Dataset Information

Effectiveness of a Comprehensive 4-Week Course in HIV Medicine for Postgraduate Doctors at University of Nigeria: A Preservice Education Initiative.

ABSTRACT: There is a critical shortage of trained human immunodeficiency virus (HIV) providers in resource-limited settings. To strengthen preservice HIV training for postgraduate health care providers, University of Maryland's Institute of Human Virology and Center for Clinical Care and Research Nigeria collaborated with University of Nigeria to plan and implement a comprehensive 4-week course in HIV medicine. The first course was piloted with 30 postgraduate doctors. Mean objective structured clinical examinations (OSCE), pretest, and posttest scores score were 51%, 53%, and 75%, respectively; follow-up examination at 6 months showed mean score of 74%. In multivariate regression analysis, pretest score was positively associated with posttest score (22.03, P < .001) and OSCE (0.29, P = .04), age negatively associated with pretest score (-0.94, P = .001), and female gender positively associated with OSCE score (6.15, P = .05). Six- and 18-month online surveys revealed trainees continued to apply knowledge and skills gained. North-south university collaborations to develop practicum-based preservice curricula offer a sustainable way to strengthen preservice evidence-based HIV medicine training with long-lasting retention of skills and knowledge.

SUBMITTER: Nwandu A

PROVIDER: S-EPMC6748509 | biostudies-literature | 2019 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effectiveness of a Comprehensive 4-Week Course in HIV Medicine for Postgraduate Doctors at University of Nigeria: A Preservice Education Initiative.

Nwandu Anthea A Claassen Cassidy Wayne CW Riedel David James DJ Madubuko Theresa T Olutola Ayodotun A Onu Eugene E Onyekonwu Chinwe C Nwobi Emmanuel E Chukwuka Chinwe C

Journal of the International Association of Providers of AIDS Care 20190101

There is a critical shortage of trained human immunodeficiency virus (HIV) providers in resource-limited settings. To strengthen preservice HIV training for postgraduate health care providers, University of Maryland's Institute of Human Virology and Center for Clinical Care and Research Nigeria collaborated with University of Nigeria to plan and implement a comprehensive 4-week course in HIV medicine. The first course was piloted with 30 postgraduate doctors. Mean objective structured clinical e ...[more]

PMID: 30915880

Similar Datasets

Project description:BackgroundIndustry and higher education sectors devote considerable, but independent resources to deliver postgraduate nursing education. This leads to duplication, uncertainty among students, and critical gaps in nursing education. Establishing and sustaining meaningful partnerships between invested university and industry stakeholders can strengthen workforce capability and improve patient care.MethodsTo evaluate the feasibility and effectiveness of using a University-Industry Integration Framework to develop a postgraduate nursing education program. Prospective mixed methods cohort study (STROBE). A co-design approach, using an established University-Industry Integration Framework, leveraged expert stakeholder partnerships to contextualise knowledge and service need for developing a postgraduate education program for cancer care nurses.ResultsAll participants (n = 46) were 100% satisfied with the online resources, support, and communication processes applied. Qualitative data generated three major analytical interpretations (reciprocity, flexible adaptations, authentic learning), highlighting the experiences and connections and how the partnership evolved. Program participants (n = 15) undertook a six-week cancer education program with eight responding to the survey with overwhelming satisfaction (100%), increasing their knowledge and skills. While barriers were evident, three quarters (n = 6) indicated these were addressed and enabled progress in the program. However, 63% (n = 5) were not satisfied with the program workload.ConclusionsUniversity and industry partners can apply the University-Industry Integration Framework and deliver a successful postgraduate education program for cancer care services. Within a co-design partnership it is possible to develop strategies and processes to overcome barriers and deliver a program for mutual benefit. The culmination of this successful education program has enhanced collaborations between partners and likely will sustain the offering of future co-design endeavours.

Project description:Background and objective: Integrative Medicine and Health (IMH) is a theory-based paradigm shift for health, disease and health care, which can probably only be achieved by supplementing medical roles and competences. Definition of IMH: The definitions of the Academic Consortium for Integrative Medicine and Health 2015 and the so-called Berlin Agreement: Self-Responsibility and Social Action in Practicing and Fostering Integrative Medicine and Health Globally are used. The basic features of evidence-based Integrative Medicine and Health (EB-IMH) are based on the recommendations on EBM by David L. Sackett. Global State of Undergraduate and Postgraduate Medical Education (UG-PGME) for IMH: The USA and Canada are most advanced in the development of IMH regarding practice, teaching and research worldwide. Despite socio-cultural peculiarities, they can provide guidance for Europe and especially for Germany. Of interest here are competences for UG-PGME in IMH in primary care and in some specialist disciplines (e.g. internal medicine, gynecology, pediatrics, geriatrics, oncology, palliative care). For these specialties, the need for an interprofessional UG-PGME for IMH was shown in the early stages of development. UG-PGME for IMH in Germany: In the course of the development of the new Medical Licensure Act in Germany (ÄApprO), based on a revision of the National Competence-based Catalogue of Learning Objectives for Medicine (NKLM 2.0) and new regulations for Postgraduate Medical Education in Germany, suggestions for an extension of UG-PGME are particularly topical. To some extent there are already approaches to IMH. Old and new regulations are set out and are partly compared. As a result, some essential elements of IMH are mapped in the new ÄApprO. The new regulations for Postgraduate Medical Education do not mention IMH. Conclusion: The development of medical competences for IMH in the continuum of the UG-PGME could be supported by the coordinated introduction of appropriate entrustable professional activities (EPA) and IMH sub-competences combined with appropriate assessment.

Project description:BackgroundMedical postgraduates' demand for data capabilities is growing, as biomedical research becomes more data driven, integrative, and computational. In the context of the application of big data in health and medicine, the integration of data mining skills into postgraduate medical education becomes important.ObjectiveThis study aimed to demonstrate the design and implementation of a medical data mining course for medical postgraduates with diverse backgrounds in a medical school.MethodsWe developed a medical data mining course called "Practical Techniques of Medical Data Mining" for postgraduate medical education and taught the course online at Peking Union Medical College (PUMC). To identify the background knowledge, programming skills, and expectations of targeted learners, we conducted a web-based questionnaire survey. After determining the instructional methods to be used in the course, three technical platforms-Rain Classroom, Tencent Meeting, and WeChat-were chosen for online teaching. A medical data mining platform called Medical Data Mining - R Programming Hub (MedHub) was developed for self-learning, which could support the development and comprehensive testing of data mining algorithms. Finally, we carried out a postcourse survey and a case study to demonstrate that our online course could accommodate a diverse group of medical students with a wide range of academic backgrounds and programming experience.ResultsIn total, 200 postgraduates from 30 disciplines participated in the precourse survey. Based on the analysis of students' characteristics and expectations, we designed an optimized course structured into nine logical teaching units (one 4-hour unit per week for 9 weeks). The course covered basic knowledge of R programming, machine learning models, clinical data mining, and omics data mining, among other topics, as well as diversified health care analysis scenarios. Finally, this 9-week course was successfully implemented in an online format from May to July in the spring semester of 2020 at PUMC. A total of 6 faculty members and 317 students participated in the course. Postcourse survey data showed that our course was considered to be very practical (83/83, 100% indicated "very positive" or "positive"), and MedHub received the best feedback, both in function (80/83, 96% chose "satisfied") and teaching effect (80/83, 96% chose "satisfied"). The case study showed that our course was able to fill the gap between student expectations and learning outcomes.ConclusionsWe developed content for a data mining course, with online instructional methods to accommodate the diversified characteristics of students. Our optimized course could improve the data mining skills of medical students with a wide range of academic backgrounds and programming experience.

Project description:BackgroundThe use of Complementary and Alternative Medicine (CAM) by cancer patients is very common and varies between populations. The referenced English literature has no local study from Africa on this subject. This study was conducted to define the prevalence, pattern of use, and factors influencing the use of CAM by cancer patients at the University of Nigeria Teaching Hospital Enugu (UNTH-E), NigeriaMethodFace-to-face interviews using semi-structured questionnaire were used to determine the use of CAM by cancer patients. All consenting cancer patients were interviewed as they presented at the core surgical units of the UNTH- E, from June 2003 to September 2005.Results160 patients were interviewed; 68 (42.5%) were males and 94 (57.5%) were females. Ages ranged from 13-86 years. Breast, urogenital system, gastrointestinal system, and soft tissue cancers predominated. One hundred and four patients (65.0%) have used CAM at some time during their current cancer illness; 56 (35.0%) patients have not used any form of CAM. There were more females than males among the non-CAM users. The use of CAM was not affected by age, marital status, level of education, religious affiliation, or socioeconomic status. The most frequently used CAMs were herbs (51.9%), faith/prayer healing (49.4%), aloe vera (23.1%), Forever Living Products (16.3%), medicinal tea (14.4%), and Blackstone (12.5%). Over 23% of those who used CAM were satisfied, but 68.3% were disappointed. Most users (67.3%) did not see any benefit from the CAM, but 25% could describe some specific benefits. More than 21% of users reported various unwanted effects. While 86.5% of CAM users will use orthodox medicine instead of CAM in the future, 9.6% will use the two together to help each other. Most users (79.8%) will not repeat CAM or recommend its use for cancer. The majority of patients (55.8%) did not mention their use of CAM to their doctors - mostly because the doctor did not ask.ConclusionCAM use is common among cancer patients in Nigeria. Most users do not obtain the expected benefits, and adverse events are not uncommon. Every clinician in the field of oncology should ask his/her patients about the use of CAM; this knowledge will enable them to better counsel the patients.

Project description:BackgroundArtificial intelligence (AI) technologies are increasingly used in clinical practice. Although there is robust evidence that AI innovations can improve patient care, reduce clinicians' workload and increase efficiency, their impact on medical training and education remains unclear.MethodsA survey of trainee doctors' perceived impact of AI technologies on clinical training and education was conducted at UK NHS postgraduate centers in London between October and December 2020. Impact assessment mirrored domains in training curricula such as 'clinical judgement', 'practical skills' and 'research and quality improvement skills'. Significance between Likert-type data was analysed using Fisher's exact test. Response variations between clinical specialities were analysed using k-modes clustering. Free-text responses were analysed by thematic analysis.ResultsTwo hundred ten doctors responded to the survey (response rate 72%). The majority (58%) perceived an overall positive impact of AI technologies on their training and education. Respondents agreed that AI would reduce clinical workload (62%) and improve research and audit training (68%). Trainees were skeptical that it would improve clinical judgement (46% agree, p = 0.12) and practical skills training (32% agree, p < 0.01). The majority reported insufficient AI training in their current curricula (92%), and supported having more formal AI training (81%).ConclusionsTrainee doctors have an overall positive perception of AI technologies' impact on clinical training. There is optimism that it will improve 'research and quality improvement' skills and facilitate 'curriculum mapping'. There is skepticism that it may reduce educational opportunities to develop 'clinical judgement' and 'practical skills'. Medical educators should be mindful that these domains are protected as AI develops. We recommend that 'Applied AI' topics are formalized in curricula and digital technologies leveraged to deliver clinical education.

Dataset Information

Effectiveness of a Comprehensive 4-Week Course in HIV Medicine for Postgraduate Doctors at University of Nigeria: A Preservice Education Initiative.

Publications

Effectiveness of a Comprehensive 4-Week Course in HIV Medicine for Postgraduate Doctors at University of Nigeria: A Preservice Education Initiative.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets