From March through April 2019, semi-structured interviews with PHPs were conducted in Dutch by one male interviewer (YBH). Interviews were held at interviewees’ respective PHS, and lasted approximately 1 h. We developed an interview guide based on the ‘innovation decision-process’ model from Rogers’ ‘diffusion of innovations’ theory [15]. Following this model, the intention to adopt RDD for CT is assumed to be influenced by 1) prior conditions, such as existing CT-practices, 2) user characteristics, such as PHPs’ age and work experience, 3) anticipated attributes (characteristics) of RDD, such as its relative advantage, compatibility, complexity, observability, and trialability, and 4) communication channels through which the innovation (RDD) is communicated to PHPs. For the purposes of this study, we focused on topics 1 through 3.

Interviews consisted of four parts. First, exploratory questions regarding PHPs’ experiences with CT were asked, focusing on their perceptions of current CT practices. Second, since at the time of the interviews most PHPs were unfamiliar with RDD, we introduced RDD to interviewees using a PowerPoint presentation designed for this purpose. The presentation consisted of a step-by-step walkthrough of the RDD process, based on Fig. Fig.1.1. A standardised script for the explanation of RDD was used to ensure all interviewees received the same information (see Additional file 1). Third, the potential application of RDD for CT was discussed with interviewees in the context of three hypothetical scenarios. The use of scenarios is an effective method to elicit perceptions and attitudes towards certain actions in a real-life context [16]. To develop realistic and relatable scenarios, we developed these in collaboration with PHPs employed at the Dutch National Coordination Centre for Communicable Disease Control (LCI), which is part of the National Institute for Public Health and the Environment in the Netherlands. Based on their input, the scenarios reflected situations in CT that are relatively common in the Netherlands and are perceived to be of sufficient public health significance, in the sense that PHPs consider CT to be an appropriate intervention. In addition, in order to obtain insights into the wider applicability of RDD for CT, the scenarios differed in terms of the particular diseases at hand, with different epidemiological characteristics (e.g. transmission routes, incubation period, etc.) and respective guidelines for CT, the index case’s background (such as work and living situation), and the number and types (in terms of their risk) of contact persons potentially involved (for a detailed description of the scenarios, see Additional file 2):

Scenario 1, ‘Scabies’: A student living in a student housing complex, who was diagnosed with scabies after having had experienced symptoms for approximately 3 months.

Scenario 2, ‘Shigella’: A middle-aged individual who was diagnosed with shigella upon returning to his home country from an organised group holiday with friends.

Scenario 3, ‘Mumps’: A student with a side-job as a baby-sitter, who was diagnosed with mumps.

For each scenario, interviewees were asked whether and how they would consider applying RDD for CT and why (not), and what they considered advantages and challenges of this approach. Thereafter, interviewees were asked to rank the scenarios in terms of their suitability for applying RDD, and to explain their ranking. Fourth, the potential application of RDD for CT in interviewees’ ‘day-to-day practice’ was discussed.

The interview guide and the materials used during the interviews (PowerPoint introduction to RDD and scenarios) were extensively pilot tested among a small sample of PHPs employed at the LCI.

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