Title |
Simple construct evaluation with latent class analysis: An investigation of Facebook addiction and the development of a short form of the Facebook Addiction Test (F-AT)
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Published in |
Behavior Research Methods, March 2016
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DOI | 10.3758/s13428-016-0716-2 |
Pubmed ID | |
Authors |
Michael Dantlgraber, Eunike Wetzel, Petra Schützenberger, Stefan Stieger, Ulf-Dietrich Reips |
Abstract |
In psychological research, there is a growing interest in using latent class analysis (LCA) for the investigation of quantitative constructs. The aim of this study is to illustrate how LCA can be applied to gain insights on a construct and to select items during test development. We show the added benefits of LCA beyond factor-analytic methods, namely being able (1) to describe groups of participants that differ in their response patterns, (2) to determine appropriate cutoff values, (3) to evaluate items, and (4) to evaluate the relative importance of correlated factors. As an example, we investigated the construct of Facebook addiction using the Facebook Addiction Test (F-AT), an adapted version of the Internet Addiction Test (I-AT). Applying LCA facilitates the development of new tests and short forms of established tests. We present a short form of the F-AT based on the LCA results and validate the LCA approach and the short F-AT with several external criteria, such as chatting, reading newsfeeds, and posting status updates. Finally, we discuss the benefits of LCA for evaluating quantitative constructs in psychological research. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 40% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 2 | 40% |
Members of the public | 2 | 40% |
Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 2% |
Unknown | 52 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 15% |
Student > Master | 8 | 15% |
Researcher | 7 | 13% |
Student > Bachelor | 4 | 8% |
Student > Doctoral Student | 4 | 8% |
Other | 12 | 23% |
Unknown | 10 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 22 | 42% |
Social Sciences | 7 | 13% |
Medicine and Dentistry | 5 | 9% |
Computer Science | 2 | 4% |
Mathematics | 1 | 2% |
Other | 5 | 9% |
Unknown | 11 | 21% |