Evidence map›Paper›PMID 39322919›Full record

ArticleBehavior research methods2024

Assessing computational reproducibility in Behavior Research Methods.

David A Ellis, John Towse, Olivia Brown, Alicia Cork, Brittany I Davidson, Sophie Devereux, Joanne Hinds, Matthew Ivory, Sophie Nightingale, Douglas A Parry and 3 more

Abstract read
In one paragraph

Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

David A EllisSchool of Management, University of Bath, Bath, UK. dae30@bath.ac.uk.ORCID 0000-0001-6172-3323
John TowseDepartment of Psychology, Lancaster University, Lancaster, UK.
Olivia BrownSchool of Management, University of Bath, Bath, UK.
Alicia CorkSchool of Management, University of Bath, Bath, UK.
Brittany I DavidsonSchool of Management, University of Bath, Bath, UK.
Sophie DevereuxDepartment of Psychology, Lancaster University, Lancaster, UK.
Joanne HindsSchool of Management, University of Bath, Bath, UK.
Matthew IvoryDepartment of Psychology, Lancaster University, Lancaster, UK.
Sophie NightingaleDepartment of Psychology, Lancaster University, Lancaster, UK.
Douglas A ParryDepartment of Information Science, Stellenbosch University, Stellenbosch, South Africa.
Lukasz PiwekSchool of Management, University of Bath, Bath, UK.
Heather ShawDepartment of Psychology, Lancaster University, Lancaster, UK.
Andrea S TowseDepartment of Psychology, Lancaster University, Lancaster, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psychological science has thrived thanks to new methods and innovative practices. Journals, including Behavior Research Methods (BRM), continue to support the dissemination and evaluation of research assets including data, software/hardware, statistical code, and databases of stimuli. However, such research assets rarely allow for computational reproducibility, meaning they are difficult to reuse. Therefore, in this preregistered report, we explore how BRM's authors and BRM structures shape the landscape of functional research assets. Our broad research questions concern: (1) How quickly methods and analytical techniques reported in BRM can be used and developed further by other scientists; (2) Whether functionality has improved following changes to BRM journal policy in support of computational reproducibility; (3) Whether we can disentangle such policy changes from changes in reproducibility over time. We randomly sampled equal numbers of papers (N = 204) published in BRM before and after the implementation of policy changes. Pairs of researchers recorded how long it took to ensure assets (data, software/hardware, statistical code, and materials) were fully operational. They also coded the completeness and reusability of the assets. While improvements were observed in all measures, only changes to completeness were altered significantly following the policy changes (d = .37). The effects varied between different types of research assets, with data sets from surveys/experiments showing the largest improvements in completeness and reusability. Perhaps more importantly, changes to policy do appear to have improved the life span of research products by reducing natural decline. We conclude with a discussion of how, in the future, research and policy might better support computational reproducibility within and beyond psychological science.

Indexed as

Behavioral ResearchHumansPeriodicals as TopicReproducibility of ResultsResearch DesignSoftwareMeta-researchOpen scienceReproducibilityResearch policyTransparency

Identifiers

PMID39322919
PMCPMC11525395

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.