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Journal Article

Citation

Kirtley OJ, Janssens JJ, Kaurin A. Crisis 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, International Association for Suicide Prevention, Publisher Hogrefe Publishing)

DOI

10.1027/0227-5910/a000859

PMID

35915973

Abstract

Implementing Open Science Practices Into Ongoing and Concluded Studies
Electronic Supplementary Material

Suicide claims more than 700,000 lives globally every year (World Health Organization, 2021) and affects approximately 135 people per individual who dies by suicide (Cerel et al., 2019). Those affected by suicide - from people with lived experience to policy-makers - are depending on researchers to provide reliable evidence: a prerequisite of effective prevention and treatment. However, not all evidence is equal; studies with small sample sizes may produce spurious results (Carpenter & Law, 2021) and measures may be unable to capture suicidal thoughts and behaviors in a reliable and valid way (Millner et al., 2020), which can compromise the generalizability of findings.

The quality of the research methods used to generate evidence is the key to determining the credibility we afford it (Vazire et al., 2021). Although we have undoubtedly made progress over the years in our understanding of suicide, recent research does not appear to have built upon previous work to the extent it could have done - mostly because of major methodological limitations in suicide research and publication bias limiting insights into the full range of existing findings (Franklin et al., 2017; Pirkis, 2020).

To build on what has come before us, we need to be able to see what we are building on. Beyond unpublished null-findings, there are many other reasons the evidence base is incomplete. Journal word limits may preclude sufficiently detailed descriptions of methods and statistical analysis to enable replication, abandoned research questions and analysis plans may not be reported as they make for a messier story, or after a long period of data collection, the original hypotheses and analysis plans may have become hazy, or could have changed based on knowledge of the data...


Language: en

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