GamePlan4Care, a Web-Based Adaptation of the Resources for Enhancing Alzheimer’s Caregiver Health II Intervention for Family Caregivers of Persons Living With Dementia: Formative, Qualitative Usability Testing Study
Notice bibliographique
Résumé
Background: The negative consequences of caregiving can be mitigated by providing caregivers with support programs that increase their dementia care skills and provide emotional and tangible support. Web-based technology can increase the availability of evidence-based caregiver interventions. GamePlan4Care (GP4C) is a web-based adaptation of the Resources for Enhancing Alzheimer's Caregiver Health II (REACH II) intervention, redesigned and reformatted for web-based delivery. Objective: The goal of GP4C is to create a web-based family caregiver support platform that facilitates self-directed exposure to evidence-based skills training and support for caregivers of persons living with dementia. This multidimensional approach of using technology enhanced with live support has the potential for improved scalability and sustainability. In preparation for a randomized clinical trial of the new intervention, the GP4C platform underwent user interface/user experience (UI/UX) testing with caregivers as part of an iterative design process. Methods: UI/UX testing of caregivers' reactions to technical and content-related aspects of the platform was conducted with 31 caregivers recruited through partnerships with community-based organizations in central Texas. Usability testing consisted of performing system tasks, answering open-ended questions on the tasks, and providing feedback on their experience with the platform. Two researchers used an inductive thematic approach to data analysis using transcripts of individual audio and screen-recorded sessions with each participant. The analysis consisted of 3 phases: data familiarization, coding, and theme formulation. Results: In total, 18 participants tested technical-related aspects of the GP4C platform, and 13 participants tested content-related aspects. The average age of participants was 62 (SD 12.2, range 31-86). A majority of participants were female (27/31, 87.1%) and White or Caucasian (26/31, 83.1%) while almost one-third were Hispanic (10/31, 32.3%). The thematic analysis revealed 3 themes: supportive resources as a common theme, active engagement for technical aspects of the platform, and a comprehensive approach for content aspects of the platform. Participants also suggested changes in navigation and content. Conclusions: Findings from the usability testing sessions indicate that the platform provided engaging, useful content that the caregiver would continue to use, resonated with their caregiving experience, helped the caregivers think through their choices and emotions, and could be used to help communicate with the person living with dementia. Caregivers appreciated the personalization based on what they had already completed and the concept of having a Dementia Care Navigator when they needed additional help. Caregivers also provided multiple suggestions on how to improve the system, including changes for easier navigation and inclusiveness. This positive feedback indicates that with a few changes, the platform would be beneficial to meet the needs and provide resources for caregivers of persons living with dementia. The process of involving end users in usability testing during the development stage ensures that the finished tool will better meet users' expectations and current needs.
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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 | 0,010 | 0,013 |
| 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 | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».