Mobile Electronic Devices as Means of Facilitating Patient Activation and Health Professional Empowerment Related to Information Seeking on Chronic Conditions and Medications: Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: Patient activation has an impact on the management of patients' health, clinical outcomes, and treatment costs. Mobile electronic devices (MEDs) have shown the potential to engage patients in wellness behavior. Furthermore, the potentially positive role of MEDs is evident in supporting health professionals in their practice. OBJECTIVE: This study aims to explore the impact of MEDs on patient activation to search for information on chronic conditions and medications and the impact of MEDs on the empowerment of health professionals or future health professionals. METHODS: We conducted 6 focus groups-2 with health sciences students, 2 with health professionals, and 2 with hospitalized patients with chronic conditions. A protocol comprising eight questions was used to guide discussions. Audio-recorded data were transcribed verbatim and analyzed thematically; a ranking system was used to analyze the relevance of identified themes and subthemes, using a coding system depicted by the + symbol, to indicate different relevance levels. RESULTS: Our results suggest that MEDs can positively affect patient activation to search for chronic conditions and medication information by facilitating patients' information-seeking behavior. Key drivers leading to patients' activation to seek information related to chronic conditions and medications through MEDs were the accessibility and abundance of available and detailed information, reduced search time, information updates, and convenience in finding information at any time and place. The lack of accurate information in one's native language, access to incorrect information, and limited access to the internet were key obstacles to seeking information related to chronic conditions and medications via MEDs. In addition, findings of this study suggest that MEDs in general and mobile apps, in particular, may have a positive impact on the work routine of health care professionals as they enable them to make quicker decisions by accessing the required information faster, thus improving practice efficiency. Furthermore, the appropriate usage of MEDs by patients for seeking information about their chronic conditions and medications may positively impact the physician-patient relationship. All focus groups recognized the questionable reliability of health information on the internet and its potential negative effects on patients. Therefore, our findings suggest the need for an additional role of health professionals in assisting patients in using MEDs to search for health and medication information, such as providing reliable websites and mobile apps where patients can safely search for health-related information on the web. CONCLUSIONS: The use of MEDs may help activate patients to seek chronic conditions and medication-related information, potentially leading to better management of their chronic conditions and medications. Our findings also highlight the positive impact MEDs may have on empowering health professionals in their practice and the need for health professionals to help patients through specific education that addresses MEDs utilization for chronic conditions and medication information seeking.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».