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23-11-2018 | Original Paper | Uitgave 3/2019

Journal of Child and Family Studies 3/2019

The Development and Validation of the Parental Involvement Survey in their Children’s Elementary Studies (PISCES)

Journal of Child and Family Studies > Uitgave 3/2019
P. Cristian Gugiu, Mihaiela Ristei Gugiu, Michael Barnes, Belinda Gimbert, Megan Sanders
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The online version of this article (https://​doi.​org/​10.​1007/​s10826-018-1294-y) contains supplementary material, which is available to authorized users.


The purpose of the present study was to (1) examine the internal validity of the Parental Involvement Survey in their Children’s Elementary Studies (PISCES) and (2) illustrate how survey instruments can be validated using modern psychometric techniques. The PISCES was developed by the present authors by adopting items from the Hoover-Dempsey and Sandler Revised Model of Parent Involvement and the Parent Reading Belief Inventory. The PISCES is comprised of 49 new items and 35 modified items that measure parental beliefs about education, reading with children, self-efficacy, and involvement in school activities. Data were collected from 230 parents of kindergarten students enrolled in a major Midwest school district. We utilized modern psychometric techniques to validate the instrument, including ordinal parallel analysis, ordinal exploratory factor analysis (EFA), Rasch modeling, second-order EFA, and reliability analysis. Our findings revealed the PISCES attained a very high level of internal validity although some of its subscales could benefit from the addition of more items. Tables for converting the sum of individual item scores to Rasch scores are provided. We advise readers to use the whole instrument if they want a holistic measure of parental involvement and the individual scales if they are only interested in a particular domain of parental involvement. We also advise readers to adopt our conversion tables to facilitate comparisons across studies. Finally, we recommend that survey researchers utilize ordinal parallel analysis and ordinal EFA to investigate the dimensionality of survey instruments and Rasch modeling to further explore and refine them.

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