Dataset Information

A survey on the effectiveness of WhatsApp for teaching doctors preparing for a licensing exam.

ABSTRACT:

Introduction

The use of WhatsApp for health professional education is not novel and is described increasingly in literature as an affordable, familiar, and convenient tool for collaboration. Social media technologies for health practitioner education allow the use of text and audio-visual aids, peer-to-peer based learning, and problem-based learning. This study presents a survey on the effectiveness of WhatsApp in doctors' preparation for a medical licensing exam.

Methods

A cross-sectional study was conducted among one hundred and ninety-four participants of a WhatsApp group preparing for the PLAB exam over a three-month period. A twenty-item questionnaire designed on Google Form was completed by consenting participants on the publication of exam results.

Results

Of the one hundred and ninety-four participants, one hundred and fourteen met the eligibility criteria, 57.9 percent were male and 42.1 percent were female, aged between twenty-four and forty-three years of age ([Formula: see text] years). A total of 88.6 percent of participants passed the exam in contrast to the global average pass rate of 69 percent, while the average score among participants was 131.5 compared to a global average score of 128. Passing the exam was significantly associated with combining the WhatsApp group with the online question bank Plabable (p = 0.001). While the mean age of those who passed the PLAB exam was lower than those who did not pass the exam, the number of years post-graduation had no significant association with passing the exam. A total of 93.8 percent stated that moderators were knowledgeable, 83.3 percent reported that the platform increased their motivation to learn, 72.8 percent felt that the session were organised and easy-to-follow, and 97.4 percent of participants reported they would recommend the PLAB network.

Conclusion

WhatsApp can be an effective tool for health professional education, using a pre-defined curriculum coupled with organizational structure. This study reported both subjective and objective measures of effectiveness and demonstrated that the use of multiple e-learning resources can lead to improved learning outcomes.

SUBMITTER: Oyewole BK

PROVIDER: S-EPMC7117696 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A survey on the effectiveness of WhatsApp for teaching doctors preparing for a licensing exam.

Oyewole Bankole K BK Animasahun Victor J VJ Chapman Helena J HJ

PloS one 20200402 4

<h4>Introduction</h4>The use of WhatsApp for health professional education is not novel and is described increasingly in literature as an affordable, familiar, and convenient tool for collaboration. Social media technologies for health practitioner education allow the use of text and audio-visual aids, peer-to-peer based learning, and problem-based learning. This study presents a survey on the effectiveness of WhatsApp in doctors' preparation for a medical licensing exam.<h4>Methods</h4>A cross- ...[more]

PMID: 32240259

Similar Datasets

Project description:Evidence-based teaching practices are associated with improved student academic performance. However, these practices encompass a wide range of activities and determining which type, intensity or duration of activity is effective at improving student exam performance has been elusive. To address this shortcoming, we used a previously validated classroom observation tool, Practical Observation Rubric to Assess Active Learning (PORTAAL) to measure the presence, intensity, and duration of evidence-based teaching practices in a retrospective study of upper and lower division biology courses. We determined the cognitive challenge of exams by categorizing all exam questions obtained from the courses using Bloom's Taxonomy of Cognitive Domains. We used structural equation modeling to correlate the PORTAAL practices with exam performance while controlling for cognitive challenge of exams, students' GPA at start of the term, and students' demographic factors. Small group activities, randomly calling on students or groups to answer questions, explaining alternative answers, and total time students were thinking, working with others or answering questions had positive correlations with exam performance. On exams at higher Bloom's levels, students explaining the reasoning underlying their answers, students working alone, and receiving positive feedback from the instructor also correlated with increased exam performance. Our study is the first to demonstrate a correlation between the intensity or duration of evidence-based PORTAAL practices and student exam performance while controlling for Bloom's level of exams, as well as looking more specifically at which practices correlate with performance on exams at low and high Bloom's levels. This level of detail will provide valuable insights for faculty as they prioritize changes to their teaching. As we found that multiple PORTAAL practices had a positive association with exam performance, it may be encouraging for instructors to realize that there are many ways to benefit students' learning by incorporating these evidence-based teaching practices.

Project description:Traditional Korean medicine (TKM) emphasizes individualized diagnosis and treatment. This uniqueness makes AI modeling difficult due to limited data and implicit processes. Large language models (LLMs) have demonstrated impressive medical inference, even without advanced training in medical texts. This study assessed the capabilities of GPT-4 in TKM, using the Korean National Licensing Examination for Korean Medicine Doctors (K-NLEKMD) as a benchmark. The K-NLEKMD, administered by a national organization, encompasses 12 major subjects in TKM. GPT-4 answered 340 questions from the 2022 K-NLEKMD. We optimized prompts with Chinese-term annotation, English translation for questions and instruction, exam-optimized instruction, and self-consistency. GPT-4 with optimized prompts achieved 66.18% accuracy, surpassing both the examination's average pass mark of 60% and the 40% minimum for each subject. The gradual introduction of language-related prompts and prompting techniques enhanced the accuracy from 51.82% to its maximum accuracy. GPT-4 showed low accuracy in subjects including public health & medicine-related law, internal medicine (2), and acupuncture medicine which are highly localized in Korea and TKM. The model's accuracy was lower for questions requiring TKM-specialized knowledge than those that did not. It exhibited higher accuracy in diagnosis-based and recall-based questions than in intervention-based questions. A significant positive correlation was observed between the consistency and accuracy of GPT-4's responses. This study unveils both the potential and challenges of applying LLMs to TKM. These findings underline the potential of LLMs like GPT-4 in culturally adapted medicine, especially TKM, for tasks such as clinical assistance, medical education, and research. But they also point towards the necessity for the development of methods to mitigate cultural bias inherent in large language models and validate their efficacy in real-world clinical settings.

Project description:Quality of health care needs to be improved in rural China. The Chinese government, based on the 1999 Law on Physicians, started implementing the Rural Doctor Practice Regulation in 2004 to increase the percentage of certified physicians among village doctors. Special exam-targeted training for rural doctors therefore was launched as a national initiative. This study examined these rural doctors' perceptions of whether that training helps them pass the exam and whether it improves their skills.Three counties were selected from the 4 counties in Changzhou City in eastern China, and 844 village doctors were surveyed by a questionnaire in July 2012. Chi-square test and Fisher exact test were used to identify differences of attitudes about the exam and training between the rural doctors and certified (assistant) doctors. Longitudinal annual statistics (1980-2014) of village doctors were further analyzed.Eight hundred and forty-four village doctors were asked to participate, and 837 (99.17%) responded. Only 14.93% of the respondents had received physician (assistant) certification. Only 49.45% of the village doctors thought that the areas tested by the certification exam were closely related to the healthcare needs of rural populations. The majority (86.19%) felt that the training program was "very helpful" or "helpful" for preparing for the exam. More than half the village doctors (61.46%) attended the "weekly school". The village doctors considered the most effective method of learning was "continuous training (40.36%)" . The majority of the rural doctors (89.91%) said they would be willing to participate in the training and 96.87% stated that they could afford to pay up to 2000 yuan for it.The majority of village doctors in Changzhou City perceived that neither the certification exam nor the training for it are closely related to the actual healthcare needs of rural residents. Policies and programs should focus on providing exam-preparation training for selected rural doctors, reducing training expenditures, and utilizing web-based methods. The training focused on rural practice should be provided to all village doctors, even certified physicians. The government should also adjust the local licensing requirements to attract and recruit new village doctors.

Project description:BackgroundImportance of awareness of medical ethics and its integration into medical curriculum has been frequently highlighted. Study 1 aimed to assess the knowledge, attitude, and reported practices of medical ethics among clinicians at Patan Academy of Health Sciences, a tertiary care teaching hospital in Nepal. Study 2 was conducted to assess whether there was a difference in knowledge, attitude, and reported practices of medical ethics among doctors who received formal medical ethics education during undergraduate studies and those who did not.MethodsTwo cross-sectional surveys using self-administered questionnaires were conducted. Study 1 included 72 participants; interns, medical officers, and consultants working at Patan Academy of Health Sciences. Study 2 was a comparative study conducted among 54 medical officers who had received formal medical ethics education (Group 1) and 60 medical officers who did not (Group 2).ResultsParticipants who had completed post-graduate education had higher knowledge (p = 0.050), practice (p < 0.001), and overall combined scores (p = 0.011). Participants with ethics education had higher knowledge (p < 0.001), attitude (p = 0.001), practice (p < 0.001), and overall score (p < 0.001). Most participants preferred consulting colleagues if an ethical dilemma arose. Fewer participants had heard of the Declaration of Helsinki. Most participants thought doctors to be most capable of judging what is best for the patient (Study 1: 70.42%, Study 2 Group 1: 42.59%, Group 2: 80%). Case scenarios in which participants demonstrated poor practice were ethical issues concerning truth-telling, end-of-life decisions, treating HIV/AIDS patients, treating a minor, and reporting colleague's errors.ConclusionsThis study found that participants who have received medical ethics education have higher knowledge, attitude, and practice scores. The results further justify the need for medical ethics education to be a part of the core medical curriculum. A blame-free environment where seniors can be approached for advice should be created. Research ethics should also be given attention. During medical ethics training, ethical issues where doctors perform poorly should be given more priority and should be discussed in a country-specific context.

Dataset Information

A survey on the effectiveness of WhatsApp for teaching doctors preparing for a licensing exam.

Introduction

Methods

Results

Conclusion

Publications

A survey on the effectiveness of WhatsApp for teaching doctors preparing for a licensing exam.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets