Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT06105307 |
| Other study ID # |
K01OH012549 |
| Secondary ID |
K01OH012549 |
| Status |
Not yet recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
February 20, 2024 |
| Est. completion date |
August 31, 2026 |
Study information
| Verified date |
January 2024 |
| Source |
University of Cincinnati |
| Contact |
Beverly Hittle, PhD, RN |
| Phone |
513-558-5186 |
| Email |
Beverly.Hittle[@]uc.edu |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
The U.S. registered nurse (RN) workforce is the largest in the Healthcare and Social
Assistance Sector and is at high risk for injuries and errors due to poor sleep and fatigue.
Shift work (i.e., nights, evenings, rotating shifts) can contribute to RNs not obtaining
adequate, restful sleep. Work intensity, including heavy physical and emotional workloads of
caring for critically ill patients, can contribute to job stress, resulting in spill-over
effects at home when RNs experience difficulties falling and staying asleep. To address work
and home sleep barriers, this project proposes the development and pilot testing of RN-SLEEP,
a skill-building mobile application designed to improve sleep. RN-SLEEP will provide a
convenient, flexible space to learn sleep-enhancing evidence-based shift work-specific
strategies, and cognitive-behavioral methods, (e.g., goal setting, relaxation training).
Using NIOSH's Research 2 Practice (R2P) approach, the study team will collaborate with
participants (N=18-24) from an RN union to refine RN-SLEEP content, integrating current sleep
literature (including National Institute for Occupational Safety and Health [NIOSH] material)
with cognitive-behavioral based training. RN-SLEEP will be pilot-tested using a two-group
pretest-posttest study design, comparing sleep outcome measures (duration, quality) of
RN-SLEEP participant users (n=38) with participants from an education control group (n=38).
Data trends on fatigue, what drives behavior change (beliefs and self-efficacy), and other
sleep outcome measures (timing, regularity, efficiency, daytime sleepiness) will be explored.
RN-SLEEP goals align with Healthy People 2030, NIOSH's strategic goal to promote safe and
healthy work design and well-being through two NIOSH Healthcare and Social Assistance
Sector/Healthy Work Design Cross-Sector (HCSA/HWD) intermediate goals. HWD goal 7.2A is to
conduct intervention research addressing fatigue (poor sleep sequela) due to suboptimal work
designs (shift work) in the healthcare industry. HCSA/HWD goal 7.12A prioritizes
interventions designed to impact work and non-work contributors to safety and health. This
RN-SLEEP intervention aims to improve sleep by building skills that help RNs overcome
obstacles to sleep from work and home, thus improving health and safety. Immediate outputs
include a mobile app, designed and tested in collaboration with RNs, to improve sleep. Study
results will be disseminated through our union collaborators, nursing conferences and journal
publications, and our University's NIOSH-sponsored Education and Research Center social media
outlets. Intermediate outcomes include enhancing RN sleep through training rarely available
in nursing schools and traditional hospital health and safety training programs. Improving
sleep can reduce fatigue and may decrease occupational injuries and errors. RN-SLEEP is
adaptable, where future versions could be modified to meet the needs of other HCSA workers
(i.e., nursing aides) and workers in other industries (e.g., oil and gas) scheduled to work
non-standard work hours. End outcomes include integrating RN-SLEEP into a broader hospital
organization intervention to mitigate fatigue risks.
Description:
The majority of RNs in the U.S. work in hospitals and post-acute care centers where their
sleep could be compromised as a result of shift work (i.e., work outside 7 a.m. to 6 p.m.)
and long work hours. RNs also face tremendous job stress when caring for critically ill
patients, which can disrupt sleep. Sleep health is defined by multiple components including
sleep timing, regularity, efficiency, duration, quality, and daytime sleepiness. When RNs
experience poor sleep they are at increased risk for outcomes that have negative health and
safety concerns for the RNs (e.g., fatigue, chronic disease development, on-the-job injuries)
and for their patients. Despite these risks, RNs are reporting poor sleep quality and shorter
sleep duration than what is recommended 7-9 hours/24-hour. Some research has been conducted
that shows when RNs obtain training on sleep strategies (e.g., pre-shift naps) related to
working shift work, they see an improvement in their sleep. While helpful, RNs may further
benefit from a more holistic training approach to address the wider barriers to sleep, such
as job stress. A holistic sleep approach can provide RNs with evidence-based skills to cope
with shift adaptation and psychological sleep barriers while motivating RNs with encouraging
behavior change strategies (e.g., goal setting). As a result, RNs may see an improvement in
sleep health and decreased fatigue.
This project proposes to develop a sleep training program designed to meet the needs of RNs
working shift work. As such, the training program, RN-SLEEP, would include shift work
strategies, basics of sleep science and physiology, behavior change components, and
strategies found in an effective behavioral sleep medicine treatment known as cognitive
behavioral therapy for insomnia (CBT-I). The candidate, Dr. Hittle, has expertise in
occupational health and safety, including sleep and shift work in the healthcare industry.
Dr. Hittle has assembled a mentoring team of experts to guide her training in
cognitive-behavioral sleep methods for integration into worker sleep interventions,
intervention research with a focus on mHealth, and implementation science using a Total
Worker Health approach. Dr. Hittle's short-term goal is to become an independent occupational
health and safety scientist skilled in the use of methodologies and techniques required for
intervention research and successful implementation in the workplace. This K01 proposal
serves as an opportunity for Dr. Hittle to gain these skills and build a body of research
focused on sleep training for workers. The resources, time, and, materials needed for this
project are available through the University of Cincinnati (UC), the College of Nursing, and
resources from Dr. Wong (Primary Mentor) at the National Institute for Occupational Safety
and Health. Other UC-based resources include UCIT which will support Dr. Hittle's mobile
application development and the Center for Clinical & Translational Training and Science
which offers services for K01 awardees in an effort to foster junior researchers.
This project has two aims:
1. To refine a mobile application, RN-SLEEP, to determine the training components of most
interest to RNs when looking to improve their sleep.
2. To pilot test RN-SLEEP with a pretest-posttest, repeated measure study design to measure
RN participant engagement with RN-SLEEP, appeal (e.g., aesthetics, ease of use), and the
usefulness of the training contents to improve RN sleep over the study period versus an
educational training on healthy living. This pilot test will also help the researchers
better understand the functionality of study activities.
For aim 1, RN-SLEEP content refinement:
This qualitative component of the project will recruit 18-24 participants for focus group
data collection. Participants will be recruited using a convenience sampling method and will
be assigned as recruited (non-randomized) to one of three focus groups. Six to eight
participants will be in each focus group. The first set of focus groups will be conducted to
determine the best content to include in RN-SLEEP. RN-SLEEP content will be refined. Then, a
second set of focus groups will occur, sharing the updated RN-SLEEP with participants for
final feedback. Focus group sample sizes were determined based on the literature. Focus group
data will be analyzed using a modified constant comparative analysis method.
For aim 2, RN-SLEEP intervention will be pilot-tested. Method for assigning participants to
intervention versus control groups: Once participants are determined to be eligible for the
study and informed consent is signed, the investigators will randomize participants to the
RN-SLEEP intervention or educational control group. The investigators will use REDCap, a data
management platform, to randomly assign participants, stratifying groups by self-reported
sex.
Method for delivering the intervention: Baseline measures will be collected. Participants
will then be asked to engage daily with the RN-SLEEP or educational control group, based on
their assigned group, for four weeks. Post-intervention measures will be collected 4 and
8-weeks after the intervention period is complete.
Method for sample size determination: Our goal for recruitment is 76 participants (38 for
each group). The investigators determined our sample size based on power calculations for our
primary outcome measures (sleep duration and sleep quality) and based on the literature and
previous work by the PI. The investigators increased the power calculation total sample goal
of 58 total participants by 30% to account for any participants lost to attrition.
Method for data analysis:
Primary outcome measures (sleep duration, sleep quality): Descriptive statistics (i.e.,
means, 95% confidence intervals) will be used to describe characteristics and outcome
variables for the overall study sample and each study group (intervention and education
control). Between group differences for sleep duration and quality will be assessed using a
two group independent t-test or Mann-Whitney U (if non-parametric testing needed). If
statistical differences are noted between sleep duration and quality, appropriate statistical
analyses will be completed with positively correlating covariates included in model.
Secondary outcome measures: Fatigue, other measures of Sleep Health (timing, regularity,
efficiency, daytime sleepiness), Sleep efficacy and beliefs Descriptive statistics on
fatigue, sleep beliefs, self-efficacy and remaining sleep health measures will be explored
for pre-and-post-training data trends for the intervention and control groups.
Secondary outcome measures: Mobile App metrics for Acceptability, Usability, and Engagement
The investigators will compute and report descriptive statistics on 4 and 8-week
post-training acceptability, usability, and app engagement measures.
Other outcome measures: study feasibility measures The investigators will be monitoring
recruitment and retention statistics throughout the study. The investigators will report on
screened, screened eligible, and enrolled participants, and participant retention rates at 4
and 8-week post-training data collection.
