Evidence map›Paper›PMID 39663878›Full record

ArticleJournal of evaluation in clinical practice2025

Commentary: Without Values, Complexity is Reduced to Mathematics.

Trisha Greenhalgh

Abstract readComment
In one paragraph

Article in Journal of evaluation in clinical practice, 2025. 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

5 · Who and what money

Authors and funding

1 author.

Trisha GreenhalghNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, Oxfordshire, UK.ORCID 0000-0003-2369-8088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This commentary on Sturmberg and Mercuri's paper 'Every Problem is Embedded in a Greater Whole' [1] argues that those authors have approached complexity from a largely mathematical perspective, drawing on the work of Sumpter. Whilst such an approach allows us to challenge the simple linear causality assumed in randomised controlled trials, it is itself limited. Mathematical complexity can explain nonlinearity and network effects but it cannot explain human values. It overlooks, for example, how science itself is historically and culturally shaped and how values-driven misunderstandings and conflicts are inevitable when people with different world views come together to try to solve a problem. This paper argues that the mathematical version of complexity thinking is necessary but not sufficient in medical research, and that we need to enhance such thinking further with attention to human values.

Indexed as

Social ValuesBiomedical ResearchHumansMathematicscausationcomplexity sciencehealth policymedical ethics

Identifiers

PMID39663878
PMCPMC11635397

What OpenQuestion holds

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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.