Skill‐based versus effort‐based task difficulty: A task‐analysis approach to the role of specific emotions in motivating difficult actions

We make a distinction between primarily effort-based and skilled-based tasks and examine the correspondence between emotion and task. We reverse attribution theory results wherein failure to expend effort engenders regret and accomplishing tasks with skill engenders pride, and propose these emotions as antecedents to effort-based and skill-based behaviors. Specifically, pride (regret) produces higher self-efficacy, behavioral intentions and sign-ups when the task (CPR training) is portrayed as skill-intensive (effort-intensive) compared to effort-intensive (skill-intensive) or easy. Our research highlights the value of integrating an attributional analysis of tasks into an appraisal theory of emotions and suggests mechanisms that might underlie this relationship.     

Age at menarche and digit ratio (2D:4D): relationships with body dissatisfaction, drive for thinness, and bulimia symptoms in women

This study examined the hypothesis that lower prenatal androgen exposure and earlier puberty are associated with more dysfunctional eating attitudes and behaviors. Relationships between both age at menarche (AAM) and 2D:4D (a marker of prenatal androgen exposure), and EDI-2-Body Dissatisfaction, EDI-2-Drive for Thinness, and EDI-2-Bulimia scores, were examined in women using correlations and regressions. Earlier menarche was associated with higher drive for thinness after controlling for BMI and negative affect, but only in women who were not exclusively heterosexual. Higher 2D:4D was associated with higher Bulimia and Body Dissatisfaction scores, but only in exclusively heterosexual women, and relationships disappeared when covariates were controlled. Later AAM and higher 2D:4D were unique predictors of higher Bulimia scores for exclusive heterosexuals when BMI was controlled. These findings suggest future research should examine sexual orientation as a mediator or moderator of prenatal and postnatal organizational hormonal effects on women's disordered eating attitudes and behaviors.     

Inanspruchnahme psychosozialer Versorgungsstrukturen

In spite of the high proportion of persons with a migration background in Germany, professional mental health care utilization by this population group still seems to be insufficient. This could be due to social as well as structural and individual barriers which impede the professional mental health care-seeking process. The heuristic Mental Health Action Process Approach (M-HAPA) model was developed in order to be able to empirically investigate the specific mechanism of action as well as the specific time of influence of these factors. An empirically supported model should possibly be able to justify targeted interventions. The M-HAPA model describes mental health care utilization behavior, combines the basic ideas of already existing models describing health behavior and health care utilization behavior as well as factors which are specifically relevant for the health care utilization behavior of persons with a migration background. This combination may serve as a basis for future research in the field of mental health care utilization behavior of persons with a migration background.     

Artificial Intelligence and Medical Humanities

The use of artificial intelligence in healthcare has led to debates about the role of human clinicians in the increasingly technological contexts of medicine. Some researchers have argued that AI will augment the capacities of physicians and increase their availability to provide empathy and other uniquely human forms of care to their patients. The human vulnerabilities experienced in the healthcare context raise the stakes of new technologies such as AI, and the human dimensions of AI in healthcare have particular significance for research in the humanities. This article explains four key areas of concern relating to AI and the role that medical/health humanities research can play in addressing them: definition and regulation of “medical” versus “health” data and apps; social determinants of health; narrative medicine; and technological mediation of care. Issues include data privacy and trust, flawed datasets and algorithmic bias, racial discrimination, and the rhetoric of humanism and disability. Through a discussion of potential humanities contributions to these emerging intersections with AI, this article will suggest future scholarly directions for the field.

     

Early evidence affects later decisions: Why evidence accumulation is required to explain response time data

Models of decision making differ in how they treat early evidence as it recedes in time. Standard models, such as the drift diffusion model, assume that evidence is gradually accumulated until it reaches a boundary and a decision is initiated. One recent model, the urgency gating model, has proposed that decision making does not require the accumulation of evidence at all. Instead, accumulation could be replaced by a simple urgency factor that scales with time. To distinguish between these fundamentally different accounts of decision making, we performed an experiment in which we manipulated the presence, duration, and valence of early evidence. We simulated the associated response time and error rate predictions from the drift diffusion model and the urgency gating model, fitting the models to the empirical data. The drift diffusion model predicted that variations in the evidence presented early in the trial would affect decisions later in that same trial. The urgency gating model predicted that none of these variations would have any effect. The behavioral data showed clear effects of early evidence on the subsequent decisions, in a manner consistent with the drift diffusion model. Our results cannot be explained by the urgency gating model, and they provide support for an evidence accumulation account of perceptual decision making.