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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Online Survey: Knowledge of Sex and Gender in German Data Integration Centers

Authors: Schindler, Lea; Beelich, Hilke; Gütebier, Lea; Katsari, Elpiniki; Stracke, Sylvia; Waltemath, Dagmar;

Online Survey: Knowledge of Sex and Gender in German Data Integration Centers

Abstract

The original survey questionnaire (Survey_Questions.pdf) consists of 11 single- and multiple-choice questions and was developed to assess the level of knowledge among Data Integration Centers in Germany regarding sex, gender, and the use of gender scores. The questionnaire was distributed in February 2024 to the entire German Data Integration Centers community via a national mailing list, and is presented in its original German language. An English translation of the questionnaire is also provided (Survey_Questions_Translated.pdf). Please note that the translation of the survey may result in slight variations in the questionnaire's subtleties. The dataset (Survey_Dataset.csv) contains the responses from the survey, with question titles and answer options translated to English, while keeping the originally given German responses by participants in the short-answer fields to maintain subtleties and nuances. The dataset contains information about each participant, including their case number (CASE), time spent answering the survey (TIME_SUM), and completion status (FINISHED), as well as their responses to the 11 questions, which are sorted as they appeared in the survey. Responses to single-choice questions are directly shown (Yes, No, not specified, I don't know), while the answer options of multiple-choice questions are listed separately (e.g. Gender_Classification+female, Gender_Classification+male, ...) and are coded as TRUE (if selected) or FALSE (if not selected). Multiple choice questions are also summarized in an additional column (Gender_Classification, Gender_Coding_Options, Gender_Scores) which indicates whether the question was answered and how many answering options were selected. The code used for the analysis was written in R (version 4.3.1) and is provided in both PDF and R Markdown formats(Survey_Analysis.pdf und Survey_Analysis.qmd). First results were already published as conference abstract: https://doi.org/10.3205/24gmds016

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Keywords

clinical routine data, Data Integration Center, health research, gender scores, Online Survey, data competency, gender, Gender studies, survey, Data Management

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average