All questionnaire items will be rated on a seven-point Likert scale ranging from 1 'strongly disagree' to 7 'strongly agree.' In line with our study framework, we will examine the following four concepts: knowledge sharing, shared decision making, HCPs' innovative behavior, and patient satisfaction. To examine knowledge sharing within healthcare teams, every participant will be asked to indicate how often (daily, weekly, monthly, or less than once a month) he/she interacts with each team member to exchange procedural knowledge (
e.g., information about healthcare procedures and processes) and declarative knowledge (
e.g. information about diagnosis, symptoms, or therapies). This means of measuring knowledge sharing was adapted from Bakker
et al.[
15] and will result in a matrix that captures the intensity of knowledge sharing regarding procedural and declarative information between members of each team. We will use the nine-item Shared Decision-Making Questionnaire (SDM-Q-9) from Kriston
et al.[
19] to assess the use of shared decision making within healthcare teams. SDM is defined here as an interactive process in which patients and their HCPs share information equally in reaching an agreement on treatment. Hence, the questionnaire consists of nine items each describing one step of the SDM process. A sample item is 'My doctor helped me understand all the information.' Innovative behavior will be measured with a scale combined from two previously developed scales: the creativity scale of Zhou and George [
29] (three items,
e.g., 'I am/He/She is a good source of creative ideas') and the innovation scale developed by Scott and Bruce [
20] (two items,
e.g., 'I/He/She promote(s) and champion(s) ideas to others.'). We chose this combination of items because they represent the major stages in the individual innovative behavior process (problem identification, information searching and encoding, idea generation, and implementation) and because they are the most appropriate for the given context of healthcare teams working on uncertain tasks such as rare diseases. The innovative behavior of each HCP will be measured using a two-informant design via self-evaluation and external evaluation through patients. To explore patient satisfaction, we will use a patient satisfaction scale based on the Munich Patient Satisfaction Scale (MPSS-24), which in its original form consists of 24 items mainly addressing socio-emotional and communicative aspects of the patient-HCP relationship [
30]. For this study, we omitted six items,
e.g., 'The doctors are being interested in my problems;' additionally, we included an item to measure overall satisfaction. We chose the MPSS-24 because it focuses on the HCPs' competence. The scale will be adopted for each subgroup (doctors, physicians, healthcare givers, therapists). In addition, patients also rated their overall level of satisfaction with healthcare on a 10-point scale ranging from 1 (least satisfied) to 10 (most satisfied). In addition, we will control for several aspects to limit the influence of unobserved variance. We will control for functional diversity among healthcare teams by drawing on past research [
2,
31] that operationalizes this concept by addressing the tenure, educational background, and functional background of the team. In line with recommendations on how to measure diversity [
32], we will measure the mentioned variables using Blau's index of heterogeneity, 1- ∑p
i
2[
33]. In this formula, p represents the proportion of a team in the respective diversity category, and i is the number of different categories represented within a team. Thus, an index of 0 indicates no diversity, while a higher index score indicates that more diversity exists in the measured variable among team members. Additionally, we integrate the context of uncertainty as a second control variable, which will be measured by a three-item scale originally used by Gladys
et al.,
e.g., 'The intensity of the patients' healthcare is unpredictable' [
34]. The statistical analysis will explore the relationships between the two predictor variables (knowledge sharing and shared decision making) and both the dependent variable of patient satisfaction and the mediating effect of HCPs' innovative behavior by controlling for functional diversity within each team and environmental uncertainty. The theoretical model will be tested using multiple regression analysis and structural equation modeling. In addition to phase II, we will evaluate the qualitative data within phase III using MAXQDA in line with recommendations for qualitative research and grounded theory [
26‐
28].