| Title: |
Quest markup for developing FAIR questionnaire modules for epidemiologic studies. |
| Authors: |
Russ, DE; Gerlanc, NM; Shen, B; Patel, B; Berrington de González, A; Freedman, ND; Cusack, JM; Gaudet, MM; García-Closas, M; Almeida, JS |
| Publisher Information: |
BMC |
| Publication Year: |
2023 |
| Collection: |
The Institute of Cancer Research (ICR): Publications Repository |
| Subject Terms: |
Data collection; Data commons; Data science; Epidemiologic methods; Surveys and questionnaires; Humans; Software; Epidemiologic Studies |
| Subject Geographic: |
England |
| Description: |
BACKGROUND: Online questionnaires are commonly used to collect information from participants in epidemiological studies. This requires building questionnaires using machine-readable formats that can be delivered to study participants using web-based technologies such as progressive web applications. However, the paucity of open-source markup standards with support for complex logic make collaborative development of web-based questionnaire modules difficult. This often prevents interoperability and reusability of questionnaire modules across epidemiological studies. RESULTS: We developed an open-source markup language for presentation of questionnaire content and logic, Quest, within a real-time renderer that enables the user to test logic (e.g., skip patterns) and view the structure of data collection. We provide the Quest markup language, an in-browser markup rendering tool, questionnaire development tool and an example web application that embeds the renderer, developed for The Connect for Cancer Prevention Study. CONCLUSION: A markup language can specify both the content and logic of a questionnaire as plain text. Questionnaire markup, such as Quest, can become a standard format for storing questionnaires or sharing questionnaires across the web. Quest is a step towards generation of FAIR data in epidemiological studies by facilitating reusability of questionnaires and data interoperability using open-source tools. |
| Document Type: |
article in journal/newspaper |
| File Description: |
Electronic; application/pdf |
| Language: |
English |
| ISSN: |
1472-6947 |
| Relation: |
238; BMC Medical Informatics and Decision Making, 2023, 23 (1), pp. 238 -; https://repository.icr.ac.uk/handle/internal/6076 |
| Availability: |
https://repository.icr.ac.uk/handle/internal/6076 |
| Rights: |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Accession Number: |
edsbas.CB514BAC |
| Database: |
BASE |