Evidence map›Paper›PMID 37878189›Full record

ArticleSports medicine - open2023

Developing Decision-Making Expertise in Professional Sports Staff: What We Can Learn from the Good Judgement Project.

P J Wilson, John Kiely

Abstract read
In one paragraph

Article in Sports medicine - open, 2023. 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. Article
  3. Article
  4. Article
  5. Review
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

2 authors.

P J WilsonSetanta College, Limerick, Ireland.
John KielyDepartment of PE and Sports Sciences, University of Limerick, Limerick, V94 T9PX, Ireland. john.kiely@ul.ie.ORCID http://orcid.org/0000-0002-8336-2351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Success within performance sports is heavily dependent upon the quality of the decisions taken by educated and experienced staff. Multi-disciplinary teams (MDTs) typically collate voluminous data, and staff typically undergo extensive and rigorous technical and domain-specific training. Although sports professionals operate in sometimes volatile, uncertain, complex and ambiguous decision-making environments, a common assumption seems to be that education and experience will automatically lead to enhanced and effective decision-making capabilities. Accordingly, there are few formal curriculums, in coaching or sports science contexts, focussed on translating the extensive research on judgement and decision-making expertise to professional sports staff. This article aims to draw on key research findings to offer insights and practical recommendations to support staff working within professional performance contexts. Through this distillation, we hope to enhance understanding of the factors underpinning effective decision-making in dynamic, high-stakes professional sporting environments. Broadly, the conclusions of this research demonstrate that decision-making efficacy is enhanced through application of three specific strategies: (i) Design of more engaging professional cultures harnessing the power of collectives encouraging diverse opinions and perspectives, and fostering and promoting collaborative teamwork, (ii) education specifically targeting debiasing training, designed to counter the most common cognitive pitfalls and biases and, (iii) the implementation of evaluation strategies integrating rigorous testing and real-time feedback.

Indexed as

Decision-makingExperienceExpertiseForecastingIntuitionJudgementProfessional sportUncertainty

Identifiers

PMID37878189
PMCPMC10600061

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.