Alarm bells should start ringing when a PI or head of department starts setting targets related to quantity of papers. As a lot of junior researchers' time is going to be be wasted churning out low quality papers of little scientific quality, and of no benefit to anybody other than PI or head of department.

#ResearchWaste

#researchwaste

COMET initiative newsletter out:
https://mailchi.mp/422a8e7f2f98/jan2023-6226622

Core outcome sets are an important infrastructure to reduce #ResearchWaste.

Read about research waste in #HRQL research in our most recent special section on that topic (Oct-2022):
https://link.springer.com/journal/11136/volumes-and-issues/31-10

#PrePrint of our editorial:
https://psyarxiv.com/879xp/
(w Claudia Rutherford, Sydney)

#Psychometrics

Already widely shared, but this article from the BMJ Christmas issue has a lot of content we have been discussing in our editorial board meetings:
https://www.bmj.com/content/379/bmj-2022-072883

Submissions to QLR are screened for good use of reporting guidelines.

Our #HRQL #ResearchWaste special issue touches on a number of these issues:
https://psyarxiv.com/879xp/

eg. research questions:
https://rdcu.be/c2nJv

and appropriate sample size planning:
https://rdcu.be/c2nJy

#NightshiftEditor

🔖 Do cancer researchers make their data and code available?

306 cancer studies:

16% shared data

4% shared analysis code

1% of data were FAIR (posted to a recognised repository, in a non-proprietary format, with an identifier and a license)

Cancer research transparency was this bad despite many journals having policies mandating openness.

Daniel Hamilton et al
https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-022-02644-2

#MedMastodon
#OpenScience
#ResearchIntegrity
#ResearchWaste
#doi:10.1186/s12916-022-02644-2

🔖 Statistical code in a high-impact medical journal

A journal started asking authors to submit code with their manuscripts. They then analysed the next 314 papers accepted

87% denied using code, even when publishing substantial statistical analysis

10% used code but refused to share it with the journal

For the few that provided code, none scored even moderately on basic quality criteria

Assel & Vickers
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6705117/

#MedMastodon
#OpenScience
#ResearchWaste
#doi:10.7326/M17-2863

RT @GSCollins@twitter.com

'Interesting' and flawed response (https://tinyurl.com/y4yfbvvj) to our critical letter (with @MaartenvSmeden@twitter.com & @Richard_D_Riley@twitter.com) on a poorly developed/reported covid prediction model (https://tinyurl.com/y3ua4ejx). #researchwaste

🐦🔗: https://twitter.com/GSCollins/status/1294400040602079234