Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication

NCT ID: NCT03795129

Last Updated: 2019-01-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

200 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-06-10

Study Completion Date

2019-02-28

Brief Summary

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Sleep related disorders are common in primary care practice. Sleep wear related data has not been utilized to improve sleep related communication between patients and providers. The study team is conducting a randomized study to improve physical-patient communication regarding sleep through a novel intervention based upon sleep wear and the SleeplifeĀ® app.

Detailed Description

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Based on a National US survey in 2012, 69% adults track at least one health indicator using either a tracking device or some other means. The main health indicators tracked were diet, weight, and exercise. Although not as extensive as the above health indicators, certain studies also looked at sleep indicators through the trackers to support validity of their use. Based on the study team's literature review, none of the studies looked at an intervention designed to utilize data-trackers-based data to improve physician-patient communication regarding sleep.

Commercially available and inexpensive exercise, fitness and sleep trackers are broadly available and consumer use is growing rapidly. Industry analysts estimate that over 30 million Americans have access to their sleep tracking data (e.g. Fitbit. Jawbone). Physicians seldom use patient-generated (i.e. subjective) sleep data (e.g. sleep diaries) and have been slow to integrate objective sleep data collected from commercial sleep trackers. Two commercial sleep trackers have been validated by independent testing. The National Sleep Foundation (NSF) has led recent efforts to establish normative data (i.e. appropriate ranges) for sleep duration and sleep quality. NSF, together with the Consumer Electronics Association (now Consumer Technology Association), has established a work-group involving over 40 sleep tracking technology companies which is working to standardize sleep tracking data collection and reporting. Finally, NSF has developed a tool ("SleepLife") that translates data retrieved from all commercially available sleep trackers into a personal sleep tracking record. This product has been tested rigorously for two years and publicly released in January 2016. These developments present the timely opportunity to test a new paradigm for patient and physician communication using objective patient data (sleep).

The study team will utilize a combination of observational and interventional study designs to achieve study objectives.

Conditions

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Insomnia

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

This is a cluster randomized trial that is randomized at the clinic level.
Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

NONE

Masking will not occur.

Study Groups

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SleepLife Application w/FitBit

Subject receives a FitBit. Subjects receive access to the SleepLife Application. Subjects receive training and assistance setting up use and access to the SleepLife Application.

Subject physicians will receive subject sleep data. Subject and physicians have the option of messaging each other through the SleepLife application.

Group Type EXPERIMENTAL

SleepLife Application w/FitBit

Intervention Type BEHAVIORAL

Subjects receive a FitBit. Subjects receive access to the SleepLife Application. Subjects receive training and assistance setting up use and access to the SleepLife Application.

Subjects' physicians will receive subject sleep data. Subjects and physicians have the option of messaging each other through the SleepLife application.

FitBit w/Minimal to No SleepLife App.

Subjects will receive a FitBit Subjects will be told about the SleepLife Application (but not be shown how to access it).

Subjects will receive no training with regard to how to access SleepLife Application.

Subjects' physicians will receive no subject sleep data.

Group Type ACTIVE_COMPARATOR

FitBit w/Minimal to No SleepLife App.

Intervention Type BEHAVIORAL

Subjects will receive a FitBit. Subjects will be told about the SleepLife Application (but not be shown how to access it).

Subjects will receive no training with regard to how to access SleepLife Application.

Subjects' physicians will receive no subject sleep data.

Interventions

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SleepLife Application w/FitBit

Subjects receive a FitBit. Subjects receive access to the SleepLife Application. Subjects receive training and assistance setting up use and access to the SleepLife Application.

Subjects' physicians will receive subject sleep data. Subjects and physicians have the option of messaging each other through the SleepLife application.

Intervention Type BEHAVIORAL

FitBit w/Minimal to No SleepLife App.

Subjects will receive a FitBit. Subjects will be told about the SleepLife Application (but not be shown how to access it).

Subjects will receive no training with regard to how to access SleepLife Application.

Subjects' physicians will receive no subject sleep data.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

1. 18 and older
2. Have insomnia as identified by electronic record and/or a validated questionnaire
3. Prescription medication for insomnia with International Classification of Disease (ICD) codes: 327.\*, 780.5\*, 347.\*; icd-10's G47\* and medications: Ambien (zolpidem), Belsomra (suvorexant), Butisol (butabarbital), Doral (quazepam), Edluar (zolpidem), Estazolam, Flurazepam, Halcion (triazolam), Hetlioz (tasimelteon), Intermezzo (zolpidem), Lunesta (eszopiclone), Restoril (temazepam), Rozerem (ramelteon), Seconal (secobarbital), Silenor (doxepin), Sonata (zaleplon), and Zolpimist (zolpidem)

3\. English speaking 4. Consentable in-person 5. Have access to a telephone with smart phone capabilities. (iOS/Android)

Exclusion Criteria

1. Not English speaking
2. Have ischemic or hemorrhagic cerebrovascular disease affecting collection of study outcomes (via ICD codes I6\*, 43\*)
3. History of dementia (via ICD codes F0\*, 290\*)
4. History of Bipolar/Schizophrenia/Depression (via ICD codes F2\*, F31\*, 296\*, 295\*)
5. History of alcohol or substance abuse (via ICD codes F1\*, 304\*, 303\*)
6. Incarcerated/Long Term Care (LTC)
7. Unable to complete study questionnaires due to hearing loss or blindness
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Merck Sharp & Dohme LLC

INDUSTRY

Sponsor Role collaborator

National Sleep Foundation

OTHER

Sponsor Role collaborator

Regenstrief Institute, Inc.

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Babar Khan, MD

Role: PRINCIPAL_INVESTIGATOR

Regenstrief Institute, Inc.

Locations

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Regenstrief Institute

Indianapolis, Indiana, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Jarod R Baker, MS

Role: CONTACT

317-274-9274

Bridget A Fultz

Role: CONTACT

317-274-9088

Facility Contacts

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Lori Rawlings

Role: primary

317-274-9052

References

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Fox S, & Duggan M. Tracking for health. Pew Research Center, Pew Internet and American Life Project. 2013.

Reference Type RESULT

Evenson KR, Goto MM, Furberg RD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015 Dec 18;12:159. doi: 10.1186/s12966-015-0314-1.

Reference Type RESULT
PMID: 26684758 (View on PubMed)

de Zambotti M, Baker FC, Willoughby AR, Godino JG, Wing D, Patrick K, Colrain IM. Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents. Physiol Behav. 2016 May 1;158:143-9. doi: 10.1016/j.physbeh.2016.03.006. Epub 2016 Mar 9.

Reference Type RESULT
PMID: 26969518 (View on PubMed)

de Zambotti M, Claudatos S, Inkelis S, Colrain IM, Baker FC. Evaluation of a consumer fitness-tracking device to assess sleep in adults. Chronobiol Int. 2015;32(7):1024-8. doi: 10.3109/07420528.2015.1054395.

Reference Type RESULT
PMID: 26158542 (View on PubMed)

Knutson KL, Phelan J, Paskow MJ, Roach A, Whiton K, Langer G, Hillygus DS, Mokrzycki M, Broughton WA, Chokroverty S, Lichstein KL, Weaver TE, Hirshkowitz M. The National Sleep Foundation's Sleep Health Index. Sleep Health. 2017 Aug;3(4):234-240. doi: 10.1016/j.sleh.2017.05.011. Epub 2017 Jun 20.

Reference Type RESULT
PMID: 28709508 (View on PubMed)

Hays, R.D., Davies, A.R., & Ware, J.E. (1987). Scoring the medical outcomes study patient satisfaction questionnaire: PSQ-III. MOS Memorandum.

Reference Type RESULT

Campbell C, Lockyer J, Laidlaw T, Macleod H. Assessment of a matched-pair instrument to examine doctor-patient communication skills in practising doctors. Med Educ. 2007 Feb;41(2):123-9. doi: 10.1111/j.1365-2929.2006.02657.x.

Reference Type RESULT
PMID: 17269944 (View on PubMed)

Charlson ME, Sax FL, MacKenzie CR, Fields SD, Braham RL, Douglas RG Jr. Resuscitation: how do we decide? A prospective study of physicians' preferences and the clinical course of hospitalized patients. JAMA. 1986 Mar 14;255(10):1316-22. doi: 10.1001/jama.255.10.1316.

Reference Type RESULT
PMID: 3944949 (View on PubMed)

KATZ S, FORD AB, MOSKOWITZ RW, JACKSON BA, JAFFE MW. STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. JAMA. 1963 Sep 21;185:914-9. doi: 10.1001/jama.1963.03060120024016. No abstract available.

Reference Type RESULT
PMID: 14044222 (View on PubMed)

Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969 Autumn;9(3):179-86. No abstract available.

Reference Type RESULT
PMID: 5349366 (View on PubMed)

D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993 Nov;32(5):382-7.

Reference Type RESULT
PMID: 8295545 (View on PubMed)

Herr KA, Garand L. Assessment and measurement of pain in older adults. Clin Geriatr Med. 2001 Aug;17(3):457-78, vi. doi: 10.1016/s0749-0690(05)70080-x.

Reference Type RESULT
PMID: 11459715 (View on PubMed)

Other Identifiers

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Merck - 34

Identifier Type: -

Identifier Source: org_study_id

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