Investigating the Comparability of Two Multi-Item-Scales for Cyber Bullying Measurement
Bibliographic Data
| ID | 15471976 |
|---|---|
| Authors | Julia Fluck (University of Koblenz and Landau, corresponding author) |
| Year | 2018 |
| Volume | 15 |
| Issue | 11 |
| Pages | 2356-2356 |
| Publication date | 2018-10-25 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph15112356 |
| PMID | 30366413 |
| OpenAlex | W2898259529 |
| Language | EN |
| Citations received | 2 |
| References cited | 26 |
In current cyberbullying literature, researchers assess the phenomenon using a large variety of measurement approaches. This poses a problem in light of comparability of study results. The most common approaches are singular global questions or multi-item scales that list several forms of cyberbullying. Such lists contain either different types of actions or different types of media. This study explores different measurement approaches. Two multi-item scales, one listing different actions and one listing different media, are compared to investigate whether they measure the same latent construct. Confirmatory factor analysis is used to model one factor for each of the multi-item scales. In the first study, the items cover victimization experiences while in the second study they cover estimation of severity. Results show that the two different multi-item scales measure the same latent construct. These results have a substantial impact on the future of cyberbullying research with regard to study comparability
Comparability · Confirmatory factor analysis · Construct (python library · Construct validity · Data mining · Data science · Econometrics · Listing (finance · Machine learning · Measure (data warehouse · Measurement invariance · Psychometrics · Structural equation modeling · Bullying, Victimization, and Aggression · Clinical Psychology · Computer Science · Hate Speech and Cyberbullying Detection · Mathematics · Plant Virus Research Studies · Psychology
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| Citations per year | 0.33 |
|---|---|
| Citation span | 2020 - 2021 (2) |
| Highly cited | No |