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Case Scenarios of People Living with Dementia Who Go Missing: An Education Tool to Manage Risks

Published online by Cambridge University Press:  09 July 2026

Vanessa Vahedi
Affiliation:
School of Public Health Sciences, University of Waterloo Faculty of Health, Waterloo, Canada
Christine Daum
Affiliation:
School of Public Health Sciences, University of Waterloo Faculty of Health, Waterloo, Canada
Emily Rutledge
Affiliation:
School of Public Health Sciences, University of Waterloo Faculty of Health, Waterloo, Canada
Adebusola Adekoya
Affiliation:
School of Public Health Sciences, University of Waterloo Faculty of Health, Waterloo, Canada
Antonio Miguel Cruz
Affiliation:
Department of Occupational Therapy, University of Alberta, Edmonton, Canada
Lili Liu*
Affiliation:
School of Public Health Sciences, University of Waterloo Faculty of Health, Waterloo, Canada
*
Corresponding author: La correspondance et les demandes de tirés-à-part doivent être adressées à : / Correspondence and requests for offprints should be sent to: Lili Liu, School of Public Health Sciences, University of Waterloo Faculty of Health, 200 University Avenue West, Waterloo, ON, N2L 3G1 Canada (lili.liu@uwaterloo.ca).
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Abstract

People living with dementia are at risk of going missing. The goal of this project was to develop case scenarios for health service providers, service recipients, and care partners to facilitate dialogues about managing risks related to going missing. This paper presents 10 case scenarios, based in real events, created to describe factors related to missing incidents of people living with dementia. Scenarios were developed following qualitative analysis of dementia-related missing incident reports from 515 MedicAlert Foundation Canada® hotline call summary notes, 1760 missing incident reports from three Canadian police departments and one search and rescue unit, and the experiences of two families. The case scenarios were reviewed by five participants for comprehensibility and validity. The case scenarios are an educational tool for health service providers, first responders, care partners, and persons living with dementia to use when discussing ways to manage risks of going missing.

Résumés

Résumés

Les personnes atteintes de démence risquent de disparaître. Ce projet visait à élaborer des scénarios de cas pour aider les prestataires de services, les bénéficiaires de services et leurs proches aidants à discuter des risques de disparition. Cet article présente dix scénarios, fondés sur des événements réels, décrivant les facteurs liés aux disparitions de personnes atteintes de démence. Ces scénarios ont été élaborés à partir d’une analyse qualitative de 515 résumés d’appels de la ligne d’assistance de la Fondation MedicAlert Canada®, de 1760 rapports d’incidents provenant de trois services de police canadiens et d’une unité de recherche et sauvetage et de l’expérience de deux familles. Cinq participants ont évalué la compréhensibilité et la validité des scenarios. Ceux-ci peuvent servir d’outil pédagogique pour les professionnels de la santé, les intervenants d’urgence, les proches aidants et les personnes atteintes de démence afin de discuter de la gestion du risque de disparition.

Information

Type
Policy and Practice Note/Note de politique et practique
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press or the rights holder(s) must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of The Canadian Association on Gerontology
Figure 0

Figure 1. Generating the case scenarios using MedicAlert® data (August 2022 to March 2023).Figure 1. long description.

Figure 1

Table 1. Case scenariosTable 1. long description.

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