InsomniaNCT03795129
Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication
A study testing SleepLife Application w/FitBit and FitBit w/Minimal to No SleepLife App. in people with Insomnia, run by Regenstrief Institute, Inc. at 1 site in United States.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Insomnia
- What is being tested?
- SleepLife Application w/FitBit and FitBit w/Minimal to No SleepLife App.
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 200 participants
- Where
- 1 siteUnited States
- Study dates
- 10 Jun 2018to 28 Feb 2019
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 18 and older
- Have insomnia as identified by electronic record and/or a validated questionnaire
- 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)
Who cannot join
- Not English speaking
- Have ischemic or hemorrhagic cerebrovascular disease affecting collection of study outcomes (via ICD codes I6*, 43*)
- History of dementia (via ICD codes F0*, 290*)
- History of Bipolar/Schizophrenia/Depression (via ICD codes F2*, F31*, 296*, 295*)
- History of alcohol or substance abuse (via ICD codes F1*, 304*, 303*)
- Incarcerated/Long Term Care (LTC)
- Unable to complete study questionnaires due to hearing loss or blindness
Trial locations and contacts
1 site in 1 country.
United States1 site, 1 recruiting
- Recruiting
Regenstrief Institute
Indianapolis, Indiana, 46202
Lori Rawlings, 317-274-9052, rawlingl@regenstrief.org
About this study
Official title: Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication Around Sleep Experience, Habits, and Behaviors
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 Sleeplife® app.
Read the detailed description
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
- Insomnia
- Being tested
- SleepLife Application w/FitBit, FitBit w/Minimal to No SleepLife App.
- Keywords
- Early awakening
- Medical subject headings
- Sleep Initiation and Maintenance Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
SleepLife Application w/FitBitBehavioural
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.Behavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| SleepLife Application w/FitBit | Experimental | 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. Receives: Behavioral: SleepLife Application w/FitBit |
| FitBit w/Minimal to No SleepLife App. | Active comparator | 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. Receives: Behavioral: FitBit w/Minimal to No SleepLife App. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of physicians using a commercially available sleep tracker assessed by the "Physician Satisfaction/Communication" questionnaire who saw an improvement in physician-patient dialogue regarding sleep and related behaviors and habits
For patient-physician communications from the physicians' end, the team will collect all scores, ranging from 1 to 5, for all the "Communication" questions in the "Physician Satisfaction/Communication" questionnaire. The scores will be summed up as the total communication score from physician, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the physician is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. We will use linear regression model, and select relevant variables using Bayesian information criterion (BIC) in a step-wise manner. The SleepLife app will be pulling time-to-sleep (TST), amount of time in minutes to sleep, number of awakenings greater than 5 minutes, and sleep efficiency.
Measured: Six Months
Number of patient-physician communicationdialog assessed by using a commercially available sleep tracker assessed by the "Patient Satisfaction" questionnaire.
For patient-physician communications from the patients' end, the team will collect all the scores, ranging from 1 to 5, for all the "Communication" questions in the "Patient Satisfaction" questionnaire. The scores will be summed up as the total communication score from the patients' end, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, the team will use generalized estimating equation (GEE) model with an identity link function, and the team will select relevant variables using QIC in a step-wise manner.
Measured: Six Months
Secondary outcomes (2)
Number of physician subjects with satisfaction with sleep counseling that improves when presented with objective patient sleep data.
For physicians' satisfactory score, the team will collect all the scores, ranging from 1 to 5, for all the "GS" questions in the "Physician Satisfaction/Communication" questionnaire. The scores will be summed up as the total physicians' satisfaction score, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the physician is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. The team will use linear regression model, and select relevant variables using BIC in a step-wise manner.
Measured: Six Months
Number of patients who feel that their communication with their physician has improved as a result of the program as measured by the "Patient Satisfaction" survey.
For patients' satisfaction, the team will collect all scores, ranging from 1 to 5, for all the "General Satisfaction" questions in the "Patient Satisfaction" questionnaire. These scores will be summed up as the total patients' satisfaction score for the treatment and interaction with the physician, as a result of the program. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, the team will use GEE model with an identity link function, and we will select relevant variables using QIC in a step-wise manner.
Measured: Six Months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jan 2019
- Study start10 Jun 2018
- Primary completion31 Dec 2018 (estimated)
- Study completion28 Feb 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (12)Papers the sponsor has linked to this study.
- Other trials for InsomniaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- This is a cluster randomized trial that is randomized at the clinic level.
- Masking
- None (open label)
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Regenstrief Institute, Inc.
- Sponsor type
- University, hospital or other
- Collaborators
- Merck Sharp & Dohme LLC, National Sleep Foundation
- Responsible party
- Sponsor
- Investigators
- Babar Khan, MD, Principal investigator, Regenstrief Institute, Inc.
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03795129
- Sponsor's protocol ID
- Merck - 34
- Status last verified
- Jan 2019
- First submitted
- 3 May 2018
- Last updated
- 7 Jan 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The Regenstrief research team will use Protected Health Information (PHI) to conduct this study. Data that does not identify the subject will be shared with Merck Sharp \& Dohme Corp. and the National Sleep Foundation. At this time, that is only the study visit day.
Publications
Fox S, & Duggan M. Tracking for health. Pew Research Center, Pew Internet and American Life Project. 2013.
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.
PubMed 26684758de 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.
PubMed 26969518de 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.
PubMed 26158542Knutson 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.
PubMed 28709508Hays, R.D., Davies, A.R., & Ware, J.E. (1987). Scoring the medical outcomes study patient satisfaction questionnaire: PSQ-III. MOS Memorandum.
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.
PubMed 17269944Charlson 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.
PubMed 3944949KATZ 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.
PubMed 14044222Lawton 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.
PubMed 5349366D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993 Nov;32(5):382-7.
PubMed 8295545Herr 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.
PubMed 11459715
Study at a glance
From the registry record, last updated by the sponsor on 7 Jan 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication Around Sleep Experience, Habits, and Behaviors
- ClinicalTrials.gov ID
- NCT03795129
- Acronym / sponsor ID
- Merck - 34
- Conditions
- Insomnia
- Keywords
- Early awakening
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Regenstrief Institute, Inc.University, hospital or other
- Collaborators
- Merck Sharp & Dohme LLC, National Sleep Foundation
- Study start
- 10 Jun 2018 (actual)
- Primary completion
- 31 Dec 2018 (estimated)
- Study completion
- 28 Feb 2019 (estimated)
- First posted
- 7 Jan 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 Sleeplife® app.
Detailed description
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- This is a cluster randomized trial that is randomized at the clinic level.
| Arm | Type | Receives |
|---|---|---|
| SleepLife Application w/FitBit | Experimental | Behavioral: SleepLife Application w/FitBitSubject 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. |
| FitBit w/Minimal to No SleepLife App. | Active comparator | 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 18 and older
- Have insomnia as identified by electronic record and/or a validated questionnaire
- 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)
Key exclusion criteria (7 listed)
- Not English speaking
- Have ischemic or hemorrhagic cerebrovascular disease affecting collection of study outcomes (via ICD codes I6*, 43*)
- History of dementia (via ICD codes F0*, 290*)
- History of Bipolar/Schizophrenia/Depression (via ICD codes F2*, F31*, 296*, 295*)
- History of alcohol or substance abuse (via ICD codes F1*, 304*, 303*)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| SleepLife Application w/FitBitSubjects 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. | Behavioural | SleepLife Application w/FitBit |
| 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. | Behavioural | FitBit w/Minimal to No SleepLife App. |
Primary outcome
Number of physicians using a commercially available sleep tracker assessed by the "Physician Satisfaction/Communication" questionnaire who saw an improvement in physician-patient dialogue regarding sleep and related behaviors and habits
Time frame: Six Months
For patient-physician communications from the physicians' end, the team will collect all scores, ranging from 1 to 5, for all the "Communication" questions in the "Physician Satisfaction/Communication" questionnaire. The scores will be summed up as the total communication score from physician, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the physician is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. We will use linear regression model, and select relevant variables using Bayesian information criterion (BIC) in a step-wise manner. The SleepLife app will be pulling time-to-sleep (TST), amount of time in minutes to sleep, number of awakenings greater than 5 minutes, and sleep efficiency.
Number of patient-physician communicationdialog assessed by using a commercially available sleep tracker assessed by the "Patient Satisfaction" questionnaire.
Time frame: Six Months
For patient-physician communications from the patients' end, the team will collect all the scores, ranging from 1 to 5, for all the "Communication" questions in the "Patient Satisfaction" questionnaire. The scores will be summed up as the total communication score from the patients' end, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, the team will use generalized estimating equation (GEE) model with an identity link function, and the team will select relevant variables using QIC in a step-wise manner.
2 secondary outcomes
Number of physician subjects with satisfaction with sleep counseling that improves when presented with objective patient sleep data.
Time frame: Six Months
Number of patients who feel that their communication with their physician has improved as a result of the program as measured by the "Patient Satisfaction" survey.
Time frame: Six Months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jan 2019.
- Results publicationFox S, & Duggan M. Tracking for health. Pew Research Center, Pew Internet and American Life Project. 2013.
- Results publication: PubMed 26684758Evenson 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.
- Results publication: PubMed 26969518de 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.
- Results publication: PubMed 26158542de 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.
- Results publication: PubMed 28709508Knutson 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.
- Results publicationHays, R.D., Davies, A.R., & Ware, J.E. (1987). Scoring the medical outcomes study patient satisfaction questionnaire: PSQ-III. MOS Memorandum.
- Results publication: PubMed 17269944Campbell 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.
- Results publication: PubMed 3944949Charlson 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.
- Results publication: PubMed 14044222KATZ 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.
- Results publication: PubMed 5349366Lawton 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.
- Results publication: PubMed 8295545D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993 Nov;32(5):382-7.
- Results publication: PubMed 11459715Herr 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.
- Individual participant dataSharing planned: No. The Regenstrief research team will use Protected Health Information (PHI) to conduct this study. Data that does not identify the subject will be shared with Merck Sharp \& Dohme Corp. and the National Sleep Foundation. At this time, that is only the study visit day.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Babar Khan, MD principal investigator
Regenstrief Institute, Inc.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing SleepLife Application w/FitBit and FitBit w/Minimal to No SleepLife App. in people with Insomnia, run by Regenstrief Institute, Inc. at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 7 Jan 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Jarod R Baker, MS (317-274-9274, bakerjar@regenstrief.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of physicians using a commercially available sleep tracker assessed by the "Physician Satisfaction/Communication" questionnaire who saw an improvement in physician-patient dialogue regarding sleep and related behaviors and habits (time frame: Six Months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03795129, which also lists 12 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Jan 2019.