DIPHDEM: Digital Phenotyping for Changes in Activity at the End of Life in People With Dementia
Study Details
Study Description
Brief Summary
Background:
Almost 90% of people with dementia develop serious symptoms such as apathy, agitation, pain, and sleep disturbances. Movement and participation in daily activities also decrease dramatically over time. Traditional measures for these symptoms are usually in the form of a questionnaire and are not very accurate. Technology, such as a smartwatch, can be an effective tool for complementing traditional measures. Currently, there are few studies which look at activity and symptom measurements at the end-of-life. This makes results from this study extremely valuable for future care decisions, especially for people which may not be able to communicate their needs during the end-of-life period.
Method/Design:
DIgital PHenotyping in DEMentia (DIPH.DEM), a 3-year cross-sectional observational study (N=50), will look at activities, apathy, agitation, and sleep disturbances using sensing technologies to monitor participants at the end of life. The objective of the study is to use a smartwatch and wireless radar (bedside) device (Somnofy), in addition to validated assessment tools to describe the activity patterns for patients with dementia at the end of life (baseline and every 6.months). We hypothesize that this will enable better estimation of time of death, facilitating discussion surrounding improvement of end-of-life interventions and directives.
Discussion:
The use of sensors (smartwatch and wireless beside device) can provide valuable knowledge on living and dying with dementia, improve end-of-life directives, and provide guidance for timely, appropriate interventions, including referral to palliative services.
Impact on society:
DIPH.DEM has the potential to enable more timely, precise, and quality care for people with dementia living at home, in nursing homes, and hospitals.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
About 90% of people with dementia develop behavioral and psychological symptoms such as agitation, depression and psychosis. In addition, their activity levels decrease over time. Traditional outcome measures can capture physical, mental and social activities of clinical conditions, but usually have low validity.The use of sensor technology in people with dementia is currently poorly validated. DIPH.DEM will examine whether digital tools such as a smartwatch and Somnofy (radar installation) can provide objective measurements of the patient's activities and symptoms throughout the nursing home/hospital stay, including the end of life phase. The participants are people with dementia, >64 years, who have lived in a nursing home for >1 year. A selection of traditional tools and sensor data is collected at baseline and every 6 months (7 days continuous monitoring). If the participant has a significant change in health status, we will begin with continuous sensor measurements until the end of life (up to 12 weeks). DIPH.DEM can provide valuable information on activity development and symptom presentation toward the end of life in people with dementia. Informal caregivers (usually a family member) will be included to assist with the outcome measures within the study. Participants will be recruited from the Health Region West Norway and Bergen Municipality (sampling method is by invitation to volunteer). All consent procedures will be developed in accordance with Norwegian law.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Participants Persons with dementia |
Other: No intervention
The study is observational and will not include any specific interventions other than the regular care practice that the participants receive from their care providers. The study will use a wrist-mounted smartwatch for monitoring. Previous studies show acceptability toward wearable devices among persons with dementia; however, if the care staff recognize discomfort or distress caused by the devices, they will be immediately removed and the participant will drop-out.
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Outcome Measures
Primary Outcome Measures
- Edmonton Symptom Assessment System (ESAS) [Baseline and every 6.months (up to one year)]
Symptom assessment for palliative care period and the end of life period, with added items: death rattle, dyspnea, sleep disturbances, emesis.
- Activities of Daily Living (ADL) [Baseline and every 6.months (up to one year)]
Personal functional daily activities such as toileting, eating, self-care, movement/ambulation, transfers, bathing.
- Digital biomarker estimations for apathy, agitation, pain, and sleep disturbances [Baseline and every 6.months (up to one year), continuous up to 12 weeks if a serious health event occurs]
Estimation of activity changes and selected behavioral disturbances resulting from the combined digital phenotype modeling
Secondary Outcome Measures
- Neuropsychiatric Inventory - Nursing Home Version (NPI-NH) [Baseline and every 6.months (up to one year)]
Validated in Norwegian nursing homes, measuring symptoms of behavioral and psychological symptoms of dementia (BPSD) such as: apathy, agitation, depression, anxiety, sleep disturbance, and appetite/eating.
- Mobilization, Observation, Behavioral, Intensity Dementia (MOBID-2) [Baseline and every 6.months (up to one year)]
Measurement of pain specific to a dementia population.
- InterRai-Palliative Care (InterRai-PC) [Baseline and every 6.months (up to one year)]
Oral health section only/specific of the InterRai-PC
- Digital secondary outcomes [Baseline and every 6.months (up to one year)]
Device-native scores for activity and sleep.
Other Outcome Measures
- Chart review [Baseline]
A medication list will be compiled according to the Anatomical Therapeutic Chemical classification (ATC codes) and the Defined Daily Dose (DDD) of regularly scheduled treatments, diagnosis and medical history will be reviewed.
- Mini-Mental-State Examination (MMSE) [Baseline]
Classification of disease, <20 (mild-severe dementia)
- Short Form of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) [Baseline]
Classification of disease and cognitive impairment
- Functional Assessment Staging Tool (FAST) [Baseline]
Staging of disease and associated with mortality risk measurement.
- General Medical Health Rating Scale (GMHR) [Baseline]
Mortality risk measure for general wellbeing.
- 4 A's Test for Delirium (4AT) [Baseline]
Distinction between dementia and delirium for inclusion to study.
- Clinical Frailty Scale (CFS) [Baseline]
Mortality risk measure for general wellbeing.
Eligibility Criteria
Criteria
Inclusion Criteria:
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People with dementia (Mini-Mental-State Examination (MMSE) <20 or have a likely diagnosis of dementia based on a medical review)
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Hospital (admitted for >3 days)
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Nursing home (where they have resided for >1 year)
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64 years old
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Score of <4 on the 4 A's Test for Delirium (4AT) will be required for inclusion (no delirium)
Exclusion Criteria:
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People without dementia or cognitive impairment
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People that are considered already in a health status emergency (< 6 weeks to live)
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People that have lived <1 year in the nursing home
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- University of Bergen
- Helse Vest
- Haukeland University Hospital
- Haraldsplass Deaconess Hospital
- Bergen Red Cross Nursing Home
Investigators
- Study Director: Bettina S Husebo, MD, PhD, University of Bergen, Center for Elderly and Nursing Home Medicine, Neuro-SysMed Center
- Principal Investigator: Monica Patrascu, PhD, Eng, University of Bergen, Center for Elderly and Nursing Home Medicine, Neuro-SysMed Center
- Study Chair: Lydia Boyle, MSc, DPT, University of Bergen, Center for Elderly and Nursing Home Medicine, Neuro-SysMed Center
Study Documents (Full-Text)
None provided.More Information
Publications
- Abbott KM, Bangerter LR, Humes S, Klumpp R, Van Haitsma K. "It's important, but...": Perceived Barriers and Situational Dependencies to Social Contact Preferences of Nursing Home Residents. Gerontologist. 2018 Nov 3;58(6):1126-1135. doi: 10.1093/geront/gnx109.
- Au-Yeung WM, Miller L, Beattie Z, May R, Cray HV, Kabelac Z, Katabi D, Kaye J, Vahia IV. Monitoring Behaviors of Patients With Late-Stage Dementia Using Passive Environmental Sensing Approaches: A Case Series. Am J Geriatr Psychiatry. 2022 Jan;30(1):1-11. doi: 10.1016/j.jagp.2021.04.008. Epub 2021 Apr 22.
- Browne B, Kupeli N, Moore KJ, Sampson EL, Davies N. Defining end of life in dementia: A systematic review. Palliat Med. 2021 Dec;35(10):1733-1746. doi: 10.1177/02692163211025457. Epub 2021 Jun 17.
- Evensen S, Hylen Ranhoff A, Lydersen S, Saltvedt I. The delirium screening tool 4AT in routine clinical practice: prediction of mortality, sensitivity and specificity. Eur Geriatr Med. 2021 Aug;12(4):793-800. doi: 10.1007/s41999-021-00489-1. Epub 2021 Apr 4.
- Faeo SE, Husebo BS, Bruvik FK, Tranvag O. "We live as good a life as we can, in the situation we're in" - the significance of the home as perceived by persons with dementia. BMC Geriatr. 2019 Jun 6;19(1):158. doi: 10.1186/s12877-019-1171-6.
- Hui D, Bruera E. The Edmonton Symptom Assessment System 25 Years Later: Past, Present, and Future Developments. J Pain Symptom Manage. 2017 Mar;53(3):630-643. doi: 10.1016/j.jpainsymman.2016.10.370. Epub 2016 Dec 29.
- Husebo BS, Heintz HL, Berge LI, Owoyemi P, Rahman AT, Vahia IV. Sensing Technology to Monitor Behavioral and Psychological Symptoms and to Assess Treatment Response in People With Dementia. A Systematic Review. Front Pharmacol. 2020 Feb 4;10:1699. doi: 10.3389/fphar.2019.01699. eCollection 2019. Erratum In: Front Pharmacol. 2020 Mar 06;11:254.
- Husebo BS, Ostelo R, Strand LI. The MOBID-2 pain scale: reliability and responsiveness to pain in patients with dementia. Eur J Pain. 2014 Nov;18(10):1419-30. doi: 10.1002/ejp.507. Epub 2014 May 5.
- Johansen RH, Olsen K, Bergh S, Benth JS, Selbaek G, Helvik AS. Course of activities of daily living in nursing home residents with dementia from admission to 36-month follow-up. BMC Geriatr. 2020 Nov 20;20(1):488. doi: 10.1186/s12877-020-01877-1.
- Jorm AF. The Informant Questionnaire on cognitive decline in the elderly (IQCODE): a review. Int Psychogeriatr. 2004 Sep;16(3):275-93. doi: 10.1017/s1041610204000390.
- Lyketsos CG, Galik E, Steele C, Steinberg M, Rosenblatt A, Warren A, Sheppard JM, Baker A, Brandt J. The General Medical Health Rating: a bedside global rating of medical comorbidity in patients with dementia. J Am Geriatr Soc. 1999 Apr;47(4):487-91. doi: 10.1111/j.1532-5415.1999.tb07245.x.
- Park C, Mishra R, Golledge J, Najafi B. Digital Biomarkers of Physical Frailty and Frailty Phenotypes Using Sensor-Based Physical Activity and Machine Learning. Sensors (Basel). 2021 Aug 5;21(16):5289. doi: 10.3390/s21165289.
- Puaschitz NG, Jacobsen FF, Mannseth J, Angeles RC, Berge LI, Gedde MH, Husebo BS. Factors associated with access to assistive technology and telecare in home-dwelling people with dementia: baseline data from the LIVE@Home.Path trial. BMC Med Inform Decis Mak. 2021 Sep 15;21(1):264. doi: 10.1186/s12911-021-01627-2.
- Reisberg B. Functional assessment staging (FAST). Psychopharmacol Bull. 1988;24(4):653-9. No abstract available.
- Sallnow L, Smith R, Ahmedzai SH, Bhadelia A, Chamberlain C, Cong Y, Doble B, Dullie L, Durie R, Finkelstein EA, Guglani S, Hodson M, Husebo BS, Kellehear A, Kitzinger C, Knaul FM, Murray SA, Neuberger J, O'Mahony S, Rajagopal MR, Russell S, Sase E, Sleeman KE, Solomon S, Taylor R, Tutu van Furth M, Wyatt K; Lancet Commission on the Value of Death. Report of the Lancet Commission on the Value of Death: bringing death back into life. Lancet. 2022 Feb 26;399(10327):837-884. doi: 10.1016/S0140-6736(21)02314-X. Epub 2022 Feb 1. No abstract available.
- Sandvik RK, Selbaek G, Bergh S, Aarsland D, Husebo BS. Signs of Imminent Dying and Change in Symptom Intensity During Pharmacological Treatment in Dying Nursing Home Patients: A Prospective Trajectory Study. J Am Med Dir Assoc. 2016 Sep 1;17(9):821-7. doi: 10.1016/j.jamda.2016.05.006. Epub 2016 Jun 16.
- Schuurmans AAT, de Looff P, Nijhof KS, Rosada C, Scholte RHJ, Popma A, Otten R. Validity of the Empatica E4 Wristband to Measure Heart Rate Variability (HRV) Parameters: a Comparison to Electrocardiography (ECG). J Med Syst. 2020 Sep 23;44(11):190. doi: 10.1007/s10916-020-01648-w.
- Selbaek G, Kirkevold O, Sommer OH, Engedal K. The reliability and validity of the Norwegian version of the Neuropsychiatric Inventory, nursing home version (NPI-NH). Int Psychogeriatr. 2008 Apr;20(2):375-82. doi: 10.1017/S1041610207005601. Epub 2007 Jun 11.
- Taylor-Rowan M, Nafisi S, Owen R, Duffy R, Patel A, Burton JK, Quinn TJ. Informant-based screening tools for dementia: an overview of systematic reviews. Psychol Med. 2023 Jan;53(2):580-589. doi: 10.1017/S0033291721002002. Epub 2021 May 25.
- Thorpe O, McCabe E, Herrero EM, Doyle WO, Dillon A, Edge L, Flynn S, Mullen A, Davis A, Molamphy A, Kirwan A, Briggs R, Lavan AH, Shields D, McMahon G, Hennessy A, Kennedy U, Staunton P, Kidney E, Yeung SJ, Glynn D, Horgan F, Cunningham C, Romero-Ortuno R. Scoring the Clinical Frailty Scale in the Emergency Department: The Home FIRsT Experience. J Frailty Sarcopenia Falls. 2022 Jun 1;7(2):95-100. doi: 10.22540/JFSF-07-095. eCollection 2022 Jun.
- Toften S, Pallesen S, Hrozanova M, Moen F, Gronli J. Validation of sleep stage classification using non-contact radar technology and machine learning (Somnofy(R)). Sleep Med. 2020 Nov;75:54-61. doi: 10.1016/j.sleep.2020.02.022. Epub 2020 Mar 6.
- Torrado JC, Husebo BS, Allore HG, Erdal A, Faeo SE, Reithe H, Forsund E, Tzoulis C, Patrascu M. Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study. PLoS One. 2022 Oct 14;17(10):e0275747. doi: 10.1371/journal.pone.0275747. eCollection 2022.
- Vahia IV, Forester BP. Motion mapping in humans as a biomarker for psychiatric disorders. Neuropsychopharmacology. 2019 Jan;44(1):231-232. doi: 10.1038/s41386-018-0205-7. No abstract available.
- Vik-Mo AO, Giil LM, Borda MG, Ballard C, Aarsland D. The individual course of neuropsychiatric symptoms in people with Alzheimer's and Lewy body dementia: 12-year longitudinal cohort study. Br J Psychiatry. 2020 Jan;216(1):43-48. doi: 10.1192/bjp.2019.195.
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