Effects of a WhatsApp-Delivered Education Intervention to Enhance Breast Cancer Knowledge in Women: Mixed-Methods Study
Notice bibliographique
Résumé
BACKGROUND: Breast cancer is the leading cause of cancer-related death in the female population. Health education interventions based on the use of mobile technologies enable the development of health self-care skills and have emerged as alternative strategies for the control of breast cancer. In previous studies, WhatsApp has stood out as a useful tool in health education strategies; however, it has not yet been applied for breast cancer education. OBJECTIVE: This study aimed to analyze the potential of WhatsApp as a health education tool used to improve women's knowledge on the risk reduction of breast cancer. It also aimed to understand how women feel sensitized within the WhatsApp group throughout the intervention and how they incorporate information posted to improve knowledge about early detection and risk reduction methods. METHODS: The study involved a pre-post health educational intervention with 35 women (aged 45-69 years) included in a WhatsApp group to share information (audio, video, text, and images) over 3 weeks on the early detection and risk reduction of breast cancer. Data were collected through questionnaires on topics related to risk reduction, as well as qualitative content analysis of group interactions. Effectiveness and feasibility were analyzed through conversations and the comparison of the scores obtained in the questionnaires before and after the intervention. RESULTS: A total of 293 messages were exchanged (moderator 120 and users 173). The average scores of the participants were 11.21 and 13.68 points before and after the educational intervention, respectively, with sufficient sample evidence that the difference was significant (P<.001). The intervention enabled women to improve their knowledge on all topics addressed, especially "myths and truths," "incidence," "clinical manifestations," and "protective factors." Some themes emerged from the interactions in the group, including group dynamics, general doubts, personal narratives, religious messages, daily news, and events. CONCLUSIONS: The use of groups for women in WhatsApp for health education purposes seems to be a viable alternative in strategies on breast cancer control, especially as it provides a space for the exchange of experiences and disinhibition. However, the need for a moderator to answer the questions and the constant distractions by members of the group represent important limitations that should be considered when improving this strategy.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».