Community outreach and engagement to increase colorectal cancer screening in ethnic minority communities

PURPOSE: Colorectal cancer (CRC) is preventable with screening, yet remains the second leading cause of cancer deaths in the U.S. Nationally, CRC screening substantially declined during the COVID-19 pandemic and is underutilized by ethnic minorities and in safety-net systems. Therefore, City of Hope partnered with Federally Qualified Health Centers (FQHCs) and community and faithbased organizations to improve CRC screening among medically underserved communities. METHOD(S): Between October 2020 and October 2022, we implemented a multi-component intervention that included community outreach and education (a multi-ethnic multimedia campaign and community training adapted from the NCI Screen2Save (S2S) program) and clinic-based interventions (provider/staff training and patient education). Intervention reach and training participant surveys were assessed. Within our four FQHC sites, we also compared clinic-level CRC screening rates among age-eligible patients before (June 2021) and after implementation of the clinic-based intervention (June 2022). RESULT(S): Our reach assessment showed that our multi-ethnic multimedia campaign reached 35.4 million impressions, our S2S education training reached 300 diverse community members, and our provider/staff training reached 150 medical providers. Among the 100 providers surveyed, >80% felt confident they could get their patients to complete their CRC screening test and follow-up care. For the clinic-based intervention component, our baseline sample included 11,259 age-eligible patients across the four FQHC sites. Overall CRC screening rates increased from 45% to 52% before vs. after the intervention implementation period. The site with the highest CRC screening rate (>62%) maintained steady rates over the observation period, whereas three sites with lower baseline rates showed greater pre-post improvements (average 15 percentage-point increase). CONCLUSION(S): An overall increase in CRC screening rates was achieved across FQHCs, despite clinic staffing challenges during the COVID-19 pandemic. Intervention implementation is ongoing with attempts to document individual, clinic improvements by race/ethnicity.

Implementation of a home blood pressure monitoring program for the management of hypertensive disorders of pregnancy, an observational study in British Columbia, Canada

Background: COVID-19 pandemic has influenced health care delivery. We conducted an observational study to understand how obstetric medicine (ObM) physicians utilized home blood pressure monitoring (HBPM) to manage hypertension in pregnancy. Method(s): Pregnant participants with risk factors or diagnosis of hypertensive disorders of pregnancy (HDP) were enrolled, May 2020-December 2021, and provided with validated home blood pressure (BP) monitor. ObM physicians completed questionnaires to elicit how home BP readings were interpreted to manage HDP. Result(s): We enrolled 103 people: 44 antepartum patients (33.5 +/- 5 years, gestational age of 24 +/- 5 weeks);59 postpartum patients (35 +/- 6 years, enrolled 6 +/- 4 days post-partum). ObM physicians used range of home BP readings (70%) for management of HDP. Conclusion(s): HBPM to manage HDP is acceptable and can be used to manage hypertension during pregnancy. Further studies are needed to assess the generalizability of our findings and the safety of HBPM reliance alone in management of HDP.Copyright © The Author(s) 2023.

Implementation of a Home Blood Pressure Monitoring Program for Management of Hypertensive Disorders of Pregnancy, a Quality Improvement Study, in British Columbia, Canada

Background & Purpose: Home blood pressure monitoring (HBPM) in pregnant women is common, but uncertainty exists on utilization of home blood pressure (BP) readings for management of hypertensive disorders of pregnancy (HDP). We conducted a qualitative improvement study to understand how physicians utilize HBPM for pregnant patients and patient acceptability. Method(s): Pregnant patients with risk factors for HDP were recruited. Participants were provided with a validated home BP monitor (Microlife Watch BP) and monitored their BP two times in the morning/evening and manually entered data into a paper diary. Obstetrical Medicine physicians completed written survey after each clinic visit to understand how they used HBPM. Surveys were sent to all participants to assess acceptability of HBPM. Result(s): In total, 103 women were recruited for the study, of which, 43% were enrolled antepartum (mean age 34+/-5 years;mean gestation 171+/-61 days) and 57% postpartum (mean age 35+/-6 years;mean days postpartum 6+/-4 days). Median compliance with home BP readings was 0.94 (IQR 0.57, 1.00). Obstetrical Medicine physicians relied on the range of HBPM readings (70%) to make clinical decisions for management of HDP. Antepartum, 13% of clinic visits resulted in an increase of antihypertensive medications, and 82% required no change in medication. Post-partum, 44% of visits required a decrease anti-hypertensive medication. 98% of participants found HBPM easy to do, and 51% were able to strictly adhere to their measurement schedule. Barriers to HBPM included newborn care (57%), forgetting to check (39%), and lack of time in the mornings (35%). Conclusion(s): HBPM to manage HDP is acceptable to patients and can be safely used to manage HDP ante-partum and post-partum. In light of the COVID-19 pandemic and increasing demand for virtual healthcare visits, further studies are need to assess the effectiveness of HBPM on management of HDP.

The double-edged effects of data privacy practices on customer responses

Requesting personal information in frontline service encounters raises privacy concerns among customers. The proximity contact tracing that occurred during the COVID-19 pandemic provides an intriguing context of information requests. Hospitality venues required contact tracing details from customers, and customer cooperation varied with concerns about privacy. Drawing on gossip theory, we investigate the roles of businesses' data privacy practices and government support in driving customers' responses to contact tracing. Our findings show that perceived transparency of a business's privacy practices has a positive effect on customers' commitment to the business, while perceived control exerts a negative effect on commitment. These effects are mediated by customers' information falsification rather than disclosure, because the former is a sensitive behavioral indicator of privacy concerns. The results also reveal the moderating roles of government support. This research contributes to the customer data privacy literature by demonstrating the distinct effects of perceived transparency and control on commitment and revealing the underlying mechanism. Moreover, the research extends the conceptual understanding of privacy practices from online contexts to face-to-face contexts of frontline service. The findings offer implications for the management of customer data privacy. © 2022 Elsevier Ltd

A Comparative Study of Question Answering over Knowledge Bases

Question answering over knowledge bases (KBQA) has become a popular approach to help users extract information from knowledge bases. Although several systems exist, choosing one suitable for a particular application scenario is difficult. In this article, we provide a comparative study of six representative KBQA systems on eight benchmark datasets. In that, we study various question types, properties, languages, and domains to provide insights on where existing systems struggle. On top of that, we propose an advanced mapping algorithm to aid existing models in achieving superior results. Moreover, we also develop a multilingual corpus COVID-KGQA, which encourages COVID-19 research and multilingualism for the diversity of future AI. Finally, we discuss the key findings and their implications as well as performance guidelines and some future improvements. Our source code is available at https://github.com/tamlhp/kbqa.

A Comparative Study of Question Answering over Knowledge Bases

Question answering over knowledge bases (KBQA) has become a popular approach to help users extract information from knowledge bases. Although several systems exist, choosing one suitable for a particular application scenario is difficult. In this article, we provide a comparative study of six representative KBQA systems on eight benchmark datasets. In that, we study various question types, properties, languages, and domains to provide insights on where existing systems struggle. On top of that, we propose an advanced mapping algorithm to aid existing models in achieving superior results. Moreover, we also develop a multilingual corpus COVID-KGQA, which encourages COVID-19 research and multilingualism for the diversity of future AI. Finally, we discuss the key findings and their implications as well as performance guidelines and some future improvements. Our source code is available at https://github.com/tamlhp/kbqa. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Forecasting Sales Profiles of Products in an Exceptional Context: COVID-19 Pandemic

Accurate demand forecasting has always been essential for retailers in order to be able to survive in the highly competitive, volatile modern market. However, anticipating product demand is an extremely difficult task in the context of short product life cycles in which consumer demand is influenced by many heterogeneous variables. During the COVID-19 pandemic in particular, with all its related new constraints, the fashion industry has seen a huge decline in sales, which makes it difficult for existing sales forecasting methods to accurately predict new product sales. This paper proposes an original sales forecasting framework capable of considering the effect of the COVID-19 related crisis on sales. The proposed framework combines clustering, classification, and regression. The main goals of this framework are (1) to predict a sales pattern for each item based on its attributes and (2) to correct it by modelling the impact of the crisis on sales. We evaluate our proposed framework using a real-world dataset of a French fashion retailer with Omnichannel sales. Despite the fact that during the lockdown period online sales were still possible, consumer purchases were significantly impacted by this crisis. Experimental analysis show that our methodology learns the impact of the crisis on consumer behavior from online sales, and then, adapts the sales forecasts already obtained.

How perceived effectiveness of social media platform and satisfaction affect continuance intention in a pandemic: The moderating role of perceived benefit

Firms facing a global pandemic need to shift to online supply to satisfy customer demand. This study develops a valid measure of the perceived effectiveness of social media platforms (PESMP) and analyzes its effect on customer satisfaction in predicting continuance intentions under the boundary condition of perceived benefit. Drawing on the uses and gratification theory and a sample of 508 customers, the authors substantiate perceived benefits moderating role. At high levels of perceived benefit, PESMP exerts a strong effect on satisfaction that increases continuance intention. Implications to increase strategic effectiveness are also discussed.

Improving Traffic Load Prediction with Multi-modality: A Case Study of Brisbane

Fast and accurate traffic load prediction is a pivotal component of the Intelligent Transport System. It will reduce time spent by commuters and save our environment from vehicle emissions. During the COVID-19 pandemic, people prefer to use private transportation;thus predicting the traffic load becomes more critical. In these years, researchers have developed some traffic load prediction models and have applied these models successfully on data from the US, China or Europe. However, none of these models has been applied to traffic data in Australia. Considering that Australia bears different political, geographical, and climate conditions from other countries, these models may not be suitable to predict the traffic load in Australia. In this paper, we investigate this problem and proposes a multi-modal method that is capable of using Australia-specific data to assist traffic load prediction. Specifically, we use daily social media data together with traffic data to predict the traffic load. We illustrate a protocol to pre-process raw traffic and social media data and then propose a multi-modal model, namely DM2T, which accurately make time-series prediction by using both time-series data and other media data. We validate the effectiveness of our proposed method by a case study on Brisbane city. The result shows that with the help of Australia-specific social media data, our proposed method can make more accurate traffic load prediction for Brisbane than conventional methods. © 2022, Springer Nature Switzerland AG.

Communicating With Breast Imaging Patients During the COVID-19 Pandemic: Impact on Patient Care and Physician Wellness

Objective Assess the impact of COVID-19 on patient-breast radiologist interactions and evaluate the relationship between safety measure-constrained communication and physician wellbeing. Methods A 41-question survey on the perceived effect of COVID-19 on patient care was distributed from June 2020 to September 2020 to members of the Society of Breast Imaging and the National Consortium of Breast Centers. Non-radiologists and international members were excluded. Anxiety and psychological distress scores were calculated. A multivariable logistic model was used to identify demographic and mental health factors associated with responses. Results Five hundred twenty-five surveys met inclusion criteria (23% response rate). Diminished ability to fulfill patients' emotional needs was reported by 46% (221/479), a response associated with younger age (OR, 0.8 per decade;P < 0.01), higher anxiety (OR, 2.3;P < 0.01), and higher psychological distress (OR, 2.2;P = 0.04). Personal protective equipment made patient communication more difficult for 88% (422/478), a response associated with younger age (OR, 0.8 per decade;P = 0.008), female gender (OR, 1.9;P < 0.01), and greater anxiety (OR, 2.6;P = 0.001). The inability to provide the same level of care as prior to COVID-19 was reported by 37% (177/481) and was associated with greater anxiety (OR, 3.4;P < 0.001) and psychological distress (OR, 1.7;P = 0.03). Conclusion The majority of breast radiologists reported that COVID-19 has had a negative impact on patient care. This perception was more likely among younger radiologists and those with higher levels of anxiety and psychological distress.

Piezoelectric Nanofiber Membrane for Reusable, Stable, and Highly Functional Face Mask Filter with Long-Term Biodegradability

The emergence of the SARS-CoV-2 pandemic and airborne particulate matter (PM) pollution has led to remarkably high demand for face masks. However, conventional respirators are intended for single use and made from nondegradable materials, causing serious concern for a plastic-waste environmental crisis. Furthermore, these facemasks are weakened in humid conditions and difficult to decontaminate. Herein, a reusable, self-sustaining, highly effective, and humidity-resistant air filtration membrane with excellent particle-removal efficiency is reported, based on highly controllable and stable piezoelectric electrospun poly (l-lactic acid) (PLLA) nanofibers. The PLLA filter possesses a high filtration efficiency (>99% for PM 2.5 and >91% for PM 1.0) while providing a favorable pressure drop (≈91 Pa at normal breathing rate) for human breathing due to the piezoelectric charge naturally activated by respiration through the mask. The filter has a long, stable filtration performance and good humidity resistance, demonstrated by a minimal declination in the filtration performance of the nanofiber membrane after moisture exposure. The PLLA filter is reusable via common sterilization tools (i.e., an ultrasonic cleaning bath, autoclave, or microwave). Moreover, a prototype of a completely biodegradable PLLA nanofiber-based facemask is fabricated and shown to decompose within 5 weeks in an accelerated degradation environment. © 2022 Wiley-VCH GmbH

Intra-Organizational Factors Affecting Business Performance: An Empirical Study in Vietnam

In the era of industry 4.0 with the robust digital transformation, especially under the trigger of the Covid-19 pandemic, the process of transforming businesses to achieve the desired business performance depends much on the mindset transformation of each member of the organization, beginning with the thoughts of leadership and stakeholders. This study will evaluate the relationship between leadership's strategic reasoning perspectives on employee engagement or commitment and the company's reputation, thereby directly or indirectly affecting organizational performance. The study examines data from 382 companies out of 500 samples in typical industries in Vietnam using the exploratory factor analysis (EFA) and partial least squares structural equation modeling (PLS-SEM) techniques. The results show that holistic thinking is closely related to employee retention and corporate reputation, thereby increasing the business outcomes of the organization, whereas there was no evidence to support analytical thinking in this study. As a consequence, transforming the business to achieve the desired business performance is heavily reliant on changing the mindset of each member of the organization, beginning with the top leaders and influencers of the business. This will assist Vietnamese leaders in gaining a comprehensive understanding of corporate governance and controlling the relationships between organizational constructs.

Bupropion for Treatment-Resistant Depression

Major depressive disorder (MDD) is a common and disabling illness and 1 of the most common mood disorders. It affects the entire body and mind, leading to reductions in quality of life and significant costs to the health care sector and society.1 MDD is associated with a high risk of mortality with a relative risk of 1.81 compared with persons without depression.2 According to Statistics Canada's 2012 Canadian Community Health Survey on Mental Health, it is estimated that 5.4% of the Canadian population aged 15 years and older have reported mood disorders in the previous 12 months, including 4.7% for major depression.1 A recent survey on COVID-19 and mental health during the last 3 months of 2020 found that 1 in 5 Canadians had a positive screening for at least 1 of the 3 mental disorders: MDD, generalized anxiety disorder, and post-traumatic stress disorder.3 MDD was the most prevalent mental disorder, with 15% Canadians screening positive with moderate or severe symptoms.3 A variety of antidepressant agents have been used for the treatment of patients with MDD including selective serotonin reuptake inhibitor (SSRI), serotonin-norepinephrine reuptake inhibitor (SNRI), tricyclic antidepressant (TCA), monoamine oxidase inhibitor (MAOI), glutamate antagonist, and atypical antidepressants such as bupropion.4 Despite advances in understanding the efficacy and safety of those pharmacological agents, 10% to 15% of patients do not respond to their first course of antidepressant pharmacotherapy, and 30% to 40% achieve only partial remission.5 After proper diagnosis and adequate treatment of MDD with antidepressants, individuals who are still nonresponders or partial responders are considered to have treatment-resistant depression (TRD). Although there is no universally accepted definition of TRD, approximately half of clinical trials required a minimum of 2 treatment failures to be considered TRD.6 The pharmacological options for treating TRD are not well-established and remain a challenge for physicians.7 Options for treatment of TRD include augmentation and switching of the initial antidepressant.7 Bupropion is an atypical antidepressant which inhibits the reuptake of noradrenaline and dopamine and has been used for treatment of MDD.8 It is generally well-tolerated but can cause weight loss and low rates of sexual dysfunction.8 However, its clinical effectiveness and cost-effectiveness in the treatment of TRD is less well understood. The current report aims to review the clinical effectiveness and cost-effectiveness of bupropion for the treatment of adults with TRD.

The questions of compulsory organ donation: The trolley dilemma-a discussion from ethical, legal, and social-economical perspectives

The Covid-19 pandemic has inflicted disastrous damages on various aspects of human lives, especially the healthcare sector. The shortage of beds, medical staff, and other facilities in hospitals posed an acute dilemma over who should be given precedence in the treatment process and whether a more seriously ill person should sacrifice for people with less severe illness. With an interpretative approach, this short research article discusses the above questions by using compulsory organ donations as a proxy. After evaluating the compulsory organ donation from the ethical aspect, researchers then dig into the issue from legal and socioeconomic perspectives. The authors are convinced by Kant and Nozick’s proposals on ethics and justice regarding organ donation and patient sacrifice. The research also found out that the problem is not merely limited to the question of morality but also extended to an opt-out system for ensuring social welfare. Finally, the paper encourages medical practitioners, legislators, and social activists to make decisions about medical-legal issues based on interdisciplinary views.

Online academic support during the COVID-19 pandemic: Reflections on unexpected outcomes that challenge assumptions

The shift to entirely online delivery due to the COVID-19 pandemic has been challenging for higher education institutions, students and staff. However, it has also led to new opportunities and new ways of working to deliver learning and teaching support online. In this reflective paper, we report on the outcomes of the shift to online academic support at our institution, and we specifically focus on how certain assumptions that we held about our students and our work with colleagues have been challenged over the last few months. We examine the four key areas of focus of our learning and teaching support service: in-class and individual student support, online resources, teaching support, and collaboration with other academic teams. We conclude by reflecting on how we adapted, the outcomes and how this will influence our practice beyond the time of the pandemic.

Ethical considerations and patient safety concerns for cancelling non-urgent surgeries during the COVID-19 pandemic: a review

At the time of writing of this article, there have been over 110 million cases and 2.4 million deaths worldwide since the start of the Coronavirus Disease 2019 (COVID-19) pandemic, postponing millions of non-urgent surgeries. Existing literature explores the complexities of rationing medical care. However, implications of non-urgent surgery postponement during the COVID-19 pandemic have not yet been analyzed within the context of the four pillars of medical ethics. The objective of this review is to discuss the ethics of elective surgery cancellation during the COVID-19 pandemic in relation to beneficence, non-maleficence, justice, and autonomy. This review hypothesizes that a more equitable decision-making algorithm can be formulated by analyzing the ethical dilemmas of elective surgical care during the pandemic through the lens of these four pillars. This paper's analysis shows that non-urgent surgeries treat conditions that can become urgent if left untreated. Postponement of these surgeries can cause cumulative harm downstream. An improved algorithm can address these issues of beneficence by weighing local pandemic stressors within predictive algorithms to appropriately increase surgeries. Additionally, the potential harms of performing non-urgent surgeries extend beyond the patient. Non-maleficence is maintained through using enhanced screening protocols and modifying surgical techniques to reduce risks to patients and clinicians. This model proposes a system to transfer patients from areas of high to low burden, addressing the challenge of justice by considering facility burden rather than value judgments concerning the nature of a particular surgery, such as cosmetic surgeries. Autonomy can be respected by giving patients the option to cancel or postpone non-urgent surgeries. However, in the context of limited resources in a global pandemic, autonomy is not absolute. Non-urgent surgeries can ethically be postponed in opposition to the patient's preference. The proposed algorithm attempts to uphold the four principles of medical ethics in rationing non-urgent surgical care by building upon existing decision models, using additional measures of resource burden and surgical safety to increase health care access and decrease long-term harm as much as possible. The next global health crisis will undoubtedly present its own unique challenges. This model may serve as a comprehensive starting point in determining future guidelines for non-urgent surgical care.