PDPL Metric: Validating a Scale to Measure Personal Data Privacy Literacy Among University Students
Brady D. Lund, Nathan Brown, Ana Roeschley, Gahangir Hossain

TL;DR
This paper develops and validates a new scale to measure personal data privacy literacy among university students, encompassing key privacy-related skills and perceptions in digital environments.
Contribution
It introduces the PDPL Metric, a psychometric scale that reliably assesses six core privacy constructs in a university student population.
Findings
The scale is unidimensional and internally consistent.
No PDPL differences based on gender or academic level.
A difference in PDPL was found based on domestic/international status.
Abstract
Personal data privacy literacy (PDPL) refers to a collection of digital literacy skills related to an individuals ability to understand, evaluate, and manage the collection, use, and protection of personal data in online and digital environments. This study introduces and validates a new psychometric scale (PDPL Metric) designed to measure data privacy literacy among university students, focusing on six key privacy constructs: perceived risk of data misuse, expectations of informed consent, general privacy concern, privacy management awareness, privacy-utility trade-off acceptance, and perceived importance of data security. A 24-item questionnaire was developed and administered to students at U.S.-based research universities. Principal components analysis confirmed the unidimensionality and internal consistency of each construct, and a second-order analysis supported the integration of…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Impact of Technology on Adolescents · Privacy-Preserving Technologies in Data
