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Reminiscentiebenadering verbetert kwaliteit van leven mensen met dementie

Radio Remember

In de loop van het leven wordt muziek voor de meeste mensen een drager van herinneringen en emoties. In de jeugd en vroege volwassenheid ontwikkelen we onze persoonlijke muzieksmaak. De muziek uit die tijd blijft ons het beste bij. Voor mensen met dementie, meestal 80 plussers, is dat ruim zestig jaar geleden. Daarom maakten de lectoraten Psychogeriatrie en Informatie, Technologie en Samenleving, in samenwerking met muziektherapeut Machgiel Bakker, een online muziekstation dat muziek uit die periode draait: Radio Remember. Een station om naar te luisteren, maar ook om in te zetten als psychosociale interventie om de kwaliteit van leven van mensen met dementie te verbeteren. In dit artikel wordt verslag gedaan van de eerste ervaringen en worden de volgende stappen van het project beschreven.

‘The Chitchatters’: a leisure activity for people with dementia to stimulate social interaction

Purpose Worldwide, there are 30 million people with dementia (PWD) in 2009 and 100 million in 2050, respectively.These numbers show the need for a change in care for PWD. Leisure is one of these care aspects. Leisure activities can support PWD in several ways: meeting basic needs, providing comfort and social interaction, and reducing boredom, agitation, and isolation. An exemplary activity targeted at meeting these needs is ‘De Klessebessers (KB)’ (The Chitchatters), which aims to stimulate social interaction among PWD and provide comfort with supporting technology. This is innovative since technology for PWD generally concentrates on safety and monitoring activities. The activity comprises a radio, television, telephone, and treasure box. Method This study’s focus follows from the original aim of the KB-designers; to stimulate social interaction. In a nursing home and day care centre, the KB game was played with different groups of PWD (n=21: 12 females, 9 males, mean MMSE=17, range 3-28). In the morning KB (with technology), and in the afternoon an activity called ‘Questiongame’ (without technology) were played for 45 minutes. These activities were played twice in a two-month period, and outcomes were compared in terms of impact on social interaction. Group sizes ranged from 3 to 8 PWD assisted by 1 or 2 activity therapists. Two researchers observed the players during the activity with the Oshkosh Social Behavior Coding (OSBC) scale, which encompasses both verbal and nonverbal social and nonsocial behaviour. These behaviours can have a person-initiated and otherinitiated character (quantitative study). A total of 6 activity therapists were interviewed on the KB afterwards (qualitative study). Results & Discussion The quantitative results showed significantly higher scores for KB for the total of social interaction compared to Questiongame. Most of the behaviour is other-initiated (activity therapist). PWD with a lower MMSE score showed more non-verbal behaviour. For PWD with a MMSE score below 7, there was no difference in social interaction between the two activities. According to the qualitative research, KB triggered more social interaction, since the movies and music were stimulating the players to initiate a conversation, to which other players responded. The results of this research correspond with earlier research, which concludes that leisure activities with technology can show positive results on well-being.

Dementia Enlightened?!

Light therapy for older persons with dementia is often administered with light boxes, even though indoor ambient light may more comfortably support the diverse lighting needs of this population. Our objective is to investigate the influence of indoor daylight and lighting on the health of older adults with dementia living in long-term care facilities. A systematic literature search was performed within PubMed, CINAHL, PsycINFO, Web of Science and Scopus databases. The included articles (n=37) were published from 1991 to 2020. These articles researched the influence of existing and changed indoor light conditions on health and resulted in seven categories of health outcomes. Although no conclusive evidence was found to support the ability of indoor light to decrease challenging behaviors or improve circadian rhythms, findings of two studies indicate that exposure to (very) cool light of moderate intensity diminished agitation. Promising effects of indoor light were to reduce depressive symptoms and facilitate spatial orientation. Furthermore, there were indications that indoor light improved one’s quality of life. Despite interventions with dynamic lighting having yielded little evidence of its efficacy, its potential has been insufficiently researched among this study population. This review provides a clear and comprehensive description of the impact of diverse indoor light conditions on the health of older adults with dementia living in long-term care facilities. Variation was seen in terms of research methods, (the description of) light conditions, and participants’ characteristics (types and severity of dementia), thus confounding the reliability of the findings. The authors recommend further research to corroborate the beneficial effects of indoor light on depression and to clarify its role in supporting everyday activities of this population. An implication for practice in long-term care facilities is raising the awareness of the increased lighting needs of aged residents. Original article at: https://doi.org/10.2147/CIA.S297865

Monitoring challenging behaviors in dementia with sensor technology

Purpose People with dementia (PwD) often present Behavioral and Psychological Symptoms of Dementia, which include agitation, apathy, and wandering amongst others, also known as challenging behaviors (CBs). These CBs worsen the quality of life (QoL) of the PwD and are a major source/reason of (increased) caregiver burden. The intricate nature of the symptoms implies that there is no “one size fits all solution”, and necessitates tailored approaches for both PwDs and caregivers. To timely prevent these behaviors assistive technology can be utilized to guide caregivers by enabling remote monitoring of contextual, environmental, and behavioral parameters, and subsequently alarming nurses on early-stage behavioral changes prior to the presentation of CBs. Eventually, the system should propose an intervention/action to prevent escalation. In turn, improvement in QoL for both caregivers and PwD living in nursing homes (NHs) is expected. In the current project “MOnitoring Onbegrepen Gedrag bij Dementie met sensortechnologie” (MOOD-Sense), we aim to develop such a monitoring system. The strengths of this new monitoring system lie in its ability to align with the individual needs of the PwD, utilization of a combination of wearables and ambient sensors to obtain contextual data, such as location or sound, and predict or monitor CBs individually rather than in groups, thus facilitating person-centered care, based on ontological reasoning. The project is divided into three parts, Toolbox A, B and C. Toolbox A focuses on obtaining insight in which behaviors are challenging according to nurses and how they are described. Previous studies utilize clinical terminology to describe or classify behavior, we aim to employ concrete descriptions of behavior that are observable and independent of clinical terminology, aligning with nurses who are often the first to notice behavior and can be operationalized such that it can also be aligned with sensor data. As a result, an ontology will be developed based on the data such that sensor data can be integrated into the same conceptual information that standardizes the communication in our monitoring system. Toolbox B focuses on translating data coming from various sensors into the concepts expressed in the ontology, and timely communicate situations of interest to the caregivers. In Toolbox C the focus is exploring interventions/actions employed in practice to prevent CBs. Method In Toolbox A we used a qualitative approach to collect descriptions of CBs. For this purpose, we employed focus groups (FGs) with nursing staff who provide daily care to PwD. In Toolbox B pilot studies were conducted. A set of experiments using sensors in NHs were performed. During each pilot, multiple PwD with CBs in NHs were monitored with both ambient and wearables sensors. The pilots were iteratively approached, which means that insights from previous pilot studies were used to improve consecutive pilot studies. Lastly, the elaboration of Toolbox C is ongoing. Results and Discussion Regarding Toolbox A four FGs were conducted during the period from January 2023 to May 2024. Each FG was comprised of four nurses (n = 16). From the FGs we gained insights into behavioral descriptions and the context of CBs. Although data analysis has to be performed yet, there are indications that changes preceding CBs can be observed, such as frowning or clenching fists for agitation or aggression. Further results will be available soon. Regarding Toolbox B a monitoring system, based on sensors, is developed iteratively (see Figure 1) and piloted in three consecutive NHs from January 2021 to December 2023. Each pilot was comprised of two PwD (n = 6). Analysis of sensor data is ongoing.

Sensor-based agitation prediction in institutionalized people with dementia A systematic review

Early detection of agitation in individuals with dementia can lead to timely interventions, preventing the worsening of situations and enhancing their quality of life. The emergence of multi-modal sensing and advances in artificial intelligence make it feasible to explore and apply technology for this goal. We conducted a literature review to understand the current technical developments and challenges of its integration in caregiving institutions. Our systematic review used the Pubmed and IEEE scientific databases, considering studies from 2017 onwards. We included studies focusing on linking sensor data to vocal and/or physical manifestations of agitation. Out of 1622 identified studies, 12 were selected for the final review. Analysis was conducted on study design, technology, decisional data, and data analytics. We identified a gap in the standardized semantic representation of both behavioral descriptions and system event generation configurations. This research highlighted initiatives that leverage existing information in a caregiver's routine, such as correlating electronic health records with sensor data. As predictive systems become more integrated into caregiving routines, false positive reduction needs to be addressed as those will discourage their adoption. Therefore, to ensure adaptive predictive capacity and personalized system re-configuration, we suggest future work to evaluate a framework that incorporates a human-in-the-loop approach for detecting and predicting agitation.