  A clinical study is often necessary for exploring important research
questions; however, this approach is sometimes time and money consuming.
Another extreme approach, which is to collect and aggregate opinions from
crowds, provides a result drawn from the crowds' past experiences and
knowledge. To explore a solution that takes advantage of both the rigid
clinical approach and the crowds' opinion-based approach, we design a framework
that exploits crowdsourcing as a part of the research process, whereby crowd
workers serve as if they were a scientist conducting a "pseudo" prospective
study. This study evaluates the feasibility of the proposed framework to
generate hypotheses on a specified topic and verify them in the real world by
employing many crowd workers. The framework comprises two phases of crowd-based
workflow. In Phase 1 - the hypothesis generation and ranking phase - our system
asks workers two types of questions to collect a number of hypotheses and rank
them. In Phase 2 - the hypothesis verification phase - the system asks workers
to verify the top-ranked hypotheses from Phase 1 by implementing one of them in
real life. Through experiments, we explore the potential and limitations of the
framework to generate and evaluate hypotheses about the factors that result in
a good night's sleep. Our results on significant sleep quality improvement show
the basic feasibility of our framework, suggesting that crowd-based research is
compatible with experts' knowledge in a certain domain.
