Background: Pregnancy decision-making is complicated for HIV-positive women because they have to contend with unpredictable symptoms, potential vertical transmission, and often a problematic life context including poverty, abuse, and stigma. Purpose: The purpose of the study was to explore the views of HIV-positive women attending a support group at a clinic in the Mpumalanga Province, on becoming pregnant. Methods: A qualitative, descriptive, and phenomenological research design was adopted to conduct one-on-one interviews using a semi-structured interview guide. Purposive sampling aided the selection of fifteen HIV-positive women who were members of the HIV/AIDS support group at the clinic. Data saturation was reached at participant number 15. Lincoln and Guba's four criteria for ensuring the trustworthiness of data were applied. Data were analysed using the open coding technique. Results: The following categories emerged: Mitigating fears of becoming pregnant through the prevention of mother-to-child transmission (PMTCT) programme; relationship between becoming pregnant and stigma attached to HIV/AIDS; cultural and social norms about becoming pregnant and the relationship between support groups and becoming pregnant. Conclusion: The study concluded that the desire to become pregnant amongst HIV-positive women is influenced by several aspects such as knowledge about the prevention of mother to child transmission, cultural values and social norms, and belonging to support groups where they were able to share experiences. Furthermore, becoming pregnant was viewed as an obligation to satisfy their partners/husbands and security to maintain marriages.
Keyphrases
- hiv positive
- south africa
- hiv aids
- antiretroviral therapy
- pregnant women
- pregnancy outcomes
- polycystic ovary syndrome
- mental health
- hiv infected
- men who have sex with men
- human immunodeficiency virus
- healthcare
- primary care
- cervical cancer screening
- electronic health record
- public health
- decision making
- machine learning
- big data
- insulin resistance
- type diabetes
- mental illness
- clinical trial
- metabolic syndrome
- data analysis
- minimally invasive
- preterm birth
- study protocol
- physical activity