RESUMO
OBJECTIVE: Naturalness preference can influence important health decisions. However, the literature lacks a reliable way to measure individual differences in naturalness preferences. We fill this gap by designing and validating a scale to measure individual differences in naturalness preference. METHODS: We conducted 3 studies among Amazon Mechanical Turk participants. In study 1 (N = 451), we created scale items through an iterative process that measured naturalness preference in hypothesized domains. We conducted exploratory factor analysis (EFA) to identify items that assess the naturalness preference construct. In study 2 (N = 448), we conducted confirmatory factor analysis (CFA) and tests of criterion, discriminant, convergent, and incremental validity. In study 3 (N = 607), we confirmed test-retest reliability of the scale and performed additional validity tests. RESULTS: EFA revealed 3 correlated factors consistent with naturalness preference in medicine, food, and household products. The CFA confirmed the 3-factor structure and led to the decision to drop reverse-coded items. The finalized Naturalness Preference Scale (NPS) consists of 20 items and 3 subscales: NPS-medicine, NPS-food, and NPS-household products. The NPS demonstrated good test-retest reliability, and subscales had good validity in their respective domains. The NPS-medicine subscale was predictive of the uptake of a hypothetical COVID-19 vaccine (r = -0.45) and belief in unproven natural COVID remedies and treatments (r = 0.29). CONCLUSIONS: The NPS will allow researchers to better assess individual differences in naturalness preference and how they influence decision making and health behaviors. HIGHLIGHTS: This research created and validated a scale to measure individual differences in naturalness preference in 3 domains: medicine, food, and household products.This study confirms that the strength of the naturalness preference differs in different domains.An important and timely finding is that higher scores in the naturalness preference medical subscale are associated with belief in COVID-19 misinformation and reluctance toward COVID-19 vaccination.