Background and Objective: Contact tracing (CT) can be an effective tool to prevent transmission of communicable diseases. However, public health services may not always have sufficient human resources at their disposal to facilitate CT adequately. In the EU-project ‘CORESMA’, we investigated if and how this may be compensated by involving cases and contacts more actively and autonomously in the identification, notification, and monitoring of contacts through digital tools, from the perspective of Dutch public health professionals (PHPs). Methods: Between November 2020 and April 2022, we conducted interviews (N=17) and distributed an online questionnaire (N=637) among PHPs involved in CT for COVID-19 in the Netherlands. An inductive thematic analysis of the interviews was performed to identify barriers/facilitators influencing PHPs’ intention to involve cases and contacts in CT through digital tools. Random forest analyses of the questionnaire data were performed to prioritize the qualitatively identified barriers/facilitators to inform the future development and implementation of digital tools. Results: Interviewees were generally open towards more actively and autonomously involving cases and contacts in CT for COVID-19 through digital tools. Most questionnaire respondents had a positive intention to use digital tools for the identification (66.1%), notification (58.6%), and monitoring (55.1%) of contacts. Random forest models accurately predicted the (positive or neutral/negative) intention of 80-82% of questionnaire respondents to use digital tools for the identification, notification, and monitoring of contacts, respectively. Accelerating the CT-process, reducing PHPs’ workload, and sufficient support for cases and contacts were the top predictors of PHPs’ intention. Conclusions: Most PHPs are open towards involving cases and contacts through digital tools. Based on our Results, we created a ‘blueprint’ for the development and implementation of digital tools in CT. In a small-scale randomized pilot study, we are currently comparing different digital methods to let cases autonomously identify and notify their contacts.