Everett Community College

Abstract Wabanaki Public Health and Wellness is a Tribally operated public health that serves the four federally recognized Tribes in the state of Maine . Wabanaki Public Health and Wellness is the principal investigator on the Wabanaki Native American Research Center for Health (Wabanaki NARCH), which is supported by the National Institutes of Health. Wabanaki NARCH aims to enhance support systems, promote cultural continuity, and improve the overall well-being of Wabanaki Elders living with dementia. In partnership with two academic institutions, Washington State University and the University of Miami, Wabanaki Public Health and Wellness, through Wabanaki NARCH, is conducting Voices of Our Elders (VOE), an epidemiologic study that seeks to better understand the prevalence of Alzheimer’s disease and Alzheimer’s disease and related dementia (AD/ADRD) and cognitive decline. VOE also seeks to assess health and lifestyle risk factors for AD/ADRD and cognitive decline among Wabanaki Elders. This presentation will offer the perspectives and lessons learned from a Tribal public health district and its academic partners on: 1. The process of developing, adapting, and Indigenizing study designs and research methodologies of an AD/ADRD study that seeks to better serve the needs and perspectives of Wabanaki Elders; 2. Community engagement strategies employed to reach Wabanaki Elders to participate in VOE; and 3. Ethical aspects and strength-based and capacity building approaches for all research partners to consider when conducting research with Tribal communities in addition to the engagement with academic institutional review boards.

The modern marketing approach highly relies on behavioural segmentation to allow businesses the capability of reaching customers through their observed behaviours and preferences. The combination of traditional segmentation tools and AI-powered marketing platforms proves inaccessible to small businesses because of their high implementation expenses and technical complexity together with their requirement for specialized expertise. The article introduces an extensive system to implement affordable AI technologies specifically designed for behavioural segmentation operations within small business domains. An approach that uses lightweight machine learning models alongside open-source platforms and cloud-based infrastructures allows us to perform precise customer clustering and personalized marketing while avoiding requirements for large-scale data and computational resources. The research team establishes and tests a program framework that utilizes K-Means clustering with decision trees alongside sentiment analysis APIs on genuine dataset samples extracted from local storefronts and service firms. Our method proves successful in detecting separate behavioural patterns while maintaining below 15% error rate using minimal financial resources and limited training sessions. The paper presents implementation strategies along with recommendations for ethical AI usage in small-scale marketing fields and scales to process requirements.

Asking students to write practice questions for tests is an active learning strategy utilized to facilitate understanding and application of course material. The use of student-generated questions has been studied in medical education and other academic fields but not in undergraduate Anatomy and Physiology (A&P) education. Mixed results from existing literature hint at three possibly important components of effective assignments for students writing test questions: assignment structure, instructor/expert feedback, and alignment with summative assessment. Accordingly, this study investigated the impact of each of these components on students' learning or perceptions of learning. Our methods included 1) a reanalysis of papers on medical student question-writing, 2) a survey of 22 A&P instructors who have tried this method, and 3) detailed studies of efforts at two institutions to implement structured discussion-board assignments in which undergraduate A&P students write and share practice questions. Collectively, these approaches revealed positive correlations between each of the three components and students' learning or perception thereof. In light of these data, especially our students' satisfaction with our implementation of discussion-board assignments, we suggest that structured question-writing and question-sharing activities with instructor feedback and clear connections to summative assessment can increase student engagement and learning.NEW & NOTEWORTHY This paper reports the results of a mixed-methods study of student question-writing assignments. Our results regarding the effect of three intervention parameters (structure, feedback, and alignment) on the learning outcomes of performance and perception suggest that highly structured assignments closely aligned with summative assessments elicit positive learning outcomes when combined with instructor feedback.

Learning objectives (LOs) are a pillar of course design and execution and thus a focus of curricular reforms. This study explored the extent to which the creation and usage of LOs might be facilitated by three leading chatbots: ChatGPT-4o, Claude 3.5 Sonnet, and Google Gemini Advanced. We posed three main questions, as follows: question A: when given course content, can chatbots create LOs that are consistent with five best practices in writing LOs?; question B: when given LOs for a low level of the revised Bloom's taxonomy, can chatbots convert them to a higher level?; and question C: when given LOs, can chatbots create assessment questions that meet six criteria of quality? We explored these questions in the context of four undergraduate courses: Applied Exercise Physiology, Human Anatomy, Human Physiology, and Motor Learning. According to instructor ratings, chatbots had a >70% success rate on most individual criteria for questions A-C. However, chatbots' "difficulties" with a few criteria (e.g., provision of appropriate context for an LO's action, assignment of an appropriate revised Bloom's taxonomy level) meant that, overall, only 38.3% of chatbot outputs fully met all criteria and thus were possibly ready for use with students. Our findings thus underscore the continuing need for instructor oversight of chatbot outputs but also illustrate chatbots' potential to expedite the design and improvement of LOs and LO-related curricular materials such as test question templates (TQTs), which directly align LOs with assessment questions.NEW & NOTEWORTHY Amid much recent interest in the impact of generative artificial intelligence on education, one relatively underexplored issue is the extent to which instructors can use chatbots to work more efficiently. This study determined whether the challenging tasks of writing learning objectives (LOs) and writing LO-linked assessment questions can be delegated to advanced chatbots. The chatbots' outputs were often impressive yet often imperfect and thus can be useful as solid drafts that still require instructor oversight.

INTRODUCTION: Although the current treatment of choice of severe pure aortic regurgitation (AR) is surgical aortic valve replacement, increasing evidence has shown the potential of transcatheter aortic valve replacement (TAVR) in the management of patients who have high surgical risk profiles. AIMS: To conduct a systematic review and meta-analysis in evaluating the outcome of TAVR for pure AR based on current emerging evidence. Methods: Articles on MEDLINE, CINAHL, Web of Science, Embase, and Cochrane that studied the outcome of TAVR for the management of pure native AR were extracted. Device success rates, post-procedure moderate to severe AR rates as well as in-hospital, 30-day, and 1-year all-cause mortality rates were pooled for meta-analysis. Subgroup analyses of the above outcome comparing early-generation devices (EGD) and new-generation devices (NGD) were performed. Data were presented with incidences and 95% confidence intervals (CI), and I 2 was used to analyze heterogeneity. Results: Twenty-four studies involving 4435 patients were included. The pooled device success rate was 89.6% (95% CI 81.7% to 92.2%, I 2 = 91.63%), and 88.2% (95% CI 83.4% to 92.9%, I 2 =86.0%) of device placement was achieved by single implantation. Compare to EGD (72.2%, 95% CI 58.3% to 86.1%, I 2 =94.1%), NGD (91.6%, 95% CI 87.4% to 95.8%, I 2 =83.8%) has a higher device success rate. The overall in-hospital, 30-day, and 1-year all-cause mortality of TAVR for AR was 3.7% (95% CI 2.1% to 5.2%, I 2 =70.2%), 6.9% (95% CI 4.8% to 9.0%, I 2 =79.5%), and 13.9% (95% CI 8.5% to 19.2%, I 2 =89.1%), respectively. A higher 30-day all-cause mortality rate was observed in patients who received EGD implantations (12.6%, 95% CI 7.7% to 17.5%, I 2 =61.4%) than those have NGD placements (6.3%, 95% CI 3.9% to 8.7%, I 2 =51.0%). About 6.9% (95% CI 4.6% to 9.3%, I 2 =72.4%) and 4.6% (95% CI 1.5% to 7.7%, I 2 =86.2%) of patients continue to have moderate to severe AR post-procedure and at 30 days, respectively. CONCLUSION: Our current systematic review and meta-analysis suggests that TAVR may be a feasible option for patients with pure AR who have high surgical risks. NGD is superior to EGD in AR management due to its higher device success rate and favorable mortality outcome.

BACKGROUND: Atrial fibrillation (AF) imposes substantial health care and economic burden on health care systems and patients. Previous studies failed to examine health care resource utilization (HCRU) and costs among patients with incident AF and potential disparity with regard to geographic location. OBJECTIVES: To examine HCRU and costs among patients with incident AF compared with patients without AF and examine whether a geographic disparity exists. METHODS: This was a retrospective cohort study. We selected patients with AF and patients without AF from IBM/Watson MarketScan Research Databases 2014-2019. HCRU and costs were collected 12 months following an AF index date. We used 2-part models with bootstrapping to obtain the marginal estimates and CIs. Rural status was identified based on Metropolitan Statistical Area. We adjusted for age, sex, plan type, US region, and comorbidities. RESULTS: Among 156,732 patients with AF and 3,398,490 patients without AF, patients with AF had 9.04 (95% CI = 8.96-9.12) more outpatient visits, 0.82 (95% CI = 0.81-0.83) more emergency department (ED) visits, 0.33 (95% CI = 0.33-0.34) more inpatient admission, and $15,095 (95% CI = 14,871-15,324) higher total costs, compared with patients without AF. Among patients with AF, rural patients had 1.99 fewer (95% CI = -2.26 to -1.71) outpatient visits and 0.05 (95% CI = 0.02-0.08) more ED visits than urban patients. Overall, rural patients with AF had decreased total costs compared with urban patients (mean = $751; 95% CI = -1,227 to -228). CONCLUSIONS: Incident AF was associated with substantial burden of health care resources and an economic burden, and the burden was not equally distributed across patients in urban vs rural settings. DISCLOSURES: Dr Hansen reports grants from the National Science Foundation during the conduct of the study.

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