Improving Sleep Using Mentored Behavioral and Environmental Restructuring
Phase: NA
Conditions: Insomnia
Sponsor: NYU Langone Health

SLUMBER Protocol V.8/27/2018 
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Study Title 
Improving Sleep Using Mentored Behavioral and Environmental Restructuring (SLUMBER) 
Study Number 
s17-00338   
Principal Investigator 
Joshua Chodosh, MD, MSHS  
Study Center 
NYU Langone Medical Center  
 
A. Purpose of Study and Background 
A1. Purpose 
The goal of this research is to demonstrate that a mentored non-pharmacologic quality improvement 
intervention to improve sleep quality can improve common sleep-related symptoms among skilled nursing 
facility residents. In this study, we will perform a stepped wedge randomized trial of the Improving Sleep Using 
Mentored Behavioral and Environmental Restructuring (SLUMBER) program. SLUMBER is a non-
pharmacological intervention program, delivered by providing mentoring to facility staff who work directly with 
residents. The study will be conducted in three urban SNFs with the goal of enhancing resident sleep quality, 
mood, anxiety, pain, cognitive performance, and activity engagement. 
 
A2. Specific Aims 
Sleep disturbances are common in skilled nursing facilities (SNFs), affecting 69% or more of residents.4,5 Poor 
sleep often coincides with substantial worsening of depressive symptoms6 and pain,7 making them markedly 
more difficult to manage. Additionally, poor sleep often co-occurs with declines in cognitive functioning, leading 
to worse patient-centered outcomes.8 However, sleep disturbances are understudied, under-recognized and 
poorly treated in SNFs. This may be due, in part, to insufficient understanding among SNF staff about the 
potential benefits of non-pharmacological approaches to improve sleep. Given that residents depend on SNF 
staff to meet their basic daily needs, participation of staff members in sleep improvement efforts is essential. 
The goal of this research is to demonstrate that a mentored non-pharmacologic intervention to 
improve resident sleep quality can improve common sleep-related symptoms among SNF residents. 
 
Across settings, sedative-hypnotic medications have been commonly used as first-line therapy to address 
sleep disturbances in older adults.9-11 This approach, however, is less than ideal. Sedative-hypnotic 
medications have considerable adverse effects for older patients including impaired cognition, increased fall 
risk, and even worsened sleep quality over the long-term.12,13 These adverse effects have led to systematic 
efforts to reduce use of these medications.14 Such efforts have created an even more pressing need for multi-
faceted strategies for improved sleep quality among SNF residents who continue to suffer from sleep 
disturbances. Extensive prior research demonstrates short-term (i.e., immediate) symptom improvement with 
non-pharmacological interventions,15-18 but no intervention programs have been successfully implemented or 
sustained in SNFs. Our proposed study will build on our prior work by combining the successful components of 
a multi-component sleep intervention program designed for SNF residents1 with the structure used in a 
successful clinician-delivered intervention program for antidepressant medication reduction and non-
pharmacological depression care in SNFs.3 The goal of our proposed program is to improve sleep and related 
symptoms in SNFs for up to 3 months follow-up using this approach.  
 
 
In this study we will perform a stepped wedge randomized trial of the Improving Sleep Using Mentored 
Behavioral and Environmental Restructuring (SLUMBER). SLUMBER is a non-pharmacological intervention 
program, delivered by providing mentoring to facility staff who work directly with residents. SLUMBER consists 
of three core components: 1) improving the nighttime sleep environment; 2) increasing patient activity 
during the day and reducing daytime behaviors that lead to sleep disturbances at night; and 3) 
identifying and assisting individual residents experiencing difficulties with sleep, with four specific aims. 
 
Aim 1: Test whether the SLUMBER intervention improves objectively measured sleep quality. 
Hypothesis 1: Residents of SNF units receiving SLUMBER will achieve better nighttime sleep quality 
quantified by increased total sleep time and reduced number of awakenings measured objectively with wrist 
actigraphy. 
 
NCT03327324

SLUMBER Protocol V.8/27/2018 
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Aim 2: Test whether the SLUMBER intervention improves resident-reported symptoms of poor sleep quality, 
depressed mood, anxiety, and pain. 
Hypothesis 2: Residents of SNF units receiving the SLUMBER intervention will report better sleep quality, 
and will experience less depressed mood, anxiety, and pain symptoms. 
 
Aim 3: Test whether the SLUMBER intervention improves cognitive function, and increases engagement in 
facility activities. 
Hypothesis 3: Residents of SNF units receiving the SLUMBER intervention will achieve better cognitive 
function and increased engagement in facility activities. 
 
Aim 4: Test to what extent staff use of technology and data promotes a better sleep environment, reflected in 
decreased nighttime noise, increased daytime light exposure, and use of sleep-promoting strategies. 
Hypothesis 4: Nighttime noise will decrease, residents will have increased daytime light exposure, and staff 
will use nighttime strategies to promote sleep on units exposed to the SLUMBER intervention. 
 
 
This study will be amongst the first to take a previously tested program for non-pharmacological approaches to 
improve depression care, and apply this methodology to test validated approaches for sleep improvement in 
SNFs. Furthermore, we will test whether SLUMBER can improve the negative consequences of poor sleep, 
including symptoms of depression, anxiety, and pain and evaluate the benefits of SLUMBER in improving 
cognitive function and activity participation. The potential impact of this research includes improved quality of 
care and quality of life for hundreds of thousands of SNF residents who suffer from poor sleep and its 
associated adverse effects. 
 
A. Specific Aims (SLUMBER-RD) 
 
Sleep disturbances are common among individuals with Alzheimer’s Disease living in skilled nursing facilities 
(SNFs).1,2  Poor sleep often coincides with substantial worsening of depressive symptoms3 and behavioral 
disturbances,4 both of which are common in Alzheimer’s Disease. Additionally, poor sleep is associated with 
cognitive decline. Sleep disturbances are understudied, under-recognized and poorly treated in SNFs, and 
there are unique challenges faced in addressing sleep difficulties among the subset of residents who have 
Alzheimer’s Disease. One key factor is an insufficient understanding among SNF staff about the potential 
benefits of non-pharmacological approaches to improve sleep and methods to overcome the challenges of 
improving sleep for Alzheimer’s disease patients. Given that residents depend on SNF staff to meet their basic 
daily needs, participation of staff members in sleep improvement efforts is essential. The goal of this 
research is to develop and test whether a mentored non-pharmacologic intervention to improve 
resident sleep quality among SNF residents with Alzheimer’s Disease can improve common sleep 
quality and sleep-related symptoms among SNF residents. 
 
Decreasing use of psychotropic medications, including those commonly used to address sleep, is a high 
priority.5 Adverse effects of sedative-hypnotic medications in Alzheimer’s disease are well known.6,7  These 
effects have created an even more pressing need for multi-faceted strategies for improved sleep quality among 
SNF residents with Alzheimer’s Disease and Related Dementias (ADRD) without using medications. Extensive 
research using non-pharmacological interventions has demonstrated behavioral symptom improvement and 
improved sleep in individuals with ADRD,8-12 but to our knowledge none have been successfully implemented 
by nursing unit staff or sustained in ADRD units. 
 
We are currently studying a sleep improvement program that combines successful aspects of a multi-
component sleep intervention tested in prior work12 with the structure used in a successful clinician-delivered 
intervention for antidepressant medication reduction and non-pharmacological depression care in non-
dementia SNF units.13 This supplemental funding will enable us to 1) revise a sleep intervention approach 
using a plan-do-study-act 14,15 approach in one ADRD unit and 2) test that revised approach in a second ADRD 
unit. We will use the framework of our ongoing trial, with adjustments to content areas (adding strategies 
specifically for residents with Alzheimer’s Disease and sleep problems) and primary outcome measures (less 
reliance on patient questionnaires and greater reliance on objective and observational outcomes). 

SLUMBER Protocol V.8/27/2018 
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The ADRD-specific Improving Sleep Using Mentored Behavioral and Environmental Restructuring (SLUMBER) 
for Residents with Dementia (SLUMBER-RD) is a non-pharmacological intervention program, delivered by 
mentoring facility staff who work directly with residents. SLUMBER consists of three core components: 1) 
improving the nighttime sleep environment; 2) increasing patient activity during the day and reducing 
daytime behaviors that lead to sleep disturbances at night; and 3) identifying and assisting individual 
residents experiencing difficulties with sleep. The specific aims of this supplemental funding request are: 
 
Aim 1: Revise and optimize ADRD-specific SLUMBER-RD components to ensure feasibility on ADRD units. 
Hypothesis 1: SLUMBER-RD is feasible as demonstrated by adequate subject recruitment, compliance with 
wearing wrist actigraphy, and nursing staff participation in providing feedback and implementing behavioral 
approaches on the selected Alzheimer’s disease units. 
Aim 2: Test whether SLUMBER-RD improves objectively measured sleep quality in dementia care units. 
Hypothesis 2: Residents of units receiving SLUMBER will achieve better nighttime sleep quality quantified by 
increased total sleep time and reduced number of awakenings measured objectively with wrist actigraphy. 
Aim 3: Test whether the SLUMBER intervention improves behavioral symptoms of dementia and engagement 
in facility activities.  
Hypothesis 3: Residents of units receiving the SLUMBER intervention will demonstrate reduced behavioral 
symptoms of dementia and increased engagement in facility activities. 
Exploratory Aim 4: Measure the impact of SLUMBER-RD on Minimum Data Set (MDS) 3.0 collected 
measures of depressed mood, pain, and cognitive function. 
 
Building upon our successful ongoing study, this project will advance Alzheimer’s Disease research by 
testing a novel, mentoring approach to improving sleep among SNF residents with ADRD. We will revise and 
pilot-test SLUMBER-RD with the goal of conducting a large-scale trial in dementia care units at the conclusion 
of this preliminary work.  The potential impact of this research includes improved quality of care and quality 
of life for residents with Alzheimer’s Disease who suffer from poor sleep and its associated adverse effects. 
 
A3. Background 
Of the more than 1.4 million Americans who reside in skilled nursing facilities (SNFs),19 over two-thirds 
experience sleep problems,4,5 exceeding what is typical for similarly-aged adults living in the community.20 
Facility residents are seldom able to maintain nighttime sleep for a full hour and seldom stay awake for a full 
hour during the day.21 Both nighttime sleep fragmentation and daytime sleepiness, manifested by frequent brief 
sleep episodes, are “the norm” in SNF settings.22-24 It is widely known that poor sleep is strongly correlated with 
multiple negative conditions and symptoms including depressed mood,25 anxiety,26,27 pain,28,29 cognitive 
impairment,8 physical disability,4,30-32 and decreased engagement in activities.33,34 
 
 
Sleep disturbance is common and often severe among older people in SNF’s.5,13 Institutional routines 
and nursing care practices (which encourage excessive time spent in bed, limited bright light 
exposure, and a noisy nighttime environment) contribute to this sleep impairment.35 Some sleep 
improvement practices (e.g., sedating medications) may be ineffective and contribute to declining 
health.36 The high rates of dependencies in activities of daily living (ADLs)37 require frequent interactions with 
cross-discipline staff to meet ongoing care needs.38-40 Achieving better sleep therefore depends on the staff’s 
interactions with residents; a program implemented by staff therefore has the greatest potential for positive 
outcomes and is best achieved through mentored collaboration with sleep experts to facilitate grounded 
approaches. Our SNF research involving staff engagement and mentoring3 positions us well to successfully 
conduct the Improving Sleep Using Mentored Behavioral and Environmental Restructuring (SLUMBER) 
intervention. 
 
 
Poor sleep is related to symptoms of depression, anxiety, pain and cognitive deficits. In its more severe 
forms, 67% of persons with major depressive disorder (MDD) meet criteria for chronic insomnia.41 Although 
insomnia has traditionally been thought of as a ‘symptom’ of depression, 40-69% of patients with MDD report 
that insomnia occurred prior to the onset of depressed mood.42 Moreover, whereas incident insomnia in the 
setting of other comorbidities predicts future MDD, prior MDD does not predict onset of insomnia.42 Finally, 

SLUMBER Protocol V.8/27/2018 
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insomnia persists in more than half of patients after resolution of symptoms of MDD.41 Anxiety, as a symptom 
closely related to depression, is uniquely associated with perceived sleep quality.43 Efforts to address either 
sleep problems or anxiety/depression may positively impact both. 
 
Although the relationship between impaired sleep and pain has been broadly acknowledged, the complex 
temporal relationship remains inadequately understood. Sleep disturbances may predict pain more effectively 
than pain predicts sleep disturbances. Experimental studies of intentional sleep disruption show substantial 
associations with increased pain sensitivity in healthy volunteers and those with chronic musculoskeletal and 
other pain.44 The potential for decreasing pain symptoms through improvement of sleep is important given the 
high prevalence of pain among SNF residents.45,46 
 
There is general consensus that sleep benefits neuronal plasticity and therefore, cognitive function.47-49 Based 
on accumulating evidence, sleep deprivation specifically impairs hippocampal neuronal plasticity and 
subsequent memory function.50 Potential benefit from improved sleep is large when considering that nearly two 
thirds of SNF residents have moderate-to-severe dementia based on national Minimum Data Set (MDS) data,19 
exacerbating disability and the need for care assistance. 
 
 
Sleep disruption is related to less activity participation in SNF residents.51 Functional impairment further 
challenges activity participation. In 2012, 80% of SNF residents required assistance with one or more activities 
of daily living (ADL); 62% had four or five ADL impairments while 11-27% of residents had a fall in the 3 
months prior to assessment.19  Residents with poor nighttime sleep are more likely to sleep during the day and 
to experience depressed mood, both of which limit participation in activities that might enhance cognitive and 
other domains of function. Sleep disturbance may also be an independent risk factor for social isolation, with 
greater risk for further morbidity and mortality.52 We have also found that residents who are excessively sleepy 
during the day spend more time in bed, engage in fewer social and physical activities, and require more 
assistance with ADLs than residents who are less sleepy.5 
 
 
Sleep disturbances in SNF residents result from both resident-specific and environmental factors. 
Some factors, such as primary sleep disorders (e.g. sleep apnea53,54), medical conditions (particularly those 
causing pain28,29), mood disorders (e.g., depression,25 anxiety26,27), medications (sedating and/or alerting53), 
and circadian (24-hour) rhythm disruption53, can be considered “resident factors;” however, above and beyond 
these considerations, “environmental factors” disrupt sleep considerably. These include nighttime noise 
produced by caregiving staff, housekeeping staff and other residents, lights left on or turned on at night, and 
inadequate indoor daytime light levels with residents seldom taken outdoors thereby limiting light exposure 
during the daytime.55 The additive effect of these environmental factors on resident factors can exacerbate the 
severity and impact of sleep problems. In fact, addressing resident level factors alone leads to only modest 
improvements in nighttime sleep quality.21,56,57  
 
 
Non-pharmacological approaches may reduce perceived pharmacotherapy needs, which includes use of 
off-label sedating agents with considerable potential for adverse effects.58,59 These effects include daytime 
sedation, cognitive and motor impairment (incoordination, weakness), medication dependence, and hip 
fracture.56 Non-pharmacological approaches include: 1) daytime efforts to increase daylight exposure, 
physical activity, activating activities, social engagement and limits on daytime sleeping; 2) environmental 
modifications to improve the nighttime sleep environment with respect to staff care-directed disruptions, lighting 
and noise; and 3) components of cognitive behavioral therapy for insomnia (CBT-I).15-17,60,61 The principles of 
CBT-I include stimulus control, sleep hygiene, sleep restriction, relaxation, and education. However, CBT-I is 
typically delivered to patients without cognitive impairment. In the SNF setting, it is essential to involve staff in 
creating an environment and supporting behaviors conducive to and supportive of the principles of CBT-I. 
 
Interventions targeting “resident factors” to improve sleep have led to modest improvements in sleep 
quality. Randomized controlled trials have shown that timed exposure to bright artificial light can regularize 

SLUMBER Protocol V.8/27/2018 
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circadian (24-hour) activity and sleep/wake patterns and circadian rhythms in SNF residents.22,57,62 However, 
these interventions have been largely unsustainable. 
 
Interventions targeting “environmental factors” to improve sleep include randomized controlled trials to 
reduce nighttime noise and light in resident rooms using research staff to deliver the interventions.55,63 In one 
study, noise was reduced significantly from 77 to 54 noises per night, although this still represents a significant 
amount of nighttime noise.55 One multicomponent intervention conducted by our research group targeted 
patient and environmental factors,1 using research personnel to provide nighttime personal care leading to 
improvement in resident sleep outcomes during the daytime (i.e., reduced daytime sleep), but not reductions in 
nighttime noise or nighttime sleep quality,1 suggesting that staff must be engaged to reduce nighttime noise 
and improve nighttime sleep quality.  
 
 
Conceptual Model for SLUMBER: sleep interventions are relatively simple and largely relate to 
environmental modification. In this causal model (Figure 1), the methods of SLUMBER (described below) 
focus on detecting sleep-disruptive factors 
including: nighttime noise and patient 
behaviors associated with poor sleep 
quality; disruptions caused by nighttime 
caregiving; daytime inactivity; and limited 
light exposure. In this model, staff-
delivered interventions to improve these 
factors improve sleep quality thereby 
creating opportunities to test the impact of 
improving sleep quality (measured by actigraphy) on mood (depression and anxiety), pain, cognitive function, 
functional ability, and observed activity levels. 
 
 
SNF staff’s access to clinically relevant data has greatly improved with the Minimum Data Set (MDS) 
3.0, making more accurate and relevant assessments readily available.64 MDS 3.0 assessment data—
including the Patient Health Questionnaire-9 (PHQ-9);65 the Brief Interview of Mental Status (BIMS);66,67 
behavioral, functional, and pain assessments; active diagnoses; and medication data—are readily available for 
directing clinical care. These data also support interventions that lessen the burden of additional data 
collection. Drs. Joshua Chodosh (NYU) and Mary Cadogan (UCLA), SLUMBER investigators, were on the 
team that developed and tested MDS 3.0 and have subsequently demonstrated the feasibility of using already-
collected MDS 3.0 data to engage SNF staff in self-evaluation and program implementation to improve resident 
outcomes. 
 
A4. Preliminary Studies 
Our team has conducted descriptive and interventional research in SNFs for over two decades and has 
the combined skill set to conduct this work. We recently developed and tested a depression care 
improvement program in five SNFs throughout California.3 That successful intervention program informed our 
approach to SLUMBER. We also have extensive experience delivering sleep interventions to SNF 
residents.1,2,5,36,53,63,68 SLUMBER is informed by this work as well, and is based on a solid theoretical framework 
for sleep disturbances in SNFs. Most importantly, the synergy between these two areas of expertise has led us 
to the innovative and highly structured SLUMBER intervention program, which, if effective, can be broadly 
applied to improve sleep and associated clinical outcomes in SNFs nationwide.  
 
 
A Practice Improvement Education Program Using a Mentored Approach to Improve Depression Care 
in SNFs: We developed and tested a depression care intervention in five SNFs to increase each facility’s 
capability in depression assessment and care. This work used cross-disciplinary team building and clinical 
mentorship.3 Our 6-month intervention included five components: 1) facilitated collection of MDS 3.0 Patient 
Health Questionnaire (PHQ-9) and medication data for diagnostic interpretation; 2) education and modeling for 
team building and non-pharmacological depression care; 3) mentored team meetings; 4) educational webinars; 

SLUMBER Protocol V.8/27/2018 
6 
 
and 5) technical assistance. Five SNFs established cross-disciplinary teams, including nursing, social work, 
physicians, and other disciplines. Participation in three mentored meetings and five educational webinars was 
61% overall and competencies improved across multiple depression-care processes (p =.05 to <.001). For 336 
residents with depression (PHQ-9) and medication data, depressive symptom scores did not worsen when 
medication use declined, from 37.2% receiving antidepressants at baseline to 31.0% at 9 months (p<.001). 
Non-pharmacological behavioral activation69 was reported as being widely implemented as antidepressant use 
was reduced. This suggests that staff members used alternative strategies learned during the program to 
supplant the use of medications for depression. The numerous instances where collaborative staff provided 
important solutions to implementation challenges suggest the success of this approach to staff engagement.  
 
 
Rates of sleep disturbance among SNF residents: We have conducted studies on sleep disturbance among 
residents of long-term care (LTC) facilities.1,2,5,20,22-24,55,63 Among 118 residents at four SNFs, mean nighttime 
percent sleep was 65.8% (SD 20.1) based on wrist actigraphy.24 This is dramatically lower than the 85% 
typically observed among healthy older people living in the community.70 SNF residents had marked sleep 
disruption, with average sleep duration of only 20.0 minutes (SD 17.8) between awakenings during the night, 
and extended time in bed during the day. They had little or no bright light exposure, and little evidence of a 
standard routine to prepare for nighttime sleep.24 In another study, we observed daytime time in bed, using 
observations every 15 minutes for 3 days, among 230 SNF residents in eight SNFs.36,71 Residents were in bed 
for 36% and asleep for 24% of daytime observations. Daytime in-bed time was associated with more daytime 
sleeping (r=.48, p <.001). Residents within the same facility had a very similar timing of daytime bedrest and 
transfers in and out of bed; however, residents from different facilities had very different patterns despite 
similar subject characteristics. This suggests that facility characteristics and routines (rather than resident 
characteristics and needs) determined day/night bed routines.  
 
In another study, we found that 69% of 492 residents at four SNFs met our definition of excessive daytime 
sleeping (i.e., asleep >15% of observations from 9am-5pm).5 Of these residents, 60% also had disturbed 
nighttime sleep (asleep <80% of time from 10pm-6am) based on wrist actigraphy. Residents spent one third of 
the day in their rooms, typically in bed, and were seldom outdoors or exposed to bright light (Table 1).  
 
These findings suggest that more 
sleep disruption (particularly 
excessive daytime sleeping) is 
associated with more dependency in 
activities of daily living and less social 
interaction, offering considerable 
opportunity to improve overall well 
being by improving sleep quality and 
associated symptoms. 
 
 
 
We have performed several interventional trials to test non-pharmacological sleep interventions in 
institutionalized older adults.68,72,73 We evaluated the sleep effects of a facility nighttime intervention 
designed to decrease noise and light levels, and to limit sleep-disruptive nighttime nursing care practices 
(N=92, mean age=87.3 years).74 At follow-up testing, there was a significant decrease in the number of 
awakenings per night coincident with less noise and light in the intervention compared with the control group. 
We also performed randomized trials to examine the effects of timed exposure to bright light on sleep patterns. 
In the first study (n=77 residents), morning bright light exposure delayed the peak (i.e., acrophase) of activity 
rhythms, increased the mean activity level (i.e., mesor), and led to an overall strengthening of activity rhythms 
compared with participants who received evening bright light or evening dim light (placebo).57 In a second 
study (n=92 residents), we examined the effects of bright light exposure on sleep and agitation among nursing 
residents with Alzheimer’s disease. In this study, both morning and evening exposure to bright light resulted in 
more consolidated sleep at night.22  
 

SLUMBER Protocol V.8/27/2018 
7 
 
Based on our single-component interventions, we tested a multi-component intervention in a randomized 
controlled trial to improve sleep among SNF residents. Among 118 residents (mean age=87 years, 77% 
female) who had excessive daytime sleeping and disrupted nighttime sleep,1,2 our intervention combined: 1) 
efforts to decrease daytime in-bed time, 2) > 30 minutes of daily sunlight exposure, 3) increased physical 
activity, 4) structured bedtime routine, and 5) efforts to decrease nighttime noise and light. Compared with 
control participants, intervention participants had a nearly 40% decrease in daytime sleeping (F=13.48, p < 
.001). Intervention participants also demonstrated improvement in certain quality of life measures, including 
increased participation in social (F=22.42, p < .001) and physical (F=12.65, p =.001) activities and increased 
social conversation (F=5.04, p = .027).1,2 However, nighttime noise levels in resident rooms were not reduced, 
and this likely attenuated the potential benefits of improving the nighttime environment on nighttime sleep 
quality.  
 
Taken together these findings suggest that non-pharmacological interventions can significantly improve 
daytime sleeping and when environmental modifications are achieved, these can also improve nighttime sleep. 
The overall impact, however, is limited by factors that require the engagement of facility caregiving staff. 
Empowering SNF staff through education and technology to decrease those behaviors that contribute to 
nighttime noise is essential to optimizing the benefits of sleep intervention programs.  
 
 
Impact of Nursing Home (NH) staff on the nighttime environment: Recognizing the challenges of 
implementing our multicomponent intervention, we 
gathered more information (Table 2) about the 
nighttime sleep environment and interviewed nursing 
staff at two SNFs. First we examined minute-by-
minute noise and light levels in patient rooms. To 
identify possible sources of noise at night, we documented noise levels and sources in patient rooms in one 
SNF and found that facility staff created a majority of noises that were sufficiently loud to awaken residents 
(Figure 2). In fact, staff members produced an average of seven 
noises per hour between 10pm-6am that were at least as loud as 
conversational speech at the resident’s bedside (i.e., sufficiently 
loud to awaken most sleepers). Other residents and environmental 
sources produced additional sleep-disruptive noises.75 Further 
investigations revealed that the distribution of caregiving practices 
across nursing shifts (e.g., weighing patients monthly during the 
night shift; waking, dressing, and serving breakfast to residents 
during the night shift) might contribute to overall disruption of 
residents’ sleep. Effective, sustainable interventions to improve 
sleep will require engagement of facility staff members at all levels, 
from bedside caregivers to administrators who set policy and procedures at the facility. 
 
A5. Study Design 
Overview: We propose a 4-year intervention trial of a comprehensive sleep improvement program, 
SLUMBER, which is a mentored approach for unit staff. This is a single-center study involving NYU Langone 
School of Medicine. The researchers from UCLA are responsible for providing the sleep expertise, participating 
in the quality improvement aspect of the study, and participating in analyses and manuscripts. The NYU 
personnel are responsible for the research aspects of the study, which include all interactions with research 
subjects (Nursing Home Residents). The study statistician is at UCLA, but will be provided access to de-
identified data via an NYU Datacore portal (see Data Collection Overview and Data Analysis and Data 
Monitoring). No UCLA personnel will have access to the Personal Health Information of the study participants.  
The study will be conducted within three SNFs in New York City, The New Jewish Home, Terence 
Cardinal Cooke Health Care Center, and the Mary Manning Walsh Home. The study will be conducted in three 
urban SNFs with the goal of enhancing resident sleep quality, mood, anxiety, pain, cognitive performance, and 
activity engagement. None of the SNF will be engaged in the study related procedures. All procedures will be 
performed by the NYULMC IRB approved personnel.  

SLUMBER Protocol V.8/27/2018 
8 
 
  
Design: This is a 4-year stepped wedge intervention trial (SWT) in six SNF units within three SNFs (two 
units/SNF, Figure 3). In a SWT, all clusters (here, SNF units) receive the intervention but at different time 
points.76 The stepped wedge design is a useful alternative to a parallel cluster trial with multiple advantages, 
including: 1) increased efficiency, 2) requirement for fewer research staff (thereby reducing costs) due to 
sequential rather than parallel intervention testing for each cluster, 3) more observations, with each cluster 
serving as its own “control”, and 4) ultimately greater power for a given same sample size when the intra-class 
correlation is high.77 There will 
be no engagement of the 
second unit within each facility 
prior to their scheduled 
engagement and facilities 
randomized to later allocation 
will wait for the intervention. In 
place of an “attention control,” 
Dr. Chodosh will provide all 
unengaged facilities with 
quarterly geriatric education 
offerings to avoid loss of 
interest while waiting for the 
sleep improvement program. In 
SLUMBER, every unit provides baseline and follow-up data. We will collect baseline data just prior to the 
intervention on a given unit and within 1 month after a 3-month exposure to the SLUMBER program. Facilities 
will encourage staff to continue to use intervention approaches after the 3-month intervention period. We will 
collect additional follow-up sleep and activity data with resident surveys and repeat wrist actigraph measures 3 
and 6 months after the post-intervention period for all units to test for increased or continued benefit 
(sustainment) over time and assess for the possibility of reduced benefits over time (relapse). From the 
intervention beginning and throughout the remaining study duration, real-time environmental data 
(noise via decibel meters) and observed sleep disturbance (by staff anonymous recording of sleep 
disturbances) will be available to SNF staff on a visible computer interface (described below) to 
facilitate continued use of SLUMBER strategies. MDS 3.0 data collection will provide repeated measures of 
mood, cognitive function, and physical function for the full study duration (Figure 3). We selected a 3-month 
follow-up time point to strike a balance between sufficient time for intervention effects to emerge while 
considering the rapidly changing health status of LTC residents. Also, MDS data are collected quarterly and 
the intervention itself includes an initial mentoring session, three additional meetings over the next two months, 
and a follow-up session at the end of three months.  
 
Supplement Design:  
1. Overview: For this supplement application, we propose a 12-month intervention trial focused on 
dementia care SNF units using a modified comprehensive sleep improvement program, SLUMBER-RD, 
which is a mentored approach for unit staff. The study will be conducted in two urban SNFs with the goal of 
enhancing sleep quality, mood, cognitive performance, and activity engagement.  
 
.2. : Because this is a two-unit supplement to the parent study, we will conduct this intervention in parallel to 
the ongoing trial, which focuses on units that are not focused on care for residents with ADRD. Although we 
recognize that some residents on the units within the parent study have dementia, they have less severe 
behavioral issues than what would warrant being on a unit whose care is more dementia-specific. We aim to 
conduct the modified SLUMBER-RD intervention in parallel to our other work, thus benefitting from economies 
of scale in utilizing training times and travel needed to complete work on the parent grant, coordinating 
technology use with our software company, CaseWorthyTM, and research meetings utilizing shared learnings 
between dementia and non-dementia-specific work. The two units (one in each of two facilities) will be 
engaged in randomized order (coin-flip). The first unit will provide experience and subsequent modifications for 
the second unit. Because these two units are in separate facilities, the stagger time for the second unit is only 
dependent upon completing enough intervention time on the first unit to provide enhanced modifications to the 

SLUMBER Protocol V.8/27/2018 
9 
 
second unit intervention (i.e., some overlap would be feasible). In SLUMBER and SLUMBER-RD, every unit 
provides baseline and follow-up data. We will collect baseline actigraphy and observational data just prior to 
the intervention on each unit and within 1 month after a 3-month exposure to the SLUMBER-RD program. Staff 
will be encouraged to continue to use intervention approaches after the 3-month intervention period and we will 
leave study resources at the site for ongoing use. We will collect additional follow-up sleep and activity data 
with repeat wrist actigraph measures, as well as observations at three months after the post-intervention 
period, similar to what we are doing in the parent R01; however, further follow-up will be truncated due to the 
one-year time frame for the supplement. From the intervention beginning and throughout the remaining 
study duration, real-time environmental data (noise) and observed sleep disturbance will be available 
to SNF staff on a visible computer interface (described below) to facilitate continued use of SLUMBER 
strategies. MDS 3.0 data collection will provide repeated measures of mood and cognitive function for the full 
study duration. We selected a 3-month follow-up time point to strike a balance between sufficient time for 
intervention effects to emerge while considering the rapidly changing health status of LTC residents, especially 
those with ADRD. Moreover, MDS data are collected quarterly and the intervention itself includes an initial 
mentoring session, two additional meetings over the next two months, and a follow-up session at the end of 
three months. Because we are interested in a measure of trend for the MDS measures of mood and cognition, 
we will include two quarters of data for each resident that precedes their time of enrollment. 
 
 
B. Characteristics of the Research Population 
This study will be conducted within three SNFs in New York City, all three of which are currently engaged and 
have provided letters of intent to participate. The facilities’ units average 40 beds/unit and are ethnically diverse 
(40–45% other than non-Hispanic White). MDS-reported cognitive impairment varies broadly across sites, and 
up to 73% of residents have depressive symptoms documented on the MDS. Based on most recent estimates, 
two thirds of nursing facility residents may have some degree of cognitive impairment. Cognitive impairment is 
not in and of itself a deterrent to subject consent or an exclusion criterion as many individuals even with levels 
of cognitive function that meet criteria for dementia will maintain the capacity to provide informed consent 
adhering to the criteria specific to that process. Moreover, many will be able to answer the in-person survey 
interview as has been noted in other studies that are referenced within the research plan. Moderate to severely 
demented residents do not typically reside in the units chosen for the SLUMBER intervention. 
 
B1. Number of Subjects 
The facilities’ units average 40 beds/unit. We expect to consent at least 50% of unit residents, for an expected 
average sample size of 20 per unit, for an expected total of 200 subjects. The grant packet “Planned 
Enrollment Report” is based on 50% of the total number of subjects and reads 61 participants.  A revised 
estimate to account for 200 subjects was submitted post review per the request of the program officer and this 
number is correctly stated in “E3. Settings and Participants” of the NIH-submitted protocol. 
 
B2. Gender of Subjects 
Women will be included and are likely to be the majority of subjects in this study given the demographics of 
nursing home populations in general and of these facilities in particular. An average of 68% of nursing home 
residents within the selected units in these three facilities are women. 
 
B3. Age of Subjects 
This study involves an elderly population due to the typical age of a nursing home resident. No children are 
included. The minimum age is 18 with no upper limit.  
 
B4. Racial and Ethnic Origin 
Minority populations will be included and distributions are based on naturally occurring proportions within the 
selected facilities and units for this study. Among the candidate population, 40-45% indicate a race or ethnicity 
other than non-Hispanic white. 
 
B5. Inclusion Criteria 

SLUMBER Protocol V.8/27/2018 
10 
 
Inclusion criteria for nursing facility residents are: 1) living in the unit of intervention, 2) ability to communicate 
and follow simple commands, 3) English- or Spanish-speaking, and 4) capacity to consent assessed with 
standard questions used to assess capacity or having a surrogate who can provide consent.  
 
B6. Exclusion Criteria 
Exclusion criteria for nursing facility residents include: 1) obtunded or comatose state, 2) inability to 
communicate verbally, 3) inability to consent and without surrogate, and 4) non-English and non-Spanish 
speaking. In keeping with QI strategies, all residents will be exposed to the environmental aspects of the 
intervention, as these strategies represent clinically proven non-experimental behavioral strategies with no 
perceptible harm. Recorded nurse observations, actions taken and observed outcomes will include all unit 
residents and will be recorded using the technology system to support staff-level interventions for any resident 
with a sleep behavioral issue. All staff input into this system is done without resident identification.  
 
B7. Vulnerable Subjects 
Nursing facility residents are a vulnerable group; however, the procedures employed in this clinical trial are low 
risk and have been successfully employed without incident in a number of other studies by this research team 
as well as by other investigative teams. We have specifically targeted this group because sleep disorders are 
more prevalent in nursing facilities and the adverse effects of poor sleep may be greater for this group as well. 
 
C. Methods & Procedures 
C1. Methods & Procedures 
Randomization of SNF units: Randomization of the six units will be a two-step process, using a sequence 
generated by the study statistician (Mitchell). The order of the three facilities will be determined randomly 
before the order of the units within each facility is determined randomly. Dr. Michael Mitchell (UCLA) will 
maintain the sequence, which will be revealed immediately before the intervention begins at each facility to 
preserve “allocation concealment” for those involved with data collection or intervention.  
 
 
Unit Level Study Procedures: The study process will involve eight steps (A–H) for each unit, some of which 
run concurrently (Figure 4). The first three steps will begin as soon as possible after randomization.  
 
Step A. Each unit will identify a “sleep improvement team” with representatives from all three shifts (days, 
evenings and nights) in addition to other facility staff members. They will first identify a team leader for each 
shift, address issues of team membership, and establish expectations for engagement and program 
participation. Given that facility staff include individuals from the many different disciplines who have direct 
resident contact, the best strategies for implementation require an interdisciplinary team that is empowered to 
use the trainings to identify solutions for successful implementation of the sleep improvement program. To 
ensure healthy team functioning, we will facilitate identification of team leadership or a Sleep Champion for 
each unit. Based on our experience, we anticipate that this will be the unit nurse but the team itself will dictate 
who serves as team leader.78 Since this study is based on a “quality improvement” framework, no 
personally identifiable data will be collected from facility staff who participate on the sleep team, and 
because this aspect of the project is a quality improvement intervention, informed consent will not be 
obtained as the staff are not considered research subjects. Participation at the facility-level is “non-
experimental” and is part of that facility’s engagement in quality improvement. As such, nursing home staff are 
not considered to be study team members, nor are they considered study participants. Nonetheless, we will 
take multiple steps to avoid coercion including ensuring that use of the technology is voluntary and any related 
measurements will be only in aggregate. 
 
Our research team has conducted multiple meetings at each facility to establish relationships with medical 
directors, directors of nursing, chief administrators, and representatives from social work, occupational/physical 
therapy and psychology. In addition to these individuals, cross-disciplinary care-delivery teams from each 
nursing unit will be formed and mentored to establish a sleep improvement program (See Draft SLUMBER 
Manual—Appendix 1). Participation on the sleep team will be described as voluntary. Based on our prior 
experience, we expect a high level of interest from facility staff. Members of day-shift and night-shift staff will 

SLUMBER Protocol V.8/27/2018 
11 
 
have brief twice-monthly shift change meetings to discuss strategies and specific sleep-related problems that 
cross shifts (e.g., daytime napping) and strategies that positively impact sleep-related staff efforts required on 
any shift (e.g. avoiding caffeine).  
 
Step B. A research assistant (RA) from the NYU site will consent unit residents and collect observational, 
survey, and actigraphic baseline data. These metrics are described in detail below. We will attempt to obtain 
consent on each unit 
during the baseline 
pre-intervention 
period from all 
residents. Severely 
demented residents 
do not reside in the 
units chosen for the 
SLUMBER 
intervention; 
however, we 
anticipate some 
residents will have 
some level of 
cognitive 
impairment. Dr. 
Chodosh, (a 
cognitive and 
capacity specialist) 
will train research 
assistants in the 
methods of 
capacity 
assessment). 
Research 
assistants will 
assess capacity for 
all residents by using Evaluation to Consent assessment tool ( Appendix 9). Dr. Chodosh will be 
available to make final determinations related to capacity to consent for participants based on the 
information collected with Evaluation to Consent tool , For those residents indicating a wish to 
participate but who are unable to demonstrate capacity, the Research Assistant will notify the facility 
to approach legal surrogates with an informational letter and self-addressed, stamped postcard to 
indicate a willingness or refusal to receive a phone call where the research assistant will explain the 
study and request consent for that resident to participate (see Appendix 2 and F. Subject Identification, 
Recruitment and Consent/Assent). Due to the time sensitive nature of the research, any surrogate who 
does not return the postcard within 10 days from postmark will be called by a Research Assistant. 
Verbal consent will be obtained via the phone (see Appendix 3 Surrogate Verbal Consent). Consent will 
be for agreement to wear a wrist actigraph, observation, and provide brief interview responses at baseline, 
post-intervention, and at 3 and 6-month follow-up. Our procedure to assess capacity to consent for research 
has been used in several prior studies. We note that even some patients with moderate levels of cognitive 
impairment have the capacity to consent and we will use standardized IRB-approved protocols for conducting 
this capacity assessment. 
Inclusion criteria for residents are: 1) living in the unit of intervention, 2) ability to communicate and follow 
simple commands, 3) English- or Spanish-speaking, and 4) capacity to consent assessed with standard 
questions used to assess capacity or having a surrogate who can provide consent.  
 

SLUMBER Protocol V.8/27/2018 
12 
 
Exclusion criteria include: 1) obtunded or comatose state, 2) inability to communicate verbally, 3) inability to 
consent and without surrogate, and 4) non-English and non-Spanish speaking. In keeping with QI strategies, 
all residents will be exposed to the environmental aspects of the intervention, as these strategies represent 
clinically proven non-experimental behavioral strategies with no perceptible harm. Recorded (anonymous) 
nurse observations, actions taken and observed outcomes will include all unit residents and will be recorded 
using the technology system to support staff-level interventions for any resident with a sleep behavioral issue. 
All staff input into this system is done without resident identification.  
 
Step C. The collection of unit-level environmental data will focus on noise levels and documentation of resident 
symptoms in the MDS 3.0 (described below). MDS data will be de-identified and linked through unique random 
numbers. Data will include the routinely collected measures (MDS 3.0) by the facility on all consented residents 
as well as data from scheduled evaluations by research staff of residents who have consented to participate in 
evaluation components that are not part of usual clinical care. We have successfully employed this type of 
nested design for data collection in prior research. Federally mandated MDS 3.0 data is collected by the facility 
for all residents at admission and quarterly thereafter.  We will obtain these data covering the time period of 
last collection beginning just prior to the introduction of the SLUMBER intervention, and ending at the 
conclusion of all data collection at each study site (nursing facility unit). 
 
Steps D, E and F will comprise the SLUMBER intervention program itself. This process will begin as soon as 
the sleep team is identified, and will continue in sequence. Besides a “menu” of sleep improvement 
procedures, we will present the 3-component SLUMBER intervention to unit staff: 1) Improving the 
nighttime sleep environment; 2) Increasing patient activity levels during the day and reducing daytime 
behaviors that lead to sleep disturbances at night; and 3) Identifying and assisting individual residents 
experiencing difficulties with sleep. We will deliver the intervention over 3 months including the provision of 
five mentoring sessions and data feedback, which will cover the 3-month intervention period. 
 
Table 3 shows the three components, outlining the workshop content (D): targeted changes within the facility; 
examples of strategies staff members might identify (E; from our preliminary work); and use of data for 
feedback and mentoring (F).  
 
Steps G and H will follow the 3-month intervention period. Resident (actigraphy, resident-reported symptoms 
and observation) and unit level measures (MDS 3.0) will be collected as “post-intervention” data for analysis. 
 
 
C2. Additional features of the SLUMBER intervention: 
Use of Technology to enhance SLUMBER: A key innovation in the proposed study is to use technology to 
display real-time data, based on our positive experience with improving depression care.3 Staff recording of 
sleep-related problems and actions to address these problems (using simple drop-down lists) reinforces 
program fidelity and provides the research team with a measure of program utility. In other words, the research 
team will be able to know whether staff are identifying problems and implementing the environmental and 
therapeutic strategies of SLUMBER that they have been coached to use by the team of mentors because 
these strategies will be recorded using technological applications within a HIPPA compliant web-based 
platform (CaseWorthyTM). This platform will support staff use of behavioral strategies as well as feedback from 
decibel meters that are strategically placed around the unit. Ongoing environmental monitoring with 
immediate staff feedback is a key advantage of this intervention. An additional advantage of this platform 
is easy access to the training content that has been provided during team meetings. These will include 
PowerPoint presentations as well as video-recorded recommendations from mentors. During the 3-month 
intervention period, staff will also be able to send video, voice, or text messages to the mentors and receive 
responses to their questions within 24 hours. In this way, they will be better prepared to deliver the SLUMBER 
program and will increase their knowledge and abilities while improving the likelihood of sustainability over 
time. Giving staff this type of technological support is likely to further their engagement and empowerment 
enabling a stronger staff-delivered program.82-85 
 

SLUMBER Protocol V.8/27/2018 
13 
 
Decibel meters will be placed in at least 3 locations per unit, dependent upon the physical layout of the unit. 
These meters have BluetoothTM capability and will upload data in real time to the web-based platform, with 
archived data display comparing noise levels over time and across days for each unit. We will also place 
decibel meters in resident rooms and provide staff with a free decibel meter smart phone app for personal use 
when there is concern about noise levels and they are not near the data display. In addition to a decibel meter 
smart phone application, we will provide staff with free light meter applications so that they can identify and 
record nighttime light levels and take steps to reduce light as a potential sleep-disruptive factor. Staff will utilize 
all technological assists on a voluntary-only basis.  
 
Environmental scan and monitoring for sleep promotion: As in our prior work, we will link Decibel Meter 
data to recorded sleep at night (based on actigraphy) using decibel meters placed in the rooms of residents 
who consent to actigraphy recordings. While these data may not be immediately available, staff can review 
decibel levels as they relate to resident sleep during mentoring meetings. Using unit decibel meter data, staff 
behaviors and environmental problems such as a noisy door that creaks when opened or bangs when closed 
can be identified and corrected. The unit Sleep Champion will be armed with data to recommend actions to 
reduce unwanted noise. These data, which will also be presented at unit meetings, provide an opportunity for 
more public display and encourage staff engagement and participation. 
 
 
Recorded data and presentation for unit staff use: Recorded data and presentation is in reference to staff 
observations that are recorded on a web-based platform and environmental data from decibel meter output. 
We will provide a dropdown list of possible observations about sleep related behavior, appropriate actions to 
be taken for those behaviors, and observed outcomes. For example, one observation from the dropdown will 
be: “resident still awake [X time] after going to bed”; possible action taken: “asked if resident needs anything” 
or “encouraged resident to get out of bed for quiet activity until sleepy”, outcome: “resident sleeping [X time] 
later”. (See Appendix 4 for sample of Behavioral Monitor dropdown choices.) Recorded data will include 
location, time stamp for data entry, and time of observed behavior, action taken, and observed outcome, again 
using dropdown menus for simplicity. This tool will provide additional information on which interventions 
worked for which residents. These data will also be displayed as counts on a graphical interface (bar and linear 
graphs) for staff to review. Graphical display will include the most recent 24 hours, and any number of historical 
days back to one week before implementation of the intervention on the unit. Staff will be able to see trends in 
how strategies were used and identify additional actions to be taken.  
 
 
Directed Interventions: Staff will also have the benefit of pre-intervention RA observation results, which can 
be loaded into the web platform as anonymous data only. These data will be presented using the same 
categorical dropdowns that staff can use for their observations. With permission from the residents (or proxy), 
we will provide pre-intervention resident reported and actigraph results (for those who consent) to enable staff 
to target residents with sleep difficulties. 
 
 
Unit Meetings—content and structure (Part of Step D, above): We will conduct unit team meetings for 
SLUMBER training, explanation of sleep improvement strategies, and use of installed technologies. We will 
provide Sleep Champions (typically unit nurses) with additional training as needed so that they can serve as 
“content experts” and reinforce sleep strategies. Members of the professional mentor group (Drs. Chodosh 
(JC), Martin (JM), Cadogan (MC), and Brody (AB)) will meet with each intervention unit team five times: one 
pre-intervention introduction and training session (in person); three intervention period meetings at the 
beginning each month (JM and MC by phone/videoconference, others in person) for additional sleep related 
education, review of strategies, shared experiences, problem sharing, and team-based solutions; and one post 
3-month intervention period for follow-up and closure (in person). Drs. Martin and Cadogan will travel to NYC 
for in-person meetings. Facilitation strategies include modeling cross-discipline collaboration between mentors, 
identifying and nurturing team leaders and leadership skills, and facilitating contributions from all team 
members. Training meetings will be recorded for review by those who cannot attend and for reinforcement 
during and after the intervention period. Additional training on sleep promotion strategies will be stored and 
delivered as “on-demand” education using the web-based platform. This web-platform approach will serve as a 
model for a scalable program. Access to expert clinical support through an easy-to-use communication system 

SLUMBER Protocol V.8/27/2018 
14 
 
with timely responsiveness for all unit shifts should also serve to build stronger and more engaged teams by 
demonstrating the importance of the team’s collective work. The mentor team will address sustainability issues 
at the fifth and final meeting at the end of the 3-month intervention. 
 
Intervention monitoring and follow-up includes three activities: 1) on-line recording of web-based data for 
ongoing assessment of intervention fidelity; 2) monthly unit-level team meetings for reviewing recorded 
observations and decibel data, to facilitate review and reinforcement of the sleep program implementation; and 
3) web-based “office hours” for recorded staff questions and responses by the sleep experts. 
 
C3. Data Collection Overview: Data collection includes the use of resident worn devices (actigraphs) that will 
download 3 days of data onto a computer interface collected at baseline, post-intervention, 3-months, and 6- 
months follow-up. Resident survey data and RA 3-day observations will be collected during the same time 
intervals. Decibel meters will link to a software platform via BluetoothTM for continuous monitoring. Specific 
MDS 3.0 survey items that are collected quarterly by SNF staff will include the measures most proximal to and 
preceding baseline assessments. The RA will enter de-identified data from each in-person survey into a 
HIPAA-compliant REDCap electronic database hosted at NYU.86 REDCap data will be electronically linked to 
MDS data. Throughout the study period MDS data will be collected from each SNF’s data storage. DataCore, 
formed in collaboration with the NYU Langone Medical Center (NYULMC) Clinical and Translational Science 
Institute (CTSI), the Biomedical Informatics and Translational Library Programs, and the Department of 
Population Health, will provide enterprise level support to ensure data integrity during its capture, storage, 
management, extraction, and sharing. DataCore will merge these multiple data streams using unique study 
participant identifiers and will provide regular backups onto a secure server. Dr. Mitchell (study statistician) will 
access the data using remote desktop connection into NYULMC’s secure Virtual Desktop Infrastructure (VDI). 
The VDI will be configured so that all analyses and derivative datasets performed by Dr. Martin will remain 
within the NYULMC datacenter. 
 
Sources of materials: All data that is planned for collection will be obtained from surveys or interviews, wrist 
actigraphy, unit observations that are de-identified and administrative data all of which are maintained in 
electronic secure databases. Consenting subjects will participate in up to four actigraphy measurement 
periods, four observations, and four surveys collected during a 9-month period, depending on when they enter 
the study (determined by randomization procedures) and whether they leave the facility prior to the completion 
of the study period. 
 
We will obtain all data through computerized assisted interview instruments (CATI), observation instruments, 
directly downloaded actigraphy data, and electronic transfer of MDS 3.0 data. This enables all data to be 
stored in electronic files that are physically separate from any identifiable data. These data will be kept on a 
password-protected encrypted server that will be accessible the research PI and statistician. Data will 
maintained with a unique linking ID kept by the study team in locked files and used later for analytic 
assignment of the randomization status. DataCore will merge all data streams using unique study participant 
identifiers and will provide regular backups onto a secure server. Dr. Mitchell (study statistician) will access the 
data using remote desktop connection into NYULMC’s Virtual Desktop Infrastructure (VDI). The VDI will be 
configured so that all analyses and derivative datasets performed by Dr. Martin will remain within the NYULMC 
datacenter. This strategy provides a high level of data security. (See Data Storage and Confidentiality). 
 
C4. Primary Outcome Measures:  
The primary outcome measures are listed here (See Appendix 5 for a table of all outcome measures): Primary 
Aim 1: percent and hours of sleep at night, percent and hours of sleep during the day (i.e., napping), time in 
bed at night, nighttime awakenings; Primary Aim 2: PSQI total score87, 3 subscale scores, BADS depression 
and anxiety factors88, MDS PHQ-989 and Pain Assessment Interview; Primary Aim 3: BCAT 21-item 
instrument88, BIMS 7-item instrument66, ADL 10-item instrument90, percent of daytime observations of sleep 
and other activities; and Primary Aim 4: noise (decibel levels) and bright light (Lux) exposure. 
 
 
Primary Aim 1 measures – Objective sleep assessment: Wrist actigraphy: Participants will wear an 
actigraph on the dominant wrist for at least three consecutive days and nights. The actigraph is a small watch-

SLUMBER Protocol V.8/27/2018 
15 
 
sized device useful in longitudinal, naturalistic assessments of sleep-wake patterns.91 Actigraphs are 
commercially available devices with tri-axial accelerometers used to assess movement. Whereas wrist activity 
below an established threshold is interpreted as sleep, high wrist activity is interpreted as wakefulness. 
Commercially available software uses validated algorithms to determine the likelihood of sleep versus 
wakefulness during each recorded minute. We have experience with over 1,000 recordings with the device we 
propose to use here, and have procedures and protocols in place that have reduced the rate of data loss due 
to human or device error to 1-3%.  
 
Wrist actigraphy has been validated as a measure of sleep in numerous studies, and use of this technology is 
guided by evidence-based guidelines.91 Previously reported agreement between wrist actigraphy and 
polysomnography scoring of sleep variables (e.g., total sleep time) is .89–.95.92 We have developed highly 
standardized research procedures and protocols to use and score actigraphy for research applications 
(Actigraphy Study Manual, Appendix 6), and we have trained, experienced members of our research team to 
apply these protocols. In our prior work, SNF residents tolerate the actigraph devices well. As in our prior and 
ongoing work, we will perform careful visual review of raw actigraphy data to eliminate technical (device failure) 
and situational (e.g., device removed) artifacts, prior to scoring sleep with validated algorithms within the 
software that accompanies the device. Key variables (Appendix 5): Percent and hours of sleep at night, 
percent and hours of sleep during the day (i.e., napping), time in bed at night, nighttime awakenings. 
 
 
Primary Aim 2 Measures – Symptoms include subjective sleep quality, mood, and pain, using patient-
reported measures. This will include RA administration of questionnaires as well as quarterly facility-collected 
measures as part of the federally mandated MDS 3.0.  
 
Subjective sleep quality: Pittsburgh Sleep Quality Index (PSQI):87 The PSQI is a widely-used 18-item 
questionnaire that assesses sleep quality and disturbances over the last month. The PSQI measures sleep 
quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping medication, and 
daytime dysfunction. The PSQI has a sensitivity for distinguishing normal and abnormal sleepers of 89.6%, 
and a specificity of 86.5% (k=.75, p<.001).87 The PSQI also has good test-retest reliability over 1 month (r=.85; 
p<.001).87 We will use the three-factor scoring system, which has superior psychometric properties compared 
to the original seven-factor scoring system.93 We will ask residents and nightshift staff to complete the PSQI 
independently. Though many residents will have some level of cognitive impairment, the PSQI has been 
successfully used in subjects with mild-to-moderate dementia.94-96 Resident reported sleep quality will be a 
main outcome measure (PSQI total score). 
 
Mood: We will assess mood in two ways: 1) the Patient Heath Questionnaire 9-item89 (PHQ-9) and 2) the Brief 
Anxiety and Depression Scale88 (BADS). The PHQ-9, part of the MDS 3.0, is a 9-item, 4-minute, resident 
interview, and for those that cannot self-report (PHQ-9 OV) is used as an observation instrument. In the MDS 
development studies in 71 SNFs,66 86% of the 3258 residents completed the instrument and agreement 
between PHQ-9 and a gold standard measure was very good (weighted κ=.69, 95% CI=.61-.76).97 Similarly, in 
residents with severe cognitive impairment, correlations with the criterion standard Cornell Scale98 were very 
good to excellent for both the PHQ-9 (.63) and the PHQ-9 OV (.84). The BADS is an 8-item, 3-minute scale 
that is an additional measure for depression and generalized anxiety. Among 227 individuals living in a SNF 
(n=179) or assisted living (n=98), age: 61-102 years, mean depression score was 2.05 (range=0-6; SD=1.39); 
the mean anxiety score was 2.47 (range=0-8; SD=2.32). Using a gold standard comparator, a depression 
score of >2 had a sensitivity of .76 (.67-.81) while for generalized anxiety, a score of > 4 (range: 0–10) had a 
sensitivity of .73 (.62-.82) and a specificity of .81 (.73-.87).88 Pain: The MDS Pain Assessment Interview 
inquires about the presence of pain (yes/no), pain duration (past 5 days), effect on function (yes/no), and 
intensity (mild to very severe: range=1-4). Key variables: PSQI total score, 3 subscale scores, BADS 
depression and anxiety factors, MDS PHQ-9 and Pain Assessment Interview. 
 
 

SLUMBER Protocol V.8/27/2018 
16 
 
Primary Aim 3 Measures – Function: Cognitive performance will be measured using a targeted sleep-related 
cognitive instrument (described below) in addition to the already collected MDS measure of cognitive function, 
the Brief Interview of Mental Status (BIMS). BIMS was developed for MDS 3.0 by Dr. Chodosh and has 
been validated in SNF populations with excellent test characteristics compared to the gold standard 3MS.99 In 
the MDS 3.0 feasibility and validation study,66 the BIMS had 90% completion for 3,258 residents and 
correlation with the criterion measure (3MS) was high (.91, p<.0001). The Brief Cognitive Assessment Tool 
(BCAT)100 is a 21-item instrument that can be administered in 10–15 minutes. Scores range from 0–50 and a 
score <38 is indicative of dementia. This instrument is 
sensitive to the full spectrum of cognitive function (Table 4) 
and has demonstrated excellent internal reliability 
(Cronbach’s α=.92) and test-retest reliability (r=.99), making it 
particularly suitable for repeated measures. This instrument 
measures sleep-related cognitive domains of contextual 
memory, executive control, and attentional capacity with the 
ability to distinguish mild cognitive impairment from dementia 
and functional states of instrumental activities of daily living 
(IADLs). Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) are 0.99, 0.77, 0.91, and 
0.96, respectively with mean scores across three diagnostic categories of MCI, mild dementia, and moderate 
dementia being significantly different.  
 
Resident engagement in facility activities will be assessed with RA observations at 15-minute intervals 
using a standardized observation form from our prior studies (Table 1 and Appendix 7). Observations will be 
conducted on the facility unit over an 8-hour day for three successive days. For each participant, the following 
observations will be documented: being asleep, in bed, in one’s own room, involvement in a social activity, 
having a conversation with another person (resident or staff), and doing a physical activity (e.g., walking, group 
exercise). We will compute the proportion of time in each activity as the percentage of total observations made 
for that resident (e.g., percent observations asleep out of 96 total observations over 3-days). Key Variables: 
BCAT 21-item instrument100, BIMS 7-item instrument66, ADL 10-item instrument90, percent of daytime 
observations of sleep and other activities 
 
 
Primary Aim 4 Measures – Sleep improvement strategies will be measured as degree of reduction in 
nighttime noise (by decibel meters), light exposure (lux recorded on actigraph watches), and staff recorded 
observations/actions on the web-interface. The strategically placed decibel meters (dictated by anticipated 
noise areas, e.g., nurses station and unit layout and in rooms of consented residents) will measure and 
continuously record the frequency of noise by decibel level and time of recording with frequency counts noted 
at greater than 50 and 60 decibels. The WHO recommended bedroom noise for single event noise is less than 
45 decibels.101 During the day we will determine the number of minutes residents are exposed to light >1000 
lux and the proportion of observations for which residents are NOT in bed. 
 
 
C5. Other Measures: Other measures will be considered potential covariates, including acute illness events 
and hospital days during the study, Charlson comorbidity102 index diagnoses (as recorded in MDS 3.0 during 
the study period), demographics, and length of SNF stay (days) from medical records. SNF administrative files 
will provide data on use of sedative hypnotics (FDA-approved sedative-hypnotics, over-the-counter sleep 
medications, “off-label” medications, and benzodiazepines) and will be measured as change in use over time. 
 
C6. Data Analysis and Data Monitoring 
Data Analyses: The outcome variables in the study can be categorized as scheduled study assessments 
(e.g., those measured at baseline, and post-intervention and 3 and 6 month follow-up) and routinely collected 
measures (MDS 3.0 variables measured on a quarterly basis, collected by the facility). Analysis strategies for 
each type of measure are described below. Hypothesis 1 outcomes (wrist actigraphy) are scheduled study 
assessments. Hypothesis 2 outcomes include both scheduled study assessments (PSQI87 and BADS88) and 
routinely collected measures (PHQ-989 and Pain Assessment Interview). Hypothesis 3 outcomes include both 
scheduled study assessments (BCAT100; observed engagement in Facility Activities) and routinely collected 

SLUMBER Protocol V.8/27/2018 
17 
 
measures (BIMS66; ADLs90). Hypothesis 4 outcomes are scheduled study assessments (Decibel meters; 
actigraphy-based light meters, recorded staff interventions for residents with sleep-disturbed behaviors). 
 
 
Analysis of Scheduled Study Assessments: Mixed-effects models will be used to assess improvement in 
sleep outcomes due to the SLUMBER intervention. When applied to repeated measures designs, mixed-
effects models accommodate incomplete data across time points (e.g., due to resident death) and can permit 
specification of a wide variety of residual covariance structures.103 Each outcome will be analyzed using a two-
level mixed-effects model with time as a fixed factor having four levels (baseline, post-intervention, 3-months, 
and 6-months), and residents nested within SNF units. We will also conduct a sensitivity analysis that takes 
into account nesting of units within facilities. Non-independence of residuals across time will be modeled using 
a variety of covariance structures (e.g., unstructured, compound symmetric, autoregressive) by selecting the 
covariance structure that provides the best fit (according to the Bayesian Information Criteria). We will assess 
the primary hypothesis concerning the intervention effect by comparing the average baseline score to the 
average post-intervention and 3-month scores. We will test the secondary hypothesis concerning withdrawal of 
the intervention by comparing the 3-month to 6-month data. 
 
 
Analysis of Routinely Collected Measures: Routinely collected measures (for all consented residents on 
intervention units) will be analyzed using a three-level model in which time is nested within resident and 
residents are nested within SNF units.104 A sensitivity analysis will consider a model in which a fourth level of 
units nested within facilities is considered. The three-level 
model will include two key time varying predictors: Intv, 
coded as 1 if the intervention is implemented in the current (or prior) 3-month 
period; and otherwise coded as 0. IntvQtr will be the number of quarters since 
the intervention was applied. We will examine the nature of growth in the 
outcome as a function of IntvQtr and introduce terms to account for non-linearity 
as needed. The model to be fit, expressed as a 3-level model fits the "jump" in 
outcome due to the introduction of the intervention (via the coefficient for γ100) as 
well as the "slope" over time due to the intervention (via the coefficient for 
γ200). To examine the impact of removing the intervention, we will further 
consider a model that introduces two additional time varying covariates 
(not shown): RemInt coded as 1 if the intervention was removed in the 
current (or prior) 3-month period, and otherwise coded as 0. This 
accounts for any deterioration in sleep outcomes when the intervention is 
ended. RemIntQtr: is the number of quarters since the intervention was 
removed, capturing the change in the slope over time. We will examine 
the nature of growth in the outcome as a function of RemIntQtr and 
introduce terms to account for non-linearity as well. 
 
Power Analysis: The purpose of this study is to discover clinically 
meaningful effects. Using guidelines from Cohen,105 who describes 
standardized effects of .80 as large, .50 as medium and .20 as small, we 
consider standardized effects >.60 to be clinically meaningful. Our power 
analysis is designed to detect effects of this size or larger. For this study, the 
final sample size (i.e., the number of people who do not withdraw from the 
study) and the Intra-Cluster Correlation (ICC) regarding the people within 
units were used to determine power. The final sample was determined by 1) 
the number of participants in the unit, 2) the consent rate, and 3) the attrition rate. Using the expected unit size 
of 40, Table 5 shows the final sample size as a function of consent and the attrition rates. These final sample 
sizes (per unit) are used in the following power calculations (which assume six units, 80% power, alpha of .05, 
and 2-tailed tests). 
 
 
Power Analysis of Scheduled Study Assessments: For the analysis of the scheduled study assessments, 
the primary analysis will test the average of the outcome at baseline versus post-treatment and 3-months. The 
Level 1 (time) Outcomeijk=π0jk+π1jk(Intv)+π2jk(IntvQtr)+eijk  
Level 2 (person) π0jk=β00k+r0jk  
 
              π1jk=β10k  
 
              π2jk=β20k  
Level 3 (unit) β00k=γ000+u00  
 
         β10k=γ100  
 
         β20k=γ200 

SLUMBER Protocol V.8/27/2018 
18 
 
standardized effect that could be detected was computed as a function of the final sample size per unit 
(drawing values from Table 5) and the ICC. These values are shown in Table 6,77 where shaded cells reflect 
conditions that achieve sufficient power to detect an effect of d=.60. For example, the rightmost column of 
Table 6 (final N=18) shows that this final sample size will have sufficient power to detect an effect of .60 or 
smaller across all ICC values considered. Referring to table 5, a final N of 18 is achieved with a 60% consent 
rate and a 25% attrition rate. Considering a final sample size of N=14, Table 6 shows that the study would 
have sufficient power to detect an effect of .6 or smaller when the ICC is .20 or smaller. Table 5 shows that a 
number of combinations of consent rates and attrition rates achieve a final sample size of 14 or larger. Finally if 
the ICC (from Table 6) is as low as .10, a final sample size of N=12 would have sufficient power to detect an 
effect of .60 or greater. In this case, all of the cells in Table 5 achieve a final sample size of N=12 or larger. 
While it is not possible to definitively determine the enrollment rate, attrition rate, and size of the ICC in 
advance, Tables 5 and 6 show that most plausible combinations of values would yield sufficient power to 
detect an effect of .60 or greater. 
 
 
Power Analysis for Routinely Collected Measures: For the analysis of routinely collected measures, the 
primary outcome concerns the test of the average of measures prior to the 
implementation of the intervention compared with the average of the measures after 
the implementation of the intervention. Using six steps in the stepped wedge design, 
the detectable standardized effect associated with the introduction of the 
intervention (the primary hypothesis) was computed as a function of the final sample 
size within each unit (columns) and the intra-cluster correlation (rows) shown in 
Table 777. All conditions specified have the ability to detect a medium or smaller 
effect (< .50). The smallest final sample size of N=10 provides sufficient power to 
detect an effect of 0.60 or smaller. Referring to Table 5, we see that all 
combinations of consent rate and attrition rate yield a final sample size of 10 or 
larger. Based on the results of Tables 7 and 5, the analyses for the routinely 
collected measures will have sufficient power to detect a clinically meaningful effect 
(i.e., a standardized effect of .60 or smaller).  
 
 
Threats to Internal Validity: If outcomes improve with SLUMBER, we will consider explanations alternative to 
the treatment effect. While unlikely, residents may improve over time unrelated to the SLUMBER intervention. 
Use of routinely collected measures (MDS) will be investigated to identify possible improvements prior to the 
introduction of the intervention. MDS measures will also counterbalance the influence that the act of measuring 
has on the outcome since these measure are collected within routine care. Individuals with poorer outcomes 
might withdraw due to refusal, discharge or death, thereby creating an illusion of improvement. We will test for 
systematic attrition by comparing baseline scores of those who withdraw to those who remain. The stepped 
wedge design staggers introduction of the intervention to mitigate this threat. Spillover training and effects from 
one unit to the next unit in the same facility not yet engaged are also possible. We will include “manipulation 
checks” measuring intended changes between units (e.g., noise reductions) to assess whether contamination 
of sleep strategies occurred in the second unit at a facility before introducing SLUMBER to that unit.  
 
C7. Data Storage and Confidentiality 
Data management and quality control are achieved through our electronic data capture and immediately 
downloaded survey data using computer-assisted data interviewing (CATI). We will conduct monthly data 
quality checks examining for missing data and out-of-range variable output. 
 
The study PI (Chodosh) will conduct periodic data quality checks for data storage security and will conduct 
weekly reviews with the RA and study coordinator to identify potential issues with subject consent and 
assessment procedures. The New York University Langone Medical Center (NYULMC) Clinical Research Data 
Management Core (DataCore) will conduct the data management and data quality assurance activities for the 
SLUMBER study. DataCore personnel have been providing data management support for a combined 50-60 
FDA-regulated phase 1 to 4 randomized clinical trials as well as numerous investigator-initiated and National 
Institute of Health (NIH) funded studies. The primary objectives of the DataCore data management 

SLUMBER Protocol V.8/27/2018 
19 
 
methodology are to ensure the completeness and integrity of all study data. To accomplish these objectives, 
DataCore will provide a comprehensive data management methodology combined with planning, control, and 
coordination with site staff. 
 
DataCore will develop study Case Report Forms (CRFs) in collaboration with the principal investigator, to 
standardize collection of survey data. A comprehensive web-based electronic data capture (EDC) system (e.g., 
REDCap) will be programmed to process, edit and store study data in a centralized database within NYULMC. 
Each clinical site will enter de-identified data from their corresponding participants directly into the EDC and will 
not be able to access data from the other sites. DataCore personnel will implement rigorous data validation 
checks using the EDC system to ensure the highest possible level of data accuracy. The EDC System will be 
implemented under the spirit of CFR-21 part 11 compliance, with built-in electronic audit trail that maintains a 
permanent record of all additions, modifications, and deletions of data throughout the life of the study. The 
system is in compliance with the primary regulatory organizations governing the handling of clinical research 
study data and is compliant with Food and Drug Administration data systems requirements. 
 
Additional data from the sites (e.g., actigraphy) will be transferred directly to DataCore using a managed file 
transfer (MFT) platform from Globalscape. The MFT has been implemented at NYULMC to provide enterprise-
level security for inter-site collaboration, with built-in regulatory compliance and governance to ensure data 
safety. DataCore will merge these multiple data streams using unique study participant identifiers and will 
provide regular backups onto a secure server. This secure server utilizes state-of-the-art firewalls and data 
encryption services. Moreover, these data are stored without identifying data. A linking file is kept in a separate 
secure electronic location and contains only data linking information but no other study or clinical data. All data 
that is transferred to DataCore will remain in the NYULMC datacenter. Dr. Mitchell from UCLA will access the 
data using a remote desktop connection into NYULMC’s Virtual Desktop Infrastructure (VDI). The VDI will be 
configured so that all analyses and derivative datasets performed by Dr. Mitchell will remain within the 
NYULMC datacenter. No UCLA individuals will have access to identifiable PHI of study participants.  
 
NYULMC’s state-of-the-art high-availability, high-performance offsite datacenter uses a network design based 
on Cisco Systems’ Nexus data center switches. Converged network architecture is optimized for virtualization 
and uses multiple zones to facilitate a multi-layered environment for additional redundancy and scalability. The 
data center network provides 10Gbit/sec connectivity to servers and to users in the main campus. Data 
security is integrated into the network design by segmenting web tier, application tier, and database tier 
servers. A next generation firewall system 
from Palo Alto Networks enables access 
control based on applications and user 
profiles; this granular, flexible security policy 
engine simultaneously enables better 
services and better security. 
 
C8. Project Management Plan and 
Timeline (Table 8) 
 
 
Our research team has been meeting 
regularly for 18 months and has been in close 
communication for the past year. We will 
continue to hold virtual weekly meetings 
throughout the study period and additional face-to-face meetings linked to New York trips by Drs. Martin and 
Cadogan to conduct SLUMBER trainings. We already use conference call systems, Adobe Connect, and video 
conferencing quite ably to facilitate communication across institutions. Given that data will be captured 
electronically in real time, we will be able to manage intervention procedures and data quality and to review our 
progress at weekly meetings. All key research team members will participate in all aspects of the study design, 
data analyses, manuscript preparation and manual creation for a multi-site dissemination. 
 
D. Risk/Benefit Assessment 

SLUMBER Protocol V.8/27/2018 
20 
 
D1. Risk 
No pharmacological intervention or medical procedures will be used in this study. Rather this study aims to 
provide mentoring to nursing facility staff to provide sleep improvement procedures, which are consistent with 
high quality clinical care.  
 
No interview data will be gathered without resident or proxy consent and although the study procedures are 
minimal risk, some questions may cause anxiety, embarrassment or be emotionally upsetting. The RA and 
Study coordinator will receive training in minimizing emotional impact or discomfort and will remind residents 
that they may discontinue participation or skip portions of the assessments that make them uncomfortable at 
any time. In the event of significant emotional upset, the PI will be notified and will intervene to address any 
concerns. A wrist actigraph could become uncomfortable to wear and with that complaint or concern, the 
device will be promptly removed. We have used the shortest possible recording period to minimize this risk. 
 
Subject loss of confidentiality is another potential risk in clinical trials like the one proposed here and with this 
type of data collection. However, our CATI data and other data collection methods are specifically designed to 
eliminate risk of such loss as no data are collected with personal identifiers. Linking files are stored separately. 
All study personnel will complete training in Human Subjects Research and HIPPA training prior to engaging 
with participants, and we have a strong record of quality assurance and maintained confidentiality from prior 
projects. (See C7. Data Storage and Confidentiality) 
 
D2. Protection Against Risk 
Any resident who refuses participation will not be approached again. Any resident who declines further 
participation once enrolled can request to discontinue participation and/or to have his/her data removed. Any 
subject may become upset, annoyed, or fatigued with interview questions, or use of actigraphy and we will stop 
gathering study data at the point that this occurs, only resuming if and when that subject is ready and willing to 
proceed. Our experience with these interview procedures, and wrist actigraphy indicates that this is unlikely to 
occur but we recognize this possibility and will respond as described. Residents can also request at any time 
that they not be observed (but note that these observations are done in a completely unobtrusive manner, 
something that we have successfully done in other studies). 
 
The principal investigator (PI) will provide additional risk protection through notifying the nursing facility about 
any health related issues that appear to be of an urgent or potentially life threatening nature. A process of 
study monitoring to review any procedural concerns or subject issues will be included at monthly meetings 
between the research staff and facility leadership. 
 
We will obtain approvals from the NYU Institutional Review Board (Human Subjects Protection Committee) 
prior to proceeding with any study procedures. We will also request an exemption from the UCLA IRB, since 
the only study activities carried out at UCLA will be analyses, and an ‘Adverse Events’ will be reported to the 
study IRBs and will include any medical event regardless of its relationship to the study intervention. 
 
D3. Potential Benefit to Subjects 
Our proposed research study will provide new information that will address our limited understanding of the 
measureable impacts of improved sleep. Should we be able to demonstrate improved symptoms among those 
residents who achieve better sleep, a dissemination of this sleep improvement program could lead to improved 
quality of life for thousands of nursing facility residents who suffer from negative symptoms that are 
exacerbated by poor sleep. 
 
This study will enable those engaged nursing facilities and their units to employ targeted practices to promote 
better sleep and those residents who reside on those units may benefit from an environment that is conducive 
to better sleep. This study poses minimal risk to subjects, since the study does not involve tests or treatments 
beyond that which they would normally receive as part of their normal care. Therefore, the benefits outlined 
above likely exceed the risks of participation in this study. 
 

SLUMBER Protocol V.8/27/2018 
21 
 
E. Investigator’s Qualifications and Experience 
The team of mentors will include Drs. Joshua Chodosh (NYU), Mary Cadogan (UCLA), Jennifer Martin (UCLA), 
and Abraham Brody (NYU). Drs. Chodosh and Cadogan have experience with the methodology for mentored 
intervention delivery, and Dr. Martin has content expertise on training providers from multiple disciplines on 
sleep improvement. Dr. Brody will contribute additional expertise on how to implement interventions into clinical 
care in nursing. This team of mentors, with complementary expertise, will work closely with the unit staff during 
the 3-month intervention period. (See also A4. Preliminary Studies) 
 
Personnel include research assistants (RA) who will be trained in the human subjects’ procedures of 
recruitment, consent, and protection of patient health information before participating in any research activities. 
All personnel have completed their human subjects training and will be thoroughly trained in the research 
protocol.  Drs. Chodosh (NYU) and Brody (NYU) have submitted their CVs and investigator financial disclosure 
forms. The UCLA researchers will submit through their respective IRB. The RAs for the NYU site will be added 
to this study via a modification submission once they are hired. 
 
F. Subject Identification, Recruitment and Consent/Assent 
F1. Method of Subject Identification and Recruitment 
The unit nurse will approach all unit residents and ask permission for our research assistant (RA) to approach 
each resident who agrees to that have that discussion. The RA will not approach any resident who has not 
given permission to the unit nurse. 
 
F2. Process of Consent 
Once the potential subject has been approached and approved by the Unit Nurse, the RA will approach 
the potential subject for consent. The RA will consent the subject verbally. We request a waiver of 
documentation of consent as we have done successfully for several other studies where there are issues of 
literacy and capability to consent in writing (e.g., due to arthritis or visual problems). Under these 
circumstances, consent is best obtained verbally and actually offers the opportunity to assess for capacity, 
which cannot be done as easily with written consent alone (see Appendix 8 Resident Script). A requirement of 
written consent would also unfairly discriminate against those who are not literate, have poor vision or have 
difficulties with fine motor tasks. 
 
The RA will assess the capacity of every potential subject after they have informed the potential subject about 
the study. The assessment includes questions about study participation expectations, risks and potential 
benefits, and what they can do if they feel discomfort (see Appendix 9 Evaluation to Sign Consent Form). 
 
Residents who lack capacity will be verbally assented after the surrogate consents (see Appendix 10 Resident 
Assent). The assent form will be kept secure with the surrogate’s consent form.  
 
F3. Subject Capacity 
The Research Assistant will assess capacity for all residents, and any resident who lacks capacity (see 
Appendix 9 Evaluation to Consent) will not be consented but the Research Assistant will provide the facility 
with the resident’s interest in participation but inability to demonstrate capacity in order to contact his/her 
identified surrogate via an explanatory letter and a self-addressed, stamped postcard, which will be mailed to 
the surrogate (see Appendix 2 Surrogate Postcard and Appendix 3 Surrogate Verbal Consent) if they 
otherwise meet inclusion/exclusion criteria. The facility will identify the resident’s legally authorized 
representative. The Research Assistant and/or PI will offer to meet the surrogate in person, but for the 
convenience of the surrogate, consent may also be obtained over the phone.  
 
Due to the time sensitive nature of the research, any surrogate who does not return the postcard within 
10 days from postmark will be called by a Research Assistant. Verbal consent will be obtained via the 
phone (see Appendix 3). Consent will be for agreement to wear a wrist actigraph, observation, and provide 
brief interview responses at baseline, post-intervention, and at 3 and 6-month follow-up. 
 

SLUMBER Protocol V.8/27/2018 
22 
 
Our procedure to assess capacity to consent for research has been used in several prior studies. We note that 
even some patients with moderate levels of cognitive impairment have the capacity to consent and we will use 
standardized IRB-approved protocols for conducting this capacity assessment. 
 
F4. Subject/Representative Comprehension 
Potential subjects will be told that their involvement in the study is completely voluntary and that they can 
withdraw from the study at any point. For all potential participants, we will assess the individual’s ability to 
provide informed consent using the interview procedures described in this protocol to assess capacity to 
consent for research. Some subjects may be too hearing impaired to communicate and with their permission, 
we may ask their proxy to provide informed consent or we may use assistive technologies or devices such as 
large-scale print materials or pocket hearing amplifiers to facilitate communication. 
 
F7. Documentation of Consent 
Once the RA consents either the subject or the surrogate, they will document their discussion. A signed copy 
of the informed consent (Appendix 11 Informed Consent Form) signed by the RA will be provided to the 
subject, and a copy will be provided to the surrogate when applicable. A second signed version of the informed 
consent document will be kept by the PI in a double-locked file cabinet that is accessible only to the PI and 
study coordinator.  
 
F8. Cost to Subject 
There are no costs for participation. 
 
F9. Payment for Participation 
Subjects will not be paid for their participation. 
 
Appendix Table 
 
1. SLUMBER Intervention Manual 
2. Surrogate Postcard 
3. Surrogate Verbal Consent 
4. Sample Behavior Dropdown Choices 
5. Outcome Measures 
6. Actigraph Study Manual 
7. Data Collection 
8. Resident Verbal Consent 
9. Evaluation to Consent 
10. Resident Assent 
11. English Language Consent Form 
 
 
 
 
 
 
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