Evidence map›Paper›PMID 42297361›Full record

ArticleJMIR research protocols2026

Evaluating the Effectiveness of Nonpharmacological Self-Management Interventions for Persistent Pain: Protocol for Single-Case Experimental Designs.

Nancy Sturman, Jane Nikles, Peter Worthy, Shauna Fjaagesund, Rachel A Elphinston, Nicole Andrews, Michele Sterling, Stefan Konigorski

Abstract readClinical Trial Protocol
In one paragraph

Article in JMIR research protocols, 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

8 authors.

Nancy SturmanGeneral Practice Clinical Unit, The University of Queensland, Brisbane, Australia.ORCID 0000-0002-7124-5553
Jane NiklesGeneral Practice Clinical Unit, The University of Queensland, Brisbane, Australia.ORCID 0000-0001-5356-2291
Peter WorthySchool of Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0002-9124-1330
Shauna FjaagesundGeneral Practice Clinical Unit, The University of Queensland, Brisbane, Australia.ORCID 0000-0002-5759-7173
Rachel A ElphinstonRECOVER Injury Research Centre, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0002-3704-0052
Nicole AndrewsRECOVER Injury Research Centre, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0002-7739-1738
Michele SterlingRECOVER Injury Research Centre, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0003-1772-2248
Stefan KonigorskiHasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Brandenburg, Germany.ORCID 0000-0002-9966-6819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNonpharmacological self-management interventions are often recommended for general practice patients with persistent pain-a distressing, costly, and heterogeneous condition with variable responses to treatment interventions. Single-case experimental designs ("self-experiments") evaluate intervention effectiveness at the individual level. StudyU is an open-source digital platform designed to help patients undertake these self-experiments.

objectiveThis study aims to investigate the feasibility and acceptability (for patients, practitioners, and other practice staff) of integrating digitally enabled, withdrawal/reversal self-experiments in the general practice care of patients with persistent pain.

methodsWe will recruit 50 patients from a large Australian general practice. Participants will trial a self-selected, self-management intervention (such as physical activity, mindfulness practice, or online self-guided cognitive behavioral therapy) approved by their general practitioner (GP) and use the StudyU app to rate the daily impact of their pain over the 10-week study period. The primary clinical outcome of the self-experiments is pain interference (measured using the modified Brief Pain Inventory), testing for its mean difference between usual routine and intervention conditions. Clinical reports will be generated for the patient and their GP. We will use validated measures of app usability and acceptance, pre-post measures of patient self-efficacy, quality of life, health service use, self-reported health; individual interviews informed by the Normalization Process Theory; and a nested process evaluation to examine the feasibility and acceptability for patients and practice staff of embedding these self-experiments in general practice care.

resultsThe research was funded in September 2023, funding and other agreements were completed by December 2024, patient recruitment commenced in January 2025, and publication of results is anticipated by January 2027.

conclusionsDigitally enabled self-experiments testing nonpharmacological treatment effectiveness may empower patients to self-manage persistent pain and adopt personally effective nonpharmacological interventions in partnership with their GPs and provide a model for integrating other new technologies into the general practice care of patients with other chronic conditions.

trial registrationAustralia and New Zealand Clinical Trials Registry ACTRN12624000459527; https://tinyurl.com/bdhabjd2. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/79810.

Indexed as

Chronic PainPain ManagementSelf-ManagementAustraliaFeasibility StudiesFemaleGeneral PracticeHumansPain MeasurementSingle-Case Studies as TopicTreatment Outcomegeneral practicemHealthmobile healthN-of-1 trialspainself-managementsingle-case experimental designs

Identifiers

PMID42297361
PMCPMC13315998

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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.