Table 1.

Distinction between citizen, implementation, and improvement sciences

	Citizen Science [15]	Implementation Science [16]	Improvement Science [17]
Historical tradition	Natural Sciences, such as bird observations, classifications, and collection of data by “non-scientists” for use by scientists. Participants as volunteer data collectors with aim to collect large datasets. Variants on this term are used in the literature and include civic science, community environmental policing, street science, popular epidemiology, and crowd science.	The implementation of evidence into practice and translation gap. Identification of evidence into practice roadblocks to improve implementation.	The quality chasm and improvement of quality of care to increase safety, with a focus on changing physician behavior. Highly influenced by the United States Institute of Medicine Quality Chasm reports.
Original purpose	To address some of the problems of time, space, and large amounts of data required for the biological sciences. People being able to collect data in different geographical locations. Some work was undertaken in medical research, such as Malaria Spot.	To promote uptake of evidence-based interventions into practice and policy. Early work had empirical focus with less attention to theory.	Systems-level work to improve the quality, safety, and value of health care. Premised on the idea that improvement would result in greater efficiencies in terms of both patient outcomes and cost.
Contemporary variants	A science that is focused on the needs and concerns of citizens and is developed and enacted by citizens. Shift from the person as the object of study to the citizen as a research subject (for data collection and analysis). Part of the evolution of digital humanities where large repositories of data can be collected (eg, Zooniverse platform). Also used in human-computer interaction studies to develop gamified solutions from data people contribute.	Progression of theoretical models and approaches to better understand and explain how and why implementation fails or succeeds. Identification of the conditions for implementation readiness in different settings.	Greater focus on the association between patient experience of care and quality, safety, and value of health care. Embedding public and patient in the processes of identification of systems of change areas, design, and co-development of solutions with professionals. Working in a partnership model between academia and frontline clinicians. Contribution to theories of how change happens.