Using Hackathons to Transform Complex Educational Problems Into Innovative Prototypes.
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ABSTRACT:
SUBMITTER: Brown A
PROVIDER: S-EPMC6108349 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Publications
Using Hackathons to Transform Complex Educational Problems Into Innovative Prototypes.
Brown Alisha A Jauregui Joshua J Chipman Anne K AK Ilgen Jonathan S JS
Journal of graduate medical education 20180801 4
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Project description:This article presents the design process of innovative prototypes for cervical cancer prevention in primary care centers located in low-income settings in Cali, Colombia, using the Human-Centered Design (HCD). The project was developed in collaboration with a public healthcare network comprised of 38 urban and rural centers with women between the ages of 25 and 65 years, healthcare providers of the cancer program, healthcare administrators and the general manager of said network. Our HCD process involved five stages: research, need synthesis, ideation and co-design process, prototyping and in-context usability testing. In practice, some of the stages are overlapped and iterated throughout the design process. We conducted observations, open-ended interviews and conversations, multi-stakeholder workshops, focus groups, systematic text condensation analyses and tests in real contexts. As a result, we designed four prototypes: (1) 'Encanto': An educational manicure service, (2) 'No le des la espalda a la citología': A media-based strategy, (3) An educational wireless queuing device in the waiting room, and (4) Citobot: A cervical cancer early detection device, system, and method. The tests carried out with each prototype showed their value, limitations and possibilities in terms of subsequent development and validation through public health research or clinical research. We recognize that a longer-term evaluation is required in order to determine whether the prototypes will be used regularly, integrated into cervical cancer screening services and effectively improve access to cytology as a screening test. We conclude that HCD is a useful for design-based prevention in the field of cervical cancer. The integration of this approach with public health research would allow the generation of evidence during to the formulation of policies and programs as well as optimize existing interventions and, ultimately, facilitate the scalability and financing of what actually works.
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Project description:This paper implements the unified transform to problems in unbounded domains with solutions having corner singularities. Consequently, a wide variety of mixed boundary condition problems can be solved without the need for the Wiener-Hopf technique. Such problems arise frequently in acoustic scattering or in the calculation of electric fields in geometries involving finite and/or multiple plates. The new approach constructs a global relation that relates known boundary data, such as the scattered normal velocity on a rigid plate, to unknown boundary values, such as the jump in pressure upstream of the plate. By approximating the known data and the unknown boundary values by suitable functions and evaluating the global relation at collocation points, one can accurately obtain the expansion coefficients of the unknown boundary values. The method is illustrated for the modified Helmholtz and Helmholtz equations. In each case, comparisons between the traditional Wiener-Hopf approach, other spectral or boundary methods and the unified transform approach are discussed.
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Project description:The purpose of this article is to describe the design of a unique, bilingual (English and French) Master of Applied Sciences (M.Sc.) in Anatomical Sciences Education (ASE) program at a Canadian postsecondary institution. Anatomy is a core foundational discipline that is essential to many undergraduate, graduate, and professional programs in the health sciences. However, the number of new individuals with the necessary knowledge base and the pedagogical training to teach cadaveric anatomy are in short supply and cannot satisfy the number of openings for trained educators in the field. The M.Sc. in ASE was created to meet the increasingly critical need for instructors trained in human anatomy. The program is designed to prepare students for a career teaching human anatomy to students in the health sciences, emphasizing hands-on cadaveric dissection. Moreover, this program aims to develop educational scholarship skills in trainees by leveraging faculty expertise in medical education research, particularly in the field of anatomy education research. This focus on scholarships will make graduates more competitive for future faculty positions. During their first year of the program, learners will develop clinically relevant anatomy knowledge, teaching skills, and anatomy education scholarship. In the second year, students will benefit from an immediate, hands-on application of this acquired knowledge. In the same year, students will serve as anatomy teachers in the faculty's Medical Program and conduct their education scholarship projects, culminating in a formal research paper. Although similar programs have been developed in recent years, this article provides the first description of the creation of a graduate program in anatomy education. It includes needs assessment, program development, challenges faced, and lessons learned during the approval process. The article serves as a valuable resource for other institutions aspiring to develop similar initiatives.
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Project description:BackgroundCommunity health workers (CHWs) are vital yet often invisible contributors to care coordination, health equity, and public health (PH) in medically underserved areas. The Atlanta Regional Community Health Workforce Advancement (ARCHWAy) Program leverages cross-sector partners to increase the number of CHWs on integrated care teams in metro Atlanta in the United States.MethodsThe ARCHWAy Program provides an innovative educational curriculum guided by United States Department of Labor CHW competencies and cross-walked with the Georgia CHW Initiative competencies. The 12-week in-person/online curriculum includes 155 h of content on becoming a CHW, mental health first aid, social determinants of health, trauma informed care, population health, community outreach, engagement, and capacity building, resiliency, communication, care coordination, advocacy, emergency preparedness, health promotion/disease prevention, 20 h of simulation including motivational interviewing, point of care testing, first aid, and 80 h of experiential learning through field placements. Project team members represent racial, ethnic, linguistic, and gender diversity ensuring culturally congruent content.ResultsSince program inception, the public health workforce in the region has been expanded by over 200 CHWs to date (goal of 446 CHWs) with specialized training offered in both English and Spanish.DiscussionPositioning well-trained CHWs as members of integrated care teams promotes health equity by advancing PH, strengthening the PH workforce, reducing health disparities, and helping underserved populations address social determinants that can undermine health. The ARCHWAy program, by increasing CHW employment readiness through developing field placements with cross-sector partners, aspires to set the standard for apprenticeships in CHW training programs.
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Project description:BackgroundEducational autopsy (EA) is an innovative technique designed to improve the quality of feedback provided to conference presenters. In response to survey fatigue and suboptimal feedback from online evaluations, this postlecture group debrief was adapted to emergency medicine residency didactics, with a goal of collecting timely, specific, and balanced feedback for presenters. Other aims include encouraging participants to think critically about educational methods and providing presenters with formal feedback for a portfolio or promotion packet. It was hypothesized that EA provides more specific and actionable feedback than traditional online evaluations deployed individually to conference attendees.MethodsThe authors analyzed 4 months of evaluations pre- and postimplementation of EA. Rate of completion, presence of comments, and types of comments were compared. Comments were coded as specific, nonspecific, and unrelated/unclear. Specific comments were further categorized as about audiovisual presentation design, speaker presentation style, and educational methods of the session.ResultsA total of 46 of 65 (71%) preimplementation presentations eligible for evaluation received comments through traditional online evaluations. A total of 44 of 75 (59%) eligible postimplementation presentations generated comments via EA. Among presentations that received comments, none received nonspecific comments via EA, compared to 46% of lectures through traditional evaluations. EA generated specific comments for more presentations regarding presentation design (91% vs. 63%), presentation style (66% vs. 24%), and educational methods (48% vs. 28%). EA produced no unclear comments; traditional evaluations resulted in unclear comments for 15% of lectures.ConclusionsEA generated more specific feedback for residency conference presenters, although there were a number of sessions not evaluated by EA. Although this limited analysis suggested that EA produced higher-quality presenter feedback, it also showed a drop-off in the proportion of didactic sessions that received narrative feedback.
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Project description:BackgroundCost is a barrier to creating educational resources, and new educational initiatives are often limited in distribution. Medical training programs must develop strategies to create and implement cost-effective educational programming.ObjectiveWe developed high-quality medical programming in procedural instruction with efficient economics, reaching the most trainees at the lowest cost.MethodsThe Just-In-Time online procedural program was developed at the University of Toronto in Canada, aiming to teach thoracentesis, paracentesis, and lumbar puncture skills to internal medicine trainees. Commercial vendors quoted between CAD $50,000 and $100,000 to create 3 comprehensive e-learning procedural modules-a cost that was prohibitive. Modules were therefore developed internally, utilizing 4 principles aimed at decreasing costs while creating efficiencies: targeting talent, finding value abroad, open source expansion, and extrapolating efficiency.ResultsProcedural modules for thoracentesis, paracentesis, and lumbar puncture were created for a total cost of CAD $1,200, less than 3% of the anticipated cost in utilizing traditional commercial vendors. From November 2016 until October 2018, 1800 online instructional sessions have occurred, with over 3600 pageviews of content utilized. While half of the instructional sessions occurred within the city of Toronto, utilization was documented in 10 other cities across Canada.ConclusionsThe Just-in-Time online instructional program successfully created 3 procedural modules at a fraction of the anticipated cost and appeared acceptable to residents based on website utilization.
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Project description:PAM50 intrinsic subtype classification (Parker JS, Mullins M, Cheang MCU, et al: Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes. J Clin Oncol 27:1160-1167, 2009) was used for the Z1031 patient cohort. However, to account for potential technical biases such as differences in platforms and laboratory protocols between the Z1031 data set and the PAM50 training set2, we normalized the Z1301 data set before applying the PAM50 algorithm. This is a critical step that must be taken into consideration for appropriate subtype predictions as our group and others have previously shown3,4. To appropriately normalize the Z1301 microarray data, which is entirely composed of ER-positive tumors, we needed to estimate technical bias from a cohort with equivalent subtype representation as the PAM50 training set. A set including ER-negative, HER2-positive and true normal breast samples were profiled under the same platform, protocol and laboratory (i.e. WashU) as the Z1301 data set. A total of 40 prototypic samples of the various molecular subtypes were selected to match the distribution in the PAM50 training set. The mean expression of each PAM50 gene was calculated in this set of 40. These values obtained from the prototypical sample set were used for calibration purposes and were included as a new WashU_4X44K_Calibration column in the CalibrationParameter file, which has been already provided in the PAM50 algorithm2. This adjustment step assures that each sample is placed in the appropriate ‘prototypic space’ by subtracting the calibration value of each PAM50 gene from the expression value of the corresponding gene in each tested sample. Finally, single sample predictions were performed in every Z1301 sample using the WashU_4X44K_Calibration parameter. The complete data set for the 40 prototypic arrays is submitted under GSE26082.
2011-05-10 | GSE26082 | GEO
Project description:The diversity forest algorithm is an alternative candidate node split sampling scheme that makes innovative complex split procedures in random forests possible. While conventional univariable, binary splitting suffices for obtaining strong predictive performance, new complex split procedures can help tackling practically important issues. For example, interactions between features can be exploited effectively by bivariable splitting. With diversity forests, each split is selected from a candidate split set that is sampled in the following way: for l=1,⋯,nsplits : (1) sample one split problem; (2) sample a single or few splits from the split problem sampled in (1) and add this or these splits to the candidate split set. The split problems are specifically structured collections of splits that depend on the respective split procedure considered. This sampling scheme makes innovative complex split procedures computationally tangible while avoiding overfitting. Important general properties of the diversity forest algorithm are evaluated empirically using univariable, binary splitting. Based on 220 data sets with binary outcomes, diversity forests are compared with conventional random forests and random forests using extremely randomized trees. It is seen that the split sampling scheme of diversity forests does not impair the predictive performance of random forests and that the performance is quite robust with regard to the specified nsplits value. The recently developed interaction forests are the first diversity forest method that uses a complex split procedure. Interaction forests allow modeling and detecting interactions between features effectively. Further potential complex split procedures are discussed as an outlook.Supplementary informationThe online version contains supplementary material available at 10.1007/s42979-021-00920-1.
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