ArticlePreventive medicine reports2024
The HIV prevention decision-making cascade: Integrating behavioural insights into HIV prevention efforts.
Article in Preventive medicine reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Decision-making and acceptability of subcutaneously administered broadly neutralising monoclonal antibodies for HIV prevention amongst CAPRISA 012A trial participants in Durban, South Africa.Scientific reports · 2025Trial
- A qualitative study assessing the acceptability of a multi-agent AI Chatbot for providing HIV and mental health support among men who have sex with men and transgender women in KwaZulu-Natal, South Africa.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2026Article
- "I Just Stopped Taking PrEP Without a Reason": Understanding PrEP Decision-Making Amongst South African Adolescent Girls and Young Women (AGYW).AIDS and behavior · 2025Article
- Perspectives on App-Assisted Self-Testing Using Rapid Diagnostic Tests Among Community Members, Health Care Providers, and Public Health Leaders in Kenya, South Africa, and Zambia: Qualitative Study.Journal of medical Internet research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The syndemic of HIV, sexually transmitted infections (STIs), and early pregnancy remain a key challenge to global public health. Decision-making around sexual and reproductive health (SRH) behaviours is critical to ensuring the uptake of biomedical technologies. Drawing from behavioural science theories, we propose a novel conceptual framework-the Decision Cascade-to describe the decision-making process that a user will go through as they navigate these decisions. Analogous to the HIV prevention and treatment cascade, this model describes key steps individuals go through when deciding to use HIV prevention technologies. Each step (being cued/triggered to act, reacting to the behaviour, evaluating the behaviour, assessing the feasibility of acting and the timing and final execution of the action), is influenced by a myriad of individual and socio-cultural factors, shaping the ultimate decision and behaviour outcome in a continual cycle. This framework has applications beyond HIV prevention, extending to other SRH technologies and treatments. By prioritizing human-centered design and understanding user decision-making intricacies, interventions can enhance effectiveness and address the complexities of SRH service uptake across diverse populations. The Decision Cascade framework offers a comprehensive lens to inform intervention design, emphasizing the need for nuanced approaches that resonate with the realities of decision-makers. Adopting such approaches is essential to achieving meaningful impact in HIV prevention and broader SRH initiatives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.