Development of an mHealth Solution for Tailored Communication Between Patients With Inflammatory Bowel Disease and Health Care Professionals: Participatory Design Study
Notice bibliographique
Résumé
Background: Patients with inflammatory bowel disease (IBD) have periods with flare-ups, including abdominal pain, diarrhea, bloody stools, and systemic symptoms that may negatively influence the patients' quality of life. Hence, prompt and intensified treatment is often required, and patients need to pay attention to self-management, including easy access to health care professionals. Seeking support is essential in patients' self-management and beneficial for their quality of life. However, patients may experience difficulties in gaining access to health care professionals by phone or email when needed. Mobile health (mHealth) interventions have been shown to support patients with flexible, timely, and ongoing communication with health care professionals. However, the most prevalent functions of current apps for patients with IBD are tracking disease symptoms and accessing information. In addition, patient and clinician involvement in the design and development of eHealth apps for patients with IBD has been limited, although engaging patients is emphasized as essential for identifying tools and functionalities that they find relevant and effective. Objective: This study aimed to develop an mHealth solution for patients with IBD using participatory design to support tailored communication between patients and health care professionals. Methods: Through participatory design, we completed 3 focus groups, 4 mock-up workshops, and 2 prototype tests involving patients, health care professionals, and an IT designer to collaboratively develop a prototype. The iterative process allowed for feedback from all stakeholders to inform the design and development. This approach facilitated ongoing refinement of the prototype until a mutually satisfactory solution was achieved. Data analysis followed the structured phases inherent to participatory design: planning, acting, observing, and reflecting. Results: A total of 14 patients with IBD aged 18-65 years and 9 health care professionals from 2 outpatient clinics in Denmark contributed to the mHealth design. The analysis generated 6 themes of patients' suggestions for app content: easy-access messaging, agreement overviews, self-initiated patient-reported outcomes with free text, treatment and blood test notifications, an IBD knowledge base, and self-monitoring via diary and symptom registration. An intervention that reflected users' needs and requests to support patients' access to and communication with health care professionals in outpatient clinics was developed. The intervention included messaging, symptom registration, notifications, questionnaires with free-text space, a knowledge base, and an appointment overview. Conclusions: The participatory design served as a usable approach to designing and developing a tailored mHealth solution for patients with IBD and their health care professionals in an outpatient clinic. On the basis of the iterative design process with mutual learning and democratic voices, the participants had a significant impact on the solution, which reflected users' needs and resulted in the effective adaptation of the solution to the clinical setting.
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 | 0,002 | 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 ».