final QT ppr published in JNN, Aug 2010

Copyright @ 2010 American Association of Neuroscience Nurses. Unauthorized reproduction of this article is prohibited.
Benefits of Quiet Time for NeuroYIntensive
Care Patients
Christina M. Dennis, Robert Lee, Elizabeth Knowles Woodard,
Jeffery J. Szalaj, Catrice A. Walker
ABSTRACT
The primary mission of any intensive care unit (ICU) is to provide critically ill patients with high-quality
care and an atmosphere in which to recuperate. However, all too often, the intensive environment, which
is often busy, chaotic, and noisy, may contribute to just the opposite. Patients overstimulated with noise,
lights, and other distractions often suffer from sleep deprivation. Research in medicine and nursing has
shown that sleep deprivation can have detrimental effects on an ailing patient. Therefore, a quiet time
program was developed in the neuro-ICU to reduce noise and light levels, with the ultimate goal to allow
sleep. Quiet time, a period of reduced controllable noise and light, took place twice daily coinciding
with circadian rhythms. The study included 50 neuro-ICU patients, 35 observed during day hours and
15 observed during night hours. Noise and light levels were measured at multiple locations before, during,
and after quiet time hours. Patients’ sleep behavior was recorded every half hour, beginning 1/2 hour
before quiet time until 30 minutes after. Analysis of data, adjusted for multiple testing and repeated
measures on patients, demonstrated significantly lower noise and light levels during day shift quiet time. In
addition, patients were significantly more likely to be observed sleeping during day shift quiet time hours.
S
leep is essential for energy restoration and
physical recuperation. During sleep, protein syn-
thesis and cell division organize, resulting in a
restorative process. Contemporary intensive care units
(ICUs) use highly trained staff and technological
innovations to provide high-quality care to critically
ill patients. However, the chaotic critical care envi-
ronment can often negatively affect these patients. For
example, in the ICU setting, nursing interventions
occur at least every hour and often much more fre-
quently. In fact, one study found that patients were
disturbed on average every 20 minutes, even while
sleeping (Cmiel, Karr, Gasser, Oliphant, & Neveau,
2004; DeKeyser, 2003; Edwards & Schuring, 1993;
Grumet, 1993; Guidelines for Intensive Care Unit
Design, 1995; Kahn, 1998; Mazer, 2006; Olson,
Borel, Laskowitz, Moore, & McConnell, 2001; Penney,
2004; Shattel, 2005; Tamburri, 2004; Topf, 2001; U.S.
Environmental Protection Agency [EPA], 1974). With
the average sleepYwake cycle being 90 minutes, such
frequent interruptions leave little time for rest. Stimuli
overload has been documented in numerous studies as
detrimental to the well-being of all patients, particu-
larly critical care patients (Tamburri, 2004).
The harmful results of sleep deprivation are nu-
merous, and it is one of the most common stressors
for intensive care patients. It can take as little as 24
to 48 hours for the body to begin reacting nega-
tively to a lack of sleep in the ICU patient (Olson
et al., 2001). As stress levels rise, serum cortisol
levels increase. This will result in the number of
circulating lymphocytes in the blood stream and func-
tioning monocytes to decrease; thus, natural killer cell
activity and cytokine production drop, resulting in a
depressed immune system (DeKeyser, 2003). Addi-
tional negative responses include alterations in
breathing and ventilation, vasoconstriction of periph-
eral blood vessels, gastrointestinal motility changes,
blood and urine chemical modifications, and an in-
crease in skeletal and muscular tension (Cmiel et al.,
2004). Furthermore, an environment of constant noise
and light stimulates the sympathetic nervous system
to release substances such as epinephrine and other
endogenous stimulants that, in turn, lead to an in-
creased heart rate and blood pressure. This constant
stimulation of excitatory neurotransmitter release can
be harmful to critically ill patients because it taxes an
already stressed body system (DeKeyser, 2003).
Volume 42 & Number 4 & August 2010 217
Christina M. Dennis, MSN APRN RN CCRN, is a neuroscience
clinical nurse specialist at the Adult Acute Care Nursing Services,
WakeMed Health and Hospitals, Raleigh, NC.
Questions or comments about this article may be directed to
Robert Lee, MS MA, at rolee@wakemed.org. He is a research
associate at the Clinical Research Unit, Emergency Services
Institute, WakeMed Health and Hospitals, Raleigh, NC.
Elizabeth Knowles Woodard, PhD MSN, is director of Nursing
Research and Evidence-Based Practice, WakeMed Health and
Hospitals, Raleigh, NC.
Jeffery J. Szalaj, BSN RN, is a staff nurse at the NeuroYIntensive
Care Unit, WakeMed Health and Hospitals, Raleigh, NC.
Catrice A. Walker, BSN RN, is a clinical educator and nursing
supervisor at the NeuroYIntensive Care Unit, WakeMed Health
and Hospitals, Raleigh, NC.
Copyright B 2010 American Association of Neuroscience Nurses

As early as 1993, Grumet reported that patients
demonstrated increased agitation when exposed to
increased stimuli and noise levels. Grumet (1993)
explained that the human ear, as a highly sensitive
organ, has auditory pathways that are rich with brain
stem and thalamic connections. These pathways lead
to the reticular activating system, which is the system
in the brain responsible for arousal and attention.
Thus, when noise levels are elevated or at a high pitch,
these pathways can become overloaded and lead to
increased restlessness (Grumet, 1993). Sleep depri-
vation has been linked to a rise in patient falls,
patients being more confused, and an increase in
medication and restraint use (Mazer, 2006). In 1974,
the EPA recommended that hospital noise levels not
exceed and average of 45 dB during the day and 35
dB during night hours (EPA, 1974). More than 30
years later, this recommendation remains the same.
Recent studies have assessed the level of noise in the
ICU in comparison with noises commonly heard in
daily living. Cmiel et al. (2004) reported that a
portable X-ray machine was louder than a motor-
cycle (98 vs. 95 dB, respectively), and other
common ICU noises such as telephones, pagers,
monitor alarms, and intercoms had noise levels
similar to the levels of heavy truck traffic (80 dB).
Routine conversation recorded at a nursing station
averaged at 60 dB (Lower, 2003). Cmiel et al.
reference a library at 50 dB, a quiet woodland at
30 dB, a whisper at 20 dB, and the threshold of
hearing at 0 dB. In one literature review, many
studies indicated peak hospital noise level to ex-
ceed 90 dB (Joseph, 2007).
In this study, a quiet time (QT) protocol was im-
plemented in an eight-bed neuro-ICU. The purpose
of this study was twofold. The first was to determine
if the implementation of a QT protocol twice a day
would reduce noise to the EPA-recommended levels.
The second was to determine if reducing light levels
and other impinging environmental stimuli would al-
low neuro-ICU patients to sleep or rest peacefully.
Methods
Setting
The setting for this study was in a large level 1
regional trauma center located in the central southeast,
which houses the busiest emergency department in
the state. The neuro-ICU was designed in the 1980s
and reflects the standard floor plan of the time. The
rooms are placed at the perimeter of a circle, with the
nursing station at the core. Individual patient rooms
are separated by a partition and from the core by a
curtain. As in most ICUs, most activity occurs in the
core, which is also the site for computers, telephones,
printers, and fax machines. In addition, several patient
rooms have higher levels of noise because of their
proximity to automatic exit doors and the staff lounge.
Photographs are included in Figures 1 and 2.
Sample
The study occurred throughout the spring and fall
of 2008. Potential participants included patients
who were admitted to the neuro-ICU, were at least
18 years of age, and had a Glasgow Coma Scale
(GCS) of 10 or higher. Patients who were sedated,
had a GCS of less than 10, were less than 18 years
of age, or were being mechanically ventilated were
excluded. Once institutional review board approval
was obtained, patients meeting the inclusion criteria
were considered enrolled in the study and were
assigned a random number to protect their anonym-
ity. The study included 35 patients who were
observed during day shift hours and 15 separate
patients who were observed during night shift
hours.
The Study
The study consisted of two phases: (a) preinterven-
tion phase and (b) intervention phase.
FIGURE 1 Patient’s Room in the Neuro-ICUFIGURE 1
Note. The curtains in the front of the room provide for privacy but
are ineffective for noise.
Stimuli overload has been
documented in numerous studies
as detrimental to the well-being
of all patients, particularly
critical care patients.
Journal of Neuroscience Nursing218

Preintervention
Before implementing QT (the intervention), baseline
measurements of light and noise were collected.
These measures were followed by educational ses-
sions orienting neuro-ICU staff to the QT protocol.
Educational content included the effects of sleep
deprivation, EPA noise recommendations, and strat-
egies to reduce environmental stimuli. Education
was accomplished via one-to-one interactions be-
tween the staff, distribution of printed materials, and
posting of information in the staff lounge. Ancillary
departments affected by the new protocol were in-
formed and collaborated with nursing staff to reduce
interruptions during QT. The nursing staff and the
physicians, including neurosurgeons, neurologists,
critical care intensivists, and trauma surgeons, who
regularly admitted and/or consulted on neuro-ICU
patients, were educated regarding the intervention.
Other ancillary personnel oriented to the protocol
included environmental and nutritional services, hos-
pital volunteers, therapists (physical, occupational,
and speech pathologists), respiratory care services,
laboratory, and radiology. Education for patients and
their families included literature and personal expla-
nation from their care nurse.
QT hours were chosen on the basis of circadian
rhythms. Circadian (Baround the clock[) rhythms
are regular changes in physical and mental charac-
teristics that occur in the course of the day. The
body is at its lowest state during its circadian
rhythms, when propensity for normal physiological
sleep is at its highest. Therefore, it would make
sense to take a nap when the body is at its most vul-
nerable. Considering this, it was determined that QT
would occur during the day shift, specifically from
2:00 to 4:00 p.m., and during the night shift from 1:30
to 3:30 a.m. In the hospital setting, day shift hours are
generally considered between 7 a.m. and 7 p.m., with
night hours encompassing 7 p.m. to 7 a.m. Night shift
QT was modified from 2:00 to 4:00 a.m. to prevent
the interruption of regularly scheduled diagnostic tests
such as X-rays and CAT scans.
Intervention
The implementation phase began in the early spring
of 2008 and ran for six consecutive months. At the
onset of each period of QT, lights were turned off or
dimmed in both patient rooms and at the central
station. Telephone volumes were decreased; the staff
were expected to interact quietly and to remind
anyone entering the unit that QT was in process. Staff
limited nursing activities and did not enter the
patient’s room unless necessary. Charting and con-
versations took place at the central station. Given the
open design of the neuro-ICU, the staff were unable to
close doors but did close privacy curtains and turned
off radios and televisions. Whenever possible, diag-
nostic tests, laboratories, consults, and procedures
were conducted outside QT hours. When therapeutic
interventions were necessary, they were performed as
quietly as possible. Unless requested by patients, vis-
iting was prohibited during QT. During this phase,
reminders, updates, and stimuli-reducing strategies
concerning the QT protocol were distributed through-
out the unit.
Measurements
Noise and light data were collected six times a day for
a period of 5 seconds: one measurement 30 minutes
before and after QT hours and one measurement 1
hour to 30 minutes before the end of QT hours (see
Table 4). Noise measurements were taken with a
digital sound meter (model 8400029; Sper Scientific,
Ltd., Scottsdale, AZ). Noise measurements were
taken at three distinct sites: central nursing station,
entrance of the patient’s doorway, and next to the
patient’s ear. Light was measured with a light meter
(model 8400060; Sper Scientific) at the same time as
the sound measurement for a period of 5 seconds. To
replicate the effect of light on the patient, all of
whom were supine, we measured the light at the
patient’s ear by turning the light meter up toward the
ceiling. Both instruments have been validated in
previous studies (Olson et al., 2001).
Polysomnography, the most accurate method for
evaluating sleep, was not a realistic option because of
the cost and the requirement of expert interpretation.
Observation of sleep has traditionally been part of
nursing assessment and is reasonably valid, shown to
have greater than 80% agreement with polysom-
nography (Edwards & Schuring, 1993). This study
FIGURE 2 Central Station in the Neuro-ICUFIGURE 2
Note. Most of the day-to-day activities occur in this area, and thus, this
area has the most noise due to telephones, pagers, faxes, and staff
congregating. Note the patients’ rooms located all around the central
station.

analyzed sleep using the method previously men-
tioned by Olson et al. (2001), which was Edwards
and Schuring’s 1993 sleep observation tool (SOT).
Patients were observed, using the SOT, seven times
a day by one of three neuro-ICU registered nurses.
The registered nurses recorded one of three findings:
(a) patient appeared to be asleep, (b) patient was
awake, or (c) unable to assess. Therefore, we will refer
to patients appearing to be asleep as Basleep[ or
Bsleeping,[ acknowledging that patients may be
simply resting and displaying behavior consistent
with sleep. BUnable to assess[ was selected for only
two observations where patient behavior was such
that sleep was indeterminate; for example, the
patient’s eyes were consistently closed, but the patient
was frequently moving. For analysis purposes, these
patients were considered Bawake.[
Sleep observations occurred beginning 30 minutes
before QT and proceeded every half hour until 30
minutes after QT. Orientation to the tools and the
reliability of the tools were validated by comparing
the nurse observers’ results with that of the primary
investigator’s results before study implementation. In
addition, the three nurse observers were educated
and their competence validated on the GCS, the
study criteria, and the use of the noise and light
instruments.
Analysis
The outcomes of interest were the ability to de-
crease noise and light during QT as well as to
determine if there was a difference in the numbers of
patients asleep during QT compared with preceding
and following periods. The data were analyzed using
SAS statistical software.
Tabulated information and means for noise and
light levels were computed. Further analysis included
ANOVA analysis with contrasts for noise and light
levels as well as logistic modeling and odds ratios for
comparing sleep behavior during QT hours with times
before and after. These were performed using SAS
PROC GENMOD, modeling the mean noise and light
levels for the time preceding, during, and after the
QT period.
Generalized estimating equations (GEEs) were used
to adjust standard errors and contrast results for the
correlation between the repeated measurements from
each patient; multiple observations from doors or
curtain entrances and beds of the same patient were
considered correlated, whereas observations from the
nursing station taken on the same day were considered
correlated. GEE is a commonly used method that
employs iterative algorithms to estimate the correlation
structure of nonindependent data points and subse-
quently adjust statistical models. Because of the
number of independent tests, the level of significance
is adjusted to .01, and because of inherent difference in
sleep practices between the periods of the day shift and
night shifts, these data were analyzed separately.
Sleep behavior data were similarly analyzed sep-
arately for day and night shift observations. Logistic
models, performed with SAS PROC GENMOD,
were used to estimate odds ratios comparing the
likelihood of being observed asleep during periods
before and after QT with the observations during
QT. For these purposes, the two initial time points
as Bbefore QT,[ the last time point as Bafter QT,[
and remaining time points as Bduring QT.[ GEEs
were used to adjust the model for the correlation
between the seven observations from each patient.
An autoregressive correlation structure was assumed;
meaning time points closer together were considered
more correlated than those farther apart.
Results
Fifty patients were included in the final sample.
Thirty-five patients were observed during the day
shift QT, and 15 patients were observed during the
night shift QT. Relevant demographics, such as gender,
mean age, and GCS, are presented in Table 1. Mean
values, adjusted standard errors, and statistical p values
for both noise and light levels are presented in Tables
2 and 3. The p values represent comparisons between
before and after measurements and those taken during
QT. Table 4 displays both the number and the
proportion of patients displaying observed sleeping.
Table 5 shows estimated odds ratios and confidence
intervals comparing the likelihood of sleep during QT
hours with those times immediately before and after.
The purpose of the QT intervention was to create
an environment with reduced light and noise to
promote rest for neuro-ICU patients. Observations
during the day shift QT showed mean reduction of
average noise levels by approximately 10 decibels at
two locations: doors to patient rooms and heads of
TABLE 1. Patient Sample Demographics
Shift Patients
Mean
Age (SE)
Mean
GCS (SE)
Day shift Total 35 55.5 (2.43) 13.7 (0.29)
Male 19 55.8 (3.08) 13.7 (0.40)
Female 16 55.1 (3.98) 13.8 (0.42)
Night shift Total 15 52.9 (4.21) 14.9 (0.09)
Male 6 53.8 (9.18) 14.8 (0.17)
Female 9 52.3 (4.07) 14.9 (0.11)
Note. GCS = Glasgow Coma Scale.

patients’ beds (a reduction of approximately 15%).
The reduction of noise level at the center of the unit
was almost as large, representing an approximate 10%
reduction in this noisier area. At each measured
location, these differences were statistically signifi-
cant at the .025 level. Comparable differences in
recorded noise levels during the night shift hours were
less dramatic than differences during day shift hours
but statistically significant. It should be noted,
however, that recorded noise levels during the night
shift, at all times and locations, were substantially
lower than QT noise levels during the day shift.
Results of differences in light levels were similar.
Light levels measured during the day shift showed
average light levels during QT to be only a fraction
(15Y25%) of those recorded both before and after QT.
These differences were statistically significant with
p values less than .025. As with noise levels, light
levels during night shift hours showed no statistically
significant differences across measurements. As with
noise levels, light levels during the day shift were
overall much lower than those taken during the night
shift. In fact, light measurements at all night time
points were comparable with the QT measurements
in the night shift. This was particularly true of those
most directly affecting patients: those taken at the
entrance of the patient room and the head of the bed.
Such a low light level during the night shift left little
need for improvement during the QT hours.
Discussion
There were several important findings in this study.
The results of this study suggest success of the QT
intervention at least during the day shift hours. Day
shift hours between 2:00 and 4:00 p.m., when
patients’ circadian rhythms would promote sleep,
were proven to be periods of relatively high noise and
light levels in the neuro-ICU. The QT intervention
significantly lowered these. With these lower levels,
patients were significantly more likely to be observed
sleeping. During the QT hours, patients had four
times higher odds of being observed sleeping than in
the half hour before. The night shift was found to be a
time of reduced light and noise, regardless of the QT
intervention. Similarly, a greater proportion of patients
were sleeping during this night shift both before and
during the intervention.
The results of this study are consistent with those
of Olson et al. (2001), which instituted a QT in a
neuroYcritical care unit with similar time frames and
found that patients were 1.6 times more likely to be
found asleep during the QT. Furthermore, our study
had greater success in reducing daytime background
noise levels than that conducted by Walder, Francioli,
TABLE 2. Noise Levels Recorded at Different Locations Before, During, and After Quiet Time
Shift Time Mean (SEa
) pb
Day shift (n = 35) Center of station Prior 83.1 (2.09) .0018*
During 71.9 (1.60) Y
After 78.2 (2.34) .0197*
Door of room Prior 74.1 (1.62) G.0001*
During 65.1 (1.29) Y
After 74.5 (1.85) G.0001*
Head of bed Prior 71.2 (2.02) G.0001*
During 62.2 (1.75) Y
After 72.6 (1.79) G.0001*
Night shift (n = 15) Center of station Prior 59.9 (1.42) .9828
During 59.9 (1.81) Y
After 63.2 (1.90) .0392*
Door of room Prior 58.7 (0.67) .1582
During 56.7 (1.62) Y
After 59.2 (1.00) .0365*
Head of bed Prior 58.3 (1.37) .3151
During 56.9 (2.31) Y
After 59.5 (1.96) .0227*
a
Standard errors and p values are adjusted for repeated measures on patients. b
p values represent a test of significance between noise
levels at periods before and after quiet time compared with during quiet time.
*Statistically significant difference between this measurement and the respective quiet time measurement.

Meyer, Lancon, and Romand (2000). Walder et al.
designed a prospective intervention study in a surgical
ICU, resulting in reductions in light and some noise
but having no effect on background noise levels.
Another interesting result was the effect of QT on
the neuro-ICU staff. Shortly after the study began,
staff reported that they enjoyed QT. It was a time for
them to review the patient’s chart, to update their
documentation, and to find respite from a hectic pace.
One of the neuro-ICU nurses commented that QT
offered her an opportunity to Brefocus and repri-
oritize[; another nurse reported a chance to Bfeel
caught up[ and Bto think better[ during QT.
Implications for Nursing Practice
It is evident that much remains to be learned regarding
the effects of environmental overload on critically ill
patients. Unit design, timing of care activities, level of
nursing intensity, and the resultant amount of noise
and light are all important and interrelated factors.
This study contributes to our understanding of how
one intervention, QT, can improve a patient’s oppor-
tunity to rest. Other opportunities for studying this
phenomenon should include expanding the QT
intervention beyond the neuro-ICU, such as to large,
open patient care units. Future investigations might
also incorporate alternative therapies such as music
TABLE 4. Number of Patients Asleepa
at Each Time Period
Shift Quiet Time Prior Begins During During During Ends After
Day shift Time 1:30 p.m. 2:00 p.m. 2:30 p.m. 3:00 p.m. 3:30 p.m. 4:00 p.m. 4:30 p.m.
Asleep 10 (26.6%) 14 (40%) 25 (71.4%) 26 (74.3%) 25 (71.4%) 21 (60%) 16 (45.7%)
Awake 25 (71.4%) 21 (60%) 10 (28.6%) 9 (25.7%) 10 (28.6%) 14 (40%) 19 (54.3%)
Night shift Time 1:00 a.m. 1:30 a.m. 2:00 a.m. 2:30 a.m. 3:00 a.m. 3:30 a.m. 4:00 a.m.
Asleep 10 (66.7%) 11 (73.3%) 11 (73.3%) 11 (73.3%) 8 (53.3%) 10 (66.7%) 7 (46.7%)
Awake 5 (33.3%) 4 (26.7%) 4 (26.7%) 4 (26.7%) 7 (46.7%) 5 (33.3%) 8 (53.3%)
a
Asleep refers to sleep-like behavior, sleeping, and displaying behavior consistent with sleep as measured with Edwards and Schuring’s
(1993) sleep observation tool.
TABLE 3. Light Levels Recorded at Different Locations Before, During, and After Quiet Time
Shift Time Mean (SEa
) pb
Day shift (N = 35) Center of station Prior 283.6 (8.8) .0021*
During 53.5 (11.82) Y
After 268.0 (11.4) .0028*
Door of room Prior 111.2 (9.24) G.0001*
During 26.1 (7.57) Y
After 109.8 (9.32) G.0001*
Head of bed Prior 165.4 (50.24) G.0070*
During 22.8 (5.24) Y
After 131.9 (43.14) G.0155*
Night shift (N = 15) Center of station Prior 135.1 (36.99) .2568
During 116.8 (40.84) Y
After 122.30 (41.78) .4332
Door of room Prior 19.3 (4.49) .4949
During 21.1 (5.85) Y
After 24.1 (7.66) .4159
Head of bed Prior 13.2 (9.18) .2849
During 3.4 (1.15) Y
After 16.5 (12.38) .3051
a
Standard errors and p values are adjusted for repeated measures on patients. b
p values represent a test of significance between light
levels at periods before and after quiet time compared with during quiet time.
*Statistically significant difference between this measurement and the respective quiet time measurement.

therapy, massage, hypnosis, and utilization of ear-
plugs, headphones, and white noise machines.
It is interesting that with the advances in tech-
nology, little has been done to reduce noise volumes
and light intensity in healthcare settings. In fact, it
can be argued that technological innovations have
increased these environmental stimuli and may have
contributed to delayed recovery.
Limitations of the Study
Several limitations were identified. The architectural
design of the neuro-ICU made reducing light and
noise levels a challenge. On several occasions, patient
care made it impossible to keep the noise and light
levels lowered during QT. It was also necessary to
constantly remind staff and visitors that QTwas being
observed and noise and light levels needed to be
lowered. Investigators also discovered that almost
everything seemed noisy during QT. Specifically,
telephones, beepers, and staff conversations seemed
normal except during QT when they became more
intrusive. We also found that some noise could not be
controlled for, as in the overhead paging of a code
blue or rapid response.
Although the SOT has been proven a valid and
reliable measure (r =.81), future studies might be
more rigorous with other measures of sleep such as
polysomnography. Polysomnography provides more
detail about the quality and cycle of sleep; thus,
investigators could examine the effect of QT on the
amount of time patients spent in REM and NREM
sleep.
The patients in our neuro-ICU often required fre-
quent assessment and interventions, thereby not
always making QT possible. In addition, unit trans-
fers and admissions, activities that cannot be delayed,
sometimes prevented strict adherence to the QT
protocol.
Finally, there were some limitations in the analysis
of study data and subsequent conclusions. First, the
entire study population consisted of neurological
patients, housed in the neuro-ICU; however, results
were consistent with referenced studies consisting of
broader samples. Second, all comparisons are be-
tween QT observations versus observations taking
either shortly before or after QT. In further study, it
would be advantageous to have comparison observa-
tions from various periods. In addition, the scope and
the length of the study limited the major outcomes. A
study of larger scope with more subjects would be
required to examine the impact of a QT protocol and
patient recovery outcomes.
Summary
Within the neuroYintensive care setting, creating a
healing environment, devoid of unnecessary noise
and light, is not always possible. However, imple-
menting a QT can help move us forward in that goal.
As Florence Nightingale stated, the first aim of a
hospital is to do the sick no harm (Lower, Bonsack, &
Guion, 2003). This proclamation came after she
observed the beneficial effects of simple adjustments
in the hospital environment, that is, reducing light and
noise and improving room ventilation and cleanliness.
With an engaged and informed staff, modern hospitals
can meet Nightingale’s challenge.
Acknowledgments
The authors thank Natalie Rathvon, PhD, Miriam
Rogers, EdD RN CNS, DaiWai Olson, PhD RN,
and the staff of the WakeMed Neuro-ICU.
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TABLE 5. Odds Ratios Being Observed
Sleeping
Shift Comparison
Odds
Ratio
97.5% Confidence
Intervala
Day shift QT vs. before 4.04 2.24Y7.30
QT vs. after 2.14 1.17Y3.95
Night shift QT vs. before 0.96 0.41Y2.24
QT vs. after 2.31 0.59Y9.09
Note. QT = quiet time.
a
Confidence intervals were narrowed to 97.5% to adjust for
multiple comparisons.

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effects on blood pressure: Exploring the relationship of
hypertension and noise exposure in workers. AAOHN
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that make the environment good or bad: The patient’s
experience of the acute care hospital environment. AACN
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(2004). Nocturnal care interactions with patients in critical care
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hospital patients’ noise-induced stress and other stress with
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WANTED!
The Journal of Neuroscience Nursing (JNN) is seeking authors interested in
submitting manuscripts for publication. Although JNN is a clinically focused
journal, we do include topics addressing nursing practice as a whole; research
articles are encouraged as well. Both new and experienced authors are
welcome; a new author mentor program is available.
Need topic ideas? A wide variety of articles are possible. JNN is actively
seeking manuscripts in the following areas:
& Case studies elaborating approaches to care for a challenging or unique patient
& Outcomes studies
& Geriatric aspects of neuroscience nursing
& Pediatric-focused articles
& Novel drug therapies for neurologic diseases
& Intraoperative considerations and surgical instrumentation
& Focused assessment articles (e.g., spine assessment)
& New products related to neuroscience nursing care
& Literature review of a neuroscience-related topic
& Home care of the chronic neurologically impaired patient
& Nursing management in the neuroscience outpatient settings
(e.g., nurse-managed back-pain clinic)
& Ethical issues in neuroscience nursing
& Care of the patient undergoing neurointerventional procedures
& Noninvasive surgical and treatment techniques
& Collaborative approaches to care
Guidelines for authors can be found at www.editorialmanager.com/neuronurse/.
To query the editor about a specific manuscript idea, send an e-mail to
susan.carroll25@gmail.com. Review time after submission is about 6Y8 weeks.

final QT ppr published in JNN, Aug 2010

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