Page 63 - SAMRC AnnualReport 2025-26

P E R FOR M A NC E I N FOR M A T I ON

Building Capacity Through relationships within large datasets beyond the
Training, Mentoring, and Support scope of traditional statistical methods.

The Unit undertakes targeted capacity The Unit is progressively integrating AI and data-
development initiatives to strengthen research driven approaches to strengthen research and
skills while promoting equity and dignity in mental decision-making. These methods are being applied
health research and care. This includes structured to existing clinical, neurocognitive, neurogenomic,
supervision and mentorship of postgraduate and neuroimaging datasets to identify predictors
students and early-career researchers, with practical of treatment response and illness trajectories. The
training in clinical assessment, epidemiology, and Unit is also preparing to apply these approaches
neuroimaging methodologies. within longitudinal cohort studies, including the
The Unit also provides training in culturally sensitive Drakenstein Child Health Study, to better understand
participant engagement, particularly within cohort early risk and resilience factors associated with
studies such as the Drakenstein Child Health Study, mental health outcomes.
where community engagement and respectful Future priorities include strengthening data science
research practices are prioritised.
capacity among researchers and expanding the
Through its collaboration with the Mental Health appropriate use of AI-driven methodologies to
Information Centre, the Unit contributes to broader support innovative and contextually relevant mental
capacity building by equipping counsellors health research.
and student volunteers with skills in community
engagement, mental health literacy, and responsible
media communication to help reduce stigma and
promote dignity in care.

Participation in international initiatives, including
collaborations with the World Health Organization,
further exposes researchers and students to
global standards and best practices while ensuring
relevance to local mental health priorities.

AI in Medical and Health Research

From the Unit’s perspective, artificial intelligence
(AI) refers to computational approaches, including Drakenstein Health Study – Participant doing
machine learning, pattern recognition, and one of the neurocognitive tasks.
multivariate modelling, that can identify complex

Drakenstein Health Study-Psychosocial team on the DCHS, with amongst others, Ms Nadia Hoffman and the
late Prof Dan J Stein on the right.

SA M R C A N N U A L R EP O R T 2 0 2 5 / 2 0 2 6 61