Impact of a Translated Disease Self-Management Program on Employee Health and Productivity: Six-Month Findings from a Randomized Controlled Trial
Abstract
:1. Introduction
2. Materials and Methods
2.1. Translation Process
2.2. Recruitment
2.3. Data Collection
2.4. Outcome Measures
2.5. Statistical Methods
3. Results
4. Discussion
Limitations
5. Conclusions
Author Contributions
Acknowledgments
Conflicts of Interest
References
- Bureau of Labor Statistics. Labor Force Statistics from Current Population Study; United States Department of Labor: Washington, DC, USA, 2017. Available online: https://www.bls.gov/cps/cpsaat03.htm (accessed on 1 March 2018).
- Lerner, D.; Allaire, S.; Reisine, S. Work disability resulting from chronic health conditions. J. Occup. Environ. Med. 2005, 47, 253–264. [Google Scholar] [CrossRef] [PubMed]
- Goetzel, R.Z.; Pei, X.; Tabrizi, M.J.; Henke, R.M.; Kowlessar, N.; Nelson, C.F.; Metz, R.D. Ten Modifiable Health Risk Factors Are Linked to More Than One-Fifth of Employer-Employee Health Care Spending. Health Aff. 2012, 31, 2474–2484. [Google Scholar] [CrossRef] [PubMed]
- Bhattacharya, J.; Choudhry, K.; Lakdawalla, D. Chronic disease and severe disability among working-age populations. Med. Care 2008, 46, 92–100. [Google Scholar] [CrossRef] [PubMed]
- Sorensen, G.; Landsbergis, P.; Hammer, L.; Amick, B.C., III; Linnan, L.; Yancey, A.; Workshop Working Group on Worksite Chronic Disease Prevention. Preventing chronic disease in the workplace: A workshop report and recommendations. Am. J. Public Health 2011, 101, S196–S207. [Google Scholar] [CrossRef] [PubMed]
- Goetzel, R.Z.; Ozminkowski, R.J.; Sederer, L.I.; Mark, T.L. The business case for quality mental health services: Why employers should care about the mental health and well-being of their employees. J. Occup. Environ. Med. 2011, 44, 320–330. [Google Scholar] [CrossRef]
- Goetzel, R.Z.; Long, S.R.; Ozminkowski, R.J.; Hawkins, K.; Wang, S.; Lynch, W. Health, absence, disability, and presenteeism cost estimates of certain physical and mental health conditions affecting US employers. J. Occup. Environ. Med. 2004, 46, 398–412. [Google Scholar] [CrossRef] [PubMed]
- Caloyeras, J.P.; Liu, H.; Exum, E.; Broderick, M.; Mattke, S. Managing manifest diseases, but not health risks, saved PepsiCo money over seven years. Health Aff. 2014, 33, 124–131. [Google Scholar] [CrossRef] [PubMed]
- Chapman, L.S. Meta-evaluation of worksite health promotion economic return studies: 2005 update. Am. J. Health Promot. 2005, 19, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Loeppke, R.; Taitel, M.; Haufle, V.; Parry, T.; Kessler, R.C.; Jinnett, K. Health and Productivity as a Business Strategy: A Multiemployer Study. J. Occup. Environ. Med. 2009, 51, 411–428. [Google Scholar] [CrossRef] [PubMed]
- Ory, M.G.; Smith, M.L.; Kulinski, K.P.; Lorig, K.; Zenker, W.; Whitelaw, N. Self-management at the tipping point: Reaching 100,000 Americans with evidence-based programs. J. Am. Geriatr. Soc. 2013, 61, 821–823. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.L.; Ory, M.G.; Ahn, S.; Kulinski, K.P.; Jiang, L.; Horel, S.; Lorig, K. National dissemination of Chronic Disease Self-Management Education (CDSME) Programs: An incremental examination of delivery characteristics. Front. Public Health 2015. [Google Scholar] [CrossRef]
- Bandura, A. Social cognitive theory of self-regulation. Organ. Behav. Hum. Decis. Process. 1991, 50, 248–287. [Google Scholar] [CrossRef]
- Stanford Patient Education Research Center. Stanford Small Group Self-Management Programs in English. 2017. Available online: http://patienteducation.stanford.edu/programs/ (accessed on 1 March 2018).
- Lorig, K.R.; Sobel, D.S.; Ritter, P.L.; Laurent, D.; Hobbs, M. Effect of a self-management program on patients with chronic disease. Eff. Clin. Pract. 2000, 4, 256–262. [Google Scholar]
- Lorig, K.R.; Sobel, D.S.; Stewart, A.L.; Brown, B.W., Jr.; Bandura, A.; Ritter, P.; Holman, H.R. Evidence suggesting that a chronic disease self-management program can improve health status while reducing hospitalization: A randomized trial. Med. Care 1999, 37, 5–14. [Google Scholar] [CrossRef] [PubMed]
- Lorig, K.R.; Ritter, P.; Stewart, A.L.; Sobel, D.S.; Brown, B.W., Jr.; Bandura, A.; Holman, H.R. Chronic disease self-management program: 2-year health status and health care utilization outcomes. Med. Care 2001, 39, 1217–1223. [Google Scholar] [CrossRef] [PubMed]
- Boutaugh, M.L.; Jenkins, S.M.; Kulinski, K.P.; Lorig, K.R.; Ory, M.G.; Smith, M.L. Closing the Disparity Gap: The Work of the Administration on Aging. Generations 2014, 38, 107. [Google Scholar]
- Ory, M.G.; Ahn, S.; Jiang, L.; Smith, M.L.; Ritter, P.L.; Whitelaw, N.; Lorig, K. Successes of a national study of the Chronic Disease Self-Management Program: Meeting the Triple Aim of Health Care Reform. Med. Care 2013, 51, 992–998. [Google Scholar] [CrossRef] [PubMed]
- Ory, M.G.; Ahn, S.; Jiang, L.; Lorig, K.; Ritter, P.; Laurent, D.D.; Smith, M.L. National study of chronic disease self-management: Six-month outcome findings. J. Aging Health 2013, 25, 1258–1274. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.L.; Towne, S.D., Jr.; Herrera-Venson, A.; Cameron, K.; Kulinski, K.P.; Lorig, K.; Horel, S.A.; Ory, M.G. Dissemination of Chronic Disease Self-Management Education (CDSME) Programs in the United States: Intervention delivery by rurality. Int. J. Environ. Res. Public Health 2017, 16, 638. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.L.; Wilson, M.G.; DeJoy, D.M.; Padilla, H.; Zuercher, H.; Corso, P.S.; Vandenberg, R.J.; Lorig, K.; Ory, M.G. Chronic Disease Self-Management Program (CDSMP) in the workplace: Opportunities for health improvement. Front. Public Health 2015. [Google Scholar] [CrossRef] [PubMed]
- Wilson, M.G.; DeJoy, D.M.; Vandenberg, R.J.; Padilla, H.; Davis, M. FUEL Your Life: A translation of the Diabetes Prevention Program to worksites. Am. J. Health Promot. 2016, 30, 188–197. [Google Scholar] [CrossRef] [PubMed]
- Wilson, M.G.; DeJoy, D.M.; Vandenberg, R.J.; Corso, P.; Padilla, H.; Zuercher, H. Effect of intensity and program delivery on the translation of Diabetes Prevention Program to worksites. A randomized controlled trial of Fuel Your Life. J. Occup. Environ. Med. 2016, 58, 1113–1120. [Google Scholar] [CrossRef] [PubMed]
- National Council on Aging. Frequently Asked Questions: CDSME Grantees. Available online: https://www.ncoa.org/resources/frequently-asked-questions-cdsme-grantees (accessed on 1 March 2018).
- Belza, B.; Petrescu-Prahova, M.; Kohn, M.; Miyawaki, C.E.; Farren, L.; Kline, G.; Heston, A.H. Adoption of evidence-based health promotion programs: Perspectives of early adopters of Enhance® Fitness in YMCA-affiliated sites. Front. Public Health 2015, 3, 164. [Google Scholar] [CrossRef] [PubMed]
- Ritter, P.L.; González, V.M.; Laurent, D.D.; Lorig, K.R. Measurement of pain using the visual numeric scale. J. Rheumatol. 2006, 33, 574–580. [Google Scholar] [PubMed]
- Centers for Disease Control and Prevention. Measuring Healthy Days: Population Assessment of Health-Related Quality of Life; Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Adult and Community Health: Atlanta, GA, USA, 2000.
- Lorig, K. (Ed.) Outcome Measures for Health Education and Other Health Care Interventions; Sage Publications: Thousand Oaks, CA, USA, 1996. [Google Scholar]
- Kroenke, K.; Strine, T.W.; Spitzer, R.L.; Williams, J.B.; Berry, J.T.; Mokdad, A.H. The PHQ-8 as a measure of current depression in the general population. J. Affect. Disord. 2009, 114, 163–173. [Google Scholar] [CrossRef] [PubMed]
- Paxton, A.E.; Strycker, L.A.; Toobert, D.J.; Ammerman, A.S.; Glasgow, R.E. Starting the conversation: Performance of a brief dietary assessment and intervention tool for health professionals. Am. J. Prev. Med. 2011, 40, 67–71. [Google Scholar] [CrossRef] [PubMed]
- Brown, W.J.; Miller, Y.D.; Miller, R. Sitting time and work patterns as indicators of overweight and obesity in Australian adults. Int. J. Obes. 2003, 27, 1340–1346. [Google Scholar] [CrossRef] [PubMed]
- Morisky, D.E.; Green, L.W.; Levine, D.M. Concurrent and predictive validity of a self-reported measure of medication adherence. Med. Care 1986, 24, 67–74. [Google Scholar] [CrossRef] [PubMed]
- Lerner, D.; Amick, B.C., III; Rogers, W.H.; Malspeis, S.; Bungay, K.; Cynn, D. The work limitations questionnaire. Med. Care 2001, 39, 72–85. [Google Scholar] [CrossRef] [PubMed]
- Toumi, K.; Ilmarinen, J.; Jahkola, A.; Katajarinne, L.; Tulkki, A. Work Ability Index. Occupational Health Care 19, 2nd ed.; Finnish Institute of Occupational Health: Helsinki, Finland, 1998. [Google Scholar]
- Cohen, S.; Kamarck, T.; Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 1983, 24, 385–396. [Google Scholar] [CrossRef] [PubMed]
- McArdle, J.J. Latent variable modeling of differences and changes with longitudinal data. Annu. Rev. Psychol. 2009, 60, 577–605. [Google Scholar] [CrossRef] [PubMed]
- Newsom, J.T. Longitudinal Structural Equation Modeling: A Comprehensive Introduction; Routledge: New York, NY, USA, 2015. [Google Scholar]
- Muthén, L.K.; Muthén, B.O. Mplus User's Guide, 7th ed.; Muthén & Muthén: Los Angeles, CA, USA, 2012. [Google Scholar]
- Shubert, T.E.; Smith, M.L.; Goto, L.; Jiang, L.; Ory, M.G. Otago Exercise Program in the United States: Comparison of 2 Implementation Models. Phys. Ther. 2017, 97, 187–197. [Google Scholar] [CrossRef] [PubMed]
- Ory, M.G.; Ahn, S.; Smith, M.L.; Jiang, L.; Lorig, K.; Whitelaw, N. National Study of Chronic Disease Self-Management: Age comparison of outcome findings. Health Educ. Behav. 2014, 41 (Suppl. 1), 34S–42S. [Google Scholar] [CrossRef] [PubMed]
- Varekamp, I.; Van Dijk, F.J.H. Workplace problems and solutions for employees with chronic diseases. Occup. Med. 2010, 60, 287–293. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.L.; Wilson, M.G.; DeJoy, D.M.; Padilla, H.B.; Zuercher, H.; Vandenberg, R.; Corso, P.S.; Lorig, K.; Ory, M.G. Translating the Chronic Disease Self-Management Program (CDSMP) for use in the workplace: Stakeholders and processes. Presented at the 143rd American Public Health Association Annual Conference, Chicago, IL, USA, 31 October–4 November 2015. [Google Scholar]
- Smith, M.L.; Wilson, M.G.; Zuercher, H.; DeJoy, D.M.; Padilla, H.B.; Vandenberg, R.; Corso, P.S.; Lorig, K.; Ory, M.G. The role of trained facilitators in translating CDSMP for use in the workplace. Presented at the Gerontological Society of America Annual Conference, Orlando, FL, USA, 18–22 November 2015. [Google Scholar]
- Jiang, L.; Smith, M.L.; Chen, S.; Ahn, S.; Kulinski, K.P.; Lorig, K.; Ory, M.G. The role of session zero in successful completion of Chronic Disease Self-Management Program (CDSMP) workshops. Front. Public Health 2015. [Google Scholar] [CrossRef] [PubMed]
- Meng, L.; Galyardt, A.; Robinson, K.; DeJoy, D.M.; Padilla, H.; Bien, M.B.; Zuercher, H.; Smith, M.L. Factors associated with interest in worksite health-related discussions/events among employed adults with chronic conditions. J. Occup. Environ. Med. 2017, 59, e145–e149. [Google Scholar] [CrossRef] [PubMed]
- Meng, L.; Wolff, M.B.; Mattick, K.A.; Wilson, M.G.; DeJoy, D.M.; Smith, M.L. Strategies for worksite health interventions to employees with elevated risk of chronic diseases. Saf. Health Work 2017, 8, 117–129. [Google Scholar] [CrossRef] [PubMed]
- American Psychological Association. Center for Organizational Excellence. 2017 Work and Well-Being Survey. Available online: http://www.apaexcellence.org/assets/general/2017-work-and-wellbeing-survey-results.pdf?_ga=2.143452918.2120307487.1496324171–161101498.1496323427 (accessed on 3 March 2018).
CDSMP (Usual Care) | wCDSMP (Workplace-Tailored) |
---|---|
Format | |
6 weeks | 8 weeks |
2.5 h sessions (1 session per week) | 50 min sessions (2 sessions per week) |
On-site or off-site (worksite dependent) | On-site or off-site (worksite dependent) |
On or off work time (worksite dependent) | On or off work time (worksite dependent) |
Facilitated by 2 leaders | Facilitated by 2 leaders |
Leader training (4-day training) | Leader Training (4-day training) + bridge training (4 h) |
Participant materials (book & CD) | Participant materials (book & CD) [consider lending library] |
Target participants aged 50 years and older | Target participants aged 40 years and older |
Up to 18 participants | Up to 16 participants |
Content | |
Reorganized order of activities | |
Emphasis on work-life balance | |
Updated work-related examples, content, and activities | |
Addition of stress-related content/activities | |
Revised communication activity | |
Revised and streamlined information about nutrition | |
Reduced information about falls |
Total (n = 181) | CDSMP (n = 109) | wCDSMP (n = 72) | Χ2 or t | p | |
---|---|---|---|---|---|
Age (range 23 to 72) | 47.90 (±10.10) | 46.51 (±9.78) | 49.99 (±10.29) | 2.27 | 0.024 |
Sex | 0.01 | 0.937 | |||
Male | 23 (12.9%) | 14 (13.1%) | 9 (12.7%) | ||
Female | 155 (87.1%) | 93 (86.9%) | 62 (87.3%) | ||
Race | 1.59 | 0.208 | |||
Non-Hispanic White | 107 (62.2%) | 68 (66.0%) | 39 (56.5%) | ||
Racial/Ethnic Minority | 65 (37.8%) | 35 (34.0%) | 30 (43.5%) | ||
Education | 9.61 | 0.142 | |||
Some high school | 2 (1.1%) | 0 (0.0%) | 2 (2.9%) | ||
High school graduate or GED | 14 (8.0%) | 5 (4.8%) | 9 (12.9%) | ||
Some college or technical/vocational training | 46 (26.3%) | 26 (24.8%) | 20 (28.6%) | ||
Associate’s degree | 25 (14.3%) | 14 (13.3%) | 11 (15.7%) | ||
Bachelor’s degree | 22 (12.6%) | 15 (14.3%) | 7 (1.0%) | ||
Postgraduate work | 5 (2.9%) | 4 (3.8%) | 1 (1.4%) | ||
Postgraduate degree | 61 (34.9%) | 41 (39.0%) | 20 (28.6%) | ||
Chronic Conditions | |||||
Obesity | 132 (73.3%) | 74 (68.5%) | 58 (80.6%) | 3.20 | 0.074 |
High Cholesterol | 78 (45.1%) | 44 (41.9%) | 34 (50.0%) | 1.09 | 0.296 |
High Blood Pressure | 81 (44.8%) | 42 (38.5%) | 39 (54.2%) | 4.29 | 0.038 |
Anxiety or Other Emotional/Mental Health Condition | 47 (26.4%) | 30 (27.5%) | 17 (23.6%) | 0.35 | 0.557 |
Diabetes | 44 (25.1%) | 18 (17.1%) | 26 (37.1%) | 8.93 | 0.003 |
Musculoskeletal Injury/Disorder | 41 (22.7%) | 23 (21.1%) | 18 (25.0%) | 0.38 | 0.540 |
Depression | 40 (22.1%) | 21 (19.3%) | 19 (26.4%) | 1.28 | 0.258 |
Arthritis or Other Rheumatic Disease | 36 (19.9%) | 21 (19.3%) | 15 (20.8%) | 0.07 | 0.796 |
Digestive Diseases/Conditions | 35 (19.3%) | 20 (18.3%) | 15 (20.8%) | 0.17 | 0.679 |
Asthma | 12 (6.6%) | 7 (6.4%) | 5 (6.9%) | 0.02 | 0.890 |
Cancer | 6 (3.3%) | 3 (2.8%) | 3 (4.2%) | 0.27 | 0.603 |
Heart Disease | 4 (2.2%) | 1 (0.9%) | 3 (4.2%) | 2.12 | 0.146 |
Other Physical Injuries | 4 (2.2%) | 2 (1.8%) | 2 (2.8%) | 0.18 | 0.673 |
Chronic Bronchitis, Emphysema, or Other COPD | 2 (1.1%) | 1 (0.9%) | 1 (1.4%) | 0.09 | 0.766 |
Other Lung Diseases | 2 (1.1%) | 2 (1.8%) | 0 (0.0%) | 1.34 | 0.248 |
Other Chronic Condition | 25 (13.9%) | 18 (16.5%) | 7 (9.9%) | 1.59 | 0.207 |
Number of Chronic Conditions (range 1 to 16) | 3.25 (±2.02) | 3.00 (±1.87) | 3.64 (±2.19) | 2.10 | 0.037 |
Body Mass Index (Categorical) | 3.94 | 0.269 | |||
Normal Weight (18.5–24.9) | 16 (8.9%) | 13 (12.0%) | 3 (4.2%) | ||
Overweight (25–29.9) | 32 (17.8%) | 21 (19.4%) | 11 (15.3%) | ||
Obese (30–39.9) | 89 (49.4%) | 50 (46.3%) | 39 (54.2%) | ||
Extremely Obese (40+) | 43 (23.9%) | 24 (22.2%) | 19 (26.4%) | ||
Body Mass Index (Continuous) | 34.90 (±7.91) | 34.20 (±8.30) | 35.95 (±7.23) | 1.46 | 0.145 |
Glucose | 103.84 (±36.42) | 100.45 (±38.87) | 108.89 (±32.03) | 1.52 | 0.131 |
Elevated (>99 mg/dL) | 60 (33.9%) | 29 (27.4%) | 31 (43.7%) | 5.04 | 0.025 |
Systolic Blood Pressure | 116.24 (±16.37) | 114.99 (±14.83) | 118.08 (±18.35) | 1.40 | 0.217 |
Elevated (>119) | 42 (23.6%) | 24 (22.6%) | 18 (25.0%) | 0.13 | 0.716 |
Diastolic Blood Pressure | 76.10 (±9.84) | 75.98 (±8.97) | 76.26 (±11.06) | 0.19 | 0.851 |
Elevated (>80) | 54 (30.3%) | 32 (30.2%) | 22 (30.6%) | 0.00 | 0.958 |
Total Cholesterol | 192.20 (±35.30) | 190.82 (±34.94) | 194.28 (±35.98) | 0.64 | 0.524 |
Elevated (>199 mg/dL) | 74 (41.6%) | 43 (40.2%) | 31 (43.7%) | 0.21 | 0.645 |
LDL Cholesterol | 109.95 (±30.13) | 110.22 (±30.90) | 109.54 (±29.13) | −0.15 | 0.884 |
Elevated (>129 mg/dL) | 45 (25.4%) | 30 (28.0%) | 15 (21.4%) | 0.98 | 0.323 |
Proportion of Sessions Attended (Categorical) | 19.73 | <0.001 | |||
75–100% Sessions | 76 (42.0%) | 51 (46.8%) | 25 (34.7%) | ||
50–74% Sessions | 56 (30.9%) | 41 (37.6%) | 15 (20.8%) | ||
25–49% Sessions | 24 (13.3%) | 10 (9.2%) | 14 (19.4%) | ||
<25% Sessions | 25 (13.8%) | 7 (6.4%) | 18 (25.0%) | ||
Proportion of Sessions Attended (Continuous) | 0.61 (±0.28) | 0.68 (±0.24) | 0.52 (±0.31) | −3.80 | <0.001 |
CDSMP (Usual Care) | wCDSMP (Workplace−Tailored) | Between−Group Difference | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Baseline Mean (SE) | n | uΔ (S.E.) | p | Effect Size | Baseline Mean (SE) | n | uΔ (S.E.) | p | Effect Size | uΔ Difference (SE) | p | |
Physically Unhealthy Days | 4.48 (0.78) | 108 | −2.13 (1.65) | 0.198 | −0.04 | 6.06 (0.73) | 72 | −2.07 (0.87) | 0.018 | −0.02 | 8.34 (4.48) | 0.063 |
Mentally Unhealthy Days | 6.25 (0.79) | 106 | 2.61 (1.02) | 0.010 | 0.05 | 5.33 (0.72) | 72 | −1.75 (0.94) | 0.062 | −0.04 | −2.32 (3.53) | 0.512 |
Stress | 5.53 (0.32) | 109 | 0.42 (0.45) | 0.354 | 0.06 | 4.98 (0.25) | 71 | −0.84 (0.55) | 0.127 | −0.10 | 0.06 (1.54) | 0.969 |
Pain | 2.75 (0.31) | 109 | 0.66 (0.50) | 0.179 | 0.09 | 2.40 (0.29) | 71 | −0.90 (0.46) | 0.052 | −0.01 | 0.28 (1.92) | 0.883 |
Fatigue | 4.41 (0.26) | 107 | 0.18 (0.46) | 0.697 | 0.03 | 4.46 (0.25) | 70 | −2.88 (0.92) | 0.002 | −0.17 | −3.68 (1.31) | 0.005 |
Sleep Problems | 3.70 (0.24) | 109 | −0.70 (0.54) | 0.109 | −0.12 | 3.66 (0.27) | 72 | −0.22 (0.56) | 0.694 | −0.04 | 0.72 (1.24) | 0.560 |
Depression | 5.40 (0.40) | 109 | −0.80 (1.18) | 0.500 | −0.06 | 5.58 (0.30) | 72 | −1.07 (0.60) | 0.077 | −0.07 | 0.63 (2.29) | 0.782 |
Eating Behavior—Fast Food Intake (Past Week) | 2.74 (0.13) | 109 | −0.59 (0.34) | 0.082 | −0.34 | 2.65 (0.15) | 72 | −0.76 (0.29) | 0.009 | −0.27 | −1.04 (1.04) | 0.317 |
Eating Behavior—Fruit/Vegetable Intake (Past Week) | 2.76 (0.09) | 109 | 0.56 (0.34) | 0.097 | 0.25 | 2.75 (0.22) | 72 | 0.36 (0.20) | 0.077 | 0.17 | −0.01 (1.05) | 0.991 |
Eating Behavior—Soda/Sugar Beverage Intake (Past Week) | 1.61 (0.09) | 108 | 0.15 (0.49) | 0.765 | 0.05 | 1.69 (0.17) | 72 | −0.78 (0.35) | 0.028 | −0.24 | −2.70 (0.92) | 0.003 |
Physical Activity—Days Exercise (Past Week) | 1.43 (0.15) | 108 | −0.84 (0.51) | 0.102 | −0.19 | 1.34 (0.26) | 72 | 0.28 (0.35) | 0.424 | 0.07 | 2.88 (1.40) | 0.039 |
Sedentary Behavior on Work Days | 9.02 (0.49) | 109 | −0.17 (1.02) | 0.870 | −0.01 | 9.66 (0.74) | 72 | −4.49 (1.90) | 0.018 | −0.02 | −14.22 (9.24) | 0.124 |
Self-Efficacy for Managing Chronic Disease | 7.70 (0.23) | 86 | 0.33 (0.73) | 0.657 | 0.09 | 7.22 (0.41) | 63 | −0.28 (0.72) | 0.695 | −0.06 | −2.63 (1.38) | 0.056 |
Prescription Medication Adherence | 1.24 (0.10) | 96 | −0.09 (0.65) | 0.895 | −0.06 | 1.22 (0.24) | 65 | −0.03 (0.30) | 0.923 | −0.02 | −1.20 (1.15) | 0.297 |
Patient–Provider Communication | 3.28 (0.12) | 109 | 0.41 (0.43) | 0.334 | 0.26 | 3.28 (0.14) | 72 | 0.46 (0.21) | 0.031 | 0.33 | 1.34 (0.83) | 0.106 |
WLQ: Time Demands | 17.06 (1.64) | 105 | 3.12 (6.89) | 0.651 | 0.01 | 23.12 (2.98) | 68 | 1.88 (8.43) | 0.824 | 0.00 | −7.43 (21.03) | 0.724 |
WLQ: Physical Demands | 19.58 (3.80) | 107 | −1.06 (6.74) | 0.875 | 0.00 | 21.01 (3.16) | 71 | 3.51 (5.32) | 0.525 | 0.00 | 9.94 (20.35) | 0.625 |
WLQ: Mental Demands | 16.30 (1.40) | 107 | 1.54 (7.26) | 0.832 | 0.00 | 19.80 (2.22) | 71 | −8.89 (4.47) | 0.010 | −0.02 | −30.56 (14.87) | 0.040 |
WLQ: Interpersonal Demands | 7.12 (1.51) | 105 | −1.15 (8.82) | 0.896 | 0.00 | 12.44 (2.48) | 71 | −3.62 (3.21) | 0.529 | −0.01 | −9.52 (15.19) | 0.531 |
WLQ: Output Demands | 9.08 (1.07) | 107 | 2.78 (6.06) | 0.646 | 0.01 | 13.35 (2.58) | 71 | 2.08 (4.66) | 0.655 | 0.00 | −8.57 (16.36) | 0.600 |
Work Ability | 37.55 (0.77) | 109 | −0.65 (1.83) | 0.720 | −0.01 | 36.63 (1.46) | 72 | −2.32 (1.36) | 0.088 | −0.04 | −4.26 (7.48) | 0.569 |
Job Stress | 1.31 (0.12) | 109 | 0.23 (0.27) | 0.385 | 0.35 | 1.13 (0.17) | 72 | −0.18 (0.23) | 0.452 | −0.17 | −0.35 (0.58) | 0.548 |
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Share and Cite
Smith, M.L.; Wilson, M.G.; Robertson, M.M.; Padilla, H.M.; Zuercher, H.; Vandenberg, R.; Corso, P.; Lorig, K.; Laurent, D.D.; DeJoy, D.M. Impact of a Translated Disease Self-Management Program on Employee Health and Productivity: Six-Month Findings from a Randomized Controlled Trial. Int. J. Environ. Res. Public Health 2018, 15, 851. https://doi.org/10.3390/ijerph15050851
Smith ML, Wilson MG, Robertson MM, Padilla HM, Zuercher H, Vandenberg R, Corso P, Lorig K, Laurent DD, DeJoy DM. Impact of a Translated Disease Self-Management Program on Employee Health and Productivity: Six-Month Findings from a Randomized Controlled Trial. International Journal of Environmental Research and Public Health. 2018; 15(5):851. https://doi.org/10.3390/ijerph15050851
Chicago/Turabian StyleSmith, Matthew Lee, Mark G. Wilson, Melissa M. Robertson, Heather M. Padilla, Heather Zuercher, Robert Vandenberg, Phaedra Corso, Kate Lorig, Diana D. Laurent, and David M. DeJoy. 2018. "Impact of a Translated Disease Self-Management Program on Employee Health and Productivity: Six-Month Findings from a Randomized Controlled Trial" International Journal of Environmental Research and Public Health 15, no. 5: 851. https://doi.org/10.3390/ijerph15050851