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BackgroundWhile high blood alcohol concentrations (BACs) are required for alcohol-related blackouts (ARBs), additional characteristics also contribute to the risk, including a person's ethnicity, sex, and phenotypes relating to heavier drinking. Few prospective studies of ARBs have evaluated how these additional characteristics interact.MethodData regarding 398 European American (EA), Asian and Hispanic students were extracted from a 55-week prospective study of different approaches to decrease heavy drinking among college freshmen. Information on past month ARB frequency was determined at 8 assessments. While controlling for the prior month maximum BAC and active education vs. control group assignment, the patterns and intensities of ARBs over time across ethnic groups were evaluated with ANOVA at each follow-up for the full sample, and then separately by sex and then by low vs. high levels of response to alcohol status (LR). The overall pattern of ARBs over time was evaluated with a 3 ethnic groups by 2 sexes by 2 LR status by 8 time points mixed-design ANOVA.ResultsHigher rates of ARBs over time were associated with EA ethnicity, female sex and a low LR to alcohol, with the ethnic differences in ARBs most robust in females and drinkers with high LRs. Participation in education programs aimed at heavy drinking was associated with decreases in ARBs.ConclusionsThe data indicate that in addition to BACs achieved, propensities toward ARBs relate to complex interactions between additional risk factors, including ethnicity, sex, and LR status.

BackgroundStudent heavy drinking and associated problems are common at most universities and fluctuate throughout the calendar year, with marked increases during celebrations. Most studies of student drinking are limited to the academic year itself, and relatively few focus specifically on special heavy drinking events. Even fewer studies include drinking during summer break and subsequent school return.MethodsIn the context of an experimental protocol, beginning in January 2014, alcohol-related characteristics were evaluated 8 times over 55 weeks for 462 college freshmen, including periods that incorporated a campus festival, summer, and school return. Baseline predictors of drinking quantities over time included demography, substance use patterns, as well as environmental and attitudinal characteristics. Product-moment correlations evaluated relationships between baseline characteristics and subsequent quantities, and simultaneous entry regression analyses evaluated which characteristics most robustly predicted usual and maximum drinks over time.ResultsMaximum drinks per occasion increased 18% from the early spring (4/8/14 to 5/6/14) to the campus festival period (5/7/14 to 6/3/14), decreased 29% in the summer (7/8/14 to 8/5/14), and increased 31% on school return (10/7/14 to 11/4/14). The most robust predictors of higher quantities in regression analyses included items from each of the 3 major domains with the most consistent results seen for most baseline alcohol-related items and descriptive drinking norms (R(2) = 0.20 to 0.31).ConclusionsThese data demonstrate important changes in students' drinking during the calendar year, including expected large increases during the month of a 1-day festival, large decreases over the summer, and resumption of relatively high quantities upon return to school.

ObjectiveHeavy drinking is common on college campuses, with a marked increase from high school to freshman year. Programs addressing heavy campus drinking often personalize prevention protocols to fit a student's demography and prior drinking characteristics. Few efforts have individualized approaches to address a person's vulnerability through his or her low level of response (low LR) to alcohol.MethodThis article describes the recently completed 55-week outcome in drinking quantities and problems for the >90% of 500 participants in a prevention program at a U.S. university (62% female, mean age = 18 years) who completed a 4-week series of 50-minute videos delivered via the Internet. We evaluated whether, for low LRs, participation in an educational approach that focused on a low LR (the LR-based [LRB] condition) was associated with better outcomes than a state-of-the-art (SOTA) general education or with a no-intervention control condition.ResultsUsing a mixed-design analysis of variance and focusing on the most closely ethnically matched high and low LR pairs, students with low LRs in the LRB condition demonstrated the greatest decreases in usual and maximum drinks over the 55 weeks, especially when compared with closely ethnically matched students with high LRs. Low LR controls showed the highest drinking values over time.ConclusionsThis study underscores the potential importance of targeting a person's specific preexisting vulnerability toward heavy drinking when he or she enters college. The approach can be used in a relatively inexpensive protocol of video education sessions delivered via the Internet.

BackgroundLow levels of alcohol responses (low LRs) are genetically influenced phenotypes that are identified before alcohol dependence and predict future heavy drinking and alcohol problems. A recent paper described 13 LR-related blood oxygen level-dependent (BOLD) response contrast patterns observed during an emotional face recognition task that might reflect cognitive processes contributing to LR and that might themselves predict adverse alcohol outcomes (Paulus et al., Biol Psychiatry 2012; 72: 848). This paper evaluates the predictive implications of those functional magnetic resonance imaging (fMRI) patterns.MethodsOf 120 subjects from Paulus and colleagues (2012), 114 (57 low and high LRs; ~50% females) were interviewed 5 years later at age 25. Correlations between baseline fMRI patterns and alcohol-related outcomes were evaluated, and regression analyses were used to determine if BOLD response contrasts incremented over LR in predicting outcomes.ResultsBaseline fMRI patterns in 5 of 13 baseline regions of interest correlated with adverse outcomes. Such patterns in insular regions, particularly the left anterior insula, and the right frontal gyrus, added to LR in predicting alcohol problems. The relationships remained robust when exact binomial procedures were used, but, reflecting the small sample size, it was not possible to adequately consider Bonferroni corrections.ConclusionsThe data suggest that fMRI BOLD response contrasts predicted heavier drinking and alcohol problems 5 years later, even after considering baseline low LRs. Future work will focus on whether fMRI results can predict outcomes in larger samples and among young nondrinkers, as well as how the imaging results increase understanding of the processes through which LR operates.

BackgroundHeavy alcohol consumption and alcohol problems among college students are widespread and associated with negative outcomes for individuals and communities. Although current methods for prevention and intervention programming have some demonstrated efficacy, heavy drinking remains a problem. A previous pilot study and a recent large-scale evaluation (Schuckit et al., , ) found that a tailored prevention program based on a risk factor for heavy drinking, low level of response (low LR) to alcohol, was more effective at reducing heavy drinking than a state-of-the-art (SOTA) standard prevention program for individuals with the low LR risk factor.MethodsThis study enrolled 231 first-semester college freshmen with either high or low LR into the same level of response-based (LRB) or SOTA online prevention programs as in the previous reports (consisting of 4 weeks of video modules), as well as a group of matched controls not receiving alcohol prevention, and compared changes in alcohol use between these groups across a 6-month period.ResultsIndividuals in alcohol prevention programs had a greater reduction in maximum drinks per occasion and alcohol use disorder symptoms than controls. There was limited evidence for interactions between LR and prevention group in predicting change in alcohol use behaviors; only among participants with strict adherence to the program was there an interaction between LR and program in predicting maximum drinks per occasion. However, overall, low LR individuals showed greater decreases in drinking behaviors, especially risky behaviors (e.g., maximum drinks, frequency of heavy drinking) than high LR individuals.ConclusionsThese results indicate that prevention programs, including brief and relatively inexpensive web-based programs, may be effective for persons at highest risk for heavier drinking, such as those with a low LR. Tailored programs may provide incremental benefits under some conditions. Long-term follow-ups and further investigations of tailored prevention programs based on other risk factors are needed.

BackgroundHeavy drinking is common during transitions from high school to college. Optimal programs for diminishing risks for high alcohol consumption often tailor the approach to the specific needs of students. This study describes the results of an Internet-based prevention protocol that tailors the information to the risk associated with a pre-existing phenotype, the Low level of Response (Low LR) to alcohol.MethodsUsing stratified random assignment, 454 freshmen with Low and High LR values were assigned to 2 education groups (LR-based where all examples were given the context of the Low LR model of heavy drinking or a State Of The Art (SOTA) Group where the same lessons were taught but without an emphasis on LR) or a no-intervention Control Group. Individuals in the 2 education groups viewed 50-minute online videos once per week for 4 weeks. Changes in drinking patterns were assessed at Baseline, 4 weeks, and 8 weeks using a 2 (LR status) by 3 (education group) by 3 (time points) analysis of variance, with additional tests for ethnicity and sex.ResultsLow LR participants tended to decrease their usual (p

BackgroundAlcohol-related blackouts (ARBs) are reported by ~50% of drinkers. While much is known about the prevalence of ARBs in young adults and their cross-sectional correlates, there are few prospective studies regarding their trajectories over time during mid-adolescence. This paper reports latent trajectory classes of ARBs between age 15 and 19, along with predictors of those patterns.MethodsLatent class growth analysis (LCGA) was used to evaluate the pattern of occurrence of ARBs across 4 time points for 1,402 drinking adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC). Multinomial regression analyses evaluated age-15 demography, substance-related items, externalizing characteristics, and estimated peer substance use as predictors of latent class membership.ResultsARBs were reported at age 15 in 30% and at age 19 in 74% of these subjects. Four latent trajectory classes were identified: Class 1 (5.1%) reported no blackouts; for Class 2 (29.5%), ARBs rapidly increased with age; for Class 3 (44.9%), blackouts slowly increased; and for Class 4 (20.5%), ARBs were consistently reported. Using Class 2 (rapid increasers) as the reference, predictors of class membership included female sex, higher drinking quantities, smoking, externalizing characteristics, and estimated peer substance involvement (pseudo R(2)  = 0.22).ConclusionsARBs were common and repetitive in these young subjects, and predictors of their trajectories over time involved multiple domains representing diverse characteristics.

A new study finds that there has been a notable global increase in the acceptance of homosexuality over the past 20 years. This study examines the responses to 2000 questions asked in hundreds of surveys since 1981. Each included questions about attitudes regarding lesbians and gay men in 10 to 52 countries. The findings show that residents in 90% of all surveyed countries have become more accepting of homosexuality over the past 20 years. Age and gender were shown to have an impact on an individual’s likelihood of accepting homosexuality.

ObjectiveA person's pattern of heavier drinking often changes over time, especially during the early drinking years, and reflects complex relationships among a wide range of characteristics. Optimal understanding of the predictors of drinking during times of change might come from studies of trajectories of alcohol intake rather than cross-sectional evaluations.MethodThe patterns of maximum drinks per occasion were evaluated every 2 years between the average ages of 18 and 24 years for 833 subjects from the Collaborative Study on the Genetics of Alcoholism. Latent class growth analysis identified latent classes for the trajectories of maximum drinks, and then logistic regression analyses highlighted variables that best predicted class membership.ResultsFour latent classes were found, including Class 1 (69%), with about 5 maximum drinks per occasion across time; Class 2 (15%), with about 9 drinks at baseline that increased to 18 across time; Class 3 (10%), who began with a maximum of 18 drinks per occasion but decreased to 9 over time; and Class 4 (6%), with a maximum of about 22 drinks across time. The most consistent predictors of higher drinking classes were female sex, a low baseline level of response to alcohol, externalizing characteristics, prior alcohol and tobacco use, and heavier drinking peers.ConclusionsFour trajectory classes were observed and were best predicted by a combination of items that reflected demography, substance use, level of response and externalizing phenotypes, and baseline environment and attitudes.

BackgroundAlcohol and drug use disorders (AUDs and SUDs) and their combination are relatively common and often occur together. However, the relationships of potential early life correlates of alcohol and drug disorders to the combined diagnoses have rarely been evaluated in long-term prospective studies or in populations at high risk of one of these diagnoses but not the other.MethodsData were analyzed from 397 males (half with an alcohol-dependent father) who had no AUDs or SUDs at age 20 and who were followed approximately every 5 years for 3 decades. Early life correlates and the course of AUDs, SUDs, and combined disorders were evaluated for 4 groups of subjects based on subsequent alcohol and/or drug diagnoses.ResultsWhile the overall rates of the development of AUDs and SUDs were 41 and 21%, respectively, the rates of the second substance-related diagnosis were almost 2-fold higher for individuals who had the first condition. Among potential risk factors, scores for externalizing traits were elevated for men with AUDs, SUDs, and their combination, but a low level of response (low LR) to alcohol was associated only with the risk of AUDs, even when observed in the context of SUDs. The same earlier life characteristics that related to AUDs and to SUDs also related to the combination of these diagnoses in the same person. Finally, in this prospective study, subjects with both AUDs and SUDs had a more severe course than subjects with either condition alone.ConclusionsThis prospective evaluation of a group at high risk of AUDs confirmed the selective impact of the low LR on the risk of AUDs, the relationship of externalizing characteristics to both AUDs and SUDs and confirmed the more severe clinical course for both conditions when seen together.

This article explores the impact of artificial intelligence (AI) on the construction industry and the potential for disputes to arise from its use. It specifically focuses on two types of claims that could occur: breach of obligation to use reasonable skill and care in design, and breach of obligation to deliver a project fit for purpose. The article offers recommendations for parties involved in construction projects that utilize AI, including the importance of generating documentation and evidence to defend against claims. It also discusses the implications of AI on claims and disputes in the future, highlighting the power and limitations of generative AI systems in decision-making and the need for supporting evidence. The article further addresses potential areas of dispute related to AI in construction, such as duty to warn, cybersecurity, and unforeseeable events. It concludes by emphasizing the significance of taking proactive measures to protect one's position in potential disputes. [Extracted from the article]

This document contains summaries of various studies related to medical communications. The studies cover topics such as the use of artificial intelligence (AI) in generating plain language summaries (PLS) of scientific manuscripts, the development of reporting guidelines for consensus methods in biomedical research, patient awareness of PLS for diabetes information, and the use of AI in medical communications. Other studies explore the readability of patient-level summaries, author satisfaction with authorship algorithms, guidelines for using AI tools in biomedical journals, barriers to developing enhanced publication content, and the use of generative AI for PLS abstracts. The document also discusses the use of graphical abstracts and PLS in nephrology and gastroenterology journals, as well as the quality and efficiency of generative AI tools for content generation in medical publications. The studies provide valuable insights into various aspects of medical communications and emphasize the importance of clear and engaging content. [Extracted from the article]