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Web-Based Application to Support Caregivers in the Use of Learning Optimization Methods: Participatory Action

Chantal Viscogliosi1, Hubert Kenfack Ngankam2, Romane Duquette-Laplante3

  • 1École de réadaptation, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, 3001, 12e avenue Nord, Sherbrooke, QC, J1H 5N4, Canada, 1 819 821-8000 #72934.

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Summary
This summary is machine-generated.

This study developed the Aide-Mémoire-Interactif (AMI) web application to personalize cognitive rehabilitation strategies for individuals with major neurocognitive disorders (MNCDs). The AMI tool helps tailor learning optimization methods to daily situations, improving functional independence.

Keywords:
family caregiversinterventionlearning-optimizing methodsmajor neurocognitive disorderqualitative researchweb application

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Rehabilitation Science

Background:

  • Major neurocognitive disorders (MNCDs) impair daily activities.
  • Cognitive rehabilitation uses learning optimization methods (e.g., error-free learning, spaced retrieval) to aid individuals with MNCDs.
  • Personalizing these methods to specific situations is challenging.

Purpose of the Study:

  • To describe the codevelopment and validation of the Aide-Mémoire-Interactif (AMI) web application.
  • To create a tool that personalizes learning optimization methods for individuals with MNCDs.

Main Methods:

  • Participatory action research involving codevelopment and validation.
  • Three phases: needs assessment, initial development, and validation.
  • Interviews and workshops with 20 participants (caregivers, professionals).

Main Results:

  • The AMI web application was iteratively developed with user feedback.
  • Features include tailored strategy generation, educational capsules, and saved personalized strategies.
  • Participants reported enhanced clarity, usability, and relevance of the AMI tool.

Conclusions:

  • Participatory research successfully codeveloped and validated the AMI web application.
  • The AMI tool operationalizes learning optimization methods for MNCDs by personalizing them to daily situations and cognitive needs.
  • User involvement ensured the application meets practical needs and is well-received.