Frontiers in Psychology (Nov 2016)

Personalized behavioral feedback for online gamblers: A real world empirical study

  • Michael Mario Auer,
  • Michael Mario Auer,
  • Mark Damien Griffiths,
  • Mark Damien Griffiths

DOI
https://doi.org/10.3389/fpsyg.2016.01875
Journal volume & issue
Vol. 7

Abstract

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Some gambling companies around the world have started to utilize responsible gambling tools to support their clientele gamble more responsibly (e.g., limit-setting tools, pop-up messages, personalized feedback). However, relatively few studies have evaluated whether such tools actually work. The present study examined whether the use of three types of information (i.e., personalized feedback, normative feedback, and/or a recommendation) could enable players to gamble more responsibly as assessed using three measures of behavior, i.e., theoretical loss (TL), amount of money wagered, and gross gaming revenue (GGR). By manipulating the three forms of information, data from six different groups of players were analyzed. The participant sample drawn from the population were those that had played at least one game for money on the Norsk Tipping online platform (Intaspill) during April 2015. A total of 17,452 players were randomly selected from 69,631 players that fulfilled the selection criteria. Gambling activity among the control group (who received no personalized feedback, normative feedback or no recommendation) was also compared with the other five groups that received information of some kind (personalized feedback, normative feedback and/or a recommendation). Results clearly showed that overall gambling behavior (as assessed by the three measures) was significantly higher in the control group than the other five groups. Players that received both personalized feedback and a recommendation decreased gambling behavior the most. It is concluded that personalized behavioral feedback can enable behavioral change in gambling but that normative feedback does not appear change behavior significantly more than personalized feedback.

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