People judge the risks in their environment not only based on objective measures such as lives lost or dollars spent, but also based on their subjective perceptions of those risks. These perceptions can depend on a number of different characteristics of risk, including: how voluntarily the risk is undertaken, how immediately effects are seen, how known the risks are to scientists and to those exposed to them, how controllable those risks are, how new the risks feel, how catastrophic the effects tend to be, how likely the effects are to be fatal, and how dreaded the risk feels on a gut level. These nine characteristics of risk tend to load onto two orthogonal factors, or risk dimensions: unknown risk, and dread risk. While past research using such a psychometric approach to risk perception has established dread and unknown risk levels, as well as relative risk ratings, for a slate of 30 common technologies and activities (e.g., nuclear power, pesticides, skiing, fire fighting), most of these studies are now over three decades old. Chapter 1 of this dissertation replicates and updates the findings from those original psychometric studies of risk perception, showing that the dread-unknown factor space is still a useful framework for studying risk perceptions, and illustrating some of the ways that risk perceptions for technologies have changed since the 1970s. Chapter 2 applies the same methodology to study people’s responses to the risks of natural hazards and climate change. Although the slate of nine risk characteristics used to assess technological risk in Chapter 1 does not apply perfectly to a study of natural hazards on their own, Chapter 2 shows that this framework does work well as a means of assessing the differences in risk perception between natural hazards and climate change–related risks. We find that climate change and sea-level rise are not treated similarly to natural hazards like floods and wildfires; relative to the natural hazards, they fall at the extreme low end of the dread risk dimension, and the extreme high end of the unknown risk dimension. Chapter 3 goes on to apply the dread-unknown risk framework to directly compare attitudes toward technological risks, natural hazards, and climate-related risks. Nearly all natural hazards rank higher on dread than nearly all of the man-made risks, but the natural hazards tend to cluster near the mean on the unknown-risk dimension while technological risks vary across the full unknown-risk scale. Climate change and sea-level rise, on the other hand, both fall among the highest-unknown items on the list, and lie just below the mean on dread risk. Climate change and sea-level rise continue to show risk profiles that clearly differentiate them from the natural hazards; instead, they more closely resemble the profiles for low-dread, high-uncertainty technologies like pesticides. This characterization of climate change as highly uncertain but relatively non-dread is consistent with theories that link the public’s failure to engage on climate-related issues with a lack of vividness or immediacy to the concept of climate change. Since dread risk invokes the affective processing systems that can be more successful than analytical risk estimates at inspiring action, communicators or policymakers who are currently struggling to engage the public on the risks of climate change might find more success by linking these topics to hazards, such as hurricanes and floods, which appear to naturally invoke these desired qualities of dread risk.

This study attempts to document the process of change in an example of cognitive behavior therapy conducted as part of larger research project in the effectiveness of this approach with parents having a potential for child abuse. One example of therapy was chosen for in depth analysis using a discourse analysis approach based on that of Labov and Fanshel (1977). Tape-recordings of the eight meetings between the client and the therapist--six therapy sessions, and two additional sessions to administer a pre and post test questionnaire required by the larger study--were transcribed. Selected segments of these transcripts were subjected to a microanalysis, the aim of which was to identify evidence of therapeutic change. Although the client did not follow the therapist in every respect, considerable evidence was found of a process of change--which began prior to the first therapy session with the research oriented questionnaire session and ended with the final questionnaire session. Certain moments in the dialogue, which occurred in nearly every session, were especially significant in revealing change. Through the sessions, a process was identified in which the client adopts, but also adapts ideas put forward by the therapist.

In the absence of direct experience with physical stimuli, people generate mental models to facilitate cognitive processes involved in problem solving. Mental models are viewed as internal representations that help people understand, reason about, predict, and investigate causal relationships contained within physical systems. In addition, more recent findings distinguish mental models from other mental representations by suggesting that people actively construct mental models, switch between different mental models of a given problem, and alternate between mental models and rules to solve problems. Piecemeal animation of a system’s action has been identified as the cognitive strategy people use to reason about dynamic physical systems. Emphasizing function over form in multimedia presentations about physical systems has been shown to improve the leaners’ mental models. Novice leaners’ mental models are reported to emphasize structure, while the experts’ mental models include more functional and behavioral elements. Mental models of causal complex systems that operate in perceptually novel environments remain largely unstudied. Two experiments were conducted to study peoples’ mental models of single and functionally coupled causal complex systems and investigate the influences of text organization and strategy training on novice learners’ mental model development. A modified version of the Structure Behavior Function (SBF) framework was developed to facilitate the investigation of mental models of causal complex systems. Results suggest that in the absence of explicit instruction, people utilize a combination of cognitive strategies ranging from rote memorization to piecemeal simulation of the systems’ functions to form incomplete, but coherent mental models of causal complex systems from text and static diagrams. A brief training session was effective in teaching novice learners to use envisioning strategy and help promote piecemeal animation of the system. Envisioning strategy training significantly improved the subjects’ mental model complexity as well as knowledge of structural, functional, and mechanistic components involved in achieving the systems’ overall functions in both single and functionally coupled causal complex systems (p<0.05). For the single causal complex system (CCS), function-salient text improved subjects’ structure and function subscores significantly (p<0.05), but did not affect the mechanism subscore. The interaction between text and strategy training was not significant. For the functionally coupled causal complex system (FC-CCS), text was not a significant predictor of mental model complexity or its subcomponents. The interaction between text and strategy training was also insignificant. Though subjects’ mental models included more structural than functional elements for both CCS and FC-CCS, majority demonstrated understanding of the overall systems’ functions (formation of end products). The subjects appeared to pay selective attention to the change producing steps and points of functional coupling (product of the first system, which serves as the template for the second system).

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abstract: Older adults often experience communication difficulties, including poorer comprehension of auditory speech when it contains complex sentence structures or occurs in noisy environments. Previous work has linked cognitive abilities and the engagement of domain-general cognitive resources, such as the cingulo-opercular and frontoparietal brain networks, in response to challenging speech. However, the degree to which these networks can support comprehension remains unclear. Furthermore, how hearing loss may be related to the cognitive resources recruited during challenging speech comprehension is unknown. This dissertation investigated how hearing, cognitive performance, and functional brain networks contribute to challenging auditory speech comprehension in older adults. Experiment 1 characterized how age and hearing loss modulate resting-state functional connectivity between Heschl’s gyrus and several sensory and cognitive brain networks. The results indicate that older adults exhibit decreased functional connectivity between Heschl’s gyrus and sensory and attention networks compared to younger adults. Within older adults, greater hearing loss was associated with increased functional connectivity between right Heschl’s gyrus and the cingulo-opercular and language networks. Experiments 2 and 3 investigated how hearing, working memory, attentional control, and fMRI measures predict comprehension of complex sentence structures and speech in noisy environments. Experiment 2 utilized resting-state functional magnetic resonance imaging (fMRI) and behavioral measures of working memory and attentional control. Experiment 3 used activation-based fMRI to examine the brain regions recruited in response to sentences with both complex structures and in noisy background environments as a function of hearing and cognitive abilities. The results suggest that working memory abilities and the functionality of the frontoparietal and language networks support the comprehension of speech in multi-speaker environments. Conversely, attentional control and the cingulo-opercular network were shown to support comprehension of complex sentence structures. Hearing loss was shown to decrease activation within right Heschl’s gyrus in response to all sentence conditions and increase activation within frontoparietal and cingulo-opercular regions. Hearing loss also was associated with poorer sentence comprehension in energetic, but not informational, masking. Together, these three experiments identify the unique contributions of cognition and brain networks that support challenging auditory speech comprehension in older adults, further probing how hearing loss affects these relationships. / Dissertation/Thesis / Doctoral Dissertation Neuroscience 2019

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A cognitive-behavioral technique for developing dream control was examined. Twenty paid subjects were randomly assigned to either an attention-placebo control group or a cognitive-behavioral training group. Subjects met in the respective groups for a total of three hours of "training." Subjects in the actual training group were presented with a self-instruction sequence to practice and use in attempting to manipulate dream content. The control group subjects met to only discuss dreams and dreaming and were given no specific instruction in content control. After completion of the training, each subject individually spent two consecutive nights in a sleep laboratory. The first night of sleep served as an adaptation night, and the second night constituted the posttest portion of the experiment. Prior to going to sleep on the posttest night, all subjects were randomly assigned one of five possible topics to dream about throughout the night and were awakened during every REMP in order to provide a dream report. Eighty-one reports were obtained and given to two independent, "blind" judges for scoring. These judges were requested to match each report with the appropriate topic, evaluate the degree of control present, and rate each report on a measure of dream-like quality.