Psychometric Evaluation of an Instrument to Measure Prospective Pregnancy Preferences: The Desire to Avoid Pregnancy Scale.

BACKGROUND:Existing approaches to measuring women's pregnancy intentions suffer important limitations, including retrospective assessment, overly simple categories, and a presumption that all women plan pregnancies. No psychometrically valid scales exist to prospectively measure the ranges of women's pregnancy preferences. MATERIALS AND METHODS:Using a rigorous construct modeling approach, we developed a scale to measure desire to avoid pregnancy. We developed 60 draft items from existing research, assessed comprehension through 25 cognitive interviews, and administered items in surveys with 594 nonpregnant women in 7 primary and reproductive health care facilities in Arizona, New Jersey, New Mexico, South Carolina, and Texas in 2016-2017. We used item response theory to reduce the item set and assess the scale's reliability, internal structure validity, and external validity. Items were included based on fit to a random effects multinomial logistic regression model (partial credit item response model), correspondence of item difficulty with participants' pregnancy preference levels, and consistency of each item's response options with overall scale scores. RESULTS:The 14 final items covered 3 conceptual domains: cognitive preferences, affective feelings, and practical consequences. Items fit the unidimensional model, with a separation reliability of 0.90 (Cronbach α: 0.95). The scale met established criteria for internal validity, including correspondence between each item's response categories and overall scale scores. We found no important differential item functioning by participant characteristics. CONCLUSIONS:A robust measure is available to prospectively measure desire to avoid pregnancy. The measure can aid in identifying women who could benefit from contraceptive care and research on less desired pregnancy

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

The Ah receptor: adaptive metabolism, ligand diversity, and the xenokine model

Author Posting. © American Chemical Society, 2020. This is an open access article published under an ACS AuthorChoice License. The definitive version was published in Chemical Research in Toxicology, 33(4), (2020): 860-879, doi:10.1021/acs.chemrestox.9b00476.The Ah receptor (AHR) has been studied for almost five decades. Yet, we still have many important questions about its role in normal physiology and development. Moreover, we still do not fully understand how this protein mediates the adverse effects of a variety of environmental pollutants, such as the polycyclic aromatic hydrocarbons (PAHs), the chlorinated dibenzo-p-dioxins (“dioxins”), and many polyhalogenated biphenyls. To provide a platform for future research, we provide the historical underpinnings of our current state of knowledge about AHR signal transduction, identify a few areas of needed research, and then develop concepts such as adaptive metabolism, ligand structural diversity, and the importance of proligands in receptor activation. We finish with a discussion of the cognate physiological role of the AHR, our perspective on why this receptor is so highly conserved, and how we might think about its cognate ligands in the future.This review is dedicated in memory of the career of Alan Poland, one of the truly great minds in pharmacology and toxicology. This work was supported by the National Institutes of Health Grants R35-ES028377, T32-ES007015, P30-CA014520, P42-ES007381, and U01-ES1026127, The UW SciMed GRS Program, and The Morgridge Foundation. The authors would like to thank Catherine Stanley of UW Media Solutions for her artwork

Chandra localization of XTE J1906+090 and discovery of its optical and infrared counterparts

We present the Chandra identification and localization of the transient X-ray source XTE J1906+090 and the discovery of its optical and infrared counterparts. Our analysis of archival Chandra ACIS-I observations of the field found the source approximately 8 away from the position determined earlier with the RXTE PCA. We have confirmed the source identification with timing analysis of the X-ray data, which detected the source spin period of 89.6 s. The best Chandra position for the source is R.A. = 19h04m47491, decl. = +09024140. Subsequently, we performed optical observations of the field around the new location and discovered a coincident optical source with R-band magnitude of 18.7. A search in the Two Micron All Sky Survey catalog revealed an infrared point source with J = 15.2, H = 14.2, and K = 13.5, whose location is also coincident with our Chandra and optical positions. Our results add fresh evidence for a Be/X-ray transient nature for XTE J1906+090

Monitoring Cen X-3 with BATSE

The eight uncollimated BATSE Large Area Detectors (LAD's) provide the ability to monitor pulsed hard x ray sources on a nearly continuous basis. Using data from the LAD's, the pulse timing and pulsed flux of the 4.8 second period binary x ray pulsar Centaurus X-3 was analyzed over a two month period. The methods and initial results of this analysis, which includes both data folded onboard GRO and 1.024 second resolution discriminator rates folded on the ground, are presented

A Sea-Level Lowstand (Devil\u27s Point Event) Recorded in Bahamian Reefs: Comparison with Other Last Interglacial Climate Proxies

Reprinted from: Benjamin J. Greenstein and Cindy K. Carney (eds.) Proceedings of the 10th Symposium on the Geology of the Bahamas and Other Carbonate Regions: San Salvador, Gerace Research Cente

Bahamian Sangamonian Coral Reefs and Sea-Level Change

Reprinted from James L. Carew (ed.) May 30–June 3, 1996, Proceedings of the 8th Symposium on the Geology of the Bahamas and Other Carbonate Regions: Bahamian Field Station, San Salvador, Bahamas