Zhang, H., Gagnon, J., & Schuster, T. (2018, March). Web app for questionnaire validation in instrument development. Poster session presented at the 18th Annual McGill Biomedical Graduate Conference (AMBGC).
Abstract
Introduction: In primary health care research, questionnaires are an important instrument to collect data in target populations and the process of obtaining information that are relevant to the research question brings up the challenges of obtaining estimation about statistical parameters from small sample sizes.
Methods: We developed a web app adapting existing Bayesian methods for questionnaire validation to the specifics of questionnaire development and the associated sequential data acquisition in primary care. We used simulation data and two real data as examples to demonstrate the application of our app. Our web app further incorporated improved understanding of the principle intentions of the questionnaire designers (the domain experts) and related expectations of the scope and usefulness of the developed instruments.
Results: Modern Bayesian methods and our web app offer promising solutions to the small sample size problem as they allow for the incorporation of prior information to increase the efficiency of the conventional methods for instrument validation.
Conclusion: Our app offers a user-friendly, free and practical alternative for questionnaire validation improving use of data and the efficiency of our health care system.