Pushing Notifications as Dynamic Information Design

We study the dynamic information design problem of a firm seeking to influence consumer checking behavior by designing push notifications.

The Association of Muscle Dysmorphia, Social Physique Anxiety, and Body Checking Behavior in Male College Students With Weight Exercise

Objectives: To investigate the association between muscle dysmorphia (MD), social physique anxiety, and body-checking behavior in male college students with weight exercise, and to reveal the association between them.Methods: A total of 492 male college students with weight exercise from 18 Fitness Clubs or bodybuilding centers in Chengdu, China, participated in this study.Results: First, the social physique anxiety scores, body checking frequency, and weight exercise behavior (i.e., frequency, time, and intensity) in male college students with MD were significantly higher than those without MD; it indicated that the higher the exercise frequency they had, the longer the exercise time they cost, and the higher exercise intensity carried out, and the higher the social physique anxiety scores tended to be, the higher the frequency of body checking on “global muscles,” “chest and shoulder muscles,” “comparison with others” and “posture measurement” they did. Second, the mediating effect of the social physique anxiety on MD and body checking was established in the “MD → global muscle checking,” “MD → chest and shoulder muscle checking,” “MD → comparison with others,” and “muscle dysmorphia → posture measurement.”Conclusion: Male college students with MD not only have a higher social physique anxiety, but also a higher frequency of body-checking behavior than the ordinary individuals. Social physique anxiety is one of the important mediating factors to those with MD which affects the body-checking behavior.

Joint contributions of metacognition and self-beliefs to uncertainty-guided checking behavior

Checking behavior is a natural and adaptive strategy for resolving uncertainty in everyday situations. Here, we aimed at investigating the psychological drivers of checking and its regulation by uncertainty, in non-clinical participants and controlled experimental settings. We found that the sensitivity of participants’ explicit confidence judgments to actual performance (explicit metacognition) predicted the extent to which their checking strategy was regulated by uncertainty. Yet, a more implicit measure of metacognition (derived from asking participants to opt between trials) did not contribute to the regulation of checking behavior. Meanwhile, how participants scaled on questionnaires eliciting self-beliefs such as self-confidence and self-reported obsessive–compulsive symptoms also predicted participants’ uncertainty-guided checking tendencies. Altogether, these findings demonstrate that checking behavior is likely the outcome of a core explicit metacognitive process operating at the scale of single decisions, while remaining influenced by general self-beliefs. Our findings are thus consistent with two mechanisms (micro vs. macro) through which this otherwise adaptive behavior could go awry in certain psychiatric disorders such as obsessive–compulsive disorder.

Mice are not automatons; subjective experience in premotor circuits guides behavior

Subjective experience is a powerful driver of decision-making and continuously accrues. However, most neurobiological studies constrain analyses to task-related variables and ignore how continuously and individually experienced internal, temporal, and contextual factors influence adaptive behavior during decision-making and the associated neural mechanisms. We show mice rely on learned information about recent and longer-term subjective experience of variables above and beyond prior actions and reward, including checking behavior and the passage of time, to guide self-initiated, self-paced, and self-generated actions. These experiential variables were represented in secondary motor cortex (M2) activity and its projections into dorsal medial striatum (DMS). M2 integrated this information to bias strategy-level decision-making, and DMS projections used specific aspects of this recent experience to plan upcoming actions. This suggests diverse aspects of experience drive decision-making and its neural representation, and shows premotor corticostriatal circuits are crucial for using selective aspects of experiential information to guide adaptive behavior.

Joint contribution of metacognition and self-beliefs to uncertainty-guided checking behavior

Checking behavior is a natural and adaptive strategy in uncertain situations. Here, we aimed at investigating the psychological drivers of checking and its regulation by uncertainty, in non-clinical participants and controlled experimental settings. We found that the sensitivity of participants’ explicit confidence judgments to actual performance (explicit metacognition) predicted the extent to which their checking strategy was regulated by uncertainty. This was, however, not the case of how participants used confidence to guide subsequent decision-making (implicit metacognition). Meanwhile, how participants scaled on questionnaires eliciting self-beliefs such as self-confidence and self-reported obsessive-compulsive symptoms also predicted participants’ uncertainty-guided checking tendencies. Altogether, these findings demonstrate that checking is likely the outcome of a core metacognitive process operating at the scale of single decisions, while remaining influenced by general self-beliefs. Our findings thus propose two mechanisms (micro vs. macro) through which this otherwise rational behavior could go awry in certain psychiatric disorders such as obsessive-compulsive disorder.

Issues in Survey Development: Assumption Checking, Behavior Coding, Cognitive Interviewing, and Design Testing

Survey research can benefit from pretesting and greatly enhance the effectiveness of data collection and analytic processes. For this purpose, a comprehensive process involving four aspects of testing is proposed, namely, assumption checking, behavior coding, cognitive interviewing, and design testing. In this article, I briefly explain each aspect with relevant illustrations.