From Bots to Better Hearts: Improving Cardiovascular Care in Low-Income South African Communities
1
Information Systems, University of the Western Cape, Bellville, South Africa
2
CHS, University of the Western Cape, Bellville, South Africa
Popul. Med. 2026;8(Supplement Supplement 1):A2845
ABSTRACT
BACKGROUND:
Cardiovascular disease (CVD) is a leading cause of mortality in South Africa. CVD disproportionally affects low socioeconomic communities with limited access to healthcare and self-management resources. Artificial intelligence (AI) chatbots have the potential to support self-management by delivering real-time and personalised health guidance. However, the usability and acceptance of these chatbots in underserved communities remain underexplored.
OBJECTIVES:
This study explores user experience with Cardia, a CVD self-management chatbot developed at the University of the Western Cape.
METHODS:
Data were collected through structured questionnaires and semi-structured interviews from 150 participants from Fisentakraal, a low socioeconomic community in Cape Town. Thematic analysis was guided by the Unified Theory of Acceptance and Use of Technology (UTAUT3) and the Health Belief Model (HBM) constructs.
RESULTS:
Provisional results indicate that users found Cardia easy to use. Cardia provided timely, relevant information. However, digital literacy, limited conversational depth, and language emerged as barriers. Positive engagement was associated with effort expectancy, perceived health risk, perceived health benefit, and cues to action.
CONCLUSIONS:
Cardia shows potential in enhancing cardiovascular self-management in low socioeconomic communities. However, its adoption depends on improving the design, based on user feedback. These findings are critical in designing Cardia as a culturally and contextually relevant digital tool for populations at risk of CVD.
Cardiovascular disease (CVD) is a leading cause of mortality in South Africa. CVD disproportionally affects low socioeconomic communities with limited access to healthcare and self-management resources. Artificial intelligence (AI) chatbots have the potential to support self-management by delivering real-time and personalised health guidance. However, the usability and acceptance of these chatbots in underserved communities remain underexplored.
OBJECTIVES:
This study explores user experience with Cardia, a CVD self-management chatbot developed at the University of the Western Cape.
METHODS:
Data were collected through structured questionnaires and semi-structured interviews from 150 participants from Fisentakraal, a low socioeconomic community in Cape Town. Thematic analysis was guided by the Unified Theory of Acceptance and Use of Technology (UTAUT3) and the Health Belief Model (HBM) constructs.
RESULTS:
Provisional results indicate that users found Cardia easy to use. Cardia provided timely, relevant information. However, digital literacy, limited conversational depth, and language emerged as barriers. Positive engagement was associated with effort expectancy, perceived health risk, perceived health benefit, and cues to action.
CONCLUSIONS:
Cardia shows potential in enhancing cardiovascular self-management in low socioeconomic communities. However, its adoption depends on improving the design, based on user feedback. These findings are critical in designing Cardia as a culturally and contextually relevant digital tool for populations at risk of CVD.
| eISSN: | 2654-1459 |
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