Evidence map›Paper›PMID 30323649›Full record

ReviewJournal of pain research2018

Current status of acceptance and commitment therapy for chronic pain: a narrative review.

Albert Feliu-Soler, Francisco Montesinos, Olga Gutiérrez-Martínez, Whitney Scott, Lance M McCracken, Juan V Luciano

3 registry-linked trialsAbstract readReview
In one paragraph

Review in Journal of pain research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 87 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05498454 naunknown statusnot on this mapstarted 2022, after this paper: background citation

Differential Contributions of Online Stress and Pain-explicit Mindfulness Treatment Groups to Processes, Patient Experience and Outcomes in Chronic Pain: A Randomized Controlled Trial and Qualitative Analysis

TypeinterventionalSponsorGovernment of JerseyRan2022 to 2023Enrolled96ConditionsChronic PainArmsBreathworks Mindfulness (Health or Stress Arm)
NCT06179264 nacompletednot on this mapstarted 2024, after this paper: background citation

Preliminary Evaluation of an Online Acceptance and Commitment Training Program for Individuals with Chronic Health Conditions

TypeinterventionalSponsorUtah State UniversityRan2024 to 2024Enrolled101ConditionsStress, Psychological, Depression, Well-Being, PsychologicalArmsACT Guide for Chronic Health Conditions
NCT07270588 narecruitingnot on this mapstarted 2025, after this paper: background citation

MOBACT: An Internet-Based Guided Self-Help Intervention Based on Acceptance and Commitment Therapy for Chronic Pain

TypeinterventionalSponsorCatholic University of the Sacred HeartRan2025 to 2027Enrolled140ConditionsChronic PainArmsInternet-based intervention
3 · Its place in the literature

Who cites it

87 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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27 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Albert Feliu-SolerTeaching, Research and Innovation Unit, Parc Sanitari Sant Joan de Déu, St. Boi de Llobregat, Spain, jvluciano@pssjd.org.
Francisco MontesinosDepartment of Psychology, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid, Spain.
Olga Gutiérrez-MartínezFundación Biomédica Galicia Sur, Vigo, Spain.
Whitney ScottDepartment of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Lance M McCrackenDepartment of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Juan V LucianoTeaching, Research and Innovation Unit, Parc Sanitari Sant Joan de Déu, St. Boi de Llobregat, Spain, jvluciano@pssjd.org.

Funding

Department of Health PDF-2015-08-059
6 · The paper itself

Abstract

It is well known that chronic pain is prevalent, complex to manage, and associated with high costs, in health care and society in general. Thanks to advances in new forms of cognitive behavioral therapy (known as third-wave CBT), currently clinicians and researchers have an empirically validated psychological treatment with increasing research support for the treatment of chronic pain. This treatment is called acceptance and commitment therapy (ACT). The main aim of this paper is to provide a narrative review that summarizes and integrates the current state of knowledge of ACT in the management of chronic pain as well as discuss current challenges and opportunities for progress. Based on the psychological flexibility model, ACT extends previous forms of CBT and integrates many CBT-related variables into six core therapeutic processes. ACT is a process-based therapy that fosters openness, awareness, and engagement through a wide range of methods, including exposure-based and experiential methods, metaphors, and values clarification. To our knowledge, there are three published systematic reviews and meta-analyses that support the effectiveness of ACT for chronic pain and many studies focused on specific processes derived from the psychological flexibility model. There is also promising support for the cost-effectiveness of ACT; however, the current evidence is still insufficient to establish firm conclusions about cost-effectiveness and the most efficient means of delivery. Additional well-designed economic evaluations are needed. Other research aims include delineating the neurobiological underpinnings of ACT, refining available outcome and process measures or develop new ones for ACT trials, and meeting the challenge of wide dissemination and implementation in real-world clinical practice.

Indexed as

acceptance and commitment therapyassessmentchronic painclinical evidencecost-effectivenessreview

Identifiers

PMID30323649
PMCPMC6174685

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.