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Regressed person-environment interest fit : validating polynomial regression for a specific environment

Stijn Schelfhout (UGent) , Mona Bassleer (UGent) , Bart Wille (UGent) , Sofie Van Cauwenberghe (UGent) , Merel Dutry (UGent) , Lot Fonteyne (UGent) , Nicolas Dirix (UGent) , Eva Derous (UGent) , Filip De Fruyt (UGent) and Wouter Duyck (UGent)
(2022) JOURNAL OF VOCATIONAL BEHAVIOR. 136.
Author
Organization
Abstract
Polynomial regression is a proven method to calculate person-environment (PE) interest fit between the RIASEC (realistic, investigative, artistic, social, enterprising and conventional) interests of a student and the RIASEC profile of a study program. The method has shown much larger effects of PE interest fit on academic achievement than earlier approaches in literature. However, the polynomial regression method in its current form only focuses on establishing the regressed interest fit (RIF) of a population of students with their study environments, in order to observe how large the general impact of PE interest fit can become on academic achievement. The present study (N = 4407 across n = 22 study programs) further validates this method towards new applications by theoretically deriving two measures of RIF that only affect a single environment like a study program. Analyses show that the use of RIF for a single study environment results in an even stronger positive relation between PE interest fit and academic achievement of r = 0.36, compared to r = 0.25 for the original polynomial regression method. Analyses also show that RIF for one environment can be used to generate interpretable and reliable RIASEC environment profiles. In sum, RIF for a single (study) environment is a promising operationalization of PE interest fit which facilitates both empirical research as well as the practical application of interest fit in counseling settings
Keywords
Life-span and Life-course Studies, Organizational Behavior and Human Resource Management, Applied Psychology, Education, Vocational interests, RIASEC, Academic achievement, PE interest fit, Polynomial regression

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MLA
Schelfhout, Stijn, et al. “Regressed Person-Environment Interest Fit : Validating Polynomial Regression for a Specific Environment.” JOURNAL OF VOCATIONAL BEHAVIOR, vol. 136, 2022, doi:10.1016/j.jvb.2022.103748.
APA
Schelfhout, S., Bassleer, M., Wille, B., Van Cauwenberghe, S., Dutry, M., Fonteyne, L., … Duyck, W. (2022). Regressed person-environment interest fit : validating polynomial regression for a specific environment. JOURNAL OF VOCATIONAL BEHAVIOR, 136. https://doi.org/10.1016/j.jvb.2022.103748
Chicago author-date
Schelfhout, Stijn, Mona Bassleer, Bart Wille, Sofie Van Cauwenberghe, Merel Dutry, Lot Fonteyne, Nicolas Dirix, Eva Derous, Filip De Fruyt, and Wouter Duyck. 2022. “Regressed Person-Environment Interest Fit : Validating Polynomial Regression for a Specific Environment.” JOURNAL OF VOCATIONAL BEHAVIOR 136. https://doi.org/10.1016/j.jvb.2022.103748.
Chicago author-date (all authors)
Schelfhout, Stijn, Mona Bassleer, Bart Wille, Sofie Van Cauwenberghe, Merel Dutry, Lot Fonteyne, Nicolas Dirix, Eva Derous, Filip De Fruyt, and Wouter Duyck. 2022. “Regressed Person-Environment Interest Fit : Validating Polynomial Regression for a Specific Environment.” JOURNAL OF VOCATIONAL BEHAVIOR 136. doi:10.1016/j.jvb.2022.103748.
Vancouver
1.
Schelfhout S, Bassleer M, Wille B, Van Cauwenberghe S, Dutry M, Fonteyne L, et al. Regressed person-environment interest fit : validating polynomial regression for a specific environment. JOURNAL OF VOCATIONAL BEHAVIOR. 2022;136.
IEEE
[1]
S. Schelfhout et al., “Regressed person-environment interest fit : validating polynomial regression for a specific environment,” JOURNAL OF VOCATIONAL BEHAVIOR, vol. 136, 2022.
@article{8756957,
  abstract     = {{Polynomial regression is a proven method to calculate person-environment (PE) interest fit between the RIASEC (realistic, investigative, artistic, social, enterprising and conventional) interests of a student and the RIASEC profile of a study program. The method has shown much larger effects of PE interest fit on academic achievement than earlier approaches in literature. However, the polynomial regression method in its current form only focuses on establishing the regressed interest fit (RIF) of a population of students with their study environments, in order to observe how large the general impact of PE interest fit can become on academic achievement. The present study (N = 4407 across n = 22 study programs) further validates this method towards new applications by theoretically deriving two measures of RIF that only affect a single environment like a study program. Analyses show that the use of RIF for a single study environment results in an even stronger positive relation between PE interest fit and academic achievement of r = 0.36, compared to r = 0.25 for the original polynomial regression method. Analyses also show that RIF for one environment can be used to generate interpretable and reliable RIASEC environment profiles. In sum, RIF for a single (study) environment is a promising operationalization of PE interest fit which facilitates both empirical research as well as the practical application of interest fit in counseling settings}},
  articleno    = {{103748}},
  author       = {{Schelfhout, Stijn and Bassleer, Mona and Wille, Bart and Van Cauwenberghe, Sofie and Dutry, Merel and Fonteyne, Lot and Dirix, Nicolas and Derous, Eva and De Fruyt, Filip and Duyck, Wouter}},
  issn         = {{0001-8791}},
  journal      = {{JOURNAL OF VOCATIONAL BEHAVIOR}},
  keywords     = {{Life-span and Life-course Studies,Organizational Behavior and Human Resource Management,Applied Psychology,Education,Vocational interests,RIASEC,Academic achievement,PE interest fit,Polynomial regression}},
  language     = {{eng}},
  pages        = {{15}},
  title        = {{Regressed person-environment interest fit : validating polynomial regression for a specific environment}},
  url          = {{http://doi.org/10.1016/j.jvb.2022.103748}},
  volume       = {{136}},
  year         = {{2022}},
}
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