<p>Experiences and Views of Medicine Information Among the General Public in Thailand</p>
Notice bibliographique
Résumé
PURPOSE: Written and electronic medicine information are important for improving patient knowledge and safe use of medicines. Written medicine information in Thailand is mostly in the form of printed package inserts (PIs), designed for health professionals, with few medicines having patient information leaflets (PILs). The aim of this study was to determine practices, needs and expectations of Thai general public about written and electronic medicine information and attitudes towards PILs. PATIENTS AND METHODS: Cross-sectional survey, using self-completed questionnaires, was distributed directly to members of the general public in a large city, during January to March 2019. It explored experiences of using information, expectations, needs and attitudes, the latter measured using a 10-item scale. Differences between sub-groups were assessed, applying the Bonferroni correction to determine statistical significance. RESULTS: Of the total 851 questionnaires distributed, 550 were returned (64.2%). The majority of respondents (88%) had received PIs, but only a quarter (26.2%) had received PILs. Most respondents (78.5%) had seen medicine information in online form. High educational level and income increased the likelihood of receiving PILs and electronic information. The majority of respondents (88.5%) perceived PILs as useful, but 70% considered they would still need information about medicines from health professionals. Indication, drug name and precautions were the most frequently read information in PIs and perceived as needed in PILs. Three-quarters of respondents would read electronic information if it were available, with more who had received a PIL having previously searched for such information compared to those who had not. All respondents had positive overall attitudes towards PILs. CONCLUSION: Experiences of receiving PILs and electronic medicine information in Thailand are relatively limited. However, the general public considered PILs as a useful source of medicine information. Electronic medicine information was desired and should be developed to be an additional source of information for consumers.
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 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 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».