Evidence map›Paper›PMID 38975026›Full record

ReviewBMJ open sport & exercise medicine2024

Target trial framework for determining the effect of changes in training load on injury risk using observational data: a methodological commentary.

Chinchin Wang, Jay S Kaufman, Russell J Steele, Ian Shrier

Abstract readReview
In one paragraph

Review in BMJ open sport & exercise medicine, 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

4 authors.

Chinchin WangDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.ORCID 0000-0002-8472-9936
Jay S KaufmanDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
Russell J SteeleDepartment of Mathematics and Statistics, McGill University, Montreal, Canada.
Ian ShrierCentre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, Canada.ORCID 0000-0001-9914-3498

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, a large focus has been placed on managing training load for injury prevention. To minimise injuries, training recommendations should be based on research that examines causal relationships between load and injury risk. While observational studies can be used to estimate causal effects, conventional methods to study the relationship between load and injury are prone to bias. The target trial framework is a valuable tool that requires researchers to emulate a hypothetical randomised trial using observational data. This framework helps to explicitly define research questions and design studies in a way that estimates causal effects. This article provides an overview of the components of the target trial framework as applied to studies on load and injury and describes various considerations that should be made in study design and analyses to minimise bias.

Indexed as

MethodologicalSporting injuriesSports & exercise medicineTraining

Identifiers

PMID38975026
PMCPMC11227826

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.