Get Started Mobile-based approach bias modification versus pseudomodification for problematic usage of the internet in adolescents and young adults

Problematic usage of the internet (PUI) represents a growing public health concern, par-
ticularly among adolescents and young adults. Implicit cognitive mechanisms such as ap-
proach bias – automatic tendencies to approach rather than avoid addiction-related cues
– are considered important drivers of PUI. Approach bias modification (ApBM) aims to
counteract these tendencies through systematic retraining of stimulus–response contin-
gencies. Mobile-based ApBM has shown promising effects in reducing severity of PUI;
however, its mechanisms of change and superiority over non-specific factors remain un-
clear. This two-arm randomized controlled pilot trial will evaluate the feasibility and pre-
liminary efficacy of a 3-week mobile-based ApBM training (i.e., employing incompatible
stimulus-response contingencies) compared with a structurally identical pseudomodifi-
cation employing balanced (i.e., both compatible and incompatible) stimulus-response
contingencies among adolescents and young adults aged 16-25 years with elevated PUI
(Compulsive Internet Use Scale ≥30). A total of 60 participants will be randomized (1:1)
to either condition and complete training on personal mobile devices for 21 consecutive
days. Assessments at baseline, post-intervention, and 3-month follow-up will measure se-
verity of PUI and approach bias as primary outcomes. Secondary outcomes include inter-
net-related craving, motivation to change, psychological symptoms, and sleep quality. We
hypothesize that ApBM will show greater reductions in PUI and approach bias compared
with pseudomodification. Additionally, feasibility outcomes including adherence and at-
trition rates, blinding of group allocation, and psychometric properties of the mobile-
based approach bias assessment will be examined to inform the design of a fully powered
randomized controlled trial.

Project Duration

01.04.2026 - 31.12.2026

Project Lead 

Daniel Huth