High prevalence of chronic viral hepatitis B and C in Minnesota Somalis contributes to rising hepatocellular carcinoma incidence

BACKGROUND: Chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections are known risk factors for liver disease, cirrhosis and hepatocellular carcinoma (HCC). There is substantial global variation in HBV and HCV prevalence resulting in variations in cirrhosis and HCC. We previously reported high prevalence of HBV and HCV infections in Somali immigrants seen at an academic medical center in Minnesota. AIM: To determine the prevalence of chronic viral hepatitis in Somali immigrants in Minnesota through a community-based screening program. METHODS: We conducted a prospective community-based participatory research study in the Somali community in Minnesota in partnership with community advisory boards, community clinics and local mosques between November 2010 and December 2015 (data was analyzed in 2020). Serum was tested for hepatitis B surface antigen, hepatitis B core antibody, hepatitis B surface antibody and anti-HCV antibody. RESULTS: Of 779 participants, 15.4% tested positive for chronic HBV infection, 50.2% for prior exposure to HBV and 7.6% for chronic HCV infection. Calculated age-adjusted frequencies in males and females for chronic HBV were 12.5% and 11.6%; for prior exposure to HBV were 44.8% and 41.3%; and for chronic HCV were 6.7% and 5.7%, respectively. Seven participants developed incident HCC during follow up. CONCLUSION: Chronic HBV and HCV are major risk factors for liver disease and HCC among Somali immigrants, with prevalence of both infections substantially higher than in the general United States population. Community-based screening is essential for identifying and providing health education and linkage to care for diagnosed patients

Embedding Archival Collections in the Postgraduate Curriculum at Maynooth University Library

The Ken Saro-Wiwa Archive, a collection of deathrow correspondence and other material from Nigerian writer and activist Ken Saro-Wiwa to Irish nun Sister Majella McCarron (OLA), is one of Maynooth University Library’s most hard-working collections. Since acquiring the archive in 2011, it has been utilised as part of a wide range of outreach experiences, including seminars, exhibitions (nationally and internationally), blog posts, articles, poetry workshops, school visits, and guided tours.Most recently, the collection was the focus of a workshop delivered as part of the module Peace, Religion and Diplomacy offered on both the MA in Mediation and Conflict Intervention and the MA in International Peacebuilding, Security, and Development Practice at Maynooth University (MU). New approaches to skill acquisition and critical thinking using primary sources are increasingly common across campus and beyond. They present to the Library exciting ways to engage with users, and to the archivists awonderful opportunity to share their knowledge and love of archival collections to an engaged and enthusiastic audience

Embedding Archival Collections in the Postgraduate Curriculum at Maynooth University Library

The Ken Saro-Wiwa Archive, a collection of deathrow correspondence and other material from Nigerian writer and activist Ken Saro-Wiwa to Irish nun Sister Majella McCarron (OLA), is one of Maynooth University Library’s most hard-working collections. Since acquiring the archive in 2011, it has been utilised as part of a wide range of outreach experiences, including seminars, exhibitions (nationally and internationally), blog posts, articles, poetry workshops, school visits, and guided tours.Most recently, the collection was the focus of a workshop delivered as part of the module Peace, Religion and Diplomacy offered on both the MA in Mediation and Conflict Intervention and the MA in International Peacebuilding, Security, and Development Practice at Maynooth University (MU). New approaches to skill acquisition and critical thinking using primary sources are increasingly common across campus and beyond. They present to the Library exciting ways to engage with users, and to the archivists awonderful opportunity to share their knowledge and love of archival collections to an engaged and enthusiastic audience

Disrupted reward processing in Parkinson's disease and its relationship with dopamine state and neuropsychiatric syndromes: a systematic review and meta-analysis

Background: Neuropsychiatric symptoms are common in Parkinson’s disease (PD) and predict poorer outcomes. Reward processing dysfunction is a candidate mechanism for the development of psychiatric symptoms including depression and impulse control disorders (ICDs). We aimed to determine whether reward processing is impaired in PD and its relationship with neuropsychiatric syndromes and dopamine replacement therapy. // Methods: The Ovid MEDLINE/PubMed, Embase and PsycInfo databases were searched for articles published up to 5 November 2020. Studies reporting reward processing task performance by patients with PD and healthy controls were included. Summary statistics comparing reward processing between groups were converted to standardised mean difference (SMD) scores and meta-analysed using a random effects model. // Results: We identified 55 studies containing 2578 participants (1638 PD and 940 healthy controls). Studies assessing three subcomponent categories of reward processing tasks were included: option valuation (n=12), reinforcement learning (n=37) and reward response vigour (n=6). Across all studies, patients with PD on medication exhibited a small-to-medium impairment versus healthy controls (SMD=0.34; 95% CI 0.14 to 0.53), with greater impairments observed off dopaminergic medication in within-subjects designs (SMD=0.43, 95% CI 0.29 to 0.57). Within-subjects subcomponent analysis revealed impaired processing off medication on option valuation (SMD=0.57, 95% CI 0.39 to 0.75) and reward response vigour (SMD=0.36, 95% CI 0.13 to 0.59) tasks. However, the opposite applied for reinforcement learning, which relative to healthy controls was impaired on-medication (SMD=0.45, 95% CI 0.25 to 0.65) but not off-medication (SMD=0.28, 95% CI −0.03 to 0.59). ICD was the only neuropsychiatric syndrome with sufficient studies (n=13) for meta-analysis, but no significant impairment was identified compared tonon-ICD patients (SMD=−0.02, 95% CI −0.43 to 0.39). // Conclusion: Reward processing disruption in PD differs according to subcomponent and dopamine medication state, and warrants further study as a potential treatment target and mechanism underlying associated neuropsychiatric syndromes

Identifying contributors to disparities in patient access of online medical records: Examining the role of clinician encouragement

OBJECTIVE: The aim of this study was to understand the influence of clinician encouragement and sociodemographic factors on whether patients access online electronic medical records (EMR). MATERIALS AND METHODS: We analyzed 3279 responses from the Health Information National Trends Survey 5 cycle 4 survey, a cross-sectional, nationally representative survey administered by the National Cancer Institute. Frequencies and weighted proportions were calculated to compare clinical encouragement and access to their online EMR. Using multivariate logistic regression, we identified factors associated with online EMR use and clinician encouragement. RESULTS: In 2020, an estimated 42% of US adults accessed their online EMR and 51% were encouraged by clinicians to access their online EMR. In multivariate regression, respondents who accessed EMR were more likely to have received clinician encouragement (odds ratio [OR], 10.3; 95% confidence interval [CI], 7.7-14.0), college education or higher (OR, 1.9; 95% CI, 1.4-2.7), history of cancer (OR, 1.5; 95% CI, 1.0-2.3), and history of chronic disease (OR, 2.3; 95% CI, 1.7-3.2). Male and Hispanic respondents were less likely to have accessed EMR than female and non-Hispanic White respondents (OR, 0.6; 95% CI, 0.5-0.8, and OR, 0.5; 95% CI, 0.3-0.8, respectively). Respondents receiving encouragement from clinicians were more likely to be female (OR, 1.7; 95% CI, 1.3-2.3), have college education (OR, 1.5; 95% CI, 1.1-2.0), history of cancer (OR, 1.8; 95% CI, 1.3-2.5), and greater income levels (OR, 1.8-3.6). DISCUSSION: Clinician encouragement of patient EMR use is strongly associated with patients accessing EMR, and there are disparities in who receives clinician encouragement related to education, income, sex, and ethnicity. CONCLUSIONS: Clinicians have an important role to ensure that all patients benefit from online EMR use

Early Stage Breast Cancer and Its Association with Diet and Exercise-Related Perceptions and Behaviors to Prevent Recurrence

Background The favorable prognosis for early stage breast cancer survivors may be a reason for the minimal research regarding their quality of life. Prior research has observed more long-term weight gain among early stage survivors compared to cancer-free women of a similar age. It would be useful to study survivors’ perceptions and reported behaviors regarding diet and exercise to see if there is a correlation with previous studies. Methods A sample of 700 breast cancer survivors from Ohio and Michigan was randomly selected from the Northwest Ohio affiliate of the Susan G. Komen For the Cure mailing list and sent a survey for completion. Results 389 survivors completed the survey and among Stage 1 (50/197 = 25.4%) and Stage 2 survivors (24/105 = 22.9%), a small proportion had a positive correlation between self-reported dietary behaviors and their perceived benefits of eating fruits and vegetables. Similar correlations were observed between their self-reported exercise behaviors and their perceived benefits of exercise (Stage 1: 36/197 = 18.3%, Stage 2: 18/105 = 17.1%). Conclusions Regardless of stage, a small proportion of survivors’ self-reported dietary and exercise behaviors match their perceived benefits of diet and exercise. Factors such as access, motivation, and lack of co-morbidities among early stage survivors may prevent them from living healthier post-diagnosis. More thorough dietary and clinical measurements will provide greater certainty. Thus, innovative, sustainable programs must be accessible and provide motivation and social support from family, friends, and other survivors to truly improve quality of life

Differences in electronic personal health information tool use between rural and urban cancer patients in the United States: Secondary data analysis

BACKGROUND: Studies have previously shown that rural cancer patients are diagnosed at later stages of disease. This delay is felt throughout treatment and follow-up, reflected in the fact that rural patients often have poorer clinical outcomes compared with their urban counterparts. OBJECTIVE: Few studies have explored whether there is a difference in cancer patients\u27 current use of health information technology tools by residential location. METHODS: Data from 7 cycles of the Health Information National Trends Survey (HINTS, 2003-2017) were merged and analyzed to examine whether differences exist in managing electronic personal health information (ePHI) and emailing health care providers among rural and urban cancer patients. Geographic location was categorized using Rural-Urban Continuum Codes (RUCCs). Bivariate analyses and multivariable logistic regression were used to determine whether associations existed between rural/urban residency and use of health information technology among cancer patients. RESULTS: Of the 3031 cancer patients/survivors who responded across the 7 cycles of HINTS, 797 (26.9%) resided in rural areas. No difference was found between rural and urban cancer patients in having managed ePHI in the past 12 months (OR 0.78, 95% CI 0.43-1.40). Rural cancer patients were significantly less likely to email health care providers than their urban counterparts (OR 0.52, 95% CI 0.32-0.84). CONCLUSIONS: The digital divide between rural and urban cancer residents does not extend to general ePHI management; however, electronic communication with providers is significantly lower among rural cancer patients than urban cancer patients. Further research is needed to determine whether such disparities extend to other health information technology tools that might benefit rural cancer patients as well as other chronic conditions

Closing the gap between ecosystem management and ecosystem research

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45450/1/11077_2004_Article_162710.pd

Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review

Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been little research into how to make the most of SBDH information from EHRs. Methods: A systematic search was conducted in six databases to find relevant peer-reviewed publications that had recently been published. Relevance was determined by screening and evaluating the articles. Based on selected relevant studies, a methodological analysis of AI algorithms leveraging SBDH information in EHR data was provided. Results: Our synthesis was driven by an analysis of SBDH categories, the relationship between SBDH and healthcare-related statuses, and several NLP approaches for extracting SDOH from clinical literature. Discussion: The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using Natural Language Processing (NLP) technology to support the extraction of SBDH and other clinical ideas simplifies the identification and extraction of essential concepts from clinical data, efficiently unlocks unstructured data, and aids in the resolution of unstructured data-related issues. Conclusion: Despite known associations between SBDH and disease, SBDH factors are rarely investigated as interventions to improve patient outcomes. Gaining knowledge about SBDH and how SBDH data can be collected from EHRs using NLP approaches and predictive models improves the chances of influencing health policy change for patient wellness, and ultimately promoting health and health equity. Keywords: Social and Behavioral Determinants of Health, Artificial Intelligence, Electronic Health Records, Natural Language Processing, Predictive ModelComment: 32 pages, 5 figure