Altmetric coverage of health research in Ireland 2017-2023: a protocol for a cross-sectional analysis [version 2; peer review: 2 approved, 1 approved with reservations, 1 not approved]

<strong>Background:</strong> Scientific publications have been growing exponentially, contributing to an oversaturated information environment. Quantifying a research output's impact and reach cannot be solely measured by traditional metrics like citation counts as these have a lag time and are largely focused on an academic audience. There is increasing recognition to consider 'alternative metrics' or altmetrics to measure more immediate and broader impacts of research. Better understanding of altmetrics can help researchers better navigate evolving information environments and changing appetites for different types of research. <strong>Objectives:</strong> Our study aims to: 1) analyse the amount and medium of Altmetric coverage of health research produced by Irish organisations (2017 - 2023), identifying changes over time and 2) investigate differences in the amount of coverage between clinical areas (e.g., nutrition vs. neurology). <strong>Methods:</strong> Using Altmetric institutional access, we will gather data on research outputs published 1 January 2017 through 31 December 2023 from active Irish organisations with Research Organisation Registry (ROR) IDs. Outputs will be deduplicated and stratified by their Australian and New Zealand Standard Research Classification relating to ≥1 field of health research: Biological Sciences, Biomedical and Clinical Sciences, Chemical Sciences, Health Sciences, and Psychology. We will clean data using R and perform descriptive analyses, establishing counts and frequencies of coverage by clinical area and medium (e.g., traditional news, X, etc.); data will be plotted on a yearly and quarterly basis where appropriate. <strong>Results and conclusions:</strong> Improved understanding of one's information environment can help researchers better navigate their local landscapes and identify pathways for more effective communication to the public. All R code will be made available open-source, allowing researchers to adapt it to evaluate their local landscapes.