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Physical characteristics used to identify racial groups vary with geography and do not correspond to underlying biological traits” (Cerdeña et al., 2020). [...]race is not a biological reality but a social construct. During the study, penicillin was later identified as an appropriate treatment for syphilis; however, treatment was withheld while researchers continued observing the progression of the disease among participants. Throughout the study, the boys were placed on a low-protein diet, not allowed water intake during overnight sessions and were not given any prescribed maintenance medications for underlying chronic conditions, such as asthma (Brown, 2003). [...]HeLa cells have been used for human genome studies, virology and for the development of the COVID-19 vaccine (Johns Hopkins Medicine, 2022).

While all healthcare workers are exposed to occupational hazards, workers in sub-Saharan Africa have higher rates of occupational exposure to infectious diseases than workers in developed countries. Identifying prevalence and context of exposure to blood and bloodborne pathogens may help guide policies for prevention. This systematic review examined occupational exposure rates to blood and bloodborne pathogen among healthcare workers in sub-Saharan Africa. In November 2017, a comprehensive literature search was conducted to identify studies reporting exposure of health workers in African coutnries to blood and bodily fluids. Title, abstract and full text screening were used to narrow our search. Studies more than 10 years old, or published in non-English languages were excluded. Fifteen studies reported a variety of exposures. The lifetime prevalence of needlestick injury ranged from 22-95%, and one-year prevalence ranged from 39-91%. Studies included a range of descriptive statistics of knowledge, attitudes, practice and access factors related to exposures. Two studies reported 21-32% of respondents linked poor knowledge or training with prevention of needlestick injuries. Rates of recapping needles ranged from 12-57% in four studies. Attitudes were generally positive toward occupational safety procedures while access was poor. The high burden of blood and bloodborne pathogen exposures demonstrated here indicates a high risk for contracting bloodborne illnesses. Although the data are sparse, implementation of preventative policies based on current knowledge remains critical to minimize risk and reduce exposure. There remains a pressing need for high quality data on occupational hazards to identify the burden of exposures and inform preventive policies in Sub-Saharan Africa. Additional studies are needed to determine whether differential exposures exist between professions and the associations with knowledge, attitudes, practices, and access factors to create targeted strategies to diminish occupational hazards.

Background: Smartphone ownership and mobile app use are steadily increasing in individuals of diverse racial and ethnic backgrounds living in the United States. Growing adoption of technology creates a perfect opportunity for digital health interventions to increase access to health care. To successfully implement digital health interventions and engage users, intervention development should be guided by user input, which is best achieved by the process of co-design. Digital health interventions co-designed with the active engagement of users have the potential to increase the uptake of guideline recommendations, which can reduce morbidity and mortality and advance health equity. Objective: We aimed to co-design a digital health intervention for patients with atrial fibrillation, the most common cardiac arrhythmia, with patient, caregiver, and clinician feedback and to describe our approach to human-centered design for building digital health interventions. Methods: We conducted virtual meetings with patients with atrial fibrillation (n=8), their caregivers, and clinicians (n=8). We used the following 7 steps in our co-design process: step 1, a virtual meeting focused on defining challenges and empathizing with problems that are faced in daily life by individuals with atrial fibrillation and clinicians; step 2, a virtual meeting focused on ideation and brainstorming the top challenges identified during the first meeting; step 3, individualized onboarding of patients with an existing minimally viable version of the atrial fibrillation app; step 4, virtual prototyping of the top 3 ideas generated during ideation; step 5, further ranking by the study investigators and engineers of the ideas that were generated during ideation but were not chosen as top-3 solutions to be prototyped in step 4; step 6, ongoing engineering work to incorporate top-priority features in the app; and step 7, obtaining further feedback from patients and testing the atrial fibrillation digital health intervention in a pilot clinical study. Results: The top challenges identified by patients and caregivers included addressing risk factor modification, medication adherence, and guidance during atrial fibrillation episodes. Challenges identified by clinicians were complementary and included patient education, addressing modifiable atrial fibrillation risk factors, and remote atrial fibrillation episode management. Patients brainstormed more than 30 ideas to address the top challenges, and the clinicians generated more than 20 ideas. Ranking of the ideas informed several novel or modified features aligned with the Theory of Health Behavior Change, features that were geared toward risk factor modification; patient education; rhythm, symptom, and trigger correlation for remote atrial fibrillation management; and social support. Conclusions: We co-designed an atrial fibrillation digital health intervention in partnership with patients, caregivers, and clinicians by virtually engaging in collaborative creation through the design process. We summarize our experience and describe a flexible approach to human-centered design for digital health intervention development that can guide innovative clinical investigators.

The Ghanaian health system is plagued with several challenges including poor transportation systems, inadequate logistics and medical equipment and relevant human resource to enhance healthcare delivery (Sulemana & Dinye, 2014). Furthermore, Ghana is experiencing a double burden of communicable and noncommunicable diseases, which threatens efforts to achieve the sustainable development goals. [...]we seek to describe the state of nursing education and practice in Ghana and highlight the role of The Ghanaian-Diaspora Nursing Alliance (G-DNA) in supporting efforts to enhance nursing education and practice to improve the health of Ghanaians. Between 2008 and 2018, the nursing and midwifery workforce increased by almost 370% due to a Human Resources for Health (HRH) strategy implemented by the Ministry of Health between 2007 and 2011 in response to the human resource crisis in the African region (Asamani et al., 2019). The 2021 Ghana Health Service Holistic Assessment Report showed that the number of nurses in Ghana particularly enrolled and community health increased from 44,167 in 2020 to 58,217 in 2021 (Asamani et al., 2019; Ghana Health Service, 2022).

Background Almost twenty percent of adults with COVID-19 develop Long COVID, leading to prolonged symptoms and disability. Understanding the supportive needs of people with Long COVID is vital to enacting effective models of care and policies. Design/methods This qualitative sub-study explored the experiences of people with Long COVID and their unmet needs. Participants enrolled in a larger study to evaluate the post-acute cardiovascular impacts of COVID-19 were invited to participate in subsequent in-depth interviews. Participants were enrolled purposively until saturation at 24 participants. Data were analyzed using thematic content analysis. Results Participants focused on adaptations to life with Long COVID and their unmet needs in different life spheres. Three domains, 1) occupational and financial; 2) healthcare-related; and 3) social and emotional support, emerged as areas affecting quality of life. Although participants were motivated to return to work for financial and personal reasons, Long COVID symptoms often resulted in the inability to perform tasks required by their existing jobs, and unemployment. Those who maintained employment through employer accommodations still needed additional support. Participants encountered diagnostic challenges, challenges in accessing specialty appointments, insurance loopholes, high healthcare costs, and medical skepticism. Existing social networks provided support for completing daily tasks; however, those with Long COVID typically turned to others with similar lived experiences for emotional support. Participants found government support programs inadequate and difficult to access in all three domains. Discussion We propose a five-pronged policy approach to support persons with Long COVID. These overarching recommendations are (1) improve public awareness of Long COVID; (2) improve clinical care quality and access; (3) implement additional school and workplace accommodations; (4) strengthen socioeconomic benefits and social services; and (5) improve research on Long COVID.

Telemedicine expanded during the COVID-19 pandemic, though use differed by age, sex, race or ethnicity, educational attainment, income, and location. It is unclear if high telehealth use or inequities persisted late into the pandemic. This study aims to evaluate the prevalence of, inequities in, and primary reasons for telehealth visits a year after telemedicine expansion. We used cross-sectional data from the 2022 Health Information National Trends Survey (HINTS 6), the first cycle with data on telemedicine. In total, 4830 English- and Spanish-speaking US adults (aged ≥18 years) were included in this study. The primary outcomes were telehealth visit attendance in the 12 months before March 7, 2022, to November 8, 2022, and the primary reason for the most recent telehealth visit. We evaluated sociodemographic and clinical predictors of telehealth visit attendance and the primary reason for the most recent telehealth visit through Poisson regression. Analyses were weighted according to HINTS 6 standards. We included 4830 participants (mean age 48.3, SD 17.5 years; 50.28% women; 65.21% White). Among US adults, 38.78% reported having a telehealth visit in the previous year. Telehealth visit attendance rates were similar across age, race or ethnicity, income, and urban versus rural location. However, individuals with a telehealth visit were less likely to live in the Midwest (adjusted prevalence ratio [aPR] 0.65, 95% CI 0.54-0.77), and more likely to be women (aPR 1.21, 95% CI 1.06-1.38), college graduates or postgraduates (aPR 1.24, 95% CI 1.05-1.46), covered by health insurance (aPR 1.56, 95% CI 1.08-2.26), and married or cohabitating (aPR 1.17, 95% CI 1.03-1.32), adjusting for sociodemographic characteristics, frequency of health care visits, and comorbidities. Among participants with a telehealth visit in the past year, the primary reasons for their most recent visit were minor or acute illness (32.15%), chronic disease management (21%), mental health or substance abuse (16.94%), and an annual exam (16.22%). Older adults were more likely to report that the primary reason for their most recent telehealth visit was for chronic disease management (aPR 2.08, 95% CI 1.33-3.23), but less likely to report that it was for a mental health or substance abuse issue (aPR 0.19, 95% CI 0.10-0.35), adjusting for sociodemographic characteristics and frequency of health care visits. Among US adults, telehealth visit attendance was high more than a year after telemedicine expansion and did not differ by age, race or ethnicity, income, or urban versus rural location. Telehealth could continue to be leveraged following COVID-19 to improve access to care and health equity.

Mobile health (mHealth) technology has the potential to support shared decision-making (SDM) and improve hypertension control. However, our understanding of the variations in individuals’ involvement in SDM and mHealth usage across different racial and ethnic groups in the United States is still limited. This study aimed to investigate the extent of involvement in SDM and the usage of mHealth technology in health-related activities among US adults with hypertension from diverse racial and ethnic backgrounds and to examine whether the mHealth usage differed by individuals’ level of engagement in SDM. This study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey, which was conducted on US adults with self-reported hypertension, and race and ethnicity data were included. The exposure of interest was race and ethnicity. The outcomes were SDM and mHealth usage. SDM was assessed using an item: “In the past 12 months, how often did your health professional: involve you in decisions about your healthcare as much as you wanted?” mHealth usage was defined as using a smartphone or tablet to engage in (1) making health decisions, (2) discussing health decisions with health providers, (3) tracking health progress, and (4) sharing health information. Weighted multivariable logistic regression models were used to examine the association between race and ethnicity and SDM or mHealth usage adjusted for covariates and stratified by the level of engagement in SDM. This study included 4893 adults with hypertension, and the mean age was 61 (SD 13) years. The sample was 53% female, 61% (n=3006) non-Hispanic White, 19% (n=907) non-Hispanic Black or African American, 12% (n=605) Hispanic, 4% (n=193) non-Hispanic Asian, and 4% (n=182) non-Hispanic other. Compared to the non-Hispanic White adults, non-Hispanic Black adults were more likely to use mHealth to make health decisions (adjusted odds ratio [aOR] 1.70, 95% CI 1.23-2.34), share health information (aOR 1.46, 95% CI 1.02-2.08), and discuss health decisions with health providers (aOR 1.38, 95% CI 1.02-1.87). Significant associations were observed specifically among those who were always involved in SDM. Asian adults were less likely to be involved in SDM (aOR 0.51, 95% CI 0.26-0.99) and were more likely to use mHealth to track progress on a health-related goal (aOR 2.07, 95% CI 1.28-3.34) than non-Hispanic White adults. Hispanic adults were less likely to use mHealth to share health information (aOR 0.47, 95% CI 0.33-0.67) and discuss health decisions with health providers (aOR 0.65, 95% CI 0.46-0.94) compared to non-Hispanic White adults. This study observed racial and ethnic disparities in SDM and mHealth usage among US adults with hypertension. These findings emphasize the significance of comprehending the involvement of SDM and the usage of mHealth technology within racially and ethnically diverse populations.

BackgroundForced displacement has created widespread health disparities, with refugees experiencing disproportionate risks of chronic conditions like hypertension. In the United States, a limited understanding of how knowledge, attitudes, and practices (KAP) shape blood pressure (BP) outcomes continues to hinder equitable care. This study explores the relationship between KAP and BP control among Iraqi and Syrian refugees who resettled in the United States.MethodsIraqi and Syrian refugees (n = 95) with hypertension at a federally qualified health center in San Diego, California, participated in this study. They completed a survey in Arabic assessing KAP based on a scale validated in non-English speakers and were instructed to do home BP monitoring using digital cuffs for at least 3 days per week for 4 weeks. The outcome was BP control based on the American College of Cardiology (ACC) criteria, calculated from an average of home BP readings. Mixed-effect logistic regression was used to assess the relationship between each KAP quartile and BP control. KAP quartile was categorized into (poor, fair, good, excellent).ResultsParticipants were 56% male, and the mean age was 58.8 (± 15.97) years. 86% were unemployed, 40% had at least a bachelor’s degree, 63% had limited English proficiency, and only 3.6% had an annual income of ≥$35,000. Mean BP was 129/79 mmHg (SD systolic: 22.17 mmHg; SD diastolic: 11.15 mmHg). Scores were computed for each KAP sub-scale: knowledge (0–16), attitude (1–20), and practice (1–8). Knowledge 13.2 (± 2.37), attitude 14.6 (± 2.38), and practice 6.5 (± 1.17). Higher knowledge levels were associated with higher odds of BP control (OR 1.89, 95% CI 1.39–2.55). An inverse relationship was observed between attitudes and BP control: participants with “Fair” and “Good” scores had reduced odds of BP control (OR = 0.63, 95% CI: 0.52–0.77; and OR = 0.58, 95% CI: 0.45–0.75, respectively).ConclusionsThese findings highlight the urgent need for culturally grounded health education and systems-level strategies that address both informational and perceptual barriers to BP control. Advancing health equity for refugee populations demands interventions that go beyond awareness, integrating trust-building, accessibility, and empowerment into chronic disease management.

Self-care is a critical component of chronic disease management and is linked to better health outcomes. The Hypertension Self-Care Profile (HBP SCP) is one of the few validated instruments designed to assess not only behaviors but also self-efficacy and motivation in HBP self-care. This scoping review synthesized published research using the HBP SCP to examine its scope and utility across diverse populations. A total of 48 studies were reviewed—34 non-validation studies and 14 validation studies—spanning regions including Asia, the Middle East, and the Americas. The HBP SCP showed strong psychometric performance across multiple cultural adaptations, with Cronbach’s alpha values ranging from 0.73 to 0.99. Several correlates of HBP self-care emerged, including self-efficacy, social support, health literacy, and education. Findings also revealed that HBP self-care remains suboptimal, particularly among rural populations and low- and middle-income countries. The HBP SCP has proven to be a versatile and culturally adaptable instrument for evaluating HBP self-care behaviors, self-efficacy, and motivation. Its consistently demonstrated validity and reliability across diverse contexts, combined with its responsiveness in randomized controlled trials, affirm its value as both a clinical assessment tool and a research outcome measure in interventions aimed at improving cardiovascular health.

Numerous studies have suggested that the relationship between cardiovascular disease (CVD) risk and the usage of mobile health (mHealth) technology may vary depending on the total number of CVD risk factors present. However, whether higher CVD risk is associated with a greater likelihood of engaging in specific mHealth use among US adults is currently unknown. We aim to assess the associations between the composite CVD risk and each component of mHealth use among US adults regardless of whether they have a history of CVD or not. This study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey. The exposure was CVD risk (diabetes, hypertension, smoking, physical inactivity, and overweight or obesity). We defined low, moderate, and high CVD risk as having 0-1, 2-3, and 4-5 CVD risk factors, respectively. The outcome variables of interest were each component of mHealth use, including using mHealth to make health decisions, track health progress, share health information, and discuss health decisions with health providers. We used multivariable logistic regression models to examine the association between CVD risk and mHealth use adjusted for demographic factors. We included 10,531 adults, with a mean age of 54 (SD 16.2) years. Among the included participants, 50.2% were men, 65.4% were non-Hispanic White, 41.9% used mHealth to make health decisions, 50.8% used mHealth to track health progress toward a health-related goal, 18.3% used mHealth to share health information with health providers, and 37.7% used mHealth to discuss health decisions with health providers (all are weighted percentages). Adults with moderate CVD risk were more likely to use mHealth to share health information with health providers (adjusted odds ratio 1.49, 95% CI 1.24-1.80) and discuss health decisions with health providers (1.22, 95% CI 1.04-1.44) compared to those with low CVD risk. Similarly, having high CVD risk was associated with higher odds of using mHealth to share health information with health providers (2.61, 95% CI 1.93-3.54) and discuss health decisions with health providers (1.56, 95% CI 1.17-2.10) compared to those with low CVD risk. Upon stratifying by age and gender, we observed age and gender disparities in the relationship between CVD risk and the usage of mHealth to discuss health decisions with health providers. Adults with a greater number of CVD risk factors were more likely to use mHealth to share health information with health providers and discuss health decisions with health providers. These findings suggest a promising avenue for enhancing health care communication and advancing both primary and secondary prevention efforts related to managing CVD risk factors through the effective usage of mHealth technology.