ClinicalTrials.gg
RecruitingNCT07819409Updated Sep 17, 2026

Sleep Detection in Residents of Long-term Care Facilities

An observational study in Sleep Disturbance, sponsored by Eastern Switzerland University of Applied Sciences. Recruiting at 1 site in Switzerland. Per ClinicalTrials.gov, last updated 2026-09-17.

Sponsored by Eastern Switzerland University of Applied Sciences · Observational

From the registry’s dates

  • Started Aug 2025; still recruiting 1 year 2 months later.
Study type
Observational
Model
Other
Time perspective
Cross-sectional
Enrollment
52
Sex
All
01

Study summary

Sleep disorders are common among older people. People who suffer from sleep disorders typically have difficulty falling asleep, staying asleep, wake up early and do not get restful sleep.

Research on sleep disorders in humans is already underway. Previous research projects in humans have shown that sleep disorders have an impact on bodily functions and quality of life. Disruptions to the sleep-wake cycle can also affect memory. Previous research projects have examined the measurement differences between polysomnography, an overnight sleep measurement in a sleep laboratory, which is currently the gold standard, and various contactless sleep sensor systems. The measurement differences are minor to moderate. However, the investigators do not yet know how large the difference is between different days when using contactless sleep sensor systems in order to determine the accuracy of such devices for residents in retirement and nursing homes.

In this research project, the investigator are therefore investigating sleep variability over a period of 14 days in 52 residents of retirement and nursing homes in Switzerland in order to be able to assess the smallest detectable difference in sleep quality.

The investigators are conducting this research project in accordance with Swiss law. The investigators also comply with all internationally recognized guidelines. The responsible ethics committee has reviewed and approved the research project.

Read the detailed description

Insomnia is a common sleep problem among older adults, with an overall prevalence reported between 30% and 50% and an even higher value among those living in nursing homes. Symptoms such as difficulty in falling asleep, difficulty in maintaining sleep, early morning awakening and non-restorative sleep not only have an important impact on the functional status and quality of life in older adults, but disturbances of the sleep-wake cycle are also known to be associated with cognitive decline. Polysomnography (PSG) is the current gold standard measuring for sleep disturbances using a collection of surface electrodes, physiologic an sleep parameters (including brain dynamics of electroencephalography (EEG)) in a sleep laboratory overnight. However, a 24-hour sleep detection based on objective measurement in older adults is of importance because excessive daytime sleepiness, and excessive napping are associated with negative health outcomes such as accelerated cognitive decline. Furthermore, Canadian 24-hours movement guidelines recommend to detect movement behavior, with sleep as a movement behavior included, over a 24-hour time span. Contactless sleep technologies (CSTs) may offer a low-burden and feasible assessment to monitoring sleep over 24-hours in older adults. To date there are several CSTs available with differences in accuracy compared to PSG. However, little is known regarding smallest detectable difference based on test-retest analysis based on intraday variability to effectively test the accuracy of such devices in older adults living in long-term care facilities. The objective of this study is to evaluate the smallest detectable difference of sleep quality based on test-retest analysis of two CSTs: (i) the Withings Sleep Analyzer and (ii) the Sleepiz One+ hardware in older adults.

02

Conditions studied

  • Sleep Disturbance

Keywords

  • sleep detection
  • residents of long-term care facilities
  • interrater agreement
03

In context

Lead sponsor

Eastern Switzerland University of Applied Sciences is the lead sponsor of 9 studies on the registry; 4 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
Child (0–17), Adult (18–64), Older adult (65+)
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

Older Adults living in long-term care facilities without any neurocognitive disorder

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Signed
  • Older adults living in the long-term care facilities

Exclusion criteria

Exclusion Criteria:

  • Neurocognitive disorders based on Alzheimer's Disease, Parkinson's disease, Lewy body dementia or Mixed dementia according to patient record
Terms in these criteria, in plain language(1)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

05

Study design

Observational model
Other
Time perspective
Cross-sectional
Enrollment
52 participants (estimated)
Patient registry
No

Groups and cohorts

  • residents of long-term care facilities without any neurocognitive disorders

    residents of long-term care facilities without any neurocognitive disorders according to patient record

06

What researchers measure

Primary outcomes

  1. Total Sleep Time

    The time a person lying in bed actually sleeping

    Time frame: From enrollment to 14 days after

07

Study locations

1 of 1 sites recruiting
  • Easternswiss University of Applied Sciences
    Sankt Gallen, St.Gallen 9001, Switzerland
    Recruiting
08

References and documents

Publications

  • Lee T, Cho Y, Cha KS, Jung J, Cho J, Kim H, Kim D, Hong J, Lee D, Keum M, Kushida CA, Yoon IY, Kim JW. Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study. JMIR Mhealth Uhealth. 2023 Nov 2;11:e50983. doi: 10.2196/50983. PubMed 37917155 ↗
  • Oskarsdottir M, Islind AS, August E, Arnardottir ES, Patou F, Maier AM. Importance of Getting Enough Sleep and Daily Activity Data to Assess Variability: Longitudinal Observational Study. JMIR Form Res. 2022 Feb 22;6(2):e31807. doi: 10.2196/31807. PubMed 35191850 ↗
  • Perez-Pozuelo I, Zhai B, Palotti J, Mall R, Aupetit M, Garcia-Gomez JM, Taheri S, Guan Y, Fernandez-Luque L. The future of sleep health: a data-driven revolution in sleep science and medicine. NPJ Digit Med. 2020 Mar 23;3:42. doi: 10.1038/s41746-020-0244-4. eCollection 2020. PubMed 32219183 ↗
  • de Zambotti M, Menghini L, Grandner MA, Redline S, Zhang Y, Wallace ML, Buxton OM. Rigorous performance evaluation (previously, "validation") for informed use of new technologies for sleep health measurement. Sleep Health. 2022 Jun;8(3):263-269. doi: 10.1016/j.sleh.2022.02.006. Epub 2022 May 3. PubMed 35513978 ↗
  • G Ravindran KK, Della Monica C, Atzori G, Lambert D, Hassanin H, Revell V, Dijk DJ. Three Contactless Sleep Technologies Compared With Actigraphy and Polysomnography in a Heterogeneous Group of Older Men and Women in a Model of Mild Sleep Disturbance: Sleep Laboratory Study. JMIR Mhealth Uhealth. 2023 Oct 25;11:e46338. doi: 10.2196/46338. PubMed 37878360 ↗
  • Ross R, Chaput JP, Giangregorio LM, Janssen I, Saunders TJ, Kho ME, Poitras VJ, Tomasone JR, El-Kotob R, McLaughlin EC, Duggan M, Carrier J, Carson V, Chastin SF, Latimer-Cheung AE, Chulak-Bozzer T, Faulkner G, Flood SM, Gazendam MK, Healy GN, Katzmarzyk PT, Kennedy W, Lane KN, Lorbergs A, Maclaren K, Marr S, Powell KE, Rhodes RE, Ross-White A, Welsh F, Willumsen J, Tremblay MS. Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2020 Oct;45(10 (Suppl. 2)):S57-S102. doi: 10.1139/apnm-2020-0467. PubMed 33054332 ↗
  • Leng Y, Redline S, Stone KL, Ancoli-Israel S, Yaffe K. Objective napping, cognitive decline, and risk of cognitive impairment in older men. Alzheimers Dement. 2019 Aug;15(8):1039-1047. doi: 10.1016/j.jalz.2019.04.009. Epub 2019 Jun 18. PubMed 31227429 ↗
  • Owusu JT, Wennberg AMV, Holingue CB, Tzuang M, Abeson KD, Spira AP. Napping characteristics and cognitive performance in older adults. Int J Geriatr Psychiatry. 2019 Jan;34(1):87-96. doi: 10.1002/gps.4991. Epub 2018 Oct 12. PubMed 30311961 ↗
  • Li P, Gao L, Yu L, Zheng X, Ulsa MC, Yang HW, Gaba A, Yaffe K, Bennett DA, Buchman AS, Hu K, Leng Y. Daytime napping and Alzheimer's dementia: A potential bidirectional relationship. Alzheimers Dement. 2023 Jan;19(1):158-168. doi: 10.1002/alz.12636. Epub 2022 Mar 17. PubMed 35297533 ↗
  • Cross N, Terpening Z, Rogers NL, Duffy SL, Hickie IB, Lewis SJ, Naismith SL. Napping in older people 'at risk' of dementia: relationships with depression, cognition, medical burden and sleep quality. J Sleep Res. 2015 Oct;24(5):494-502. doi: 10.1111/jsr.12313. Epub 2015 Jun 21. PubMed 26096839 ↗
  • Marino M, Li Y, Rueschman MN, Winkelman JW, Ellenbogen JM, Solet JM, Dulin H, Berkman LF, Buxton OM. Measuring sleep: accuracy, sensitivity, and specificity of wrist actigraphy compared to polysomnography. Sleep. 2013 Nov 1;36(11):1747-55. doi: 10.5665/sleep.3142. PubMed 24179309 ↗
  • Winsky-Sommerer R, de Oliveira P, Loomis S, Wafford K, Dijk DJ, Gilmour G. Disturbances of sleep quality, timing and structure and their relationship with other neuropsychiatric symptoms in Alzheimer's disease and schizophrenia: Insights from studies in patient populations and animal models. Neurosci Biobehav Rev. 2019 Feb;97:112-137. doi: 10.1016/j.neubiorev.2018.09.027. Epub 2018 Oct 9. PubMed 30312626 ↗
  • Balouch S, Dijk DAD, Rusted J, Skene SS, Tabet N, Dijk DJ. Night-to-night variation in sleep associates with day-to-day variation in vigilance, cognition, memory, and behavioral problems in Alzheimer's disease. Alzheimers Dement (Amst). 2022 May 16;14(1):e12303. doi: 10.1002/dad2.12303. eCollection 2022. PubMed 35603140 ↗
  • Fung CH, Vitiello MV, Alessi CA, Kuchel GA; AGS/NIA Sleep Conference Planning Committee and Faculty. Report and Research Agenda of the American Geriatrics Society and National Institute on Aging Bedside-to-Bench Conference on Sleep, Circadian Rhythms, and Aging: New Avenues for Improving Brain Health, Physical Health, and Functioning. J Am Geriatr Soc. 2016 Dec;64(12):e238-e247. doi: 10.1111/jgs.14493. Epub 2016 Nov 14. PubMed 27858974 ↗
  • Ebben MR. Insomnia: Behavioral Treatment in the Elderly. Clin Geriatr Med. 2021 Aug;37(3):387-399. doi: 10.1016/j.cger.2021.04.002. Epub 2021 Jun 4. PubMed 34210445 ↗
  • Flaxer JM, Heyer A, Francois D. Evidenced-Based Review and Evaluation of Clinical Significance: Nonpharmacological and Pharmacological Treatment of Insomnia in the Elderly. Am J Geriatr Psychiatry. 2021 Jun;29(6):585-603. doi: 10.1016/j.jagp.2020.10.011. Epub 2020 Oct 27. PubMed 33218915 ↗
  • Samara MT, Huhn M, Chiocchia V, Schneider-Thoma J, Wiegand M, Salanti G, Leucht S. Efficacy, acceptability, and tolerability of all available treatments for insomnia in the elderly: a systematic review and network meta-analysis. Acta Psychiatr Scand. 2020 Jul;142(1):6-17. doi: 10.1111/acps.13201. Epub 2020 Jun 30. PubMed 32521042 ↗
  • Orhan FO, Tuncel D, Tas F, Demirci N, Ozer A, Karaaslan MF. Relationship between sleep quality and depression among elderly nursing home residents in Turkey. Sleep Breath. 2012 Dec;16(4):1059-67. doi: 10.1007/s11325-011-0601-2. Epub 2011 Nov 27. PubMed 22120045 ↗
  • Dopheide JA. Insomnia overview: epidemiology, pathophysiology, diagnosis and monitoring, and nonpharmacologic therapy. Am J Manag Care. 2020 Mar;26(4 Suppl):S76-S84. doi: 10.37765/ajmc.2020.42769. PubMed 32282177 ↗
  • Patel D, Steinberg J, Patel P. Insomnia in the Elderly: A Review. J Clin Sleep Med. 2018 Jun 15;14(6):1017-1024. doi: 10.5664/jcsm.7172. PubMed 29852897 ↗

Individual participant data

Plan to share: No

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Started Aug 2025 (actual). Primary completion is estimated for Feb 2027, 18 months after the start.

How these figures are worked out, and which studies are left out of them.

Registered
Sep 9, 2026
First posted
Sep 14, 2026
StartActual
Aug 28, 2025
Primary completionEst.
Feb 2027
CompletionEst.
Aug 2027
Last update
Sep 17, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Sep 17, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07819409
Lead sponsor
Eastern Switzerland University of Applied Sciences
Responsible party
Sponsor
First posted
Sep 14, 2026
Start date
Aug 28, 2025
Primary completion
Feb 2027 (estimated)
Completion
Aug 2027 (estimated)
Last update
Sep 17, 2026

Study contacts

Eling D de Bruin, Prof. Dr.
Contact
eling.debruin@ost.ch
+41 58 257 14 11
Andrea C Hausheer
Contact
andrea.hausheer@ost.ch
+41 58 257 14 77
Eling D de Bruin, Prof. Dr.
principal investigator · Eastern Swiss University of Applied Sciences, ETH Zruich

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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