Enjoy! Assertive Language and Consumer Compliance in (Non)Hedonic Contexts

This paper is concerned with the tension between consumer persuasion and freedom of choice. We study how assertive language (as in the slogan Just do it!) affects consumer compliance in hedonic vs. utilitarian contexts. Previous literature consistently claimed that forceful language would cause reactance and decreased compliance. However, we find in four studies that assertive persuasion is effective in contexts involving hedonic goods and hedonically framed utilitarian goods. Our hypotheses emerge from sociolinguistic research and confirm the relevance of linguistic research in consumer behavior

Gambling Problems among Community Cocaine Users

Cocaine use is highly prevalent and a major public health problem. While some studies have reported frequent comorbidity problems among cocaine users, few studies have included evaluation of gambling problems. This study aimed to estimate the prevalence of gambling problems and compare those who were at-risk gamblers with non-problem gamblers in terms of mental health problems, substance use problems, and some risk factors (i.e. family antecedents, erroneous perceptions and coping strategies) among individuals who smoke or inject cocaine. METHOD: A total of 424 smoked or injected cocaine users recruited through community-based programs in Montreal, Quebec completed the questionnaire, including the Canadian Pathological Gambling Index, the Composite International Diagnostic Interview (CIDI), the CAGE, and the Severity Dependence Scale (SDS). RESULTS: Of the sample, 18.4 % were considered at-risk gamblers, of whom 7.8 % had problems gambling and 10.6 % were moderate-risk gamblers. The at-risk group was more likely to have experienced a recent phobic disorder and alcohol problems than the non-problem group. A multivariate analysis showed that, compared to those who were non-problem gamblers, the at-risk ones were more likely to have lost a large sum of money when they first started gambling, believed that their luck would turn, and gambled in reaction to painful life events. These results indicate the need to include routines for screening to identify gambling problem among cocaine user

Some but not all dispreferred turn markers help to interpret scalar terms in polite contexts

International audienceIn polite contexts, people find it difficult to perceive whether they can derive scalar inferences from what others say (e.g., does “some people hated your idea” mean that not everyone hated it?). Because this uncertainty can lead to costly misunderstandings, it is important to identify the cues people can rely on to solve their interpretative problem. In this article, we consider two such cues: Making a long Pause before the statement, and prefacing the statement with Well. Data from eight experiments show that Pauses are more effective than Wells as cues to scalar inferences in polite contexts—because they appear to give a specific signal to switch expectations in the direction of bad news, whereas Well appears to give a generic signal to make extra processing effort. We consider the applied value of these findings for human–human and human–machine interaction, as well as their implications for the study of reasoning and discours

Testing the Acceptability of Social Support Agents in Online Communities

This paper describes the first steps towards development and evaluation of an 'artificial friend', i.e., an intelligent agent that provides support via text messages in social media in order to alleviate the stress that users experience as a result of everyday problems. The agent consists of three main components: (1) a module that processes text messages based on text mining and classifies them into categories of problems, (2) a module that selects appropriate support strategies based on a validated psychological model of emotion regulation, and (3) a module that generates appropriate responses based on the output of the first two modules. The application has been tested in a pilot study involving 33 participants that were asked to interact with different variants of the agent via the social network Telegram. The results provide hints that the agent is appreciated over a baseline version that generates random support messages, but also point at some possibilities to further improve the agent