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PurposeThis study aims to identify how objective indicators of destination country risk differentiate business study abroad programs from those in other academic disciplines.Design/methodology/approachThe authors trained a neural network model on six years of student-initiated inquiries about study abroad programs at a large US university. The model classified business versus nonbusiness study abroad programs using objective measures of destination country risk as the primary inputs.FindingsThe model correctly classifies business and nonbusiness study abroad programs with over 70% accuracy. Business programs were found to be 20% less likely to include destinations where the Centers for Disease Control and Prevention recommend nonroutine vaccinations and favor countries with higher Global Peace Index scores.Practical implicationsThese results underscore the need to consider destination country risk in the design and administration of study abroad programs. An understanding of student preferences for lower risk destinations can contribute to improved planning, execution and student experiences in these programs.Social implicationsBetter planning and management of study abroad programs based on understanding of destination country risk can lead to enhanced student safety and experiences.Originality/valueThis study offers a unique perspective on understanding study abroad programs by focusing on objective measures of destination country risk rather than risk perceptions. It also is, to the best of the authors’ knowledge, the first to use a neural network to classify study abroad programs as business versus nonbusiness using objective measures of country-specify risk indicators.

The aim of this study is to evaluate the factors of implant failure in patients with periodontitis and their impact on the prognosis of having a peri-implant disease and/or implant failure. Data regarding 325 implants among 84 patients with periodontitis were retrospectively examined. Patients were classified by Stage (I, II, III, IV) and Grade (A, B, C), implant failures for peri-implant disease and lack of osseointegration. Clinical data, including implant- and patient-related variables were evaluated by principal components analysis (PCA) and two-step cluster analysis (CA). Survival and success rates were 96.3% and 87.1%, respectively. Prevalence of peri-implant disease was significantly higher in Stage IV patients (p < 0.05), and incidence of lost implant due to peri-implantitis was significantly higher in patients with bone augmentation (BA) (p < 0.05). PCA and CA revealed five of eleven variables and four clusters at patient level, and six of fourteen variables and three clusters at implant level. Stage and Grade are useful indicators for the development of peri-implant diseases in which BA and the number of implants are involved.

The driving safety performance of autonomous driving vehicles must be ensured before on-road implementation. Because it is not realistic to evaluate every single test condition in real-world traffic, computer simulation methods can be used. The driving safety performance can be evaluated by simulating various driving scenarios and calculating surrogate indicators representing dangerous collision risk. This study used a near-miss database and introduced a surrogate indicator that represents a potential risk in the driving scenarios for rear-end and cut-in collisions. The near-miss video database includes several driving scenarios experienced by human drivers, such as dangerous situations that lead to accidents, potentially dangerous situations that have a risk probability to escalate into dangerous situations, and normal driving situations. A skilled and attentive human driver foresees dangerous situations while driving and avoids them. Therefore, autonomous driving vehicles, which should be safer than human driving, must avoid potentially dangerous situations, as well as overtly dangerous ones. Level 3 autonomous driving vehicles must be safely operated to prevent potentially dangerous situations for rear-end collisions and cut-in collisions, which are the most frequent danger cases on highways. A calculation method of surrogate indicators to predict the severity of driving scenarios for rear-end and cut-in collisions was developed. The near-miss video database was used to validate that these indicators can illustrate risk probabilities and help assess dangerous situations. Thus, dangerous situations and potentially dangerous situations in the driving scenarios for rear-end and cut-in collisions were quantified using the surrogate indicators, and the driving safety performance of autonomous driving vehicles could be evaluated.

Background Health literacy concerns the ability of citizens to meet the complex demands of health in modern society. Data on the distribution of health literacy in general populations and how health literacy impacts health behavior and general health remains scarce. The present study aims to investigate the prevalence of health literacy levels and associations of health literacy with socioeconomic position, health risk behavior, and health status at a population level. Methods A nationwide cross-sectional survey linked to administrative registry data was applied to a randomly selected sample of 15,728 Danish individuals aged ≥25 years. By the short form HLS-EU-Q16 health literacy was measured for the domains of healthcare, disease prevention, and health promotion. Adjusted multinomial logistic regression analyses were used to estimate associations of health literacy with demographic and socioeconomic characteristics, health risk behavior (physical activity, smoking, alcohol consumption, body weight), and health status (sickness benefits, self-assessed health). Results Overall, 9007 (57.3%) individuals responded to the survey. Nearly 4 in 10 respondents faced difficulties in accessing, understanding, appraising, and applying health information. Notably, 8.18% presented with inadequate health literacy and 30.94% with problematic health literacy. Adjusted for potential confounders, regression analyses showed that males, younger individuals, immigrants, individuals with basic education or income below the national average, and individuals receiving social benefits had substantially higher odds of inadequate health literacy. Among health behavior factors (smoking, high alcohol consumption, and inactivity), only physical behavior [sedentary: OR: 2.31 (95% CI: 1.81; 2.95)] was associated with inadequate health literacy in the adjusted models. The long-term health risk indicator body-weight showed that individuals with obesity [OR: 1.78 (95% CI: 1.39; 2.28)] had significantly higher odds of lower health literacy scores. Poor self-assessed health [OR: 4.03 (95% CI: 3.26; 5.00)] and payments of sickness absence compensation benefits [OR: 1.74 (95% CI: 1.35; 2.23)] were associated with lower health literacy scores. Conclusions Despite a relatively highly educated population, the prevalence of inadequate health literacy is high. Inadequate health literacy is strongly associated with a low socioeconomic position, poor health status, inactivity, and overweight, but to a lesser extent with health behavior factors such as smoking and high alcohol consumption.

Background Understanding the burden and determinants of suicide during adolescence is key to achieving global health goals. We examined the prevalence and determinants of self-reported suicidal ideation and attempts among younger (13–15 years) and older adolescents (16–17 years). Methods Pooled prevalence estimates with 95% confidence interval, were calculated for suicide ideation and attempts for 118 surveys from 90 countries that administered the Global School-based Student Health Survey (GSHS) to adolescents (13–17 years of age) from 2003 to 2017. Indicators (including individual and social factors) associated with suicidal ideation and attempts were determined from multivariable linear regressions on key outcomes. Results The prevalence of suicidal ideation representing 397,299 adolescents (51.3% female) was significantly higher among girls than boys whereas attempts did not differ by age or sex. Being bullied, or having no close friends was associated with suicidal ideation among girls 13–15 years and 16–17 years, respectively. Among all boys, being in a fight and having no close friends was associated with suicidal ideation with the addition of serious injury for boys 13–15 years. Common to all younger adolescents was an association of suicide attempt with being bullied and having had a serious injury. Among young boys, having no close friends was an additional indicator for suicide attempt. Having no close friends was associated with suicide attempt in older adolescents with the addition to being bullied in older girls and serious injury in older boys. Conclusions Building positive social relationships with peers and avoiding serious injury appear key to suicide prevention strategies for vulnerable adolescents. Targeted programs by age group and sex for such indicators could improve mental health during adolescence in low and middle-income countries, given the diverse risk profiles for suicidal ideation and attempts.

Background Identify and compare health risk indicators for common chronic diseases between different occupational groups. Methods A total of 72,855 participants (41% women) participating in an occupational health service screening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3). Results The greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR = 0.68 to OR = 5.12), physically demanding work (OR = 0.55 to OR = 45.74) and high sitting at work (OR = 0.04 to OR = 1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71–1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88–2.13) as high-skilled blue-collar workers (1.98; 1.86–2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17–2.48). Conclusion There were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.

Road tunnels are associated with numerous risks including traffic accidents and fires, posing threats to individual or group users. Key risk indicators such as Risk Quantum, Individual Risk, Societal Risk, and Expected Number of Fatalities are instrumental in evaluating the level of risk exposure. These indicators empower Rights-Holders and Duty-Holders to report hazards, prevent disasters, and implement timely remedial measures. A crucial indicator, the Scenario Risk Quantum, has its roots in the forensic evaluation of responsibility in a fatal tunnel accident in the UK since 1949. The Quantum of Risk of each design scenario, reasonably selected among rational and practicable possibilities, has both a deterministic and probabilistic character. The Risk Tolerability and Acceptability criteria are modelled according to risk indicators by selecting the parameters according to ethical principles and societal policy. Scenarios are meticulously identified, described, probabilised and assigned probabilities prior to the quantitative risk analysis. These risk indicators are integral to the risk assessment process. This article delves into the understanding of these indicators within the context of Italian road tunnels, employing the Quantum Gu@larp Model to analyse Risk Acceptability and Tolerability.

Background This study aimed to compare the quality of life (QoL) reported by childhood cancer survivors (CCS) drawn from a cohort of the German Childhood Cancer Registry with a representative general population sample and, within CCS, to test associations between QoL and health behavior, health risk factors, and physical illness. Methods CCS ( N  = 633, age at diagnosis M  = 6.34 ( SD  = 4.38), age at medical assessment M  = 34.92 ( SD  = 5.70)) and a general population sample (age-aligned; N  = 975) filled out the EORTC QLQ-C30. Comparisons were performed using General linear models (GLMs) (fixed effects: sex/gender, group (CCS vs. general population); covariates: age, education level). CCS underwent an extensive medical assessment (mean time from diagnosis to assessment was 28.07 ( SD  = 3.21) years) including an objective diagnosis of health risk factors and physical illnesses (e.g., diabetes and cardiovascular disease). Within CCS, we tested associations between QoL and sociodemographic characteristics, health behavior, health risk factors, and physical illness. Results CCS, especially female CCS, reported both worse functional QoL and higher symptom burden than the general population. Among CCS, better total QoL was related to younger age, higher level of education, being married, and engaging in active sports. Both health risk factors (dyslipidemia and physical inactivity) and manifest physical illnesses (cardiovascular disease) were associated with lower total QoL. Conclusions In all domains, long-term CCS reported worse QoL than the comparison sample. The negative associations with risk factors and physical illnesses indicate an urgent need for long-term surveillance and health promotion.