Fig 1.
Motivations arranged along a spectrum of increasing self-determination.
More self-determined motivations (i.e., those regulated by factors internal to the self) are facilitated by meeting individuals’ needs for competence, relatedness and autonomy and are linked to longer-lasting and more impactful behaviors. Figure adapted from Ryan & Deci [50] and does not include integrated regulation, which is sometimes situated between identified and intrinsic regulation.
Table 1.
Citizen science participation patterns of corporate employees according to population-level data for the entire volunteer sample (N = 13,425) and survey data from a smaller subset of volunteers (n = 343).
Table 2.
The ten most popular projects for participants in the corporate citizen science volunteer program.
Table 3.
Summary socio-demographic data for corporate volunteers, typical citizen science volunteers on SciStarter [5], and the general US population.
Table 4.
Means and loadings across three factors for volunteers’ motivation to participate in citizen science (n = 388).
Fig 2.
Associations between volunteers’ motivations for participating in the citizen science program and the number of hours they spent contributing to projects.
Figure is separated into panels for autonomous (A), controlled (B), and amotivated (C) motivations. Panel (D) depicts the association between hours of participation and a “Relative Autonomy Index,” which combines the three motivation factors into a single measure of self-determined motivation. Vertical black line denotes median, blue dot denotes mean (n = 356).
Fig 3.
Model of the effects of volunteer motivation on the number of hours spent contributing to citizen science (log-corrected).
Regression model controls for volunteers’ race/ethnicity, gender, education, political beliefs, age, whether they worked in STEM, when they completed the survey and whether they had prior citizen science experience. Figure shows 95% confidence intervals for the three motivation variables (vertical black lines). Degrees of freedom = 221; adjusted r2 = 0.11.
Table 5.
Results of regression predicting hours of citizen science contributions (log-corrected) from volunteers’ motivations, socio-demographics and other factors.
Table 6.
Suggestions for designing citizen science projects to facilitate self-determined motivation by meeting volunteers’ needs for competence, relatedness and autonomy, using examples from popular projects among corporate volunteers.