RESUMO
Background: Dementia is a neurodegenerative disease resulting in the loss of cognitive and psychological functions. Artificial intelligence (AI) may help in detection and screening of dementia; however, little is known in this area. Objectives: The objective of this study was to identify and evaluate AI interventions for detection of dementia using motion data. Method: The review followed the framework proposed by O'Malley's and Joanna Briggs Institute methodological guidance for scoping reviews. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist for reporting the results. An information specialist performed a comprehensive search from the date of inception until November 2020, in five bibliographic databases: MEDLINE, EMBASE, Web of Science Core Collection, CINAHL, and IEEE Xplore. We included studies aimed at the deployment and testing or implementation of AI interventions using motion data for the detection of dementia among a diverse population, encompassing varying age, sex, gender, economic backgrounds, and ethnicity, extending to their health care providers across multiple health care settings. Studies were excluded if they focused on Parkinson's or Huntington's disease. Two independent reviewers screened the abstracts, titles, and then read the full-texts. Disagreements were resolved by consensus, and if this was not possible, the opinion of a third reviewer was sought. The reference lists of included studies were also screened. Results: After removing duplicates, 2,632 articles were obtained. After title and abstract screening and full-text screening, 839 articles were considered for categorization. The authors categorized the papers into six categories, and data extraction and synthesis was performed on 20 included papers from the motion tracking data category. The included studies assessed cognitive performance (n = 5, 25%); screened dementia and cognitive decline (n = 8, 40%); investigated visual behaviours (n = 4, 20%); and analyzed motor behaviors (n = 3, 15%). Conclusions: We presented evidence of AI systems being employed in the detection of dementia, showcasing the promising potential of motion tracking within this domain. Although some progress has been made in this field recently, there remain notable research gaps that require further exploration and investigation. Future endeavors need to compare AI interventions using motion data with traditional screening methods or other tech-enabled dementia detection mechanisms. Besides, future works should aim at understanding how gender and sex, and ethnic and cultural sensitivity can contribute to refining AI interventions, ensuring they are accessible, equitable, and beneficial across all society.
RESUMO
OBJECTIVES: We evaluated the willingness of Family Medicine residents to engage in SDM, before and after an educational intervention. METHODS: We delivered a lecture and a workshop for residents on implementing SDM in preventive health care. Before the lecture (T1), participants completed a measure of their willingness to engage in SDM. Six months later, participants completed the measure a second time (T2). RESULTS: At T1, 64 of 73 residents who attended the educational session completed incorpoRATE. Six months later, 44 of 64 participants completed the measure a second time (T2). The range of incorpoRATE sum scores at T1 was from 4.9 to 9.1 out of 10. Among the 44 participants who completed incorpoRATE at both time points, the mean scores were 7.0 ± 1.0 at T1 and 7.4 ± 1.0 at T2 (t = -2.833, p = 0.007, Cohen's D = 0.43). CONCLUSION: Among Family Medicine residents, the willingness to engage in SDM is highly variable. This suggests a lack of consensus in the mind of these residents about SDM. Although mean scores at T2 were significantly higher, we question the educational importance of this change. PRACTICE IMPLICATIONS: incorpoRATE is a promising measure for educators. Understanding how willing a particular physician audience is to undertake SDM, and which elements require attention, could be helpful in designing more targeted curricula. Further research is needed to understand how the perceived stakes of a clinical situation influence physician willingness to engage in SDM.
