Evidence map›Paper›PMID 16937239›Full record

ArticleMedicine, health care, and philosophy2006

The causation of disease - the practical and ethical consequences of competing explanations.

Ulla Räisänen, Marie-Jet Bekkers, Paula Boddington, Srikant Sarangi, Angus Clarke

Abstract read
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In one paragraph

Article in Medicine, health care, and philosophy, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Complex causation and the virtue of pluralism.Medicine, health care, and philosophy · 2006
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Ulla RäisänenHealth Communication Research Centre, Cardiff University, Cardiff, Wales, UK.
Marie-Jet Bekkers
Paula Boddington
Srikant Sarangi
Angus Clarke

Funding

Wellcome Trust
6 · The paper itself

Abstract

The prevention, treatment and management of disease are closely linked to how the causes of a particular disease are explained. For multi-factorial conditions, the causal explanations are inevitably complex and competing models may exist to explain the same condition. Selecting one particular causal explanation over another will carry practical and ethical consequences that are acutely relevant for health policy. In this paper our focus is two-fold; (i) the different models of causal explanation that are put forward within current scientific literature for the high and rising prevalence of the common complex conditions of coronary artery disease (CAD) and type 2 diabetes mellitus (T2D); and (ii) how these explanations are taken up (or not) within national health policy guidelines. We examine the causal explanations for these two conditions through a systematic database search of current scientific literature. By identifying different causal explanations we propose a three-tier taxonomy of the most prominent models of explanations: (i) evolutionary, (ii) lifecourse, and (iii) lifestyle and environment. We elaborate this taxonomy with a micro-level thematic analysis to illustrate how some explanations are semantically and rhetorically foregrounded over others. We then investigate the uptake of the scientific causal explanations in health policy documents with regard to the prevention and management recommendations of current National Service Frameworks for CAD and T2D. Our findings indicate a lack of congruence between the complexity and frequent overlap of causal explanations evident in the scientific literature and the predominant focus on lifestyle recommendations found in the mainstream health policy documents.

Indexed as

BioethicsCausalityModels, TheoreticalPhilosophy, MedicalCoronary Artery DiseaseDiabetes Mellitus, Type 2EnvironmentGenetic Predisposition to DiseaseHealth BehaviorHumansLife Style

Identifiers

What OpenQuestion holds

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Read underepoch 390

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.