Samuel S. Monfort

Placebo effects in cognitive training

Significance Placebo effects pose problems for some intervention studies, particularly those with no clearly identified mechanism. Cognitive training falls into that category, and yet the role of placebos in cognitive interventions has not yet been critically evaluated. Here, we show clear evidence of placebo effects after a brief cognitive training routine that led to significant fluid intelligence gains. Our goal is to emphasize the importance of ruling out alternative explanations before attributing the effect to interventions. Based on our findings, we recommend that researchers account for placebo effects before claiming treatment effects. Although a large body of research shows that general cognitive ability is heritable and stable in young adults, there is recent evidence that fluid intelligence can be heightened with cognitive training. Many researchers, however, have questioned the methodology of the cognitive-training studies reporting improvements in fluid intelligence: specifically, the role of placebo effects. We designed a procedure to intentionally induce a placebo effect via overt recruitment in an effort to evaluate the role of placebo effects in fluid intelligence gains from cognitive training. Individuals who self-selected into the placebo group by responding to a suggestive flyer showed improvements after a single, 1-h session of cognitive training that equates to a 5- to 10-point increase on a standard IQ test. Controls responding to a nonsuggestive flyer showed no improvement. These findings provide an alternative explanation for effects observed in the cognitive-training literature and the brain-training industry, revealing the need to account for confounds in future research.

A Contextual Approach to Experiential Avoidance and Social Anxiety: Evidence From an Experimental Interaction and Daily Interactions of People With Social Anxiety Disorder

Experiential avoidance (EA), the tendency to avoid internal, unwanted thoughts and feelings, is hypothesized to be a risk factor for social anxiety. Existing studies of experiential avoidance rely on trait measures with minimal contextual consideration. In two studies, we examined the association between experiential avoidance and anxiety within real-world social interactions. In the first study, we examined the effect of experiential avoidance on social anxiety in everyday life. For 2 weeks, 37 participants with Social Anxiety Disorder (SAD) and 38 healthy controls provided reports of experiential avoidance and social anxiety symptoms during face-to-face social interactions. Results showed that momentary experiential avoidance was positively related to anxiety symptoms during social interactions and this effect was stronger among people with SAD. People low in EA showed greater sensitivity to the level of situational threat than high EA people. In the second study, we facilitated an initial encounter between strangers. Unlike Study 1, we experimentally created a social situation where there was either an opportunity for intimacy (self-disclosure conversation) or no such opportunity (small-talk conversation). Results showed that greater experiential avoidance during the self-disclosure conversation temporally preceded increases in social anxiety for the remainder of the interaction; no such effect was found in the small-talk conversation. Our findings provide insight into the association between experiential avoidance on social anxiety in laboratory and naturalistic settings, and demonstrate that the effect of EA depends upon level of social threat and opportunity.

Almost human: Anthropomorphism increases trust resilience in cognitive agents.

We interact daily with computers that appear and behave like humans. Some researchers propose that people apply the same social norms to computers as they do to humans, suggesting that social psychological knowledge can be applied to our interactions with computers. In contrast, theories of human–automation interaction postulate that humans respond to machines in unique and specific ways. We believe that anthropomorphism—the degree to which an agent exhibits human characteristics—is the critical variable that may resolve this apparent contradiction across the formation, violation, and repair stages of trust. Three experiments were designed to examine these opposing viewpoints by varying the appearance and behavior of automated agents. Participants received advice that deteriorated gradually in reliability from a computer, avatar, or human agent. Our results showed (a) that anthropomorphic agents were associated with greater trust resilience, a higher resistance to breakdowns in trust; (b) that these effects were magnified by greater uncertainty; and c) that incorporating human-like trust repair behavior largely erased differences between the agents. Automation anthropomorphism is therefore a critical variable that should be carefully incorporated into any general theory of human–agent trust as well as novel automation design.

Anxiety symptoms and functional impairment: A systematic review of the correlation between the two measures

Researchers and clinicians assume a strong, positive correlation between anxiety symptoms and functional impairment. That assumption may be well-justified since diagnostic criteria typically include functional impairment. Still, the relationship remains largely unavailable in any systematic review. Our aim with this paper was to provide empirical evidence for this assumed relationship and to document the observed correlations between anxiety symptom measures and functional impairment measures. Correlations existed for symptoms of six anxiety disorders (Panic Disorder, Agoraphobia, Social Anxiety Disorder, Post-Traumatic Stress Disorder, Generalized Anxiety Disorder, Obsessive Compulsive Disorder) across four functional domains (global, social, occupational, and physical). Overall, the mean of 497 correlations across all disorders and functional domains was modest (r=.34); since the variability between disorders and functional domains tended to be rather large, we explored these correlations further. We presented these results and the potential explanations for unexpected findings along with the clinical and research implications.

A longitudinal examination of re-employment quality on internalizing symptoms and job-search intentions.

Underemployed workers-those receiving less pay, working fewer hours, or using fewer skills than they would prefer-appear to experience negative mental health outcomes similar to the unemployed. Prior cross-sectional research provides mixed empirical evidence for this conclusion, however. The current study sought to clarify the impact of underemployment longitudinally, assessing mental health 5 times over 8 months after job loss. In addition to the commonly used indicators of underemployment, we designed a measure of cognitive complexity using the Occupational Information Network (O*NET), an extensive government database used to organize and categorize occupational information. Replicating past research, we found concurrent associations between all indexes of reemployment job quality and internalizing symptoms in the period immediately after reemployment. However, when controlling for quality of prior employment, all indicators except our measure for cognitive complexity became nonsignificant. As participants transitioned from unemployment to reemployment, only reductions in cognitive complexity were associated with sustained general internalizing symptoms. We also found that although changes in cognitive complexity had an immediate impact on the well-being of the recently reemployed, only the number of available weekly hours (full-time vs. part-time status) was relevant 6 to 12 weeks later. Our longitudinal model thus provides significant nuance to the current understanding of underemployment and mental health.

Proactive decision support for dynamic assignment and routing of Unmanned Aerial Systems

Unmanned Aerial System (UAS) missions are executed by teams of operators with highly specialized training and roles; however, the task demands on each operator are highly variable, often resulting in uneven workloads among operators and sometimes in mishaps. Therefore, there is a need to develop anticipative and effective decision support algorithms that permit the evaluation of courses of action (COAs), while assuring that operators are attending to the right task at the right time and that task demands do not exceed the operators cognitive capabilities in dynamic multi-mission environments. Motivated by the need to assist UAS operators in efficiently managing their workloads, this paper develops algorithms for the dynamic scheduling of UAS tasks by providing efficient COA recommendations in an unobtrusive manner. The dynamic scheduling of a set of UASs to search for targets with varying rewards is an NP-hard problem. We model this problem as an extension to the open vehicle routing problem (OVRP). Extensions to OVRP include risk propensity of human decision making, task deadlines, and multiple vehicle types. UAS operators would benefit greatly from the COA recommendations and the algorithms proposed in this paper by (a) enhancing rapid planning and re-planning capabilities; (b) proactive allocation of UASs, while balancing operator workloads; and (c) adapting plans as new targets of opportunity appear or information is updated about a target and/or UAS. The proposed algorithms are embedded in the Supervisory Control Operations User Testbed (SCOUTTM), an experimental paradigm developed by the Naval Research Laboratory-Washington DC.

Perceived responsiveness during an initial social interaction with a stranger predicts a positive memory bias one week later

Prior research has found that perceiving positive responses from others following self-disclosures enhances social bonds and plays a role in the maintenance of romantic relationships. We sought to extend this effect by exploring perceived responsiveness to good news in the context of initial social interactions with a stranger. In this study, unacquainted college students (n = 106) participated in a 45-minute semi-structured social interaction, and information on their emotions and behaviours was collected immediately after and one week later. We found that the receipt of supportive reactions to self-disclosure attempts during the social interaction was associated with immediate positivity and a more positive memory of the event (remembered enjoyment and positive emotions) one week later. This effect could not be attributed to how positively the event was experienced immediately afterwards, suggesting that perceived responsiveness during an initial social interaction facilitates a positive memory bias. These results offer new insights into how friendships might develop and be maintained.

Personality Strengths in Romantic relationships: Measuring Perceptions of Benefits and Costs and Their Impact on Personal and Relational Well-Being.

Three studies using samples of people in romantic relationships were conducted to create a new individual difference measure of partner strengths in couples. The 2 perceptions of partner strengths included (1) appreciation of their use and effectiveness and (2) recognition of costs associated with their use. Factor analyses supported 2-factors and we found that greater appreciation of partner strengths predicted greater relationship satisfaction, commitment, investment, intimacy, self-expansion, and support for goal pursuit; recognizing significant costs with partner strengths was inversely related to several outcomes. Using a 1-week daily diary, we found that appreciation of partner strength use and recognition of costs associated with these strengths predicted daily relationship satisfaction and whether basic psychological needs were met within the relationship. The explanatory power of partner strength perceptions could not be explained by the actual character strengths or Big Five personality traits of partners, support for positive self-disclosures (capitalization), or gratitude for relationship partners. Finally, we found that the relational consequences of partner strength perceptions were not just “in the head” of the perceiver—influencing partner relational outcomes. This research program provides evidence for the use of a new measure of how strengths are perceived to better understand romantic couples and aspirational targets in clinical interventions.

A Little Anthropomorphism Goes a Long Way.

Objective: We investigated the effects of exogenous oxytocin on trust, compliance, and team decision making with agents varying in anthropomorphism (computer, avatar, human) and reliability (100%, 50%). Background: Authors of recent work have explored psychological similarities in how people trust humanlike automation compared with how they trust other humans. Exogenous administration of oxytocin, a neuropeptide associated with trust among humans, offers a unique opportunity to probe the anthropomorphism continuum of automation to infer when agents are trusted like another human or merely a machine. Method: Eighty-four healthy male participants collaborated with automated agents varying in anthropomorphism that provided recommendations in a pattern recognition task. Results: Under placebo, participants exhibited less trust and compliance with automated aids as the anthropomorphism of those aids increased. Under oxytocin, participants interacted with aids on the extremes of the anthropomorphism continuum similarly to placebos but increased their trust, compliance, and performance with the avatar, an agent on the midpoint of the anthropomorphism continuum. Conclusion: This study provides the first evidence that administration of exogenous oxytocin affected trust, compliance, and team decision making with automated agents. These effects provide support for the premise that oxytocin increases affinity for social stimuli in automated aids. Application: Designing automation to mimic basic human characteristics is sufficient to elicit behavioral trust outcomes that are driven by neurological processes typically observed in human–human interactions. Designers of automated systems should consider the task, the individual, and the level of anthropomorphism to achieve the desired outcome.

Using machine learning and real-time workload assessment in a high-fidelity UAV simulation environment

Future unmanned vehicle operations will see more responsibilities distributed among fewer pilots. Current systems typically involve a small team of operators maintaining control over a single aerial platform, but this arrangement results in a suboptimal configuration of operator resources to system demands. Rather than devoting the full-time attention of several operators to a single UAV, the goal should be to distribute the attention of several operators across several UAVs as needed. Under a distributed-responsibility system, operator task load would be continuously monitored, with new tasks assigned based on system needs and operator capabilities. The current paper sought to identify a set of metrics that could be used to assess workload unobtrusively and in near real-time to inform a dynamic tasking algorithm. To this end, we put 20 participants through a variable-difficulty multiple UAV management simulation. We identified a subset of candidate metrics from a larger pool of pupillary and behavioral measures. We then used these metrics as features in a machine learning algorithm to predict workload condition every 60 seconds. This procedure produced an overall classification accuracy of 78%. An automated tasker sensitive to fluctuations in operator workload could be used to efficiently delegate tasks for teams of UAV operators.