Co-designing with people with dementia (PwD) can uncover their needs and preferences, which have been often overlooked. It is difficult for PwD to understand designers and express themselves in a conventional co-design session. This study aims to evaluate the effects of involving PwD in design research on both PwD and the design process; to identify the trends of involving PwD in design research; to extract tools, recommendations, and limitations of involving PwD from reviewed studies to update the recommendations on how to co-design with PwD. A scoping review was carried out within the electronic databases PubMed and Scopus, and eight research questions were proposed, in order to gain specific knowledge on the involvement of PwD in design research. Twenty-six studies met the inclusion criteria, and 32 sessions were evaluated. Beneficial effects on both PwD and the design process were reported. The number of studies involving PwD in the moderate and severe stages of dementia has increased. Based on the review, an update of the existing tools and recommendations for codesigning with PwD is provided and a list of limitations of involving PwD is presented. The review shows that involving PwD in design research is beneficial for both the PwD and the design process, and there is a shift towards involving people who are in the moderate and severe stages of dementia. The authors propose that multidisciplinary meetings and case studies should be carried out to evaluate and refine the list of tools and recommendations as well as the list of limitations generated in this review.

Background: Since subjective cognitive decline (SCD) was standardized in 2014, many studies have investigated its features. However, the risk of SCD (plus) progressing to AD is much higher, and yet there have been few studies reporting the risk factors and neuropsychological assessment characteristics of SCD (plus). Objective: To characterize SCD (plus) by comparing it with normal control (NC), amnesic mild cognitive impairment (aMCI), and Alzheimer Disease (AD) regarding their demographics, lifestyle, family history of dementia, multimorbidity and the neuropsychological assessments. Methods: A total of 135 participants were recruited, including 23 NC, 30 SCD (plus), 45 aMCI and 37 AD. Descriptive statistics were provided. A logistic regression model was used to analyze the affecting factors of SCD (plus), and finally the Receiver Operating Characteristic (ROC) analysis was applied to distinguish between SCD (plus) and NC. Results: (1) SCD (plus) group was younger than both the aMCI group and AD group. It consisted of more participants with mental work and higher body mass index (BMI) than the AD group. (2) Scores of Auditory Verbal Learning Test-Immediate recall (AVLT-IR) and AVLT-Long delayed recall (AVLT-LR) decreased in the following order: NC→SCD (plus)→aMCI→AD. (3) The Area Under Curve (AUC) for discriminating SCD (plus) and NC group was from 0.673 to 0.838. Conclusion: Aging is an important risk factor of both NC progressing to SCD (plus), and SCD (plus) progressing to aMCI or AD. In addition to aging, lower education level and

Background: Non-pharmacological interventions for Behavioral and Psychological Symptoms of Dementia (BPSD) have been developed; however, a systematic review on the effectiveness of this type of intervention from a perspective of ergonomics is lacking. According to ergonomics, the capabilities of Persons with Dementia (PwD) should be considered in the interventions for the outcomes to be reliable. We aimed to systematically review the non-pharmacological interventions for BPSD in nursing home residents with an additional assessment criterion based on ergonomics, specifically, capability consideration. Methods: The electronic databases MEDLINE, EMBASE, and PsycINFO were searched for nonpharmacological interventions treating BPSD in nursing homes. The interventions were categorized according to the capabilities of PwD required to participate. Study quality was assessed by National Health and Medical Research Council (NHMRC) evidence hierarchy and the capability consideration.Results: Sixty-four clinical trials met the inclusion criteria; 41 trials reported a significant reduction in at least one BPSD symptom; 20 trials reported no significant reduction in BPSD symptoms; three trials reported adverse effects after the intervention. Interventions were categorized into sensory-, cognition-, and movementoriented. Capabilities of PwD were not considered in 28 trials, especially for sensory capabilities. Conclusions:The majority of the clinical trials reported a significant reduction in BPSD. The quality of evidence for nonpharmacological interventions in these trials is low due to the lack of capability consideration, data inhomogeneity, and inadequate study design and reporting. Future studies should focus on improving the quality of evidence by including capability consideration and examining if a relationship between capability consideration and effectiveness of non-pharmacological interventions exists.

Researchers have been exploring how to manage Behavioural and Psychological Symptoms of Dementia (BPSD) in a personalised way, meanwhile, assistive technologies have been developed to collect a variety of personal data. This urges more research in investigating the combination of: data collected by the care team, which are mainly qualitative; and data collected by assistive technologies, the majority of which are quantitative. Previous studies, however, have yet to explore if and how a combination of quantitative and qualitative data could facilitate the care team to better understand each resident with dementia in the nursing home context for personalised BPSD management. Guided by a Research through Design approach, a prototype for collecting and visualising the quantitative and qualitative data towards personalised BPSD management was developed together with the care team. Via developing this prototype, knowledge was gained in what types of data could be combined for personalised BPSD management in nursing homes, what are their values, how to collect and present them, and how to introduce them in the working routine of the care team for analysis. The main findings suggest that the types of data to be collected could be unique for each resident with dementia; the quantitative and qualitative data are of value to each other during data collection and analysis; data collection should be quick and standardised yet flexible for the care team; the overview page is vital for data presentation; and user scenarios could be created to nudge the care team to analyse the data at certain points of their working routine. In general, a combination of qualitative data and quantitative data could help the care team to discover more insights about each resident with dementia and thus improve the current practice of personalised BPSD management.

BACKGROUND Person-centered care is key to the wellbeing of people with dementia. A large quantity of personal data can be collected with the development of the Internet of Things, which has the potential to facilitate person-centered care for people with dementia. Yet, there are limited assistive technologies developed for this purpose, and the user acceptance for assistive technologies is low in nursing homes. Through a data-enabled design approach, a digital platform was developed for helping the care team to personalize the management of behavioral and psychological symptoms for people with dementia in nursing homes. OBJECTIVE This study aims to evaluate the digital platform from three aspects, in a real-life context with potential users. First, its technical feasibility in collecting sufficient data for pattern analysis; second, the types of insights and actions generated from the potential users by using it, if any; third, its perceived usefulness and its future improvements that potential users would like to see. METHODS The digital platform was deployed in a nursing home for seven weeks, and the data collected were first analyzed by the researchers for a technical feasibility check. The data were then visualized and presented to the potential users via the digital platform. The potential users were asked to analyze the visualizations and were interviewed on 1) the insights and actions generated, if any; 2) the usefulness of the digital platform and 3) what could be improved. RESULTS The data collected in the digital platform demonstrate its technical potential to reveal behavior patterns for PwD. The insights generated by the potential users were categorized into “client level”, “ward level” and “team level”. The actions taken by the potential users were classified into “investigation” and “implementation”. The user acceptance varied across potential users, and three aspects of improvements for the digital platform were identified. CONCLUSIONS This study provides the first evidence for the technical feasibility of the digital platform; besides, it offers future researchers some recommendations on how to integrate assistive technologies in the nursing home context from exploring the types of insights and actions identified, the varied perceived usefulness, and the areas of improvement for the digital platform.