Illustrating User Needs for eHealth With Experience Map: Interview Study With Chronic Kidney Disease Patients
Notice bibliographique
Résumé
BACKGROUND: Chronic kidney disease (CKD) is a common condition worldwide and home dialysis (HD) provides economic, quality of life, and clinical advantages compared to other dialysis modalities. Human-centered design aims to support the development of eHealth solutions with high usability and user experience. However, research on the eHealth needs of patients using HD is scarce. OBJECTIVE: This study aimed to support the design of eHealth for patients with CKD, particularly for patients using HD, by developing a kidney disease experience map that illustrates user needs, concerns, and barriers. The research questions were (1) what experiences do patients, particularly older adults, have in their everyday lives with CKD? (2) what user needs do patients with CKD have for HD eHealth? (3) how can these needs be illustrated using the experience map technique? The study focused on patients aged >60 years, as they are at a higher risk of chronic conditions. The study was conducted as part of the eHealth in HD project, coordinated by Hospital District of Helsinki and Uusimaa, Finland. METHODS: In total, 18 patients in different care modalities participated in retrospective interviews conducted between October 2020 and April 2021. The interviews included a preliminary task with patient journey illustrations and questions about their experiences and everyday lives with CKD. The data analysis was conducted using a thematic analysis approach and the process included several phases. RESULTS: On the basis of the thematic analysis, 5 categories were identified: healthy habits, concerns about and barriers to eHealth use, digital communication, patients' emotions, and everyday life with CKD. These were illustrated in the first version of the kidney disease experience map. The patients had different healthy habits regarding social life, sports, and other activities. They had challenges with poorly functioning eHealth software and experienced other factors, such as a lack of interest and lack of skills for eHealth use. Technical devices do not always meet the emotional or physical needs of their users. This caused feelings of frustration, worry, and fear in patients, yet also fostered situational awareness and hope. CONCLUSIONS: The experience map is a promising method for illustrating user needs and communicating the patient's voice for eHealth development. eHealth offers possibilities to support patient's everyday life with chronic disease. The patient's situation and capacity to use eHealth solutions vary with their everyday challenges, opportunities, and their current stage of treatment. The kidney disease experience map will be used and further developed in the ongoing research project "Better Health at Home-Optimized Human-Centered Care of Predialysis and Home Dialysis Patients" (2022 to 2026).
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 | 0,008 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».