Development of a prediction model on the acceptance of electronic laboratory notebooks in academic environments.
Documentation of research data plays a key role in the biomedical engineering innovation processes. It makes an important contribution to the protection of intellectual property, the traceability of results and fulfilling the regulatory requirement. Because of the increasing digitalization in laboratories, an electronic alternative to the commonly-used paper-bound notebooks could contribute to the production of sophisticated documentation. However, compared to in an industrial environment, the use of electronic laboratory notebooks is not widespread in academic laboratories. Little is known about the acceptance of an electronic documentation system and the underlying reasons for this. Thus, this paper aims to establish a prediction model on the potential preference and acceptance of scientists either for paper-based or electronic documentation. The underlying data for the analysis originate from an online survey of 101 scientists in industrial, academic and clinical environments. Various parameters were analyzed to identify crucial factors for the system preference using binary logistic regression. The analysis showed significant dependency between the documentation system preference and the supposed workload associated with the documentation system (p<0.006; odds ratio=58.543) and an additional personal component. Because of the dependency of system choice on specific parameters it is possible to predict the acceptance of an electronic laboratory notebook before implementation.
Frederik
F
Kloeckner
Robert
R
Farkas
Tobias
T
Franken
Thomas
T
Schmitz-Rode
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D057205:Automation, Laboratory / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003258:Consumer Behavior / Q000706:statistics & numerical data*; D003625:Data Collection / Q000706:statistics & numerical data*; D004282:Documentation / Q000706:statistics & numerical data*; D017753:Ecosystem; D005260:Female; D006801:Humans; D019451:Information Management / Q000706:statistics & numerical data*; D007753:Laboratories / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D012108:Research Personnel / Q000706:statistics & numerical data*; D012586:Science / Q000706:statistics & numerical data; D014495:Universities / Q000706:statistics & numerical data*; D014584:User-Computer Interface; D055815:Young Adult