Ryan Olson1, Tori L Crain2, Todd E Bodner2, Rosalind King3, Leslie B Hammer2, Laura Cousino Klein4, Leslie Erickson5, Phyllis Moen6, Lisa F Berkman7, Orfeu M Buxton8. 1. Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L606, Portland, OR 97239; Department of Public Health & Preventive Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Mail Code CB 669, Portland, OR 97239; Department of Psychology, Portland State University, 1721 SW Broadway, Rm 317, Portland, OR 97201. 2. Department of Psychology, Portland State University, 1721 SW Broadway, Rm 317, Portland, OR 97201. 3. Population Dynamics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, 6100 Executive Blvd., Bethesda, MD 20892-7510. 4. Department of Biobehavioral Health and Penn State Institute of the Neurosciences, Pennsylvania State University, 221 Biobehavioral Health Bldg, University Park, PA 16802. 5. RTI International, 3040 East Cornwallis Road, Research Triangle Park, NC 27709. 6. Department of Sociology and Minnesota Population Center, University of Minnesota, 50 Willey Hall, 225-19th Ave South, Minneapolis, MN 55455. 7. Harvard Center for Population and Development Studies, Harvard University, 9 Bow Street, Cambridge MA 02138; Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Kresge Building, Boston, MA 02115. 8. Department of Biobehavioral Health and Penn State Institute of the Neurosciences, Pennsylvania State University, 221 Biobehavioral Health Bldg, University Park, PA 16802; Harvard Center for Population and Development Studies, Harvard University, 9 Bow Street, Cambridge MA 02138; Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Kresge Building, Boston, MA 02115; Department of Medicine, Brigham and Women's Hospital, 221 Longwood Ave, Boston, MA 02115; Division of Sleep Medicine, Harvard Medical School, 221 Longwood Ave, Boston, MA 02115. Electronic address: Orfeu@PSU.edu.
Abstract
STUDY OBJECTIVES: The Work, Family, and Health Network Study tested the hypothesis that a workplace intervention designed to increase family-supportive supervision and employee control over work time improves actigraphic measures of sleep quantity and quality. DESIGN: Cluster-randomized trial. SETTING: A global information technology firm. PARTICIPANTS: US employees at an information technology firm. INTERVENTIONS: Randomly selected clusters of managers and employees participated in a 3-month, social, and organizational change process intended to reduce work-family conflict. The intervention included interactive sessions with facilitated discussions, role playing, and games. Managers completed training in family-supportive supervision. MEASUREMENTS AND RESULTS: Primary outcomes of total sleep time (sleep duration) and wake after sleep onset (sleep quality) were collected from week-long actigraphy recordings at baseline and 12 months. Secondary outcomes included self-reported sleep insufficiency and insomnia symptoms. Twelve-month interviews were completed by 701 (93% retention), of whom 595 (85%) completed actigraphy. Restricting analyses to participants with e3 valid days of actigraphy yielded a sample of 473-474 for intervention effectiveness analyses. Actigraphy-measured sleep duration was 8 min/d greater among intervention employees relative to controls (P < .05). Sleep insufficiency was reduced among intervention employees (P = .002). Wake after sleep onset and insomnia symptoms were not different between groups. Path models indicated that increased control over work hours and subsequent reductions in work-family conflict mediated the improvement in sleep sufficiency. CONCLUSIONS: The workplace intervention did not overtly address sleep, yet intervention employees slept 8 min/d more and reported greater sleep sufficiency. Interventions should address environmental and psychosocial causes of sleep deficiency, including workplace factors.
STUDY OBJECTIVES: The Work, Family, and Health Network Study tested the hypothesis that a workplace intervention designed to increase family-supportive supervision and employee control over work time improves actigraphic measures of sleep quantity and quality. DESIGN: Cluster-randomized trial. SETTING: A global information technology firm. PARTICIPANTS: US employees at an information technology firm. INTERVENTIONS: Randomly selected clusters of managers and employees participated in a 3-month, social, and organizational change process intended to reduce work-family conflict. The intervention included interactive sessions with facilitated discussions, role playing, and games. Managers completed training in family-supportive supervision. MEASUREMENTS AND RESULTS: Primary outcomes of total sleep time (sleep duration) and wake after sleep onset (sleep quality) were collected from week-long actigraphy recordings at baseline and 12 months. Secondary outcomes included self-reported sleep insufficiency and insomnia symptoms. Twelve-month interviews were completed by 701 (93% retention), of whom 595 (85%) completed actigraphy. Restricting analyses to participants with e3 valid days of actigraphy yielded a sample of 473-474 for intervention effectiveness analyses. Actigraphy-measured sleep duration was 8 min/d greater among intervention employees relative to controls (P < .05). Sleep insufficiency was reduced among intervention employees (P = .002). Wake after sleep onset and insomnia symptoms were not different between groups. Path models indicated that increased control over work hours and subsequent reductions in work-family conflict mediated the improvement in sleep sufficiency. CONCLUSIONS: The workplace intervention did not overtly address sleep, yet intervention employees slept 8 min/d more and reported greater sleep sufficiency. Interventions should address environmental and psychosocial causes of sleep deficiency, including workplace factors.
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