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Fulltext Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa

Mohammed M, Muhammad S, Mohammed FZ, Mustapha S, Sha'aban A, Sani NY, et al.

J Racial Ethn Health Disparities, 2021 10;8(5):1267-1272.
PMID: 33051749 DOI: 10.1007/s40615-020-00888-3

BACKGROUND: The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China and later spread rapidly to other parts of the world, including Africa. Africa was projected to be devastated by COVID-19. There is currently limited data regarding regional predictors of mortality among patients with COVID-19. This study aimed to evaluate the independent risk factors associated with mortality among patients with COVID-19 in Africa.
METHODS: A total of 1028 confirmed cases of COVID-19 from Africa with definite survival outcomes were identified retrospectively from an open-access individual-level worldwide COVID-19 database. The live version of the dataset is available at https://github.com/beoutbreakprepared/nCoV2019 . Multivariable logistic regression was conducted to determine the risk factors that independently predict mortality among patients with COVID-19 in Africa.
RESULTS: Of the 1028 cases included in study, 432 (42.0%) were females with a median (interquartile range, IQR) age of 50 (24) years. Older age (adjusted odds ratio {aOR} 1.06; [95% confidence intervals {95% CI}, 1.04-1.08]), presence of chronic disease (aOR 9.63; [95% CI, 3.84-24.15]), travel history (aOR 2.44; [95% CI, 1.26-4.72]), as well as locations of Central Africa (aOR 0.14; [95% CI, 0.03-0.72]) and West Africa (aOR 0.12; [95% CI, 0.04-0.32]) were identified as the independent risk factors significantly associated with increased mortality among the patients with COVID-19.
CONCLUSIONS: The COVID-19 pandemic is evolving gradually in Africa. Among patients with COVID-19 in Africa, older age, presence of chronic disease, travel history, and the locations of Central Africa and West Africa were associated with increased mortality. A regional response should prioritize strategies that will protect these populations. Also, conducting a further in-depth study could provide more insights into additional factors predictive of mortality in COVID-19 patients.
Fulltext Assessment of COVID-19 Information Overload Among the General Public

Mohammed M, Sha'aban A, Jatau AI, Yunusa I, Isa AM, Wada AS, et al.

J Racial Ethn Health Disparities, 2022 Feb;9(1):184-192.
PMID: 33469869 DOI: 10.1007/s40615-020-00942-0

BACKGROUND: A relentless flood of information accompanied the novel coronavirus 2019 (COVID-19) pandemic. False news, conspiracy theories, and magical cures were shared with the general public at an alarming rate, which may lead to increased anxiety and stress levels and associated debilitating consequences.
OBJECTIVES: To measure the level of COVID-19 information overload (COVIO) and assess the association between COVIO and sociodemographic characteristics among the general public.
METHODS: A cross-sectional online survey was conducted between April and May 2020 using a modified Cancer Information Overload scale. The survey was developed and posted on four social media platforms. The data were only collected from those who consented to participate. COVIO score was classified into high vs. low using the asymmetrical distribution as a guide and conducted a binary logistic regression to examine the factors associated with COVIO.
RESULTS: A total number of 584 respondents participated in this study. The mean COVIO score of the respondents was 19.4 (± 4.0). Sources and frequency of receiving COVID-19 information were found to be significant predictors of COVIO. Participants who received information via the broadcast media were more likely to have high COVIO than those who received information via the social media (adjusted odds ratio ([aOR],14.599; 95% confidence interval [CI], 1.608-132.559; p = 0.017). Also, participants who received COVID-19 information every minute (aOR, 3.892; 95% CI, 1.124-13.480; p = 0.032) were more likely to have high COVIO than those who received information every week.
CONCLUSION: The source of information and the frequency of receiving COVID-19 information were significantly associated with COVIO. The COVID-19 information is often conflicting, leading to confusion and overload of information in the general population. This can have unfavorable effects on the measures taken to control the transmission and management of COVID-19 infection.
Psychometric Properties and Assessment of Knowledge, Attitude, and Practice Towards ChatGPT in Pharmacy Practice and Education: a Study Protocol

Mohammed M, Kumar N, Zawiah M, Al-Ashwal FY, Bala AA, Lawal BK, et al.

J Racial Ethn Health Disparities, 2023 Jul 10.
PMID: 37428357 DOI: 10.1007/s40615-023-01696-1

ChatGPT represents an advanced conversational artificial intelligence (AI), providing a powerful tool for generating human-like responses that could change pharmacy prospects. This protocol aims to describe the development, validation, and utilization of a tool to assess the knowledge, attitude, and practice towards ChatGPT (KAP-C) in pharmacy practice and education. The development and validation process of the KAP-C tool will include a comprehensive literature search to identify relevant constructs, content validation by a panel of experts for items relevancy using content validity index (CVI) and face validation by sample participants for items clarity using face validity index (FVI), readability and difficulty index using the Flesch-Kincaid Readability Test, Gunning Fog Index, or Simple Measure of Gobbledygook (SMOG), assessment of reliability using internal consistency (Cronbach's alpha), and exploratory factor analysis (EFA) to determine the underlying factor structures (eigenvalues, scree plot analysis, factor loadings, and varimax). The second phase will utilize the validated KAP-C tool to conduct KAP surveys among pharmacists and pharmacy students in selected low- and middle-income countries (LMICs) (Nigeria, Pakistan, and Yemen). The final data will be analyzed descriptively using frequencies, percentages, mean (standard deviation) or median (interquartile range), and inferential statistics like Chi-square or regression analyses using IBM SPSS version 28. A p<0.05 will be considered statistically significant. ChatGPT holds the potential to revolutionize pharmacy practice and education. This study will highlight the psychometric properties of the KAP-C tool that assesses the knowledge, attitude, and practice towards ChatGPT in pharmacy practice and education. The findings will contribute to the potential ethical integration of ChatGPT into pharmacy practice and education in LMICs, serve as a reference to other economies, and provide valuable evidence for leveraging AI advancements in pharmacy.
Lost in Translation: Impact of Language Barriers and Facilitators on the Health Care of Asian Americans Living with HIV

Chen WT, Sun W, Huang F, Shiu CS, Kim B, Candelario J, et al.

J Racial Ethn Health Disparities, 2023 Jun 12.
PMID: 37306920 DOI: 10.1007/s40615-023-01674-7

Language barriers are major obstacles that Asian American immigrants face when accessing health care in the USA. This study was conducted to explore the impact of language barriers and facilitators on the health care of Asian Americans. Qualitative, in-depth interviews and quantitative surveys were conducted with 69 Asian Americans (Chinese, Filipino, Japanese, Malaysian, Indonesian, Vietnamese, and mixed Asian backgrounds) living with HIV (AALWH) in three urban areas (New York, San Francisco, and Los Angeles) in 2013 and from 2017 to 2020. The quantitative data indicate that language ability is negatively associated with stigma. Major themes emerged related to communication, including the impact of language barriers on HIV care and the positive impact of language facilitators-family members/friends, case managers, or interpreters-who can communicate with healthcare providers in the AALWH's native language. Language barriers negatively impact access to HIV-related services and thus result in decreased adherence to antiretroviral therapy, increased unmet healthcare needs, and increased HIV-related stigma. Language facilitators enhanced the connection between AALWH and the healthcare system by facilitating their engagement with health care providers. Language barriers experienced by AALWH not only impact their healthcare decisions and treatment choices but also increase levels of external stigma which may influence the process of acculturation to the host country. Language facilitators and barriers to health services for AALWH represent a target for future interventions in this population.
Fulltext Advancing Health Disparities Research: The Need to Include Asian American Subgroup Populations

Yom S, Lor M

J Racial Ethn Health Disparities, 2022 Dec;9(6):2248-2282.
PMID: 34791615 DOI: 10.1007/s40615-021-01164-8

BACKGROUND: Despite recognition that the health outcomes of Asian American subgroups are heterogeneous, research has mainly focused on the six largest subgroups. There is limited knowledge of smaller subgroups and their health outcomes. This scoping review identifies trends in the health outcomes, reveals those which are under-researched, and provide recommendations on data collection with 24 Asian American subgroups.
METHODS: Our literature search of peer-reviewed English language primary source articles published between 1991 and 2018 was conducted across six databases (Embase, PubMed, Web of Sciences, CINAHL, PsychINFO, Academic Search Complete) and Google Scholar, yielding 3844 articles. After duplicate removal, we independently screened 3413 studies to determine whether they met inclusion criteria. Seventy-six studies were identified for inclusion in this review. Data were extracted on study characteristics, content, and findings.
FINDINGS: Seventy-six studies met the inclusion criteria. The most represented subgroups were Chinese (n = 74), Japanese (n = 60), and Filipino (n = 60), while Indonesian (n = 1), Malaysian (n = 1), and Burmese (n = 1) were included in only one or two studies. Several Asian American subgroups listed in the 2010 U.S. Census were not represented in any of the studies. Overall, the most studied health conditions were cancer (n = 29), diabetes (n = 13), maternal and infant health (n = 10), and cardiovascular disease (n = 9). Studies showed that health outcomes varied greatly across subgroups.
CONCLUSIONS: More research is required to focus on smaller-sized subgroup populations to obtain accurate results and address health disparities for all groups.