Home > RNJ > 2009 > March/April > Readiness to Manage Arthritis: A Pilot Study Using a Stages-of-Change Measure for Arthritis Rehabilitation (CE)

Readiness to Manage Arthritis: A Pilot Study Using a Stages-of-Change Measure for Arthritis Rehabilitation (CE)
A. Barbara Arthur, MSN RN Jacek A. Kopec, MD PhD Alice V. Klinkhoff, MD FRCPC Paul M. Adam, MSW Susan L. Carr, PT Jane M. Prince, BScN RN Kelly E. Dumont, OT BSc Claudio R. Nigg, PhD

The purpose of this pilot study was to evaluate the Readiness to Manage Arthritis Questionnaire (RMAQ), a new multibehavior measure of readiness for change in arthritis management. Data were obtained from 46 patients with chronic inflammatory arthritis admitted for intensive treatment. Test-retest reliability, correlations with clinical variables and theoretically related constructs, and responsiveness to change were assessed. Test-retest reliability indicated reasonable stability, with intraclass correlation coefficients ranging from 0.30 to 0.75. A significant association was observed between psychological well-being and readiness status. Clinical variables of disease duration, disease severity, pain, and function were not related to readiness status. Correlations between stages-of-change scores and self-efficacy for managing arthritis symptoms were mostly nonsignificant, with the exception of modest agreement between readiness to engage in physical activity and exercise self-efficacy (0.43). Significant changes were observed in mean RMAQ scores from initial assessment to 12 weeks posttreatment for the behaviors of using joint protection, dealing with frustration, learning about arthritis, engaging in physical activity, and stress management. Findings from this pilot study suggest that the RMAQ has adequate psychometric properties in patients with chronic inflammatory arthritis and can be used to assess an individual’s readiness to adopt important arthritis self-management behaviors.

Management of chronic inflammatory arthritis is a multidisciplinary effort, consisting of early and continuous use of medication, exercise, ergonomic measures, and joint arthroplasty for individuals with advanced joint disease (American College of Rheumatology Subcommittee on Rheumatoid Arthritis Guidelines [ACRSRAG], 2002). Goals in the management of rheumatoid arthritis (RA) are to prevent or control joint damage and subsequent disability, decrease pain, optimize quality of life, and maintain the ability to work (Scott, 2004). Developing effective and efficient strategies to promote self-management is of critical importance to this process. Recent American College of Rheumatology (ACR) guidelines for managing RA (ACRSRAG) point out that patient education in self-management is an essential component in long-term treatment. Research spanning 20 years has shown that patient involvement in self-management efforts can significantly affect the health behaviors and health status of people with arthritis (Lorig, Mazonson, & Holman, 1993; Taal, Rasker, & Wiegman, 1996).

Success of self-management education and treatment during a rehabilitation process frequently depends on how ready patients are to make changes in their lifestyle and behaviors (Gard, Rivano, & Grahn, 2005; Lineker, Kennedy, Beaton, Shupak, Bradley, & Ross, 2004). Oftentimes with multidisciplinary arthritis treatment programs, patients faced with learning multiple behaviors typically are ready to make changes in one or more parts of their life but not in others. It is not uncommon, for example, to encounter a patient who is prepared to practice stress management and learn therapeutic exercises, but he or she may not be ready to take medications to control disease activity or retrain for a job that is more manageable. Only two studies were found that evaluated arthritis patients’ readiness for self-management (Lineker et al.; Keefe et al., 2000). In the study by Keefe and colleagues, a significant portion of arthritis patients was categorized as “precontemplative,” that is, not intending to make changes toward the new behavior in the near future.

Outcome measures in the rheumatic diseases include disease activity, function, pain, quality of life, fatigue, and psychological status and well-being (Felson et al., 1995; Lubeck, 2004). Although treatment decisions are based on information provided by these measures, they are not helpful in identifying those precontemplators and contemplators who are not motivated to participate in a rehabilitation process. Assessment of readiness based on the stage-of-change construct ensures these motivational differences are taken into account. The aim of this pilot study was to develop and test a theory-based measure for assessment of readiness across multiple self-management behaviors relevant to arthritis.

The Transtheoretical Model

The Transtheoretical Model (TTM) of behavior change has been used to categorize the different stages of motivational readiness and has been applied to numerous behaviors, including physical activity (Marcus et al., 1998; Nigg & Courneya, 1998), weight control and diet (Riebe et al., 2005; Vallis et al., 2003), and medication adherence in chronic disease (Robbins, 1999; Willey et al., 2000), among others. More recently, the TTM has been used in HIV/AIDS treatment to assess readiness for adherence to antiretroviral therapy (Enriquez, Gore, O’Connor, & McKinsey, 2004; Gardner et al., 2007; Nordqvist, Sodergard, Tully, Sonnerborg, & Lindblad, 2006), rehabilitation counseling (Chou, Chan, & Tsang, 2004; Mannock, Levesque, & Prochaska, 2002), diabetes self-management (Gambling & Long, 2006; Jones et al., 2003; Vallis et al.), and eating disorders (Geller, Cockell, & Drab, 2001; Hasler, Delsignore, Milos, Buddeberg, & Schnyder, 2004; Leichner, 2005), where multiple health behavioral changes are necessary for long-term management.

A central construct in the TTM is the stages of change (Prochaska, DiClemente, & Norcross, 1992). Through the use of the staging construct, individuals can be classified into a series of five stages: precontemplation (PC), contemplation (C), preparation (PR), action (A), and maintenance (M). People are thought to progress through these stages at varying rates, often moving back and forth along the continuum a number of times before attaining the goal of maintenance. Preaction stages include PC, during which the individual is not intending to adopt the criteria behavior in the near future, usually measured as the next 6 months; C, during which the individual is intending to adopt the criteria behavior within the near future, operationalized as in the next 6 months; and PR, when the individual is actively considering to adopt the criteria behavior in the immediate future. Action stages include A, during which the individual has adopted the behavior change in the recent past but the changes are not well established (e.g., within 6 months of change), and M, during which the individual has adopted the criteria behavior and is working to sustain the change after the first 6 months (Prochaska & Velicer, 1997).

As people progress, stage-specific strategies (or processes of change), decisional balance, and self-efficacy are used to mediate behavior change. In general, the processes used in the earlier stages involve thinking and feeling. Action-related or behavioral processes are used to a greater extent in the later stages (Prochaska & Velicer, 1997). The decisional balance concept, based on Janis and Mann’s (1977) model of decision making, refers to the weighing of pros and cons, or benefits and barriers, associated with engaging in a particular behavior. Self-efficacy involves judgment of one’s perceived ability to engage in a particular behavior under specific circumstances and is believed to be critical in behavior change (Bandura, 1977). For exercise behavior, self-efficacy has been shown to increase from precontemplation to maintenance (Grace, Barry-Bianchi, Stewart, Rukholm, & Nolan, 2007; Tung, Gillet, & Pattillo, 2005). Recent studies in the exercise literature (Kim, Hwang, & Yoo, 2004; Marcus et al., 1998) and diabetes care (Jones et al., 2003) have found that tailored interventions based on TTM constructs are more effective than traditional approaches that focus on the individual who is assumed to be ready to change.

The most widely used method for assessing readiness to change is the University of Rhode Island Change Assessment (URICA), a 32-item scale used originally in psychotherapy (McConnaughy, Prochaska, & Velicer, 1983) and in substance abuse (Pollini, O’Toole, Ford, & Bigelow, 2006). Items refer generically to the individual’s “problem” but do not specify a particular behavior. This generic reference is not helpful in identifying level of readiness for specified health behaviors in arthritis populations. Given that readiness status differs across behaviors in individuals with arthritis, a multibehavior profile is required to guide treatment.

Using a novel application of the well-established TTM and building on expertise in measurement and health behavior change, the Readiness to Manage Arthritis Questionnaire (RMAQ) was developed. The RMAQ is a new multibehavior stage-of-change measure for arthritis management that allows patients to identify their level of readiness to adopt new behaviors to improve control of their arthritis. The purpose of this pilot study was to develop and evaluate the psychometric properties of the RMAQ in patients with chronic inflammatory arthritis. Test-retest reliability, correlations with clinical variables and other theoretically related constructs, and responsiveness to change were assessed.


Questionnaire Development

Questionnaire development was guided by the literature, clinical observation, expert opinion, and input from patients. Objectives of this phase were to select self-care behaviors shown to improve outcomes in arthritis and obtain feedback on face and content validity. Fifteen behaviors were initially considered. Once the behaviors were identified, eight experts in clinical rheumatology, health behavioral sciences, and measurement/epidemiology were asked to comment on whether questionnaire items covered the spectrum of self-management behaviors and whether they were consistent with the theoretical framework and measurement theory. Complete agreement among reviewers was required to retain a behavior.

A preliminary questionnaire was tested for clarity and ease of use on a sample of 20 patients with chronic inflammatory arthritis receiving treatment at the Mary Pack Arthritis Program. Based on comments received during the testing, the behaviors of finding more suitable employment, changing housing, applying for financial assistance, and engaging in alternate leisure activities were removed. Clinically, these behaviors were perceived as major lifestyle issues rather than health behaviors that could be changed during a 3–4 week treatment period. Eleven arthritis management behaviors were retained for further analysis, and each behavior was measured by a single question. Classification into stages was based on current recommendations by Reed, Velicer, Prochaska, Rossi, and Marcus (1997) for a staging algorithm. A 5-point scale was used to assess level of readiness, with higher scores indicating higher levels of readiness (1 = precontemplation to 5 = maintenance). Typical strategies were provided for each behavior to help patients assess their own readiness levels. Stages of change were considered for the following behaviors: using joint protection devices, communicating effectively, eating a healthy diet, managing fatigue, dealing with the frustration of living with arthritis, learning about arthritis, taking medications as prescribed, controlling pain, engaging in physical activity, getting a restful sleep, and practicing stress management. An example staging algorithm for the behavior of physical activity is presented in Figure 1.


Data were obtained from a convenience sample of patients identified prior to admission to an outpatient rheumatology clinic. The intervention consisted of intensive multidisciplinary treatment of 3–4 weeks in duration, focusing on rehabilitation and education. Eligibility criteria included patients with confirmed diagnosis of inflammatory arthritis, aged 19–74 years, no comorbid conditions associated with chronic pain, and the ability to complete the questionnaires in English. A target sample size of 50 subjects was based on two factors. First, because the reliability and validity analyses involved correlations, the confidence interval (CI) was considered around a correlation coefficient (Streiner & Norman, 1995). Fifty subjects would provide an adequate CI (e.g., for n = 50 and r = 0.8, 95% CI = 0.67–0.88). Second, a recruitment period of 12 months was considered feasible based on an admission rate for intensive rehabilitation of 4–6 patients per month. The University of British Columbia Behavioral Research Ethics Board and the Vancouver Coastal Health Ethical Review Committee approved the study procedures. All subjects signed the informed consent. Of 71 patients identified as eligible during the recruitment period, 25 were excluded: 6 were too ill, 4 could not be scheduled, 9 patients did not return follow-up telephone calls, and 6 refused participation, leaving a final sample of 46, representing a 65% overall participation rate.


Outcome measures included the RMAQ, Centre for Epidemiologic Studies-Depression Scale (CES-D), Arthritis Self-Efficacy Scale (ASES), Health Assessment Questionnaire (HAQ), and a demographic and medical status questionnaire. Participants completed the CES-D Scale, ASES, and HAQ on the day of admission (baseline) and at discharge. The RMAQ was administered to all participants at four time-points: the day of admission, 1 week postadmission, at discharge, and 12 weeks posttreatment. Demographic and medical status information was collected the day of admission. Of the 46 participants who completed assessment measures on the day of admission, 37 (80%) completed all follow-up questionnaires.

The CES-D scale is a 20-item, self-administered instrument for identifying persons at risk for clinical depression (Radloff, 1977). The range of scores is 0–60; higher scores reflect greater symptoms of depression. The CES-D also measures frequency of depressive symptoms during the past week on a scale of 0 (less than 1 day) to 3 (5–7 days). This scale has been extensively used and validated in numerous populations, including RA cohorts, allowing comparisons across studies. The CES-D is considered a reliable instrument with coefficient alphas ranging from 0.85 to 0.90 (Callahan, Kaplan, & Pincus, 1991).

The ASES is a self-administered instrument used to measure whether arthritis patients are able (or believe they are able) to perform specific tasks or behaviors to cope with the consequences of arthritis (Lorig, Chastain, Ung, Shoor, & Holman, 1989). Since its development, the ASES has become the gold-standard measure of self-efficacy (Brady, 2003). Items are designed to capture how certain the individual is that he or she can perform a specific activity. The self-efficacy pain subscale (alpha 0.87) and arthritis-related symptoms subscale (alpha 0.90) were used in this study. In addition, self-efficacy scales developed for managing chronic conditions (Lorig et al., 2001) were used to measure patients’ ability to exercise regularly (Cronbach’s alpha 0.89).

The HAQ is a self-administered instrument used to measure difficulty in performing activities of daily living among individuals with RA and osteoarthritis (OA; Fries, Spitz, Kraines, & Holman, 1980). A 20-item total scale, comprising 8 subscales, uses a 3-point response set of 0 (no difficulty) to 3 (unable to do) to respond to descriptors of function, such as dressing and grooming, arising, eating, walking, and personal hygiene. Higher scores reflect greater limitation, and the highest score within a category is used as the category score. The HAQ is the most widely used functional measure in rheumatology, with test-retest correlations ranging from 0.87 to 0.99 (Bruce & Fries, 2003). A visual analog scale measuring disease severity and severity of pain during the last week was also included.

Statistical Analysis

Descriptive statistics were used to describe the participants. Distribution of RMAQ scores for 11 arthritis self-management behaviors was assessed prior to treatment and at 12 weeks postdischarge. Test-retest reliability was assessed with the intraclass correlation coefficient using data at two time points prior to treatment, with 1 week between administrations. For multi-item scales, test-retest correlation of 0.70 or greater is usually considered adequate (Nunnally & Bernstein, 1994). Because the single-item approach was used to measure each behavior, slightly lower reliability coefficients had been expected; therefore, an intraclass correlation coefficient ≥ 0.60 was considered to be sufficient.

Construct validity of the RMAQ was assessed by correlating RMAQ behaviors with theoretically related constructs and clinical variables. Convergent validity was assessed by calculating the Spearman correlation coefficients between RMAQ scores and measures of self-efficacy, depression, pain, functional status, and disease severity. Direct comparisons were made because several self-efficacy domains corresponded with RMAQ behaviors such as engaging in physical activity, managing pain, dealing with frustration, and managing fatigue. It was hypothesized that self-efficacy scores for behaviors corresponding with RMAQ behaviors would show larger correlations. It was also expected that RMAQ scores would correlate negatively with depression (Geller et al., 2001). Because the analysis comparing stages-of-change scores with clinical indicators of arthritis (e.g., pain, disease severity, physical function) was exploratory, no hypothesis regarding this association was proposed.

We also examined correlations between RMAQ scores and demographic variables and disease duration. The Kruskal-Wallis test was used to evaluate the relationship between mean RMAQ scores and the nominal variables of gender, race, arthritis diagnosis, and employment status. The Spearman-ranked correlation coefficient was used to calculate the relationship between mean RMAQ scores and age, disease duration, and education level. Based on limited research comparing demographic information and disease duration among arthritis patients with readiness for change (Keefe et al., 2000; Lineker et al., 2004), strong correlations between RMAQ scores for the 11 behaviors and age, gender, ethnicity, arthritis diagnosis, employment status, education level, and disease duration were not expected. Responsiveness to change from initial assessment to 12 weeks postdischarge was measured by change in mean RMAQ scores and effect size for each of the 11 behaviors. Data analysis was performed using the SAS statistical package, version 9.1.3 for Windows (SAS Institute, Carey, NC).


Characteristics of the study population are reported in Table 1. Participants (N = 46) ranged in age from 26 to 73 years, with a mean age of 50.1 years. There were 33 women and 13 men. Twenty-five patients (54%) had a high-school education, and 21 (46%) had some postsecondary education. Thirteen patients (28%) were employed, 4 (9%) were retired, and 29 (63%) were unemployed. The admitting diagnosis for 33 subjects was RA, 11 had inflammatory arthritis (3 psoriatic, 3 seronegative, 4 with ankylosing spondylitis, and 1 reactive), and 2 were admitted with complex OA. Disease duration for 34 patients (74%) was more than 1 year, and 12 (26%) were newly diagnosed, with disease duration less than 1 year. Mean disease severity (measured by visual analog scale) was 6.5 (0–10 scale from very well to very poor), and mean pain severity was 6.3 (0–10 scale from no pain to the most severe pain imaginable).

Baseline distribution of stages-of-change scores by self-report for multiple arthritis management behaviors prior to treatment are presented in Figure 2. More than half of subjects were in the maintenance stage for 6 of 11 behaviors: communicating (64%), eating a healthy diet (60%), learning about arthritis (60%), taking medications (74%), controlling pain (65%), and getting a restful sleep (70%). Many reported that they were in the preaction stages prior to treatment for the behaviors of using joint protection (45%), healthy eating (31%), dealing with frustration (47%), and engaging in physical activity (48%). For the behavior of engaging in physical activity, there were similar proportions in preparation (37%) and in maintenance (37%).

Test-retest coefficients and Spearman correlation coefficients between stages of change for arthritis behaviors at baseline with measures of self-efficacy, depression, pain, functional status, and disease severity are reported in Table 2. Test-retest reliability coefficients for the 11 RMAQ behaviors indicated reasonable stability, with intraclass correlation coefficients ranging from 0.30 to 0.75. Coefficients > 0.6 were seen in seven domains: using joint protection (0.67), communicating (0.61), managing fatigue (0.66), learning about arthritis (0.72), taking medications (0.75), engaging in physical activity (0.66), and getting a restful sleep (0.61). Intraclass correlation coefficients < 0.60 were seen in the following domains: healthy eating (0.58), dealing with frustration (0.50), and managing pain (0.52). Test-retest reliability for stress management demonstrated the greatest variability (0.30).

Support for the hypothesized agreement between self-efficacy scores for behaviors corresponding with RMAQ behaviors was marginal. Coefficients for corresponding behaviors of controlling pain (0.16), dealing with frustration (0.01), and managing fatigue (0.29) were generally weak, with the exception of a significant moderate relationship between stages of change for physical activity and self-efficacy to exercise regularly (0.43). Depression scores measured by the CES-D scale correlated in the expected direction for nine RMAQ behaviors. There were statistically significant correlations between depression and communicating (-0.34), healthy eating (-0.48), managing fatigue (-0.34), and learning about arthritis (-0.40). Correlations between RMAQ scores and other indicators of arthritis (e.g., pain, function, disease severity) were mostly nonsignificant. RMAQ scores did not correlate with gender, age, disease duration, arthritis diagnosis, ethnicity, employment status, and education level.

As shown in Table 3, significant changes in RMAQ scores were observed during the course of treatment in the areas of using joint protection, dealing with frustration, learning about arthritis, engaging in physical activity, and managing stress. The behavior of learning about arthritis had the largest effect size (0.54). Effect sizes of other behaviors ranged from 0.11 to 0.49. From initial assessment to 12 weeks posttreatment, forward-stage transition or stage stability in action or maintenance was observed. There was no backward-stage movement.


The RMAQ is a new multibehavior stage-of-change measure for arthritis management. This study’s findings demonstrate that the RMAQ has adequate psychometric properties in people with inflammatory arthritis. The study’s findings support the clinical observation that level of motivational readiness varies considerably across self-management behaviors in individuals with arthritis. The rather polar distribution, with most subjects in action or maintenance stages, suggests that participants were already well-established in their self-management behaviors. This was a selected sample of adults with inflammatory arthritis who chose to participate in an intensive treatment intervention. Lineker and colleagues (2004) reported similar stage distributions among arthritis patients attending an outpatient rheumatology clinic, with a significant portion (46%) in the action or maintenance stage for adopting self-management strategies. Keefe and colleagues (2000) examined stage distributions among a pretreatment sample of arthritis patients and found particularly high scores on the precontemplation scale (44%) compared with the action (6%) and maintenance subgroups (17%). The authors suggest that high precontemplation scores may be due to the fact that this subgroup had lower levels of pain, physical disability, and psychological disability than patients in other subgroups. Collectively, these findings warrant further evaluation of stage distributions among treatment and nontreatment individuals and of factors associated with the five stages of change.

Test-retest reliability coefficients were moderate, with intraclass correlations > 0.6 observed for seven behaviors. The goals in developing the RMAQ were brevity, ease of use and interpretation, and clinical utility. Although a multi-item scale for each behavior might have greater reliability than a single item, the increased length and complexity of the instrument would have made it less acceptable to patients and clinicians. Furthermore, it was not the authors’ intent that this new instrument be the sole tool for assessing readiness levels. A more realistic approach recommended by Miller and Tonigan (1996) is to “provide patients with feedback on their readiness to change scores as a starting point for discussion about their motivation for change” (p. 88).

In assessing a possible relationship between stages of change and self-efficacy, the authors report that only stages of change for physical activity correlated moderately with perceived self-efficacy to exercise. This finding is well-supported in the exercise literature, which consistently reports a positive association between stages-of-change scores and exercise self-efficacy (Grace et al., 2007; Nigg & Courneya, 1998; Reid et al., 2007; Tung et al., 2005). The authors have also observed this relationship in clinical practice. A major barrier to exercise among arthritis patients is pain (Bajwa & Rogers, 2007; Fontaine & Haaz, 2006). Exercise is also known to reduce pain among patients with arthritis (Hammond, 2004; Neuberger et al., 2007). During rehabilitation, patients are taught therapeutic exercises. As a result, patients become more active, experience less pain, and feel more confident in their ability to exercise without exacerbating symptoms. A clinical explanation for the weak associations observed between self-efficacy and readiness levels for managing pain (0.16) and controlling fatigue (0.29) might be that arthritis patients who appear to be actively engaged in self-management efforts are not necessarily confident that their efforts will be effective in controlling arthritis-related symptoms. Taken together, these findings suggest that the increase of self-efficacy across stages seems to be dependent upon the health behavior studied.

The association between readiness levels and psychological distress was comparable to prior research. Research conducted by Geller and colleagues (2001) on the TTM in eating disorders found that a lower level of psychological distress was associated with actively working on symptom reduction. Strand and colleagues (2007) also found an association between higher levels of readiness to change and positive effect in 40 patients with RA. These data suggest that patients do not necessarily need to experience intense distress to begin working on symptom change. Helping patients to reduce their psychological distress may be a helpful step in promoting self-management behaviors. The weak association between the clinical variable of pain and RMAQ scores was also shown by Strand and colleagues, who found no association between readiness to manage pain and pain severity. Clinical observations suggest that although arthritis patients appear to be working very hard to self-manage their disease, they may be experiencing active disease and severe pain. Finally, the lack of correlation observed between RMAQ scores and disease duration is consistent with the results of Keefe and colleagues (2000), who suggest that the adoption of self-management is not simply a function of the length of time someone has arthritis.

Preliminary evidence was found supporting longitudinal validity. The RMAQ appears to measure clinically relevant change in readiness status across multiple behaviors following participation in rehabilitation and education. From initial assessment to 12 weeks posttreatment, this study’s findings showed significant stage progression in using joint protection, engaging in physical activity, increasing knowledge about arthritis management, and practicing stress management. The behaviors that showed more change in readiness status corresponded with the areas of care addressed during multidisciplinary treatment of active arthritis disease. In the absence of a control group, this finding should be interpreted with caution.

This pilot study has several implications for rehabilitation nursing practice, including a focus on the important issue of developing a stage-of-change measure for multiple arthritis self-management behaviors. The demonstrated applicability of the TTM to clients with complex health problems such as HIV (Enriquez et al., 2004; Highstein, Willey, & Mundy, 2006; Nordqvist et al., 2006), eating disorders (Leichner, 2005), coronary artery disease (Johnson et al., 2006; Reid et al., 2007), and diabetes (Gambling & Long, 2006; Jones et al., 2003), suggests that it would be useful for arthritis patients in rehabilitation settings.

This study’s results show an interesting distribution pattern for readiness to use joint protection devices, eat a healthy diet, deal well with frustration, and engage in physical activity. More than one-third of the participants were in the preaction stages for these particular behaviors prior to treatment. Clinically, these finding are important because some of these patients are at a stage during which they intend to change, whereas others are not. Guided by individualized readiness profiles obtained by the RMAQ, the authors recommend that the rehabilitation nurse intervene first with behaviors in preparation because patients in this stage are ready to adopt a behavior. Next, work with those behaviors in contemplation because this stage implies intention to change in the foreseeable future. And, finally, intervene with those behaviors in precontemplation. A patient who is in action or maintenance stages for particular behaviors is already meeting criteria for that behavior so this behavior would require less attention. However, these behaviors could also be used as examples of success as the patient attempts to change others.

There were several limitations of this study. The relatively small sample size may have reduced statistical power to find significant differences. Because the participants were a self-selected group of patients with severe inflammatory arthritis participating in an intensive rehabilitation program, the generalizability of the findings is limited to this population. Another limitation was the data collection of 4 months, which restricted the types of stage transitions that could be observed. The next level of research on the RMAQ will focus on a larger and more representative sample of arthritis patients, with longer follow-up to evaluate stage transitions. This will increase generalizability of results and allow further exploration of theoretical and clinical variables associated with stages of change among arthritis patients. In addition, the matrix of correlation coefficients between the 11 behaviors will be examined, and an exploratory factor analysis will be conducted to determine whether the measured behaviors could be reduced to a smaller number of conceptually meaningful constructs. Finally, it would be interesting to test the new hypothesis that the increase of self-efficacy across the stages seems to be dependent on the health behavior studied.


This pilot study extends the concept of stages of change to the multiple behaviors necessary for successful arthritis treatment. The results indicate that the RMAQ is an appropriate clinical tool for assessing a patient’s readiness to engage in important self-management behaviors. The behaviors identified for multidisciplinary arthritis treatment are using joint protection devices, communicating effectively, eating a healthy diet, managing fatigue, dealing with frustration, learning about arthritis, taking medications as prescribed, controlling pain, engaging in physical activity, getting a restful sleep, and practicing stress management. Ideally, this assessment would be initiated and results taken into consideration before complex treatment recommendations are prescribed.


The authors thank Eric C. Sayre, MSc, research statistical analyst, Arthritis Research Centre of Canada, for his invaluable support. This research was supported by grants from the Vancouver Foundation (File No. BCM02-0090) and the Arthritis Research Center of Canada.

About the Authors

A. Barbara Arthur, MSN RN, is a research coordinator at the Arthritis Research Centre of Canada, Vancouver, and an instructor in the nursing program at Vancouver Community College in Vancouver, BC. Address correspondence to her at barthur@vcc.ca.

Jacek A. Kopec, MD PhD, is a research scientist and epidemiologist at the Arthritis Research Centre of Canada and associate professor of health care and epidemiology at the University of British Columbia, Vancouver, BC.

Alice V. Klinkhoff, MD FRCPC, is medical director at the Mary Pack Arthritis Centre, Vancouver Coastal Health Authority, Vancouver, BC, and clinical associate professor at the University of British Columbia, Vancouver, BC.

Paul M. Adam, MSW, is a social worker and the rheumatology liaison and outreach services coordinator at the Mary Pack Arthritis Program, Vancouver Coastal Health Authority, Vancouver, BC.

Susan L. Carr, PT, is a physiotherapist at the Mary Pack Arthritis Program, Vancouver Coastal Health Authority, Vancouver, BC.

Jane M. Prince, BScN RN, is a clinical resource nurse at the Mary Pack Arthritis Program, Vancouver Coastal Health Authority, Vancouver, BC.

Kelly E. Dumont, OT BSc, is an occupational therapist at the Mary Pack Arthritis Program, Vancouver Coastal Health Authority, Vancouver, BC.

Claudio R. Nigg, PhD, is chair of the Social and Behavioral Health Sciences Program and associate professor in the Department of Public Health Sciences and Epidemiology at the University of Hawaii at Manoa.


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