Social media 'addiction': The absence of an attentional bias to social media stimuli

Abstract

Background and aims: Social media use has become a ubiquitous part of society, with 3.8 billion users worldwide. While research has shown that there are positive aspects to social media engagement (e.g. feelings of social connectedness and wellbeing), much of the focus has been on the negative mental health outcomes which are associated with excessive use (e.g. higher levels of depression/anxiety). While the evidence to support such negative associations is mixed, there is a growing debate within the literature as to whether excessive levels of social media use should become a clinically defined addictive behaviour.

Methods: Here we assess whether one hallmark of addiction, the priority processing of addiction related stimuli known as an 'attentional bias', is evident in a group of social media users (N = 100). Using mock iPhone displays, we test whether social media stimuli preferentially capture users' attention and whether the level of bias can be predicted by platform use (self-report, objective smartphone usage data), and whether it is associated with scores on established measures of social media engagement (SMES) and social media 'addiction' severity scales (BSNAS, SMAQ).

Results: Our findings do not provide support for a social media specific attentional bias. While there was a large range of individual differences in our measures of use, engagement, and 'addictive' severity, these were not predictive of, or associated with, individual differences in the magnitude of attentional capture by social media stimuli.

Conclusions: More research is required before social media use can be definitively placed within an addiction framework.

Keywords: addictive behaviour; attention; attentional bias; individual differences; social media use.

Fig. 1.

Due to copyright reasons we are not able to show examples of the actual trials used in the experiment, these used real smartphone app icons and mirrored a regular iPhone display very closely. Here we present a close approximation of the layout of the display on trials in each condition. (Left) Example trial from the baseline condition with no social media distractor. (Middle) Example trial from the ‘mere presence’ condition with a social media distractor present. (Right) Example trial from the ‘+notification’ condition in which social media distractors, and non-social media control distractors, were overlaid with a notification symbol

Fig. 2.

Condition 1 mean correct target response times (RTs) in the absence of a social media distractor app (black) and the presence of a social media distractor app (grey; Facebook, Twitter, Instagram, Snapchat). Error bars denote standard error of the mean

Fig. 3.

Condition 1 scatterplots showing Pearson's correlation coefficients for the level of attentional capture by the presence of a social media distractor app (i.e. RT cost; social media distractor app present RT – social media distractor app absent) and scores on the established social media engagement (SMES) and ‘addictive’ severity scales (BSNAS, SMAQ). Note: some of the n values are lower than the total user sample size for each platform as a small number of participants did not complete all sections of all of the questionnaires)

Fig. 4.

Condition 2 mean correct target response times (RTs) in the non-social media distractor app condition (black), in the non-social media distractor app + notification condition (dark blue), in the social media distractor app condition (grey), and the social media distractor app + notification condition (light blue). Error bars denote standard error of the mean.

Fig. 5.

Condition 2 scatterplots showing Pearson's correlation coefficients for the level of attentional capture by a social media distractor paired with a notification symbol (i.e. RT cost; social media distractor app + notification RT – social media distractor app RT) and scores on the established social media scales, the BSNAS (left), the SMAQ (middle), and the SMES (right), presented as a function of social media platform. Note: some of the n values are lower than the total user sample size for each platform as a small number of participants did not complete all sections of all of the questionnaires