Introduction to systematic literature review Systematic literature review is a fundamental step in scientific work where researchers identify and evaluate relevant literature and studies to answer their own research questions and support their work[1]. The definition and purpose of literature review is to gain a comprehensive understanding of the current state of research on a particular topic or question and to uncover possible knowledge gaps or research needs[2]. The process of literature review involves finding, compiling, and analyzing published information and studies in order to track research progress in a particular area and critically evaluate the quality and relevance of the identified literature[3]. Identifying relevant literature requires a thorough and systematic search of various sources such as scientific databases, books, journals, and online platforms[1]. Several factors must be taken into account to ensure that the selected sources are actually relevant and valid for one’s own research work. These include, but are not limited to: – The use of appropriate search terms and strategies to make the search effective and targeted – Assessing the quality and credibility of the sources, for example by checking the author’s qualifications, year of publication and citation frequency – Taking into account different perspectives and opinions in order to obtain a balanced and comprehensive picture of the state of research[3]. The critical evaluation of the literature is another important step in the process of literature review, in which researchers assess the quality, relevance, and reliability of the identified sources[2]. The aim is not only to check the methodological quality of the studies, but also to evaluate their contribution to the understanding of the research topic. Some aspects that should be considered when critically evaluating literature include: – The clarity and validity of the research question or hypothesis – The adequacy of the methods and analytical procedures – The quality and representativeness of the data – The coherence and comprehensibility of the reasoning and results – The limitations and possible bias of the studies[4]. By applying these criteria to the critical evaluation of literature, they can ensure that their own work is based on solid and reliable evidence and makes a valuable contribution to scientific research[3]. Conducting expert interviews according to Mayring Expert interviews are a valuable method for gathering detailed, qualitative data from knowledgeable sources within a specific subject area or subject area [2]. The main purpose of these interviews is to obtain specific information, opinions, and insights that can help answer specific research questions or address complex problems [4]. Conducting expert interviews using Mayring’s qualitative content analysis method ensures a systematic and structured approach to the evaluation and interpretation of the collected data, which can ultimately increase the quality and validity of a research project [3]. To conduct expert interviews effectively, researchers need to follow several important steps. This includes the planning and preparation, the conduct of the interview, the transcription of the interview and finally the analysis of the data using the method of qualitative content analysis according to Mayring [2]. Proper planning and preparation includes identifying suitable experts, developing clear research questions, and deciding on the appropriate interview format (e.g., face-to-face, phone, or online) [3]. During the interview, researchers should focus on building a relationship with the expert, asking open-ended questions, and actively listening to the expert’s answers [5]. After the interview, the researcher must transcribe the recorded conversation, which means that the audio or video recording is converted into a written document that can be analyzed more easily [6]. The analysis of expert interviews according to Mayring’s qualitative content analysis requires a systematic and structured process of coding and categorizing the textual data [7]. This method can be divided into four main steps: implementation, coding, inductive categorization, and summary of results [2]. Implementation requires splitting the textual data into manageable units, while encoding requires assigning codes to those units based on specific themes or themes [1]. Inductive category formation is about developing categories from the coded data, which can be achieved through a step-by-step process, as described in Mayring’s much-cited book [8]. Finally, the purpose of summarizing the results is to draw conclusions from the categorized data that will help answer the research question and feed into the overall results of the scientific work [1]. By following this structured approach, researchers can ensure a thorough and rigorous analysis of expert interview data and ultimately contribute to the credibility and reliability of their research findings [9]. Statistical analysis of online interviews Online interviews, also known as web-based interviews or internet interviews, are an increasingly popular method of data collection in qualitative and quantitative research. This includes conducting interviews with research participants via online platforms such as video conferencing software, chat rooms or email[10]. The main purpose of online interviews is to gather in-depth information and insights from respondents that can be used to explore complex topics, understand individual experiences, or evaluate expert opinions[3]. Online interviews allow researchers to access a wide range of participants, overcome geographical barriers, and reduce the costs associated with traditional in-person interview methods[11]. There are several advantages and disadvantages associated with online interviews. Key benefits include: – Flexibility in scheduling and conducting interviews, allowing researchers to cater to participants’ availability and time zones[11]. – Reduced costs as online interviews eliminate travel expenses and venue bookings[11]. – The ability to reach a wider range of participants, including those who may be geographically dispersed or have limited access to traditional research environments[11]. – Increased anonymity, which can lead to more honest and open responses from participants[3]. However, online interviews also have some drawbacks: – Potential problems with the technology, such as poor internet connections, software bugs, or difficulty navigating online platforms[11]. – Challenges in building rapport and trust with participants, as non-verbal cues and body language are often limited in online settings[5]. – Greater difficulties in ensuring the privacy and confidentiality of participants, especially when discussing sensitive issues[4]. When analyzing data from online interviews, researchers can use various statistical methods to identify patterns, trends, and correlations within the information collected.