The effects of liking norms and descriptive norms on vegetable consumption: a randomised experiment

There is evidence that social norm messages can be used to promote the selection of fruit and vegetables in low habitual consumers of these foods but it is unclear whether this effect is sustained over time. It is also unclear whether information about others’ liking for a food (liking norm) could have the same effect. Using a 2 x 5 x 2 experimental design we investigated the effects of exposure to various messages on later intake from a food buffet and whether any effects were sustained 24 hours after exposure in both low and high consumers of vegetables. There were three factors: delay (immediate food selection versus food selection 24 hours after exposure), message type (liking norm, descriptive norm, health message, food-based vegetable variety control, and neutral control message) and habitual consumption (low versus high). The buffet consisted of three raw vegetables, three energy-dense foods and two dips. For vegetables and non-vegetables there were no main effects of message type, nor any main effect of delay. There was a significant message x habitual vegetable consumption interaction for vegetable consumption; however, follow up tests did not yield any significant effects. Examining each food individually, there were no main effects of message type, nor any main effect of delay, for any of the foods; however, there was a message x habitual vegetable consumption interaction for broccoli. Consumption of broccoli in the health message and descriptive norm conditions did not differ from the control neutral condition. However, habitually low consumers of vegetables increased their consumption of broccoli in the food-based vegetable variety control and liking norm conditions relative to habitual low vegetable consumers in the neutral control condition (p < 0.05). Further investigation of the effects of the liking norm and vegetable variety message on vegetable intake is warranted. This trial is listed as NCT02618174 at clinicaltrials.gov.