Evidence map›Paper›PMID 41607292›Full record

Trial reportDeutsches Arzteblatt international2026

Digital Acceptance and Commitment Therapy for the Treatment of Chronic Pain: Findings of a Randomized Controlled Efficacy Trial.

Anne Etzelmüller, Antonia Barke, Marie Feiler, Matthias Guth, Elena Heber, Harald Baumeister, David Daniel Ebert

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Deutsches Arzteblatt international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Anne EtzelmüllerProfessorship in Psychology & Digital Mental Health Care, Technical University of Munich, Munich, Germany
Antonia BarkeDepartment of Clinical Psychological Intervention, Institute of Psychology, University of Duisburg-Essen, Essen, Germany
Marie FeilerGET. ON Institute for Online Health Training GmbH (HelloBetter)
Matthias GuthDepartment of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
Elena HeberGET. ON Institute for Online Health Training GmbH (HelloBetter)
Harald BaumeisterDepartment of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany
David Daniel EbertProfessorship in Psychology & Digital Mental Health Care, Technical University of Munich, Munich, Germany

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeople with chronic pain are confronted with limited access to established forms of treatment. Acceptance and commitment therapy (ACT) has been found to be an effective extension of cognitive behavioral therapy (CBT) for chronic pain. In this study, we evaluated the ACT-based online therapy program

methodsIn a randomized, controlled, and investigator-blinded trial, the program was tested against a treatment-as-usual control group (waiting list).

resultsAt 12 weeks, the patients in the intervention group exhibited significantly lower pain interference scores (d = 0.69; 95% confidence interval: [0.46; 0.92]) than those in the control group; they also had fewer depressive symptoms (d = 0.40; [0.17; 0.63]) and experienced better health-related quality of life (d = -0.23; [-0.40; -0.06). These effects were still present at 6 and 12 months.

conclusion

Indexed as

Acceptance and Commitment TherapyChronic PainPain ManagementTherapy, Computer-AssistedAdultAgedFemaleGermanyHumansMaleMental Health TeletherapyMiddle AgedPain MeasurementTreatment Outcome

Identifiers

PMID41607292
PMCPMC13193243

What OpenQuestion holds

Textmetadata
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Registered trials

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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.