Access High-Quality Data to Advance Your Research

Collecting data on mindfulness-based interventions requires substantial time, funding, infrastructure, and participant access. Many talented researchers have the expertise and ideas to advance the field but lack immediate access to such data.

The Mindfulness Consortium bridges that gap. We connect ambitious researchers who have methodological expertise with existing datasets contributed by investigators across the world. This way, you gain access to opportunities that would otherwise require years of recruitment, coordination, and funding to establish independently.

Datasets include trials of mindfulness-based interventions using various psychological, neural, or other biological measures across diverse populations. This enables you to, for example:

  • Identify for whom mindfulness-based interventions work best (e.g., latent profile analysis or machine learning approaches)
  • Investigate mechanisms of change (e.g., mediation models, structural equation modelling)
  • Analyse secondary outcomes or longer-term follow-up data that were not central to the original publications
  • Combine and harmonise similar datasets to address research questions that require larger samples (e.g., approaches from precision medicine)
  • Apply network analysis to, e.g., examine how relationships between psychological or biological variables change during the intervention

Data access is determined by the dataset owner, and projects proceed only with mutual consent and clearly defined authorship expectations.

For early-career researchers, the Mindfulness Consortium offers the opportunity to publish papers with advanced data analyses without waiting years to build an independent dataset. For established researchers, it provides a way to expand methodological scope, initiate new collaborations, or sustain productivity between grants.

Datasets shared with The Mindfulness Consortium are searchable:

Step 1: Use the search bar to enter key terms related to your research question (Boolean operators may be used to refine results).

 

Step 2: Optimise your search using structured filters, including:

        • Data availability status
        • Publication year
        • Study type
        • Population characteristics
        • Intervention characteristics
        • Construct and measure types

Step 3: Once you have identified a promising dataset, review its availability status to determine whether it is openly accessible or requires permission and collaboration.

 

Step 4: Initiate contact! Each dataset includes contact information for the primary investigator or designated representative. All collaboration discussions take place directly between researchers.

Database

Ready to search? Access the Mindfulness Consortium Database here:

What's Next?

Successful collaboration depends on transparency and clear communication. Before beginning a project, we strongly recommend discussing:

Seamless and efficient research partnerships begin with clear contribution agreements. We recommend aligning authorship with APA Ethics Code Standard 8.12 (Publication Credit) and using the Contributor Role Taxonomy (CRediT) to define roles transparently and strategically.

Robust data stewardship strengthens both scientific integrity and long-term impact. APA’s data sharing guidance provides a framework for secure, transparent, and reproducible research practices.

Pre-specifying analytic strategies enhances rigor and credibility. We encourage teams to document analysis plans and follow APA’s Transparency and Openness Promotion (TOP) Guidelines to support cumulative science.

High-impact projects require coordinated execution. Establishing shared timelines, manuscript plans, and communication norms early ensures efficient progress and sustained collaboration. The APA’s Monitor on Psychology article on cooperation and communication provides practical guidance for structuring effective research partnerships.

All collaborative projects must meet applicable ethical and institutional standards. APA Ethics Code Standard 8.14 (Sharing Research Data for Verification) outlines responsible practices that protect participants while advancing scientific discovery.