Digital encounter decision aids linked to clinical practice guidelines: results from user testing SHARE-IT decision aids in primary care
Notice bibliographique
Résumé
BACKGROUND: Encounter decision aids (EDAs) are tools that can support shared decision making (SDM), up to the clinical encounter. However, adoption of these tools has been limited, as they are hard to produce, to keep up-to-date, and are not available for many decisions. The MAGIC Evidence Ecosystem Foundation has created a new generation of decision aids that are generically produced along digitally structured guidelines and evidence summaries, in an electronic authoring and publication platform (MAGICapp). We explored general practitioners' (GPs) and patients' experiences with five selected decision aids linked to BMJ Rapid Recommendations in primary care. METHODS: We applied a qualitative user testing design to evaluate user experiences for both GPs and patients. We translated five EDAs relevant to primary care, and observed the clinical encounters of 11 GPs when they used the EDA with their patients. We conducted a semi-structured interview with each patient after the consultation and a think-aloud interview with each GPs after multiple consultations. We used the Qualitative Analysis Guide (QUAGOL) for data analysis. RESULTS: Direct observations and user testing analysis of 31 clinical encounters showed an overall positive experience. The EDAs created better involvement in decision making and resulted in meaningful insights for patients and clinicians. The design and its interactive, multilayered structure made the tool enjoyable and well-organized. Difficult terminology, scales and numbers hindered understanding of certain information, which was sometimes perceived as too specialized or even intimidating. GPs thought the EDA was not suitable for every patient. They perceived a learning curve was required and the need for time investment was a concern. The EDAs were considered trustworthy as they were provided by a credible source. CONCLUSIONS: This study showed that EDAs can be useful tools in primary care by supporting actual shared decision making and enhancing patient involvement. The graphical approach and clear representation help patients better understand their options. To overcome barriers such as health literacy and GPs attitudes, effort is still needed to make the EDAs as accessible, intuitive and inclusive as possible through use of plain language, uniform design, rapid access and training. TRIAL REGISTRATION: The study protocol was approved by the The Research Ethics Committee UZ/KU Leuven (Belgium) on 31-10-2019 with reference number MP011977.
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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 | 0,265 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».