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Understanding the adoption of arthritis self-management: stages of change profiles among arthritis patients

Keefe, Francis J.a,*; Lefebvre, John C.a,1; Kerns, Robert D.b; Rosenberg, Robertab; Beaupre, Patc; Prochaska, Judithd; Prochaska, James O.e; Caldwell, David S.f

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doi: 10.1016/S0304-3959(00)00294-3
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Abstract

1. Introduction

Over the past 10 years, there has been growing interest in self-management training for patients having arthritic disorders (Rene et al. 1992; Lorig and Holman, 1993; Goeppinger et al., 1995; Keefe et al., 1996). Educational programs for arthritis patients, that in the past primarily focused on providing detailed information about arthritis and its medical management, are now emphasizing systematic training in self-management strategies (e.g. relaxation training, activity pacing) (Lorig and Gonzalez, 1992). Newly developed cognitive behavioral interventions that provide intensive training in self-management skills for controlling pain have been shown to reduce pain and disability in many arthritis patients (Keefe and Caldwell, 1997). With recognition of the effectiveness of self-management training, there also has been increasing interest in incorporating this training in primary and specialty care treatments for arthritis (Daltroy and Liang, 1993; Hawley, 1995).

Although self-management training appears to be a promising intervention, clinical observations suggest that patients who suffer from arthritic disorders such as osteoarthritis or rheumatoid arthritis may vary considerably in their involvement in self-management efforts (Keefe and Caldwell, 1996). Some arthritis patients lack confidence in their coping abilities, are passive in their coping efforts, and view medical treatment as the only effective way of managing their disease. As a result, they may not be at a stage at which they are interested or willing to become involved in self-management training. Other arthritis patients, however, seem much more confident in their coping abilities, are more active in their coping efforts, and seem more likely to be interested and willing to become involved in formal training in self-management strategies.

In the literature on health promotion, there is growing recognition that patients may be at different stages of change with respect to the adoption of self-management strategies (Velicer et al., 1995). There is also an increasing awareness that health promotion efforts can be more effective if they are tailored to take into account the individual's stage of change (Velicer et al., 1995). The transtheoretical model provides a useful way of understanding the concept of stages of change (Prochaska and DiClemente, 1992). This model, initially developed in the area of smoking cessation, has since been demonstrated to be relevant to over 12 problem or target behaviors (Prochaska, 1992; Prochaska et al., 1994b). In this model, stage is the temporal dimension that represents when particular changes occur (Prochaska and DiClemente, 1998). Stage also represents a continuum of motivational level to take and sustain action. The stages of change described by the transtheoretical model are summarized in Table 1. Individuals are conceptualized as moving from precontemplation, not intending to change, to contemplation, intending to change but being undecided on when to begin, to preparation, actively planning change within the near future, to action, overtly making changes, and into maintenance, taking steps to sustain change and resist temptation to relapse (Prochaska and DiClemente, 1998).

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Table 1:
The five stages of change

Recently, there has been interest in applying the transtheoretical model and stages of change concept to patients suffering from chronic pain (Kerns et al., 1997). Informed by these models, Kerns and his colleagues have developed the Pain Stages of Change Questionnaire (PSOCQ; Kerns et al., 1997). The PSOCQ is comprised of four reliable scales that are consistent with the stages of the transtheoretical model. Most recently, the ability of the measure to predict engagement of chronic pain patients in treatment has been demonstrated among heterogeneous samples of chronic pain patients in several treatment settings (Biller et al., 2000).

The major goal of the present study was to examine whether cluster analysis could be used to identify homogeneous subgroups of patients having persistent arthritis pain based on their responses to a stages of change questionnaire. A major advantage of cluster analysis is that it is an exploratory procedure that is empirical in nature and does not impose any preconceived structure on the data (Velicer et al., 1995). The resulting clusters can be examined to determine whether they fit or do not fit with a theoretical model (e.g. the transtheoretical model). Cluster analysis has been used to identify stages of change subgroups for other problem behaviors such as smoking cessation (Velicer et al., 1995; Dijkstra et al. 1997; Norman et al., 1998) and drug use (El-Bassel et al., 1998). However, it has not been used to identify stages of change in arthritis patients having persistent pain.

The present study examined the adoption of a self-management approach in patients having one of two specific rheumatic diseases: osteoarthritis (OA) or rheumatoid arthritis (RA). There are several reasons why it is particularly appropriate to focus on self-management in patients with these two arthritic disorders. First, these disorders are the most common rheumatic conditions (Felson, 1998). Osteoarthritis affects up to 65% of older adults and rheumatoid arthritis about 5% of the general population. Second, recent clinical guidelines for the treatment of these two disorders emphasize the importance of self-management and self-care as part of an overall treatment program (American College of Rheumatology Ad Hoc Committee on Clinical Guidelines, 1996; Hochberg et al., 1995a,b). Third, since they have a specific medical diagnosis, some patients with OA and RA view their disease as a medical problem that requires medical management and are resistant to and skeptical about the role of self-management (Keefe and Caldwell, 1996).

The goals of the present study were threefold: (1) to determine whether homogeneous subgroups can be identified among OA and RA patients based on their responses to a questionnaire assessing adoption of a self-management approach to their disease; (2) to determine whether the subgroups identified differ in terms of demographic and medical status variables and measures of arthritis pain, physical disability and psychological disability; and (3) to determine whether the subgroups differed in terms of pain-coping strategies and self-efficacy. Based on the transtheoretical model, we anticipated we would identify five subgroups that would correspond to precontemplation, contemplation, preparation, action, and maintenance. We also expected that patients in the action and maintenance subgroups would be more active in their pain-coping efforts and have higher levels of self-efficacy than patients in the other subgroups.

2. Participants and methods

Data presented in this manuscript were collected as part of a pretreatment evaluation in two different randomized clinical treatment outcome studies conducted in our laboratory (one study conducted with RA patients and the other with OA patients). The RA study sample included 103 individuals (19 men and 84 women) with a mean age of 56.2 years (SD 11.7 years), mean disease duration of 13.1 years (SD 11.4 years), and average of 13.7 years of education (SD 2.7 years). The OA study sample included 74 individuals (39 men and 35 women), with a mean age of 60.5 years (SD 10.9 years), a mean disease duration of 12.6 years (SD 13.8 years), and an average of 16.0 years of education (SD 2.7 years).

All participants were volunteers who were recruited from rheumatology clinics, public posters, and newspaper advertisements. All participants had their diagnosis of OA or RA confirmed by the study rheumatologist. To be included, participants had to have no other arthritic disorder in addition to OA or RA, and no other disease that would significantly affect function (e.g. chronic obstructive pulmonary disease, osteoporosis).

All subjects participated in a pretreatment evaluation session during which they completed: (1) a stages-of-change measure specific to adoption of a self-management approach to their arthritis; (2) demographic and medical status measures; (3) measures of pain and adjustment; and (4) measures of self-efficacy and the use of pain-coping strategies.

2.1. Stages-of-change measure

The degree to which each participant was prepared to adopt a self-management approach to managing arthritis symptoms (pain, stiffness, fatigue, sleep, and mood problems) was assessed using the University of Rhode Island Change Assessment questionnaire (URICA; McConnaughy et al., 1983), a 32-item self-report instrument. The URICA has been used to assess stages of adoption of self-management across a broad range of clinical conditions and health behaviors (McConnaughy et al., 1983; DiClemente and Hughes, 1990; DiClemente et al., 1991; Dijkstra et al., 1997; El-Bassel et al., 1998). For this study, the instructions for the URICA were modified slightly so as to indicate that subjects should respond to each of the 32 items based on their beliefs about arthritis and its treatment. Participants rated the degree to which they agreed or disagreed with these items using a 5 point scale (1=strongly disagree to 5=strongly agree). The URICA provides four empirically derived scale scores: (1) precontemplation; (2) contemplation; (3) action; and (4) maintenance. The precontemplation scale is characterized by items that reflect a belief that arthritis pain is primarily a medical problem for physicians to treat. Patients scoring high on this scale may lack knowledge of how to manage their arthritis or believe that a self-management program would not be very likely to be beneficial. The contemplation scale reflects a belief that a self-management program may be beneficial, but the participant is undecided about engaging in self-management. The action scale reflects an acceptance that a self-management program would be beneficial and an active engagement in learning new self-management skills. The maintenance scale reflects an established self-management perspective on chronic arthritis symptoms and a desire to continue to learn and use self-management skills.

Prior studies have provided strong support for the reliability and validity of the URICA (McConnaughy et al., 1983; El-Bassel et al., 1998) and cluster analyses using the URICA (in populations of smokers and drug users) have identified homogeneous subgroups that are consistent with the transtheoretical model (Velicer et al., 1995; Dijkstra et al., 1997; Norman et al., 1998).

2.2. Demographic and medical status measures

All patients completed a demographic/medical status questionnaire on which they were asked to provide information on age, gender, education level, and disease duration. Obesity was assessed by comparing the participant's current weight with their ideal weight. Each participant was weighed and their current weight was converted into the percentage of weight they were above or below the ideal weight given his/her height. The ideal weight was based on standards of ideal weight by height published by the Metropolitan Life Insurance Company (1983).

2.3. Measures of pain and adjustment

The level of pain, physical disability, and psychological disability due to arthritis was assessed using the Arthritis Impact Measurement Scales (AIMS; Meenan et al., 1980). The AIMS is a 45-item self-report measure that is widely used in the rheumatic disease literature. The AIMS pain measure is based on four items that assess the severity of pain, duration of morning stiffness, frequency of severe pain, and frequency of pain in multiple joints. The AIMS physical disability measure is based on scales assessing dexterity, physical activity level, mobility, household activities, and activities of daily living. The AIMS psychological disability measure is based on scales assessing depression and anxiety. Previous studies have supported the reliability of the AIMS and supported its validity in measuring pain, psychological disability, and physical disability (Meenan et al., 1982; Kazis et al., 1983).

2.4. Measures of pain-coping strategies and self-efficacy

2.4.1. Pain-coping strategies

The frequency of pain-coping strategies used in response to pain was assessed using the Coping Strategies Questionnaire (CSQ; Rosenstiel and Keefe, 1983). The CSQ is a 42-item instrument that includes six cognitive pain-coping scales (distracting attention, coping self-statements, ignoring pain sensations, reinterpreting pain sensations, praying/hoping, and catastrophizing), and one behavioral pain-coping scale (increasing behavioral activity). Respondents rate the frequency of use of each coping item on the CSQ using a seven-point scale ranging from 0 (never) to 6 (always). The CSQ also contains two questions that assess the degree to which respondents perceive themselves as able to control and decrease pain on a seven-point scale ranging from 0 (no control/can't decrease it at all) to 6 (complete control/can decrease it completely).

Scores on the CSQ were converted to scores on two coping factors (pain control and rational thinking (PCRT), coping attempts (CA)) using factor loadings identified in prior research with osteoarthritis patients (Keefe et al., 1987). These same factors with very similar factor loadings have also been identified by Parker and his associates in research conducted with rheumatoid arthritis patients (Parker et al., 1989).

2.4.2. Arthritis self-efficacy

The Arthritis Self-Efficacy Scale (ASES: Lorig et al., 1989) was used to assess patients’ confidence that they could control arthritis pain, perform routine physical functions, and control other arthritis symptoms. The ASES is a 20-item scale on which patients are is asked to rate how certain they are that they can perform a particular task, on a 100-point scale ranging from 10 (very uncertain) to 100 (very certain).

The ASES has three subscales: pain management (assessing patients’ confidence that they can decrease arthritis pain), physical function (assessing patients’ confidence that they can perform certain daily activities without assistance), and other arthritis symptoms (assessing patients’ confidence that they can control symptoms related to arthritis such as fatigue and frustration). A composite measure, total self-efficacy, was computed by summing scores on each of the self-efficacy subscales (Parker et al., 1995; Keefe and Caldwell, 1996; Smarr et al., 1997). The ASES has been found to have good reliability, internal consistency, and validity (Lorig et al., 1989).

3. Results

Data analysis involved four steps: (1) a cluster analysis of the responses on the URICA to identify subgroups of participants; (2) a comparison of the identified subgroups in terms of important demographic and medical variables; (3) a comparison of the identified subgroups in terms of measures of pain, physical disability, and psychological disability; and (4) a comparison of the identified subgroups in terms of pain coping, and arthritis self-efficacy.

3.1. Identification of stages-of-change clusters

Cluster analysis is a heuristic technique for classifying participants into groups. One strength of cluster analysis is that it is highly empirical (Afifi and Clark, 1996). That is, the number and characteristics of the groups are derived from the data, and not from theoretically derived classifications. However, the empirically derived clusters can then be interpreted to determine whether they are in agreement with the theoretical model. For the current analyses, cluster analysis was used to identify subgroups of participants who were similar with respect to their reported use of and intentions to engage in self-management strategies for arthritis care.

Scores for each of the four scales of the URICA were standardized for each subject. T-scores for the 103 RA subjects were then submitted to a cluster analysis using Ward's minimum variance technique. The cubic clustering criterion (CCC) employed by SAS (1990) indicated a five-cluster solution accounting for 55% of the variance.

All of the participants were able to be classified into one of five cluster profiles, representing the five stages of change. Fig. 1 presents these clusters. We shall describe each profile, and compare it to what has been found in other behavior areas that have applied the URICA type measure of stages.

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Fig. 1.:
Five cluster profiles derived from scores on the URICA scales among the 103 participants with rheumatoid arthritis.

(1) The first cluster was labeled a ‘precontemplation’ profile. This cluster makes up a full 39% of the patient sample. This profile is characterized by high scores on the precontemplation scale and relatively low scores on the contemplation scale. Action and maintenance scale scores for this cluster were at the mean for the sample. Historically, this profile was called immotive, reflecting a lack of motivation to take action in the foreseeable future. The historic practice was to apply a different label to a profile than was used for a scale so as to avoid confusion. However, there is a long tradition in psychological assessment of using the same label for a scale as for a profile. With the Minnesota Multiphasic Personality Inventory (MMPI; Hathaway and McKinley, 1943), for example, there are scales labeled depression (D) and mania (Ma.) There also exist MMPI profiles that represent a diagnosis or assessment of depression or mania. In the MMPI research area, the use of the same labels for scales and profiles has not produced undue confusion. Most recently, cluster profiles for the stages of change have been labeled with respect to the stage they most reflect.

(2) The second cluster profile was labeled ‘contemplation’. This cluster comprises 10% of the sample. Historically, this profile was labeled uninvolved or pre-participation. In the current study this profile is characterized by a clear elevation on the contemplation scale.

(3) The third cluster profile was labeled ‘preparation’. This cluster comprises 24% of the sample. Participants in this cluster were all within half a standard deviation of the mean for all four URICA scales and accounted for 24% of the sample. Historically, this profile was labeled decision making, reflecting the early name given to the transition stage between contemplation and action. This profile is characterized by elevation on both the contemplation and action scales, reflecting preparation as combining the intention of contemplation with overt behavior changes characteristic of action. In the current cluster, the contemplation and action scales are not as elevated as those usually found with other problem behaviors.

(4) The fourth cluster profile was labeled ‘unprepared action’. This profile makes up about 8% of the sample. This profile has been labeled non-reflective action (Levesque et al., 2000) or non-contemplative action (McConnaughy et al., 1983, 1989) because the precontemplation scale is elevated along with action while the contemplation scale is down. This profile has been interpreted as indicative of action taken with no contemplation or preparation for increasing the intensity of action taken.

(5) The fifth cluster profile was labeled ‘prepared maintenance’. This cluster constitutes about 20% of the sample. Historically, this was labeled as a participation cluster reflecting elevations in contemplation and action scales as well as maintenance scales. This cluster reflects a preparation to increase the intensity of the action that has been sustained to date.

Each of the 103 RA patients was categorized into one of the five clusters and a discriminant function analysis was performed to examine the fit of the data to the structure provided by the cluster analysis. Results of this analysis were impressive, revealing an error count of less than 1%. Only one subject was considered misclassified, having been classified as preparation by the cluster analysis but reclassified into the precontemplation cluster by the discriminant function analysis. Average posterior probabilities were excellent, ranging from 0.92 to 0.99. Similarly, the posterior probability error rate was only 3.5%.

To validate the cluster structure, the algorithm employed by the discriminant function analysis was applied to the sample of 74 osteoarthritis patients. A discriminant function analysis performed on this second sample revealed equally impressive results. Average posterior probabilities ranged from 0.74 to 0.94, with the posterior probability error rate at 12%.

Given the high similarity between the RA and OA cluster solutions, these two samples were combined for all subsequent analyses.

3.2. Comparison of cluster subgroups: demographic and medical status variables

Table 2 presents the means, standard deviations, and frequencies for the demographic and medical status variables. A series of one-way analyses of variance (ANOVAs) and chi-square analyses was conducted to determine if there were any significant differences among the five cluster subgroups on demographic and medical status variables. The results of the ANOVAs indicated that there were significant between group differences in obesity (F(4,168)=3.18, P<0.02). Post hoc analyses using Fisher's least significant difference (LSD) revealed that participants in the precontemplation cluster subgroup were significantly less obese than those in the preparation subgroup and that those in the unprepared action subgroup were significantly less obese than those in the contemplation, preparation, and prepared maintenance clusters. Group differences were also found for years of education (F(4,172)=3.31, P<0.02) with participants in the contemplation subgroup having significantly more years of education than those in each of the other subgroups.

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Table 2:
Mean (SD) for the demographic, medical status, pain, disability, pain-coping, and arthritis self-efficacy variables for the five subgroupsa

Due to the significant differences between the cluster subgroups in terms of obesity and years of education, these variables were used as covariates in all subsequent analyses.

3.3. Comparison of cluster subgroups: pain and adjustment measures

Fig. 2a–c present the means and standard deviations for the pain, physical disability, and psychological disability scores from the AIMS for the five subgroups. A series of analyses of covariance tests (ANCOVAs) was conducted to examine differences among the subgroups on measures of pain and adjustment. The results indicated that there was a significant difference among the subgroups in pain (F(6,166)=6.66, P<0.001), physical disability (F(6,165)=4.47, P<0.001), and psychological disability (F(6,166)=3.63, P<0.01). A series of post hoc analyses were conducted using Fisher's LSD. As can be seen in Fig. 2a, participants in both the preparation and prepared maintenance subgroups had significantly higher levels of pain than those in the precontemplation and contemplation subgroups. Participants in the preparation subgroup also had higher levels of pain than participants in the unprepared action subgroup. As can be seen in Fig. 2b, the overall pattern of subgroup means was similar for the measure of psychological disability. Participants in the preparation and prepared maintenance subgroups had significantly higher levels of psychological disability than those in the precontemplation, contemplation, and unprepared action subgroups. Fig. 2c displays the pattern of subgroup means for physical disability. Participants in the preparation subgroup had the highest level of physical disability (significantly higher than those in the precontemplation subgroup and those in the unprepared action subgroup).

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Fig. 2.:
(a) Mean AIMS pain score for each stages of change cluster. Error bars represent SEM. Bars represent significant pairwise comparisons using Fisher's LSD post hoc test. (b) Mean AIMS psychological disability score for each stages of change cluster. Error bars represent SEM. Bars represent significant pairwise comparisons using Fisher's LSD post hoc test. (c) Mean AIMS physical disability score for each stages of change cluster. Error bars represent SEM. Bars represent significant pairwise comparisons using Fisher's LSD post hoc test.

Taken together, the overall pattern of findings suggests that individuals in the preparation and prepared maintenance subgroups tended to have the highest levels of pain and disability and that individuals in the precontemplation and unprepared action subgroups tended to have the lowest levels of pain and disability.

3.4. Comparison of cluster subgroups: arthritis self-efficacy and pain coping

Table 2 presents the means and standard deviations for the each of the five subgroups on the pain-coping strategies and self-efficacy measures. A series of ANCOVAs was conducted to examine differences among the five subgroups on the two coping measures: coping attempts, and pain control and rational thinking. The results indicated a significant difference between the subgroups on coping attempts (F(6,164)=7.356, P<0.0001). The results of post hoc analyses are displayed in Fig. 3. As can be seen, individuals in the prepared maintenance subgroup scored significantly higher on coping attempts than patients in each of the subgroups except for the preparation subgroup. Individuals in the preparation subgroup had the next highest scores on coping attempts and scored higher on coping attempts than individuals in the precontemplation and contemplation subgroups.

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Fig. 3.:
Mean coping attempts score for each stages of change cluster. Error bars represent SEM. Bars represent significant pairwise comparisons using Fisher's LSD post hoc test.

The ANCOVA for self-efficacy was also significant (F(6,164)=3.52, P<0.01). As can be seen in Fig. 4, post hoc analyses revealed that participants in the unprepared action subgroup had significantly higher levels of self-efficacy than participants in each of the other subgroups.

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Fig. 4.:
Mean total self-efficacy score for each stages of change cluster. Error bars represent SEM. Bars represent significant pairwise comparisons using Fisher's LSD post hoc test.

4. Discussion

The main advantage of cluster analysis is that it provides an empirically based approach to identifying subgroups of individuals with similar characteristics, in this case, their stage of change with regard to adoption of arthritis self-management. These empirically based subgroups can then be examined to determine if they are consistent with the transtheoretical model (Velicer et al., 1995). To our knowledge, this study represents the first attempt to use a cluster analysis to identify stages-of-change subgroups in an arthritis population having persistent pain. The cluster analysis conducted in this study found that, within a population of RA patients, one can identify five homogeneous subgroups on the basis of their stage of adoption of a self-management approach to arthritis. Each of the subgroups was replicated in a second sample of OA patients.

The transtheoretical model of behavior change proposes that individuals may be at different stages of being prepared for behavior change (Prochaska and DiClemente, 1992). These stages include precontemplation, contemplation, preparation, action, and maintenance. We conducted a cluster analysis based on a questionnaire (the URICA) that assesses the extent to which individuals are considering making behavioral changes to cope with their arthritis. A cluster analysis identified five distinct subgroups that are consistent with the transtheoretical model.

There is growing agreement that self-management is a very important element of arthritis care (Daltroy and Liang, 1993; Hawley, 1995). The recent American College of Rheumatology guidelines for the management of osteoarthritis (Hochberg et al., 1995a,b) and rheumatoid arthritis (American College of Rheumatology Ad Hoc Committee on Clinical Guidelines, 1996) in fact point out that patient education in self-management is an essential component of optimal longitudinal treatment. These guidelines underscore the importance of actively involving arthritis patients in such self-management strategies as exercise, joint protection efforts, and pain control skills. They also emphasize that arthritis patients need to be involved in self-management efforts early in the longitudinal course of their disease since these efforts may play a role in preventing pain and disability. Studies have shown that training in self-management can be beneficial in patients who have moderate to high levels pain and disability (Keefe and Caldwell, 1997).

The subgroups identified in this study are interesting from a clinical perspective because they hypothetically may require somewhat different approaches to training in self-management. The first subgroup identified (making up 44% of the total sample of arthritis patients) was labeled as the precontemplation group because examination of this profile of scores revealed particularly high scores on the precontemplation scale. Patients in this subgroup appear to lack motivation to take action and scored low on a measure of active coping (the coping attempts factor of the CSQ). In part, this may be due to the fact that they had lower levels of pain, physical, and psychological disability than patients in many of the other subgroups. Those treating patients in this subgroup need to be aware that resistance to self-management is likely to be a problem and that patients may rationalize or make excuses for their failure to change. Several steps hypothetically could be taken to encourage patients in this subgroup to adopt a self-management approach (Prochaska et al., 1994a). Future controlled outcome studies need to explore the effects of such interventions as: (1) consciousness raising – helping patients recognize the positive consequences of adopting a self-management approach to managing their arthritis symptoms; (2) developing a helping relationship – a relationship with a friend, fellow arthritis sufferer, or health care professional can provide a supportive context in which the patient can provided with feedback and reflect on their own behavior; and (3) avoiding pushing the patient into action – urgently insisting that the patient engage in self-management behaviors may backfire and undermine the major goal which is to help the person at the precontemplative stage move to contemplating making a change (the next stage).

The second subgroup, made up of 11% of the arthritis patients, was labeled as the contemplation subgroup because they had high scores on the contemplation scale. Patients in this subgroup intend to take action in the future, but as can be seen by their scores on the action scale, are not engaging in active coping efforts at this time. Again, this pattern of findings may stem from the fact these patients are currently experiencing low levels of pain and psychological disability. A major goal in treating patients in this subgroup would be to move them from thinking about taking action in the future to preparing to take action (Prochaska et al., 1994a,b). Future controlled studies need to empirically test change techniques for helping arthritis patients at the contemplation stage such as: (1) self-monitoring – asking patients to keep records of key symptoms (e.g. pain) can make them more aware of its severity and frequency and the factors that might be controlling it; and (2) self-reevaluation – instructing patients to systematically assess the pros and cons of adopting versus not adopting a self-management approach often increases their motivation to begin preparing for change.

The third subgroup (22% of the arthritis patients) was labeled as the preparation subgroup. Patients in this subgroup had elevations on both the contemplation and action scales suggesting they are at a transitional stage in which they are both thinking about change and making some overt behavior changes. The severity of pain was significantly higher in this subgroup than in the precontemplation and contemplation subgroups. Patients in the preparation subgroup also had higher levels of physical and psychological disability. Taken together, these results suggest that the severity of pain and disability is highest in those patients who are intending to increase the intensity of their self-management efforts in the near future. The severity of their symptoms may well be a key variable motivating them to take more action. Controlled studies are needed to examine the utility of several change techniques for helping patients at this stage such as: (1) taking small steps – signing up for an exercise class or self-help group; (2) setting a date – selecting a specific date on which to begin engaging in self-management efforts; or (3) going public – making a commitment to adopting a self-management approach to family, friends, and coworkers (Prochaska et al., 1994a,b).

One of the most interesting subgroups identified was the unprepared action subgroup (6% of the sample). This subgroup resembles profiles identified in cluster analyses of other problem areas (McConnaughy et al., 1983, 1989; Levesque et al., 2000) and appears to consist of a group of patients who are taking action but who have not really thought about or prepared for action. The patients in this subgroup may be content with the amount of action and coping taken, since the levels of pain, physical disability, and psychological disability seem to be adequately managed. Consistent with this notion was the finding that these patients also had the highest level of self-efficacy of any of the subgroups identified. The fact that patients in this subgroup are taking action is noteworthy, but they may have difficulty with maintenance of self-management efforts. Cognitive behavior therapy protocols for arthritis self-management (Keefe and Caldwell, 1997) typically include a number of techniques that can help patients who are at this stage. Controlled research is need to test the effects of strategies such as: (1) using rewards – programming in a variety of rewards as consequences can increase the likelihood that self management efforts will become habitual; and (2) setting graded goals – goal setting is structured so that initial goals are easily achieved and later goals more challenging.

The final subgroup identified was the prepared maintenance subgroup that comprised 17% of the patients studied. These patients appeared to be working the hardest to cope and were coping with more severe pain and physical and psychological disability. They also appear to intending to work even harder in the near future to manage their arthritis. None of the patients in this subgroup (or any other of the subgroups) had formal training in self-management techniques. Future studies need to examine whether or not systematic training in coping skills coupled with training in relapse prevention methods (Keefe and Van Horn, 1993) may help these patients better control their pain and disability and maintain their coping efforts.

Based on the transtheoretical model we expected that pain-coping attempts would be most frequent in people who are in preparation, action, and maintenance clusters subgroups and least frequent in those in the contemplation and precontemplation subgroups. As expected, we did find that patients in the preparation and prepared maintenance subgroups scored higher on pain-coping attempts than those in the precontemplation and contemplation subgroups. Two unexpected findings, however, were also noted. First, patients in the unprepared action subgroup had lower levels of pain-coping attempts than patients in the preparation or prepared maintenance subgroups. As noted earlier, the unprepared action subgroup may well be content with the pain-coping efforts they are making since their self-efficacy is high and their pain and physical and psychological disability are low. Rather than engaging in very high levels of pain-coping attempts on a regular basis, patients in the unprepared action subgroup may make frequent pain-coping attempts only when they feel they need to (e.g. when pain increases). Second, although patients in the precontemplation subgroup had relatively low levels of pain-coping attempts, they did have higher levels of pain-coping attempts than patients in the contemplation subgroup. It is possible that patients who are contemplating engaging in self-management may need to temporarily decrease their coping efforts in order to have the energy to contemplate moving on to adopt a more active stance in dealing with their pain (we wish to thank an anonymous reviewer for suggesting this possibility).

Based on the transtheoretical model we also expected that self-efficacy would be highest in patients in the action and maintenance subgroups. Consistent with this expectation, we did find that patients in the unprepared action subgroup showed significantly higher levels of self-efficacy than patients in each of the other subgroups. Patients in the prepared maintenance subgroup, however, did not report higher levels of self-efficacy than patients in the other subgroups. As noted earlier, the arthritis patients in this study had not participated in formal training in self-management strategies. As a result, the confidence of those patients who were trying to maintain coping efforts (i.e. those in the prepared maintenance subgroup) may not have been as high as it could be. It would be interesting to conduct cluster analysis in a group of arthritis patients who had completed formal training in self-management techniques and to examine whether patients in a subgroup that corresponds to maintenance actually had higher levels of self-efficacy.

This study did not find that disease duration was related to subgroup status. This suggests that the adoption of self-management was not simply a function of the length of time someone has arthritis. Clinical observations suggest that some arthritis patients seem to become quite involved in self-management soon after diagnosis, whereas others do not adopt a self-management approach until very late in the course of their disease.

This study relied on a sample of patients who volunteered for participation in treatment outcome research focused on training in pain-coping skills. One might expect these patients to already be committed to making behavior changes. However, even within this population, there was a relatively large subgroup of patients who fit the characteristics of the precontemplative stage (44%). It is possible that in a more general population of arthritis patients recruited from rheumatology practices, the proportion of precontemplaters may be even higher. These results suggest that, although arthritis health professional recognize and emphasize the importance of self-management, many of the patients they treat may be in a precontemplative stage in which they are not yet thinking of adopting a self-management approach to their disease.

Taken together, the findings of this study suggest that there are distinct subgroups of arthritis patients who differ with respect to their stage of adoption of self-management efforts. Future studies are needed to replicate these findings and to validate the subgroups we have identified. These studies not only could provide important information about the validity of the clusters we have identified but also shed light on the value of the transtheoretical model for understanding self-management in arthritis patients. Recent studies carried out in diverse chronic pain samples have shown that scores on a stages-of-change measure are predictive of early drop-out and response to pain treatment programs (Kerns and Rosenberg, 1999; Biller et al., 2000). It is possible that the arthritis subgroups we identified may predict RA and OA patients’ participation in and responsiveness to pain-coping skills training, exercise interventions, or other formal self-management training programs. Further, the transtheoretical model proposes that one can enhance the outcomes of behavior change interventions by tailoring treatment to the patient's particular stage. A very interesting direction for future research would be to compare the effects of a stage-matched self-management training intervention to a standard, conventional self-management training intervention.

Acknowledgements

This study was supported by NIAMS Grants AR-42261 and AR-35270 and by a grant from the Arthritis Foundation.

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Keywords:

Arthritis; Self-management; Cluster analysis

© 2000 Lippincott Williams & Wilkins, Inc.