed crucial to the success of the vaccination drive and in providing support to local communities more generally during the pandemic, whereby such approaches were in a unique position to reach members of diverse communities to boost uptake of the vaccine. Despite this, the support delivered by the VCFSE sector remains under-recognised and under-valued by the health system and decision-makers.ConclusionsA number of challenges associated with collaborative working were experienced by the VSCE sector and health system in delivering the vaccination programme in partnership with the VCFSE sector. There is a need to create a broader, more inclusive health system which allows and promotes inter-sectoral working. Flexibility and adaptability in ongoing and future service delivery should be championed for greater cross-sector working.

Utilizing Machine Learning for Context-Aware Digital Biomarker of Stress in Older Adults

Identifying stress in older adults is a crucial field of research in health and well-being. This allows us to take timely preventive measures that can help save lives. That is why a nonobtrusive way of accurate and precise stress detection is necessary. Researchers have proposed many statistical measurements to associate stress with sensor readings from digital biomarkers. With the recent progress of Artificial Intelligence in the healthcare domain, the application of machine learning is showing promising results in stress detection. Still, the viability of machine learning for digital biomarkers of stress is under-explored. In this work, we first investigate the performance of a supervised machine learning algorithm (Random Forest) with manual feature engineering for stress detection with contextual information. The concentration of salivary cortisol was used as the golden standard here. Our framework categorizes stress into No Stress, Low Stress, and High Stress by analyzing digital biomarkers gathered from wearable sensors. We also provide a thorough knowledge of stress in older adults by combining physiological data obtained from wearable sensors with contextual clues from a stress protocol. Our context-aware machine learning model, using sensor fusion, achieved a macroaverage F-1 score of 0.937 and an accuracy of 92.48% in identifying three stress levels. We further extend our work to get rid of the burden of manual feature engineering. We explore Convolutional Neural Network (CNN)-based feature encoder and cortisol biomarkers to detect stress using contextual information. We provide an in-depth look at the CNN-based feature encoder, which effectively separates useful features from physiological inputs. Both of our proposed frameworks, i.e., Random Forest with engineered features and a Fully Connected Network with CNN-based features validate that the integration of digital biomarkers of stress can provide more insight into the stress response even without any self-reporting or caregiver labels. Our method with sensor fusion shows an accuracy and F-1 score of 83.7797% and 0.7552, respectively, without context and 96.7525% accuracy and 0.9745 F-1 score with context, which also constitutes a 4% increase in accuracy and a 0.4 increase in F-1 score from RF.

Cross-jurisdictional Data Transfer in Health Research: Stakeholder Perceptions on the Role of Law

AbstractLarge data-intensive health research programmes benefit from collaboration amongst researchers who may be located in different institutions and international contexts. However, complexities in navigating privacy frameworks and data protection laws across various jurisdictions pose significant challenges to researchers seeking to share or transfer data outside of institutional boundaries. Research on the awareness of data protection and privacy laws amongst stakeholders is limited. Our qualitative study, drawn from a larger project in Singapore, revealed insights into stakeholders’ perceptions of the role of law in cross-national health data research. Stakeholders in our study demonstrated a range of perceptions regarding the role of data protection law in governing the collection and transfer of health data for research. The main criticisms included inadequate legal protection to data and lack of uniformed data protection standards. Despite these criticisms, participants recognised the importance of data protection law in supporting cross-border data transfers and proposed measures to improve perceived limitations of existing laws. These measures include strengthening existing legal framework, establishing contractual agreements and imposing severe punishments for data misuse.

A STOCHASTIC MODEL FOR LENGTH BIASED LOAI DISTRIBUTION WITH PROPERTIES AND ITS APPLICATIONS

One of the most important applications of statistical analysis is in health research and application. Cancer studies are mostly required special statistical considerations in order to find the appropriate model for fitting the survival data. In this paper, we examine some general models leading to a weighted distribution. The developed distribution, also known as the length biased model, is referred to as the length biased Loai distribution. This distribution is a specific type of basic distribution, the Loai distribution. The length biased distribution has been compared with the original distribution. Some statistical properties of this distribution are derived, such as moments, the moment generating function, the reliability analysis, and the included functions. Also, the distribution of order statistics, quantile function, and likelihood ratio test are presented. The Bonferroni and Lorenz carvers, as well as the Rnyi and Tsallis entropies, are derived. The method of maximum likelihood estimation is used to estimate the distribution parameters. A simulation study is performed to investigate the performance of the estimation. The real data applications demonstrate that the proposed distribution can provide better results than several well-known distributions.

Understanding the impact of maternal and infant nutrition on infant/child health: Multiethnic considerations, knowledge translation, and future directions for equitable health research.

A mother's intrauterine environment influences her health and that of her offspring, at birth and in the future. Herein, we present an overview of our Canadian Institutes of Health Research (CIHR)-funded grant "Understanding the impact of maternal and infant nutrition on infant/child health" - set within The NutriGen Birth Cohort Alliance. NutriGen is a consortium of four Canadian prospective birth cohorts representing > 5000 mother-child pairs of diverse ethnic groups including South Asians, White Europeans, and Indigenous peoples. We summarize our objectives and main findings on outcomes of maternal diet, gestational diabetes, birth weight, cardiometabolic health, the microbiome, and epigenetic modifications. We append this work with 10 key messages when conducting multiethnic research and review our knowledge translation products. We describe the clinical impact of our research on maternal and child health and conclude with future directions on biomarker discovery, expansion to other ethnic groups, and interventions for high-risk populations.

National dairy research programs: what is their role in animal health and sustainability research?

The US dairy industry has made great strides in improving animal health over many decades, which has driven substantial improvements in economic, social, and environmental sustainability. As consumer and corporate focus on climate continues to grow, the continued need to research and improve animal health and understand its connection with the environment is integral to the success of the dairy industry. Research to address these areas can be supported by national research programs and collaboration between them. The USDA and Dairy Management Inc established a collaborative research agreement in 2007; to date, this collaboration has not explicitly focused on animal health or its intersection with the environment. It is integral to the success of animal agriculture in an ever-changing sustainability landscape that animal health is addressed as a key piece of socioeconomic and environmental sustainability. An academic-industry stakeholder committee reached a consensus that supported this idea and identified that it is equally important to communicate these research findings with consumers in a way that resonates. The purpose of this Viewpoint article is to highlight that national research programs at the USDA Agricultural Research Service's National Animal Disease Center and Dairy Management Inc can and should play an important role in supporting and facilitating research at the intersection of animal health and sustainability broadly.

A model for supporting biomedical and public health researcher use of publicly available All of Us data at Historically Black Colleges and Universities.

The aim of this study was to describe opportunities and challenges associated with the development and implementation of a program for supporting researchers underrepresented in biomedical research. We describe a case study of the All of Us Researcher Academy supported by the National Institutes of Health (NIH), including feedback from participants, instructors, and coaches. Lessons include the importance of inviting role models into learning networks, establishing and maintaining trusted relationships, and making coaches available for technical questions from researcher participants. Although research has focused on learning outcomes in science, technology, engineering, and mathematics at Minority Serving Institutions in the United States, literature tends to lack models for initiatives to improve everyday research experiences of faculty and researchers at such institutions or to encourage researcher use of public-use data such as that available through NIH's All of Us Research Program. The All of Us Researcher Academy offers a model that addresses these needs.

Mental Health Among Hypertensive People and its Associated Factors: Findings From RISKESDAS 2018 Data

This study aims to investigate the complex relationship between general mental health issues, specifically depression, and hypertension, and to identify associated factors among individuals affected by these conditions in Indonesia. Using data from the Indonesia National Basic Health Research (RISKESDAS) in 2018, the study included a large sample of 88,590 individuals aged 30−59 with hypertension from various provinces and districts across Indonesia. The findings show that 11.5% of hypertensive individuals in the 30−59 age range in Indonesia experience general mental health problems, including common mental disorders, while 7.0% exhibit symptoms of depression. Importantly, individuals with multiple coexisting health conditions are more susceptible to mental health issues. Furthermore, factors such as female gender, lower educational attainment, unmarried status, unemployment, physician-diagnosed hypertension, and the presence of other concurrent health conditions are identified as contributors to an increased likelihood of experiencing general mental health problems and depression. Finally, this study emphasizes the importance of addressing mental health concerns among individuals dealing with hypertension and other non-communicable diseases in Indonesia, with a particular focus on those with lower educational levels, unmarried status, and unemployment.

MHFA pilot in correctional setting benefits COs, inmates

Observing the need and opportunity for corrections officers to effectively respond to at‐risk inmates experiencing a mental health crisis, Rutgers Health researchers, with the assistance of the National Council for Mental Wellbeing, conducted a Mental Health First Aid (MHFA) pilot program in a prison setting. The evidence‐based intervention was aimed at corrections officers (COs), who are considered to be the first line of response in a correctional setting.

Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions

IntroductionThis study conducts a bibliometric analysis on neurofeedback research to assess its current state and potential future developments.MethodsIt examined 3,626 journal articles from the Web of Science (WoS) using co-citation and co-word methods.ResultsThe co-citation analysis identified three major clusters: “Real-Time fMRI Neurofeedback and Self-Regulation of Brain Activity,” “EEG Neurofeedback and Cognitive Performance Enhancement,” and “Treatment of ADHD Using Neurofeedback.” The co-word analysis highlighted four key clusters: “Neurofeedback in Mental Health Research,” “Brain-Computer Interfaces for Stroke Rehabilitation,” “Neurofeedback for ADHD in Youth,” and “Neural Mechanisms of Emotion and Self-Regulation with Advanced Neuroimaging.DiscussionThis in-depth bibliometric study significantly enhances our understanding of the dynamic field of neurofeedback, indicating its potential in treating ADHD and improving performance. It offers non-invasive, ethical alternatives to conventional psychopharmacology and aligns with the trend toward personalized medicine, suggesting specialized solutions for mental health and rehabilitation as a growing focus in medical practice.

Personalized medicine and nutrition in hepatology for preventing chronic liver disease in Mexico

Chronic liver disease is a global health issue. Patients with chronic liver disease require a fresh approach that focuses on the genetic and environmental factors that contribute to disease initiation and progression. Emerging knowledge in the fields of Genomic Medicine and Genomic Nutrition demonstrates differences between countries in terms of genetics and lifestyle risk factors such as diet, physical activity, and mental health in chronic liver disease, which serves as the foundation for the implementation of Personalized Medicine and Nutrition (PerMed-Nut) strategies. Most of the world’s populations have descended from various ethnic groupings. Mexico’s population has a tripartite ancestral background, consisting of Amerindian, European, and African lineages, which is common across Latin America’s regional countries. The purpose of this review is to discuss the genetic and environmental components that could be incorporated into a PerMed-Nut model for metabolic-associated liver disease, viral hepatitis B and C, and hepatocellular carcinoma in Mexico. Additionally, the implementation of the PerMed-Nut approach will require updated medicine and nutrition education curricula. Training and equipping future health professionals and researchers with new clinical and investigative abilities focused on preventing liver illnesses in the field of genomic hepatology globally is a vision that clinicians and nutritionists should be concerned about.

Financial Behavior and Financial Satisfaction of Non-Teaching Personnel in a City Schools Division in Negros Occidental

Financial behavior and financial satisfaction are two essential elements in the lives of the human being like non-teaching personnel. Hence, this study assessed the financial behavior of non-teaching personnel in a city schools division in Negros Occidental in terms of spending habits, borrowing practices, repayment practices, savings, and investments relative to age, sex, civil status, position level, and net take-home pay. Likewise, it determined their financial satisfaction in terms of financial solvency and financial knowledge relative to the demographics. Also, it compared their financial behavior and financial satisfaction when grouped according to the demographics. Lastly, it correlated their financial behavior and financial satisfaction. The study utilized the descriptive-comparative and correlational research design. It was responded by 106 non-teaching personnel and was determined using stratified random sampling. The instruments used were adopted-modified questionnaires. In analyzing the data, mean, standard deviation, Mann Whitney U test, and Spearman rank correlation were employed. Meanwhile, the researcher adhered to the guidelines established by the Philippine Health Research Ethics Board (PHREB). Generally, they have a very high financial behavior and high financial satisfaction. In comparing their financial behavior when grouped according to the demographics, only the net take-home pay has the significant difference. In terms of the financial satisfaction, all demographics resulted no significant differences. Regarding the relationship between the two constructs, there was a significant relationship between their financial behavior and financial satisfaction. Hence, to improve their satisfaction financially, their behavior towards finances should be given attention.