sleep health

Quantitative Research

Employee Sleep and Workplace Health Promotion: A Systematic Review

Rebecca Robbins, PhD1, Chandra L. Jackson, PhD, MS2, Phoenix Underwood, BS1, Dorice Vieira, MLS, MA, MPH1, Giradin Jean-Louis, PhD1, and Orfeu M. Buxton, PhD3,4,5,6

Abstract

Objective: Workplace-based employee health promotion programs often target weight loss or physical activity, yet there is growing attention to sleep as it affects employee health and performance. The goal of this review is to systematically examine workplace-based employee health interventions that measure sleep duration as an outcome.

Data Source: We conducted systematic searches in PubMed, Web of Knowledge, EMBASE, Scopus, and PsycINFO (n ¼ 6177 records).

Study Inclusion and Exclusion Criteria: To be included in this systematic review, studies must include (1) individuals aged >18 years, (2) a worker health-related intervention, (3) an employee population, and (4) sleep duration as a primary or secondary outcome.

Results: Twenty studies met criteria. Mean health promotion program duration was 2.0 months (standard deviation [SD]¼ 1.3), and mean follow-up was 5.6 months (SD ¼ 6.5). The mean sample size of 395 employees (SD ¼ 700.8) had a mean age of 41.5 years (SD ¼ 5.2). Measures of sleep duration included self-report from a general questionnaire (n ¼ 12, 66.6%), self-report based on Pittsburgh Sleep Quality Index (n¼ 4, 22.2%), and self-report and actigraphy combined (n¼ 5, 27.7%). Studies most commonly included sleep hygiene (35.0%), yoga (25.0%), physical activity (10.0%), and cognitive–behavioral therapy for insomnia (10.0%) interventions. Across the interventions, 9 different behavior change techniques (BCTs) were utilized; the majority of interven- tions used 3 or fewer BCTs, while 1 intervention utilized 4 BCTs. Study quality, on average, was 68.9% (SD ¼ 11.1). Half of the studies found workplace-based health promotion program exposure was associated with a desired increase in mean nightly sleep duration (n ¼ 10, 50.0%). Conclusions: Our study findings suggest health promotion programs may be helpful for increasing employee sleep duration and subsequent daytime performance.

Keywords workplace health promotion, behavior change techniques, sleep health, sleep duration, systematic review

Objective

Poor sleep is prevalent among working-age adults1,2 and is

associated with numerous adverse workplace outcomes.3 Sev-

eral national entities, including the American Heart Associa-

tion, the National Institute for Occupational Health and Safety,

and the Centers for Disease Control, call for attention to

workplace-based health promotion as a promising tool for pro-

moting population health practices, such as sleep.4-7 We sys-

tematically review the characteristics and outcomes of

workplace health promotion interventions that measure

employee sleep duration.

Insufficient sleep among employees has significant work-

place consequences. For instance, insufficient employee sleep

is associated with lower information processing,8 impaired

cognition,9-12 and reduced task performance.13 Litwiller and

1 Center for Health Behavior Change, Department of Population Health, NYU

School of Medicine, New York, NY, USA 2 Epidemiology Branch, Department of Health and Human Services, National

Institute of Environmental Health Sciences, National Institutes of Health,

Research Triangle Park, NC, USA 3 Department of Biobehavioral Health, College of Health and Human

Development, Pennsylvania State University, University Park, PA, USA 4 Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA 5 Division of Sleep and Circadian Disorders, Departments of Medicine and

Neurology, Brigham and Women’s Hospital, Sleep Health Institute, Boston,

MA, USA 6 Department of Social and Behavioral Science, Harvard Chan School of Public

Health, Boston, MA, USA

Corresponding Author:

Rebecca Robbins, 180 Madison Avenue, New York, NY, USA.

Email: rebecca.robbins@nyulangone.org

American Journal of Health Promotion 2019, Vol. 33(7) 1009-1019 ª The Author(s) 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0890117119841407 journals.sagepub.com/home/ahp

colleagues3 found a significant association between employee

sleep quality and duration and poor work-related outcomes,

including workload, depression, and fatigue. Finally, Mullins

and colleagues14 have found that sleep mediates the relation-

ship between job demands and job performance, suggesting

that employee sleep is vital for an efficient workforce.

Sleep deprivation in the workplace comes at a cost to

employers. Research has found employees with untreated

insomnia cost employers $2280 more on average than an

employee without insomnia each year in terms of absenteeism,

presenteeism (showing up to work but underperforming),

reduced performance, accidents, and injuries.15 It is estimated

that total direct and indirect health-care costs associated with

insufficient sleep duration in the United States range from $30

to $40 billion annually, an important consideration for employ-

ers with employer-based health insurance.16,17 Another study

using data from a statewide employee health program promo-

tion showed employee sleep difficulty is linked with absentee-

ism, lower workplace productivity, and increased health-care

costs.18

Although programs have been demonstrated to improve

outcomes among individuals diagnosed with insomnia, such

as cognitive behavioral therapy for insomnia (CBTI), we

know little about the efficacy of these approaches in work-

place settings. Populations, is less well known.19 Workplace-

based health promotion is a compelling approach for several

reasons, such as the ability to reach a large proportion of the

general population with evidence-based programs.20 The field

of workplace-based health promotion has become increas-

ingly prevalent among US worksites. In 2004, national data

demonstrated nearly all US employers with �750 employees offered policies and programs related to employee health; yet,

only 6.9% of worksites offered what was termed “comprehensive” worksite wellness initiatives.21 According

to Baker and colleagues, “comprehensive” programs include

both employee health promotion and employee risk reduc-

tion.22 Although one report shows over 90% of employers with �50 000 employees were offered some health promo- tion, sleep was not a focus of any of the selected programs.23

Although workplace health promotion for employees is

increasingly common in the workplace, few are comprehen-

sive, and very little attention in programming has been given

to employee sleep duration.

The goal of this review is to summarize the evidence on

workplace health promotion programs that measure employee

sleep duration as an outcome. Evidence suggests that sufficient

sleep duration is an essential and modifiable determinant of

health,24-26 and as such, sleep is a powerful potential target for

workplace wellness programs. By obtaining a more complete

summary of the role of workplace-based employee health pro-

grams and sleep duration-related outcomes, our hope is that

future workplace wellness programs can incorporate

evidence-based health promotion programs to help employees

maintain or obtain healthy sleep habits, such as sufficient sleep

duration on a regular basis.

Methods

We conducted a systematic review of studies that include sleep

duration as an outcome of a health promotion program to pro-

mote various health behaviors among employees in a workplace

setting. The search adheres to the Preferred Reporting for Sys-

tematic Review Protocols (PRISMA) guidelines. This review

has been registered with PROSPERO: CRD42016037748.

Eligibility Criteria

Studies were included if they were interventional in nature

(eg, randomized controlled trial [RCT], 2-arm nonrandomized

intervention, and 1-arm pretest/posttest), carried out in

employed adults (>18 years old), were conducted in a work-

place context, and measured sleep duration as an outcome.

Although this review did not have an English language

restriction, all included articles were published in English.

We excluded cross-sectional studies, studies that did not mea-

sure sleep duration as an outcome, and studies carried out in

nonhumans. Also, studies recruiting shift workers were

excluded as these individuals need specialized recommenda-

tions due to circadian misalignment imposed by shift work

schedules.27

Search Strategy

The following databases were searched: PubMed/Medline,

Embase, Web of Science, the Cumulative Index to Nursing and

Allied Health, PyscINFO, BIOSIS Citation Index, and the

Cochrane Library. The New York Academy of Medicine Grey

Literature, WorldCat’s OAISster, and OpenGrey databases also

retrieved relevant literature. Additionally, a search was per-

formed within the table of contents of the following journals:

Journal of Occupational and Environmental Medicine, Sleep,

International Archives of Occupational and Environmental

Health, Occupational Medicine (London), Journal of Sleep

Research, Occupational and Environmental Medicine, Sleep

Medicine, and Journal of Occupational Health. The date of the

search included all published literature in press on or before

September 1, 2018 (date last searched). From the articles that

were identified as eligible, a search of the articles within their

bibliographies was also conducted. We used combinations of

text words and thesaurus terms, that is, work [MeSH], work-

place [MeSH Terms], occupational health [MeSH Terms],

occupational health [MeSH Terms], employee [All Fields],

health promotion [MeSH Terms], interventions [All Fields],

and sleep [MeSH Terms].

Data Screening

Records were identified using the search strategy and then

exported to EndNote X7. Irrelevant records were screened out

by 2 trained research assistants (RR and PU) based on titles and

abstracts. Full-text retrieval was conducted for potentially eli-

gible articles. Bibliographies of the selected articles were also

analyzed for potentially eligible articles. The studies that were

1010 American Journal of Health Promotion 33(7)

retrieved for detailed analysis were assessed by the indepen-

dent reviewers to ensure they satisfied the inclusion criteria.

Any disagreements were resolved through consensus or discus-

sion with all coauthors.

Data Extraction

Extracted data were analyzed using RevMan (version 5). Data

were extracted in several general categories, including study

design and characteristics, study population demographics

(age, race/ethnicity), intervention characteristics (eg, work-

force population, intervention components, such as behavior

change techniques [BCTs], and duration of the intervention),

sleep duration measurement (eg, wrist actigraphy or self-

report), and outcomes (eg, change in sleep duration associ-

ated with exposure to the intervention).28 When the specific

Pittsburgh Sleep Quality Index (PSQI) item for sleep duration

was provided in selected studies,29 it was included in the

review summary; otherwise, the PSQI global score is dis-

played, as it is constitutive of sleep duration, among other

factors. In some cases, the baseline and follow-up sleep times

were reported. In other cases, change in sleep duration was

reported. The data extracted in this review reflect the pub-

lished findings.

Behavior Change Techniques

Behavior change techniques were coded in the current systema-

tic review according to the 40-BCT taxonomy published by

Michie and colleagues.30 This taxonomy of BCTs outlines a

wide array of BCTs and strategies, ranging from goal setting to

role modeling. Two reviewers assigned BCTs to each study and

then discussed any discrepancies until agreement was reached.

The BCT taxonomy was adhered to strictly with the exception

of “educational seminars” that lacked a direct corollary BCT

taxonomy. Consequently, the study team added “educational

seminars” as a BCT in this review. Figure 1 displays the flow

diagram of study screening according to PRISMA guidelines.

Intervention Type

Coders were trained to extract the “intervention type,” or the

health promotion outcome that was the focal point of the inter-

vention, such as sleep hygiene, which refers to evidence-based

recommended healthy sleep practices like obtaining sufficient

sleep duration and practicing a relaxing bedtime routine. Data

extraction identified 7 types of interventions, including (1)

sleep hygiene, (2) yoga, (3) schedule control, (4) physical

activity, (5) CBTI, (6) stress reduction, or (7) napping. For

instance, studies that offered educational interventions to

Records identified through database searching (n= 6,177)

PubMed/Medline: n=1195, Web of Science: n=1297, Biological Abstracts: n=464, Biosis

Citation Index: n=521; CINAHL: n=540, EMBASE: n=1669, PsycInfo: n=491

S cr

ee ni

ng In

cl ud

ed E

lig ib

ili ty

Id en

ti fic

at io

n Additional records

identified through other sources (n= 48)

Records screened after removal of duplicates (n=3,146)

Records excluded (n=2,927) -No intervention -Not worksite -Did not measure sleep

Record full text retrieved for detailed evaluation

(n=221)

Records excluded (n=201) -No intervention -Not worksite -Did not measure sleep -Shift workers > 50% of sample

Studies included in the qualitative synthesis

(n=20)

Figure 1. Flow diagram of study screening and selection according to Preferred Reporting for Systematic Review Protocols (PRISMA) guidelines.

Robbins et al. 1011

improve sleep behavior and hygiene were coded as “sleep

hygiene,”31 whereas yoga interventions offered instructions

in specific stretching and exercise techniques, and physical

activity interventions included teaching or coaching exercise

routines or habits broadly. The CBTI interventions were deliv-

ered in accordance with previous efforts to address insomnia-

like symptoms.32 Finally, stress reduction focused on exercises

such as meditation techniques for reducing stress, while nap-

ping interventions included policies and initiatives to encour-

age employee napping.

Study Quality Evaluation and Data Analysis

The quality of the studies included in the systematic review was

assessed using the Downs and Black checklist.33 The Downs

and Black checklist is a 27-item scoring system assessing the

following domains: reporting, external validity, internal valid-

ity/bias, internal validity/confounding, and power. While there

is some discordance on how to use the quality scores from the

Downs and Black approach,34 we used a quality rating that

determined 21 (80.8%) and higher as high quality, 11 to 20 (42.4%-80.8%) as moderate quality, and 10 or lower as poor quality (<42.2%).35 Quality ratings were determined for the studies in this systematic review independently by 2 reviewers

(R.R. and P.U.). Discrepancies were adjudicated through

discussion until consensus with coauthors was reached. We

quantitatively summarized worksite-based interventions mea-

suring employee sleep duration as an outcome by intervention

type (eg, sleep hygiene, yoga) and examined the effect of inter-

vention on sleep duration measured via self-report, actigraphy,

or both.

Results

Description of Study Characteristics

The general characteristics of the studies are shown in Table 1.

Studies used 1 of 3 designs, including RCT, 2-arm nonrando-

mized pre–post, or 1-arm pre–post. Among the studies, indus-

tries where interventions were conducted included financial

services (n ¼ 2, 10.0%), educational services (n ¼ 2, 10.0%), media (n ¼ 2, 11.1%), and manufacturing (n ¼ 2, 10.0%). Unfortunately, 6 studies did not list the industry. Target popu-

lations were mostly office employees (n ¼ 9, 45.5%) and fac- tory workers (n ¼ 2, 10.0%), with the remainder of studies including manufacturing workers, laboratory workers, cleaning

staff, and nursing home employees and managers. The remain-

ing studies did not describe the target population (n ¼ 5, 25.0%). The duration of the workplace interventions ranged from several hours44 to 4 months47 (mean ¼ 2.0, standard

Table 1. Summary of Study Characteristics.a

First Author Year Study Design Industry Workforce Population

Intervention Duration, months

Longest Follow-Up, months

Adachi36 2003 1-arm pre–post study Not specified Office employees 1 mo 1 mo Adachi37 2008 1-arm pre–post study Not specified Not specified 1 mo 12 mo Adler38 2017 1-arm pre–post study Military Soldiers 1 mo 2 mo Chen31 2010 1-arm pre–post study Not specified Not specified 1 mo 1.5 mo de Bruin39 2017 1-arm pre–post study Not specified Not specified 1.5 mo 6 mo Hallman40 2017 RCT Maintenance Cleaning staff 4 mo 4 mo Itani41 2018 2-arm nonrandomized

intervention Manufacturing Factory workers 4 mo 4 mo

Järnefelt42 2012 2-arm nonrandomized intervention

Media Office employees 1 mo 6 mo

Järnefelt43 2014 2-arm nonrandomized intervention

Media Office employees 1 wk 2 years

Kakinuma44 2010 RCT Financial services Office employees 1 hr 1 mo Klatt45 2009 RCT Educational services Office employees 2 mo 1 mo Klatt29 2017 RCT Financial services Office employees 2 mo 2 mo Li46 2017 2-arm nonrandomized

intervention Healthcare Office employees 1 mo 1 mo

Marino47 2016 RCT Nursing homes Extended care workers

4 mo 12 mo

Nakada48 2018 Quasi-randomized trial Pharmaceutical Office employees 5 mo 1 mo Olson49 2015 RCT Information

technology Office employees 3 mo 12 mo

Schiller50 2017 RCT Not specified Not specified 2 mo 18 mo Suzuki51 2008 RCT Not specified Not specified 3 wk 3 wk Takahashi52 2004 1-arm pre–post study Manufacturing Factory workers 1 wk 3 wks Trousselard53 2014 1-arm pre–post study Educational services Lab workers 3 mo 3 mo

Abbreviations: hr, hours; wk, week; mo, months; RCT, randomized controlled trial. a n ¼ 20.

1012 American Journal of Health Promotion 33(7)

deviation [SD] ¼ 1.3). The longest follow-up range from sev- eral weeks postintervention51 to 2 years postintervention43

(mean¼5.4, SD ¼ 6.5).

Demographics of Study Samples

Table 2 displays characteristics of the populations in the studies

selected for this review. Sample size ranged from 8 to 2932

(mean ¼ 395.3, SD ¼ 700.9; median ¼ 53.5).38,52 Regarding participants who were lost to follow-up, the studies ranged

from 0 (0.0%)31 to 240 (29.3%)50 participants (mean ¼ 51.6, SD ¼ 82.4; median ¼ 6.0). Participant mean age across the studies ranged from 25.9 years38 to 49.0 years30 (mean ¼ 41.5, SD ¼ 5.2). The mean proportion of females was 26.8% and males was 73.1%. Race/ethnicity information was provided by only 7 (35.0%) studies. Among those studies reporting race/ ethnicity, mean proportion reporting being white was 34.0%, 2.2% Latino/Hispanic, 0.6% Black/African American, 56.8% Asian, and 6.4% other.

Intervention Effects on Employee Sleep Duration

Table 3 summarizes the interventions and effects on employee

sleep duration. The most common focus for interventions was

on sleep hygiene (n ¼ 7, 35.0%), followed by yoga (n ¼ 5, 25.0%), schedule control (n¼ 2, 10.0%), physical activity (n¼ 2, 10.0%), CBTI (n ¼ 2, 10.0%), general healthy lifestyle (n ¼ 1, 5.0%), and napping (n ¼ 1, 5.0%). Measures of sleep dura- tion included self-report from a general questionnaire (n ¼ 12, 66.6%), self-report based on PSQI (n ¼ 4, 22.2%), and both self-report and actigraphy combined (n ¼ 5, 27.7%).

Regarding BCTs included in the 20 studies, there were 9

individual BCTs from the Michie et al taxonomy30 that were

used in the eligible interventions included in this review. The

most common BCTs were instructional seminar (n ¼ 14, 38.9%), self-monitoring (n ¼ 5, 13.2%), goal setting (n ¼ 4, 10.5%), follow-up prompts (n¼ 5, 13.2%), practice sessions (n ¼ 3, 7.9%), behavioral modeling (n ¼ 2, 5.3%), rewards con- tingent upon behavior (n¼ 2, 5.3%), and one administered one- on-one coaching (n¼ 1, 5.3%). Across the studies, 13 utilized 2 BCTs in their intervention (76.5%), 7 used 3 BCTs (7 ¼ 6, 41.2%), and 1 intervention featured 4 BCTs (n ¼ 1, 5.9%).

In terms of effects of the interventions on employee sleep

duration, this review identified a positive effect of intervention

exposure on employee sleep duration in 10 (50.0%) studies. Examining effects by intervention type, it appears CBTI inter-

ventions42,43 improved employee sleep duration (n ¼ 2/n ¼ 2, 100%). Also, one schedule control study conducted by Olson et al49 improved employee sleep duration (n¼ 1/n¼ 3, 33.3%). Among the yoga interventions, Klatt et al29 and Klatt et al45

achieved improvement in sleep duration (n ¼ 2/3, 66.7%). Similarly, among the sleep hygiene interventions, the follow-

ing studies improved sleep duration (n ¼ 4/n ¼ 6; 66.7%): Adachi et al,36 Adachi et al,37 Chen et al,31 and Li et al.46 None

of the stress reduction, schedule control, or napping interven-

tions were associated with a statistically significant improve-

ment in sleep duration among employees.

The average quality for selected studies was 70.2% (SD ¼ 10.9%, median: 71.2%, range: 53.8%-86.5%). According to Downs and Black, 80.8% or higher indicates high quality, and rating between 42% and 80.8% indicates moderate quality. Therefore, most studies were in the moderate quality range.

Table 2. Study Sample Demographics.a

First Author Year Sample

Size Lost to

Follow-Up Mean Age at

Baseline, years Males, % Females, % White, % Latino/

Hispanic, % Black/African American, % Asian, % Other, %

Adachi36 2003 114 39 37.5 45.6% 54.4% Adachi37 2008 47 0 38.7 36.2% 63.8% Adler38 2017 2932 52 25.9 92.4% 7.6% Chen31 2010 37 0 38.3 0.0% 100.0% de Bruin39 2017 26 3 44.9 15.4% 84.6% Hallman40 2017 173 34 45.1 24.3% 75.7% Itani41 2018 800 15 42.3 596 118 783 Järnefelt42 2012 33 6 44.4 18.2% 81.8% Järnefelt43 2014 59 15 46.0 50.8% 49.2% Kakinuma44 2010 581 190 44.4 80.8% 19.2% Klatt45 2009 48 6 33.8 19.0% 81.0% 88.9 4.4 6.7 Klatt29 2017 81 54 45.0 24.4% 75.6% 87.8 2.4 2.4 4.9 2.4 Li46 2017 33 6 42.0 23.1% 76.9% Marino47 2016 1285 503 38.5 8.2 91.8 66.6 11.5 12.7 6.7 Nakada48 2018 77 7 43.1 42 28 70.0 Olson49 2015 701 227 46.7 59.7% 40.3% 67.7 7.0 1.4 3.4 20.4 Schiller50 2017 820 240 44.6 0.0% 100.0% 100.0 Suzuki51 2008 43 5 39.6 0.0% 100.0% 100.0 Takahashi52 2004 8 0 49.0 100.0% 0.0% 100.0 Trousselard53 2014 9 0 39.7 100.0% 0.0%

a n ¼ 20 studies.

Robbins et al. 1013

Table 3. Impact of Interventions on Employee Sleep Behavior and Quality Ratings.a

First Author Year Intervention

Sleep Duration Measure

Behavior Change Techniques (BCTs) Main Findings (Detailed)b

Main Findings (Brief)

Study Quality

Adachi 2003 Sleep hygiene Self-report a) Self-monitoring b) Goal setting

(behavior) c) Rewards contingent

on behavior

Participation in the intervention was associated with an increase in sleep duration (5.96 to 6.1 h/night, P value <.01)

þ 53.8%

Adachi 2008 Sleep hygiene Self-report a) Instructional seminar b) Follow-up prompts c) Self-monitoring d) Rewards contingent

on behavior

Participation in the intervention was associated with an increase in sleep duration (5.52 to 5.97 h/night, P value <.05)

þ 57.7%

Adler c 2017 Sleep hygiene Self-report a) Self-monitoring b) Follow-up prompts

Participation in the intervention was associated with an increase in sleep duration (P value ¼ .05)

þ 86.5%

Chen 2010 Sleep hygiene Self-report (PSQI)

a) Instructional seminar Participation in the intervention was associated with an increase in sleep duration (PSQI sleep duration subcomponent at baseline ¼ 1.0 vs follow-up:0.6: P value ¼ .002)

þ 57.7%

de Bruin 2017 Yoga Self-report a) Instructional seminar b) Behavioral modeling C) Practice session(s)

Participants who received the intervention reported increased sleep duration (7.0 to 7.4 h/night), although no P value was provided to determine significance

NC 53.8%

Hallman 2017 Physical activity

Self-report a) Instructional seminar(s)

b) Practice session(s)

Participation in the intervention was not associated with an increase in sleep duration (7.20 vs 7.30 h/night, P ¼ ns)

NC 82.7%

Itani 2018 Sleep hygiene PSQI a) Instructional session b) Follow-up prompts

Participation in the intervention, compared to control, was not associated with a significant increase in sleep duration as measured by PSQI (P ¼ .218)

NC 49.4%

Jarnefelt 2012 CBTI Self-report, actigraph

a) Instructional seminar (CBTI)

Participation in the intervention was associated with an increase in reported duration (7.3 to 7.7 h/night, P ¼ .027), but not according to actigraphy (P ¼ ns).

þ 80.8%

Jarnefelt 2014 CBTI Self-report a) Instructional seminar(s) (CBTI)

b) One-on-one coaching

Participation in the intervention was associated with an increase in sleep duration (7.1 to 7.5 h/night, P value ¼ .05)

þ 57.7%

Kakinuma 2010 Sleep hygiene Self-report a) Instructional seminar(s)

b) Self-monitoring c) Follow-up prompts

Participation in the intervention was not associated with an improvement in sleep duration (0.03 v. 0.07 h/night, P value ¼ .69)

NC 78.8%

Klatt 2009 Yoga Self-report (PSQI sleep duration)

a) Instructional seminar(s)

b) Self-monitoring

Participantion in the intervention was associated with an improvement in PSQI global (6.73-5.00, P value: .0018), but not in PSQI sleep duration (0.91-0.82, P value ¼ .3287)

þ 80.8%

Klatt 2017 Yoga Self-report (PSQI)

a) Instructional seminar(s)

b) Goal-setting

Among participants who received the intervention, PSQI scores improved (5.93 vs 3.89, P value ¼ .005)

þ 71.2%

Li 2017 Physical activity

Self-report a) Environmental restructuring (sit/ stand workstations provided)

b) Follow-up prompts

Participation in the intervention as not associated with an increase in sleep quantity (P value ¼ .708)

NC 71.2%

(continued)

1014 American Journal of Health Promotion 33(7)

Discussion

We characterized the types of workplace-based employee

health interventions that included sleep duration as a primary

or secondary outcome and examined intervention type, study

design and quality, and intervention outcomes on employee

sleep. Approximately half of the 20 interventions in this review

achieved a statistically significant increase in sleep duration.

Intervention size ranged widely from a pilot study in a small

employee group36 to a self-monitoring intervention using a

large employee population.38 Interventions were delivered to

employees in a variety of industries, including financial ser-

vices, maintenance, and education. Target employees included

general office employees, cleaning personnel, laboratory work-

ers, and manufacturing workers. Unfortunately, several studies

did not specify their worker population or industry. The dura-

tion of the intervention in this review ranged widely from sev-

eral hours to several months, presenting a wide range of

intervention lengths.

While the participant mean age in this review was 41.5

years, it is interesting to consider the role of workplace-based

health promotion as our population growth in older adults (eg,

40 years and older) continues to accelerate.54,55 The proportion

of 50- to 65-year-old individuals will double in the next 20

years, likely shifting the age of participants in these types of

programs, presenting new challenges and opportunities for

health promotion in the workplace to advance population-

level outcomes.

In our review, the most common interventions were those

focused on improving employee sleep hygiene. Among the

Table 3. (continued)

First Author Year Intervention

Sleep Duration Measure

Behavior Change Techniques (BCTs) Main Findings (Detailed)b

Main Findings (Brief)

Study Quality

Nakada 2018 Mental health intervention

Self-report, actigraph

a) Instructional session b) Self-monitoring

Participation in the intervention, compared to control, was associated with a significant increase in sleep duration as measured by actigraphy intervention: 5.1 vs 4.6 h; P ¼ .036)

þ 54.32%

Marino 2016 Schedule control

Self-report, actigraph

a) Instructional session(s) (result- based work culture)

b) Behavioral modeling c) Goal setting

Participation in the intervention was not associated with an increase in sleep duration (employees P value ¼ .179, managers ¼ .321)

NC 76.9%

Olson 2015 Schedule control

Self-report, actigraph

a) Instructional session(s) (result- based work culture)

b) Behavioral modeling c) Goal setting

Participation in the intervention was associated with an increase in sleep duration according to actigraphy (P value ¼ .041)

þ 80.8%

Schiller 2017 Schedule control

Self-report a) Environmental restructuring (reduced working hours per week by 25%

Participation in the intervention was not associated with an increase in sleep duration (P value ¼ .263)

NC 76.9%

Suzuki 2008 Sleep hygiene Self-report (PSQI)

a) Instructional seminar(s) (sleep hygiene)

b) Self-monitoring c) Follow-up prompts

Participation in the intervention was not associated with an increase in sleep duration (5.83 vs 5.88 h/night, P value ¼ .09), but PSQI global did improve (7.70 vs 7.40, P value ¼ .009)

NC 65.4%

Takahashi 2004 Napping Actigraph a) Practice session(s) (napping)

Participation in the intervention was not associated with an increase in sleep duration according to actigraphy 5.6 vs 5.6h/night; P value ¼ ns)

NC 69.2%

Trousselard 2014 Stress reduction

Self-report a) Instructional seminar(s)

Participation in the intervention was not associated with an increase in sleep duration (6.5 vs 6.5 h/night, P value ¼ .890)

NC 61.5%

Abbreviations: CBTI, cognitive–behavioral therapy for insomnia; h, hours; PSQI, Pittsburgh Sleep Quality Index; NC, no change. a n ¼ 20 studies. Quality ratings: high >80.8%; moderate 42.2-80.8%; low <42.2%. b Main findings are reflected from the published papers. In some cases, authors present change scores; in other cases, authors compare follow-up sleep duration between intervention and control. Findings are displayed, consequently, as sleep quantity (eg, h/night), differences (eg, 0.2 h/night more than control), or PSQI global from 0 to 21 (higher scores indicate work sleep outcomes), or PSQI sleep duration from 0 to 3 (0: <7 h/night; 1: 6-7 h/night; 2: 7-8 h/night; 3:>8 h/night). c Adler et al38 used biofeedback from actigraphy in the intervention, yet did not report actigraphy output, thus self-report only is noted as the sleep duration measure.

Robbins et al. 1015

sleep hygiene interventions, most were successful in increasing

sleep quantity. This is interesting; sleep hygiene practices are

underexplored in nonclinical populations, such as working

adults, but also not always sufficient for increasing sleep dura-

tion.19 The next most common intervention type was yoga,

two-thirds of which were successful in increasing sleep among

employees. The interventions focused on CBTI were all effec-

tive for increasing sleep duration. This is not surprising, as

there is a large body of evidence to show the effectiveness of

CBTI approaches for improving sleep32,56,57; however, it

should be noted that the studies testing CBTI were not in popu-

lations with clinical insomnia diagnoses. Consequently, future

research may further explore the contributing factors to the

increased duration among recipients of CBTI when an insom-

nia diagnosis is absent.

Also effective in increasing employee sleep duration was

one intervention focused on reducing work–family conflict.

In this RCT to reduce work–family conflict conducted by

Olson et al,49 researchers evaluated a comprehensive program

to deliver multiple targeted BCTs to employees (and managers)

over 3 months. According to their results, the intervention—

while not expressly addressing sleep—increased employee

sleep duration. These results further emphasize the intercon-

nectedness of social/contextual factors that matter for health

outcomes, as well as the importance of multilevel and multi-

modal interventions.58

Only 1 study meeting our criteria focused on napping in the

workplace, although evidence suggests there are benefits of nap-

ping for reducing fatigue and improving alertness.59 In light of

the evidence to suggest a midday dip in alertness among the

majority of the population,60 napping in the afternoon may rep-

resent a healthy routine well suited to attention from workplace-

based health promotion as most workers are at the office at the

ideal time to nap. The shift-work exclusionary criteria for our

study excluded nap interventions tailored to occupational groups

such as medical residents and nurses whose jobs often include

shift work. Future research could examine the effect of napping

interventions on employee sleep and workplace-based perfor-

mance measures, such as productivity. That napping interven-

tions are precluded in some industries where napping is a firing

offense (eg, air traffic controllers) further limits nap-focused

interventions in worksites.

Our findings show a range of BCTs utilized in health pro-

motion to address employee sleep. Instructional seminars, self-

monitoring, and goal setting were the most common BCTs

applied in the studies that met criteria for this review. These

findings are consistent with previous workplace research but

did not emphasize leadership support for employee health pro-

motion, which has been a focus in other workplace health

promotion efforts.23

Overall, the findings in this study suggest the potential role

for workplace-based health promotion as a tool for improving

sleep among working adults. Our results do nevertheless high-

light limited attention to sleep as an outcome in workplace-

based interventions. Our results also illuminate future areas for

interventions that seek to improve sleep duration.

Implications of Findings

This review identified workplace-based health interventions

that measured employee sleep duration and found half of the

selected studies improved employee sleep duration. Particu-

larly important, the interventions focused on employee sleep

hygiene and CBTI had the highest success rates of behavior

change toward healthier sleep duration among employees,

offering further support from previous literature for these

approaches.19,32,61 To the extent to which employers can mean-

ingfully improve sleep, our findings suggests that workers

stand to benefit from worksite-based programs aimed at

improving sleep.15,62 Worksite-based employee health inter-

ventions could potentially also serve a benefit to society in

terms of improved work-related productivity in the

aggregate.17,18

Limitations

A major limitation of the literature to date is the paucity of

worksite-based intervention research that utilized objective

measures of sleep. As the majority of studies measured self-

reported sleep duration, the results may have been biased and

possible associations between program exposure and sleep may

have been missed. Our review identified 2 studies examining

workplace health interventions that measured sleep objectively

using actigraphy, while the remainder of studies relied on self-

report of sleep duration. Although we assessed the quality of

the studies, we were unable to evaluate intervention fidelity (or

that the interventions were delivered as intended). It is also

important to note that some interventions had multiple BCT

components (eg, one-on-one coaching and instructional semi-

nars), making it challenging to compare outcomes of different

BCTs across the studies, as the authors had originally planned a

meta-analysis. It should be noted only published research is

included; thus, there may be publication bias from studies that

did not achieve significant findings. Furthermore, studies often

had limited description of the industry or job descriptions of

employees in their studies. Finally, studies in this review did

not quantify the economic cost savings of improved employee

health or sleep duration. As well-documented evidence can

attest, sleep deprivation carries significant economic tolls in

terms of reduced productivity (due to both absenteeism and

presenteeism) as well as work-related injury.17,63,64 These fac-

tors bear consequence for outcomes but also for future inter-

ventions, as it would be useful to understand the types of

employees who enroll in health promotion programs and their

unique job demands as we consider effects of interventions.

Future Research

Future interventions may consider combining educational

approaches and intervention components for behavior change

among employees with regard to sleep identified in this review,

such as yoga plus CBTI. Future research may also examine

areas not specifically related to sleep but to implications for

1016 American Journal of Health Promotion 33(7)

sleep, such as reducing work–family conflict. There is need for

future research to utilize objective measures of sleep duration,

however, so as to better characterize the interventions specifi-

cally targeting sleep and their objective effects on employee

postintervention sleep. There is also need for future meta-

analytic work to quantify the impact of employee health pro-

motion programming and its implications for employee sleep

but also the economic benefit (or disadvantage) of interven-

tions that endeavor to increase employee sleep duration or

improve employee sleep quality. Specifically, it would be par-

ticularly useful to identify the optimal duration of intervention

exposure for optimal behavior change. Furthermore, research

might include employee populations that are racially and eth-

nically diverse. Research should also consider the independent

impact of workplace-based health promotion on sleep quality

in addition to sleep duration and determine the predictors of

effective interventions (eg, BCTs, intervention duration).

Conclusion

This systematic review provides evidence that workplace-

based interventions can improve employee sleep duration. Fur-

ther, it is noted that interventions focused on sleep hygiene,

CBTI, and reducing work–family conflict may be promising

ways to increase employee sleep duration. Given the strong

link between employee sleep health and alertness and work-

related productivity, employers would likely be well served to

draw heightened attention to sleep in their health promotion

efforts.

Authors’ Note

R. Robbins and O. Buxton contributed to study conception and design.

R. Robbins and P. Underwood contributed to acquisition of data. R.

Robbins, O. Buxton, C. Jackson, and P. Underwood contributed to

interpretation of data. R. Robbins contributed to drafting of the manu-

script. R. Robbins, C. Jackson, P. Underwood, G. Jean-Louis, and O.

Buxton contributed to critical revision of the manuscript for important

intellectual content. P. Underwood, G. Jean-Louis, and O. Buxton

contributed to administrative, technical, and material support. R. Rob-

bins, C. Jackson, P. Underwood, G. Jean-Louis, and O. Buxton gave

final approval.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for

the research, authorship, and/or publication of this article: This work,

in part, was funded by the NIH (Z1AES103325-01, K07AG052685).

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SO WHAT?

What is already known on this topic?

Workplace-based employee health promotion holds tre- mendous promise for advancing health promotional behaviors, such as exercise and nutrition. Indeed, these programs are rapidly expanding at worksites across the United States.

What does this article add?

While workplace-based health promotion programs are increasingly popular, few aim to promote healthy sleep among employees. Sleep is directly related to workplace outcomes, including employee health, absenteeism, and productivity. This systematic review systematically examines workplace-based employee health interven- tions that measured sleep duration as an outcome.

What are the implications for health promotion practice or research?

This systematic review identifies the evidence on workplace-based health promotion aiming to improve sleep health among employees. Specifically, we articulate the behavioral change techniques employed in successful programs and identify opportunities for improving employee sleep health using worksite-based health pro- motional activities.

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