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As the airline industry has become ever-more competitive and profitability more tenuous, airline service quality management has grown more important to airlines. Although many studies have focused on the evaluation of airline service quality, some common limitations need to be noted. First, traditional fuzzy logics were utilized to present linguistic variables as fuzzy numbers. However, precise quantification of lower and upper bounds with a single number is often difficult; thus, interval-valued fuzzy sets that represent the lower and upper bounds in the fuzzy number as an interval form should be applied instead. Second, while some studies have applied various multiple-criteria decision-making method [MCDM] and the service quality (SERVQUAL) method for evaluation of airline service quality, few have utilized grey relational analysis (GRA, a simple and data-driven MCDM method applicable to environments with incomplete information) and the service performance (SERVPERF), a performance-based measure that can resolve the ambiguity issue of the expectations construct in SERVQUAL. Third, extant studies dealing with the issue of weighting criteria in the evaluation of airline service quality have focused only on either subjective or objective weights, though weighting criteria based on a combined objective/subjective approach would be much better than those just considering the subjective approach. The present study endeavored to fill these literature gaps by developing, for evaluation of airline service quality, interval-valued fuzzy GRA with SERVPERF based on both subjective and objective weights. It contributes to the field by incorporating the 22 criteria from SERVPERF to effectively account for the various characteristics of airline service. Additionally, it is the first study to utilize interval-valued fuzzy GRA together with a novel technique that combines a subjective/objective weighting method for integration of objective decision-matrix-derived information with subjective decision-maker preferences. The supplemental empirical case study of airline service evaluation, further, provides researchers and practitioners with a means of better understanding the proposed approach in the practical perspectives. [ABSTRACT FROM AUTHOR]

Background: English editing services are effective for improving manuscript quality as well as providing learning opportunities for non-native English-speaking authors. Herein, we describe the effects of a combined system of in-house and external editing services for handling large volumes of editing requests and providing personalized editing service in academic hospitals. Methods: We established the Scientific Publications Team (SPT), an in-house editing team in Asan Medical Center in Seoul, Korea. The SPT is composed of two professional editors who manage editing requests sent to external companies while also providing one-on-one in-house editing services. We gathered author satisfaction data from 936 surveys between July 2017 and December 2018 and analyzed the number of editing requests and research publications by segmented regression analysis of interrupted time series data. Results: The SPT processed 3931 editing requests in 2017–2018, which was a marked increase compared with prior to its establishment (P = 0.0097). The authors were generally satisfied with the quality of editing services from both in-house and external editors. Upon conducting regular quality control, overall author satisfaction with one external company gradually increased over the course of one year (P for trend = 0.086). Author satisfaction survey results revealed that overall satisfaction of editing service was most strongly correlated with how well the edits conformed to the authors’ intentions (R = 0.796), and was only weakly correlated with quick turnaround time (R = 0.355). We also observed a significant increase in the trend of the number of research publications (P = 0.0007) at one year after the establishment of the SPT. Conclusion: Providing a combination of in-house and external editing services resulted in high author satisfaction and subsequent hospital-wide increases in manuscript writing and publication. Our model system may be adapted in academic hospitals to better address the editing needs of non-native English-speaking researchers. [ABSTRACT FROM AUTHOR]

Objective: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Korean adolescents of high risk suicide (= who have history of suicide ideation/attempt in previous year) using machine learning techniques. Methods: A nationally representative dataset of Korea Youth Risk Behavior Web-based Survey (KYRBWS) was used (n = 59,984 of middle and high school students in 2017). The classification process was performed using machine learning techniques such as logistic regression (LR), random forest (RF), support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting (XGB). Results: A total of 7,443 adolescents (12.4%) had a previous history of suicidal ideation/attempt. In the multivariable analysis, sadness (odds ratio [OR], 6.41; 95% confidence interval [95% CI], 6.08–6.87), violence (OR, 2.32; 95% CI, 2.01–2.67), substance use (OR, 1.93; 95% CI, 1.52–2.45), and stress (OR, 1.63; 95% CI, 1.40–1.86) were associated factors. Taking into account 26 variables as predictors, the accuracy of models of machine learning techniques to predict the high-risk suicidal was comparable with that of LR; the accuracy was best in XGB (79.0%), followed by SVM (78.7%), LR (77.9%), RF (77.8%), and ANN (77.5%). Conclusions: The machine leaning techniques showed comparable performance with LR to classify adolescents who have previous history of suicidal ideation/attempt. This model will hopefully serve as a foundation for decreasing future suicides as it enables early identification of adolescents at risk of suicide and modification of risk factors. [ABSTRACT FROM AUTHOR]

Personal values refer to the beliefs, principles or ideas that are important to people’s lives. We investigated the associations between personal values and happiness. We inquired about the importance of four different categories of personal values: prioritizing social relationships, extrinsic achievements, physical health, and spirituality. Data were drawn from the Korean General Social Survey (KGSS), a nationally representative cross-sectional sample collected over three years (i.e., 2007, 2008, and 2009). The findings showed that respondents prioritizing religion (i.e., spirituality) were the most likely to be happy, followed by those prioritizing social relationships, including family, friends, and neighbors. Those who prioritized extrinsic achievements (money, power, educational attainment, work, and leisure) as well as health were least likely to be happy. The findings suggest that pursuing goals focused on self-enhancement or self-centered value are less likely to result in happiness compared to pursuing alter-centered collective goals or self-transcendence/selflessness. [ABSTRACT FROM AUTHOR]

Objectives: The South Korean government required the submission of economic evidence when it implemented the Positive-List System in December 2006. This study investigates the key factors that influenced actual public insurance reimbursement decisions, including the role of economic evidence, after 10 years of decision practice under compulsory health technology assessment (HTA) for new drugs. Method: Logistic regression analysis was used to estimate the impact of the variables involved, including cost-effectiveness ratio as a key variable, on reimbursement decisions. The latter were defined as “yes” or “no” at a submitted price and indication. Only cases (n = 91) that present a cost-effectiveness ratio, and that have been reviewed based on this ratio from January 2007 to December 2016, were included in the analysis. Results: Cases with higher cost-effectiveness ratios were less likely to be accepted. In addition, drugs that were used to treat severe diseases and drugs with no substitute were more likely to be recommended. The probability of acceptance declined along with the level of uncertainty in the submitted evidence. The acceptance rate for severe-disease drugs has increased since 2013, when the government introduced several policies that lowered the existing barriers to positive reimbursement. However, such an increase was not statistically significant. Conclusions: Cost-effectiveness is one of the most influential factors in drug-reimbursement decisions. However, inclusion of other explanatory variables, in addition to the cost-effectiveness ratio, predicted the results of decisions more accurately. [ABSTRACT FROM AUTHOR]

Background: There is not enough evidence regarding how information obtained from general health check-ups can predict individual mortality based on long-term follow-ups and large sample sizes. This study evaluated the applicability of various health information and measurements, consisting of self-reported data, anthropometric measurements and laboratory test results, in predicting individual mortality. Methods: The National Health Screening Cohort included 514,866 participants (aged 40–79 years) who were randomly selected from the overall database of the national health screening program in 2002–2003. Death was determined from causes of death statistics provided by Statistics Korea. We assessed variables that were collected at baseline and repeatedly measured for two consecutive years using traditional and time-variant Cox proportional hazards models in addition to random forest and boosting algorithms to identify predictors of 10-year all-cause mortality. Participants’ age at enrollment, lifestyle factors, anthropometric measurements and laboratory test results were included in the prediction models. We used c-statistics to assess the discriminatory ability of the models, their external validity and the ratio of expected to observed numbers to evaluate model calibration. Eligibility of Medicaid and household income levels were used as inequality indexes. Results: After the follow-up by 2013, 38,031 deaths were identified. The risk score based on the selected health information and measurements achieved a higher discriminatory ability for mortality prediction (c-statistics = 0.832, 0.841, 0.893, and 0.712 for Cox model, time-variant Cox model, random forest and boosting, respectively) than that of the previous studies. The results were externally validated using the community-based cohort data (c-statistics = 0.814). Conclusions: Individuals’ health information and measurements based on health screening can provide early indicators of their 10-year death risk, which can be useful for health monitoring and related policy decisions. [ABSTRACT FROM AUTHOR]

Objectives: Little is known about health outcomes related to electronic cigarette (EC) use, despite its growing popularity. The aim of this study is to investigate the association between EC use and asthma. Methods: The study design is a cross-sectional study. A total of 35,904 high school students were included as the final study population. The presence of asthma was based on a student’s self-reported doctor diagnosis of asthma in the past 12 months. Results: Prevalence rates of asthmatics in ‘current EC users’ (n = 2,513), ‘former EC users’ (n = 2,078), and ‘never EC users’ (n = 31,313), were 3.9% (n = 98), 2.2% (n = 46) and 1.7% (n = 530), respectively. Comparing ‘current EC’ users with ‘never EC’ users, the unadjusted OR for asthma was 2.36 (95% CI: 1.89–2.94). In order to control for the effect of conventional cigarette (CC) smoking, after stratifying the subjects by the three CC smoking categories (never CC, former CC, and current CC), within the ‘never CC’ category, the unadjusted OR for asthma for ‘current EC’ users was 3.41 (95% CI: 1.79–6.49), and the adjusted OR was 2.74 (95% CI: 1.30–5.78). Severe asthma was reflected by the number of days absent from school due to asthma symptoms; current EC users had the highest adjusted OR for severe asthma compared to ‘never EC’ users. Conclusions: When compared to a reference population of high school students in South Korea, EC users have an increased association with asthma and are more likely to have had days absent from school due to severe asthma symptoms. In conclusion, the results indicate that EC use may be a risk factor for asthma. The results may be useful in developing a scientific basis for the evaluation of a potential health hazard by EC. [ABSTRACT FROM AUTHOR]