Insomnia and Work Performance Loss in Research and Development Workers

Linda Stiles, PhD, CIH, CHMM

RGAIHA Fall Technical Conference

December 4, 2014

Presentation Overview

Insomnia PrevalenceForty-three percent (43%) of Americans between the ages of 13 and 64 say they rarely or never get a good night's sleep on weeknights. (Sleep in America Poll, National Sleep Foundation, 2011).

Insomnia Prevalence• Insomnia prevalence is influenced by demographic

factors.– Age– Gender– Marital status– Education– Income– Race?

Insomnia Prevalence• Insomnia prevalence is influenced by chronic

psychological and physical health conditions• Comorbid insomnia

– Anxiety and depression (Jansson-Fröjmark & Lindblom, 2008).

– Back pain (Tang et al., 2007)– Cancer (Taylor et al., 2006)– Cardiovascular disease (Laugsand et al., 2011)– Diabetes (Cappuccio et al., 2010)– Neurologic disease, breathing problems, urinary problems,

chronic pain, and gastrointestinal problems (Taylor et al., 2006).

Impact of Insomnia in the WorkplaceWorkers represent two-thirds of the adult US population (Bureau of Labor Statistics, 2013).

NSF Sleep in America Poll, 2008

Impact of Insomnia in the Workplace

• A high prevalence of sleep disorders in workers is associated with increased: • Accidents and injuries • Disability • Absenteeism• Presenteeism• Work productivity/work performance loss

Work Performance vs. Work Productivity Loss

•Work performance differs from work productivity (Campbell, 1990; Koopmans et al., 2011)

•Work performance is multidimensional: work performance comprises both task (physical) performance and contextual (mental and social) performance (Koopsman et al., 2011).

•A high level of work performance is essential for meeting the scientific and technical objectives inherent in R & D work.

Rationale for this Study• Past research studies surveyed workers from the

manufacturing, health care, telecommunications, and service industries; or surveyed health insurance subscribers .

• However, a review of the literature found an absence of studies evaluating the relationship between insomnia and work performance loss among R & D workers.

• Inconsistencies in past studies also were found (Kessler et al., 2011; Kucharcyzk et al., 2012; Silvertsen et al., 2011).

Three Research Questions Were Posed:• What is the relationship between insomnia and

work performance loss in R & D workers?

• What influence do comorbid health conditions have on the relationship between insomnia and work performance loss in R & D workers?

• What influence do demographic factors have on the relationship between insomnia and work performance loss in R & D workers?

Insomnia and Work Performance Survey

• Five (5) demographic questions posed.• Insomnia prevalence was evaluated with the

Insomnia Severity Index (Bastien et al., 2001).• A pilot study of the survey was conducted. • The Stanford Presenteeism Scale (Turpin et al.,

2004) was used to assess work performance loss and the presence of 10 health conditions.

Please rate your sleep patterns over the past four weeks

0None

1Mild

2Moderate

3Severe

4Very Severe

Difficulty falling asleep:Difficulty staying asleep:Problem waking up too early:

How satisfied are you with your current sleep pattern?

Very Satisfied

A Little

SomeWhat

Much

Very Dissatisfied

Does your sleep pattern interfere with your daily functioning (e.g., daytime fatigue, ability to function at work/daily chores, concentration, memory, mood, etc.)?

Not at all Interfering

A Little

SomeWhat

Much

Very MuchInterfering

How distressed are you about your current sleep pattern?

Not at all

A Little Some What

Much

Very Much

Insomnia Severity Index

Stanford Presenteeism Scale

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Do you have any of the following health conditions?

•Allergies •Arthritis or joint pain/stiffness •Asthma; •Back or neck disorder •Breathing disorder-bronchitis or emphysema •Depression or anxiety disorder•Diabetes •Heart or circulatory problems •Migraines or chronic headaches •Stomach or bowel disorder

Stanford Presenteeism Scale

a. Were you able to finish hard tasks?b. Did you find your attention wandering?c. Were you able to focus on achieving work goals?d. Did you feel energetic enough to work?e. Were the stresses of your job hard to handle?f. Did you feel hopeless about finishing your work?

g. Were you able to focus on finding a solution when unexpected problems arose in your work?h. Did you need to take breaks from your work?i. Were you able to work with other people on shared tasks?j. Were you tired because you lost sleep?

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How often in the past 4 weeks?

Data Collection

• Permission to conduct the study was obtained from the Sandia Human Studies Board.

• The survey was emailed to 3,156 on-site Sandia workers with the R & D job designation.

• Four hundred eighty-nine (489) workers completed the survey (16% response rate).

• Survey data was uploaded to SPSS software (version 21.0) for analysis.

Participant Demographics: Age

Participant Demographics: Gender

Participant Demographics: Marital Status

Participant Demographics: Education

Participant Demographics: Annual Salary Range

Participants’ Comorbid Health Conditions

Data Analysis:

• Bivariate regression analysis was performed to predict the relationship between insomnia and work performance.

• Multivariate regression analyses were performed to predict the influence of demographic factors and comorbid health conditions on the relationship between insomnia and work performance.

Results: Research Question #1• The relationship between insomnia and work

performance loss was significant (p < .001).

• The null hypothesis was rejected, and the alternative hypothesis accepted.

• The regression model predicted work performance loss in R & D workers suffering from insomnia.

Results: Research Question #2• Two regression models were generated.• Model #1 evaluated whether each of the ten

health conditions predicted work performance loss variability.

• Model #1 did not predict a significant amount of work performance loss variability for the presence of eight of the health conditions.

• However, depression or anxiety (p < .001), and migraines or chronic headaches (p < .01) did account for a significant amount of work performance loss variability among participants.

Results: Research Question #2• Model #2 evaluated whether insomnia predicted

work performance loss when the 10 health conditions were controlled.

• Results: Insomnia accounted for a significant proportion of work performance loss after controlling for each of the ten comorbid health conditions (p < .001).

• The null hypothesis stating that health conditions would not influence the relationship between insomnia and work performance loss was accepted.

Results: Research Question #3

• Two regression models were generated.• Model #1 evaluated whether each of the five

demographic variables predicted work performance loss variability.

• Model #1 did not predict a significant amount of work performance loss variability for four of the demographic variables (age, gender, education, marital status).

• However, annual salary range (p < .05) did account for a significant amount of work performance loss variability among participants.

Results: Research Question #3

• Model #2 evaluated whether insomnia predicted work performance loss when the five demographic variables were controlled.

• Insomnia accounted for a significant proportion of work performance loss after controlling for each of the five demographic factors (p < .001).

• The null hypothesis stating that demographic factors would not influence the relationship between insomnia and work performance loss was accepted.

Study Limitations• Study design

– No causality was established due to the nature of the cross sectional study.

• A “convenience” population was sampled– Therefore, the external validity of the study is

limited to workers with similar demographics

• The data collection method resulted in a low response rate

• Insomnia and work performance data was self-reported by participants and not based on corporate medical or human resources data.

Recommendations

• Additional studies of workers in the R & D sector

• Prospective studies • Alternative data collection methods

– Incentives for worker participation– In-person interviews by trained interviewers

• Objective data on insomnia prevalence– Medical diagnosis– Sleep diaries/polysomnography

Implications

• The study may promote the establishment of sleep programs throughout the national laboratories.

• The study may focus more attention on the impact of depression or anxiety and chronic headaches on work performance.

• The study may give impetus to Sandia’s preventive health programs to further promote the current sleep program.

Questions?

ReferencesBastien, C. H., Vallières, A., & Morin, C. M. (2001). Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Medicine, 2(4), 297-

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Bolge, S. C., Doan, J. F., Kannan, H., & Baran, R. W. (2009). Association of insomnia with quality of life, work productivity, and activity impairment. Quality of Life Research, 18(4), 415-422.

Cappuccio, F. P., D'Elia, L., Strazzullo, P., & Miller, M. A. (2010). Quantity and quality of sleep and incidence of type 2 diabetes: A systematic review and meta-analysis. Diabetes Care, 33(2), 414-420.

Campbell, J. P. (1990). Modeling the performance prediction problem in industrial and organizational psychology. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (pp. 687–732). Palo Alto, CA: Consulting Psychologists Press.

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Department of Labor. Bureau of Labor Statistics. Labor force statistics from the current population survey, 2013.

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References, continued

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Turpin, R. S., Ozminkowski, R. J., Sharda, C. E., Collins, J. J., Berger, M. L., Billotti, G. M., . . . Nicholson, S. (2004). Reliability and validity of the Stanford Presenteeism Scale.