![]() ![]() Initially, three of the authors independently reviewed and classified features in 10 apps and 10 browser extensions (for a total of 30 unique apps and 30 unique browser extensions) before comparing and discussing the feature categories identified and create the first iteration of the coding sheet. ‘reward/punishment’ (drawing on our previous work in this area (Lyngs 2018 a)). 2013 Orji and Moffatt 2018), with the prior expectation that the relevantįeatures would be usefully classified as subcategories of the mainįeature clusters ‘block/removal’, ‘self-tracking’, ‘goal advancement’ and ![]() Iteratively developed a coding sheet of feature categories (cf. Stawarz, Cox, and Blandford 2014, 2015 Stawarz et al. 4.3 Using the model directly to guide intervention research and designįollowing similar reviews, we coded functionality based on theĭescriptions, screenshots, and videos available on a tool’s store page.4.2 Gaps identified by the dual systems model.4.1 Research opportunities prompted by widely used or theoretically interesting design features.3.2.4 Mapping identified tool features to theory.3.1.3 Identifying Apps and Extensions to Analyse.3.1.2 Identifying Potentially Relevant Apps and Extensions.3.1.1 Initial Keyword Search and Data Clean Up.3 A review and analysis of current digital self-control tools. ![]()
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