The Effect of a Tailored Activity Pacing Intervention on Pain and Fatigue for Adults with Osteoarthritis

Abstract

Objective

We examined whether a tailored activity pacing intervention was more effective at reducing pain and fatigue than a general activity pacing intervention.

Method

Adults with knee or hip osteoarthritis (N = 32) stratified by age and gender were randomized to receive either tailored or general pacing instruction. Participants wore an accelerometer for five days that measured physical activity and allowed for repeated symptom assessment. Tailoring involved using data from the accelerometer. Outcomes at 10 week follow-up were pain (WOMAC) and fatigue (Brief Fatigue Inventory).

Results

Compared to general instruction, the tailored group had less fatigue interference (p = .02) and a trend towards decreased fatigue severity (p = .10) at 10 week follow-up. No group differences were found in pain reduction.

Conclusion

Tailoring instruction based on recent symptoms and physical activity may be a more effective symptom management approach compared to general instruction given the positive effects on fatigue.

Arthritis affects approximately 43 million adults and is a leading cause of disability in the US (CDC, 2001; Hootman, Langmaid et al., 2005). Osteoarthritis (OA), the most common form of arthritis, typically affects the knee and hip joints and causes symptoms that are associated with mobility impairment, decreased physical activity, and reduced quality of life. Often people with OA receive pharmacological treatments to alleviate pain; however, a combination of pharmacological and non-pharmacological treatments is considered optimal for OA management (Zhang et al., 2007).

Non-pharmacological treatments, when offered within the context of clinical care, are usually provided by physical and occupational therapists and typically include exercise training, splinting, and adaptive equipment provision. However, these interventions often do not directly address the broader issue of how symptoms affect participation in daily activities, a common source of struggle for people with OA (Leveille et al., 2001).

Activity pacing is a strategy that occupational therapists commonly use to address symptoms that interfere with activity engagement in patients with chronic pain (Brown, 2002). Instruction in activity pacing is believed to help alter inefficient activity patterns such as being overactive with prolonged inactive periods or being under-active, both of which can lead to impaired physical capacities that increase disability (Birkholz, Aylwin, & Harman, 2004). However, a recent review on activity pacing as a management strategy for chronic pain revealed that activity pacing is poorly-defined and is open to variations in implementation among health care practitioners (Gill & Brown, 2009). Thus, while pacing strategies, as currently practiced may add to the personalization of clinical care, it is difficult to systematically evaluate their effectiveness for a given population.

Traditionally, activity pacing is taught contingent upon time; people with chronic pain gradually increase activity periods between intermittent rest breaks (Fordyce, 1976). People usually learn this technique by recording their symptoms and activities in short time increments each day (e.g., one hour blocks) in a logbook and take pre-planned rest breaks (e.g., 15 minutes of every hour) with the intent of resting before symptoms cause them to limit their activities. Although it may be counterintuitive for some people with chronic pain to stop for rest breaks when they are not in a pain ‘flare’, pacing allows them to avoid this flare and to continue with usual activities. Previous studies with people who have knee or hip OA indicate that time-based activity pacing, as part of a larger skills training intervention, is effective at reducing pain severity (Keefe et al., 1990a; Keefe et al., 1990b; Murphy et al., 2008a).

In this study, we defined activity pacing as a strategy in which people strive not to exacerbate their symptoms by planning both daily activities and rest breaks, and by segmenting tasks into multiple shorter time blocks. All participants in the study initially tracked their symptoms and activities during a home monitoring period; however, only the tailored activity pacing group received individualized feedback based on that information.

We believe using a tailored activity pacing approached based on individual activity and symptom patterns would be of particular benefit to adults with OA. Using enhanced wrist-worn accelerometers with a user input button, we can reconstruct a picture of a person’s participation in daily routines by the real-time recording of symptoms and physical activity over a series of days. Our previous studies support an individually tailored approach in several ways. First, we found individual variation in the types and patterns of pain and fatigue symptoms experienced over time (Murphy et al., 2008b). Second, we found that fatigue in participants with OA was more severe and more strongly associated with physical activity levels compared to pain, which suggests that fatigue may also be important to target for intervention (Murphy et al., 2008b). Third, we found that the natural use of activity pacing (prior to instruction) was largely used as a reactionary response to symptom severity instead of as a pre-planned strategy (Murphy et al., 2008c). The purpose of this study was to examine if an intervention tailored on individual symptom and physical activity patterns recorded during a home monitoring period would be more effective at managing pain and fatigue than general instruction about how to use activity pacing as a symptom management tool.

Methods

Sample

Potential participants responded to public advertisements in the Southeastern Michigan area. Based on an initial telephone screening, eligible adults signed consent forms from the University of Michigan Institutional Review Board and underwent x-rays of their hips or knees to determine the presence and severity of OA. Participants were eligible for the study if they were between the ages of 50 – 80, had a score of ≥ 26 on the Mini Mental Status Exam, and were English- speaking. Participants also needed to have symptomatic knee or hip OA in at least one joint as evidenced by self-reported joint pain for at least three months, a pain score of ≥ 4 out of the 5 items on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale with two items rated moderate pain or more (Goggins, Baker, & Felson, 2005), and radiographic evidence of OA in that joint (≥ 2 on the Kellgren Lawrence scale). Individuals were excluded if they were non-ambulatory, had medical conditions or problems (other than OA) that interfered with daily activity performance or caused pain and fatigue (e.g., cardiopulmonary problems, neurological conditions, autoimmune diseases), if they had a joint replacement or surgery of the knee or hip in the previous 6 months, or if they were unable to operate the accelerometer used in this study.

Procedure

Our main data collection periods were at baseline and at 10 week follow-up. We also collected data immediately following the intervention (approximately 4 weeks after baseline); however, these data were only collected to examine potential mechanisms of therapeutic change. We did not feel that application of the techniques and advice from the therapists could be adequately integrated into daily routines immediately after the intervention. At the baseline visit, demographic and health status information were collected and physical performance tests were completed. All participants were then instructed on wearing an accelerometer on their non-dominant wrist during the five day home monitoring period. The accelerometer measured physical activity and participants were also asked to track their symptoms and activity pacing behaviors six times per day (wake up, +2 hours after waking, +6 hours after waking, +10 hours after waking, +14 hours after waking and 30 minutes before bed) by entering their responses into the accelerometer. Participants were also instructed on how to record responses in a log book. The log book was used to record daily activities in addition to wake-up and bed times each day. After the home monitoring period, participants returned the accelerometer and log book and began the intervention within the week. At posttest and at 10 week follow-up, participants wore the accelerometer for a five day home monitoring period and completed questionnaires. The 10 week follow-up period also included a lab visit where participants completed physical performance tests. All testing was done by assessors who were blinded to the group assignment of participants.

Activity Pacing Interventions

Thirty-two adults with symptomatic hip or knee OA stratified by age and gender were randomized into the tailored or the general activity pacing instruction group. Regardless of group, all participants met with an occupational therapist for two one-on-one sessions (total treatment time: 1.5 hours) over a 2-week period.

At the first session, both groups received a study-specific education module on activity pacing. In the general instruction group, the OT discussed the general principles of activity pacing (i.e., pre-planning activities, alternating activity with rest before a symptom exacerbation) with a recommendation to implement the strategies over the subsequent few days. In the tailored group, the OT tailored recommendations based a personalized report that detailed the relationship between activity and symptoms using graphs and bulleted points. While the tailored group also received the education module, the report was the focus of the intervention. For both interventions, the first session involved education on activity pacing (either tailored or general), while the second session focused on individual progress with activity pacing and addressed barriers to using the recommended strategies.

Measures

The primary outcome measures were pain and fatigue. Although momentary pain and fatigue were assessed by entering those ratings into the accelerometer, we chose recall-based measures of symptoms as our primary symptom measures to reduce the possibility of a group bias in momentary symptom reporting (i.e., the tailored group was given information about their momentary symptoms during treatment). Pain was measured by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), a validated, disease-specific questionnaire (Bellamy, Buchanan, Goldsmith, Campbell, & Stitt, 1988). The pain subscale has a scale of 0 – 20 in which a higher number indicates more pain. Fatigue was measured using the Brief Fatigue Inventory (BFI) (Mendoza et al., 1999). The 10-item scale has been validated in cancer patients and among these samples, a general severity score based on an average of 9 items is used. In rheumatology samples, two fatigue subscales of the BFI (fatigue severity and fatigue interference) have been used (Wolfe, 2004). Because we were interested in fatigue as a multidimensional construct, particularly with respect to the degree of interference with daily activities, we chose to analyze our data using these subscales.

Other measures collected were assessments of physical function and physical activity. Physical function was measured by two common, validated measures: the Six Minute Walk Test (Butland, Pang, Gross, Woodcock, & Geddes, 1982) and the Timed Up and Go Test (Podsiadlo & Richardson, 1991). Physical activity was measured by wrist-worn accelerometer [Actiwatch-Score, Mini-Mitter, Bend, OR] over the 5 day home monitoring period. The Actiwatch-Score contains a piezo-electrode that records movements of >0.01g, a level of force that is sensitive to very minute movements. Movement is sampled 32 times per second, and the peak value is added to an accumulated value over a 15-second epoch period, which is recorded as an activity count. Total physical activity was calculated by averaging the cumulative daytime activity counts over 5 days. Peak physical activity was calculated by averaging the largest activity count each day over the 5 day period.

Data Analysis

To examine baseline differences between groups, we calculated each group’s means and performed independent sample t-tests. General linear models were used to examine group differences in pain and fatigue from baseline to 10 week follow-up. In the general linear models, the outcome variables were WOMAC pain, BFI fatigue severity, and BFI fatigue interference and we controlled for age and gender. The main effect is time and the interaction of interest is time x group. Because the small sample size likely affects the power to detect small to moderate effects, the effect size d is also presented for these analyses. The magnitude of d has been described as .2 = small, .5 = moderate, and .8 = large (Cohen, 1988).

Results

Of the 178 people screened by phone for eligibility, 57% were ineligible due to not meeting the study criteria, inability to re-contact, or lack of interest (Figure 1). Of those who proceeded through x-ray screening, 38% were ineligible and 7% were either not interested or withdrew. Twenty four percent of the people originally phone screened (n = 42) were randomized into either the tailored or general instruction groups. Six participants withdrew from the general instruction group and four participants from the tailored group either withdrew (n = 2) or were our first pilot participants (n = 2) which participated only to test intervention delivery and our ability to generate the individualized reports.

Figure 1.

Study Flow Chart

Of the thirty-two participants, 75% were female, and the mean age was 61.9 ± 7.9 years. Two thirds of the sample had radiographic evidence of knee osteoarthritis, and one-third had radiographic hip osteoarthritis. With respect to race, 25 were White (78%), six were African American (19%) and one was a Pacific Islander (3%). Most participants had at least some college education (28/30), and most participants worked at least part-time (26/30).

Table 1 shows characteristics by group. There were no statistically significant group differences. Participants in the tailored intervention group tended to be slightly older (64 versus 60 years), which trended towards significance (p = .10). Participants in both groups were similar in terms of baseline physical function and physical activity. Daily pain medication use by group was very similar over the five day home monitoring period. Three people in each group reported occasional narcotic (e.g., Vicodin) or narcotic-like (e.g., Tramadol) drug use for pain during the five day period. Between the general instruction and tailored groups, there were no significant differences in baseline levels of BFI fatigue severity (4.6 ± 2.3 versus 4.1 ± 1.9 respectively, p = .52) or fatigue interference (4.2 ± 2.9 versus 3.2 ± 2.2 respectively, p = .27). Baseline pain severity on the WOMAC was higher in the general instruction group (10.2 ± 3.9) compared to the tailored group (7.9 ± 3.8) respectively, a result that trended towards significance (p =.10).

Table 1.

Group Characteristics

	General Intervention (n=15)	Tailored Intervention (n=17)	p value
Female (n,%)a	11 (73%)	13 (76%)	.57
Age (yrs)	59.5 (6.6)	63.9 (7.8)	.10
BMI (kg/m2)	31.8 (6.0)	32.7 (7.2)	.59
Daily Pain Medication Useb	7.2 (8.0)	7.1 (8.2)	.98
Depression (GDS)	1.9 (1.8)	2.4 (2.8)	.56
TUG (sec)	10.3 (2.7)	10.3 (2.0)	.97
6-min Walk (feet)	1203 (257)	1120 (295)	.40
Total Physical Activityb (activity counts)	325528.3 (79407.5)	336831.5 (91435.4)	.71
Peak Physical Activity (activity counts)	941.5 (192.6)	911.7 (249.8)	.71

Note: Unless otherwise indicated, means and standard deviations are presented.

^aDue to low cell counts, Fisher exact test was used.

^bDaily average over the 5 day home monitoring period

BMI = Body mass Index; GDS = Geriatric Depression Scale; BFI = Brief Fatigue Inventory; WOMAC = Western Ontario and McMaster Arthritis Index; TUG = Timed up and go test.

Table 2 shows general linear models in which we examined changes in WOMAC pain, BFI fatigue severity, and BFI fatigue interference. For the WOMAC pain measure, both groups reported decreased pain at 10 week follow-up, but no significant time effects or time x group effects were found. A small effect size was found (d = .38). Fatigue severity on the BFI did not significantly differ by group at 10 week follow-up; however, there was a trend towards a greater decrease in the tailored group [F(1,21) = 3.27, p = .09] and there was a moderate to large effect size for this group difference (d = .79). Fatigue interference on the BFI decreased more in the tailored activity pacing group compared to the general instruction group [F(1,21) = 6.36, p = .02] and a large effect size for this group difference was found (d = 1.10). For this statistical model, our test of homogeneity revealed different group variances due to large improvements in the tailored group which caused a floor effect. While the F test is generally robust to moderate deviations of equal variances, we adjusted the alpha level to the more stringent level of .025 to account for this lack of homogeneity (Tabachnick & Fidell, 2007, p. 86). Even with the more stringent alpha level, the effect was still significant.

Table 2.

Repeated measures analyses of variance from baseline to 10 week follow-up

	General Instruction (N = 12)	Tailored Instruction (N = 13)	Time x Group (F,df)	p	d
WOMAC paina			.88 (1,24)	.35	.38
Baseline	9.4 (3.5)	7.9 (4.0)
10 week follow-up	7.6 (3.4)	6.7 (4.0)
BFI severity			3.27 (1,21)	.09	.79
Baseline	4.3 (2.3)	4.1 (2.1)
10 week follow-up	4.8 (3.1)	3.3 (1.8)
BFI interference			6.36 (1,21)	.02	1.10
Baseline	3.6 (2.6)	3.1 (2.3)
10 week follow-up	4.2 (3.4)	1.6 (1.8)

Note. Means (standard deviations) are presented at baseline and 10 week follow-up above.

^aN = 13 in the General Instruction group and N = 15 in the Tailored Instruction group

Clinical Example

To illustrate the tailoring of activity pacing instruction, Figure 2 shows the physical activity and momentary fatigue at baseline and at 10 week follow-up of a 76 year old male. In this Figure, each day is separated by a solid line, physical activity is represented in two hour blocks by the grey-shaded areas, and fatigue levels are represented along the dotted line. At baseline, this participant had fatigue that fluctuated throughout the day and was more severe than pain levels. Fatigue was also associated with bouts of physically-demanding activities (e.g., carrying loads and doing yard work). We used the accelerometer data to examine activity peaks relative to increases in symptoms and to generate an individualized report. The report summarized the symptom and activity patterns and provided person-specific recommendations such as distributing more physically demanding activities throughout the week rather than trying to complete them all in a single day. Examples of recommendations included: 1) planning for a bout of yard work or housework on a day that did not also involve being involved in child care activities; 2) incorporating short rest breaks (5–10 minutes) for every 30–60 minutes of activity; and 3) increasing the frequency of breaks earlier in the day to avoid evening symptom flares. At 10 week follow-up, fatigue was less severe over the five day monitoring period and it was also less variable. Although there was a decrease in total daily physical activity at 10 week follow-up, there was a more sustained activity pattern rather than a series of peaks followed by increased symptoms and extended rest periods. The daily activity log and the accelerometer data indicated that the individual distributed physically demanding activities throughout the week, and tried to minimize doing several demanding activities on the same day as a child-care day. The 10 week follow-up data also showed that while daily fluctuations in fatigue decreased overall, an increase in fatigue severity was seen on Day 5 suggesting another clinical issue for discussion with the participant. Although the intervention ended prior to this data collection period, it may be optimal to have a repeated number of home monitoring sessions that could be intervened upon to continue to help the participant improve or refine symptom management strategies.

Figure 2. Example of a participant in the tailored group at baseline and 10 week follow-up.

Note. Fatigue (dashed line) and activity (grey area) over a 5-day period before and after the tailored activity pacing intervention for a single subject.

Discussion

This pilot study evaluated the effectiveness of a tailored activity pacing intervention for symptom management among people with knee and hip osteoarthritis. We found that overall the tailored activity pacing group, compared to the general instruction group, reported that fatigue had less of an impact on their daily life at 10 week follow-up (d = 1.10) and that overall fatigue severity had decreased (d = .79). The large effect sizes coupled with the statistically significant finding for fatigue interference (p = .02) and the trend towards significance for fatigue severity (p = .09) suggest that the lack of statistical significance for severity measure may be an artifact of the small sample size.

We did not find an effect on pain reduction for the tailored activity pacing group compared to the general instruction group. Although not statistically significant, age and gender-adjusted models suggest that both groups reported decreased pain from baseline to 10 week follow-up [F (time) (1,24) = .09, p =.77]. This difference reached statistical significance in unadjusted models, [F (1,23) = 12.99, p = .002], suggesting a possible effect of participating in either intervention on pain reduction—although the lack of a no treatment control group complicates interpretation of this finding. A larger future study can further explore this issue.

Given that the tailored intervention was designed to target problematic symptoms from the home monitoring period, it is not surprising that fatigue was most greatly impacted in the tailored activity pacing intervention. In our previous work, we showed that momentary fatigue was higher, more variable, and more strongly associated with physical activity levels than momentary pain for people with knee or hip OA (Murphy et al., 2008b). Therefore, fatigue may have been discussed more often or to a greater extent than pain in the tailored intervention. Although fatigue was discussed in the general instruction group, it appears that the tailored activity pacing approach was needed to positively impact fatigue.

While this pilot study needs to be replicated with a larger sample, the results are promising and demonstrate a potential method to deliver a targeted symptom management intervention for people with knee or hip OA. The use of wrist-worn accelerometers to measure within-day symptoms and physical activity and the corresponding log books provide a comprehensive picture of a person’s participation in daily routines. Because these data are collected in a home monitoring period and can be synthesized for therapists into reports, the intervention can potentially have a powerful impact due to the tailoring and can be delivered in a health care setting in a limited number of sessions. Although there was a time burden for our research staff to generate reports from the data (about one hour per report), we could potentially reduce this time by working with the accelerometer software company to generate the desired graphics for reports. This collaboration has been done successfully using these types of data in a cognitive behavioral therapy intervention for people with insomnia (Loewy, 2009). The clinical example provided in the Results section is an example of how tailoring was done for symptom management in this study. Occupational therapists have the requisite knowledge in occupational performance to tailor symptom management interventions in this way.

The small sample size of this pilot study limits our ability to generalize the findings. Our analyses were only conducted on participants with 10 week follow-up data which does not take into account seven participants. Due to the small group sizes, we were unable to conduct intent-to-treat analyses to take this factor into account. In addition, in studies such as this, the possibility of a ‘therapist’ effect exists, in which one therapist could potentially be more effective in their administration of an intervention compared to the other therapist. A larger study should include more than one therapist per intervention arm. In this pilot study, we controlled for other potential therapist effects by blinding them to the study hypotheses, and separating them from the data collection process.

Further research should be done to examine the lasting effects of this type of symptom management intervention and explore the characteristics of participants who best respond to this approach. A larger study should also be designed to disentangle effects due to therapist contact by including a control group that would receive information not related to activity pacing for an equivalent treatment time as in the other interventions. In addition, based on the feedback from the therapists who conducted the intervention, we also feel that it may be important to add another treatment session. For the tailored intervention group, barriers to activity pacing were often discussed in the second session, but there was no chance to revisit these barriers since the intervention ended at that point. A third session may be necessary to have adequate time to practice symptom management strategies once barriers are identified.

Conclusion

This study provides preliminary support for the effectiveness of an OT-delivered pacing intervention tailored to symptom and activity patterns on reducing the impact of fatigue in adults with osteoarthritis. Future research to replicate and extend the findings in larger studies is needed. Given that fatigue is an important clinical symptom in knee and hip OA, interventions such as this will be needed to address this growing public health problem.