A Digital Sexual Health Education Web Application for Resource-Poor Regions in Kenya: Implementation-Oriented Case Study Using the Intercultural Research Model
Notice bibliographique
Résumé
BACKGROUND: Developing a digital educational application focused on sexual health education necessitates a framework that integrates cultural considerations effectively. Drawing from previous research, we identified the problem and essential requirements to incorporate cultural insights into the development of a solution. OBJECTIVE: This study aims to explore the Solution Room of the self-established Intercultural Research Model, with a focus on creating a reusable framework for developing and implementing a widely accessible digital educational tool for sexual health. The study centers on advancing from a low-fidelity prototype (She!Masomo) to a high-fidelity prototype (We!Masomo), while evaluating its system usability through differentiation. This research contributes to the pursuit of Sustainable Development Goals 3, 4, and 5. METHODS: The research methodology is anchored in the Solution Room of the self-expanded Intercultural Research Model, which integrates cultural considerations. It uses a multimethod, user-centered design thinking approach, focusing on extensive human involvement for the open web-based application. This includes gathering self-assessed textual user feedback, conducting a System Usability Scale (SUS) analysis, and conducting 4 face-to-face semistructured expert interviews, following COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines. RESULTS: Based on the identified limitations of the low-fidelity prototype, She!Masomo (SUS score 67), which were highlighted through textual user feedback (63/77) and prototype feature comparisons, iterative development and improvement were implemented. This process led to the creation of an enhanced high-fidelity prototype (We!Masomo). The improved effectiveness of the enhanced prototype was evaluated using the qualitative SUS analysis (82/90), resulting in a favorable score of 77.3, compared with the previous SUS score of 67 for the low-fidelity prototype. Highlighting the importance of accessible digital educational tools, this study conducted 4 expert interviews (4/4) and reported e-survey results following the CHERRIES (Checklist for Reporting Results of Internet E-Surveys) guideline. The digital educational platform, We!Masomo, is specifically designed to promote universal and inclusive free access to information. Therefore, the developed high-fidelity prototype was implemented in Kenya. CONCLUSIONS: The primary outcome of this research provides a comprehensive exploration of utilizing a case study methodology to advance the development of digital educational web tools, particularly focusing on cultural sensitivity and sensitive educational subjects. It offers critical insights for effectively introducing such tools in regions with limited resources. Nonetheless, it is crucial to emphasize that the findings underscore the importance of integrating culture-specific components during the design phase. This highlights the necessity of conducting a thorough requirement engineering analysis and developing a low-fidelity prototype, followed by an SUS analysis. These measures are particularly critical when disseminating sensitive information, such as sexual health, through digital platforms. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12905-023-02839-6.
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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 | 0,007 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».