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      Psychometric Evaluation of a Big Five Personality State Scale for Intensive Longitudinal Studies

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          Abstract

          Despite enthusiasm for using intensive longitudinal designs to measure day-to-day manifestations of personality underlying differences between people, the validity of personality state scales has yet to be established. In this study, we evaluated the psychometrics of 20-item and 10-item daily, Big Five personality state scales in three independent samples ( N = 1,041). We used multilevel models to separately examine the validity of the scales for assessing personality variation at the between- and within-person levels. Results showed that a five-factor structure at both levels fits the data well, the scales had good convergent and discriminative associations with external variables, and personality states captured similar nomological nets as established global, self-report personality inventories. Limitations of the scales were identified (e.g., low reliability, low correlations with external criterion) that point to a need for more, systematic psychometric work. Our findings provide initial support for the use of personality state scales in intensive longitudinal designs to study between-person traits, within-person processes, and their interrelationship.

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          Most cited references64

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

            Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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              The REDCap consortium: Building an international community of software platform partners

              The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Assessment
                Assessment
                SAGE Publications
                1073-1911
                1552-3489
                September 2022
                May 05 2021
                September 2022
                : 29
                : 6
                : 1301-1319
                Affiliations
                [1 ]University of Pittsburgh, Pittsburgh, PA, USA
                Article
                10.1177/10731911211008254
                33949209
                00e03313-fb2c-4b6d-91e1-788f48b6d505
                © 2022

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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