Neurophysiological Profile of Antismoking Campaigns.
Enrica ModicaDario RossiGiulia CartocciDavide PerrottaPaolo Di FeoMarco ManciniPietro AricòBianca M S InguscioFabio BabiloniPublished in: Computational intelligence and neuroscience (2018)
Over the past few decades, antismoking public service announcements (PSAs) have been used by governments to promote healthy behaviours in citizens, for instance, against drinking before the drive and against smoke. Effectiveness of such PSAs has been suggested especially for young persons. By now, PSAs efficacy is still mainly assessed through traditional methods (questionnaires and metrics) and could be performed only after the PSAs broadcasting, leading to waste of economic resources and time in the case of Ineffective PSAs. One possible countermeasure to such ineffective use of PSAs could be promoted by the evaluation of the cerebral reaction to the PSA of particular segments of population (e.g., old, young, and heavy smokers). In addition, it is crucial to gather such cerebral activity in front of PSAs that have been assessed to be effective against smoke (Effective PSAs), comparing results to the cerebral reactions to PSAs that have been certified to be not effective (Ineffective PSAs). The eventual differences between the cerebral responses toward the two PSA groups will provide crucial information about the possible outcome of new PSAs before to its broadcasting. This study focused on adult population, by investigating the cerebral reaction to the vision of different PSA images, which have already been shown to be Effective and Ineffective for the promotion of an antismoking behaviour. Results showed how variables as gender and smoking habits can influence the perception of PSA images, and how different communication styles of the antismoking campaigns could facilitate the comprehension of PSA's message and then enhance the related impact.
Keyphrases
- prostate cancer
- subarachnoid hemorrhage
- radical prostatectomy
- healthcare
- mental health
- deep learning
- randomized controlled trial
- cerebral ischemia
- systematic review
- optical coherence tomography
- risk assessment
- smoking cessation
- middle aged
- machine learning
- brain injury
- emergency department
- convolutional neural network
- heavy metals
- social media
- psychometric properties