Developing an open science ‘mindset’

Abstract

Background Identification of widespread biases present in reported research findings in many scientific disciplines, including psychology, such as failures to replicate and the likely extensive application of questionable research practices, has raised serious concerns over the reliability and trustworthiness of scientific research. This has led to the development of, and advocacy for, ‘open science’ practices, including data, materials, analysis, and output sharing, pre-registration of study predictions and analysis plans, and increased access to published research findings. Implementation of such practices has been enthusiastic in some quarters, but literacy in, and adoption of, these practices has lagged behind among many researchers in the scientific community. Advances In the current article I propose that researchers adopt an open science ‘mindset’, a comprehensive approach to open science predicated on researchers’ operating under the basic assumption that, wherever possible, open science practices will be a central component of all steps of their research projects. The primary, defining feature of the mindset is a commitment to open science principles in all research projects from inception to dissemination. Other features of the mindset include the assumption that all components of research projects (e.g. pre-registered hypotheses, protocols, materials, analysis plans, data, and output) will be accessible broadly; pro-active selection of open fora to disseminate research components and findings; open and transparent dissemination of reports of the research findings in advance of, and after, formal publication; and active promotion of open science practices through education, modeling, and advocacy. Conclusion The open science mindset is a ‘farm to fork’ approach to open science aimed at promoting comprehensive quality in application of open science, and widening participation in open science practices so that they become the norm in research in health psychology and behavioral medicine going forward.

Seeing oneself as a data reuser: How subjectification activates the drivers of data reuse in science

“…In the oral interviews, study participants described the process of coming to see oneself as a data reuser with a variety of constructs, which we inductively identified and then sought to bring together in one higher-order concept. For instance, researchers referred to the development of a data reuse mindset , an approach to research design that takes data reuse to be an option worth considering for any project (compare [ 52 ]). One researcher (Participant 11) reflected: “I think that for newcomers, like PhD students or postdocs, typically the first thought is like, ‘Let’s collect the data on my own.’ I think this might be something important…[instead] developing a mindset that, ‘Yeah, we could just reuse data, we don’t have to collect the data from scratch.” Another (Participant 4) admitted that, although he reuses data in his teaching, when it comes to his own research “I notice…that I am of course also in this automated mode, I collect my data and so on.” Here, drawing on a control systems metaphor, this researcher reflects on the incongruity of a mindset that embraces reuse in one context but fails to even consider it in another.…”

Changes in authoritarianism before and during the COVID-19 pandemic: Comparisons of latent means across East and West Germany, gender, age, and education

“…Other scales should be analyzed in the same manner to ensure previous and future findings are indeed reliable. Such replications are extremely important to build up a more solid knowledge base in the social sciences, as it has been stressed by the discussions following the replication crisis and the creation of the Open science Forum and Movement and finally an Open Science Mind-Set ( Hagger, 2022 ).…”

The connection of open science practices and the methodological approach of researchers

“…Although digital technologies and their use is omnipresent (Grand et al 2016), research practices only change slowly (Costa 2014;Hagger 2022). Additionally as Pearce et al (2010) explored, there is no "homogeneous form of 'scholarship' within academia" (Pearce et al 2010, p. 37).…”