Evidence map›Paper›PMID 34634071›Full record

ArticlePloS one2021

How does individualised physiotherapy work for people with low back pain? A Bayesian Network analysis using randomised controlled trial data.

Bernard X W Liew, Jon J Ford, Marco Scutari, Andrew J Hahne

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
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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

4 authors at 3 institutions in 3 countries.

Bernard X W LiewSchool of Sport, Rehabilitation and Exercise Sciences, University of Essex, Colchester, Essex, United Kingdom.ORCID 0000-0002-7057-7548
Jon J FordDiscipline of Physiotherapy, School of Allied Health, Human Services & Sport, La Trobe University, Melbourne, Australia.
Marco ScutariIstituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland.
Andrew J HahneDiscipline of Physiotherapy, School of Allied Health, Human Services & Sport, La Trobe University, Melbourne, Australia.
La Trobe University · AUDalle Molle Institute for Artificial Intelligence Research · CHUniversity of Essex · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIndividualised physiotherapy is an effective treatment for low back pain. We sought to determine how this treatment works by using randomised controlled trial data to develop a Bayesian Network model.

methods300 randomised controlled trial participants (153 male, 147 female, mean age 44.1) with low back pain (of duration 6-26 weeks) received either individualised physiotherapy or advice. Variables with potential to explain how individualised physiotherapy works were included in a multivariate Bayesian Network model. Modelling incorporated the intervention period (0-10 weeks after study commencement-"early" changes) and the follow-up period (10-52 weeks after study commencement-"late" changes). Sequences of variables in the Bayesian Network showed the most common direct and indirect recovery pathways followed by participants with low back pain receiving individualised physiotherapy versus advice.

resultsIndividualised physiotherapy directly reduced early disability in people with low back pain. Individualised physiotherapy exerted indirect effects on pain intensity, recovery expectations, sleep, fear, anxiety, and depression via its ability to facilitate early improvement in disability. Early improvement in disability, led to an early reduction in depression both directly and via more complex pathways involving fear, recovery expectations, anxiety, and pain intensity. Individualised physiotherapy had its greatest influence on early change variables (during the intervention period).

conclusionIndividualised physiotherapy for low back pain appears to work predominately by facilitating an early reduction in disability, which in turn leads to improvements in other biopsychosocial outcomes. The current study cannot rule out that unmeasured mechanisms (such as tissue healing or reduced inflammation) may mediate the relationship between individualised physiotherapy treatment and improvement in disability. Further data-driven analyses involving a broad range of plausible biopsychosocial variables are recommended to fully understand how treatments work for people with low back pain. TRIALS REGISTRATION: ACTRN12609000834257.

Indexed as

Bayes TheoremLow Back PainPhysical Therapy ModalitiesAdultFemaleHumansMaleMiddle AgedPrecision MedicineRandomized Controlled Trials as TopicTreatment Outcome

Identifiers

PMID34634071
PMCPMC8504753
OpenAlexW3206165839

What OpenQuestion holds

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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.