An improved method for counting stressful life events (SLEs) when predicting mental health and wellness

Objective: Checklists for registering stressful life events (SLEs) generally correlate negatively, but weakly, with mental health outcome measures. Thus, the present study examined various methodological approaches for improving these relationships.

Design: A total of 1679 participants (women?=?943, men?=?736, M age-39.8) were randomly drawn from the general Norwegian population (response rate 34%). This prospective cohort study included two follow-ups at 10 (n?=?1181) and 23 months (n?=?942).

Main outcome measures: Satisfaction with life and absence of psychological distress (i.e. anxiety and depression) represented a joint measure for indexing ‘mental wellness’ (MW).

Results: A simple count of SLEs weakly predicted MW, as expected, whereas the addition of a moderator (i.e. manageability of the event) substantially improved predictive power. Four additional moderators were examined: duration, impact, help-seeking and time since onset, but these were non-significant after inserting manageability into the model. This SLE counting method also retained its predictive power after including multiple criterion-related variables that substantially adjusted the longitudinal statistical model.

Conclusion: This new SLE counting method exhibited a considerable improvement to predicting mental health and well-being. It is well suited for use in epidemiological research requiring a short SLE checklist format with high predictive power.     

Whose promises are worth more? How social status affects trust in promises

Promises are among the most widely used tools for increasing trust in social hierarchies; yet the effect of social status on trust in promises is unknown. Here we used a modified version of the Trust Game, in which participants, acting as Investors, were paired with Trustees of varying social status who were given the opportunity to promise (or not) to return at least half of the multiplied amount (i.e., 4 × the amount invested). No return feedback was provided. Participants invested more in partners who promised than those who did not or whose promise information was concealed. Importantly, in both lab-manipulated (Exps. 1–3: math-induced) and pre-existing (Exp. 4: university-based) hierarchies, participants invested more in promises given by high status than low status partners. Post-experiment measures suggest that this may be due to greater expectations of honesty for high status than low status others. Potential explanations and implications are discussed.     

Revising the Communication Mediation Model for a New Political Communication Ecology

A long tradition of research focuses on conversation as a key catalyst for community integration and a focal mediator of media influence on participation. Changes in media systems, political environments, and electoral campaigning demand that these influences, and the communication mediation model, be revised to account for the growing convergence of media and conversation, heightened partisan polarization, and deepening social contentiousness in media politics. We propose a revised communication mediation model that continues to emphasize the centrality of face‐to‐face and online talk in democratic life, while considering how mediational and self‐reflective processes that encourage civic engagement and campaign participation might also erode institutional legitimacy, foster distrust and partisan divergence, disrupting democratic functioning as a consequence of a new communication ecology.     

Initial validation of the trust of automated systems test (TOAST)

ABSTRACT

Trust is a key determinant of whether people rely on automated systems in the military and the public. However, there is currently no standard for measuring trust in automated systems. In the present studies, we propose a scale to measure trust in automated systems that is grounded in current research and theory on trust formation, which we refer to as the Trust in Automated Systems Test (TOAST). We evaluated both the reliability of the scale structure and criterion validity using independent, military-affiliated and civilian samples. In both studies we found that the TOAST exhibited a two-factor structure, measuring system understanding and performance (respectively), and that factor scores significantly predicted scores on theoretically related constructs demonstrating clear criterion validity. We discuss the implications of our findings for advancing the empirical literature and in improving interface design.     

Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model

Background/objectivePatients with major depressive disorder (MDD) have altered learning rates for rewards and losses in non-social learning paradigms. However, it is not well understood whether the ability to learn from social interactions is altered in MDD patients. Using reinforcement learning during the repeated Trust Game (rTG), we investigated how MDD patients learn to trust newly-met partners in MDD patients.MethodSixty-eight MDD patients and fifty-four controls each played as ‘investor’ and interacted with ten different partners. We manipulated both the level of trustworthiness by varying the chance of reciprocity (10, 30, 50, 70 and 90%) and reputation disclosure, where partners’ reputation was either pre-disclosed or hidden.ResultsOur reinforcement learning model revealed that MDD patients had significantly higher learning rates for losses than the controls in both the reputation disclosure and non-disclosure condition. The difference was larger when reputation was not disclosed than disclosed. We observed no difference in learning rates for gains in either condition.ConclusionsOur findings highlight that abnormal learning for losses underlies the social learning process in MDD patients. This abnormality is higher when situational unpredictability is high versus low. Our findings provide novel insights into social rehabilitation of MDD.