The Media Council of Kenya (MCK) has emphasised the crucial role of data-driven journalism in health reporting to enhance community awareness and to foster policy transformation.
MCK's Mombasa Regional Coordinator Maureen Mudi urged journalists to highlight initiatives and interventions targeting social determinants of health and promote health equity for vulnerable and marginalised communities.
“It is important for journalists to conduct research, read ahead and debunk fake news for enhanced reporting”, she said at a data journalism training in Kilifi County, organised by the Aga Khan University.
She stressed the need for journalists to explore innovative approaches in addressing child, maternity, and mental health challenges by working with health experts to provide accurate information.
“Utilising data and technology can provide strategic advantage in comprehending and demystifying scientific terminology, which can be challenging to comprehend”, said Ms Mudi.
Associate Professor of Psychiatry and Dean at Aga Khan University Medical College Prof Lukoye Atwoli said journalists should be sensitive while covering stories on stigmatised individuals in the society.
“Journalists should observe utmost sensitivity when reporting stories on stigmatised individuals in society. This ensures they feel safe and respected”, stated Prof Atwoli.
The Director for Institute of Human Development at the Aga Khan University Prof Amina Abubakar underscored the importance of journalists understanding research procedures and processes.
The training is being implemented by the Aga Khan University’s Graduate School of Media and Communications (AKU-GSMC) as part of the dissemination and sustainability efforts on information on mental, maternal and mental health under the UZIMA project. The UZIMA-DS (UtiliZe health Information for Meaningful impact in East Africa through Data Science) project is funded by the National Institutes of Health (NIH). It is meant to create scalable and sustainable approaches through artificial intelligence/machine learning-based methods to serve as early warning systems to improve health outcomes for at-risk mothers and children and improve mental health outcomes for at-risk adolescents and young adults in Kenya.