No abstract

Understanding volunteers' motivations to participate in Citizen Science (CS) projects is essential for these projects' effective management and success. Many studies have investigated citizen scientists' motivations, but only a few have used a theory-based approach to provide a standardized methodology to measure CS motivations. The current research aims to take the literature a step further by developing and applying a general, standardized, theory-based framework of CS motivation and a CS motivation scale (CSMS) that can be used to assess volunteers' motivations across diverse CS projects. The CSMS comprises 58 items corresponding to 15 motivational categories. It is grounded in Schwartz's theory of basic human values, while incorporating the wealth of empirical knowledge on citizen scientists' motivations. We administered the scale to three separate samples of either Dutch or Hebrew-speaking participants who volunteered for three CS projects. Analysis of participants' ratings of their motivations supported our theoretical framework, showing that 13 of the scale's 15 motivational categories fell into 4 higherorder motivations, which correspond to Schwartz's theory of values: openness to change, self-enhancement, continuity (conservation), and self-transcendence. Results further provide concrete insights into CS participation behavior, showing that certain motivations (including help with research, benevolence, and self-direction) were consistently among the most important motivators for participation across CS projects. Finally, we found that prioritizing certain motivations can also predict participation behavior (e.g., duration of participation and willingness to participate in additional volunteering activities). The CSMS is a new tool that can be applied across projects spanning diverse domains and populations, advancing and standardizing the growing literature on CS motivations. design, data analysis, and writing. Anne Land-Zandstra contributed to the conception, data collection, and writing. Nirit Lavie-Alon contributed to the data collection and writing. Assaf Shwartz contributed to the conception, design, and writing.