This is a preprint. Preprints are preliminary reports that have not undergone peer review. They should not be considered conclusive, used to inform clinical practice, or referenced by the media as validated information.
Crime and physical activity measures from the Safe and Fit Environments Study (SAFE) Psychometric properties across age groups
Scott C. Roesch
San Diego State University Malcolm A Love Library
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6574-1916
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This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
Valid and reliable measures are needed to better understand the relationship between physical activity and crime. This paper provides a comprehensive psychometric evaluation of measures developed in the Safe and Fit Environments (SAFE) Study to assess a conceptual framework. In addition to assessing the basic psychometric properties of each measure (e.g., variable distributions item/scale level, internal consistency reliability), this study formally examined the measurement validity and invariance of measures across four age groups using confirmatory factor analysis. The sample (n=2,173) included 336 Adolescents (aged 12-17), 532 Young adults (aged 18-39), 838 Middle Adults, and 467 Older Adults (aged 66+). The psychometric evaluation of (sub)scales showed consistent factorial validity and internal consistency reliability across the majority of the measures and across the four age groups. Specifically, 14 of the 17 measures subjected to a test of factorial validity displayed statistically and practically significant factor loadings and internal consistency values in the overall sample and across the age groups. The pattern of correlations for each (sub)scale with other (sub)scales/indexes largely did not exhibit redundancy across measures. The findings expanded upon the test-retest reliability evaluation reported in Patch et al. (2019) and suggest these measures can be used in predictive models.
Keywords
Crime, Physical Activity, Measurement, Psychometrics, Age, Fear of Crime
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This is a preprint. It has not completed peer review.
Crime and physical activity measures from the Safe and Fit Environments Study (SAFE) Psychometric properties across age groups
Scott C. Roesch
San Diego State University Malcolm A Love Library
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6574-1916
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 22 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
Valid and reliable measures are needed to better understand the relationship between physical activity and crime. This paper provides a comprehensive psychometric evaluation of measures developed in the Safe and Fit Environments (SAFE) Study to assess a conceptual framework. In addition to assessing the basic psychometric properties of each measure (e.g., variable distributions item/scale level, internal consistency reliability), this study formally examined the measurement validity and invariance of measures across four age groups using confirmatory factor analysis. The sample (n=2,173) included 336 Adolescents (aged 12-17), 532 Young adults (aged 18-39), 838 Middle Adults, and 467 Older Adults (aged 66+). The psychometric evaluation of (sub)scales showed consistent factorial validity and internal consistency reliability across the majority of the measures and across the four age groups. Specifically, 14 of the 17 measures subjected to a test of factorial validity displayed statistically and practically significant factor loadings and internal consistency values in the overall sample and across the age groups. The pattern of correlations for each (sub)scale with other (sub)scales/indexes largely did not exhibit redundancy across measures. The findings expanded upon the test-retest reliability evaluation reported in Patch et al. (2019) and suggest these measures can be used in predictive models.
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Due to technical limitations, tables are only available as a download in the supplemental files section