DependenceNoDelayFallNCT03116386
Time Spent on Floor After Falls of Frailty People Overnight
A study testing run-in period and Etolya-F ® devices in people with Dependence and Fall From Bed, run by Centre Hospitalier Annecy Genevois at 1 site in France.
Trial summary
In the context of reduce staff for supervision of dependent elderly, automated risk alert systems could have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Dependence, Fall From Bed, Fall Injury
- What is being tested?
- run-in period and Etolya-F ® devices
- Type of treatment
- Medical device
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 0 participants
- Where
- 1 siteFrance
- Study dates
- 20 Jan 2017to May 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
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- elderly people who are resident in long term care facilities
- non opposed to participate to the study or whose his/her legal representative is not opposed to the participation of the resident to the study
Who cannot join
- the resident's bed can not be equipped with the ETOLYA-F® device for any reason
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Reduced Time on Floor After Falls at Night of People Living in Long Term Care Facilities - NoDelayFall Study
In the context of reduce staff for supervision of dependent elderly, automated risk alert systems could have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system.
The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a caregivers alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.
Read the detailed description
In France in 2011, more than 575000 elderly lived in long term care facilities. Most of them had comorbidities.
The most frequent reason for admitting in long term care facilities is the worsening of health status of elderly, often triggered by a fall. Elderly living in long term care facilities have frequently several comorbidities; the first ones are Alzheimer and related diseases. The proportion of such very dependent institutionalized people has risen for the last recent years and they represent a population at very high risk of falling. In an epidemiological analysis of more than 70,000 falls from residents of Bavarian nursing homes, the prevalence of fall was estimated at 1.49 falls for women and 2.18 for men. Those results didn't take into account the fact that people could fall more than once a day. In Alzheimer people (or people with related diseases) who lived in long term care facilities, the incidence of falls was even highest with 2.7 falls per resident per year.
The consequences of falls are not only physical injuries (wounds, fractures); they are frequently associated with psychological repercussions as loss of self-confidence, fear of new falls, reduction of abilities of moving which lead into declining of daily activities and loss of autonomy.
The incapacity of getting up alone is reported by more than a third of patients who have fallen, even if the fall is not complicated by a fracture. The length of time people stay on floor is directly link to the ability of the elderly person to give an alarm and to the presence or not of someone else to help him/her to get up. Patients who live in long term care facilities have limited functional capabilities not compatible with an operational use of active alarm systems.
In long term care facilities, 30-40% of falls occur between 8pm and 8am. Falls occurring at night seem to be associated with more severe injuries. Staff are less numerous at night with only 3 to 4 caregivers for 100 people.
To the best of the knowledge of the investigators, delay intervention time after a fall occurring at night has never been studied. Based on the investigators' experience, elderly people can only be discovered and helped when caregivers find them on floor on the occasion of a planned surveillance visit. These visits are carried out every 2 to 4 hours at night.
Automated alarms are used to alert staff to situations where there is a high risk of falling: an attempt to lift an armchair from a person who cannot stand or to detect the night-time rise of a high-risk people with the use of various sensors (pressure sensors connected to the mattress or environmental sensors).
In the context of staff reduced at night for the supervision of dependent elderly, automated risk alert systems could also have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system.
The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a personnel alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.
- Being tested
- run-in period, Control period, Etolya-F ® devices
- Medical subject headings
- Cognition Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
run-in periodOther
observational time i.e. baseline situation
Control periodDevice
neither activation of any lighting environment when the resident gets up from his bed nor alert if the resident did not return to bed after 15 minutes Etolya-F ® devices will only permit detection and recording of the moment of the elderlly will leave his/her bed and recording of the moment the elderly will be found by caregivers
Etolya-F ® devicesDevice
Etolya-F ® devices will permit detection of absence in the bed, activation of a lighting environment when the resident gets up from his bed, transmission of alert to caregivers through the centralized system of sick call if the resident do not return to bed after 15 minutes and recording the time when caregivers will find the resident out of bed, distinguishing between a fall and a night wandering in the room or corridors without a fall
| Study group | Role | What they receive |
|---|---|---|
| run-in period | Other | In order to improve the precision of data, the run-in period is dedicated to sensitize the caregivers about the importance of
* reporting all the falls occurring during the night
* tracking in each resident's file, all informations about the estimate length of time spent on floor after a fall occurring during the night
* and also reporting every other events occuring at night as wandering. All the beds will progressively equipped with the Etolya-F ® devices but the Etolya-F ® ddevices will stay off. Receives: Other: run-in period |
| control period | Sham comparator | We expect 30 falls will occurr at night during this 6 months period. Etolya-F ® devices will be installed on the bed of all participant residents but with limited fonctionnalities i.e. only the length of absence in the bed will be recorded (difference between time of detection of the beginning of absence in the bed and time where the resident will be found by the caregivers out of his bed). Receives: Device: Control period |
| Etolya-F ® devices | Experimental | We also expect 30 falls will occur at night during this 6-month period. Etolya-F ® devices will be used with all their functionalities i.e. permit detection of absence in the bed, activation of a lighting environment when the resident gets up from his bed, transmission of alert to caregivers through the centralized system of sick call if the resident do not return to bed after 15 minutes and recording the time when caregivers will find the resident out of bed, distinguishing between a fall and a night wandering in the room or corridors without a fall Receives: Device: Etolya-F ® devices |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device
Delay elapsing between the moment a resident has left his/her bed and the time he/she was found by caregivers, on floor after a fall at night
Measured: 2 periods of 6 months
Secondary outcomes (2)
Diagnostic performance of the Etolya-F® device in the detection of night falls
sensitivity and specificity of Etolya-F®
Measured: 2 periods of 6 months
Traumatic consequences of falls
Number of night falls resulting in hospitalization, fracture (s) or wound (s) requiring suture (s) or death
Measured: 2 periods of 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Apr 2017
- Study start20 Jan 2017
- Primary completionMay 2018 (estimated)
- Study completionMay 2019 (estimated)
Why it stopped: Inability of the ETOLYA®'s manufacturer to furnish the promised functionalities as those which had to be recorded for assessment of the study's end points
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (14)Papers the sponsor has linked to this study.
- Other trials for DependenceStudies 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
- Device feasibility
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Model description
- Run-in period then 6 months control period and then 6 months experimental period with activation of all the functions of Etolya-F® (the device used in the study)
- Masking
- None (open label)
- Enrolment
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Annecy Genevois
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Dr Matthieu DEBRAY, MD, Study director, CH Annecy GenevoisDr Nathalie RUEL, MD, Principal investigator, CH Annecy Genevois
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03116386
- Sponsor's protocol ID
- 2016-A01799-42
- Acronym
- NoDelayFall
- Status last verified
- Apr 2017
- First submitted
- 6 Apr 2017
- Last updated
- 10 Apr 2018
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Rapp K, Becker C, Cameron ID, Konig HH, Buchele G. Epidemiology of falls in residential aged care: analysis of more than 70,000 falls from residents of bavarian nursing homes. J Am Med Dir Assoc. 2012 Feb;13(2):187.e1-6. doi: 10.1016/j.jamda.2011.06.011. Epub 2011 Aug 4.
PubMed 21816682Pellfolk T, Gustafsson T, Gustafson Y, Karlsson S. Risk factors for falls among residents with dementia living in group dwellings. Int Psychogeriatr. 2009 Feb;21(1):187-94. doi: 10.1017/S1041610208007837. Epub 2008 Oct 6.
PubMed 18834557Jensen J, Lundin-Olsson L, Nyberg L, Gustafson Y. Falls among frail older people in residential care. Scand J Public Health. 2002;30(1):54-61.
PubMed 11928835Vu MQ, Weintraub N, Rubenstein LZ. Falls in the nursing home: are they preventable? J Am Med Dir Assoc. 2006 Mar;7(3 Suppl):S53-8, 52. doi: 10.1016/j.jamda.2005.12.016.
PubMed 16500282Lach HW, Parsons JL. Impact of fear of falling in long term care: an integrative review. J Am Med Dir Assoc. 2013 Aug;14(8):573-7. doi: 10.1016/j.jamda.2013.02.019. Epub 2013 Apr 16.
PubMed 23602257Fleming J, Brayne C; Cambridge City over-75s Cohort (CC75C) study collaboration. Inability to get up after falling, subsequent time on floor, and summoning help: prospective cohort study in people over 90. BMJ. 2008 Nov 17;337:a2227. doi: 10.1136/bmj.a2227.
PubMed 19015185Bergland A, Laake K. Concurrent and predictive validity of "getting up from lying on the floor". Aging Clin Exp Res. 2005 Jun;17(3):181-5. doi: 10.1007/BF03324594.
PubMed 16110729Lester P, Haq M, Vadnerkar A, Feuerman M. Falls in the nursing home setting: does time matter? J Am Med Dir Assoc. 2008 Nov;9(9):684-6. doi: 10.1016/j.jamda.2008.06.007. Epub 2008 Sep 25.
PubMed 18992702Pelissier C, Vohito M, Fort E, Sellier B, Agard JP, Fontana L, Charbotel B. Risk factors for work-related stress and subjective hardship in health-care staff in nursing homes for the elderly: A cross-sectional study. J Occup Health. 2015;57(3):285-96. doi: 10.1539/joh.14-0090-OA. Epub 2015 Apr 10.
PubMed 25864937Capezuti E, Brush BL, Lane S, Rabinowitz HU, Secic M. Bed-exit alarm effectiveness. Arch Gerontol Geriatr. 2009 Jul-Aug;49(1):27-31. doi: 10.1016/j.archger.2008.04.007. Epub 2008 Jun 3.
PubMed 18508138Banerjee S, Steenkeste F, Couturier P, Debray M, Franco A. Telesurveillance of elderly patients by use of passive infra-red sensors in a 'smart' room. J Telemed Telecare. 2003;9(1):23-9. doi: 10.1258/135763303321159657.
PubMed 12641889Lipsitz LA, Tchalla AE, Iloputaife I, Gagnon M, Dole K, Su ZZ, Klickstein L. Evaluation of an Automated Falls Detection Device in Nursing Home Residents. J Am Geriatr Soc. 2016 Feb;64(2):365-8. doi: 10.1111/jgs.13708. Epub 2016 Jan 19.
PubMed 26783046Tinetti ME, Williams CS. Falls, injuries due to falls, and the risk of admission to a nursing home. N Engl J Med. 1997 Oct 30;337(18):1279-84. doi: 10.1056/NEJM199710303371806.
PubMed 9345078Parker MJ, Gillespie WJ, Gillespie LD. Effectiveness of hip protectors for preventing hip fractures in elderly people: systematic review. BMJ. 2006 Mar 11;332(7541):571-4. doi: 10.1136/bmj.38753.375324.7C. Epub 2006 Mar 2.
PubMed 16513687
Study at a glance
From the registry record, last updated by the sponsor on 10 Apr 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Reduced Time on Floor After Falls at Night of People Living in Long Term Care Facilities - NoDelayFall Study
- ClinicalTrials.gov ID
- NCT03116386
- Acronym / sponsor ID
- NoDelayFall / 2016-A01799-42
- Study type
- Interventional
- Recruitment status
- WithdrawnReason stopped: Inability of the ETOLYA®'s manufacturer to furnish the promised functionalities as those which had to be recorded for assessment of the study's end points
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Centre Hospitalier Annecy GenevoisUniversity, hospital or other
- Study start
- 20 Jan 2017 (actual)
- Primary completion
- May 2018 (estimated)
- Study completion
- May 2019 (estimated)
- First posted
- 17 Apr 2017 (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.
In the context of reduce staff for supervision of dependent elderly, automated risk alert systems could have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system.
The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a caregivers alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.
Detailed description
In France in 2011, more than 575000 elderly lived in long term care facilities. Most of them had comorbidities.
The most frequent reason for admitting in long term care facilities is the worsening of health status of elderly, often triggered by a fall. Elderly living in long term care facilities have frequently several comorbidities; the first ones are Alzheimer and related diseases. The proportion of such very dependent institutionalized people has risen for the last recent years and they represent a population at very high risk of falling. In an epidemiological analysis of more than 70,000 falls from residents of Bavarian nursing homes, the prevalence of fall was estimated at 1.49 falls for women and 2.18 for men. Those results didn't take into account the fact that people could fall more than once a day. In Alzheimer people (or people with related diseases) who lived in long term care facilities, the incidence of falls was even highest with 2.7 falls per resident per year.
The consequences of falls are not only physical injuries (wounds, fractures); they are frequently associated with psychological repercussions as loss of self-confidence, fear of new falls, reduction of abilities of moving which lead into declining of daily activities and loss of autonomy.
The incapacity of getting up alone is reported by more than a third of patients who have fallen, even if the fall is not complicated by a fracture. The length of time people stay on floor is directly link to the ability of the elderly person to give an alarm and to the presence or not of someone else to help him/her to get up. Patients who live in long term care facilities have limited functional capabilities not compatible with an operational use of active alarm systems.
In long term care facilities, 30-40% of falls occur between 8pm and 8am. Falls occurring at night seem to be associated with more severe injuries. Staff are less numerous at night with only 3 to 4 caregivers for 100 people.
To the best of the knowledge of the investigators, delay intervention time after a fall occurring at night has never been studied. Based on the investigators' experience, elderly people can only be discovered and helped when caregivers find them on floor on the occasion of a planned surveillance visit. These visits are carried out every 2 to 4 hours at night.
Automated alarms are used to alert staff to situations where there is a high risk of falling: an attempt to lift an armchair from a person who cannot stand or to detect the night-time rise of a high-risk people with the use of various sensors (pressure sensors connected to the mattress or environmental sensors).
In the context of staff reduced at night for the supervision of dependent elderly, automated risk alert systems could also have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system.
The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a personnel alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.
Study design
- Primary purpose
- Device feasibility
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Masking
- None (open label)
- Number of arms
- 3
- Model description
- Run-in period then 6 months control period and then 6 months experimental period with activation of all the functions of Etolya-F® (the device used in the study)
| Arm | Type | Receives |
|---|---|---|
| run-in period | Other | Other: run-in periodIn order to improve the precision of data, the run-in period is dedicated to sensitize the caregivers about the importance of * reporting all the falls occurring during the night * tracking in each resident's file, all informations about the estimate length of time spent on floor after a fall occurring during the night * and also reporting every other events occuring at night as wandering. All the beds will progressively equipped with the Etolya-F ® devices but the Etolya-F ® ddevices will stay off. |
| control period | Sham comparator | Device: Control periodWe expect 30 falls will occurr at night during this 6 months period. Etolya-F ® devices will be installed on the bed of all participant residents but with limited fonctionnalities i.e. only the length of absence in the bed will be recorded (difference between time of detection of the beginning of absence in the bed and time where the resident will be found by the caregivers out of his bed). |
| Etolya-F ® devices | Experimental | Device: Etolya-F ® devicesWe also expect 30 falls will occur at night during this 6-month period. Etolya-F ® devices will be used with all their functionalities i.e. permit detection of absence in the bed, activation of a lighting environment when the resident gets up from his bed, transmission of alert to caregivers through the centralized system of sick call if the resident do not return to bed after 15 minutes and recording the time when caregivers will find the resident out of bed, distinguishing between a fall and a night wandering in the room or corridors without a fall |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- elderly people who are resident in long term care facilities
- non opposed to participate to the study or whose his/her legal representative is not opposed to the participation of the resident to the study
Key exclusion criteria (1 listed)
- the resident's bed can not be equipped with the ETOLYA-F® device for any reason
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 |
|---|---|---|
| run-in periodobservational time i.e. baseline situation | Other | run-in period |
| Control periodneither activation of any lighting environment when the resident gets up from his bed nor alert if the resident did not return to bed after 15 minutes Etolya-F ® devices will only permit detection and recording of the moment of the elderlly will leave his/her bed and recording of the moment the elderly will be found by caregivers | Device | control period |
| Etolya-F ® devicesEtolya-F ® devices will permit detection of absence in the bed, activation of a lighting environment when the resident gets up from his bed, transmission of alert to caregivers through the centralized system of sick call if the resident do not return to bed after 15 minutes and recording the time when caregivers will find the resident out of bed, distinguishing between a fall and a night wandering in the room or corridors without a fall | Device | Etolya-F ® devices |
Primary outcome
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device
Time frame: 2 periods of 6 months
Delay elapsing between the moment a resident has left his/her bed and the time he/she was found by caregivers, on floor after a fall at night
2 secondary outcomes
Diagnostic performance of the Etolya-F® device in the detection of night falls
Time frame: 2 periods of 6 months
Traumatic consequences of falls
Time frame: 2 periods of 6 months
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Apr 2018.
- Background: PubMed 21816682Rapp K, Becker C, Cameron ID, Konig HH, Buchele G. Epidemiology of falls in residential aged care: analysis of more than 70,000 falls from residents of bavarian nursing homes. J Am Med Dir Assoc. 2012 Feb;13(2):187.e1-6. doi: 10.1016/j.jamda.2011.06.011. Epub 2011 Aug 4.
- Background: PubMed 18834557Pellfolk T, Gustafsson T, Gustafson Y, Karlsson S. Risk factors for falls among residents with dementia living in group dwellings. Int Psychogeriatr. 2009 Feb;21(1):187-94. doi: 10.1017/S1041610208007837. Epub 2008 Oct 6.
- Background: PubMed 11928835Jensen J, Lundin-Olsson L, Nyberg L, Gustafson Y. Falls among frail older people in residential care. Scand J Public Health. 2002;30(1):54-61.
- Background: PubMed 16500282Vu MQ, Weintraub N, Rubenstein LZ. Falls in the nursing home: are they preventable? J Am Med Dir Assoc. 2006 Mar;7(3 Suppl):S53-8, 52. doi: 10.1016/j.jamda.2005.12.016.
- Background: PubMed 23602257Lach HW, Parsons JL. Impact of fear of falling in long term care: an integrative review. J Am Med Dir Assoc. 2013 Aug;14(8):573-7. doi: 10.1016/j.jamda.2013.02.019. Epub 2013 Apr 16.
- Background: PubMed 19015185Fleming J, Brayne C; Cambridge City over-75s Cohort (CC75C) study collaboration. Inability to get up after falling, subsequent time on floor, and summoning help: prospective cohort study in people over 90. BMJ. 2008 Nov 17;337:a2227. doi: 10.1136/bmj.a2227.
- Background: PubMed 16110729Bergland A, Laake K. Concurrent and predictive validity of "getting up from lying on the floor". Aging Clin Exp Res. 2005 Jun;17(3):181-5. doi: 10.1007/BF03324594.
- Background: PubMed 18992702Lester P, Haq M, Vadnerkar A, Feuerman M. Falls in the nursing home setting: does time matter? J Am Med Dir Assoc. 2008 Nov;9(9):684-6. doi: 10.1016/j.jamda.2008.06.007. Epub 2008 Sep 25.
- Background: PubMed 25864937Pelissier C, Vohito M, Fort E, Sellier B, Agard JP, Fontana L, Charbotel B. Risk factors for work-related stress and subjective hardship in health-care staff in nursing homes for the elderly: A cross-sectional study. J Occup Health. 2015;57(3):285-96. doi: 10.1539/joh.14-0090-OA. Epub 2015 Apr 10.
- Background: PubMed 18508138Capezuti E, Brush BL, Lane S, Rabinowitz HU, Secic M. Bed-exit alarm effectiveness. Arch Gerontol Geriatr. 2009 Jul-Aug;49(1):27-31. doi: 10.1016/j.archger.2008.04.007. Epub 2008 Jun 3.
- Background: PubMed 12641889Banerjee S, Steenkeste F, Couturier P, Debray M, Franco A. Telesurveillance of elderly patients by use of passive infra-red sensors in a 'smart' room. J Telemed Telecare. 2003;9(1):23-9. doi: 10.1258/135763303321159657.
- Background: PubMed 26783046Lipsitz LA, Tchalla AE, Iloputaife I, Gagnon M, Dole K, Su ZZ, Klickstein L. Evaluation of an Automated Falls Detection Device in Nursing Home Residents. J Am Geriatr Soc. 2016 Feb;64(2):365-8. doi: 10.1111/jgs.13708. Epub 2016 Jan 19.
- Diseases and loss of autonomy of residents in residential care facilities for the elderlyLink provided by the sponsor.
- 693,000 residents in residential accommodation for seniors in 2011 in FranceLink provided by the sponsor.
- New technologies likely to improve gerontological practices and the daily life of elderly patients and their familiesLink provided by the sponsor.
- Individual participant dataSharing planned: No
Related trials for Dependence
Recruiting
Effectiveness of Volitional Help Sheets as an Adjunct to Treatment to Promote Behavior Change: A Pilot Study on Smoking
Tobacco Dependence
Active, not recruitingPhase 1
Psilocybin-assisted Treatment for Cannabis Use Disorder
Cannabis Use Disorder
Not yet recruiting
Effects of Virtual Reality-Based Optokinetic Stimulation Added to Neuromuscular Training in Basketball Players
Visual Dependence, Postural Control
Recruiting
Young Adult Tobacco/Nicotine and Cannabis Co-use
Tobacco Use Disorder, Nicotine Dependence
Recruiting
Social Media Support Groups for Adolescent Vaping Cessation
Vaping, Vaping Cessation
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.
Dr Matthieu DEBRAY, MD study director
CH Annecy Genevois
Dr Nathalie RUEL, MD principal investigator
CH Annecy Genevois
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing run-in period and Etolya-F ® devices in people with Dependence and Fall From Bed, run by Centre Hospitalier Annecy Genevois at 1 site in France.
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 2 inclusion and 1 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: withdrawn, as of the sponsor's last update on 10 Apr 2018. 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 France. 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. Some participants in this study may receive a placebo. 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?
The study was withdrawn before enrolling participants, so there are no results.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device (time frame: 2 periods of 6 months). 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 NCT03116386, which also lists 14 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 10 Apr 2018.