Patterson et al. Trials
(2021) 22:212
https://doi.org/10.1186/s13063-021-05161-4
STUDY PROTOCOL
Open Access
Napping on the night shift and its impact
on blood pressure and heart rate variability
among emergency medical services
workers: study protocol for a randomized
crossover trial
P. Daniel Patterson1,2* , Leonard S. Weiss1, Matthew D. Weaver3,4, David D. Salcido1, Samantha E. Opitz1,
Tiffany S. Okerman1,2, Tanner T. Smida1, Sarah E. Martin1, Francis X. Guyette1, Christian Martin-Gill1 and
Clifton W. Callaway1
Abstract
Background: There is an emerging body of evidence that links exposure to shift work to cardiovascular disease
(CVD). The risk of coronary events, such as myocardial infarction, is greater among night shift workers compared to
day workers. There is reason to believe that repeated exposure to shift work, especially night shift work, creates
alterations in normal circadian patterns of blood pressure (BP) and heart rate variability (HRV) and that these
alterations contribute to increased risk of CVD. Recent data suggest that allowing shift workers to nap during night
shifts may help to normalize BP and HRV patterns and, over time, reduce the risk of CVD. The risk of CVD related to
shift work is elevated for emergency medical services (EMS) shift workers due in part to long-duration shifts,
frequent use of night shifts, and a high prevalence of multiple jobs.
(Continued on next page)
* Correspondence: pdp3@pitt.edu
1
Department of Emergency Medicine, University of Pittsburgh, School of
Medicine, 3600 Forbes Ave., Iroquois Building, Suite 400A, Pittsburgh, PA
15261, USA
2
Division of Community Health Services, Emergency Medicine Program,
University of Pittsburgh, School of Health and Rehabilitation Sciences,
Pittsburgh, PA 15261, USA
Full list of author information is available at the end of the article
© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article's Creative Commons
licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons
licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.
Patterson et al. Trials
Page 2 of 15
(2021) 22:212
(Continued from previous page)
Methods: We will use a randomized crossover trial study design with three study conditions. The targeted
population is comprised of EMS clinician shift workers, and our goal enrollment is 35 total participants with an
estimated 10 of the 35 enrolled not completing the study protocol or classified as lost to attrition. All three
conditions will involve continuous monitoring over 72 h and will begin with a 36-h at-home period, followed by 24
total hours in the lab (including a 12-h simulated night shift), ending with 12 h at home. The key difference
between the three conditions is the intra-shift nap. Condition 1 will involve a simulated 12-h night shift with total
sleep deprivation. Condition 2 will involve a simulated 12-h night shift and a 30-min nap opportunity. Condition 3
will involve a simulated 12-h night shift with a 2-h nap opportunity. Our primary outcomes of interest include
blunted BP dipping and reduced HRV as measured by the standard deviation of the inter-beat intervals of normal
sinus beats. Non-dipping status will be defined as sleep hours BP dip of less than 10%.
Discussion: Our study will address two indicators of cardiovascular health and determine if shorter or longer
duration naps during night shifts have a clinically meaningful impact.
Trial registration: ClinicalTrials.gov NCT04469803. Registered on 9 July 2020
Keywords: Crossover trial, Napping, Shift work
Administrative information
Title {1}
Napping on the night shift and its
impact on blood pressure and heart
rate variability among Emergency
Medical Services workers: Study
protocol for a randomized crossover
trial
Trial registration {2a} and {2b}.
Our protocol has been registered with
clinicaltrials.gov (registration number:
NCT04469803; public release date: 9
July 2020) {2a} and {2b}. All subjects are
required to provide written informed
consent.
Protocol version {3}
Protocol version 1 as of February 2021
{3}.
Funding {4}
The ZOLL Foundation has provided
funding for this study {4}. The ZOLL
Foundation has no role in the study
design, data collection, management,
analysis, interpretation of results, writing
of study findings, or decision on
publication {5c}. The ZOLL Foundation
can be reached at
foundation@zollfoundation.org and by
visiting the foundation website: www.
zollfoundation.org {5b}.
Author details {5a}
P. Daniel Patterson, PhD, NRP1,2
Leonard S. Weiss, MD1
Matthew D. Weaver, PhD3,4
David D. Salcido, PhD, MPH1
Samantha E. Opitz, MS
Tiffany S. Okerman, NRP1,2
Tanner T. Smida, EMT1
Sarah E. Martin, MPH1
Francis X. Guyette, MD, MPH1
Christian Martin-Gill, MD, MPH1
Clifton W. Callaway, MD, PhD1
1: University of Pittsburgh, School of
Medicine, Department of Emergency
Medicine, Pittsburgh, PA 15261.
2: University of Pittsburgh, School of
Health and Rehabilitation Sciences,
Division of Community Health Services,
Emergency Medicine Program,
Administrative information (Continued)
Pittsburgh, PA 15261.
3: Brigham and Women’s Hospital,
Division of Sleep and Circadian
Disorders, Boston, MA 02115.
4: Harvard Medical School, Division of
Sleep Medicine, Boston, MA 02115.
Name and contact
information for the trial
sponsor {5b}
The ZOLL Foundation can be reached
at foundation@zollfoundation.org and
by visiting the foundation website:
www.zollfoundation.org {5b}.
Role of sponsor {5c}
The ZOLL Foundation has no role in
the study design, data collection,
management, analysis, interpretation of
results, writing of study findings, or
decision on publication {5c}.
Introduction
Background and rationale {6a} {6b}
There is an emerging body of evidence that links
exposure to shift work to cardiovascular disease (CVD)
[1]. The incidence of hypertension (HTN) is higher
among shift workers compared to persons who work
traditional daylight schedules [2, 3]. Shift workers have a
23% higher risk of myocardial infarction and a 5% higher
risk of stroke relative to day workers [4, 5]. In addition,
the risk of coronary events (e.g., myocardial infarction,
coronary mortality, hospital admission due to coronary
artery disease) is greater among night shift workers
compared to day workers (risk ratio 1.41, 95%CI 1.13,
1.76) [5]. There is reason to believe that repeated
exposure to shift work creates alterations in the normal
circadian patterns of blood pressure (BP) and heart rate
variability (HRV) and that these alterations contribute to
increased risk of CVD over time [6, 7]. There is also
reason to believe that allowing shift workers to nap on
duty (especially during night shift work) may help to
Patterson et al. Trials
Page 3 of 15
(2021) 22:212
normalize BP and HRV patterns and over time reduce
the risk of CVD due in this population [8, 9].
Shift work refers to work schedules outside the
traditional daylight schedule (e.g., 9 am to 5 pm) [10].
Paramedics and emergency medical technicians (EMTs)
are shift workers within the United States Emergency
Medical Services (EMS) system, which comprised more
than one million certified/licensed personnel and
approximately 20,000 EMS agencies nationwide [11].
The clinician shift workers who work in EMS are often
deployed in crews of two and frequently work night
shifts, evening shifts, long-duration shifts (e.g., 24 h and
48 h), and rotating or irregular shift schedules [12]. Shift
work contributes to fatigue, excessive daytime sleepiness,
and problems with obtaining adequate sleep [13, 14].
Previous research shows that three quarters of EMS shift
workers report occupational fatigue, greater than half report poor sleep quality, half report inadequate recovery
between scheduled shifts, and half report sleeping less
than 6 h per night [15–19].
Shift work forces prolonged wakefulness and disrupts
a number of biological, chemical/hormonal, and
physiologic mechanisms that are closely tied to the
night/day, sleep/wake cycle (circadian rhythms) [20, 21].
The normal circadian pattern of BP is characterized by
elevations during daylight hours and wakefulness,
followed by a decrease of 10–20% during nighttime
hours and sleep [9, 22]. This decrease in BP during sleep
and nighttime hours is referred to as the “dip” [9, 22].
Blunting of the BP dip occurs when BP fails to drop by
10% during nighttime hours or during sleep [9, 22]. In
select populations, blunted BP dipping during sleep and
nighttime hours has been linked to select demographic
and physiologic factors, elevated levels of stress, stroke,
target organ damage, left ventricular hypertrophy,
progressive renal damage, and cardiovascular mortality
[23–31]. Previous research of night shift workers (e.g.,
physicians and nurses) shows that nighttime BP is often
elevated compared to daytime values [32, 33], and in
some cases, the BP dip is blunted during shift work and
during recovery immediately after shift work [34]. Our
recent study of 56 EMS clinicians shows that a large
proportion of those who work night shifts experience
blunted BP dipping during shift work [35].
Previous research also shows an association between
shift work and unhealthy HRV patterns [36–39]. Healthy
HRV may be characterized by oscillations in the heart
rate and beat-to-beat fluctuations that are more variable
over a 24-h period [40–42]. Greater variability in patterns of HRV signifies balance between sympathetic and
parasympathetic activity and is often associated with better health, better performance, and increased ability to
respond to, and cope with stress [41]. Decreased variability, or reduced HRV, may be a marker of increased
sympathetic activity and reduced parasympathetic activity. Prolonged periods of reduced HRV have been linked
to acute cardiac events and all-cause mortality [43, 44].
One study of 14 EMTs revealed reduced levels of HRV
during periods of sleep that occurred during shift work
versus during sleep on non-workdays [39]. A study of
nine paramedics in Japan showed an abnormal HRV pattern during the workday compared to the non-workday
[45]. A separate study of 14 male firefighter-paramedics
in Finland reported decreased variability in heart rate
during a 24-h shift followed by normalization to healthier levels after 3 days of rest [36]. Together, these studies
suggest that shift work may have a negative impact on
the normal circadian pattern of HRV among EMS shift
workers.
Shift work is essential for many occupations, including
public safety workers such as police, fire, and EMS,
which provide critical services that must be available all
hours, day and night [46]. Many EMS employers would
likely object to policies that restrict shift duration or
timing as a means to guard against the impact of shift
work on cardiovascular health [47]. Employers are more
likely amenable to strategies that allow for shift work to
continue and simultaneously reduce its impact on select
outcomes. One such strategy is napping during shift
work. Napping has been described as “sleep periods at
least 50% shorter than an individual’s average nocturnal
sleep length” [48, 49]. A recent systematic review and
meta-analysis shows that napping during night shifts has
a positive impact on shift worker’s subjective ratings of
sleepiness and fatigue [50]. Evidence-based guidelines
for fatigue risk management in EMS promote napping
during shift work, especially during night shifts [51].
These data and guidance support intra-shift napping as
it pertains to worker safety [51]. However, previous research devoted to the health benefits of intra-shift
napping is limited. Employers face a great deal of
uncertainty when weighing the risks versus benefits of
intra-shift napping, and uncertainty regarding
implementation.
Objectives {7}
In this paper, we present the study protocol for an
experimental study of EMS shift workers using intrashift napping during simulated night shifts. We will use
a randomized crossover study design comprised of two
intra-shift napping conditions and one no-nap comparison condition. With this design, we first aim to determine the impact of different durations of napping
during night shifts on BP dipping and HRV during sleep
and during nighttime hours. Second, we aim to determine if longer duration naps are associated with improved recovery or a more rapid normalization of BP
and HRV patterns post-shift work. We hypothesize
Patterson et al. Trials
Page 4 of 15
(2021) 22:212
higher odds of blunted BP dipping during the no-nap
condition versus the napping conditions. We
hypothesize that when compared to the napping conditions, select HRV measures taken during the no-nap
condition (i.e., the standard deviation of the inter-beat
intervals of normal sinus beats, SDNN) will be reduced.
We hypothesize that BP and HRV patterns observed immediately following the simulated night shift for both
napping conditions will normalize sooner than observed
for the no-nap condition. Finally, we hypothesize that
for both BP and HRV, the greatest benefit will be observed in the longer duration nap of 2 h versus the
shorter 30-min nap condition.
CONSORT/SPIRIT statement. Figure 1 illustrates the
flow chart of our trial, and Fig. 2 illustrates the SPIRIT
template for enrolment, intervention, and assessment.
The University of Pittsburgh Institutional Review Board
(IRB) approved this study {24}, and our protocol has
been registered with ClinicalTrials.gov ({2a} registration
number: NCT04469803; public release date: 9 July
2020). All subjects are required to provide written informed consent (see Additional file 1, which reports on
all elements of the SPIRIT checklist). All elements of the
World Health Organization Trial Registration Data Set
can be found in this article, supplemental file, and the
ClinicalTrials.gov registration.
Trial design {8}
Methods: participants, interventions, and
outcomes
We will use a randomized crossover trial study design
with three study arms/conditions. All three conditions
will involve continuous monitoring over 72 h and will
begin with a 36-h at-home period, followed by 24 total
hours in the lab (including a 12-h simulated night shift),
and ending with 12 h at home. The key difference between the three conditions is the presence or absence of
an intra-shift nap and the duration of that nap. Condition 1 will involve a simulated 12-h night shift with no
nap: total sleep deprivation. Condition 2 will comprise
another simulated 12-h night shift and a 30-min nap opportunity. Condition 3 will involve a simulated 12-h
night shift and a 2-h nap opportunity. There will be a
mandatory 1–3 week washout period between conditions. The order in which participants complete the
study conditions will be balanced by a William’s square
design. In the paragraphs below, we outline the details
of our experimental study in accordance with the
Visit lab for device
data download &
reprogramming
Visit lab to obtain
monitoring devices
Study setting {9}
The study setting is inclusive of Western Pennsylvania
in the USA. This area is home to more than 300 EMS
agencies and more than 9000 certified EMS clinicians
[52]. All laboratory-based procedures will occur on the
University of Pittsburgh campus in the Department of
Emergency Medicine’s Applied Physiology Laboratory.
In response to COVID-19, we will implement additional screening and in-laboratory procedures. These include the following: (A) during participant screening, we
will give preference to eligible participants who have received at least one dose of the COVID-19 vaccine prior
to starting the study. All non-vaccinated, yet otherwise
eligible participants will be placed on a wait-list or be
allowed to start the study after all vaccinated participants have completed the study protocol. (B) Prior to
entering the laboratory, eligible participants will undergo
Nap intervention
0200-0400
-No nap arm
-30-min nap arm Recovery period
-120-min nap arm nap opportunity
in lab 1300-1500
Sleep
2200-0800
Simulated shift
1900-0700
12hrs
24hrs
Daytime
Fig. 1 Study protocol timeline
Recovery
0700-1900
36hrs
48hrs
Nighttime
Visit lab to
return devices
Sleep
2200-0800
At Home
(12hrs)
In Lab (24 hours)
At Home (36 hours)
0800
Escorted
home
Arrive at lab
1700-1800
60hrs
72hrs
Patterson et al. Trials
Page 5 of 15
(2021) 22:212
Fig. 2 Schedule of enrolment, interventions, and assessments. 0 = start of at-home phase. t1 = 12 h post allocation. t2 = 24 h post allocation. t3 =
36 h post allocation. t4 = 48 h post allocation. t5 = 60 h post allocation. t6 = 72 h post allocation
temperature screening and questioning about recent illness, which will include any signs or symptoms of
COVID-19 (e.g., fever or chills, cough, shortness of
breath, body fatigue, muscle or body aches, headache,
new loss of taste or smell, sore throat, congestion or
runny nose, nausea, vomiting, or diarrhea). Participants
who respond yes to one or more questions and/or a
non-contact forehead temperature reading of > 100.3
°F (37.9 °C) will involve a consult with a licensed
emergency medicine physician involved with the study
protocol. (C) Masks must be worn by study staff and
by study participants at all times when inside the laboratory. Participants may remove their mask while
sleeping/napping or when not in the laboratory (e.g.,
at home). (D) We will limit the number of times and
total amount of time that study staff are within 6-ft of
study by instructing, demonstrating, and monitoring from
a safe distance (> 6 ft) while participants apply select noninvasive measurement devices (e.g., Holter monitors, ambulatory blood pressure monitoring devices, and wrist
actigraphy devices). Study staff will quickly validate placement following participant self-application. (E) Study staff
will maintain a safe distance from study participants (> 6
ft) for the duration of the laboratory-based component of
the study, except when absolutely necessary.
Eligibility criteria {10}
Inclusion criteria include the following: (A) a
commitment to 72 h of continuous monitoring on three
separate occasions; (B) a commitment to complete a
laboratory-based simulated 12-h night shift during each
72-h period; (C) a commitment to going without sleep
for at least one of the simulated night shifts; (D) a commitment to wearing multiple monitoring devices (i.e.,
Holter monitors, blood pressure monitors) during each
of the 72 h of monitoring; (E) a commitment to abstain
from exercise, caffeine, alcohol, and nicotine during the
72-h study interval and to follow a structured sleep and
food consumption protocol for 72 consecutive hours
during each visit; (F) confirmation of current licensure/
Patterson et al. Trials
Page 6 of 15
(2021) 22:212
certification as an EMS clinician (i.e., EMT, paramedic,
flight nurse, or other first responder); (G) confirmation
of current work as a front-line clinician (with full-time
administrators excluded); (H) lack of known medical
conditions that may impact findings (i.e., a sleep
disorder, hypertension, CVD, history of myocardial infarction or stroke, kidney disease, liver disease, adrenal
disease, thyroid disease, rheumatologic disease,
hematologic disease, cancer, or organ transplantation);
(I) not known to be pregnant; (J) confirmation of no
physical conditions that may prevent wearing of multiple
monitoring devices; and (K) age 18 years or older.
Who will take informed consent {26a}
All who are interested in participation will use email or
telephone to initiate contact with the study team and
schedule a time for screening and consenting. We will
determine eligibility with a standardized screening form.
A qualified member of the study team will be responsible
for obtaining written informed consent (see Additional file
2 for a copy of consent form {32}). Randomization and
scheduling will occur immediately thereafter for those
determined eligible.
Additional consent provisions for collection and use of
participant data and biological specimens {26b}
This study protocol does not include the collection of
biological specimens. The addition of ancillary studies
would involve additional approval from the University of
Pittsburgh IRB and additional consent from study
participants.
Interventions
Explanation for the choice of comparators {6b}
There is reason to believe that if given the opportunity
to nap during shift work, EMS shift workers may
experience a benefit to their cardiovascular health. Both
BP and HRV are tightly tied to timing, duration, and
depth of sleep [9, 53]. Slow-wave sleep or deep sleep will
often occur within 30 to 60 min after initiating sleep and
is associated with a significant drop in BP [9]. Some research shows that slow-wave sleep can occur with a nap
duration of < 30 min [8]. During this time, dynamic
changes will arise in HRV with an increase in parasympathetic activity and a decrease in sympathetic activity
[9, 53]. Given these data, a healthy (normal) drop in BP
of 10–20% and normal circadian changes in HRV similar
to non-workdays may be achievable during intra-shift
naps, especially when utilized during night shifts. What
is not yet clear is do EMS shift workers achieve a healthy
dip in BP and a normal circadian change in HRV during
shorter as well as longer duration naps?
Intervention description {11a}
Our intervention of interest is intra-shift napping. All
subjects in our study protocol will participate in two
intervention nap conditions and one no-nap comparison
condition. All nap opportunities will be available between 0200 and 0400 h during the in-laboratory phase
and simulated night shift. We chose this time period
given that (A) EMS call volume (workload) is often low
or limited at this time, and many who are allowed to
nap on duty may use this time period for sleep, and (B)
this window of time coincides with a known time of high
homeostatic sleep pressure and minimal circadian alerting signal [21]. Protocol conditions 2 and 3 will involve
scheduled intra-shift nap opportunities of 30 min and 2
h, respectively. Our choice of 30 min and 2 h for the nap
opportunities was based on the following: (A) previous
research has suggested that short duration naps are optimal during night shift work for sustained or improved
performance and avoidance of sleep inertia (that groggy
feeling experienced upon waking) [8]; (B) shorter duration naps are attractive in public safety because EMS
work is unpredictable and when called upon, an EMS
worker must react quickly and make medical decisions
to care for the acutely ill and injured; (C) many EMS
employers who may not endorse sleeping while on duty
might be amenable to short versus longer opportunities
for intra-shift napping [51]; and (D) blood pressure and
HRV are tightly tied to sleep and depth of sleep [9]. As
described previously, normal dips in BP and
parasympathetic-driven changes in HRV often occur
when entering deeper, slow-wave sleep, which can occur
30 min or longer after beginning sleep [9, 53]. Therefore,
the longer 2-h nap condition may be superior in terms
of a cardiovascular-focused health benefit than would
the shorter 30-min nap condition.
Following the initial 36 h at home, the laboratory
phase will begin with participants arriving at the lab
between 1700 and 1800 h. The simulated night shift will
begin at 1900 and end at 0700 (12 total hours) the next
day. Participants will follow study intervention
procedures based on the order in which they were
randomized (i.e., condition 1 = no nap, condition 2 =
brief nap opportunity of 30 min, or condition 3 = longer
nap opportunity of 2 h). We have designed the simulated
night shift to include activities that are common during
real work conditions. In most EMS operations, the
dispatch (or call) volume is often reduced during
nighttime hours. Night shifts for EMS shift workers
often involve long periods of downtime with limited and
unpredictable patient-related activity. During downtime,
EMS shift workers read, watch television, use the Internet, or complete continuing education, or sleep if
permitted. For purposes of this study, we will allow participants to engage in these activities with the exception
Patterson et al. Trials
(2021) 22:212
of sleeping. Participants will sleep only when approved
to do so for the two napping conditions. Our simulated
night shift will involve four diverse patient encounters
introduced at random times throughout the simulated
night shift (minus the set-aside times for the napping
conditions). We will separate these encounters throughout the shift so that no two occur back to back within a
short time period. We will also introduce these mock
patient encounters at similar time intervals for all study
participants so that the workload does not differ in a
meaningful way. Four patient encounters during nighttime hours is a moderate level of workload. The four
mock patient encounters will include a low acuity patient encounter (i.e., a lift assist), a high acuity patient
encounter (i.e., a cardiac arrest), and two moderate acuity patient encounters (i.e., a traumatic injury and a patient with a medical emergency). Study staff will
administer these mock patient encounters with simulated “alarms” sounding as if the participant was at work.
We will allow for the movement of the participant (and
mock patient) within the laboratory space and the office
space where the laboratory is located. Patient treatment
(e.g., cardiopulmonary resuscitation) will be performed
on a low-fidelity manikin. Study staff will use standardized checklists to document the actions of study participants in accordance with state- and national-level
protocols for EMS clinical care. The simulated patient
encounters will not involve operating an ambulance or
driving simulator.
For conditions 2 and 3, the nap opportunities will be
introduced between 0200 and 0400. In addition to
wearing wrist actigraphy for sleep/wake monitoring, all
participants will wear the portable Zmachine® Synergy
machine provided by the General Sleep Corporation
(Cleveland, OH). The Zmachine® Synergy is a noninvasive sleep staging device that produces numerous
measures to quantify and differentiate light sleep (stages
1 and 2) from deeper sleep (stages 3 and 4) from rapid
eye movement (REM) sleep. The Zmachine® Synergy will
be used only when the participant is engaging in his/her
sleep opportunity from 0200 to 0400 and during the recovery period of sleep. With these data, we will explore
the association between stages of sleep (depth of sleep)
and changes in BP and HRV during intra-shift napping/
sleep.
At the end of the simulated 12-h night shift, participants will then enter a recovery period. This period entails participants remaining in the laboratory and
maintaining wakefulness from 0700 to 1300 h. At 1300,
we will provide participants with a 2-h recovery nap opportunity from 1300 to 1500. At 1900 h, we will escort
participants to their homes, via paid transportation, for
the final phase of the study arm. Participants will continue to be monitored with ABPM, HRV Holter
Page 7 of 15
monitoring, and actigraphy for another 12 h. During this
period, participants will be asked to sleep, recover, and
not engage in scheduled or unscheduled shift work, and
avoid consumption of caffeine or alcohol and avoid nicotine. At 0800 h the following day, participants will return
to the lab and complete study-related measurements and
return study equipment. Throughout each 72-h period,
participants will be instructed to follow a scheduled dietary plan. We will use a mandatory 1–3 week washout
period between each of the three study conditions.
Confidentiality of study participation will be maintained by storing all study-related forms in locked
filing cabinets in the locked office of study investigators, located on the University of Pittsburgh campus.
All data will be examined for accuracy (quality) and
abstracted into electronic form in a University of
Pittsburgh maintained version of REDCap (Research
Electronic Data Capture) [54, 55]. Our plan for data
safety monitoring will comprise investigators and
study staff providing monthly presentations of study
enrollment, protocol non-compliance, adverse events/
harms {22}, and other activities such as protocol
modifications to the University of Pittsburgh,
Department of Emergency Medicine Departmental
Clinical Research Meeting (DCRM). One faculty
member and one IRB coordinator within the Department of Emergency Medicine of the University of
Pittsburgh School of Medicine, who are unaffiliated
with the study, will periodically audit trial conduct
{23}.
Criteria for discontinuing or modifying allocated
interventions {11b}
Participation is voluntary; thus, participants may withdraw at
any time for any reason, which may include self-reported inability to complete the study protocol as designed. Criteria
for orderly discontinuing a participant’s involvement in the
study include the following: (A) the participant voluntarily
withdraws from the study, (B) the participant does not
complete all procedures/visits per protocol, (C) the participant’s physician or one of the investigators feels that it is not
in the best interest of the subject to be in the study (i.e., severe hypertension or hypotension), and (D) the participant’s
BP exceeds a measurement value of 180/110 across multiple
measures. In the event that a participant’s BP averages exceed the value of 180/110 while being measured in the presence of the study team, the study team will direct the
participant to contact his/her healthcare provider to discuss
the measures. There are no pre-defined criteria for modifying
allocated interventions.
Strategies to improve adherence to interventions {11c}
We will use the following strategies to improve
adherence to study procedures: (A) address any and all
Patterson et al. Trials
(2021) 22:212
concerns during the consenting procedure, (B) be
flexible with study participants regarding scheduling
(e.g., allow for protocol events during both weekdays
and during the weekend), and (C) provide access to
television, radio, and the Internet during all inlaboratory phases.
Relevant concomitant care permitted or prohibited
during the trial {11d}
During the study protocol, participants will be asked to
not engage in scheduled or unscheduled shift work and
avoid consumption of caffeine or alcohol and avoid
nicotine. Two out of seven similar studies testing the
impact of two different nap durations have allowed
participants to consume one caffeinated beverage or
smoke a cigarette at select points during the study
protocol [56–66]. Caffeine is a stimulant that has a
profound impact on subjective sleepiness and alertness
[67] and therefore may impact the differences between
study conditions. While previous research has assessed
the interaction between caffeine and napping [68], that
is not the focus of this protocol.
Provisions for post-trial care {30}
All participants who may require medical attention will
be provided medical attention at the University of
Pittsburgh Medical Center, which is outlined in the
consent form.
Outcomes {12}
Our primary outcomes of interest include blunted BP
dipping and reduced HRV as measured by the standard
deviation of the inter-beat intervals of normal sinus
beats (SDNN). Blunted BP dipping will be calculated
using two measures. First, we will quantify sleep vs. wake
BP dipping by identifying the participant’s sleep and
wake times and stratifying the hourly ABPM measures
into sleep vs. wake measures. The ratio of sleep-to-wake
BP is calculated by taking the difference between the
mean systolic and diastolic BP during the sleeping hours
and the mean systolic and diastolic BP during waking
hours. We define dipping status as follows: (mean wake
hours BP − mean sleep BP divided by mean wake hours
BP) × 100. Non-dipping status will be defined as sleep
hours BP dip of less than 10%, assessed with systolic BP
(SBP) and diastolic BP (DBP) [22, 69]. Next, we will
stratify each 24-h period into nighttime vs. daytime periods and calculate nighttime BP dipping with the “wide
fixed time method” [70, 71]. Daytime hours are defined
as 0700 to 2259 h, and nighttime hours are defined as
2300 to 0659 h [70, 71]. The ratio of night-to-day BP is
determined by taking the difference between the mean
systolic and diastolic BP during the nighttime hours
(2300 to 0659 h) and the mean systolic and diastolic BP
Page 8 of 15
during daylight hours (0700 to 2259 h). For this method,
nighttime dipping status is determined as follows:
((mean daylight BP − mean nighttime BP) ÷ mean
daylight hours BP) × 100. We will assess dipping vs. nondipping status during sleep hours and during nighttime
hours for all periods of observation and for all study
conditions.
Our second outcome of interest is reduced HRV. As
prescribed [72], we will examine HRV based on five
time-based measures summarized over each 24-h period
of observation. Measures include the following: (A)
standard deviation of the inter-beat intervals of normal
sinus beats (SDNN) summarized over 24 h; (B) standard
deviation of the averaged normal sinus intervals for all
5-min segments (SDANN) summarized over 24 h; (C)
the mean of the standard deviations of all normal sinus
RR intervals for all 5-min segments (SDNN index) summarized over 24 h and stratified by wake, sleep, and
work and non-work periods; (D) root-mean-square of
the successive normal sinus RR interval difference
(rMSSD) summarized over 24 h; and (E) the lowfrequency (LF) band and high-frequency band (HF) ratio
(LF/HF) summarized over 24 h and stratified by wake,
sleep, and work and non-work periods. The LF/HF ratio
is a frequency domain measure of HRV that depicts the
balance between sympathetic and parasympathetic activity of the nervous system [41]. Low values reflect the
dominance of the parasympathetic system whereas a
high ratio is indicative of sympathetic dominance [41].
For medical risk stratification, the SDNN over a 24-h
period is considered a gold standard measure [41].
Twenty-four-hour measures of SDNN < 50 ms are considered unhealthy [41, 73, 74].
We will administer multiple survey instruments at
baseline and during the study period, including a
standard demographics survey. At baseline, we will
administer the Pittsburgh Sleep Quality Index (PSQI),
which we will use to measure sleep quality [75]. The
Epworth Sleepiness Scale (ESS) will be used to measure
daytime sleepiness [76]. The Chalder Fatigue
Questionnaire (CFQ) will measure mental and physical
fatigue [77]. With permission from the developer, we
will use the Occupational Fatigue and Recovery (OFER)
Scale to assess acute fatigue, chronic fatigue, and intershift recovery [78]. The Copenhagen Burnout Inventory
(CBI) will measure burnout [79]. Five items from the
Schedule Attitudes Survey (SAS) will measure satisfaction with shift schedule [80].
Participants will wear a wrist-worn actigraph to objectively measure sleep/wake over the entire study period.
We will also use data from these devices to estimate the
body temperature minimum for each day of the study.
Blood pressure and HRV vary by circadian phase, with a
notable surge in morning BP after arousal [81]. As the
Patterson et al. Trials
Page 9 of 15
(2021) 22:212
sleep of shift workers in our study is dependent on the
absence of emergency calls, sleep may be distributed
across the day and night, and the magnitude of BP dip
during sleep may depend on the participant’s circadian
phase. When circadian rhythms are aligned with the
sleep-wake cycle, the core body temperature minimum
(CBT-min) usually occurs 2–3 h prior to the habitual
wake time [82]. Data from actigraphy and photometry
can be used to predict the timing of the CBT-min and
determine circadian alignment/misalignment. The Circadian Performance Simulation Software (CPSS version
2.1, Brigham and Women’s Hospital, Boston, MA, USA)
will be used to estimate the circadian phase for each
sleep episode. This software was developed based on
bio-mathematical models and has been utilized to
characterize circadian rhythms of astronauts on the
International Space Station [83–88]. Sleep vs. wake (binary) and light exposure data (binned in 1-h increments)
collected from actigraphy and photometry will be used
as inputs in the CPSS model. All available complete 24-h
intervals of actigraphy and photometry data will be included in the analysis. The daily estimated endogenous
circadian temperature minimum obtained from the
CPSS program will be compared with the sleep episode
time derived from actigraphy and photometry for that
day. When the estimated endogenous circadian
temperature minimum falls within a sleep episode, that
sleep episode will be considered circadian “aligned.”
When the estimated endogenous circadian temperature
minimum falls outside the sleep episode, that day’s sleep
episode will be considered to be circadian “misaligned.”
The addition of circadian phase estimation will address a
limitation that has been identified in previous research.
During the in-laboratory sleep periods (naps), we will
use data from the Zmachine® Synergy (General Sleep
Corporation, Cleveland, OH) to (A) measure stages of
sleep and (B) explore the relationship between stages of
sleep and changes in BP and HRV. We will also pose the
question: Do EMS clinicians who obtain more time in
deeper stages of sleep (i.e., stage 3 or 4) during intrashift naps/sleep experience a deeper dip in BP (or a normal dip of 10–20%) than do clinicians who obtain more
time in lighter stages of sleep (i.e., stages 1 or 2)?
Participant timeline {13}
See Figs. 1 and 2 for the time schedule of enrollment,
intervention, measurement assessment, and other relevant
participant activities.
Sample size {14}
Our goal enrollment is 35 total participants with an
estimated 10 of the 35 enrolled not completing the study
protocol or classified as lost to attrition. Our goal for
enrollment is based on several factors. (A) Previous
research suggests 10–33% [89, 90] of EMS workers will
be willing to participate but excluded due to selfreporting a diagnosis of HTN and/or are currently
taking medication for HTN. (B) Previous research
suggests 10–15% attrition in prospective observational
studies [19]. Attrition can impact inferential statistics if
participants with complete follow-up data differ from
participants who are lost to attrition. Our strategies to
address attrition include the following: (A) provide participants with reasonable remuneration and (B) maintain
regular communication with participants including, yet
not limited to, regular email updates, telephone reminders, text message reminders, and other forms of
frequent communication. We will compare available
characteristics between those who cease participation
and those who complete the study as designed.
Recruitment {15}
We will recruit eligible participants from Western
Pennsylvania in the USA. Western Pennsylvania is home
to more than 300 EMS agencies and more than 9000
certified EMS clinicians [52]. All EMS agencies and EMS
clinicians are licensed/certified by the state of
Pennsylvania. Lists of EMS agencies and clinicians are
maintained by regional offices and by health care
systems that provide continuing education and other
resources. We will use these lists to disseminate IRBapproved study flyers. In addition, we will circulate
study-related flyers on social media and reach out to
local EMS education programs to request study-related
information be disseminated to trainees at all EMS levels
of certification. If enrollment falls below two new participants per month, we will hold an online seminar/webinar and invite EMS clinicians in Western Pennsylvania
to attend for purposes of learning more about the study
and to ask questions.
Sequence generation {16a}
An investigator not overseeing the in-lab sessions will
construct the randomization sequence for each participant using the SAS statistical software procedure PROC
PLAN (Cary, NC). The sequences will adhere to the
Williams design [91], which ensures a uniform crossover
design with a balance of order in the experiment as a
whole.
Concealment mechanism {16b}
The assignment for each participant visit will be
transferred to sealed opaque envelopes to be opened at
the beginning of each session.
Implementation {16c}
Two previous studies with a similar study design
reported concealing the objectives of the study and
Patterson et al. Trials
Page 10 of 15
(2021) 22:212
providing study participants with limited details of the
intervention until moments before the intervention was
administered [56, 59–61]. These studies show that full
blinding of study participants and concealment of
intervention details is difficult. Our protocol faces
similar challenges. For purposes of our study, once the
opaque envelope with randomization assignment is
opened, investigators, study staff, and participants will
be alerted to the assigned napping condition. Given this
design, our study is open-label.
Assignment of interventions: blinding
Who will be blinded {17a}
One member of the study team, the primary data analyst
(statistician), will be blinded for the duration of the study.
All other study investigators, staff, and participants will be
blinded to the condition assignment immediately prior to
each session. Once the envelope is opened, all who are on
site at the time of randomization will be made aware of
the assignment and unblinded.
Procedure for unblinding if needed {17b}
N/A. There are no procedures for unblinding once the
opaque envelope has been opened.
Data collection and management
Plans for assessment and collection of outcomes {18a}
The protocol for measurement assessment and
collection of outcome measures includes the use of
continuous monitoring devices, such as ABPM for serial
BP measurement, and cardiac Holter monitoring for
serial HRV measurement for the 72-h protocol repeated
three times for each study participant. For ABPM, we
will assess BP hourly with the Oscar2 device manufactured by SunTech Medical (Morrisville, NC, USA). For
HRV, we will use the NASIFF CardioCard® 5-lead, 3channel device (NASIFF Associates, Inc., Central
Square, NY, USA). As described in the “Outcomes
{12}” section, we will administer surveys at baseline
and again at pre-specified time points in order to capture subjective ratings of sleep and fatigue. Our plan
for assessment will also include monitoring of sleep
depth during the conditions that involve intra-shift
napping. We will use the Zmachine® Synergy for
purposes of assessing depth of sleep during the inlaboratory phase only and only during the two napping conditions. Sleep versus wake will be assessed
with a wrist-worn actigraphy device (wGT3X-BT by
Actigraph Corp., Pensacolo, FL, USA) worn continuously during the three 72-h protocols.
Participants will complete standardized surveys at
baseline, throughout the study protocol, and at the end of
each 72-h period. At baseline, participants will be asked to
complete a standard demographic questionnaire, the
PSQI, ESS, CFQ, OFER, CBI, and SAS surveys. Study staff
will complete seven standardized, paper-based data collection forms. These forms document the following: (A) the
time when devices (i.e., wrist actigraphy, ABPM, Holter
monitors) are applied and/or removed; (B) results of calibration of continuous monitoring devices (i.e., ABPM,
Holter monitor, wrist actigraphy, and the Zmachine® Synergy). Calibration of the Oscar2 device will be similar to
the process described in a separate publication [35]; (C)
in-laboratory hourly, self-reported, single-item assessments of fatigue, sleepiness, irritability, stress, and related
constructs analogous to the items used in previous research [92]; (D) in-laboratory, hourly measurements of
psychomotor vigilance with the brief psychomotor vigilance test (PVT-B). The PVT-B is widely used to assess reaction time (vigilance and alertness), shown to be reliable,
is sensitive to changes in sleep and sleep deprivation, resistant to practice effects, and considered a valid assessment of neurocognitive performance [93–96]; and (E)
self-reported, single-item assessments of fatigue, sleepiness, irritability, stress, and related constructs [92] immediately upon waking from in-laboratory napping periods;
again at 10 min, at 20 min, and at 30 min after waking
from a nap. We will also document vigilance with the
PVT-B immediately upon waking, at 10 min, 20 min, and
30 min. Study staff will transcribe the data documented on
paper-based forms into a REDCap database immediately
after a form is completed. A second study staff member
will review the transcription for accuracy and
completeness.
Plans to promote participant retention and complete
follow-up {18b}
We will distribute a $400 gift card to each participant at
the completion of each of the three study conditions. We
chose $400 per study condition based on our prior
success with recruitment and low attrition with the
targeted population [19, 97, 98]. In total, each participant
who completes the full study protocol will receive $1200
in remuneration. This amount is less than the total
remuneration offered in previous studies with similar
protocols and equivalent participant burden [56–58].
Data management {19}
All data will be downloaded from monitoring devices, or
abstracted from survey instruments, and uploaded to a
password-protected REDCap database maintained by the
principal investigator’s institution [54, 55].
Confidentiality {27}
Confidentiality of study participation will be maintained
by storing all paper-based data collection instruments
and study-related forms in locked filing cabinets in the
Patterson et al. Trials
Page 11 of 15
(2021) 22:212
locked office of study investigators, located on the University of Pittsburgh campus. All data obtained from
electronic devices will be assigned a code number, which
will be used to then store participant data electronically
in a password-protected REDCap database [54, 55].
Plans for collection, laboratory evaluation, and storage of
biological specimens for genetic or molecular analysis in
this trial/future use {33}
N/A this study protocol does not include the collection
of biological specimens.
Statistical methods
Statistical methods for primary and secondary outcomes
{20a}
We will report the demographic characteristics of the
study sample using descriptive statistics and stratify the
final dataset into two categories for the main analysis.
These categories will be labeled as “complete” and
“incomplete data.” We will further describe the average
systolic and diastolic BP, the incidence of blunted BP
dipping, and the proportion of participants with blunted
BP dipping. Blunted nocturnal BP dipping will be
defined as previously described. Our second outcome of
interest is HRV. As prescribed [72], we will examine
HRV based on five time-based measures summarized
over each 24-h period of observation.
To address the impact of napping on BP dipping, we
will conduct paired t tests to determine if the mean
amount of BP dipping differs across conditions.
Generalized linear mixed models (GLMM) with
participant-specific random effects will be utilized to
compare the odds of blunted BP dipping across conditions. We will evaluate the distribution of residuals at
each level of the models for linearity and heterogeneity.
We will check for outliers and influential observations
and sets of observations. The distribution of the data will
be examined, and transformations will be performed as
necessary for valid comparisons. We will use GLMM to
estimate and compare the proportion of EMS workers
with blunted BP dipping and control for the dependence
between repeated measures within each participant with
a random subject effect.
To address the impact of napping on select measures
of HRV, we will use GLMM with appropriate
distribution and link function to estimate and compare
HRV measures between EMS workers across the three
conditions. We will again account for the withinparticipant correlation of repeated measurements and
any participant-dependent covariates that vary in the
study sample. The least square means and corresponding
95% confidence intervals will be calculated from the
models for each group and the difference between
groups.
We also plan to compare the slope of HRV and BP
amplitude following the simulated shift work across the
three conditions. The hypothesis testing will again
follow the GLMM framework. Time-varying slopes will
be calculated for each participant for the recovery
period. These slopes will characterize the change in the
outcome measures (HRV and BP amplitude) following
shift work. We will account for the within-participant
correlation of repeated measurements and any
participant-dependent and time-dependent covariates.
We will account for actual sleep during the periods of
nap opportunity by running multiple statistical models
with one set of models standardized for the nap opportunity (i.e., 30 min vs. 120 min) and another set of
models that account for the depth of sleep (stage) and
the amount of time within each stage of sleep as measured by the Zmachine® Synergy.
Enrollment of 25 participants is projected to provide
80% power to detect a difference in the mean BP dip of
5 mmHg between conditions, assuming two-sided tests,
alpha set at 0.05, and a within-participant standard deviation of 6 mmHg (similar to our previous work). Power
was calculated using G*Power V3.1.9.2, using two-sided
z tests in a Poisson regression with alpha set at 0.05.
Interim analyses {21b}
N/A. This study does not include an interim analysis.
Methods for additional analyses (e.g., subgroup analyses)
{20b}
N/A. This study does not include a pre-defined list of
participant demographic characteristics for purposes of
subgroup analysis.
Methods in analysis to handle protocol non-adherence and
any statistical methods to handle missing data {20c}
Participants with < 70% of scheduled ABPM measures or
incomplete data capture (< 70%) with other measures of
interest will be classified as “incomplete.” These data will
be analyzed separately from participants with complete
data.
Plans to give access to the full protocol, participant-level
data, and statistical code {31c}
Study-related materials and study-related data would be
made available upon request and with permission and
approval from the University of Pittsburgh. All requests
must be reasonable.
Oversight and monitoring
Composition of the coordinating center and trial steering
committee {5d}
This study does not include a coordinating center. The
study principal investigator and two co-investigators will
Patterson et al. Trials
(2021) 22:212
be responsible for monitoring and managing data quality, assess completeness and accuracy of data collection,
implementation and adherence to the study protocol,
and measurement of outcomes.
Composition of the data monitoring committee, its role,
and reporting structure {21a}
Study-related progress and data (e.g., enrolment,
withdrawals) will be reported monthly to the University
of Pittsburgh, Department of Emergency Medicine
Departmental Clinical Research Meeting (DCRM). The
DCRM comprised the department’s vice chair of
research, senior faculty, study coordinators, and
department liaisons with the university’s institutional
review board. The members receive monthly updates,
provide feedback to investigators, and advise on studyrelated challenges and events that may have been or
need to be reported to the university’s institutional review board and/or funding organization.
Frequency and plans for auditing trial conduct {23}
All data maintained electronically in the REDCap
database will be examined for accuracy (quality) and
reported during the monthly DCRM meetings.
Plans for communicating important protocol amendments
to relevant parties (e.g., trial participants, ethical
committees) {25}
All protocol modifications or amendments will be
reported (submitted) to the University of Pittsburgh
Institutional Review Board. Participants will be notified
of the amendments or modifications that impact
participation, confidentiality, or safety.
Dissemination plans {31a}
Our plan for dissemination includes peer-reviewed manuscripts and presentations at professional meetings.
Discussion
Paramedics and EMTs are essential front-line public
safety workers who face excess risk of workplace injury,
mental stress, fatigue, poor sleep quality, and poor health
and well-being. The workforce is limited and poorly
compensated, which is evidenced by a large proportion
working multiple jobs or excessive hours of overtime.
There is great uncertainty regarding the optimal
duration of an intra-shift nap, how best to implement a
napping program, and how napping may impact performance and worker health. Our study will address
worker health outcomes, specifically two indicators of
cardiovascular health, and determine if shorter or longer
duration naps during night shifts have a clinically meaningful impact. Our study will also assess recovery of
these indicators immediately post-night shift, which will
Page 12 of 15
provide additional information for decision-makers and
individual EMS workers.
The experimental protocol outlined in this paper is
novel for the following reasons: (A) it builds on recent
evidence-based guidelines that promote intra-shift napping for fatigue mitigation, (B) the study will involve
EMS clinicians as study subjects and therefore provide
much needed direct evidence as opposed to indirect
evidence involving “non-EMS” volunteers, and (C) our
outcomes of interest include key indicators of cardiovascular disease. With few having assessed these outcomes
in this population [99], under these conditions, the
results of this study will provide new insights for researchers and additional evidence to guide decisionmaking.
One key component of our study is the comparison of
the shorter (30 min) nap to the longer (2 h) nap. There
are relatively few studies comparing shorter and longer
duration naps [57, 62], and even less information about
nap duration germane to EMS work [50]. Many in
public safety would likely favor shorter duration naps
given the potential for sleep inertia and how it can
negatively impact performance immediately upon
waking [8, 51]. The favorability of longer-duration naps
is unknown. However, data from our recent observational study of 56 EMS night shift workers shows that
longer duration naps (e.g., > 60 min) offer greater benefits to cardiovascular health than shorter naps in the
form of a healthy dip in BP [35]. The study protocol outlined in this paper will help clarify the differences and
similarities of different nap durations for EMS workers.
It is plausible that we discover shorter duration naps are
nearly as beneficial as longer duration naps for key indicators of cardiovascular health. It is also equally plausible that we discover longer duration naps are needed in
order to observe benefit in the form of a healthy dip in
BP. Regardless of our findings, the results will be informative to local EMS employers and decision-makers responsible for fatigue mitigation and workplace wellness.
Trial status
Protocol version 1 as of February 17, 2021. Recruitment
is scheduled to commence in March of 2021. The final
participants are expected to complete the study at the
end of the calendar year 2022.
Abbreviations
ABPM: Ambulatory blood pressure monitoring; BP: Blood pressure; CBT: Core
body temperature; CFQ: Chalder Fatigue Questionnaire; CPSS: Circadian
Performance Simulation Software; CVD: Cardiovascular disease; DBP: Diastolic
blood pressure; DCRM: Departmental Clinical Research Meeting;
EMS: Emergency medical services; EMT: Emergency medical technician;
ESS: Epworth Sleepiness Scale; GLMM: Generalized linear mixed models;
HF: High-frequency band; HRV: Heart rate variability; HTN: Hypertension;
IRB: Institutional Review Board; LF: Low-frequency band; MA: Massachusetts;
NC: North Carolina; OFER: Occupational Fatigue and Recovery Scale;
OH: Ohio; PSQI: Pittsburgh Sleep Quality Index; PVT: Psychomotor Vigilance
Patterson et al. Trials
Page 13 of 15
(2021) 22:212
Test; REDCap: Research Electronic Data Capture; rMSSD: Root-mean-square of
the successive normal sinus RR interval difference; SAS: Schedule Attitudes
Survey; SBP: Systolic blood pressure; SDNN: Standard deviation of the interbeat intervals of normal sinus beats; SDANN: Standard deviation of the
averaged normal sinus intervals for all 5-min segments; USA: United States of
America
15261, USA. 2Division of Community Health Services, Emergency Medicine
Program, University of Pittsburgh, School of Health and Rehabilitation
Sciences, Pittsburgh, PA 15261, USA. 3Division of Sleep and Circadian
Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA. 4Harvard
Medical School, Division of Sleep Medicine, Boston, MA 02115, USA.
Received: 6 January 2021 Accepted: 27 February 2021
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s13063-021-05161-4.
Additional file 1:. SPIRIT 2013 Checklist: Recommended items to
address in a clinical trial protocol and related documents.
Additional file 2:. Consent to act as a subject in a research study.
Acknowledgements
Not applicable
Authors’ contributions {31b}
All authors PDP, LSW, MDW, DDS, SEO, TSO, TTS, SEM, FXG, CMG, and CWC
contributed to the design of the study protocol. All authors contributed to
the drafting of the manuscript and provided critically important intellectual
content. All authors provided final approval of the manuscript and are
accountable for all aspects of this work in terms of accuracy and integrity of
all parts of this work. The number of future papers and authorship of papers
that report the results of this research study will be determined by a
committee of two investigators (LSW and PDP). There will be no use of
professional writers.
Availability of data and materials {29} {31c}
Study-related materials and study-related data are available from the corresponding author, and with permission/approval from the University of Pittsburgh, based on reasonable request.
Funding
The ZOLL Foundation has provided funding for this study. The ZOLL
Foundation has no role in the study design, data collection, management,
analysis, interpretation of results, writing of the study findings, or decision on
publication.
Declarations
Ethics approval and consent to participate
The University of Pittsburgh Institutional Review Board (IRB) has reviewed
and approved this study protocol (The University of Pittsburgh IRB ID#
STUDY19120222). Written informed consent to participate will be obtained
from all participants.
Consent for publication
Not applicable
Competing interests {28}
PDP reports grant support from the US Department of Transportation (DOT)
National Highway Traffic Safety Administration (NHTSA), Centers for Disease
Control National Institute for Occupational Safety and Health (CDC/NIOSH),
and the ZOLL foundation; LSW reports grant support from Pennsylvania
Infrastructure Technology Alliance, US Department of Defense (DOD),
National Institute of Health (NIH), ZOLL Foundation, and CDC/NIOSH; MDW
reports grant support from CDC/NIOSH and the Brigham Research Institute
Fund to Sustain Research Excellence; DDS reports grant support from DOD,
NIH, and the David Scaife Foundation; FXG reports grant support from DOD,
NIH, and CDC/NIOSH; CMG reports grant support from DOD, NIH, and the
Pittsburgh Emergency Medicine Foundation (PEMF); CWC reports grant
support from NIH. The other authors declare that they have no competing
interests.
Author details
1
Department of Emergency Medicine, University of Pittsburgh, School of
Medicine, 3600 Forbes Ave., Iroquois Building, Suite 400A, Pittsburgh, PA
References
1. Torquati L, Mielke GI, Brown WJ, Kolbe-Alexander T. Shift work and the risk
of cardiovascular disease. A systematic review and meta-analysis including
dose-response relationship. Scand J Work Environ Health. 2018;44(3):229–38.
2. Morikawa Y, Nakagawa H, Miura K, Ishizaki M, Tabata M, Nishijo M, et al.
Relationship between shift work and onset of hypertension in a cohort of
manual workers. Scan J Work Environ Health. 1999;25(2):100–4.
3. Oishi M, Suwazono Y, Sakata K, Okubo Y, Harada H, Kobayashi E, et al. A
longitudinal study on the relationship between shift work and the
progression of hypertension in male Japanese workers. J Hypertens. 2005;
23(12):2173–8.
4. Kecklund G, Axelsson J. Health consequences of shift work and insufficient
sleep. BMJ. 2016;355:i5210.
5. Vyas MV, Garg AX, Iansavichus AV, Costella J, Donner A, Laugsand LE, et al.
Shift work and vascular events: systematic review and meta-analysis. BMJ.
2012;345:e4800.
6. Morris CJ, Purvis TE, Hu K, Scheer FA. Circadian misalignment increases
cardiovascular disease risk factors in humans. Proc Natl Acad Sci U S A.
2016;113(10):E1402–E11.
7. Yang H, Haack M, Gautam S, Meier-Ewert HK, Mullington JM. Repetitive
exposure to shortened sleep leads to blunted sleep-associated blood
pressure dipping. J Hypertens. 2017;35(6):1187–94.
8. Hilditch CJ, Dorrian J, Banks S. A review of short naps and sleep inertia: do
naps of 30 min or less really avoid sleep inertia and slow-wave sleep? Sleep
Med. 2017;32:176–90.
9. Javaheri S, Redline S. Sleep, slow-wave sleep, and blood pressure. Curr
Hypertens Rep. 2012;14(5):442–8.
10. Sallinen M, Kecklund G. Shift work, sleep, and sleepiness - differences
between shift schedules and systems. Scand J Work Environ Health. 2010;
36(2):121–33.
11. NASEMSO. 2020 National EMS Assessment. Falls Church: The National
Association of State EMS Officials; 2020.
12. Weaver MD, Patterson PD, Fabio A, Moore CG, Freiberg MS, Songer TJ. An
observational study of shift length, crew familiarity, and occupational injury
and illness in emergency medical services workers. Occup Environ Med.
2015;72(11):798–804.
13. Boivin DB, Tremblay GM, James FO. Working on atypical schedules. Sleep
Med. 2007;8(6):578–89.
14. Patterson PD, Runyon MS, Higgins JS, Weaver MD, Teasley EM, Kroemer AJ,
et al. Shorter versus longer shift duration to mitigate fatigue and fatigue
related risks in emergency medical services: a systematic review. Prehosp
Emerg Care. 2018;22(Suppl 1):28–36.
15. Patterson PD, Suffoletto BP, Kupas DF, Weaver MD, Hostler D. Sleep quality
and fatigue among prehospital providers. Prehosp Emerg Care. 2010;14(2):
187–93.
16. Patterson PD, Weaver MD, Frank RC, Warner CW, Martin-Gill C, Guyette FX,
et al. Association between poor sleep, fatigue, and safety outcomes in
emergency medical services providers. Prehosp Emerg Care. 2012;16(1):86–
97.
17. Patterson PD, Weaver MD, Hostler D. EMS provider wellness. In: Cone DC,
Brice JH, Delbridge TR, Myers JB, editors. Emergency medical services:
clinical practice and systems oversight. 2. Chichester: Wiley; 2015. p. 211–6.
18. Patterson PD, Buysse DJ, Weaver MD, Callaway CW, Yealy DM. Recovery
between work shifts among emergency medical services clinicians. Prehosp
Emerg Care. 2015;19(3):365–75.
19. Patterson PD, Buysse DJ, Weaver MD, Doman JM, Moore CG, Suffoletto BP,
et al. Real-time fatigue reduction in emergency care clinicians: the
SleepTrackTXT randomized trial. Am J Ind Med. 2015;58(10):1098–113.
20. Caruso CC. Negative impacts of shiftwork and long work hours. Rehabil
Nurs. 2014;39(1):16–25.
21. Czeisler CA, Gooley JJ. Sleep and circadian rhythms in humans. Cold Spring
Harb Symp Quant Biol. 2007;72:579–97.
Patterson et al. Trials
(2021) 22:212
22. Bloomfield D, Park A. Night time blood pressure dip. World J Cardiol. 2015;
7(7):373–6.
23. Routledge F, McFetridge-Durdle J. Nondipping blood pressure patterns
among individuals with essential hypertension: a review of the literature.
Eur J Cardiovasc Nurs. 2007;6(1):9–26.
24. Clays E, Van Herck K, De Buyzere M, Kittel F, De Backer G, De Bacquer D.
Behavioural and psychosocial correlates of nondipping blood pressure
pattern among middle-aged men and women at work. J Hum Hypertens.
2012;26(6):381–7.
25. Viera AJ, Lin FC, Hinderliter AL, Shimbo D, Person SD, Pletcher MJ, et al.
Nighttime blood pressure dipping in young adults and coronary artery
calcium 10-15 years later: the coronary artery risk development in young
adults study. Hypertension. 2012;59(6):1157–63.
26. Phillips RA, Sheinart KF, Godbold JH, Mahboob R, Tuhrim S. The association
of blunted nocturnal blood pressure dip and stroke in a multiethnic
population. Am J Hypertens. 2000;13(12):1250–5.
27. Verdecchia P, Schillaci G, Guerrieri M, Gatteschi C, Benemio G, Boldrini F,
et al. Circadian blood pressure changes and left ventricular hypertrophy in
essential hypertension. Circulation. 1990;81(2):528–36.
28. Zakopoulos N, Stamatelopoulos S, Toumanidis S, Saridakis N, Trika C,
Moulopoulos S. 24 h blood pressure profile affects the left ventricle
independently of the pressure level. A study in untreated essential
hypertension diagnosed by office blood pressure readings. Am J Hypertens.
1997;10(2):168–74.
29. Giaconi S, Levanti C, Fommei E, Innocenti F, Seghieri G, Palla L, et al.
Microalbuminuria and casual and ambulatory blood pressure monitoring in
normotensives and in patients with borderline and mild essential
hypertension. Am J Hypertens. 1989;2(4):259–61.
30. Timio M, Venanzi S, Lolli S, Lippi G, Verdura C, Monarca C, et al. “Nondipper” hypertensive patients and progressive renal insufficiency: a 3-year
longitudinal study. Clin Nephrol. 1995;43(6):382–7.
31. Ohkubo T, Imai Y, Tsuji I, Nagai K, Watanabe N, Minami N, et al. Relation
between nocturnal decline in blood pressure and mortality. The Ohasama
Study. Am J Hypertens. 1997;10(11):1201–7.
32. Fialho G, Cavichio L, Povoa R, Pimenta J. Effects of 24-h shift work in the
emergency room on ambulatory blood pressure monitoring values of
medical residents. Am J Hypertens. 2006;19(10):1005–9.
33. Adams SL, Roxe DM, Weiss J, Zhang F, Rosenthal JE. Ambulatory blood
pressure and Holter monitoring of emergency physicians before, during,
and after a night shift. Acad Emerg Med. 1998;5(9):871–7.
34. Su TC, Lin LY, Baker D, Schnall PL, Chen MF, Hwang WC, et al. Elevated
blood pressure, decreased heart rate variability and incomplete blood
pressure recovery after a 12-hour night shift work. J Occup Health. 2008;
50(5):380–6.
35. Patterson PD, Mountz KA, Agostinelli GM, Weaver MD, Yu YC, Herbert
BM, et al. Ambulatory blood pressure monitoring among emergency
medical services night shift workers. Occup Environ Med.
2021;78(1):29–35.
36. Lyytikainen K, Toivonen L, Hynynen E, Lindholm H, Kyrolainen H. Recovery
of rescuers from a 24-h shift and its association with aerobic fitness. Int J
Occup Med Environ Health. 2017;30(3):433–44.
37. Hulsegge G, Gupta N, Proper KI, van Lobenstein N, IJzelenberg W, Hallman
DM, et al. Shift work is associated with reduced heart rate variability among
men but not women. Int J Cardiol. 2018;258:109–14.
38. Lee S, Kim H, Kim D-H, Yum M, Son M. Heart rate variability in male shift
workers in automobile manufacturing factories in South Korea. Int Arch
Occup Environ Health. 2015;88(7):895–902.
39. Neufeld EV, Carney JJ, Dolezal BA, Boland DM, Cooper CB. Exploratory study
of heart rate variability and sleep among emergency medical services shift
workers. Prehosp Emerg Care. 2017;21(1):18–23.
40. No_authors_listed. Heart rate variability. Standards of measurement,
physiological interpretation, and clinical use. Task Force of the European
Society of Cardiology and the North American Society of Pacing and
Electrophysiology. Eur Heart J 1996;17(3):354–381.
41. Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and
norms. Front Public Health. 2017;5:258.
42. Goldberger AL. Is the normal heartbeat chaotic or homeostatic? News
Physiol Sci. 1991;6:87–91.
43. Thayer JF, Yamamoto SS, Brosschot JF. The relationship of autonomic
imbalance, heart rate variability and cardiovascular disease risk factors. Int J
Cardiol. 2010;141(2):122–31.
Page 14 of 15
44. Dekker JM, Crow RS, Folsom AR, Hannan PJ, Liao D, Swenne CA, et al.
Low heart rate variability in a 2-minute rhythm strip predicts risk of
coronary heart disease and mortality from several causes: the ARIC
Study. Atherosclerosis Risk In Communities. Circulation. 2000;102(11):
1239–44.
45. Mitani S, Fujita M, Shirakawa T. Circadian variation of cardiac autonomic
nervous profile is affected in Japanese ambulance men with a working
system of 24-h shifts. Int Arch Occup Environ Health. 2006;79(1):27–32.
46. Smith L, Folkard S, Tucker P, Macdonald I. Work shift duration: a review
comparing eight hour and 12 hour shift systems. Occup Environ Med. 1998;
55(4):217–29.
47. Patterson PD, Weaver MD, Hostler D, Guyette FX, Callaway CW, Yealy DM.
The shift length, fatigue, and safety conundrum in EMS. Prehosp Emerg
Care. 2012;16(4):572–6.
48. Dinges DF, Orne MT, Whitehouse WG, Orne EC. Temporal placement of a
nap for alertness: contributions of circadian phase and prior wakefulness.
Sleep. 1987;10(4):313–29.
49. Ruggiero JS, Redeker NS. Effects of napping on sleepiness and sleep-related
performance deficits in night-shift workers: a systematic review. Biol Res
Nurs. 2014;16(2):134–42.
50. Martin-Gill C, Barger LK, Moore CG, Higgins JS, Teasley EM, Weiss PM, et al.
Effects of napping during work on sleepiness and performance in
emergency medical services personnel and similar shift workers: a
systematic review and meta-analysis. Prehosp Emerg Care. 2018;22(Suppl 1):
47–57.
51. Patterson PD, Higgins JS, Van Dongen HPA, Buysse DJ, Thackery RW, Kupas
DF, et al. Evidence-based guidelines for fatigue risk management in
emergency medical services. Prehosp Emerg Care. 2018;22(Suppl 1):89–101.
52. EMS.West.Region. The EMS West Annual Report. Pittsburgh: EMS.West; 2020.
Available from: https://www.emsi.org/wp-content/uploads/2020/07/2020EMS-West-Annual-Report-posting.pdf. Accessed 4 Aug 2020.
53. Boudreau P, Yeh WH, Dumont GA, Boivin DB. Circadian variation of heart
rate variability across sleep stages. Sleep. 2013;36(12):1919–28.
54. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research
electronic data capture (REDCap)--a metadata-driven methodology and
workflow process for providing translational research informatics support. J
Biomed Inform. 2009;42(2):377–81.
55. Harris PA, Taylor R, Minor BL, Elliot V, Fernandez M, O’Neal L, et al. The
REDCap consortium: building an international community of software
platform partners. J Biomed Inform. 2019;95:103208.
56. Della Rocco PS, Comperatore C, Caldwell L, Cruz C. The effects of napping
on night shift performance. Washington, DC: Civil Aeromedical Institute,
Federal Aviation Administration; 2000. Contract no.: DOT/FAA/AM-00/10
57. Mulrine HM, Signal TL, van den Berg MJ, Gander PH. Post-sleep inertia
performance benefits of longer naps in simulated nightwork and extended
operations. Chronobiol Int. 2012;29(9):1249–57.
58. Signal TL, van den Berg MJ, Mulrine HM, Gander PH. Duration of sleep
inertia after napping during simulated night work and in extended
operations. Chronobiol Int. 2012;29(6):769–79.
59. Hilditch CJ, Centofanti SA, Dorrian J, Banks S. A 30-minute, but not a
10-minute nighttime nap is associated with sleep inertia. Sleep. 2016;
39(3):675–85.
60. Centofanti SA, Dorrian J, Hilditch CJ, Banks S. Do night naps impact driving
performance and daytime recovery sleep? Accid Anal Prev. 2017;99(Pt B):416–21.
61. Centofanti SA, Hilditch CJ, Dorrian J, Banks S. The impact of short night-time
naps on performance, sleepiness and mood during a simulated night shift.
Chronobiol Int. 2016;33(6):706–15.
62. Kubo T, Takahashi M, Takeyama H, Matsumoto S, Takeshi E, Murata K, et al.
How do the timing and length of a night-shift nap affect sleep inertia?
Chronobiol Int. 2010;27(5):1031–44.
63. Kubo T, Takeyama H, Matsumoto S, Ebara T, Murata K, Tachi N, et al. Impact
of nap length, nap timing and sleep quality on sustaining early morning
performance. Ind Health. 2007;45(4):552–63.
64. Saito Y, Sasaki T. The effect of length of a nocturnal nap on fatigue
feelings during subsequent early morning hours. J Sci Labour. 1996;72(1
(Part II)):15–23.
65. Sallinen M, Harma M, Akerstedt T, Rosa R, Lillqvist O. Promoting alertness
with a short nap during a night shift. J Sleep Res. 1998;7(4):240–7.
66. Takeyama H, Matsumoto S, Murata K, Ebara T, Kubo T, Tachi N, et al. Effects
of the length and timing of nighttime naps on task performance and
physiological function. Rev Saude Publica. 2004;38(Suppl):32–7.
Patterson et al. Trials
Page 15 of 15
(2021) 22:212
67. Temple JL, Hostler D, Martin-Gill C, Moore CG, Weiss PM, Sequeira DJ, et al.
A systematic review and meta-analysis of the effects of caffeine in fatigued
shift workers: implications for emergency medical services personnel.
Prehosp Emerg Care. 2018;22(Suppl 1):37–46.
68. Bonnet MH, Gomez S, Wirth O, Arand DL. The use of caffeine versus
prophylactic naps in sustained performance. Sleep. 1995;18(2):97–104.
69. Parati G, Stergiou G, O’Brien E, Asmar R, Beilin L, Bilo G, et al. European
Society of Hypertension practice guidelines for ambulatory blood pressure
monitoring. J Hypertens. 2014;32(7):1359–66.
70. Henskens LH, Kroon AA, van Oostenbrugge RJ, Haest RJ, Lodder J, de
Leeuw PW. Different classifications of nocturnal blood pressure dipping
affect the prevalence of dippers and nondippers and the relation with
target-organ damage. J Hypertens. 2008;26(4):691–8.
71. Fagard R, Brguljan J, Thijs L, Staessen J. Prediction of the actual awake and
asleep blood pressures by various methods of 24 h pressure analysis. J
Hypertens. 1996;14(5):557–63.
72. Umetani K, Singer DH, McCraty R, Atkinson M. Twenty-four hour time
domain heart rate variability and heart rate: relations to age and gender
over nine decades. J Am Coll Cardiol. 1998;31(3):593–601.
73. Kleiger RE, Miller JP, Bigger JTJ, Moss AJ. Decreased heart rate variability and
its association with increased mortality after acute myocardial infarction. Am
J Cardiol. 1987;59(4):256–62.
74. Huikuri HV, Stein PK. Heart rate variability in risk stratification of cardiac
patients. Prog Cardiovasc Dis. 2013;56(2):153–9.
75. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh
Sleep Quality Index: a new instrument for psychiatric practice and research.
Psychiatr Serv. 1989;28(2):193–213.
76. Johns MW. A new method for measuring daytime sleepiness: the Epworth
sleepiness scale. Sleep. 1991;14(6):540–5.
77. Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, et al.
Development of a fatigue scale. J Psychosom Res. 1993;37(2):147–53.
78. Winwood PC, Winefield AH, Dawson D, Lushington K. Development and
validation of a scale to measure work-related fatigue and recovery: the
Occupational Fatigue Exhaustion/Recovery Scale (OFER). J Occup Environ
Med. 2005;47(6):594–606.
79. Kristensen TS, Borritz M, Villadsen E, Christensen KB. The Copenhagen
Burnout Inventory: a new tool for the assessment of burnout. Work Stress.
2005;19(3):192–207.
80. Dunham RB, Pierce JL. Attitudes toward work schedules: construct
definition, instrument development, and validation. Acad Manag J. 1986;
29(1):170–82.
81. Giles TD. Circadian rhythm of blood pressure and the relation to
cardiovascular events. J Hypertens Suppl. 2006;24(2):S11–S6.
82. Duffy JF, Dijk DJ, Klerman EB, Czeisler CA. Later endogenous circadian
temperature nadir relative to an earlier wake time in older people. Am J
Phys. 1998;275(5 Pt 2):R1478–R87.
83. Jewett ME, Forger DB, Kronauer RE. Revised limit cycle oscillator model of
human circadian pacemaker. J Biol Rhythm. 1999;14(6):493–9.
84. Kronauer RE, Forger DB, Jewett ME. Quantifying human circadian
pacemaker response to brief, extended, and repeated light stimuli over the
phototopic range. J Biol Rhythm. 1999;14(6):500–15.
85. Jewett ME, Kroemer AJ, Czeisler CA. Phase-amplitude resetting of the
human circadian pacemaker via bright light: a further analysis. J Biol
Rhythm. 1994;9(3–4):295–314.
86. Jewett ME, Rimmer DW, Duffy JF, Klerman EB, Kroemer AJ, Czeisler CA.
Human circadian pacemaker is sensitive to light throughout subjective day
without evidence of transients. Am J Phys. 1997;273(5 Pt 2):R1800–R9.
87. Jewett ME, Kronauer RE. Refinement of a limit cycle oscillator model of the
effects of light on the human circadian pacemaker. J Theor Biol. 1998;192(4):
455–65.
88. Flynn-Evans EE, Barger LK, Kubey AA, Sullivan JP, Czeisler CA. Circadian
misalignment affects sleep and medication use before and during
spaceflight. NPJ Microgravity. 2016;2:15019.
89. Studnek JR, Bentley M, Crawford JM, Fernandez AR. An assessment of key
health indicators among emergency medical services professionals. Prehosp
Emerg Care. 2010;14(1):14–20.
90. Whelton PK, Carey RM, Aronow WS, Casey DEJ, Collins KJ, Dennison
Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/
ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and
management of high blood pressure in adults: a report of the American
91.
92.
93.
94.
95.
96.
97.
98.
99.
College of Cardiology/American Heart Association Task Force on Clinical
Practice Guidelines. Hypertension. 2018;71(6):e13–e115.
Wang BS, Wang XJ, Gong LK. The construction of a Williams design and
randomization in cross-over clinical trials using SAS. J Stat Softw. 2009;
29(Code Snippet 1):1–10.
Buysse DJ, Thompson W, Scott J, Franzen PL, Germain A, Hall M, et al.
Daytime symptoms in primary insomnia: a prospective analysis using
ecological momentary assessment. Sleep Med. 2007;8(3):198–208.
Van Dongen HPA, Maislin G, Mullington JM, Dinges DF. The cumulative cost
of additional wakefulness: dose-response effects on neurobehavioral
functions and sleep physiology from chronic sleep restriction and total
sleep deprivation. Sleep. 2003;26(2):117–26.
Balkin TJ, Bliese PD, Belenky G, Sing H, Thorne DR, Thomas M, et al.
Comparative utility of instruments for monitoring sleepiness-related
performance decrements in the operational environment. J Sleep Res. 2004;
13(3):219–27.
Basner M, Mollicone D, Dinges DF. Validity and sensitivity of a brief
psychomotor vigilance test (PVT-B) to total and partial sleep deprivation.
Acta Astronaut. 2011;69(11–12):949–59.
Basner M, Hermosillo E, Nasrini J, McGuire S, Saxena S, Moore TM, et al.
Repeated administration effects of psychomotor vigilance test performance.
Sleep. 2018;41(1). https://doi.org/10.1093/sleep/zsx187.
Patterson PD, Moore CG, Guyette FX, Doman JM, Sequeira D, Werman HA,
et al. Fatigue mitigation with SleepTrackTXT2 in air medical emergency care
systems: study protocol for a randomized controlled trial. Trials. 2017;18(1):
254. https://doi.org/10.1186/s13063-017-1999-z.
Patterson PD, Weaver MD, Markosyan MA, Moore CG, Guyette FX, Doman
JM, et al. Impact of shift duration on alertness among air-medical airmedical emergency care clinician shift workers. Am J Ind Med. 2019;62(4):
325–36.
Patterson PD, Mountz KA, Budd CT, Bubb JL, Hsin AU, Weaver MD, et al.
Impact of shift work on blood pressure among emergency medical services
clinicians and related shift workers: a systematic review and meta-analysis.
Sleep Health. 2020;6(3):387–98.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.