Skip navigation
Browser upgrade notice

Gignac M, Sutton D, Badley EM. Re-examining the arthritis-employment interface: Perceptions of arthritis-work spillover. Arthritis Care 2006 Apr 15;55(2):233-40. [Pub Med ID 16583413]


To examine employed individuals’ perceptions of arthritis-work spillover (AWS), the reciprocal influence of arthritis on work and work on arthritis, and the demographic, illness, and work context factors associated with AWS.



The study group comprised 492 employed individuals (383 women & 109 men) with either osteoarthritis or inflammatory arthritis. Participants completed an interview-administered, structured questionnaire assessing AWS, demographic (e.g., age, sex), illness (e.g., disease type, pain, activity limitations), and work context (e.g., workplace control, hours of work) variables. Principal components analysis, reliability analysis, and multiple linear regression were used to analyze the data.


A single factor solution emerged for AWS. The scale had an internal reliability of 0.88. Respondents were more likely to report that work interfered with caring for their arthritis than they were to report that their disease affected their work performance. Younger respondents, those with more fatigue and workplace activity limitations, and those working in trades and transportation reported more AWS. Individuals with more control over their work schedules reported less AWS.



The results of this study extend research on arthritis by reexamining the interface between arthritis and employment. This study introduced a new measure of AWS that enhances the range of tools available to researchers and clinicians examining the impact of arthritis in individuals’ lives.


List of Tables and Figures (in the publication)

  • Table 1. Sample characteristics.
  • Table 2. Time 1 arthritis-work spillover inter-item correlations and scale internal consistency.
  • Table 3. Bivariate ANOVA/T-test/Regression for explanatory variables by total arthritis work spillover score.
  • Table 4. Multivariate unstandardized and standardized regression coefficients for explanatory variables by arthritis work spillover.
  • No figures for this paper.

Selected Tables from the Publication (with interpretation)

Table 3. Bivariate ANOVA/ t test/ regression for explanatory variables by total arthritis work spillover score.

Variables t/F P
Age (range 21-84 years) -3.05 0.00
Gender (Male/Female) -0.40 0.69
Education 0.25 0.86
Marital Status 0.30 0.74
Live Alone 0.26 0.61
Arthritis type (OA, IA or both) 0.71 0.49
Duration (years) -0.17 0.87
Number of joints affected 5.12 0.00
Pain (previous month) 6.83 0.00
Fatigue (previous month) 9.88 0.00
At home activity limitations i 11.38 0.00
Workplace activity limitations ii 14.46 0.00
Job sector 3.39 0.02
Average hours of work per week 3.37 0.00
Additional job responsibilities 2.18 0.03
Control over work schedule -5.56 0.00

Table 3 revealed that younger participants, those with more joints affected, and those with greater pain and fatigue reported more AWS. Individuals with more at-home and workplace activity limitations also reported significantly more spillover. Work context factors were related to AWS, with job type, longer work hours, and additional job responsibilities such as overtime, variable hours, or business travel being related to spillover. Greater control over work schedule was associated with less AWS.

Supplementary Tables (with interpretation)

Supplementary Table 1. Average score of AWS by Age and Gender at Wave 1.

Age group N Mean Std Dev Minimum Maximum
Less than 40 13 19.615 7.784 7 29
40-49 26 18.192 6.112 7 29
50-59 46 17.130 6.735 6 30
60 + 21 17.190 6.750 6 29
Age group N Mean Std Dev Minimum Maximum
Less than 40 40 17.950 5.306 7 27
40-49 96 18.844 5.844 6 28
50-59 167 18.036 5.283 6 30
60 + 55 16.436 6.131 6 30

Supplementary Table 2. Average score of AWS by Age at Wave 1.

All respondents
Age group N Mean Std Dev Minimum Maximum
Less than 40 53 18.358 5.968 7 29
40-49 122 18.705 5.883 6 29
50-59 213 17.840 5.624 6 30
60 + 76 16.645 6.271 6 30

The results for this study demonstrated that age accounted for 2% of the variance in AWS, with younger respondents reporting more spillover. Spillover seems to decrease markedly after age 50. Younger participants may be more likely to make arthritis-related work changes such as changing the hours of work or the type and nature of their employment.

  1. Eighteen items assessed difficulty with activities in the home environment. Four domains were tapped: personal care (e.g., dressing/undressing, eating), in-home mobility (e.g., standing up, getting in/out of bed), community mobility (e.g., getting in/out of a car), and household activities (e.g., preparing a meal, light & heavy housework).
  2. Eleven items gauged physical functioning and arthritis-related activity limitations in the workplace. Items asked about how much difficulty they had getting to, from and around the workplace; sitting and standing for long periods, the schedule, hours, and pacing of work; etc.