Publication Type

Journal Article

Version

publishedVersion

Publication Date

1-2022

Abstract

Background: Increasing need for nursing care has led to the increased burden on formal caregivers, with those in nursing homes having to deal with exhausting labor. Although research activities on the use of internet of things devices to support nursing care for older adults exist, there is limited evidence on the effectiveness of these interventions among formal caregivers in nursing homes. Objective: This study aims to investigate whether mat-type sleep state sensors for supporting nursing care can reduce the mental burden of formal caregivers in a nursing home. Methods: This was a quasi-experimental study at a nursing home in Tokyo, Japan. The study participants were formal caregivers who cared for residents in private rooms on the fourth and fifth floors of the nursing home. In the intervention group, formal caregivers took care of residents who used sleep state sensors on the fourth floor of the nursing home. The sleep state sensors were mat types and designed to detect body motion such as the frequency of toss and turning and to measure heartbeat and respiration. One sensor was placed on a bed in a private room. When body motion is detected, the information is instantly displayed on a monitor at a staff station. In addition, the mental condition of the formal caregivers was measured using a validated self-reported outcome measure-the Profile of Mood States (POMS), Short-Form, 2nd edition. Formal caregivers in both groups received the POMS at baseline, midpoint (week 4), and endpoint (week 8) to identify changes in these domains. The primary outcome was the difference in total mood disturbance (TMD) of the POMS at baseline and week 8. Results: Of the 22 eligible formal caregivers, 12 (intervention group) utilized sleep state sensors for 8 weeks. The remaining 10 formal caregivers (control group) provided nursing care as usual. As for the primary outcome of the difference between TMD at baseline and week 8, TMD in the intervention group improved by -3.67 versus 4.70 in the control group, resulting in a mean difference of -8.37 (95% CI -32.02 to 15.29; P=.48) in favor of the intervention. Conclusions: The present 8-week study showed that sleep state sensing for elderly residents might not be associated with reduced mental burdens on formal caregivers in nursing homes.

Keywords

long-term care, caregiver burden, nursing homes, aged, information technology, sensors

Discipline

Databases and Information Systems | Hospitality Administration and Management | Nursing

Research Areas

Software and Cyber-Physical Systems

Publication

JMIR Aging

Volume

5

Issue

1

First Page

1

Last Page

8

ISSN

2561-7605

Identifier

10.2196/19641

Publisher

JMIR Publications

Copyright Owner and License

Authors-CC-BY

Additional URL

https://doi.org/10.2196/19641

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