Datenpaket: Qualitative focus groups interview data on active mobility and social participation in urban neighborhood environments with objectively determined high and low walkability (year: 2024; journal: Archives of Public Health)

Data for the study from Bollenbach, L., Kanning, M., & Niermann, C. 2024. Qualitative Exploration of Determinants of Active Mobility and Social Participation in Urban Neighborhoods: Individual Perceptions Over Objective Factors? Data are the transcripts of the three focus groups that were conducted, analyzed, and transcribed for this study. The provided information is sourced from the article Qualitative Exploration of Determinants of Active Mobility and Social Participation in Urban Neighborhoods: Individual Perceptions Over Objective Factors? All details are subject to the applicable availabilities and rights. The corresponding references can be found in the published article.

Study Area, and Participants The three focus group interviews are part of the research project ‘AMbit - Active Mobility’ (ambit.uni-konstanz.de/) and were conducted in June 2021. Participants were recruited as follows: First, 3000 letters with information about the project AMbit and an invite to participate in an online questionnaire were distributed in 12 neighborhoods of the city of Stuttgart, Germany. The neighborhoods were pre-selected to ensure an even allocation of participants into six high and six low walkability neighborhoods. The classification of the neighborhoods’ walkability into high and low was derived from the first version of the ‘Walkability-Index’ of the ‘Research Institute for Regional and Urban Development (ILS)’ (Fina et al., 2022). In a second step, those who completed the questionnaire had the chance to opt in to be contacted via email to participate in the focus group interview study. Optional 20 € were offered as an incentive for participation in the focus group. Stuttgart has the particular feature of being located in a valley basin, which results in the neighborhoods being located in a variety of topographies (e.g., hillside locations with slopes, flat, urban, more rural, etc.). This allowed the inclusion of many different neighborhoods with different characteristics. The final sample consisted of a total of 17 individuals (11 individuals from high-, and 6 individuals from low walkability neighborhoods) from 11 different neighborhoods. Inclusion criteria were to be at least 18 years of age, speak German, and live in one of the residential neighborhoods of Stuttgart. Study participation was voluntary and the subjects were able to withdraw at any time without stating a reason. Participants received written and oral information about the study background, aims, procedure, rights, and data protection before the focus groups. Also before the start of the focus groups, individuals gave written and oral consent to the participation in and the recording (video / audio) of the focus groups. At the time of the focus groups, the COVID-19 pandemic was still somewhat an issue and to avoid possible uneasiness of meeting face to face, the focus groups were conducted via the online tool Zoom (Zoom Video Communications, Inc., 2021). Using Zoom further facilitated the scheduling of times and dates of the focus groups. The focus groups were conducted in German language.

Procedure of the Focus Group Interviews N = 3 focus group interviews (G1, N = 6; G2, N = 6; G3, N = 5, participants) were conducted. As is common in focus group interviews, a (pre) structured interview guideline was used, which enabled a systematic collection and comparison of key factors of AM and SocPar. Furthermore, this ensured comparability and integration of the answers of the different individuals / focus groups (Loxton, 2021). The interview guideline used in this study was created by the authors of this paper in an iterative process of discussing and testing the questions and implementing feedback loops that included other researchers of the project. Also, a pilot test was run with other researchers from the institute who were not part of the present research project. To ensure a high quality of data collection with the focus groups, the moderator received training regarding the moderation of focus groups. This training included information about possible difficulties that may occur, and how to deal with them (e.g., what to do if the focus group is stuck, if the discussion gets out of hand, the inclusion of back-up questions, etc.). The focus groups were conducted by one moderator, who was supported by two research assistants who made sure that the recording ran smoothly, and helped the moderator in making sure that no one was left out, etc. The focus group interviews had the following structure: First, participants were greeted and it was made sure that any questions or technical problems (e.g., regarding the camera, sound, internet) were cleared. If everyone was ready to proceed, each focus group received a brief (4 slides) introduction to the concept of walkability by one of the helpers. This was done as it was a goal of the focus groups to discuss not only the concept of walkability, but to enable the participant to understand the concept, what it assesses, and what use cases can be derived. After walkability was introduced, participants were asked a second time whether they were ready to start the focus group. If everyone was ready, participants were again asked for approval to start the recording, and the focus group commenced. The focus groups were divided into two main sections: While the first section had a focus on AM, the second section was used to collect information about SocPar. The two sessions were divided by a break of approximately 10 minutes.

Data Collection and Data Analysis The focus groups lasted between 89 and 108 minutes (breaks not counted; G1: 1h 29 min, G2: 1h 48 min, G3:1h 43 min) and were transcribed verbatim. Processing and editing of the transcripts and the data analysis were done using MAXQDA Plus (VERBI Software, 2021). Since there was a clear and structured approach to investigate and explore barriers and facilitators of AM and SocPar of different individuals from different urban neighborhoods, the analysis was based on categories that were created from thematic analysis (categories are predetermined). Open, axial, and selective coding was applied to the transcripts to ensure systematic analysis and interpretation of the data that included the identification of patterns, issues, and relations between the different concepts and contexts: While investigating the transcripts, the memo function in MAXQDA was used to capture ideas and thoughts right in the manuscript to aid in the open, axial, and selective coding process. First, the transcribed data were compared and coded to categories that contained information regarding the research questions (open coding). Next, in an iterative process, possible connections, relations, and overlaps between the categories were investigated, to identify patterns or structures (axial coding). Last, the focus was once again on identifying and creating the main categories that contain the central aspects and key factors regarding the research questions (selective coding). Once all categories were created, definitions and concomitant exemplary quotes for each category were added to ensure transparency and reproducibility of the coding process (Kuckartz, 2016). The data analysis process was conducted by two researchers (LB, MK), who read and analyzed the interviews independently and discussed the findings (method of consent coding; Richards, & Hemphill, 2018). If necessary, a third researcher (CN) was included in this process for consultation, and to resolve any non-concordance. For better international understanding and consistency in terminology, all quotes that are important for this paper were translated from German to English using DeepL Pro (https://www.deepl.com) and then verified for accuracy by the authors.

Code Categories Multiple code categories were created to address the research objectives based on the focus group interviews’ transcripts. The first section focused on AM, and the second on SocPar. Based on social-ecological models, the categories were allocated to dimensions: One dimension consisted of factors and characteristics regarding the environment, with the categories 1) ‘Points-of-interest, infrastructure’, 2) ‘Safety, communication, community’, and 3) ‘Topography, physical compositions, weather, aesthetics’. A second dimension consisted of factors and characteristics regarding the individual, with the category 4) ‘Personal / individual attitudes, influences, evaluations’. This was further complemented with particularities concerning AM and SocPar. In addition, two subcategories were added to categories 1-3, with the first subcategory consisting of reported barriers-, and the second consisting of proposed solutions and improvements in the context of the corresponding main category. This resulted in the categories depicted in Table 1. Note: A detailed description of all categories can be found in Appendix 1 for AM, and Appendix 2 for SocPar, respectively.