Validation of a Self-Report Version of the German Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale (SWAN-DE-SB)

Blume, Friederike; Buhr, Lilly; Kuehnhausen, Jan; Köpke, Rieke; Weber, Lydia R.; Fallgatter, Andreas J.; Ethofer, Thomas; Gawrilow, Caterina

doi:10.31234/osf.io/x6bpd

Cited by 4 publications

(9 citation statements)

References 20 publications

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“…In studies using confirmatory factor analysis ( 31 , 35 , 51 , 52 ), bifactor models were reported to have a better fit than non-hierarchical models; however, similar to studies with other measures, the results suggested a strong and reliable general ADHD factor but mostly weak or unreliable specific factors. A single study under peer review ( 38 ) reported similar results for the new self-report version of the SWAN. Blume et al.…”

Section: Introductionmentioning

confidence: 71%

“…Blume et al. ( 38 ) reported good internal reliabilities for the German version (α = 0.85 – 0.90). Up to now, only the parent and teacher versions of the SWAN have been validated in the Hungarian language showing good internal consistencies (α = 0.87 – 0.93) and convergent validity with the Hyperactivity subscale of the Strengths and Difficulties Questionnaire [SDQ ( 53 )] ( r = 0.67 - 0.74) ( 30 ).…”

Section: Methodsmentioning

confidence: 99%

“…Originally, parent-, and teacher-report versions have been developed ( 20 ), and translated into several languages ( 30 , 31 , 33 – 37 ). More recently, Blume and colleagues ( 38 ) created a self-report version the German language, extending the SWAN family.…”

Section: Introductionmentioning

confidence: 99%

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Psychometric properties of the self-report version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale in a sample of Hungarian adolescents and young adults

Vajsz,

Paulina,

Trejo

et al. 2024

Front. Psychiatry

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The Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour Scale (SWAN) measures the full spectrum of attention and activity symptoms, not just the negative end of the distribution. Previous studies revealed strong psychometric properties of the parent and teacher report versions; however, there is little research on the new self-report form of the SWAN. Therefore, our research aimed to explore the psychometric characteristics of the SWAN self-report. A non-clinical sample of young women (N = 664, mean age: 20.01 years, SD: 3.08 years) completed the SWAN self-report, the Strengths and Difficulties Questionnaire (SDQ) and the Mental Health Continuum Short Form (MHC-SF). We tested several models using confirmatory factor analyses to assess the factorial validity of the SWAN self-report. Distributional characteristics, convergent, and predictive validity were assessed. A bifactor model with a general factor and a specific inattention factor (bifactor-1) provided the best fit in our data (CFI = 0.977, TLI/NFI = 0.972, RMSEA = 0.053 [90% CI: 0.047 – 0.059], SRMR = 0.061, ω = 0.90). The reliability of the general ADHD factor was good (ωh = 0.87), and the specific inattention factor was acceptable (ωh = 0.73). The distribution of the SWAN self-report scores did not differ from the normal distribution. A strong correlation between the SWAN and the SDQ Hyperactivity subscale was found. The analyses revealed good predictive validity. Our results suggest that the SWAN self-report is a valuable tool for assessing symptoms of ADHD in adolescents and young adults.

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Section: Introductionmentioning

confidence: 71%

Section: Methodsmentioning

confidence: 99%

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Psychometric properties of the self-report version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale in a sample of Hungarian adolescents and young adults

Vajsz,

Paulina,

Trejo

et al. 2024

Front. Psychiatry

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“…Responses using these alternatives were scored as missing. Items were derived from the German self-report version of the Strength and Weaknesses of ADHD Symptoms and Normal Behaviour Scale (SWAN-DE-SB; Blume et al, 2023). Mean scores across all items were used as an indicator of students' self-regulation at the lesson level.…”

Section: Self-regulation At the Lesson Levelmentioning

confidence: 99%

It Counts in Every Single Lesson: Between- and Within-Person Associations Between Student-Perceived Teaching Quality and Student Self-Regulation

Blume¹,

Schmiedek²

2023

Preprint

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The pivotal role of classroom interactions for the development of self-regulation has long been recognised (e.g., McClelland & Cameron, 2011; Vohs & Baumeister, 2011). However, previous research mainly addressed their role for between-student differences in self-regulation, ignoring variations within individuals (e.g., Blume, Irmer, et al., 2022). Additionally, classroom interactions were primarily conceptualised within the teacher-student interaction framework (e.g., Downer et al., 2010), disregarding the teaching quality framework (e.g., Praetorius et al., 2018). Furthermore, independent observers’ ratings were usually used, overlooking students’ perceptions. Here, we therefore investigated whether average and lesson-level student-perceived teaching quality (i.e., student support, classroom management, cognitive activation) is associated with student self-regulation in individual lessons. Additionally, we examined whether the strength of associations depended on students’ dispositional self-regulation. We analysed data from 64 students (Mage = 11.71, SDage = 0.93), which were collected using a baseline questionnaire (demographics, dispositional self-regulation) and 15 daily diaries. Daily, students reported on their self-regulation and perceived teaching quality in the last lesson that day. Findings showed positive associations between average and lesson-level student support and classroom management and student self-regulation in individual lessons. No associations were found between average and lesson-level cognitive activation and students’ self-regulation in individual lessons. The findings thus emphasise the role of average and lesson-level student-perceived teaching quality for student self-regulation in general and in individual lessons.

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“…Finally, self-regulation was measured using one item (i.e., "I am concentrating right now"), reflecting both the ability to direct attention to goal-relevant information and to inhibit responses to tempting or distracting stimuli. Scales assessing self-regulation as a trait similarly inquire about these abilities (e.g., Blume et al, 2020;Lidzba et al, 2013). Nevertheless, they additionally often also address children's motor activity, while also including items particularly dedicated to assess impulsiveness (e.g., "I can wait my turn").…”

Section: Limitations and Perspectivesmentioning

confidence: 99%

Day-to-Day Variation in Students’ Academic Success: The Role of Self-Regulation, Working Memory, and Achievement Goals

Blume¹,

Schmidt²,

Dirk³

et al. 2021

Preprint

Self Cite

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Self-regulation has been shown to be positively associated with school performance. Additionally, interrelations between self-regulation, working memory (WM), and achievement goals, in particular learning goals, have been established, as well as their associations with academic outcomes. It stands to reason that self-regulation, WM, and achievement goals are related on a day-to-day level, with implications for daily and long-term academic success. However, previous research largely considered between-person differences. Here, we therefore addressed the relations of daily self-regulation, WM, and achievement goals, and their relevance for daily and long-term academic success. Data were obtained through smartphone-based ambulatory assessments of 108 students (Mage=10.12, SDage=0.45) across 20 school days. Students reported about daily achievement goals prior to, daily self-regulation at, and daily academic success after school. Additionally, they informed about their report card grades at the end of the school year. Daily WM was assessed through two updating tasks at school. Results showed positive associations between daily learning goals (but neither performance-approach nor performance-avoidance goals), daily self-regulation, and WM. Together, daily learning goals and self-regulation uniquely contributed to daily academic success, while WM, performance-approach, and performance-avoidance goals did not. Average levels of WM, but neither achievement goals, nor self-regulation predicted report card grades. Results thus corroborate theoretical considerations on the importance of distinguishing self-regulation processes on between- and within-person levels. Further theoretical and practical implications are discussed.

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Validation of a Self-Report Version of the German Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale (SWAN-DE-SB)

Cited by 4 publications

References 20 publications

Psychometric properties of the self-report version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale in a sample of Hungarian adolescents and young adults

Psychometric properties of the self-report version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale in a sample of Hungarian adolescents and young adults

It Counts in Every Single Lesson: Between- and Within-Person Associations Between Student-Perceived Teaching Quality and Student Self-Regulation

Day-to-Day Variation in Students’ Academic Success: The Role of Self-Regulation, Working Memory, and Achievement Goals

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