Evidence map›Paper›PMID 39906324›Full record

ArticleQualitative research in medicine & healthcare2024

"But when I come home…": How patients with chronic musculoskeletal pain account for their absent pain during naturally occurring clinical consultations.

Trine C B Andersen, Olaug S Lian

Abstract read
In one paragraph

Article in Qualitative research in medicine & healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Trine C B AndersenDepartment of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
Olaug S LianDepartment of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When patients' embodied experiences cannot be conveyed to clinicians in real-time, the challenges of reaching a shared understanding between patient and clinician are enhanced. In this study, we explore how patients with chronic musculoskeletal pain manage the situation of knowing that they regularly experience pain, yet exhibit minimal signs of it during clinical consultations. Utilizing a multimethod, conversation analysis approach and an interactional perspective, this paper analyzes 10 naturally occurring consultations at a specialized rehabilitation clinic in Norway. The analysis shows that patients account for the absence of pain by referring to i) specific events, ii) pain tolerance, and iii) pain periods. Such accounts were typically triggered by null findings (i.e., the absence of findings in technological and physical tests) in the physical examination and clinicians' positive summaries of patients' bodily conditions. Patients resist clinicians' positive stance by accounting for absent pain, cautiously challenging the clinicians' epistemic stance. If clinicians do not pursue patients' accounts, this might lead to a misalignment between patient and clinician which can obstruct efforts to reach a shared understanding of the pain. These findings may have general relevance for clinical consultations where patients' symptoms are difficult to measure and validate biomedically. Understanding how patients account for absent pain can enhance clinician-patient communication and improve clinicians' understanding of patients' everyday circumstances and thereby improve the outcome of consultations.

Indexed as

absent painaccountingEmbodied experiences“no-problem”diagnosispatient-clinician communication

Identifiers

PMID39906324
PMCPMC11791474

What OpenQuestion holds

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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.