The Alzheimer Society Research Portal connects researchers with Canadians looking to participate in research studies. On this website, find active studies that you can participate in to help advance research on dementia.
This research aims to explore the perspectives of older adults living with dementia, providing a nuanced understanding of their experiences and challenges. Second, it seeks to investigate the role of physical activities in their lives, examining how engagement in such activities influences their cognitive function and mental well-being. Finally, this research aims to inform interventions and policies that can support older adults in maintaining their cognitive health and overall well-being.
The data will be used for the researcher’s master’s thesis, and for publishing peer-reviewed and non-peer reviewed articles, conference presentations, webinars, and presentations for professionals.
1.You are eligible to participate if you are a member of the Minds in Motion program.
2.You are eligible to participate if you age 65 and above.
3.You are eligible to participate if you are diagnosed with mild-to-moderate dementia.
4.You are eligible to participate if you actively engaged in some form of physical activity in addition to minds in motion physical activities (e.g. swimming, nature walks, aerobics, chair exercises).
5. You are eligible to participate if you can give informed consent.
This study aims to evaluate the acceptance and usability of the GuardIO Family Care app, a mobile application designed to support community safety for individuals living with dementia or mild cognitive impairment and their care partners. The study also aims to analyze mobility patterns collected from the app to explore how mobility data can contribute to the early detection of cognitive impairment. The findings will help improve app design, inform care strategies, and support early intervention efforts for individuals living with dementia or MCI.
You are eligible to participate if you:
Are 18 years of age or older
Are living with mild cognitive impairment (MCI) or dementia, or are a care partner of someone with MCI or dementia
Are able to use a smartphone or tablet with the GuardIO app
Are willing to participate in the study activities, including using the app, completing questionnaires, and attending an optional focus group
Can understand and communicate in English (or another supported language, if applicable)
This study is testing a digital reminder system for people living with dementia. The system sends alerts when daily routines change and collects feedback from caregivers. The goal is to improve the system’s design and usefulness. Results will help make reminder tools more supportive for people living with dementia and their caregivers.
You are eligible to participate if you are a person living with dementia and you:
- Have a clinical diagnosis of mild to moderate dementia
- Were diagnosed within the past 2 years
- Speak and understand English
- Are able to give informed consent
- Have internet access at home
- Are part of a caregiver-participant pair (dyad)
You are eligible to participate if you are a caregiver and you:
- Are an informal caregiver (family member or friend)
- Provide at least 30 hours of care per week to a person living with dementia
- Speak and understand English
- Are able to give informed consent
- Can participate in a home setup session and follow-up interview
The aim of this study is to develop a large, ethically sources, and diverse database of voice recordings to determine whether voice has biomarkers for particular disease categories, including neurological and neurodevelopmental conditions. The data that is collected will be used to develop a full open-access database to fuel artificial intelligence research related to voice.
Our study titled "Investigating the Role of Quantitative Susceptibility Mapping and Oxygen Extraction Fraction as Advanced Neuroimaging Biomarkers in Alzheimer's Disease" aims to develop non-invasive diagnostic biomarkers for Alzheimer's Disease (AD). We focus on evaluating the potential of QSM and OEF to differentiate between AD, Mild Cognitive Impairment (MCI), and Cognitively Unimpaired populations and to predict amyloid and tau pathology, using a Systems Biology approach. Leveraging the McGill University's TRIAD cohort, the study utilizes advanced imaging and machine learning to predict amyloid and tau presence, which could transform AD diagnostics and treatment. Methodologically, it involves preprocessing neuroimaging data and employing machine learning classifiers to analyze these features. The anticipated outcomes include validating QSM and OEF as non-invasive biomarkers for AD, establishing their correlation with amyloid and tau proteins, and developing predictive models for clinical decision-making, potentially resulting in significant advancements in AD diagnostics.
Are a member of the TRIAD cohort at McGill University, falling within one of the following categories: young control, cognitively unimpaired, mild cognitive impairment, or Alzheimer's Disease.
Are willing and able to undergo advanced neuroimaging techniques including MRI and PET without contraindications.
Have not had any significant neurological conditions (other than AD for the AD group) that might interfere with the results of the study.
Have no metal implants, devices, or other conditions that may contraindicate or distort MRI imaging.
Are not currently participating in other clinical trials or studies that involve interventions which might interfere with the results of this study.
Are able and willing to provide informed consent for participation in the study or have a legally authorized representative who can do so.
Do not have a history of substance abuse or other conditions that might confound the imaging and cognitive data.
Have not undergone any significant head trauma or surgery in the past 6 months.
Are not pregnant or planning to become pregnant during the duration of the study.
Are willing to comply with all study-related procedures, imaging sessions, and follow-up evaluations.
Ability to speak English and French
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