Evidence map›Paper›PMID 29665780›Full record

ReviewBMC medical research methodology2018

Writing a discussion section: how to integrate substantive and statistical expertise.

Michael Höfler, John Venz, Sebastian Trautmann, Robert Miller

Abstract readReview
In one paragraph

Review in BMC medical research methodology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. The Principles of Biomedical Scientific Writing: Discussion.International journal of endocrinology and metabolism · 2019
    Review
  5. 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

4 authors.

Michael HöflerInstitute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany. michael.hoefler@tu-dresden.de.ORCID 0000-0001-7646-8265
John VenzInstitute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Sebastian TrautmannInstitute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Robert MillerFaculty of Psychology, Technische Universität Dresden, Dresden, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhen discussing results medical research articles often tear substantive and statistical (methodical) contributions apart, just as if both were independent. Consequently, reasoning on bias tends to be vague, unclear and superficial. This can lead to over-generalized, too narrow and misleading conclusions, especially for causal research questions. MAIN BODY: To get the best possible conclusion, substantive and statistical expertise have to be integrated on the basis of reasonable assumptions. While statistics should raise questions on the mechanisms that have presumably created the data, substantive knowledge should answer them. Building on the related principle of Bayesian thinking, we make seven specific and four general proposals on writing a discussion section.

conclusionMisinterpretation could be reduced if authors explicitly discussed what can be concluded under which assumptions. Informed on the resulting conditional conclusions other researchers may, according to their knowledge and beliefs, follow a particular conclusion or, based on other conditions, arrive at another one. This could foster both an improved debate and a better understanding of the mechanisms behind the data and should therefore enable researchers to better address bias in future studies.

Indexed as

Bayes TheoremBiasBiomedical ResearchHumansResearch PersonnelResearch ReportWritingAssumptionsBayesBiasCausalityConclusionDiscussionMechanismStatisticianSubstantive researcherWriting

Identifiers

PMID29665780
PMCPMC5905138

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.