Determinants of the Intention to Use Teledermatology: Evidence From Dermatologists and Primary Care Physicians
Notice bibliographique
Résumé
Background: Teledermatology (TD) is one of the applications of electronic health and telemedicine that involves the use of information and communication technologies (ICTs) for the care of skin diseases. Previous studies on TD indicate that it seems to be effective in diagnosing early malignant pathologies, such as melanoma, and in reducing waiting lists by prioritizing urgent cases of pathology. Despite these advantages, the implementation of TD is still low in many areas. Objective: Most previous studies on TD have focused on analyzing the results of TD use. However, to completely understand TD, it is necessary to consider the determinants of its use. This study analyzes the factors that motivate medical professionals to use TD in their clinical practice. Methods: A survey that targeted a total population of 743 medical professionals from health care institutions in Andalusia (Spain) was used. The study sample comprised 223 doctors (87 dermatologists and 136 primary care physicians). Results: Using an extended Technology Acceptance Model and microdata for the 223 physicians, a cluster analysis (of the user’s ICT profile) and binary logistic regression analysis were conducted. This analysis demonstrated the presence of 3 clusters in the sample with respect to the use of technology (cluster 1: advanced use of ICTs; cluster 2: moderate use of ICTs; and cluster 3: scarce use of ICTs). The analysis performed confirmed the model’s goodness of fit, which allowed 69% of the variable’s variance to be explained. The outcomes revealed that the factors that were most important when implementing a TD system were the user’s ICT profile (P=.048), system efficiency (P<.001), and preference of the subjects involved (P=.008; P<.005). The quality of the assistance, the difficulties arising from the use of technology (information security and confidentiality), or interests of the administration were not decisive factors for the implementation of TD. Subsequently, we performed a logistic regression analysis, separating primary care doctors from dermatologists. For the former, the determining factors were the ICT profile and the efficiency of the system, whereas, among dermatologists, only the preference of each individual was considered to be a determining factor. Conclusions: The use of TD should be accompanied by a comprehensive program of validation and evaluation. These results show that determinants of TD implementation differ depending on the subjects involved. Therefore, it is essential to perform studies before the implementation of a TD system to identify and influence the aforementioned predictive factors.
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 | 0,000 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| 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 ».