Implementing Findable, Accessible, Interoperable, Reusable (FAIR) Principles in Child and Adolescent Mental Health...

Area of Science:

• Health Research
• Data Science
• Mental Health

Background:

• The FAIR data principles (Findable, Accessible, Interoperable, Reusable) aim to enhance data reusability.
• Implementing FAIR principles presents significant challenges due to various barriers.

Purpose of the Study:

• Systematically identify barriers to implementing FAIR principles in child and adolescent mental health research.
• Define the most challenging barriers and propose actionable recommendations.

Main Methods:

• Utilized data manager evaluations, expert interviews, and a rapid literature review to identify barriers.
• Categorized barriers by type, affected FAIR principle, origin, and specificity to mental health.
• Employed the Delphi method for barrier impact assessment and ranking.

Main Results:

• Identified 45 unique barriers, with 'external' type (e.g., organizational policy) and 'tooling' being most common.
• Barriers affected all FAIR principles, and most were not specific to mental health research.
• Consensus on barrier ranking was achieved, highlighting the need for data stewards, guides, and funding.

Conclusions:

• Systematic identification of barriers and recommendations can improve FAIR data implementation awareness.
• Researchers and funders must recognize the need for expertise, tooling, and investment for FAIR data.