The Quality of Life for Children with Autism Spectrum Disorder Scale: Factor Analysis, MIMIC Modeling, and Cut-Off Score Analysis
Our purpose in this study was to further examine the psychometric properties of the Quality of Life for Children with Autism Spectrum Disorder (QOLASD-C) scale. We first investigated the factor structure and the internal consistency of the scale. The bifactor model showed good fit and strong reliabi...
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| Veröffentlicht in: | Journal of autism and developmental disorders 2023-08, Vol.53 (8), p.3230-3245 |
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| creator | Chezan, Laura C. Liu, Jin Drasgow, Erik Ding, Ruyi Magana, Alexandro |
| description | Our purpose in this study was to further examine the psychometric properties of the Quality of Life for Children with Autism Spectrum Disorder (QOLASD-C) scale. We first investigated the factor structure and the internal consistency of the scale. The bifactor model showed good fit and strong reliability. Second, we used multiple-indicators multiple-causes (MIMIC) modeling to examine the associations between demographic variables and the QOLASD-C dimensions. Results showed differences on overall QOL based on age, race/ethnicity, and autism spectrum disorder severity, but no relationships with gender. All demographic variables were associated with one or all three subscales (i.e., interpersonal relationships, self-determination, emotional well-being) of the QOLASD-C. Third, an optimal cut-off score of 37 was identified. Implications for research and practice are discussed. |
| doi_str_mv | 10.1007/s10803-022-05610-2 |
| format | Article |
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We first investigated the factor structure and the internal consistency of the scale. The bifactor model showed good fit and strong reliability. Second, we used multiple-indicators multiple-causes (MIMIC) modeling to examine the associations between demographic variables and the QOLASD-C dimensions. Results showed differences on overall QOL based on age, race/ethnicity, and autism spectrum disorder severity, but no relationships with gender. All demographic variables were associated with one or all three subscales (i.e., interpersonal relationships, self-determination, emotional well-being) of the QOLASD-C. Third, an optimal cut-off score of 37 was identified. Implications for research and practice are discussed.</description><identifier>ISSN: 0162-3257</identifier><identifier>EISSN: 1573-3432</identifier><identifier>DOI: 10.1007/s10803-022-05610-2</identifier><identifier>PMID: 35657447</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Age Differences ; Autism ; Autism Spectrum Disorders ; Autistic children ; Behavioral Science and Psychology ; Care and treatment ; Child and School Psychology ; Cutting Scores ; Demography ; Diagnosis ; Emotional well being ; Ethnicity ; Factor analysis ; Factor Structure ; Gender Differences ; Goodness of Fit ; Health aspects ; Interpersonal relations ; Interpersonal Relationship ; Measures (Individuals) ; Neurosciences ; Original Paper ; Pediatrics ; Pervasive developmental disorders ; Psychological aspects ; Psychology ; Psychometrics ; Public Health ; Quality of Life ; Quantitative psychology ; Race ; Reliability ; Self Determination ; Severity (of Disability) ; Well Being</subject><ispartof>Journal of autism and developmental disorders, 2023-08, Vol.53 (8), p.3230-3245</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><rights>COPYRIGHT 2023 Springer</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c536t-77473a2eb88f262c627d66cd955d8d4123d141741481d85f298abe4289ae690d3</citedby><cites>FETCH-LOGICAL-c536t-77473a2eb88f262c627d66cd955d8d4123d141741481d85f298abe4289ae690d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10803-022-05610-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10803-022-05610-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,12826,27903,27904,30978,41467,42536,51297</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1382992$$DView record in ERIC$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35657447$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chezan, Laura C.</creatorcontrib><creatorcontrib>Liu, Jin</creatorcontrib><creatorcontrib>Drasgow, Erik</creatorcontrib><creatorcontrib>Ding, Ruyi</creatorcontrib><creatorcontrib>Magana, Alexandro</creatorcontrib><title>The Quality of Life for Children with Autism Spectrum Disorder Scale: Factor Analysis, MIMIC Modeling, and Cut-Off Score Analysis</title><title>Journal of autism and developmental disorders</title><addtitle>J Autism Dev Disord</addtitle><addtitle>J Autism Dev Disord</addtitle><description>Our purpose in this study was to further examine the psychometric properties of the Quality of Life for Children with Autism Spectrum Disorder (QOLASD-C) scale. We first investigated the factor structure and the internal consistency of the scale. The bifactor model showed good fit and strong reliability. Second, we used multiple-indicators multiple-causes (MIMIC) modeling to examine the associations between demographic variables and the QOLASD-C dimensions. Results showed differences on overall QOL based on age, race/ethnicity, and autism spectrum disorder severity, but no relationships with gender. All demographic variables were associated with one or all three subscales (i.e., interpersonal relationships, self-determination, emotional well-being) of the QOLASD-C. Third, an optimal cut-off score of 37 was identified. Implications for research and practice are discussed.</description><subject>Age Differences</subject><subject>Autism</subject><subject>Autism Spectrum Disorders</subject><subject>Autistic children</subject><subject>Behavioral Science and Psychology</subject><subject>Care and treatment</subject><subject>Child and School Psychology</subject><subject>Cutting Scores</subject><subject>Demography</subject><subject>Diagnosis</subject><subject>Emotional well being</subject><subject>Ethnicity</subject><subject>Factor analysis</subject><subject>Factor Structure</subject><subject>Gender Differences</subject><subject>Goodness of Fit</subject><subject>Health aspects</subject><subject>Interpersonal relations</subject><subject>Interpersonal Relationship</subject><subject>Measures (Individuals)</subject><subject>Neurosciences</subject><subject>Original Paper</subject><subject>Pediatrics</subject><subject>Pervasive developmental disorders</subject><subject>Psychological 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| subjects | Age Differences Autism Autism Spectrum Disorders Autistic children Behavioral Science and Psychology Care and treatment Child and School Psychology Cutting Scores Demography Diagnosis Emotional well being Ethnicity Factor analysis Factor Structure Gender Differences Goodness of Fit Health aspects Interpersonal relations Interpersonal Relationship Measures (Individuals) Neurosciences Original Paper Pediatrics Pervasive developmental disorders Psychological aspects Psychology Psychometrics Public Health Quality of Life Quantitative psychology Race Reliability Self Determination Severity (of Disability) Well Being |
| title | The Quality of Life for Children with Autism Spectrum Disorder Scale: Factor Analysis, MIMIC Modeling, and Cut-Off Score Analysis |
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