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#KovsiesCare: HR prioritises mental health in the workplace

30 July 2019 | Story Valentino Ndaba | Photo Barend Nagel

HR Kovsie Care — The great poet Virgil once said: “The greatest wealth is health.”

The World Health Organisation (WHO) recently listed burnout as an occupational phenomenon in the 11th Revision of the International Classification of Diseases. Although not classified as a medical condition, its imprint on employees’ health status is absolute.

The hallmark of any conducive workplace is its ability to assist employees to successfully manage stress. The Occupational Development and Employee Wellness Division at the University of the Free State’s (UFS) Department of Human Resources (HR) continues to make concerted efforts to ensure the good mental and physical health of all staff members.

Solving an occupational dilemma

Burnout is characterised by feelings of energy depletion, increased mental distance from one’s job, and reduced professional efficacy. Over the past few years HR has launched various preventive programmes for support and academic staff as well as service workers.

One of these initiatives is the Power Hour sessions which are hosted at lunchtime across all campuses. These interactive platforms cover topics ranging from pain, emotional intelligence, bullying, healthy eating habits, resilience and anxiety.

Fitness as a stress reliever

Over the years what were known as Takkie Tuesdays and Thursdays have evolved into “Take a Break & Feel the difference”. Staff members take 30-minute walks during lunchtime to boost productivity, confidence, energy levels, concentration and creativity while reducing stress symptoms and preventing lifestyle illnesses.

“Our mission is to cultivate a culture of health and wellness. We believe that when the culture is conducive it affects staff performance. The main purpose is to create an environment where people are mentally and physically well,” said Burneline Kaars, head of the wellness division.

Caring is sharing knowledge

True to its tagline “Care”, which stands for: Create, Attract, Retain, Excellence, the division works around the clock to care for staff members’ mental wellbeing. This includes referring those who need curative measures for free counselling provided by Careways.

Another way through which the division inspires employees to enrich their minds, bodies and souls is the Workout@Work programme that offers cardio exercises after office hours and the Pedometer Challenge which tracks physical movement throughout the day.

“It all boils down to being more active. It gets people to leave the office, enjoy the sun, and become more creative and energised,” says Arina Engelbrecht, Employee Wellness Specialist.

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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