The Effectiveness of Operant Learning Versus Energy Conservation Activity Pacing Treatments in Fibromyalgia

Overview

Activity pacing (AP) is a commonly used treatment for people with chronic pain. Many people with pain try to continue their daily activities at the same level as they were able to manage before they had pain. This way of coping causes increases in their pain; they become discouraged and give up on their activities. AP treatments involve helping them regulate their activity level so that they can achieve important life goals. Although AP is widely used, its effectiveness is still unproven. There are two key approaches: The operant learning (OL) approach uses quotas related to time or goals the person sets. The energy conservation (EC) approach focuses on balancing patient energy expenditure. Both of these treatments have often been used with people with Fibromyalgia Syndrome (FMS), a common pain condition. We will examine the effects of these treatments on pain, fatigue, quality of life, physical functioning and mental well-being. We will also investigate whether other factors influence treatment effectiveness (e.g., a person's readiness to change, pain intensity level). 120 FMS patients will be randomly assigned to receive OL, EC, Delayed-OL or Delayed-EC. Data will be collected at baseline, at the end of treatment and at 3, 6 and 12 month follow-ups. FMS patients will be recruited consecutively from Rheumatologists at St. Joseph's Health Care London. OL and EC treatment manuals will be developed by experts in the field and both interventions will be given by two occupational therapists over a 3 month period as "stand-alone" interventions (10 sessions of 120 min). All sessions will be recorded in order to assess intervention fidelity. This study will be the first to base AP interventions on a clearly delineated theoretical framework. It will clarify whether AP strategies benefit individuals with FMS and whether either of these two approaches is more effective. Our results will help to direct clinical resources and funding toward the most beneficial interventions.

Rational: Activity pacing (AP) can be defined as "the regulation of activity level and/or rate in the service of a goal or goals" (Nielson, Jensen et Vlaeyen, 2012). This general coping strategy is widely used in chronic pain (CP) management both as a stand-alone treatment and as a component of multimodal treatment programs. However its potential benefits remain unproven; in fact, there is evidence that in some contexts, pacing may be a maladaptive coping response (Gill et Brown, 2009). Thus, more knowledge regarding the effects of this coping strategy is needed in order to determine if (and for whom) it is an effective pain management treatment. Two models of AP are currently in widespread use. The Operant Learning (OL) approach uses positively reinforced activity quotas that are time and/or goal contingent, rather than pain-contingent, and these are gradually increased using "activity-rest" cycling (Fordyce, 1976). In contrast, the Energy Conservation (EC) approach focuses on patient energy expenditure, and seeks to achieve a balance between accomplishing important day-to-day activities and resting in order to reduce or avoid pain and fatigue (Hammond, 2004). Despite the ubiquitous use of these two forms of AP in clinical settings, little is known about either their individual or relative efficacy. Similarly, each approach involves multiple elements, and it is unclear which of these elements might be responsible for putative treatment effects. Two recent studies (Murphy et al., 2011 ; van Koulil et al., 2010) have provided some data regarding AP, but described somewhat contradictory results and did not provide clear theoretical bases for their interventions. Future research concerning the effectiveness of AP should: (a) define the contents of interventions based on theory; (b) avoid confounding AP with non-AP treatment elements; (c) examine the relative efficacy of these two theoretically different AP methodologies; and (d) identify the clinical populations that are most likely to benefit from AP treatment. Fibromyalgia Syndrome (FMS) is a condition with a general population prevalence of approximately 3-5% and is estimated to have one of the highest psychosocial and financial impacts of all rheumatic diseases and chronic pain conditions. The predominant symptoms of FMS are chronic widespread pain and fatigue. Although there are no disease-modifying treatments available for this condition, Cognitive Behavioural and Multidisciplinary Treatment Programs, usually including some form of AP, are evidence-based and widely recommended. Because FMS is common, causes considerable suffering (personal, social and economic) and has been the frequent target of AP methods, it is particularly important to understand the efficacy of AP - both alone and as a part of multimodal treatment packages. However, before this step is taken, it is important to assess the efficacy of AP as a stand-alone treatment. Research objectives: * To examine the effectiveness and relative benefits of OL and EC interventions on pain and fatigue and to assess their impact on physical functioning, mental well-being and quality of life in patients with FMS. * To investigate factors that are hypothesized to influence AP treatment effectiveness, including use of general coping strategies and beliefs/attitudes toward pain. * To Examine the AP treatment with regard to the participant global impression of change after the group sessions and at follow-ups. Methodology: The present study has been designed according to the CONSORT (Consolidated Standards of Reporting Trials) statement. A total of 120 participants with FMS will be randomly assigned to one of four intervention groups (OL, EC, delayed-OL and delayed-EC). The delayed groups will receive the AP intervention 3 months later and will serve as a Usual Care control group. All groups will continue to receive any concomitant interventions that they are receiving (pharmacological and non-pharmacological) at the time of enrollment. Data will be collected at pretreatment assessment (T0,) at the end of the intervention group (3 months, T1), at 3 months (T2) and 6 months (T3) booster sessions and at 12 months (T4) follow-up. In order to obtain a heterogeneous sample that will be more representative of the regional FMS population, participants will be recruited from different sources including health professionals from primary and tertiary care settings, FMS associations and support groups and direct solicitation from the community (e.g., newspapers, posters). Patients will be invited to call the AP research phone line if they are interested in participating in the study. If they accept and provide their written informed consent, they will be randomly assigned to one of the two study conditions (delayed or not delayed). Men (only around 5% of FMS population) will be randomized separately in order to insure that similar proportions of each sex are included in each of our four study groups. All participants will be blinded as to the nature of the research questions involved in this study. Sample size calculation: This sample size was determined based on a standard effect size calculation (Machin et Fayers, 2010) using effect size estimates obtained from previous, related, studies of interventions for FMS (Murphy et al., 2011 ; van Koulil et al., 2010) and takes into account an attrition rate of 20%. This calculation resulted in an estimate of 60 participants per group (OL, EC). Specifically, we based our estimate on data obtained from FMS patients referred to the Rheumatology Day Program at St. Joseph Health Care as they are representative of the population from which the sample will be recruited for our study. FMS patients' referred to the program reported an average pain of 7.11 out of 10 on a numerical rating scale within each subject group was normally distributed with a standard deviation of 1.41. We are planning to use two primary outcome measures (0-10 numerical rating scale for each of pain and fatigue). Because between-group differences in non-pharmacological trials are small, we chose a between-group difference of 1 on these NRS measures as our estimate. If the true difference in the OL and EC means is 1, we will need a total of 51 participants' per group to be able to show that one treatment is more effective than the other with power (1-β) 0.9. The Type I error probability associated with this test α/2 (corrected as we have 2 primary outcomes: pain and fatigue) is 0.025. We estimated that we will require 20.4 additional participants (20%) to adjust for study attrition, resulting in a total of 120 participants. Interventions: OL and EC treatment manuals will be developed by two experienced clinical psychologists and two occupational therapists. They will be based on the theoretical underpinnings of each of the two principal AP interventions. An expert panel of 6 select researchers with extensive experience in this particular field will revise and rate the manual contents accordingly to Nielson et al. (Nielson, Jensen et Vlaeyen, 2012)review paper about activity pacing concepts in chronic pain. This will ensure that the contents of the treatment manuals are consistent with the conceptual models underlying both the OL and EC interventions. These treatments will be applied as 3 month "stand-alone" interventions that will include 10 sessions, each of 120 min duration (1-weekly for 2 months, and 2 every two weeks for 1 month). Booster sessions will also be conducted at 3, 6 and 12 months follow-up. Both interventions will be administered by two well-trained occupational therapists (OTs), who have extensive clinical experience in treating individuals with FMS. All treatment sessions will be audio-recorded. Thirty percent of all recorded sessions will then be randomly selected and reviewed by two blinded assessors (using a criterion for inter-rater reliability, Cohen's κ, of \> .80) in order to evaluate: 1) therapeutic alliance (7-points Likert scale), and 2) treatment fidelity (therapist adherence to the treatment manual) (7-point Likert scale). Questionnaires and assessment tools: Questionnaires and measurement tools has been chosen according to IMMPACT (Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials) and OMERACT (Outcome Measures in Rheumatology Clinical Trials) recommendations. Socio-demographic data and information about concurrent treatments will be collected only at baseline while participant's global impression of change will only be measured at follow-ups. All others questionnaires will be completed at baseline (T0), after the intervention (T1) and at booster sessions (T2, T3, T4). Delayed intervention groups will complete T0 once and at 3 months baseline before starting the intervention. Statistical analysis: A split-plot factorial design will serve as the basis for this study. A first set of analyses (t-tests, chi-squares) will be performed to evaluate possible baseline differences between OL, EC and the Delayed groups on the outcome and/or demographic measures. Depending on the results of these analyses, a repeated measures (T1,T2, T3, T4) ANOVA (or ANCOVA if there are significant between-group differences on baseline measures, e.g. baseline pain) will be conducted to compare the three study groups on the primary outcome measures. Similarly, repeated measures ANOVAs (and/or ANCOVAs) will be used to evaluate the secondary and tertiary outcomes measures. Post-hoc multiple comparisons will then be conducted to evaluate simple and simple-simple effects, correcting for the number of comparisons. Secondary objectives will be evaluated using multiple regression analyses examining the relationship between treatment change and each of the proposed predictor variables. Contributions: The proposed study will be an important first step in both evaluating the efficacy of the two commonly used AP strategies and understanding their relationship with other variables that influence treatment outcome. This study will also be the first to base AP interventions on a clearly delineated theoretical framework. Assuming that one or both forms of AP show a beneficial effect on treatment outcomes, subsequent research will be able to further refine the contents of AP interventions. The results will also clarify the appropriateness of using AP strategies for individuals with FMS and will provide information as to which (or both) of the two approaches provide clinical benefit. Finally, this research also has important implications for health care resource allocation and expenditures. From the perspective of evidence-based practice, clinical resources and funding can be directed toward what are identified as the most beneficial interventions.