Evidence map›Paper›PMID 41523625›Full record

ArticleJournal of clinical and translational science2025

Theory of planned behavior constructs are associated with willingness to engage in clinical trial interventions for chronic low back pain: A cross-sectional survey study.

Caleb Steeby, Caroline S Zubieta, Sana Shaikh, Guohao Zhu, Jennifer Pierce

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2025. 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

5 authors.

Caleb SteebyDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Caroline S ZubietaDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Sana ShaikhDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Guohao ZhuDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Jennifer PierceDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.ORCID https://orcid.org/0000-0002-2861-0519

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/Objective: Chronic pain research studies are important for both finding new treatments and improving existing treatments for individuals with chronic pain. For clinical trials to be effective, participants need to be engaged and willing to participate in treatment groups. Our research applies the theory of planned behavior (TPB) to understand how attitudes, perceived social norms, and perceived control over intervention engagement are associated with willingness to participate in interventions for chronic low back pain (CLBP). Methods: Adult Michigan Medicine patients were identified using electronic medical records and emailed a link to an online, cross-sectional survey. Participants who self-reported CLBP, ability to read and write in English, and consented to participate were able to complete the survey ( Results: The results showed more positive attitudes, positive social norms, and higher perceived behavioral control related to specific chronic low back pain interventions are associated with greater willingness to participate after controlling for demographic and pain-related characteristics. Conclusion: The findings suggest that TPB constructs may be useful in guiding recruitment efforts for chronic pain intervention trials.

Indexed as

chronic low back painclinical trialsrecruitmentretentionTheory of planned behavior

Identifiers

PMID41523625
PMCPMC12780809

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.