Accepted for/Published in: JMIR Human Factors
Date Submitted: Jan 19, 2022
Date Accepted: Mar 6, 2022
Interdisciplinary collaborations in digital health research: a case study using quantitative and qualitative survey methods
ABSTRACT
Background:
Digital innovations in medicine are disruptive technologies that can change the way we deliver diagnostic procedures and treatments. Such innovations are usually designed in teams from different disciplinary backgrounds. The following paper concentrates on two interdisciplinary (ID) research teams with 20 members from medicine and engineering sciences working jointly on digital health solutions.
Objective:
The aim of the following paper is to identify factors on individual, team and organisational level that influence the implementation of interdisciplinary research projects elaborating digital applications for medicine and based on the results, draw conclusions for the proactive design of the interdisciplinary research process in order to make these projects successful.
Methods:
For achieving this aim, two ID research teams were observed and a small case study (response rate 75%, n=15) was conducted by means of an online-based questionnaire containing both closed and open questions for self-report. For the analysis of the quantitative data, the Spearman rank correlation coefficient was calculated. The answers to the open questions were subjected to a qualitative content analysis.
Results:
With regard to the interdisciplinary research projects investigated, influencing factors of all three levels presented (individual, team, organisation) have proven to be relevant for an ID research cooperation.
Conclusions:
Regarding recommendations for future design of ID cooperation, management aspects are addressed, i.e. installation of a coordinator, systematic definition of goals, required resources and necessary efforts on the part of the involved interdisciplinary research partners. Due to only small groups that were investigated, further research in this field is necessary to derive more general recommendations for ID research teams. Clinical Trial: ARAILIS (DRKS00023909); PROSPER (DRKS00025077)
Citation
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