Multidimensional assessment of challenging behaviors in advanced stages of dementia in nursing homes—The insideDEM framework

Abstract

Abstract Introduction Assessment of challenging behaviors in dementia is important for intervention selection. Here, we describe the technical and experimental setup and the feasibility of long‐term multidimensional behavior assessment of people with dementia living in nursing homes. Methods We conducted 4 weeks of multimodal sensor assessment together with real‐time observation of 17 residents with moderate to very severe dementia in two nursing care units. Nursing staff received extensive training on device handling and measurement procedures. Behavior of a subsample of eight participants was further recorded by videotaping during 4 weeks during day hours. Sensors were mounted on the participants' wrist and ankle and measured motion, rotation, as well as surrounding loudness level, light level, and air pressure. Results Participants were in moderate to severe stages of dementia. Almost 100% of participants exhibited relevant levels of challenging behaviors. Automated quality control detected 155 potential issues. But only 11% of the recordings have been influenced by noncompliance of the participants. Qualitative debriefing of staff members suggested that implementation of the technology and observation platform in the routine procedures of the nursing home units was feasible and identified a range of user‐ and hardware‐related implementation and handling challenges. Discussion Our results indicate that high‐quality behavior data from real‐world environments can be made available for the development of intelligent assistive systems and that the problem of noncompliance seems to be manageable. Currently, we train machine‐learning algorithms to detect episodes of challenging behaviors in the recorded sensor data.

Keywords

• Real‐world evidence
• Nursing care
• Neuropsychiatric symptoms
• Information and communication technology
• Sensor‐based assessment
• Video recording