Development and validation of a stock addiction inventory (SAI)

  • Hyun Chul Youn
  • , Jung Seok Choi
  • , Dai Jin Kim
  • , Sam Wook Choi

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Background: Investing in financial markets is promoted and protected by the government as an essential economic activity, but can turn into a gambling addiction problem. Until now, few scales have widely been used to identify gambling addicts in financial markets. This study aimed to develop a self-rating scale to distinguish them. In addition, the reliability and validity of the stock addiction inventory (SAI) were demonstrated. Methods: A set of questionnaires, including the SAI, south oaks gambling screen (SOGS), and DSM-5 diagnostic criteria, for gambling disorder was completed by 1005 participants. Factor analysis, internal consistency testing, t tests, analysis of variance, and partial correlation analysis were conducted to verify the reliability and validity of SAI. Results: The factor analysis results showed the final SAI consisting of two factors and nine items. The internal consistency and concurrent validity of SAI were verified. The Cronbach's α for the total scale was 0.892, and the SAI and its factors were significantly correlated with SOGS. Conclusions: This study developed a specific scale for financial market investments or trading; this scale proved to be reliable and valid. Our scale expands the understanding of gambling addiction in financial markets and provides a diagnostic reference.

Original languageEnglish
Article number16
JournalAnnals of General Psychiatry
Volume15
Issue number1
DOIs
StatePublished - 28 Jul 2016

Bibliographical note

Publisher Copyright:
© 2016 The Author(s).

Keywords

  • Behavioral addiction
  • Financial markets
  • Gambling addiction
  • Stock addiction inventory
  • Stock investments
  • Trading

Fingerprint

Dive into the research topics of 'Development and validation of a stock addiction inventory (SAI)'. Together they form a unique fingerprint.

Cite this