From Academia: Developing a Scale for Tinder Addiction

27th September 2018 Scott Harvey

2016 Research in the Journal of Behavioural Addictions works to develop a Problematic Tinder Use Scale.

The study notes that despite plenty of anecdotal evidence existing which describes dating app addiction, little quantitative work has been done in the field.

The study, building on other work on the science of addiction, outlines a six-part model for problematic Tinder use.

The components of the model are as follows:

1. Salience (Tinder use dominates thinking and behaviour)

1. Mood modification (Tinder use modifies/improves mood)

1. Tolerance (increasing amounts of Tinder use are required)

1. Withdrawal (occurrence of unpleasant feelings when Tinder use is discontinued)

1. Conflict (Tinder use compromises social relationships and other activities)

Relapse (tendency for reversion to earlier patterns of Tinder use after abstinence or control)

430 Hungarians aged 18-51 participated in the study.

In the discussion, some of the features of Tinder which merit the development of an addiction scale are outlined:

“Tinder has a fast and strong rewarding value, because individuals can get immediate social appreciation especially about their appearance in terms of positive feedbacks.

“The more time is spent on Tinder, the more positive feedback can be received. There is a practically limitless possibility of choices of potential dating partners which can make it harder to stop Tinder use.

“Small effort is needed for creating a profile and it is extremely easy to use this application on a smartphone.

“Users can see the closeness of the potential partners and in case of success; a relatively commitment-free immediate date can be the anticipated “reward”.

“These aspects of Tinder use can contribute to mood modification, salience, tolerance and relapse which are the main pillars of problematic use.

The authors note that problematic Tinder use may be related to problematic internet use more generally.

Further research could look into whether users recording problematic levels of engagement on one scale are more likely to record problematic levels on the other.