Workplace Injury and Mental Health in the Nursing

Workplace Injury and Mental Health in the Nursing Home Howard B. Degenholtz, Ph. D. Graduate School of Public Health Center for Bioethics and Health Law University of Pittsburgh Gerontological Society of America Washington, DC November 20, 2004

Co-Authors n n Jules Rosen, MD Vikas Mittal, Ph. D. Nicholas Castle, Ph. D. Darren Liu n n n Funding: AHRQ Shelley Hulland Yong. Joo Rhee, Ph. D Bennoit Mulsant, MD David Nace, MD Frederick Rubin, MD

Background n Nursing Homes are a dangerous work environment n n Workers suffer back injuries more than 6 times the rate of other industries Other sources: n n n Violence, needle stick Training is inadequate Compliance with training is poor “The training is terrible and there’s not enough of it”

Hypotheses n n Poor mental health may lead to decreased vigilance and increase risk of injury Injury may lead to poor physical and mental health

Data Source n n Quality Enhancement and Education in Nursing Homes (QUEENH) Study Organizational Change in two nursing homes n n Did not target workplace safety directly ‘Consistently unstable’ environment during study period n Unit closed between waves 4 and 5

Sample n Five waves of data n n n Injury: n n Collected at 6 month intervals Anonymous self-report survey Injured on the job in past 6 months? Mental Health: n n SF-12 Mental Component Score Symptoms of depression and anxiety Wave 1 Response Rate 75% N 247 2 70% 243 3 65% 230 4 67% 258 5 71% 259

Analysis n Two models: n n n Gee model n n n Gaussian for continuous outcomes (mental health, physical health) Binomial for discrete outcomes (injury, leaving) Adjusts for multiple observations per individual n n n cross-sectional lagged 1 to 5; mean = 3 Total observations n = 693 Multivariate analyses adjust for site differences, age, gender, job satisfaction, job type

Job Type (Wave 1)

Race (Wave 1)

Descriptive Statistics (Wave 1) n n Average Age 42 (range 19 to 74) 84% Female

Injury Rates - Cumulative Combined 10% Site 1 14% Site 2 6% CNA 16% 22% 11% Other 6% 7% 5% RN/LPN

# of Injuries Person by # of Waves in Study # 2 waves 3 waves 4 waves 0 141 (83%) 89 (75%) 63 (71%) 5 waves 56 (74%) 1 22 (13%) 11 (15%) 2 7 (4%) 3 4 22 (19%) 17 (19%) 6 (5%) 5 (6%) 7 (9%) 2 (2%) 3 (3%) 1 (1%)

Cross-Sectional Findings Mental Health * Injury (Odds). 61 (p =. 043) Mental Health ** Injury -1. 49 (p =. 022) N = 693 * Unit change = 1 point on 100 point scale ** Unit change = 10 points on 100 point scale

Lagged Findings Mental Health ** Injury -2. 2 (p =. 009) N = 436 Injury (Odds). 88 (p =. 68) N = 487 Note: Independent Variables Lagged by 1 wave. * Unit change = 1 point on 100 point scale ** Unit change = 10 points on 100 point scale

Effect of Mental Health on Injury Wave 2 on 1 3 on 2 4 on 3 5 on 4 Injury -. 08 (p =. 148) -. 018 (p =. 753) -. 134 (p =. 862). 032 (p =. 741) N 161 116 87 77

Effect of Injury on Mental Health Wave 2 on 1 3 on 2 4 on 3 5 on 4 Mental Health -1. 78 (P =. 207) -2. 42 (P =. 188) -. 322 (p =. 811) -5. 75 (p =. 016) N 163 119 121 97

Consequences of Injury n Poor physical health n n n Slightly lower mental health n n n SF-12 PCS score 55 versus 49 among injured (p =. 000) Lagged injury; Unadjusted SF-12 MCS score 42. 6 versus 41. 1 among injured (p =. 023) Lagged Injury; Unadjusted Leaving the job n n Odds ratio 1. 9 (CI 1. 05 to 3. 4) Lagged Injury; Adjusted for age, gender, job type, etc

Injury and Satisfaction No Injury P (one sided) Pay 3. 4 2. 8 . 0003 Promotion 3. 8 3. 7 . 1371 Co-Workers 4. 6 4. 5 . 2278 Supervisors 3. 8 3. 3 . 0011 Work 5. 0 4. 7 . 0311 Note: Continuous measure from 1 = Very Unsatisfied to 7 = Very Satisfied Lagged Injury; Unadjusted

Limitations n Self-Report Data n Injuries are subject to recall, definition bias n n Non-work injuries may cause loss of work Other sources of injury data n OSHA Selection n n Good response rate, but less satisfied less likely to respond Attrition – people with poor mental health, injuries more likely to leave panel

Discussion n n Injury and worker’s compensation are major issues for industry Association between mental health and injury appears to be due to causal impact of injury Some staff are frequent flyers Evidence that injuries lead to other bad outcomes for organization