Background Achieving the UN Sustainable Development Goal 3.4, requires complex evidence-based interventions to be implemented sustainably in local settings. However, effective interventions are often not fully implemented, and some not at all, due to factors that could have been identified during process evaluations. Process evaluations can help to design interventions, optimise implementation, and inform sustainability and scale but are also time and resource intensive. Thus, most process evaluations are commonly performed at or near study end, and findings are not rapidly fed back to end-users. Computational linguistics could be a potential solution to enhance the process evaluation in a timely and valid manner. Computational linguistics uses advanced text mining and machine learning to discover linguistic patterns in natural language and link these patterns to process evaluation domains such as implementation measures of fidelity, acceptability, and appropriateness. Aim This study aims to use e