Human-Centered Design of an mHealth Tool for Optimizing HIV Index Testing in Wartime Ukraine: Formative Research Case Study
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,055 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».