Human-Centered Design of an mHealth Tool for Optimizing HIV Index Testing in Wartime Ukraine: Formative Research Case Study
Bibliographic record
Abstract
BACKGROUND: Assisted partner services (APSs; sometimes called index testing) are now being brought to scale as a high-yield HIV testing strategy in many nations. However, the success of APSs is often hampered by low levels of partner elicitation. The Computer-Assisted Self-Interview (CASI)-Plus study sought to develop and test a mobile health (mHealth) tool to increase the elicitation of sexual and needle-sharing partners among persons with newly diagnosed HIV. CASI-Plus provides client-facing information on APS methods and uses a standardized, self-guided questionnaire with nonjudgmental language for clients to list partners who would benefit from HIV testing. The tool also enables health care workers (HCWs) to see summarized data to facilitate partner tracking. OBJECTIVE: The formative research phase of the CASI-Plus study aimed to gather client and HCW input on the design of the CASI-Plus tool to ensure its acceptability, feasibility, and usability. METHODS: This study gathered input to prioritize features and tested the usability of CASI-Plus with HCWs and clients receiving HIV services in public health clinics in wartime Ukraine. The CASI-Plus study's formative phase, carried out from May 2023 to July 2024, adapted human-centered design (HCD) methods grounded in principles of empathy, iteration, and creative ideation. The study involved 3 steps: formative HCD, including in-depth individual interviews with clients, such as men who have sex with men and people who inject drugs, and internet-based design workshops with HCWs from rural and urban HIV clinics in Chernihiv and Dnipro; software platform assessment and heuristic evaluation, including assessment of open-source mHealth platforms against CASI-Plus requirements, prototype development, and testing of the REDCap (Research Electronic Data Capture) prototype based on usability heuristics; and usability walk-throughs, including simulated cases with HCWs and clients. RESULTS: The formative phase of the CASI-Plus study included in-depth individual interviews with 10 clients and 3 workshops with 22 HCWs. This study demonstrated how simplified HCD methods, adapted to the wartime context, gathered rich input on prioritized features and tool design. The CASI-Plus design reflected features that are both culturally sensitive and in alignment with the constraints of Ukraine's wartime setting. Prioritized features included information about the benefits of HIV index testing; a nonjudgmental, self-guided questionnaire to report partners; client stories; and bright images to accompany the text. Two-way SMS text messaging between clients and HCWs was deemed impractical based on risks of privacy breaches, national patient privacy regulations, and HCW workload. CONCLUSIONS: It was feasible to conduct HCD research in Ukraine in a wartime setting. The CASI-Plus mHealth tool was acceptable to both HCWs and clients. The next step for this research is a randomized clinical trial of the effect of the REDCap-based CASI-Plus tool on the number of partners named and the rate of partners completing HIV testing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".