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A content analysis of digital crowdsourced messages to reduce HIV stigma and promote testing among adolescents and young adults in Kazakhstan
JasSpark Study Team (2026). A content analysis of digital crowdsourced messages to reduce HIV stigma and promote testing among adolescents and young adults in Kazakhstan. AIDS and Behavior. Advance online publication. https://doi.org/10.1007/s10461-026-05095-5
In Kazakhstan, almost a quarter of HIV infections are estimated to be among adolescents and young adults (AYA). However, AYA have low testing rates, partially due to stigma. A nationwide digital crowdsourcing open call invited AYA ages 13-29 years old to create media content that could reduce HIV stigma in order to promote testing among peers. This study examines the format and content of entries to the open call, exploring whether AYA address key points about stigma and testing identified by public health professionals. The content analysis framework was informed by Nyblade et al.'s concept of immediately actionable drivers of stigma: awareness of stigma, fear of HIV acquisition, attitudes, and institutional environment. Additional codes examined content type, tone, AYA-specific appeal, social support, and testing messages. The open call received 96 entries, representing almost all provinces in Kazakhstan. AYA submitted more videos/images (67%) compared to other types of content. Most content was emotive in tone (60%) and included features with AYA-specific appeal (80%). Nearly a third of entries referenced the impact of social support. Eighty-eight percent included at least one driver of stigma; most addressed them in a positive way, but some perpetuated stigmatizing ideas. Finally, 60% explained the importance of HIV testing, mainly focusing on health implications. Findings suggest AYA are willing to submit to open calls and can produce creative, relevant content to address HIV stigma and promote testing. A minority of entries included potentially stigmatizing content, highlighting the importance of a structured, multi-phase judging process in crowdsourcing.
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