Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Training doctors in basic EEG: analysis of a learning tool relevant to resource‐limited settings

Domain:

healthcareeducation

Record type:

paper
Creator:
VeeJo
Publisher:
WILEY
Host:
Abstract Aim . Clinicians trained to interpret EEG in Africa are scarce. The region is challenged by inadequate access to healthcare professionals and a significant burden of disease, with the result that trained neurophysiologists and epileptologists may not be viewed as an immediate priority. However, approaches, specific to the African context, could be adopted to enable safe practice of basic EEG interpretation. Educational guidelines for the interpretation of paediatric studies, relevant to the region, are lacking. As a result, a handbook targeting this training need was developed and a pilot study undertaken to assess the efficacy of this tool to improve EEG‐reporting skills for clinicians at a basic level. Methods . Eleven health practitioners, who manage children with epilepsy, from various African countries, were recruited. The group analysed selected EEGs before and after reading a training manual (the handbook). A survey was conducted on how useful the participants found the handbook. Results . There was a trend ( p <0.06) supporting improvement in the ability to analyse EEGs following reading of the handbook. The doctors who had one‐on‐one tutoring, in addition to access to the handbook, did significantly better in most EEG‐reporting variables ( p <0.01). Conclusions . The handbook was found to be a viable tool to promote EEG interpretation in the African setting, where foundation skills are needed. However, optimal outcomes were evident with additional individual tutoring, as well as on‐going support to maintain skills. This curriculum will be adapted into a post‐graduate qualification intended to generate clinicians with key basic EEG skills, but not fully trained electrophysiologists. Currently, in the African setting, for maximum impact on patient care, this approach is considered the most likely to have the furthest reach.

Visit

doi.org

Licenses

http://onlinelibrary.wiley.com/termsAndConditions#vor

Similar

AI Diagnostics in Resource-Limited Healthcare Settings of Malawi: A Comparative AnalysisMachine learning for predicting measles outbreaks in resource-limited settingsUsing Fine Needle Aspiration (FNA) as a Tool to Establish Cancer Burden in Resource-Limited Settings: Liberia, 2018 [A319]Blended Bioinformatics Training in Resource-Limited Settings: A case study of challenges and Opportunities for ImplementationProposing evidence-based strategies to strengthen implementation of healthcare reform in resource-limited settings: a summative analysisRomeltk/Enhancing-Epilepsy-Care-in-Resource-Constrained-Settings-through-Streamlined-EEG-Data-Analysis

AI Diagnostics in Resource-Limited Healthcare Settings of Malawi: A Comparative Analysis

AI diagnostics are increasingly being explored as a potential solution to improve disease d

Machine learning for predicting measles outbreaks in resource-limited settings

Abstract Background Measles remains

Using Fine Needle Aspiration (FNA) as a Tool to Establish Cancer Burden in Resource-Limited Settings: Liberia, 2018 [A319]

INTRODUCTION: Low- and middle-income countries (LMICs) have a disproportionate cancer

Blended Bioinformatics Training in Resource-Limited Settings: A case study of challenges and Opportunities for Implementation

Abstract Motivation Delivering high qualit

Proposing evidence-based strategies to strengthen implementation of healthcare reform in resource-limited settings: a summative analysis

Objectives Many resource-limited countries have adopted and implemented health

Romeltk/Enhancing-Epilepsy-Care-in-Resource-Constrained-Settings-through-Streamlined-EEG-Data-Analysis

The objective of the paper is to establish a robust framework that can be effectively utilized in c