Health Information Seeking on the Internet Among Patients With and Without Cancer in a Region Affected by the 2011 Fukushima Triple Disaster: Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Health information seeking via the internet among patients with cancer in disaster-affected areas is underresearched. OBJECTIVE: This study aims not only to assess the extent and means of web-based health information seeking among patients with cancer living in the disaster-affected area of the 2011 Fukushima triple disaster but also to compare these patterns with those without cancer, identifying distinct and shared factors influencing their web-based health information behaviors. METHODS: We surveyed 404 patients (263 with and 141 without cancer) from the surgery department outpatient office at Minamisoma Municipal General Hospital, from October 2016 to January 2017. The survey included self-administered questions on internet and digital device use. Descriptive analyses were performed to examine the use patterns of digital devices and the internet and their impact on health information seeking across different age groups of patients with and without cancer. Multivariable logistic regression was used to examine factors associated with web-based health information seeking, stratifying by cancer diagnosis. RESULTS: The proportion of participants who sought health information on the internet was comparable between patients with cancer and patients without cancer (19% vs 17.4%; P=.71). Digital device use varied significantly with age, with peak smartphone use occurring among the youngest cohorts for both groups. Multivariable logistic regression revealed that patients with cancer using smartphones or tablets daily were significantly more likely to gather web-based health information (odds ratio [OR] for smartphones 3.73, 95% CI 1.58-8.80; OR for tablets 5.08, 95% CI 1.27-20.35). Trust in institutional websites also significantly influenced web-based health information gathering among patients with cancer (OR 2.87, 95% CI 1.13-7.25). Conversely, among patients without cancer, unemployment was associated with a lower likelihood of seeking web-based health information (OR 0.26, 95% CI 0.08-0.85), whereas trust in both institutional and personal websites significantly increased this likelihood (OR for institutional websites 6.76, 95% CI 2.19-20.88; OR for personal websites 6.97, 95% CI 1.49-32.58). CONCLUSIONS: This study reveals that a small proportion of both patients with cancer and patients without cancer engage in health information seeking via the internet, influenced by age, digital device use, and trust in institutional websites. Given the growing prevalence of digital literacy, strategies to enhance accessible and reliable web-based health information should be developed, particularly for patients with cancer in postdisaster settings. Future efforts should focus on tailored health communication strategies that address the unique needs of these populations.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| 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 ».