Evidence map›Paper›PMID 42422060›Full record

ArticleJournal of motor learning and development2025

Taking steps toward open data in motor control, learning, and development.

Keith R Lohse

Abstract read
In one paragraph

Article in Journal of motor learning and development, 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

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

1 author.

Keith R LohseProgram in Physical Therapy, Washington University School of Medicine, Saint Louis, MO, USA.

Funding

Building a data science workforce to improve the reproducibility of rehabilitation researchR25HD105583 · NICHD · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David Nelson Kennedy, Sook-Lei Liew · 2022 to 2026
$812k
NICHD NIH HHS R25 HD105583
6 · The paper itself

Abstract

Data sharing is increasingly becoming a scientific norm due to its potential to accelerate discovery and reduce research waste. Despite the significant investment in biomedical research, much of it fails to produce actionable knowledge, with timelines to impactful outcomes often exceeding 15 years when successful. Limited access to existing data contributes to this inefficiency, leading to redundant data collection and poorly designed studies. Governments are implementing policies that encourage data sharing for federally funded research, but all research stands to benefit from data sharing regardless of the funding source. Although data sharing practices have improved in some fields, their adoption remains minimal in areas like motor control, learning, and development (MCLD). This editorial discusses the advantages of data sharing, including accelerating discovery, enhancing collaboration, and improving transparency and reproducibility. The editorial acknowledges concerns related to privacy, recognition for data sharing, and the risk of data misuse or misinterpretation, discussing productive ways to ameliorate these concerns.

Indexed as

Data SharingOpen DataReproducibility

Identifiers

PMID42422060
PMCPMC13344195

What OpenQuestion holds

Textmetadata
LicenceTDM
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.