Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire
Psychological scales play a key role in the assessment, screening, and diagnosis of latent variables, such as emotions, mental health, and well-being. In practice, researchers need shorter scales of psychological traits to save administration time and cost. Thus, a variety of optimization algorithms...
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MDPI AG
2023-01-01
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| Online Access: | https://www.mdpi.com/2078-2489/14/2/63 |
| _version_ | 1797620330291789824 |
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| author | Sevilay Kilmen Okan Bulut |
| author_facet | Sevilay Kilmen Okan Bulut |
| author_sort | Sevilay Kilmen |
| collection | DOAJ |
| description | Psychological scales play a key role in the assessment, screening, and diagnosis of latent variables, such as emotions, mental health, and well-being. In practice, researchers need shorter scales of psychological traits to save administration time and cost. Thus, a variety of optimization algorithms have been proposed to abbreviate lengthy psychological scales into shorter instruments efficiently. The main goal of this application is to form an abbreviated scale with fewer items while maintaining reliability, relationships among the subscales, and model fit for the full scale. In this study, we use an optimization algorithm (genetic algorithm) and a feature selection algorithm (recursive feature elimination) to abbreviate a psychological scale automatically. Although both algorithms search for an optimal subset of features within a large pool of features, the search mechanism underlying each algorithm is quite different. The genetic algorithm employs a systematic but computationally-expensive sampling process to find the optimal features, whereas recursive feature elimination removes the least important features iteratively until a desired number of features are retained. In this study, we use a 77-item measure of test emotions (Test Emotions Questionnaire) to demonstrate how these algorithms can be used for scale abbreviation. We generate a 40-item short form using each algorithm and compare the quality of the selected items against the full-length scale. The results indicate that both methods can provide researchers and practitioners with a systematic procedure for creating psychometrically sound, shorter versions of lengthy psychological instruments. |
| first_indexed | 2024-03-11T08:39:38Z |
| format | Article |
| id | doaj.art-64ac425d1f8c4b3ba33df72b76bd09ae |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-11T08:39:38Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
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| spelling | doaj.art-64ac425d1f8c4b3ba33df72b76bd09ae2023-11-16T21:11:49ZengMDPI AGInformation2078-24892023-01-011426310.3390/info14020063Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions QuestionnaireSevilay Kilmen0Okan Bulut1Faculty of Nursing, University of Alberta, Edmonton, AB T6G 1C9, CanadaCentre for Research in Applied Measurement and Evaluation, University of Alberta, Edmonton, AB T6G 2G5, CanadaPsychological scales play a key role in the assessment, screening, and diagnosis of latent variables, such as emotions, mental health, and well-being. In practice, researchers need shorter scales of psychological traits to save administration time and cost. Thus, a variety of optimization algorithms have been proposed to abbreviate lengthy psychological scales into shorter instruments efficiently. The main goal of this application is to form an abbreviated scale with fewer items while maintaining reliability, relationships among the subscales, and model fit for the full scale. In this study, we use an optimization algorithm (genetic algorithm) and a feature selection algorithm (recursive feature elimination) to abbreviate a psychological scale automatically. Although both algorithms search for an optimal subset of features within a large pool of features, the search mechanism underlying each algorithm is quite different. The genetic algorithm employs a systematic but computationally-expensive sampling process to find the optimal features, whereas recursive feature elimination removes the least important features iteratively until a desired number of features are retained. In this study, we use a 77-item measure of test emotions (Test Emotions Questionnaire) to demonstrate how these algorithms can be used for scale abbreviation. We generate a 40-item short form using each algorithm and compare the quality of the selected items against the full-length scale. The results indicate that both methods can provide researchers and practitioners with a systematic procedure for creating psychometrically sound, shorter versions of lengthy psychological instruments.https://www.mdpi.com/2078-2489/14/2/63scale abbreviationrecursive feature eliminationgenetic algorithmstest emotions |
| spellingShingle | Sevilay Kilmen Okan Bulut Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire Information scale abbreviation recursive feature elimination genetic algorithms test emotions |
| title | Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire |
| title_full | Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire |
| title_fullStr | Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire |
| title_full_unstemmed | Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire |
| title_short | Scale Abbreviation with Recursive Feature Elimination and Genetic Algorithms: An Illustration with the Test Emotions Questionnaire |
| title_sort | scale abbreviation with recursive feature elimination and genetic algorithms an illustration with the test emotions questionnaire |
| topic | scale abbreviation recursive feature elimination genetic algorithms test emotions |
| url | https://www.mdpi.com/2078-2489/14/2/63 |
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