When mere action versus inaction leads to robust preference change.

Abstract

for assistance with data collection; Fabienne Voncken, Simke van Oijen and Sjors van de Schoot for creating the candy images; Xin Gao, Haokui Xu and members of the Food Choice on Impulse lab for helpful comments on earlier versions of the manuscript. The data of Experiments 1 and 2 have been reported in a master thesis by Linda Schmale at the University of Amsterdam. The data of Experiments 5 and 6 have been reported in bachelor theses by Roos Greven and Evert Palm at Radboud University. The data of Experiment 7 have been reported in bachelor theses by Wouter Aarts, Michelle de With and Gerden Ibrahim at Radboud University. Parts of the data reported here have been presented at the 2016 and 2017 annual meetings of Dutch Association of Social Psychology (ASPO; the Netherlands, 2016 and 2017), and the preconference on the self-regulation of health at the 18th General Meeting of the European Association of Social Psychology (Spain, 2017) by the first author.

Cognitive training on eating behaviour and weight loss: A meta‐analysis and systematic review

“…This approach‐healthy association might attach greater value to healthy food cues, resulting in greater choice of healthy food. Indeed, studies have found that participants chose to consume healthy foods more often when those participants were trained to respond to healthy food items without responding to other items. In short, although we did not find evidence for a main effect of approach/avoidance training on eating behaviour, some evidence suggests that approach/avoidance training focused on approach of healthy food might be an effective means of increasing the relative consumption of healthy food to unhealthy food.…”

Beyond inhibitory control training: Inactions and actions influence smartphone app use through changes in explicit liking.

“…There were no visual or formal outliers to test for robustness of the model. We were also interested whether the effect of the training would differ for different choice reaction times, as previous research has observed that the choice effect becomes weaker the more time participants take (Chen et al, 2019). However, although the coefficient was negative, reaction times were not a significant predictor of app choice χ 2 = .2.23, p = .135.…”

Updating the p-curve analysis of Carbine and Larson with results from preregistered experiments

“…Furthermore, we have substantially increased the amount of measurements we collect from each participant (e.g., they make many food choices) and moved from between-subjects to within-subjects designs when possible. By applying such procedures, we are able to consistently find effects of executing or withholding simple motor responses on food evaluation (e.g., Chen, Veling, Dijksterhuis, & Holland, 2016; and choice (Chen et al, 2019). A challenge for future work is to develop reliable experimental procedures for other outcomes than food evaluation or choice (e.g., food intake or weight loss), which can further contribute to evaluating the evidential value of ICT.…”

“…In our lab we recently conducted a series of seven preregistered well-powered experiments where we assessed effects of the go/no-go training, a widely used inhibitory control training, on food choice (Chen, Holland, Quandt, Dijksterhuis, & Veling, 2019). The aim of this research project was to obtain a high-quality data set of effects of go/no-go training on food choice.…”

“…See Figure 1 for the results of this original p-curve analysis. Chen et al (2019) have reported seven experiments on effects of go/no-go training on food choice. Two experiments revealed statistically non-significant results (Experiments 1 and 3 where participants chose with unlimited decision time) and were therefore unsuitable for the updated p-curve analysis.…”