Internet-delivered ACT for Chronic Pain

Overview

The overall aim of the present study is to evaluate an internet-delivered Acceptance and Commitment therapy treatment (iACT) for patients with chronic pain. More specifically, the study will evaluate if 1) iACT is effective in improving functioning and quality of life in comparison to a waitlist condition, 2) if iACT is cost-effective, 3) factors that influence treatment outcome (i.e. predictors, moderators or characteristics of treatment responders), 4) if psychological variables mediates the effects of treatment on outcome, and 5) if subgroups of patients varies in change processes (i.e. moderated mediation). The main hypothesis is that iACT will improve functioning and quality of life.

Chronic pain affects 12-30% of the population and often results in depression, disability, and reduced quality of life. Medical strategies are often ineffective or insufficient to alleviate symptoms and increase functioning. Instead, the empirical support for cognitive behavior therapy (CBT) is today well established, and such interventions are commonly seen as critically important for patients with chronic pain. However, modest effects sizes calls for further improvements. Recent developments within CBT, particularly Acceptance and Commitment Therapy (ACT), have suggested the utility of acceptance and mindfulness strategies to manage pain and distress. The body of evidence for ACT has grown rapidly during the past decade, and ACT is today listed by the American Psychological Association as a treatment for chronic pain, with strong empirical support. Internet-delivered ACT Despite the increased empirical support for ACT the availability is still very limited, and a large number of patients do not receive this treatment. In other domains, the accessibility of empirically supported treatments has increased during the past decade due to the development of methods to deliver the treatment via internet. For example, a large number of studies illustrate the utility of internet-delivered CBT for anxiety, insomnia and depression, with treatment effects similar to those obtained in studies with face-to-face treatment. Few studies have yet evaluated internet-delivered ACT (iACT) for chronic pain, but a recent pilot study from our group with participants suffering from fibromyalgia (n=41) illustrated very promising results that warrant further studies to evaluate the effects of this treatment. Moderators and mediators of treatment outcome If iACT shows to be effective, it is vital to identify for whom this treatment works. For example, it is possible that factors such as age, pain duration or depression may moderate the effects of treatment. Also, it is likely that some individuals who respond well to regular face-to-face treatment do not benefit from internet-delivered interventions. Furthermore, recent studies have shown that acceptance of pain and distress may be a more important mediator of change than e.g. pain intensity, catastrophizing or anxiety. However, no study has to our knowledge yet explored if subgroups of patients (e.g. men and women) improve via different change processes (i.e. moderated mediation). More information regarding moderators and mediators of change will make it possible to adjust and tailor interventions to meet specific individual needs, and thereby increase the effects of treatment. Recruitment Patients will be recruited through self referral. Thus, information regarding the study will be provided through newspapers and social media, as well as in direct communication with pain clinics and primary care units, including instructions regarding e.g. eligibility and how to sign up. Once patients have been found eligible and expressed interest in study participation they will be assessed by a psychologist, and when needed by a pain physician, via semi-structured interviews to confirm eligibility and to ensure that the patient meet the study criteria. Informed consent is obtained from all participants prior to the assessment. Statistical methods Evaluations of treatment effects are primarily based on intent-to-treat analyses. The statistical approach will primarily be based on linear multilevel modeling (LMM), which takes into account dependencies between repeated measures and differences between patients in pre-treatment status and treatment response (i.e. random effects modeling) and also provide means of handling missing data. More traditional methods, such as ANOVA and hierarchical regression, may also be utilized when appropriate. Analyses of change processes (mediation, moderation, moderated mediation) will follow guidelines and recommendations (e.g. cross-product of coefficients approach, bootstrapping). The main health economic outcomes will be the incremental cost-effectiveness ratio, which is a measure of the relationship between the cost of the treatment and the incremental value it provides in terms of functioning, compared to the control condition.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes