Mobile Phone Use Among Medical Residents: A Cross-Sectional Multicenter Survey in Saudi Arabia
Notice bibliographique
Résumé
BACKGROUND: Mobile phones have great potential for medical education, as they allow health care providers and students to access resources efficiently at the precise time at the point-of-care to help in informed decision making. OBJECTIVE: The objective of the study was to evaluate the prevalence of mobile phone usage among medical residents and to explore their attitudes, perceptions, and the challenges they experience when using mobile phones in academic and clinical practice. METHODS: A cross-sectional survey was conducted on all 133 residents in 17 different specialties across two large academic hospitals in Riyadh, Saudi Arabia. The Web-based validated questionnaire measured mobile phone platform preferences, and their uses in general and medical practice. The perception of confidentiality and safety impact of using mobile phones for communication and accessing patient's data was also explored, alongside challenges of use and how residents learn to use their mobile phone. RESULTS: With a response rate of 101/133 (75.9%) and mean age of 27.8 (SD 3.0) years, we found that 100/101 (99.0%) of participants were mobile phone users with mean duration of use of 5.12 (SD 2.4) years, and a range from 1 to 12 years. There was no significant difference in use between male and female respondents. A negative linear correlation was found between age and use duration (P=.004). The most common operating system used by participants was the iOS platform (55/101, 54.5%), with English the most commonly used language to operate residents' mobile phones (96/100, 96.0%) despite their native language being Arabic. For communication outside medical practice, chatting applications such as WhatsApp matched phone calls as most commonly used tools (each 88/101, 87.1%). These were also the primary tools for medical communication, but used at a lower rate (each 65/101, 64.4%). In medical practice, drug (83/101, 82.2%) and medical (80/101, 79.2%) references and medical calculation applications (61/101, 60.4%) were the most commonly used. Short battery life (48/92, 52%) was the most common technical difficulty, and distraction at least on a weekly basis (54/92, 58%) was the most likely side effect of using a mobile phone in medical practice. Practically, all participants agreed with the idea of integrating medical staff mobile phones with the hospital information system. Most residents described themselves as self-learners, while half learned from peers, and a quarter learned from the Internet. Only 7/101 (6.9%) had received formal training on the medical use of mobile phones. Over half of residents thought it was safe to discuss patients over their personal, nonencrypted email. CONCLUSIONS: Mobile phone use among medical residents has become almost universal in academic and clinical settings. Thus, academic and health care institutions should support proper utilization of these devices in medical training and point-of-care decision making, while continuing to protect patient confidentiality.
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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 | 0,007 | 0,002 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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.
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