Typology and Ethical Considerations of Digital Health Promotion Tools for Youth in Sub-Saharan Africa: Review of Examples From Ghana, Kenya, and South Africa
Notice bibliographique
Résumé
Background: Digital technologies for health promotion have proliferated over the past decade, with uptake increasing steadily among young people, including those in low- and middle-income countries (LMICs). Youth increasingly rely on digital tools for health information, and the early influence of this digital technology can have an impact throughout the lifespan. While there is a growing body of literature on the opportunities and challenges of digital health promotion (DHP) for young people, a gap remains in research that closely examines the characteristics of digital health strategies developed specifically for youth in LMICs. Objective: In this paper, we investigate and compare selected examples of DHP tools from 3 countries in Sub-Saharan Africa, namely Ghana, Kenya, and South Africa. Our aim is to create a multidimensional descriptive typology of DHP tools developed specifically to promote the health of adolescents and young adults in these countries. Methods: To select the tools, we conducted systematic internet-based searches using relevant keywords, incorporating the expertise of local professionals to ensure a thorough search. Included solutions originated from one of the 3 countries of focus and could take any number of forms such as apps, websites, chatbots, or social media initiatives. We thereafter deductively created a typology describing selected features of each tool, including the health area of focus, key stakeholders, type of service, and ethical values explicitly referenced within the tool. While such high-level features of interest were selected based on the existing literature in the field, the detailed descriptive categories were identified through an inductive analysis of the tools. Results: A total of 31 DHP tools were identified. Sexual and reproductive health was the most common health area of focus for DHP services, which were primarily funded and supported by local non-governmental organizations, foundations, and international organizations. The assessed tools were predominantly web-based and social media-based, with the overarching goal and core value of expanding health knowledge and offering access to health promotion services to young people. Conclusions: With sustained investment, DHP can improve the health of young people while relieving pressure on health care services. The areas of mental health, as well as substance use prevention and nutrition, stand out with clear potential for health gains through investment in DHP. Addressing ethical concerns such as privacy, transparency, equity, and inclusiveness is essential to the safety, usefulness, and fairness of DHP. To achieve the greatest benefit, local youth perspectives and priorities should be included in DHP development. Local initiatives have the potential to be the most agile, flexible, and relevant for the target audience of young people, with the overall goal of early intervention and greater health quality throughout the lifespan, and more efficient use of health care resources.
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 | 0,028 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,018 | 0,021 |
| Études des sciences et des technologies | 0,004 | 0,007 |
| Communication savante | 0,006 | 0,010 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».