I am interested in a particular class of warnings, but I don't know what to call them. The warnings are generated by tracking a user's specific usage patterns, and warns them when continued use of the current application could be detrimental to their health. I am not including the health warnings (such as for epilepsy due to flickering) that may appear at the start of some applications, since they do not involve tracking of behaviour.

I have only seen these kinds of "health warnings" displayed during the "loading screens" for some older games. The warnings were phrased in a subtle way (sometimes with humour), encouraging the user to take a break after a couple of hours of continued gaming.

More specifically, I am interested in the manifestation of compulsive checking behaviour (even on the less extreme side of the spectrum). Examples include:

  • Checking e-mail every minute (or more).
  • Checking for mobile text messages frequently.
  • Checking social media sites frequently.
  • Checking for correct meta data on large media libraries, one file at a time.

I have never seen an e-mail client that warns against excessive use. The obvious problem is how to define "excessive" in the first place? There are applications that allow blocking of applications to help you focus, that operate on an operating system level, but I have never seen the option (even optionally configurable) to detect and warn about usage inside the application itself.

The assumption is that it is good that people "become addicted" to your application. But, for a small percentage of users this could actually be bad for their physical/emotional well-being. I would be very interested in any research that discusses the efficacy of application-specific warnings to counteract such usage patterns

  • Interesting question. A lot of the things you list are things that give you a notification that there is something new, so for messages / social media I would look at my phone screen while it is locked to see if there is a new message icon. That would definitely be hard to track.
    – Franchesca
    Commented May 9, 2014 at 15:38
  • Interesting question! The Wii does this, btw. After x hours (or minutes) of play time you get an 'interstitial ad' that suggests maybe you go play outside for a bit. Does it work? I don't know. Another thought is making it a user-set option. Something akin to the browser plugins that let you block web sites for periods of times: lifehacker.com/5780575/…
    – DA01
    Commented May 9, 2014 at 16:00

1 Answer 1


If you should warn users is determined by your moral disposition on the subject and if it will work has too many variables such as the wording of the warning, the design and the frequency. As far as research, the most applicable would be split testing your users, in their environment with the definition of excessive use in relation to the users.

With that said, determining what excessive usage is could simply be gathering a baseline by averaging the usage of all users and then having a point to compare the current users usage to. At that point you could even develop different intensity levels of over usage alerts for different points above that average - light warning, warning, intervention.

There are a few mobile apps that share a similar and interesting curiosity:

There are also a large number of computer usage monitoring software, for example: RescueTime. These applications are managed by the user or the user's superior. However, for the intention of the software itself being the superior judgement with similar functionality of above mentioned software, the average usage monitoring would allow the software's judgement to be polymorphic and non biased.

  • In this particular case, I would be very hesitant about defining an "average user". I am aware of the blocking/focus software (as mentioned in my question). The question is mainly asking "If I detect a usage pattern that looks excessive according to some criterion, should I raise a warning? And if I do, will it actually make a difference?" I am specifically interested in answers backed by existing research.
    – CJF
    Commented May 9, 2014 at 16:44
  • I edited my reply Commented May 9, 2014 at 16:56

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