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20 October 2022 | Story Gerda-Marié van Rooyen
Gali Mokgosi
Gali Mokgosi uses her passion for students and films to promote conversations about mental health and how campus life inside and outside the classroom – including residence life – affects and is affected by the physical, mental, and spiritual health of its students.

Using her experience in theatre and her passion for students, Gali Mokgosi, Residence Head of House Madelief, helps students explore and implement skills to cope with the demands of university life. A Health and Wellness coordinator for residence life, she helps improve their lives by teaching them the value of sufficient sleep, nutrition, exercise, recreation, positive coping strategies, healthy social and sexual relationships, and a sense of belonging within residences.

Mentoring and supporting university students

As a former English lecturer for first-year students, this go-getter saw an urgency to mentor and support university students. In 2016, she landed a job as residence head and resigned from lecturing to focus on theatre and residence affairs. Soon after her appointment, she and her colleague, Nthabiseng Mokhethi, Residence Head of House Ardour, were asked to coordinate the Residence Life Health and Wellness portfolio at a time when there were many suicide attempts and mental health issues, and drug and alcohol abuse plagued residences.

“Our main responsibility as Health and Wellness coordinators is to support Residence Committee Health and Wellness representatives (RCHW) in their respective residences. We facilitate training for RCHW peers and help them to think broadly about how campus life inside and outside the classroom – including residence life – affects and is affected by the physical, mental, and spiritual health of its students.”

Using film to address topical issues

With an honours degree in Drama and Theatre Arts, this UFS alumna knew she had to adapt to virtual means for her portfolio to continue supporting students during COVID-19.

“There was a need for intervention, and I saw an opportunity to close this gap by helping students through their challenges using films. I wrote films that directly address the challenges students were/are facing. Being a residence head, content for my films is always under my nose, and the storyline is undeniably relevant to them.”

Mokgosi wrote and produced four films for the various student support offices, with the help of Shibashiba Moabelo, Institutional HIV/AIDS Programme Coordinator at Kovsie Health, and Pulane Malefane, Assistant Director: Residence Life. These films are, I am, Triggers, Versus me, and Monate jou lekker ding.

This scriptwriter says when students can identify themselves in a story, they tend to gravitate towards a solution as suggested by the story. Students across the University of the Free State’s (UFS) three campuses act in the films. After watching a film, students engage with each other and receive tools to explore the story and reflect on the outcomes as suggested by the film.

Proving her sensitivity for inclusiveness, she had an opportunity to be part of the art skills exchange programme in Deaf theatre at Gallaudet University, Washington, DC. She also presented a research paper in Athens, Greece.

Mokgosi is looking forward to experiment with Deaf films in 2023.

Asked how she looks after her mental health, she reveals: “I take care of my mental health through prayer and meditation. I believe the first place to prosper is through my spiritual life. God is my strength from day to day. He is my all in all. Without Him, I will fall.”

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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