An Explorative Investigation of the Effect of Naturalistic Light on Agitation-Associated Behavior in Nursing Home Residents With Dementia: A Pilot Study

Saidane, Hafed Amin; Rasmussen, Thomas Bruun; Andersen, Knud Damgaard; Iversen, Helle K.; West, Anders Sode

doi:10.1177/19375867221146154

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Additionally, minimising nighttime disturbances is vital for alleviating carer distress, thereby supporting patients to remain at home and avoid institutionalisation 34 . Our findings, along with current literature, suggest that modifiable parameters such as light exposure 35 and temperature 33 can be tailored for each PLwD to reduce the risk of agitation. Specifically, relying on natural light or adjusting artificial lighting to mimic natural light could improve light quality and alleviate agitation symptoms 35 .…”

Section: Non-agitated 52%supporting

confidence: 65%

“…Our findings, along with current literature, suggest that modifiable parameters such as light exposure 35 and temperature 33 can be tailored for each PLwD to reduce the risk of agitation. Specifically, relying on natural light or adjusting artificial lighting to mimic natural light could improve light quality and alleviate agitation symptoms 35 . Furthermore, maintaining indoor temperatures within a moderate range 33 and avoiding significant fluctuations could enhance comfort and help mitigate agitation episodes.…”

Section: Non-agitated 52%supporting

confidence: 65%

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An Interpretable Machine Learning Tool for In-Home Screening of Agitation Episodes in People Living with Dementia

Bafaloukou,

Schalkamp,

Fletcher-Lloyd

et al. 2024

Preprint

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BackgroundAgitation affects around 30% of people living with dementia (PLwD), increasing carer burden and straining care services. Agitation screening typically relies on subjective clinical scales and direct patient observation, which are resource-intensive and challenging to incorporate into routine care. Clinical applicability of data-driven methods for agitation screening is limited by constraints such as short observational periods, data granularity, and lack of interpretability and generalisability. Current interventions for agitation are primarily medication-based, which may lead to severe side effects and lack personalisation. Understanding how real-world factors affect agitation within home settings offers a promising avenue towards identifying potential personalised non-pharmacological interventions.MethodsWe used longitudinal data (32,896 person-days from n=63 PLwD) collected using in-home monitoring devices. Employing machine learning techniques, we developed a screening tool to determine the weekly risk of agitation. We incorporated a traffic-light system for risk stratification to aid clinical decision-making and employed the SHapley Additive exPlanations (SHAP) framework to increase interpretability. We designed an interactive tool that enables the exploration of personalised non-pharmacological interventions, such as modifying ambient light and temperature.ResultsLight Gradient-boosting Machine (LightGBM) achieved the highest performance in identifying agitation with a sensitivity of 71.32±7.38% and specificity of 75.28%. Implementing the traffic-light system for risk stratification increased specificity by 15% and improved all metrics. Significant contributors to agitation included low nocturnal respiratory rate, heightened alertness during sleep, and increased indoor illuminance, as revealed by statistical and feature importance analysis. Using our interactive tool, we identified that adjusting indoor lighting levels and temperature were promising and feasible interventions within our cohort.ConclusionsOur interpretable framework for agitation screening, developed using data from a dementia care study, showcases significant clinical value. The accompanying interactive interface allows for thein-silicosimulation of non-pharmacological interventions, facilitating the design of personalised interventions that can improve in-home dementia care.

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Section: Non-agitated 52%supporting

confidence: 65%

Section: Non-agitated 52%supporting

confidence: 65%

An Interpretable Machine Learning Tool for In-Home Screening of Agitation Episodes in People Living with Dementia

Bafaloukou,

Schalkamp,

Fletcher-Lloyd

et al. 2024

Preprint

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Examining the Relationships Between Indoor Environmental Quality Parameters Pertaining to Light, Noise, Temperature, and Humidity and the Behavioral and Psychological Symptoms of People Living With Dementia: Scoping Review

Au-Yeung,

Miller,

et al. 2024

Interact J Med Res

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Background A common challenge for individuals caring for people with Alzheimer disease and related dementias is managing the behavioral and psychological symptoms of dementia (BPSD). Effective management of BPSD will increase the quality of life of people living with dementia, lessen caregivers’ burden, and lower health care cost. Objective In this review, we seek to (1) examine how indoor environmental quality parameters pertaining to light, noise, temperature, and humidity are associated with BPSD and how controlling these parameters can help manage these symptoms and (2) identify the current state of knowledge in this area, current gaps in the research, and potential future directions. Methods Searches were conducted in the CINAHL, Embase, MEDLINE, and PsycINFO databases for papers published from January 2007 to February 2024. We searched for studies examining the relationship between indoor environmental quality parameters pertaining to light, noise, temperature, and humidity and BPSD. Results A total of 3123 papers were identified in the original search in October 2020. After an additional 2 searches and screening, 38 (0.69%) of the 5476 papers were included. Among the included papers, light was the most studied environmental factor (34/38, 89%), while there were fewer studies (from 5/38, 13% to 11/38, 29%) examining the relationships between other environmental factors and BPSD. Of the 38 studies, 8 (21%) examined multiple indoor environmental quality parameters. Subjective data were the only source of environmental assessments in 6 (16%) of the 38 studies. The findings regarding the relationship between agitation and light therapy are conflicted, while the studies that examined the relationship between BPSD and temperature or humidity are all observational. The results suggest that when the environmental factors are deemed overstimulating or understimulating for an individual with dementia, the behavioral symptoms tend to be exacerbated. Conclusions The findings of this scoping review may inform the design of long-term care units and older adult housing to support aging in place. More research is still needed to better understand the relationship between indoor environmental quality parameters and BPSD, and there is a need for more objective measurements of both the indoor environmental quality parameters and behavioral symptoms. One future direction is to incorporate objective sensing and advanced computational methods in real-time assessments to initiate just-in-time environmental interventions. Better management of BPSD will benefit patients, caregivers, and the health care system.

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Evaluating the Impact of a Daylight-Simulating Luminaire on Mood, Agitation, Rest-Activity Patterns, and Social Well-Being Parameters in a Care Home for People With Dementia: Cohort Study

Turley,

Rafferty,

Bond

et al. 2024

JMIR Mhealth Uhealth

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Background Living with a diagnosis of dementia can involve managing certain behavioral and psychological symptoms. Alongside cognitive decline, this cohort expresses a suppression in melatonin production which can negatively influence their alignment of sleep or wake timings with the 24 hour day and night cycle. As a result, their circadian rhythms become disrupted. Since daylight has the capacity to stimulate the circadian rhythm and humans spend approximately 90% of their time indoors, research has shifted toward the use of indoor lighting to achieve this same effect. This type of lighting is programmed in a daylight-simulating manner; mimicking the spectral changes of the sun throughout the day. As such, this paper focuses on the use of a dynamic lighting and sensing technology used to support the circadian rhythm, behavioral and psychological symptoms, and well-being of people living with dementia. Objective This study aimed to understand how dynamic lighting, as opposed to static lighting, may impact the well-being of those who are living with dementia. Methods An ethically approved trial was conducted within a care home for people with dementia. Data were collected in both quantitative and qualitative formats using environmentally deployed radar sensing technology and the validated QUALIDEM (Quality of Life for People With Dementia) well-being scale, respectively. An initial 4 weeks of static baseline lighting was used before switching out for 12 weeks of dynamic lighting. Metrics were collected for 11 participants on mood, social interactions, agitation, sense of feeling, and sleep and rest-activity over a period of 16 weeks. Results Dynamic lighting showed significant improvement with a moderate effect size in well-being parameters including positive affect (P=.03), social isolation (P=.048), and feeling at home (P=.047) after 5‐10 weeks of dynamic lighting exposure. The results also highlight statistically significant improvements in rest-activity–related parameters of interdaily stability (P<.001), intradaily variation (P<.001), and relative amplitude (P=.03) from baseline to weeks 5‐10, with the effect propagating for interdaily stability at weeks 10‐16 as well (P<.001). Nonsignificant improvements are also noted for sleep metrics with a small effect size; however, the affect in agitation does not reflect this improvement. Conclusions Dynamic lighting has the potential to support well-being in dementia, with seemingly stronger influence in earlier weeks where the dynamic lighting initially follows the static lighting contrast, before proceeding to aggregate as marginal gains over time. Future longitudinal studies are recommended to assess the additional impact that varying daylight availability throughout the year may have on the measured parameters.

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An Explorative Investigation of the Effect of Naturalistic Light on Agitation-Associated Behavior in Nursing Home Residents With Dementia: A Pilot Study

Cited by 4 publications

References 18 publications

An Interpretable Machine Learning Tool for In-Home Screening of Agitation Episodes in People Living with Dementia

An Interpretable Machine Learning Tool for In-Home Screening of Agitation Episodes in People Living with Dementia

Examining the Relationships Between Indoor Environmental Quality Parameters Pertaining to Light, Noise, Temperature, and Humidity and the Behavioral and Psychological Symptoms of People Living With Dementia: Scoping Review

Evaluating the Impact of a Daylight-Simulating Luminaire on Mood, Agitation, Rest-Activity Patterns, and Social Well-Being Parameters in a Care Home for People With Dementia: Cohort Study

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