How I experienced tele-intervention : qualitative insights from persons who stutter

Abstract

BACKFROUND : Tele-intervention gained popularity, during the coronavirus disease 2019 (COVID-19) pandemic, prompting healthcare providers to adapt to remote service delivery. Research about stuttering treatment via tele-intervention in South Africa is limited. Speech-language therapists (SLTs) require further insights to deliver a well-supported approach for treatment of stuttering using tele-intervention, despite limitations such as technological disruptions, including loadshedding, that impact service reliability. OBJECTIVES : The study aims to explore clients’ experiences with tele-intervention for stuttering therapy, and to provide recommendations to improve service delivery. METHOD : Semi-structured interviews were conducted with 11 persons who stutter (PWS) recruited through purposive sampling. Written informed consent was obtained from all participants with experience in both tele-intervention and in-person treatment. Inductive thematic analysis supplemented by descriptive statistics was used to identify patterns and trends. RESULTS : Four main themes emerged: (1) User experiences and factors shaping perceptions of tele-intervention; (2) technical infrastructure: barriers and facilitators; (3) financial and access considerations and (4) in-person treatment experience compared to tele-intervention user experience. Likert scale ratings indicated no considerable difference in preferences between tele-intervention and in-person treatment. CONCLUSION : Participants’ diverse experiences highlighted tele-intervention’s benefits and challenges for stuttering therapy. While limitations exist, findings inform service enhancement in South Africa, emphasising the importance of users’ perspectives in tele-intervention design. CONTRIBUTION : Insights from PWS can be used in informing clinical practice, aiding SLTs in meeting the needs of PWS and guiding best practice. Tele-intervention should be integrated into a hybrid intervention model that PWS prefer.