An Ecological Monitoring and Management App (EMMA) for Older Adults With Chronic Pain: Protocol for a Design and Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: Chronic pain is a complex problem for many older adults that affects both physical functioning and psychological well-being. Mobile health (mHealth) technologies have shown promise in supporting older persons in managing chronic conditions. Cognitive behavior therapy is recommended for older people with chronic pain. However, web-based treatment programs for chronic pain are not aimed at the needs of older people and offer standard therapies without providing tailored treatment for this population. OBJECTIVE: To address this problem, we aim to develop a psychological web-based intervention for ecological monitoring of daily life experiences with chronic pain called EMMA to support self-management of chronic pain in older adults. METHODS: The key clinical and engagement features of the intervention were established through the integration of evidence-based material from cognitive behavioral therapy for the treatment of chronic pain in older adults. The development process uses a co-design approach and actively involves end-users in the design process by incorporating feedback from focus groups with older adults in order to inform a user-centered intervention design. For the co-design process, we will include 10 older adults with chronic pain, who will discuss the requirements for the app in workshops in order to ensure suitability of the app for older adults with chronic pain. In order to test the feasibility and acceptability of the intervention, we will include a sample of 30 older adults with chronic pain who will test all features of the intervention for a period of 8 consecutive weeks. After the trial period, validated instruments will be used to assess usability and acceptability, as well as influence on pain levels and associated physical and psychological symptoms. Participants will be invited to take part in a semistructured telephone interviews after the trial period to explore their experiences using the app. RESULTS: Digitalization of the pain diary and psychotherapeutic content has started. Recruitment of participants for the co-design workshops will start as soon as we have a functioning prototype of the electronic pain diary and EMMA intervention, which is expected to be in September 2021. The feasibility study will start as soon as the co-design process is finished and required changes have been implemented into the pain diary and the EMMA intervention. We expect to start the feasibility study early in 2022. CONCLUSIONS: Required changes to assure usability and acceptability will be directly implemented in the app. EMMA brings together a strong body of evidence using cognitive behavioral and self-management theory with contemporary mHealth principles, allowing for a cost-effective intervention that can be used to target chronic pain anywhere and anytime by older adults. Given the ubiquity of mHealth interventions for chronic conditions, the results of this study may serve to inform the development of tailored self-management interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/26930.
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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 | 0,049 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,003 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,060 | 0,014 |
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 ».