Faculty and Staff

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

We integrate multiple domains of psychological science to identify, better understand, and manage the effects of subtle but powerful biases in forensic mental health assessment. This topic is ripe for discussion, as research evidence that challenges our objectivity and credibility garners increased attention both within and outside of psychology. We begin by defining bias and provide rich examples from the judgment and decision making literature as they might apply to forensic assessment tasks. The cognitive biases we review can help us explain common problems in interpretation and judgment that confront forensic examiners. This leads us to ask (and attempt to answer) how we might use what we know about bias in forensic clinicians’ judgment to reduce its negative effects.

We conducted an international survey in which forensic examiners who were members of professional associations described their two most recent forensic evaluations (N=434 experts, 868 cases), focusing on the use of structured assessment tools to aid expert judgment. This study describes:

1. The relative frequency of various forensic referrals.
2. What tools are used globally.
3. Frequency and type of structured tools used.
4. Practitioners’ rationales for using/not using tools.

We provide general descriptive information for various referrals. We found most evaluations used tools (74.2%) and used several (on average 4). We noted the extreme variety in tools used (286 different tools). We discuss the implications of these findings and provide suggestions for improving the reliability and validity of forensic expert judgment methods. We conclude with a call for an assessment approach that seeks structured decision methods to advance greater efficiency in the use and integration of case-relevant information.

This survey of 206 forensic psychologists tested the “filtering” effects of preexisting expert attitudes in adversarial proceedings. Results confirmed the hypothesis that evaluator attitudes toward capital punishment influence willingness to accept capital case referrals from particular adversarial parties. Stronger death penalty opposition was associated with higher willingness to conduct evaluations for the defense and higher likelihood of rejecting referrals from all sources Conversely, stronger support was associated with higher willingness to be involved in capital cases generally, regardless of referral source. The findings raise the specter of skewed evaluator involvement in capital evaluations, where evaluators willing to do capital casework may have stronger capital punishment support than evaluators who opt out, and evaluators with strong opposition may work selectively for the defense. The results may provide a partial explanation for the “allegiance effect” in adversarial legal settings such that preexisting attitudes may contribute to partisan participation through a self-selection process.

This chapter integrates from cognitive neuroscience, cognitive psychology, and social psychology the basic science of bias in human judgment as relevant to judgments and decisions by forensic mental health professionals. Forensic mental health professionals help courts make decisions in cases when some question of psychology pertains to the legal issue, such as in insanity cases, child custody hearings, and psychological injuries in civil suits. The legal system itself and many people involved, such as jurors, assume mental health experts are “objective” and untainted by bias. However, basic psychological science from several branches of the discipline suggest the law’s assumption about experts’ protection from bias is wrong. Indeed, several empirical studies now show clear evidence of (unintentional) bias in forensic mental health experts’ judgments and decisions. In this chapter, we explain the science of how and why human judgments are susceptible to various kinds of bias. We describe dual-process theories from cognitive neuroscience, cognitive psychology, and social psychology that can help explain these biases. We review the empirical evidence to date specifically about cognitive and social psychological biases in forensic mental health judgments, weaving in related literature about biases in other types of expert judgment, with hypotheses about how forensic experts are likely affected by these biases. We close with a discussion of directions for future research and practice.

Summer daytime cooling efficiency of various land cover is investigated for the urban core of Phoenix, Arizona, using the Local-Scale Urban Meteorological Parameterization Scheme (LUMPS). We examined the urban energy balance for 2 summer days in 2005 to analyze the daytime cooling-water use tradeoff and the timing of sensible heat reversal at night. The plausibility of the LUMPS model results was tested using remotely sensed surface temperatures from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery and reference evapotranspiration values from a meteorological station. Cooling efficiency was derived from sensible and latent heat flux differences. The time when the sensible heat flux turns negative (sensible heat flux transition) was calculated from LUMPS simulated hourly fluxes. Results indicate that the time when the sensible heat flux changes direction at night is strongly influenced by the heat storage capacity of different land cover types and by the amount of vegetation. Higher heat storage delayed the transition up to 3 h in the study area, while vegetation expedited the sensible heat reversal by 2 h. Cooling efficiency index results suggest that overall, the Phoenix urban core is slightly more efficient at cooling than the desert, but efficiencies do not increase much with wet fractions higher than 20%. Industrial sites with high impervious surface cover and low wet fraction have negative cooling efficiencies. Findings indicate that drier neighborhoods with heterogeneous land uses are the most efficient landscapes in balancing cooling and water use in Phoenix. However, further factors such as energy use and human vulnerability to extreme heat have to be considered in the cooling-water use tradeoff, especially under the uncertainties of future climate change.