Technische Universität Dresden

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Research data repository of Dresden University of Technology.

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Open Access
A dataset of 1550 patients to the questionnaires Dental Anxiety Scale (DAS) and Brief Symptom Inventory (BSI-18)
(Technische Universität Dresden, 2021-09-23) Berth, Hendrik
This data contains a set of 1550 patients’ answers to questionnaires taken before dental treatment in a dental clinic. The data is divided into male and female patients as well as according to their age. The level of Dental Anxiety can be interpreted by answers chosen in the Dental Anxiety Scale (DAS) and the level of psychological distress by answers chosen in the Brief Symptom Inventory-18 (BSI-18).
Open Access
Current stress and dental anxiety in a sample of 129 oral surgical patients
(Technische Universität Dresden, 2022-03-14) Berth, Hendrik
The dataset contains questionnaire data from 129 patients. The patients (62 males and 67 females, mean age 41.8 years) visited an oral surgical clinic in Wissen (Rhineland-Palatinate, Germany) for different oral surgical treatments in 2013. They completed the questionnaires Dental Anxiety Scale (DAS) and Questionnaire on current stress (KAB, “Kurzfragebogen zur aktuellen Beanspruchung”). The KAB questionnaire were answered three times by the patients: in the waiting room and in the consulting room before and directly after the treatment.
Open Access
Data and Material for "Investigating perspectives on e-health interventions to enhance maternal mental well-being: results of a stakeholder interview"
(Technische Universität Dresden, 2023-07-03) Schmidt-Hantke, Juliane
These files provide the semi-structured interview guide as well as the transcripts of the interviewed stakeholders.
Open Access
Data and Material for "Should we detach from detachment? Regulatory and post-regulatory effects of emotion downregulation"
(Technische Universität Dresden, 2021-07-22) Gärtner, Anne
These files provide first level fMRI data for reproducing the results of "Should we detach from detachment? Regulatory and post-regulatory effects of emotion downregulation" by Kersten Diers and colleagues. Due to the upload limit on OSF, the materials have been partitioned. Behavioral data, second level fMRI data, ROI masks, materials such as the experimental design and paradigms, the preprint and scripts can be found at OSF: https://osf.io/mg5ac/.
Open Access
Data and Material for "Thinking in Action: Need for Cognition Predicts Self-Control Together with Action Orientation"
(Technische Universität Dresden, 2018-10-17) Strobel, Alexander; Grass, Julia
These files provide the questionnaire data and all material for reproducing the results of "Thinking in Action: Need for Cognition Predicts Self-Control Together with Action Orientation" by Julia Grass and colleagues. In detail, it contains the raw and recoded questionnaire data in CSV and SPSS format as well as the SPSS syntax; supplemental information on the questionnaires used in this study and on the variables in the data set; descriptives and reliability of the questionnaire scales; and MPlus input files for the structural equation models estimated in this study.
Open Access
Data from "Come fly with me" VR study on Reducing Cybersickness with Foveated Depth of Field Blur across varying Locomotion Control conditions
(Technische Universität Dresden, 2025-12-03) Josupeit, Judith; Helmert, Jens; Hussain, Razeen; Solari, Fabio; Chessa, Manuela
Cybersickness, which is characterized by symptoms such as general discomfort, headaches, and nausea, is a common issue in virtual reality (VR) that negatively impacts the accessibility and user experience. Foveated depth of field blur rendering (FovDof) uses the perceptual limitations of the human eye to mitigate cybersickness. However, the external validity of this countermeasure is limited. To increase the external validity, an interactive task is introduced. In addition, the study introduces two levels of locomotion control (3 vs. 6DoF). Along with subjective measures focusing on cybersickness symptoms (SSQ/MISC), objective performance measures (eye tracker sampling frequency) were analyzed. Based on valid data from 65 participants, the analysis revealed significant main effects for both rendering and locomotion control factors for the objective measures. However, the effects of the two types of measures are in opposite directions. For the subjective measures, the combination of full rendering and 3DoF locomotion control resulted in the highest cybersickness values. These results suggest that the applicability of FovDof is universal, even when a task is included, and can be implemented using other eye tracking software and hardware. However, limited customizability for VR headsets limits the applicability. In cases where full locomotion control is provided to the user, the FovDof algorithm does not have additional mitigating effects.
Open Access
Dental anxiety and psychologial distress in 263 patients from Albania and Germany
(Technische Universität Dresden, 2023-12-12) Berth, Hendrik
The dataset contains questionnaire data from 263 patients (N = 133 Germans and N = 130 Albanians). All patients completed the questionnaires Dental Anxiety Scale (DAS) and the Brief Symptom Inventory (BSI-18). Patients also answered questions about their oral health and dental care (e.g. tooth brushing, dental visits, tartar removal, professional teeth cleaning). Data collection took place between December 2019 and July 2020.
Open Access
Documentation for paper "Ecological Momentary Assessment and Applied Relaxation: Results of a Randomized Indicated Preventive Trial in Individuals at Increased Risk for Mental Disorders"
(Technische Universität Dresden, 2023-01-11) Beesdo-Baum, Katja
Documentation including study protocol, raw data and analytic code.
Open Access
Experimental, behavioral data
(Technische Universität Dresden, 2018-04-05) Cuevas Rivera, Dario
Behavioral data for all 35 subjects
Open Access
Eyetracking Data (Fixations), Unity Logs and Survey Data (collected) for "Mitigation Virtual Nose + Previous Experience and Cybersickness"
(Technische Universität Dresden, 2023-09-14) Josupeit, Judith
The "R&I_2020_Input" folder contains 2 additional folders and 1 file (+ one Readme text document which you are currently reading) The file is named "R&I_2020_Experimental Protocol" and contains 3 sheets, these are different versions of the experimental protocol for this experiment, which are: # "Original" - the original German and experimental protocol # "kontrolliert" - a revised version of the original experimental protocol also in German (e.g. spelling mistakes are corrected or the comments are slightly rephrased to be more comprehensible) # "English Translation" - an English translation of the experimental protocol the 3 versions of the experimental protocol contain subject number ("Versuchspersonen-Nummer") and comments of the experimentor ("Kommentare") The 2 folders (each contains another Readme text document which should explain the contents further): # "R&I_2020_LimeSurvey" contains 5 different files: "R&I_2020_Unfiltered Data LimeSurvey" - contains the unfiltered data from the survey "R&I_2020_Filtered Data LimeSurvey" - contains the complete cases, a filtered version of the data from the survey "R&I_2020_Survey + Experimental Protocol" - combination of experimental protocol and filtered version of the data "R&I_2020_ReadMe LimeSurvey" - explains the variables used in the survey in "R&I_2020_Survey + Experimental Protocol" in short form "R&I_2020_Codebook LimeSurvey" - explains the variables used in the survey in "R&I_2020_Survey + Experimental Protocol" in longer form and with more details # "R&I_2020_City" contains one folder per participant, they are named like this: "VPparticipantnumber" (VP = Versuchsperson = participant, the digits/the number after VP is the participant number -> e.g. "VP18" is the folder for participant number 18 there is one exception: for participant 84 the folder is named "unvollständig VP84" (incomplete VP84)) inside each one of these folders are one file containing Unity data (named like this: "weekday, day.month.year_participant number", e.g. Dienstag, 8. Dezember 2020_11 for participant 11) and one folder named "Eyetracking" followed by the paricipant number "e.g. Eyetracking 11", which contains the Eyetracking data the variables of the Unity data are explained further in "R&I_2020_Readme City" (inside the "R&I_2020_City" folder) inside the Eyetracking folder are 4 files and one more folder and 4 files, these files are named: "fixations.pldata", "fixations_timestamps.npy", "info.player.json", "user_info" the folder inside the Eyetracking folder is named "exports" and contains the following 7 files: "participantnumber_fixations" (e.g. "011_fixations"), "export_info", "gaze_positions", "pupil_gaze_positions_info", "pupil_positions", "world_timestamps", "world_timestamps.npy" the Eyetracking files are further explained in "R&I_2020_Readme City" (inside the "R&I_2020_City" folder) if something is missing for a participant, check with the experimental protocol for the reason
Open Access
Eyetracking Data (Raw), Unity Logs and Survey Data (collected) for "Correlation OKN/OKAN and Cybersickness"
(Technische Universität Dresden, 2023-09-14) Josupeit, Judith
The "BA_2020_Input" folder contains 3 folders and 1 file (+ one Readme document which you are currently reading) The file is named "BA_2020_Experimental Protocol and Randomization Plan" and contains 3 sheets, these are different versions of the experimental protocol for this experiment, which are: # "Original" - the original German randomization plan and experimental protocol # "kontrolliert" - a revised version of the original randomization plan and experimental protocol also in German (e.g. spelling mistakes are corrected or the comments are slightly rephrased to be more comprehensible) # "English Translation" - an English translation of the randomization plan and experimental protocol the 3 versions of the experimental protocol contain subject number ("VP"), 1. and 2. Condition (-> 0 = Drum; 1 = City), time and date of the planned session of the experiment and comments of the experimentor The 3 folders (each contains another Readme text document which should explain the contents further): # "BA_2020_LimeSurvey" contains 5 different files: "BA_2020_Unfiltered Data LimeSurvey pt1" - contains the first part of the unfiltered data from the survey "BA_2020_Unfiltered Data LimeSurvey pt2" - contains the second part of the unfiltered data from the survey (does not differ form pt1 in variables, conditions or procedure of experiment; pt2 was just recorded at a later time) "BA_2020_Filtered Data LimeSurvey" - contains the usable cases, a filtered version of the data from the survey "BA_2020_Survey + Experimental Protocol" - combination of experimental protocol and filtered version of the data "BA_2020_ReadMe LimeSurvey" - explains the variables used in the survey in "BA_2020_Survey + Experimental Protocol" in short form "BA_2020_Codebook LimeSurvey" - explains the variables used in the survey in "BA_2020_Survey + Experimental Protocol" in longer form and with more details # "BA_2020_City" contains the data from the City condition of the experiment in one folder per participant, they are named after the participant number -> e.g. "003" is the folder for participant 3 inside each one of these folders are two files containing Unity data (the first is named like this: "weekday, day.month.year_participant number", e.g. "Dienstag, 27. Oktober 2020_013" for participant 13; the second has the same name just with an added "m" at the end (e.g. "Dienstag, 27. Oktober 2020_013m")) the variables of the Unity data are explained in "BA_2020_Readme City" and "BA_2020_Readme Drum" inside the "BA_2020_City" and "BA_2020_Drum" folders and one folder named "Eyetracking" followed by the paricipant number "e.g. Eyetracking 011", which contains the Eyetracking data. They are further explained in the Readmes inside the "BA_2020_City" and "BA_2020_Drum" folders. inside the Eyetracking folder are 4 files and one more folder, these files are named: "fixations.pldata", "fixations_timestamps.npy", "info.player.json", "user_info" the folder inside the Eyetracking folder is named "exports" and contains the following 6 files: "export_info", "gaze_positions", "pupil_gaze_positions_info", "pupil_positions", "world_timestamps", "world_timestamps.npy" # "BA_2020_Drum" contains the data from the Drum condition of the experiment in one folder per participant, it is organized in the same way as "BA_2020_City" if something is missing for a participant, check with the experimental protocol for the reason
Open Access
Impulsive decision-making predicts the course of substance-related and addictive disorders
(Technische Universität Dresden, 2018-12-06) Kräplin, Anja
Data and do-files for the analyses presented in the paper "Impulsive decision-making predicts the course of substance-related and addictive disorders" Aims of the analyses: To test whether impulsive decision-making (1) differs between individuals with substance use disorders (SUD) or non-substance-related addictive disorders (ND) and healthy controls and (2) predicts the course of SUD and ND severity after one year. Design of the study: Baseline and one year follow-up of a prospective-longitudinal community study. Setting of the study: Clinical interviews and behavioural tasks in the laboratory. Participants: 338 individuals between age 20 and 26 were selected from a random sample from the registration office files of Dresden, Germany. Participants fulfilled the criteria for one of three groups: SUD, ND, or healthy controls. After one year, we assessed 313 participants again (93%). Measurements: ND and SUD severity were operationalized with number of DSM-5 symptoms (partly modified for ND) and quantity-frequency indices of use. Four tasks were applied to assess independent facets of impulsive decision-making: 1) delay discounting, 2) risk seeking for gains and 3) for losses, and 4) loss aversion.
Open Access
Intermediate dataset of clustered body odor descriptors
(Technische Universität Dresden, 2023-04-06) Bierling, Antonie Louise; Croy, Ilona
The dataset shows the intermediate results from 1060 participants from nine countries and five languages: German (Germany, Austria, 414 participants), English (United States, Canada, Great Britain, Sweden, 133 participants), Czech (Czech Republic, 120 participants), Italian (Italy, 86 participants) and Chinese (Hong Kong, 307 participants). In total, 6551 body odor descriptions were collected from these participants and clustered to the 20 most frequent words in each language. The number of namings as well as an English translation are provided.
Open Access
Revised: Unity Logs and Survey Data (collected) for "virtual Rod and Frame Test and gamified spatial orientation task"
(Technische Universität Dresden, 2025-08-14) Josupeit, Judith; Andrees, Fabienne; Greim, Leonore; Sanchez Rivas, Sarah
This is a revised version of the previous version: http://dx.doi.org/10.25532/OPARA-283 The current version increases accessibility to the research data as additional translations are used and delimiters for preprocessed data are unified. "VR_RFT_Input" contains Unity-logs and survey data collected between 2022-2023 by J. Josupeit, L. Greim and S. Sanchez Rivas under the experiment title "Replication of Field-Dependency and Cybersickness". The data are structured in 3 folders for each the Unity logs of the virtual RFT "VR_RFT_RFT" and the gamified spatial orientation task "VR_RFT_City", as well as the demographic data of the LimeSurvey questionnaire "VR_RFT_Limesurvey". Aside the folders the experimental protocol and an overview text (Readme) file are included. Associated research article: Josupeit, J. (2024). In rod we trust–The evaluation of a virtual rod and frame test as a cybersickness screening instrument. PLoS ONE, 19(11), Article e0313313. https://doi.org/10.1371/journal.pone.0313313
Open Access
Supplementary materials for the publication "From sunrise to sunset: Exploring landscape preference through global reactions to ephemeral events captured in georeferenced social media" (PLOS)
(Technische Universität Dresden, 2023-01-18) Dunkel, Alexander; Burghardt, Dirk; Hartmann, Maximilian; Ross, Purves; Eva, Hauthal
Events profoundly influence human-environment interactions. Through repetition, some events manifest and amplify collective behavioral traits, which significantly affects landscapes and their use, meaning, and value. However, the majority of research on reaction to events focuses on case studies, based on spatial subsets of data. This makes it difficult to put observations into context and to isolate sources of noise or bias found in data. As a result, inclusion of perceived aesthetic values, for example, in cultural ecosystem services, as a means to protect and develop landscapes, remains problematic. In this work, we focus on human behavior worldwide by exploring global reactions to sunset and sunrise using two datasets collected from Instagram and Flickr. By focusing on the consistency and reproducibility of results across these datasets, our goal is to contribute to the development of more robust methods for identifying landscape preference using geo-social media data, while also exploring motivations for photographing these particular events. Based on a four facet context model, reactions to sunset and sunrise are explored for Where, Who, What, and When. We further compare reactions across different groups, with the aim of quantifying differences in behavior and information spread. Our results suggest that a balanced assessment of landscape preference across different regions and datasets is possible, which strengthens representativity and exploring the How and Why in particular event contexts. The process of analysis is fully documented, allowing transparent replication and adoption to other events or datasets. The data encompasses both code (jupyter notebooks) and data (abstracted using hyperloglog). Please see the git repository for any further information: https://gitlab.vgiscience.de/ad/sunset-sunrise-paper
Open Access
Unity Logs and Survey Data (collected) for "Correlation Field dependency and Cybersickness"
(Technische Universität Dresden, 2023-09-12) Josupeit, Judith
The "R&I_2019_Input" folder contains 3 additional folders and 3 files (+ one Readme document which you are currently reading) The file is named "R&I_2019_Experimental Protocol" and contains 3 sheets, these are different versions of the experimental protocol for this experiment, which are: # "Original" - the original German experimental protocol # "kontrolliert" - a revised version of the original experimental protocol also in German (e.g. spelling mistakes are corrected or the comments are slightly rephrased to be more comprehensible) # "English Translation" - an English translation of the experimental protocol the 3 versions of the experimental protocol contain participant number ("VP-Nummer"), planned date and time of the session ("Termin") and comment of the experimentor ("Kommentar") The 3 folders (each contains another Readme text document which should explain the contents further): # "R&I_2019_CSV City" contains Unity Data for the City condition of the experiment, there is ideally one file per participant. The files are named like this: "weekday, day.month.year_participant number" (in German), so the last 3 digits indicate the participant the data is for (e.g. 2Mittwoch, 22. Januar 2020_044" -> data for participant 44) sometimes there are multiple files per participant (e.g. for 55: "Donnerstag, 23. Januar 2020_059" & "Donnerstag, 23. Januar 2020_059_C" -> in this case use the experimental protocol to find out how to proceed there is also another Readme to explain the variables ("R&I_2019_ReadMe City") # "R&I_2019_CSV RFT" contains Unity Data for the RFT condition of the experiment, follows the same rules as "R&I_2019_CSV City" # "R&I_2019_SoSci Survey" contains 5 different files: "R&I_2019_Unfiltered Data SoSci" - contains the unfiltered data from the survey "R&I_2019_Filtered Data SoSci" - contains the usable cases, a filtered version of the data from the survey "R&I_2019_Survey + Experimental Protocol" - combination of experimental protocol and filtered version of the data "R&I_2019_ReadMe SoSci Survey" - explains the variables used in the survey in "R&I_2019_Survey + Experimental Protocol" in short form "R&I_2019_Codebook" - explains the variables used in the survey in "R&I_2019_Survey + Experimental Protocol" in longer form and with more details
Open Access
Virtual RFT 2022 - Descriptive and performance measures for a virtual Rod and Frame Test and a gamified spatial orientation task
(Technische Universität Dresden, 2024-03-24) Andrees, Fabienne; Josupeit, Judith; Greim, Leonore; Sanchez Rivas, Sarah
Virtual environments can cause symptoms ranging from general discomfort to disorientation and nausea (LaViola, 2000). The phenomenon called cybersickness resembles motion sickness (MS) but is visually induced (VIMS) (Muth et al., 2018). Unfortunately screening questionnaires with high prospective power are lacking which makes process indicators an interesting candidate to screen for VIMS. Working models for MS like the Sensory Conflict Theory (Reason & Brand, 1975) – postulating a mismatch in various sensory modalities between expected and actual motion – can be conveyed to VIMS to eyeball the relationships between these concepts. A subsequent theory the Subjective Vertical Mismatch Theory (Bos & Bles, 1998) stresses the importance of the sense of verticality for matching planned and external sensed motion. To test the individual sense of verticality a virtual rod and frame test (physical RFT setup was already described by Witkin and Asch (1948). was developed which measures the field dependency as a marker for the sense of verticality. In the context of MS, a positive correlation with higher field dependence has been found, for VIMS induced by simulators a contrary connection was found, but validations for VIMS or specifically for cybersickness are missing. We postulate a main effect of the virtual environment on reported cybersickness (pre-/post comparison) as a mandatory prerequisite. Moreover, we test the correlation between various metrics of Field dependency sampled with a virtual rod and frame test and the baseline corrected cybersickness self-reports. Cybersickness was sampled in the virtual rod and frame test itself but also in a virtual city environment that tests visuospatial orientation by applying a free exploration task. Hence we are enabled to addtionally control for order effects, which would limit the applicability of the VR RFT as a screening questionnaire. These data do not only serve the purpose of metanalyses and transparency of the original paper but also ethical alleviation. The induction of cybersickness regardless of being voluntarily or involuntarily is a stressful event for participants. Therefore the reuse of research data in this area reduces the need for various stressful experiments, in case reporting is rigorous.

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