School Refusal Assessment Scale-Revised: Factorial invariance and latent means differences across gender and age in Spanish children
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The aim of this study was to analyze the factorial invariance and latent means differences of the Spanish version of the School Refusal Assessment Scale-Revised for Children (SRAS-R-C) in a sample of 1,078 students (50.8% boys) aged 8-11 years (M = 9.63, SD = 1.12). The results revealed that the proposed model in this study, with a structure of 18 items divided into four factors (Negative Affective, Social Aversion and/or Evaluation, To Pursue Attention and Tangible Reinforcements), was the best-fit model with a tetra-factorial structure, remaining invariant across gender and age. Analysis of latent means differences indicated that boys and 11-year-old students scored highest on the Tangible Reinforcements subscale compared with their 8- and 9- year-old peers. On the contrary, for the subscales of Social Aversion and/or Evaluation and to Pursue Attention, the differences were significant and higher in younger age groups compared to 11-year-olds. Appropriate indexes of reliability were obtained for SRAS-R-C subscales (.70, .79, .87 and .72). Finally, the founded correlation coefficients of scores of the SRAS-R-C revealed a predictable pattern between school refusal and positive/negative affect and optimism/pessimism.
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Gonzálvez et al. (2016) found that a three-factor model was the best fit for the SRAS.
“In the first of these, Gonzálvez et al. (2016) found that the three-factor model was the best fit.”
From Differentiation between school attendance problems: why and how? (2019) · cites this paper as Gonzálvez et al., 2016
Authors point to the complex or ambiguous wording of many of the items added to the SRAS to form the SRAS-R.
“Second, authors point to the complex or ambiguous wording of many of the items added to the SRAS to form the SRAS-R (Gonzálvez et al., 2016;Heyne et al., 2017;Knollmann et al., 2017).”
From Differentiation between school attendance problems: why and how? (2019) · cites this paper as Gonzálvez et al., 2016
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References 55 · Cited by 71
Research works printed but not linked: 4
- Byrne B. M. (2008a). Structural Equation Modeling with EQS: Basic Concepts, Applications and Programing, 2nd Edn New York, NY: Routledge Taylor & Francis Group.
- Fujigaki Y. (1996). The Association Between Feelings of School Avoidance and Friend Relationship Stressors – from the Standpoint of Self Image and Coping Strategies. Master’s thesis Nagoya University Graduate School of Education, Nagoya.
- Gisbert-Ferrándiz B. Vicent J. Gisbert- Ferrándiz A. Gonzálvez C. Lagos-San Martín N. (2013). “Optimismo, pesimismo y rechazo escolar [Optimism, pessimism and school refusal],” in Rechazo escolar y variables cognitivo-motivacionales y de personalidad. Symposium Nacional de Psicología Clínica y de la Salud con Niños y Adolescentes, ed. García-Fernández J. M.: Elche.
- Organisation for Economic Co-operation and Development (2012). PISA 2012. Programa Para la Evaluación Internacional de Los Alumnos. Informe Español. Resultados y Contexto [PISA 2012. Programme for International Assessment of Spanish Students: Results and Context], Vol. 1 Madrid: Ministerio de Educación, Cultura y Deporte.
- Authors
- Gonzálvez, C., Inglés, C. J., Kearney, C. A., Vicent, M., Sanmartín, R., & García-Fernández, J. M.
- Affiliations
- University of Alicante (ES)
- Universitat de Miguel Hernández d'Elx (ES)
- University of Nevada, Las Vegas (US)
- Corresponding author
- Gonzálvez, Carolina
- ORCID
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2016-12-26
- Volume
- 7
- Pages
- 2011-2011
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC5183572
- OpenAlex
- W2565678491
- Cited by
- 71
- References
- 55
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 10 · 2023: 5 · 2022: 2 · 2021: 8 · 2020: 10 · 2019: 12 · 2018: 13 · 2017: 5
- FWCI
- 44.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Scholarship - UNLV (University of Nevada Reno) (submittedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) (submittedVersion, other-oa)
- Funders
- Ministerio de Economía y Competitividad (EDU2012-35124)
- Universidad de Alicante (FPU, 2013-5795, FPU, 2015-5995)
- Generalitat Valenciana (VALi+d ACIF-2014-368)
- Topics
- Social Sciences › Education › Youth Substance Use and School Attendance
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Social Psychology › Bullying, Victimization, and Aggression
- Keywords
- school refusal, measurement invariance, gender differences, age differences, Spanish children, negative affect, social aversion, attention seeking, tangible reinforcement, optimism and pessimism, positive and negative affect, psychometric properties
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