Introduction: Problem-based learning (PBL) was introduced to address passive teaching limitations. However, it is not fully characterised as a teaching modality in pharmacology. The present study investigated the factors affecting pharmacology learning in an integrated PBL-based curriculum in diverse learners.
Methods: Year 1 undergraduate medical students from two cohorts at St. George's University of London and University of Nicosia, participated. Statistical analysis of pharmacology knowledge scores, at the beginning (pre-test) and end of the academic year (post-test), investigated readiness to benefit from PBL based on diverse student characteristics (educational background, age, gender, country of origin, ethnicity, native language, PBL experience). Focus groups/interviews and a survey investigated aspects of integrated PBL impacting learning in depth.
Results: Pre- and post-test scores were positively correlated. Students with biomedical sciences degrees performed better at the pharmacology pre- and post-tests, while post-graduate degree holders performed better only at the pre-test. Effect size was of moderate magnitude. However, progress in learning (post-test performance after controlling for pre-test scores) was unaffected. Qualitative analysis revealed three major themes: 1) PBL as a learning environment; 2) PBL as a learning environment in pharmacology; and 3) PBL as a learning environment and confidence in prescribing. Under theme one, skill development, knowledge acquisition through collaboration and self-directed learning, group dynamics and preferred teaching methods were discussed. Under theme two, contextual learning, depth of knowledge and material correctness were raised. Under theme 3, students expressed variability in prescribing confidence. They perceived that learning could be improved by better integration, further references earlier on, more lectures and PBL facilitators with greater content expertise. The survey findings were consistent with those from focus groups/interviews.
Conclusion: Pharmacology learning in a PBL-based curriculum is facilitated by constructive, collaborative and contextual learning. While baseline pharmacology knowledge may be advantageous, the other aforementioned characteristics studied may not affect readiness to benefit from PBL. However, further instructional scaffolding is needed, for example through further resources, lectures and self-assessment. The results from our study can inform evidence-based curriculum reform to support student learning further. Addressing learning needs could ultimately contribute to reducing medication errors through effective training of future prescribers.
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http://dx.doi.org/10.1186/s12909-024-05289-2 | DOI Listing |
Brief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, Qianjin Street 2699, 130010 Changchun, China.
Imaging-based spatial transcriptomics (iST), such as MERFISH, CosMx SMI, and Xenium, quantify gene expression level across cells in space, but more importantly, they directly reveal the subcellular distribution of RNA transcripts at the single-molecule resolution. The subcellular localization of RNA molecules plays a crucial role in the compartmentalization-dependent regulation of genes within individual cells. Understanding the intracellular spatial distribution of RNA for a particular cell type thus not only improves the characterization of cell identity but also is of paramount importance in elucidating unique subcellular regulatory mechanisms specific to the cell type.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Monitoring, Evaluation, and Learning Platform USAID, Jakarta, Indonesia.
Background: Indonesia's vast archipelago and substantial population size present unique challenges in addressing its multifaceted HIV epidemic, with 90% of its 514 districts and cities reporting cases. Identifying key populations (KPs) is essential for effectively targeting interventions and allocating resources to address the changing dynamics of the epidemic.
Objective: We examine the 2022 mapping of Indonesia's KPs to develop improved HIV and AIDS interventions.
Psychol Bull
January 2025
Department of Kinesiology, University of North Carolina at Greensboro.
This meta-review provides the first meta-analytic evidence from published meta-analyses examining the effectiveness of acute exercise interventions on cognitive function. A multilevel meta-analysis with a random-effects model and tests of moderators were performed in R. Thirty systematic reviews with meta-analyses (383 unique studies with 18,347 participants) were identified.
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