Problems experienced by people with arthritis when using a computer

Arthritis & Rheumatism (Arthritis Care & Research) Vol. 61, No. 5, May 15, 2009, pp 614 – 622 DOI 10.1002/art.24465 © 2009, American College of Rheumatology

ORIGINAL ARTICLE

Problems Experienced by People With Arthritis When Using a Computer NANCY A. BAKER,1 JOAN C. ROGERS,1 ELAINE N. RUBINSTEIN,1 SARALYNN H. ALLAIRE,2 MARY CHESTER WASKO1

AND

Objective. To describe the prevalence of computer use problems experienced by a sample of people with arthritis, and to determine differences in the magnitude of these problems among people with rheumatoid arthritis (RA), osteoarthritis (OA), and fibromyalgia (FM). Methods. Subjects were recruited from the Arthritis Network Disease Registry and asked to complete a survey, the Computer Problems Survey, which was developed for this study. Descriptive statistics were calculated for the total sample and the 3 diagnostic subgroups. Ordinal regressions were used to determine differences between the diagnostic subgroups with respect to each equipment item while controlling for confounding demographic variables. Results. A total of 359 respondents completed a survey. Of the 315 respondents who reported using a computer, 84% reported a problem with computer use attributed to their underlying disorder, and ⬃77% reported some discomfort related to computer use. Equipment items most likely to account for problems and discomfort were the chair, keyboard, mouse, and monitor. Of the 3 subgroups, significantly more respondents with FM reported more severe discomfort, more problems, and greater limitations related to computer use than those with RA or OA for all 4 equipment items. Conclusion. Computer use is significantly affected by arthritis. This could limit the ability of a person with arthritis to participate in work and home activities. Further study is warranted to delineate disease-related limitations and develop interventions to reduce them.

INTRODUCTION Computers are vital tools for obtaining information, enabling efficient communication, and earning a living. They are ubiquitous in the work place and the home; 56% of workers use computers on the job and 62% of households own a computer (1,2). People who have difficulty using a computer may experience limitations at work and be unable to participate in computer-supported home activities such as using e-mail or the Internet. One population at risk for computer use problems is people with arthritis. Arthritis affects 18% of adults ages

Supported by a Chapter grant from the Arthritis Foundation of Western Pennsylvania. Dr. Baker’s work was supported by the Arthritis Foundation, Western Pennsylvania Chapter. 1 Nancy A. Baker, ScD, OTR/L, Joan C. Rogers, PhD, OTR/L, FAOTA, Elaine N. Rubinstein, PhD, Mary Chester Wasko, MD, MSc: University of Pittsburgh, Pittsburgh, Pennsylvania; 2Saralynn H. Allaire, ScD: Boston University School of Medicine, Boston, Massachusetts. Address correspondence to Nancy A. Baker, ScD, OTR/L, 5012 Forbes Tower, Department of Occupational Therapy, University of Pittsburgh, Pittsburgh, PA 15260. E-mail: [email protected]. Submitted for publication May 19, 2008; accepted in revised form January 30, 2009.

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18 – 64 years (3) and is a leading cause of work disability; recent data from the US Centers for Disease Control and Prevention show that 30% of working-age adults with osteoarthritis (OA) have an arthritis-attributable work limitation (3). Other studies have documented work limitations in those with rheumatoid arthritis (RA) and fibromyalgia (FM) (4,5). People with arthritis have difficulty performing physically demanding jobs (6), and therefore may select clerical or administrative positions that appear less physically demanding than labor and service jobs. However, these jobs often require intensive computerrelated hand use (7). People with RA and FM report problems doing hand-intensive tasks (5,7) such as using a computer. People with arthritis may have difficulties performing computer tasks due to pain, restricted movement, muscle weakness, or fatigue. However, the specific limitations in computer use experienced by people with RA, FM, and OA may differ considerably due to the clinical manifestations of each disorder. People with RA have polyarticular synovitis, which can cause structural damage to the cervical spine, shoulders, elbows, wrists, hands, hips, knees, and feet (8). They often present with pain, stiffness, and restricted movement due to fixed deformities of the wrists and hands that may limit manipulation of computer input devices such as the mouse or keyboard. People with OA

Computer Use Problems in People With Arthritis have noninflammatory joint disorders that can damage the cervical spine, lumbar spine, hands (carpometacarpal joint), hips, knees, and first metatarsal joint (8). This damage can cause pain and restricted movement that may limit their ability to sit or manipulate input devices. Common symptoms of FM are widespread myofascial pain, paresthesias, and fatigue (8). People with FM have minimal limitations in manipulating input devices, but may experience limitations in sitting or using input devices secondary to pain. Computer use has been identified as a risk factor for pain and musculoskeletal disorders of the upper extremity in the general population without arthritis (9,10). Postures during computer use, forceful keying, duration of computer use, work station set-up, and the psychosocial work environment have all been associated with upper extremity musculoskeletal disorders in computer users (9). The prevalence of computer-related upper extremity pain in a healthy working population ranges between 10% and 55% (11–13), and the prevalence of musculoskeletal disorders of the upper extremity ranges between 6% and 24% (11,14). People with arthritis are more at risk to develop upper extremity musculoskeletal disorders than those without arthritis (8,15–17). Therefore, it is of primary importance that causes of pain and discomfort be identified in computer users with arthritis so that interventions can be implemented to reduce their risks for injury. Despite the potential negative effect of computer-related problems on work activities, little is known about the magnitude of problems experienced by people with arthritis during computer use (18 –20). The purpose of this study was to describe the degree to which those with RA, OA, and FM report discomfort and problems using a computer. Three questions were addressed: 1) What is the prevalence of computer use discomfort and problems experienced in a sample of people with one of these conditions? 2) Are there differences in the magnitude of computer use discomfort and problems experienced by people with RA, FM, and OA? and 3) To what extent do problems affect overall computer use?

SUBJECTS AND METHODS Subjects. This survey study was approved by the University of Pittsburgh Institutional Review Board (IRB). Respondents were recruited from the University of Pittsburgh Medical Center Arthritis Network Disease Registry, a confidential list of people with arthritis who have signed an IRB-approved consent form that allows them to be contacted by mail about arthritis-related studies. Registrants are drawn from 1 university-based and 2 community-based rheumatology practices in western Pennsylvania. People from western Pennsylvania are primarily white and of European descent, and registrants are primarily this race. The Registry includes a representative sample of common rheumatic diseases affecting western Pennsylvanians, including RA, OA, FM, osteoporosis, and gout. Registry data are collected by self-report. Registrants who meet inclusion criteria for a study are mailed an invitation, and they respond if they are interested in participating.

615 Inclusion criteria for the present study consisted of a diagnosis of RA, FM, or OA, and between age 18 and 65 years. These diagnoses were selected because they represent the spectrum of diagnoses related to arthritis (inflammatory arthritis, noninflammatory arthritis, and myofascial pain disorder) that might result in problems using a computer. Instruments. The Computer Problems Survey (ComPS) was developed for this study by reviewing the literature on musculoskeletal disorders and computer use and talking with focus groups comprised of people with RA, FM, and OA. After the focus group, a draft was mailed to focus group participants for a review of the content and general usability. Feedback from participants led to several wording changes to increase clarity. The ComPS has 4 sections. Section I requests demographic information, including primary arthritis diagnosis and job category. Section I also identifies whether respondents currently use a computer. All respondents who use a computer completed sections II through IV. Section II obtains information about computer use, including where respondents use a computer and hours of computer use per week. Respondents indicated the importance of computer use at work and home, and identified routine computer tasks. Section III explores discomfort experienced while using each of the following 5 items of computer equipment: chair, desk, keyboard, mouse or other input device, and monitor. The chair, keyboard, mouse, and monitor have been identified as problematic for computer users, and have been associated with reports of discomfort and the development of musculoskeletal disorders of the upper extremity during computer use (21). The desk was identified during the focus groups as an additional item associated with discomfort. Discomfort is defined as experiencing aching, burning, numbness, pain, stiffness, cold, or fatigue. Respondents reporting discomfort further rated their general discomfort for each equipment item as just noticeable, mild, moderate, or severe. Section IV explores specific problems associated with each equipment item, which were identified through the literature and clinical experience; the resulting lists of problems were reviewed and discussed in the focus groups, where participants were encouraged to expand the lists by adding other problems they had experienced. The final list of problems grouped according to each equipment item is shown in Table 1. Respondents checked all problems they experienced when using each equipment item. Those indicating problems rated the degree to which all problems with each equipment item affected their overall computer usage as to a small degree, to a moderate degree, to a considerable degree, or to a very high degree. Test–retest reliability for the ComPS was assessed by administering it to 20 people with RA and FM and readministering it ⬃1 week later. The 20 subjects were recruited consecutively over 2 months from a single university-based rheumatology practice. No one with OA volunteered to participate during the time frame. Kappa statistics were calculated for dichotomous variables, and

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Table 1. List of problems for each equipment item in the Computer Problems Survey Chair Finding a chair that is comfortable Finding a comfortable position in the chair Getting up or down from the chair Sitting for ⬎20 minutes in the chair Other problems Desk Enough leg room Enough space for computer and all other materials (e.g., phone) Enough space to put the monitor directly behind the keyboard Easily accessible storage space Height of the keyboard Height of the monitor Other problems Keyboard Hitting individual keys Reaching the keys Touch typing Hitting a key accidentally Holding down 2 keys with one hand Using the numeric pad Positioning hands to use the keyboard Becoming very tired using the keyboard Other problems Mouse Right or left clicking the mouse Double clicking the mouse Positioning the cursor on a small object Holding down a button and moving the cursor at the same time Positioning hand on the mouse Moving the mouse Becoming very tired using the mouse Other problems Monitor Positioning neck/body to see the monitor Seeing the information on the screen Being able to position the monitor in front rather than to one side Glare on the screen Becoming very tired using the monitor Other problems

intraclass correlation coefficients (ICCs) were calculated for continuous or ordinal data. Kappa statistics ranged from moderate to almost perfect agreement (0.46 – 0.81) (22) and all were significant (P ⬍ 0.05). The ICCs ranged from 0.70 – 0.96 and indicated good to excellent agreement (23), except for problems related to the monitor (ICC 0.54); all ICCs were significant (P ⬍ 0.05). Procedure. The ComPS, a letter explaining the survey study, and a return envelope were mailed to 1,190 people in the Registry (502, 406, and 282 with RA, FM, and OA, respectively). Those who wanted to participate returned the completed ComPS in a postage-paid, addressed envelope. The Arthritis Network Research Registry “honest broker” recruitment system prevents release of any information to investigators about the members who received

Baker et al study recruitment mailings; therefore, differences between respondents and nonrespondents could not be ascertained. Statistical analyses. Age was collected categorically (18 –24 years, 25–34 years, 35– 44 years, 45–54 years, 55– 64 years, and ⱖ65 years). Since only 2 OA respondents were in the 18 –24 and 25–34 years categories, the age categories were collapsed into 3 levels (⬍44 years, 45–54 years, and ⱖ55 years) (Table 2). Because very few respondents indicated that they had just noticeable discomfort during computer use, the just noticeable and mild categories were combined. A “number of problems experienced” score for each of the 5 equipment items was developed by summing the number of problems. Descriptive statistics for both computer users and noncomputer users were calculated. An analysis of variance or chi-square analyses were used to determine whether there were significant differences between diagnostic subgroups for demographic data. The subgroups varied significantly for age, sex, and length of time with symptoms of the disorder. The FM subgroup was younger than the RA subgroup, whereas the OA subgroup was older (␹2 ⫽ 28.06, P ⬍ 0.001). The FM subgroup had more women than the RA subgroup (␹2 ⫽ 10.70, P ⫽ 0.005), and had a significantly shorter time of having symptoms of the disorder (F ⫽ 8.62, P ⱕ 0.001). There were no significant differences between the 3 subgroups for any other demographic variable. We used ordinal regression models to estimate if there were significant differences between diagnostic subgroups for each equipment item for 1) the number of respondents reporting discomfort, 2) the number of problems experienced, and 3) the degree to which these problems affected computer use. To control for the effect of the significant differences between the diagnostic categories for age, sex, and length of time with the disorder, we used a separate ordinal regression model for each equipment item. Analysis occurred in 2 stages: we tested a model containing only the demographic variables for significance, and then we entered the diagnostic category. If this combined model achieved significance we examined each diagnostic category to determine which one significantly contributed to the model while controlling for all other variables. No model containing only demographic variables was significant. The addition of diagnostic category made most models significant, suggesting that having any diagnosis had a strong effect on each dependent variable. To control for multiple testing (5 equipment items were evaluated), we used Bonferroni correction, setting the alpha level at 0.01 a priori.

RESULTS Sample. Four hundred fourteen (34.8%) surveys were returned. Although the ComPS instructed respondents to provide only 1 primary diagnosis to allow comparison of responses of people from distinct diagnostic subgroups, some respondents provided ⬎1 diagnosis. Therefore, 42 respondents who indicated ⬎1 diagnosis and 13 respon-

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Table 2. Demographic information on all respondents with usable surveys by diagnosis category*

Age, no. 18–44 years 45–54 years ⱖ55 years Sex, no. Female Race, no. White, non-Hispanic or non-Latino Length of time with disorder, no. Median, years Range, years Working status, no. Working (full time or part time) Student/volunteer Not working Job type, no.† Managerial/ professional jobs Technical/sales jobs Administrative support jobs Service jobs

All

RA

FM

OA

358 41 (11.5) 134 (37.4) 183 (51.1) 358 310 (86.6) 356 332 (93.3) 357 14 0.5–63 357 212 (59.4) 20 (5.6) 130 (36.4) 208 117 (56.3) 11 (5.3) 47 (22.6) 24 (11.5)

200 22 (11.0) 74 (37.0) 104 (52.0) 200 166 (83.0) 198 184 (92.9) 201 15 0.5–55 199 123 (61.8) 10 (5.0) 67 (33.5) 124 76 (61.3) 5 (4.0) 26 (21.0) 11 (8.9)

92 17 (18.5) 43 (46.7) 32 (34.8) 92 89 (96.7) 92 85 (92.4) 90 10 4.5–63 92 48 (52.2) 5 (5.4) 40 (43.5) 46 20 (43.5) 3 (6.5) 16 (34.8) 6 (13.0)

66 2 (3.0) 17 (25.8) 47 (71.2) 66 55 (83.3) 66 63 (95.5) 66 15 1.5–40 66 41 (62.1) 5 (7.6) 23 (34.8) 38 21 (55.3) 3 (7.9) 5 (13.2) 7 (18.4)

* Values are the number (percentage) unless otherwise indicated. RA ⫽ rheumatoid arthritis; FM ⫽ fibromyalgia; OA ⫽ osteoarthritis; no. ⫽ number responding to the question. † Precision production/craft/repair jobs and operator/fabricator/labor jobs comprised ⬍5% of the sample and were omitted.

dents who reported none of the diagnoses of interest were excluded from the study. The completed surveys of 359 respondents were used in data analysis: 201 with RA (40% response rate), 92 with FM (23% response rate), and 66 with OA (23% response rate). Sample description. The final sample was comprised of more than twice as many RA respondents as FM or OA respondents. The Arthritis Network Research Registry has more participants with RA than any other diagnosis, and their survey response rate was the greatest (Table 2). Slightly more than half of the respondents (51.1%) were age ⬎55 years, and 88.5% were age ⬎45 years. The final sample was overwhelmingly female (86.6%) and white. Only 6.7% were Hispanic, which is consistent with the ethnicity of the regional population. Respondents had lived with their disorder for a median of 14 years (range 0.5– 63). One 63-year-old participant reported that she had had FM since birth. Slightly more than half of the sample engaged in paid employment (59.4%; those in the volunteer/student category were considered to be unemployed for purposes of this analysis). Of those who worked, 78.9% were in managerial, professional, or administrative jobs. Of the 359 surveys returned, 87.7% of respondents reported using a computer, 86.2% at work and 93.6% at home (Table 3). Level of discomfort during computer use. Two hundred forty-one computer users (76.5%) reported discomfort using at least 1 equipment item: 124 (69.7%) of the RA subgroup, 71 (87.7%) of the FM subgroup, and 46 (82.1%) of the OA subgroup. The highest percentage of respondents reported discomfort during chair use (54.9%), followed by keyboard use (50.5%) and mouse use (49.5%)

(Figure 1). With diagnostic category included, ordinal regression models significantly predicted discomfort for the chair (P ⬍ 0.001), keyboard (P ⬍ 0.001), mouse (P ⫽ 0.002), and monitor (P ⬍ 0.001). Nagelkerke pseudo R2 for significant models ranged from 0.07 to 0.15. After controlling for the effects of the selected demographic variables, the effect of specific diagnostic category was only significant for the chair and the monitor. Significantly more respondents with RA reported lower levels of discomfort with the chair than those with FM or OA (P ⫽ 0.002), whereas significantly more respondents with FM reported higher levels of discomfort with the monitor than those with RA or OA (P ⬍ 0.001). No demographic variables had a significant effect on the level of discomfort, with one exception: a longer time since diagnosis was associated with lower levels of discomfort with the chair (P ⫽ 0.009). Number of problems during computer use. The number of problems during computer use was collapsed into 3 categories for analysis: 1–2 problems, 3– 4 problems, and ⱖ5 problems. Eighty-four percent of respondents reported at least 1 problem using at least 1 equipment item: 82.0% of the RA subgroup, 88.9% of the FM subgroup, and 85.7% of the OA subgroup. Overall, the largest percentage of respondents reported problems with the chair (69.5%), followed by the keyboard (57.8%), mouse (49.8%), and monitor (40.0%) (Figure 2). With diagnostic category included, ordinal regression models significantly predicted the number of problems experienced for the chair (P ⬍ 0.001), keyboard (P ⫽ 0.010), mouse (P ⫽ 0.002), and monitor (P ⫽ 0.002). Nagelkerke pseudo R2 for significant models ranged from 0.06 to 0.09. After controlling for the effects of the selected demographic variables, the effect of the specific diagnostic category FM was significant for the

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Table 3. Computer use information by diagnosis type*

Use a computer, no. Yes Type of computer use: work, no. Yes Type of computer use: home, no. Yes Computer use, no. Mean ⫾ SD, hours/week Range, hours/week Computer use for work, no. Very important Somewhat important Not very important Computer use for home, no. Very important Somewhat important Not very important Routine computer tasks Check news, weather, sports E-mail Pay bills Play games Search for medical information Search for other information Shop Surf the Internet Word processing

All

RA

FM

OA

359 315 (87.7) 196 169 (86.2) 311 291 (93.6) 310 18.1 ⫾ 16.5 0–105 195 161 (82.6) 23 (11.8) 11 (5.6) 296 65 (22.0) 136 (45.9) 95 (32.1)

201 178 (88.6) 115 101 (87.8) 175 164 (93.7) 174 19.2 ⫾ 18.0 0–105 115 95 (82.6) 14 (12.2) 6 (5.2) 163 31 (19.0) 77 (47.2) 55 (33.7)

92 81 (88.0) 48 43 (89.6) 81 75 (92.6) 81 18.4 ⫾ 15.8 0–60 48 43 (89.6) 2 (4.2) 3 (6.3) 79 20 (25.3) 36 (45.6) 23 (29.1)

66 56 (84.9) 33 25 (75.8) 55 52 (94.5) 55 14.1 ⫾ 11.8 0–50 32 23 (71.9) 7 (21.9) 2 (6.3) 54 14 (25.9) 23 (42.6) 17 (31.5)

193 (61.9) 281 (90.1) 104 (33.3) 142 (45.5) 223 (71.5) 217 (69.6) 166 (53.2) 183 (58.7) 230 (73.7)

116 (65.9) 162 (92.0) 59 (33.5) 80 (45.5) 124 (70.5) 120 (68.2) 96 (54.5) 107 (60.8) 123 (69.9)

50 (61.7) 68 (84.0) 25 (30.9) 40 (49.4) 61 (75.3) 54 (66.7) 41 (50.6) 45 (55.6) 59 (72.8)

27 (49.1) 51 (92.7) 20 (36.4) 22 (40.0) 38 (69.1) 43 (78.2) 29 (52.7) 31 (56.4) 48 (87.3)

* Values are the number (percentage) unless otherwise indicated. RA ⫽ rheumatoid arthritis; FM ⫽ fibromyalgia; OA ⫽ osteoarthritis.

Figure 1. Level of discomfort score by diagnostic subgroup (rheumatoid arthritis [RA; n ⫽ 178], fibromyalgia [FM; n ⫽ 81], or osteoarthritis [OA; n ⫽ 56]) for each equipment item. The number in parentheses is the overall number of computer users who had discomfort for that diagnosis. Those who reported no discomfort were not included in the figure. * ⫽ a diagnosis significantly contributed to the ordinal regression model (P ⱕ 0.01); # ⫽ a specific diagnosis significantly contributed to the model (P ⱕ 0.01).

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Figure 2. Percentage of the sample reporting a number of problems by diagnostic subgroup (rheumatoid arthritis [RA; n ⫽ 178], fibromyalgia [FM; n ⫽ 81], or osteoarthritis [OA; n ⫽ 56]) for each equipment item. The number in parentheses is the overall number of people having any problems for that diagnosis. Those reporting 0 problems were not included in the figure. * ⫽ a diagnosis significantly contributed to the ordinal regression model (P ⱕ 0.01); # ⫽ a specific diagnosis significantly contributed to the model (P ⱕ 0.01).

keyboard (P ⫽ 0.009), mouse (P ⫽ 0.002), and monitor (P ⫽ 0.009), indicating that those with FM reported more problems for these equipment items than those with RA or OA. Effect of problems on computer use. With diagnostic category included, ordinal regression models significantly predicted the effect of problems on computer use for the chair (P ⬍ 0.001), mouse (P ⫽ 0.003), and monitor (P ⫽ 0.001). Nagelkerke pseudo R2 for significant models ranged from 0.07 to 0.11. After controlling for the effects of the selected demographic variables, the effect of the specific diagnostic category FM was significant for the mouse (P ⫽ 0.002), indicating that people with FM reported that problems with the mouse had a greater effect on their computer use than people with RA or OA.

DISCUSSION The physical demands of employment, including hand use, place people with arthritis at risk for work limitations. The results of this study indicate that many people with arthritis experience both discomfort and problems during computer use that could lead to work limitations. Respondents indicated the most discomfort when using their chairs, followed by keyboards and mice. However, there were differences in subgroup reports of discomfort for equipment items. More respondents with FM reported greater discomfort than those with RA and OA for all equipment items, although only the monitor reached significance. Significantly fewer respondents with RA reported severe discomfort using the chair than respondents

with FM or OA. These results reflect characteristics of each diagnosis. FM is characterized by diffuse pain; therefore, it is not unexpected that more respondents with FM reported discomfort. Those with RA do not typically have structural damage in the low back (8) and therefore would be less likely to experience discomfort when sitting. Computer use has been identified as a risk factor for discomfort in the general population without arthritis. The equipment items in this study that caused the most discomfort for those with arthritis, including the chair, keyboard, mouse, and monitor, have also been identified as risk factors for discomfort for all computer users (24). In the general population, this discomfort has been hypothesized to be related to repetition and awkward positioning caused by the different equipment items. Because those with arthritis may experience pain and discomfort even under ideal circumstances, it is not surprising that the prevalence of respondents reporting discomfort with computer use is considerably higher than the general population of computer users (RA 69.7%, FM 87.7%, OA 82.1%, general population 10% to 55% [11–13]). There were 2 types of problems identified by respondents: finding a comfortable position (chair and monitor) and manipulating objects (keyboard and mouse) (Table 1). The number of reported problems followed a similar pattern of the discomfort reports: the greatest percentage of the sample reported problems with the chair, followed by the keyboard, mouse, and monitor. More respondents identified problems with using a computer than reported discomfort, suggesting that discomfort and problems

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Figure 3. Percentage of the sample reporting the effect that their problems had on their ability to use a computer by diagnostic subgroup (rheumatoid arthritis [RA; n ⫽ 178], fibromyalgia [FM; n ⫽ 81], or osteoarthritis [OA; n ⫽ 56]) for each equipment item. The number in parentheses is the overall number of people reporting the effect that their problem has on their ability to use a computer for that diagnosis. * ⫽ a diagnosis significantly contributed to the ordinal regression model; # ⫽ a specific diagnosis significantly contributed to the model (P ⱕ 0.01).

should be considered separately when determining interventions for computer users with arthritis. The problems listed in the ComPS for the mouse and keyboard primarily relate to manipulation, so it is not surprising that those with RA and OA, disorders characterized by both pain and restricted movement, reported problems in these areas. However, those with FM have very subtle impairments in movement such as clumsiness and stiffness (8,25), and their primary limiting factor is diffuse pain. Based on the type of impairments characteristic of each disorder, those with RA and OA should have reported more problems with the keyboard and mouse than those with FM. In this study, those with FM reported more problems. There are several possible explanations for these results: people with FM may have increased clumsiness related to abnormalities in sensory processing or fatigue (8), the presence of diffuse rather than localized pain may result in problems in manipulation, or those with movement limitations may have found methods to adapt their environment more easily than those with diffuse pain, resulting in fewer perceived problems. The effect of the problems on overall computer use provides a global estimate of computer limitations caused by the problems. The percentages of respondents with limitations are almost precisely the same as the percentages of respondents with problems for each equipment item (Figures 2 and 3), suggesting that the more problems a person had, the greater the computer limitation. To confirm these results, we ran post hoc Spearman’s correlations to determine the association between the number of problems and the effect of these problems. All of the associa-

tions were moderate (r ranged from 0.43 to 0.47) and significant (P ⬍ 0.001), supporting the association between problems and limitations. In recent years, numerous products have been designed to reduce discomfort and problems experienced during computer use, such as adjustable chairs and monitors and adapted keyboards and mice. Providing people with arthritis with appropriate strategies and equipment to prevent computer problems may significantly reduce work limitations and prevent those with arthritis from discontinuing computer use. Many respondents appeared to be experiencing work disability: 40.6% were unemployed, which is much higher than the unemployment rate of the general Pittsburgh population (5.2%) (26). Of the respondents who were working, 86.8% reported using a computer at work, which is much higher than the general US working population (56%) (1). Most of our respondents worked in administrative or managerial jobs that require intensive computer use. A high percentage of workers (82.2%) reported that computer use at work was very important. The high percentage of respondents reporting administrative and managerial jobs tends to support the idea that workers with arthritis may work in these types of jobs because they view them as less physically demanding. In addition, 94% of respondents reported that they used a computer at home, which is considerably higher than the computer use reported by the general US population for this age range (69%) (1). One explanation for this higher level of computer use is that people with arthritis use their home computer as a mechanism for tasks such as shopping or banking, or to obtain health information. However, an

Computer Use Problems in People With Arthritis alternative hypothesis is that this sample was a convenience sample that subjects self-selected to participate in the study because they had an interest in computer use. Computer use in the home environment has a greater potential to place people at risk for upper extremity musculoskeletal disorders, because people often do not set up their home computer environment to facilitate performance and reduce risk factors. People with arthritis should have both their work and home computer set-ups evaluated to ensure that both sites facilitate effective computing. This study examined a convenience sample of people with arthritis. The respondents may represent a select sample of those who have trouble using a computer and therefore were interested in completing the survey. This bias may have overestimated the prevalence of computer problems. The study also had a nonresponse rate bias (65%) and the response rate differed by diagnosis: those with RA were twice as likely to respond to the survey as those with FM or OA. This differential response rate may have also overestimated the prevalence of problems in one or more groups. It is quite likely that nonrespondents either used a computer very little or had few perceived computer use problems. Respondents with severe impairments may not have responded because their impairments precluded computer use. This survey did not take into account the effect of differences in computer use patterns, the effect of different environmental factors such as the set-up of the work station, or the psychosocial environment, all of which have been reported in the literature as affecting computer use (9). This study confirmed that a large percentage of computer users with a spectrum of arthritis disorders experience discomfort and problems during computer use, resulting in limitations in their ability to participate in computer activities. The extent of problems is of concern due to the effect that these limitations may have on their ability to use a computer for work-related tasks that appear to be very important for many workers, and the increased risk of people with arthritis developing musculoskeletal disorders of the upper extremity related to computer use. The ability to use a computer appears to be one method to prevent work limitations and eventual work disability, as well as a vital tool for both work and home activities. Therefore, health professionals must work with people with arthritis to identify problems experienced during computer use and implement computer workstation modifications to ensure safe, effective, and comfortable use of all computer equipment. Future studies should compare and contrast computer usage issues between those with and without arthritis, and more accurately describe the problems and coping strategies.

ACKNOWLEDGMENTS We would like to thank the members of the focus groups, whose input was essential in the development of the final ComPS survey instrument, and Dr. Terrance Starz, who referred subjects for the focus groups that assessed the reliability of the ComPS.

621 AUTHOR CONTRIBUTIONS All authors were involved in contributions to study conception and design, acquisition of data or analysis and interpretation of data, and drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be submitted for publication. Dr. Baker had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

REFERENCES 1. Day JC, Janus A, Davis J. Computer and Internet use in the United States: 2003. Washington, DC: US Department of Commerce; 2005. 2. Bureau of Labor Statistics. Computer and Internet use at work in 2003. Washington, DC: United States Department of Labor; 2005. 3. Theis KA, Murphy L, Hootman JM, Helmick CG, Yelin EH. Prevalence and correlates of arthritis-attributable work limitation in the US population among persons ages 18 – 64: 2002 National Health Interview Survey data. Arthritis Rheum 2007; 57:355– 63. 4. Burton W, Morrison A, Maclean R, Ruderman E. Systematic review of studies of productivity loss due to rheumatoid arthritis. Occup Med (London) 2006;56:18 –27. 5. Henriksson CM, Liedberg GM, Gerdle B. Women with fibromyalgia: work and rehabilitation. Disabil Rehabil 2005; 27:685–94. 6. Verstappen SM, Bijlsma JW, Berkleij H, Buskens E, Blaauw AA, ter Borg EJ, et al, on behalf of the Utrecht Rheumatoid Arthritis Cohort Study Group. Overview of work disability in rheumatoid arthritis patients as observed in cross-sectional and longitudinal surveys [review]. Arthritis Rheum 2004;51: 488 –97. 7. Allaire S, Wolfe F, Niu J, Baker NA, Michaud K, LaValley MP. Extent of occupational hand use among persons with rheumatoid arthritis. Arthritis Rheum 2006;55:294 –9. 8. Klippel JH. Primer on the rheumatic diseases. 12th ed. Atlanta: Arthritis Foundation; 2001. 9. Wahlstrom J. Ergonomics, musculoskeletal disorders and computer work. Occup Med 2005;55:168 –76. 10. Gerr F, Monteilh C, Marcus M. Keyboard use and musculoskeletal outcomes among computer users. J Occup Rehabil 2006;16:265–77. 11. Gerr F, Marcus M, Ensor C, Kleinbaum D, Cohen S, Edwards A, et al. A prospective study of computer users. I. Study design and incidence of musculoskeletal symptoms and disorders. Am J Ind Med 2002;41:221–35. 12. Janwantanakul P, Pensri P, Jiamjarasrangsri V, Sinsongsook T. Prevalence of self-reported musculoskeletal symptoms among office workers. Occup Med (London) 2008;58:436 – 8. 13. Klussmann A, Gebhardt H, Liebers F, Rieger MA. Musculoskeletal symptoms of the upper extremities and the neck: a cross-sectional study on prevalence and symptom-predicting factors at visual display terminal (VDT) workstations. BMC Musculoskel Disord 2008;9:96. 14. Rempel DM, Krause N, Goldberg R, Benner D, Hudes M, Goldner GU. A randomised controlled trial evaluating the effects of two workstation interventions on upper body pain and incident musculoskeletal disorders among computer operators. Occup Environ Med 2006;63:300 – 6. 15. Nordstrom DL, Vierkant RA, DeStefano F, Layde PM. Risk factors for carpal tunnel syndrome in a general population. Occup Eviron Med 1997;54:734 – 40. 16. Solomon DH, Katz JN, Bohn R, Mogun H, Avorn J. Non occupational risk factors for carpal tunnel syndrome. J Gen Intern Med 1999;14:310 – 4. 17. Perez-Ruiz F, Calabozo M, Alonso-Ruiz A, Herrero A, RuizLucea E, Otermin I. High prevalence of undetected carpal tunnel syndrome in patients with fibromyalgia syndrome. J Rheumatol 1995;22:501– 4. 18. Mancuso CA, Paget SA, Charlson ME. Adaptations made by

622

19.

20. 21. 22. 23.

Baker et al rheumatoid arthritis patients to continue working: a pilot study on workplace challenges and successful adaptations. Arthritis Care Res 2000;13:89 –99. Williams CA, Templin T, Mosley-Williams AD. Usability of a computer-assisted interview system for the unaided self-entry of patient data in an urban rheumatology clinic. J Am Med Inform Assoc 2004;11:249 –59. Henriksson C, Liedberg GM. Factors of importance for work disability in women with fibromyalgia. J Rheumatol 2000;27: 171– 6. Freivalds A. Biomechanics of the upper limbs. Boca Raton (FL): CRC Press; 2004. Landis JR, Koch CG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159 –74. Portney LG, Watkins MP. Foundations of clinical research:

applications to practice. 2nd ed. Upper Saddle River (NJ): Prentice Hall Health; 2000. 24. Hedge A, Goldstein M, Hettinger L, Varner C, Silva D, Malafronte J, et al. Longitudinal study of the effects of an adjustable ergonomic keyboard on upper body musculoskeletal symptoms. In: Proceedings of the Human Factors and Ergonomics Society 46th Annual Meeting; 2002 Sep 29 to Oct 4; Baltimore, MD. Baltimore (MD): Mira Digital; 2002. p. 602–5. 25. Vollestad NK, Mengshoel AM. Relationship between neuromuscular functioning, disability and pain in fibromyalgia. Disabil Rehabil 2005;27:667–73. 26. Bureau of Labor Statistics. Databases, tables, and calculators by subject: local area unemployment statistics, Pittsburgh. Washington, DC: Bureau of Labor Statistics; 2008. URL: http://www.bls.gov/data/.