Binge drinking is a public health concern due to its association with negative health outcomes as well as increased legal and social consequences. Previous studies have frequently used self-reported alcohol consumption to classify binge drinking episodes; however, these measures are often limited in both detail and accuracy. Some researchers have begun using additional measures such as blood (BAC) and breath (BrAC) alcohol concentrations to supplement self-report data. Transdermal alcohol testing, or the detection of alcohol expiration through the skin, offers advantages over BAC and BrAC measures by allowing for continuous and noninvasive monitoring of an individual's drinking behavior in real time. Despite these advantages, this technology has not been widely used or studied outside of forensic applications. The present research compares transdermal alcohol concentration (TAC) and BrAC readings during the consumption of alcohol ranging from moderate drinking to binge drinking in 22 adult regular drinkers in order to investigate the sensitivity and specificity of the TAC monitors. We observed that BrAC and TAC measures were broadly consistent. Additionally, we were able to develop an equation that could predict BrAC results using TAC data, indicating TAC data would be an appropriate substitute in research and clinical contexts where BrAC readings are typically used. Finally, we were able to determine a cutoff point for peak TAC data that could reliably predict whether a participant had engaged in moderate or more-than-moderate drinking, suggesting TAC monitors could be used in settings where moderate or reduced drinking is the goal.

Phishing is the spoofing of Internet websites or emails aimed at tricking users into entering sensitive information, with such goals as financial or identity theft. The current study sought to determine whether age is associated with increased susceptibility to phishing and whether tests of executive functioning can predict phishing susceptibility. A total of 193 cognitively intact participants, 91 younger adults and 102 older adults, were primarily recruited through a Psychology department undergraduate subject pool and a gerontology research registry, respectively. The Executive Functions Module from the Neuropsychological Assessment Battery and the Iowa Gambling Task were the primary cognitive predictors of reported phishing suspiciousness. Other predictors included age group (older vs. younger), sex, education, race, ethnicity, prior knowledge of phishing, prior susceptibility to phishing, and whether or not browsing behaviors were reportedly different in the laboratory setting versus at home. A logistic regression, which accounted for a 22.7% reduction in error variance compared to the null model and predicted phishing suspiciousness with 73.1% (95% CI [66.0, 80.3]) accuracy, revealed three statistically significant predictors: the main effect of education (b = 0.58, SE = 0.27) and the interactions of age group with prior awareness of phishing (b = 2.31, SE = 1.12) and performance on the Neuropsychological Assessment Battery Mazes test (b = 0.16, SE = 0.07). Whether or not older adults reported being suspicious of the phishing attacks used in this study was partially explained by educational history and prior phishing knowledge. This suggests that simple educational interventions may be effective in reducing phishing vulnerability. Although one test of executive functioning was found useful for identifying those at risk of phishing susceptibility, four tests were not found to be useful; these results speak to the need for more ecologically valid tools in clinical neuropsychology.

Understanding the relationships between health and aging is essential for delaying morbidity and maximizing independence in aging populations as life expectancies increase. Loss of cognitive function is a feared age-associated condition and growing public health concern. Alzheimer’s disease (AD), the most common cause of dementia, has no curative therapies. Characterizing the relationships between risk factors, biomarkers, and AD progression is critical for the development of effective disease prediction, clinical intervention, and ultimately, disease prevention. The Emory Healthy Aging Study (EHAS) and the Emory Healthy Brain Study (EHBS), which is nested within EHAS, aim to further the understanding of healthy aging and the pathogenesis of age-related illnesses in well-characterized, community-based prospective cohorts and to identify biomarkers for the earliest manifestations of AD for the facilitation of preventative interventions. The EHAS is an innovative, longitudinal, web-based study enrolling English-speaking adults in the U.S. who agree to be contacted for future studies. Using validated instruments, the annual questionnaire enquires about demographics, socioeconomics, self-reported cognitive function, personal and family medical history, lifestyle, and psychosocial factors. Cognitive assessments are also obtained using an ambulatory device. Nested within EHAS, the EHBS is enrolling up to 2,500 EHAS participants, 50–75 years old, who do not have a diagnosis of AD, mild cognitive impairment, or any other memory disorder. EHBS in-person, biennial study visits, include neuropsychological testing, cardiovascular measures, retinal and brain imaging, biospecimen collection (blood, cerebrospinal fluid, gut microbiome), and other assessments. Since spring 2016, EHAS and EHBS have enrolled 12,500 and 863 participants with completed baseline assessments, respectively. Data and biospecimens from EHBS participants will support a broad range of AD biomarker discovery efforts, and follow-up of EHAS participants will enable assessment of self-reported cognitive trajectories and accumulation of incident cases of a variety of health conditions. The EHAS design supports the interval deployment of new study instruments and targeted sampling for ancillary studies. This project will increase our knowledge about healthy aging, improve our understanding of risk factors for cognitive impairment and dementias, support development of biomarkers, and facilitate studies of age-associated disorders including AD.

Objective: Royall and colleagues identified a latent dementia phenotype, "delta", reflecting the "cognitive correlates of functional status." We sought to cross-validate and extend these findings in a large clinical case series of adults with and without dementia. Method: A confirmatory factor analysis (CFA) model for delta was fit to National Alzheimer's Coordinating Center data (n = 26,068). Factor scores derived from delta were compared with the Clinical Dementia Rating Sum of Boxes (CDR-SB) and to clinically diagnosed dementia. A longitudinal parallel-process growth model compared changes in delta with changes in CDR-SB over 6 annual evaluations. Results: The CFA model fit well; CFI = 0.971, RMSEA = 0.070. Factor scores derived from delta discriminated between demented and nondemented participants with an area under the curve of .96. The growth model also fit well, CFI = 0.969, RMSEA = 0.032. Conclusions: The delta construct represents a novel approach to measuring dementia-related changes and has potential to improve cognitive assessment of neurodegenerative diseases.