Behavioural data analysis

All statistical inferences are conducted on a significance level of 5%. Incorrect trials were excluded from all analyses (2.52%). Reaction times above 2000 ms and below 200 ms for the movement onset as well as reaction times above 4000 ms for the collection time on the touchscreen and in the VR were considered premature/incorrect. Movement onset is defined as the time between the presentation of the objects and the movement onset. Collection time is the time span after the participant’s hand has left the start position until the participant’s hand with the critical target has reached the position above the collection box where the target gets dragged into. Further, values deviating more than 2.5 SD, from individual cell means were considered outlier responses. 2.78 percent of the trials in the VR and 2.98 percent of the trials at the touchscreen were excluded. Only reaction times were analyzed as the block design is expected to affect reaction times rather than error rates (Zeligman and Zivotofsky 2017). To account for individual differences in motor grasping of grasp-affordant objects, we decided to standardize the reaction times for the food and office objects in relation to the ball objects. As grasping ball objects resembles exclusively motor actions which have to be executed fast and in an automatic manner, this seems to be a valid baseline correction. Furthermore, the ball objects are less complex than the other objects and demand less cognitive functions like planning. Each trial was subtracted by the individual’s mean reaction time for ball objects. To measure effects of the different target stimuli on the manual grasping times in the VR compared to the touchscreen, the linear mixed model approach was used to account for individual differences in grasping food stimuli. All linear mixed models were calculated by the lme4-package of R (Bates et al. 2014). The linear mixed effect model approach contains a random effect for each subject which comprises the interindividual differences to the manipulated fixed effects, whereas the fixed effects are the averaged prediction of the fixed effects on the reaction times across all participants. To estimate the significance of each fixed effect log-likelihood tests between a linear mixed model with the fixed effect and a linear mixed model without the fixed effect were conducted. Two fixed effects were tested within the linear mixed model: the medium (VR vs. Touchscreen) and the category of the target stimuli (Food vs. Balls). Post hoc tests to test the different contrasts within a fixed effect of the linear mixed model, the lsmeans-package of R was used. This is based on the method of the least-squares means and post hoc tests are adjusted by Tukey method (Lenth 2016). To estimate the degrees of freedom of the post hoc tests, the Satterthwaite formula for degrees of freedom was used. Effect sizes for fixed effects were estimated by f² which can also be used in mixed linear models (Aiken et al. 1991; Lorah 2018).

An individual bias separately for movement onset and collection time for each participant was calculated by the difference of the ball-standardized reaction times of food objects and the ball-standardized reaction times of office tools:

(RT_Office − RT_Ball) − (RT_Food − RT_Ball). Therefore, a higher value indicates a more prominent shift towards food.

Further exploratory analysis with linear mixed models was carried out to investigate the impact of the valence differences of the two different objects that the participants faced during each trial on the reaction times towards food. For this, reaction times were aggregated across the participants. The difference score served as a fixed effect and a random intercept on each target stimulus was modelled.