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AIM: To learn from two jurisdictions with mature genomics-informed nursing policy infrastructure-the United States (US) and the United Kingdom (UK)-to inform policy development for genomics-informed oncology nursing practice and education in Canada. DESIGN: Comparative document and policy analysis drawing on the 3i + E framework. METHODS: We drew on the principles of a rapid review and identified academic literature, grey literature and nursing policy documents through a systematic search of two databases, a website search of national genomics nursing and oncology nursing organizations in the US and UK, and recommendations from subject matter experts on an international advisory committee. A total of 94 documents informed our analysis. RESULTS: We found several types of policy documents guiding genomics-informed nursing practice and education in the US and UK. These included position statements, policy advocacy briefs, competencies, scope and standards of practice and education and curriculum frameworks. Examples of drivers that influenced policy development included nurses' values in aligning with evidence and meeting public expectations, strong nurse leaders, policy networks and shifting healthcare and policy landscapes. CONCLUSION: Our analysis of nursing policy infrastructure in the US and UK provides a framework to guide policy recommendations to accelerate the integration of genomics into Canadian oncology nursing practice and education. IMPLICATIONS FOR THE PROFESSION: Findings can assist Canadian oncology nurses in developing nursing policy infrastructure that supports full participation in safe and equitable genomics-informed oncology nursing practice and education within an interprofessional context. IMPACT: This study informs Canadian policy development for genomics-informed oncology nursing education and practice. The experiences of other countries demonstrate that change is incremental, and investment from strong advocates and collaborators can accelerate the integration of genomics into nursing. Though this research focuses on oncology nursing, it may also inform other nursing practice contexts influenced by genomics.
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Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor symptoms such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP (REal-world Mobility Activities in Parkinson's disease), a human rater-labelled dataset collected in a home-like setting. It includes people with and without PD doing sit-to-stand transitions and turns in gait. These discrete activities are captured from periods of free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their activities are labelled as being "on" or "off" medications. Accelerometry from wrist-worn wearables and skeleton pose video data is included. We present an open dataset, where the data is coarsened to reduce re-identifiability, and a controlled dataset available on application which contains more refined data. A use-case for the data to estimate sit-to-stand speed and duration is illustrated.