Development of the Korean Developmental Screening Test for Infants and Children (K-DST).

BACKGROUND: Most developmental screening tools in Korea are adopted from foreign tests. To ensure efficient screening of infants and children in Korea, a nationwide screening tool with high reliability and validity is needed. PURPOSE: This study aimed to independently develop, standardize, and validate the Korean Developmental Screening Test for Infants and Children (K-DST) for screening infants and children for neurodevelopmental disorders in Korea. METHODS: The standardization and validation conducted in 2012-2014 of 3,284 subjects (4-71 months of age) resulted in the first edition of the K-DST. The restandardization and revalidation performed in 2015-2016 of 3.06 million attendees of the National Health Screening Program for Infants and Children resulted in the revised K-DST. We analyzed inter-item consistency and test-retest reliability for the reliability analysis. Regarding the validation of K-DST, we examined the construct validity, sensitivity and specificity, receiver operating characteristic curve analysis, and a criterion-related validity analysis. RESULTS: We ultimately selected 8 questions in 6 developmental domains. For most age groups and each domain, internal consistency was 0.73-0.93 and test-retest reliability was 0.77-0.88. The revised K-DST had high discriminatory ability with a sensitivity of 0.833 and specificity of 0.979. The test supported construct validity by distinguishing between normal and neurodevelopmentally delayed groups. The language and cognition domain of the revised K-DST was highly correlated with the K-Bayley Scales of Infant Development-II's Mental Age Quotient (r=0.766, 0.739), while the gross and fine motor domains were highly correlated with Motor Age Quotient (r=0.695, 0.668), respectively. The Verbal Intelligence Quotient of Korean Wechsler Preschool and Primary Scales of Intelligence was highly correlated with the K-DST cognition and language domains (r=0.701, 0.770), as was the performance intelligence quotient with the fine motor domain (r=0.700). CONCLUSION: The K-DST is reliable and valid, suggesting its good potential as an effective screening tool for infants and children with neurodevelopmental disorders in Korea.

Acupuncture for Alcohol Use Disorder: A Meta-Analysis.

Empirical research has produced mixed results regarding the effects of acupuncture on the treatment of alcohol use disorder in humans. Few studies have provided a comprehensive review or a systematic overview of the magnitude of the treatment effect of acupuncture on alcoholism. This study investigated the effects of acupuncture on alcohol-related symptoms and behaviors in patients with this disorder. The PubMed database was searched until 23 August 2016, and reference lists from review studies were also reviewed. Seventeen studies were identified for a full-text inspection, and seven (243 patients) of these met our inclusion criteria. The outcomes assessed at the last posttreatment point and any available follow-up data were extracted from each of the studies. Our meta-analysis demonstrated that an acupuncture intervention had a stronger effect on reducing alcohol-related symptoms and behaviors than did the control intervention (g = 0.67). A beneficial but weak effect of acupuncture treatment was also found in the follow-up data (g = 0.29). Although our analysis showed a significant difference between acupuncture and the control intervention in patients with alcohol use disorder, this meta-analysis is limited by the small number of studies included. Thus, a larger cohort study is required to provide a firm conclusion.

The Effects of Acupuncture Stimulation for Brain Activation and Alcohol Abstinence Self-Efficacy: Functional MRI Study.

We attempted to investigate whether acupuncture stimulation at HT7 can have an effect on brain activation patterns and alcohol abstinence self-efficacy. Thirty-four right-handed healthy subjects were recruited for this study. They were randomly assigned into two groups: the HT7 (Shenmen) group and the LI5 (Yangxi) group. Acupuncture stimulation was performed using a block paradigm during fMRI scanning. Additionally, the Korean version of Alcohol Abstinence Self-Efficacy Scale (AASES) was used to determine the effect of acupuncture stimulation on self-efficacy to abstain from alcohol use. According to the result of fMRI group analysis, the activation induced by HT7 stimulation was found on the bilateral postcentral gyrus, inferior parietal lobule, inferior frontal gyrus, claustrum, insula, and anterior lobe of the cerebellum, as well as on the left posterior lobe of the cerebellum (p < 0.001, uncorrected). According to the AASES analysis, the interaction effect for gender and treatment was marginally significant (F(1, 30) = 4.152, p = 0.050). For female group, the simple main effect of treatment was significant (F(1, 11) = 8.040, p = 0.016), indicating that the mean change score was higher in the HT7 stimulation than in the LI5 stimulation. Therefore, our study has provided evidence to support that HT7 stimulation has a positive therapeutic effect on the alcohol-related diseases.

Molecular learning with DNA kernel machines.

We present a computational learning method for bio-molecular classification. This method shows how to design biochemical operations both for learning and pattern classification. As opposed to prior work, our molecular algorithm learns generic classes considering the realization in vitro via a sequence of molecular biological operations on sets of DNA examples. Specifically, hybridization between DNA molecules is interpreted as computing the inner product between embedded vectors in a corresponding vector space, and our algorithm performs learning of a binary classifier in this vector space. We analyze the thermodynamic behavior of these learning algorithms, and show simulations on artificial and real datasets as well as demonstrate preliminary wet experimental results using gel electrophoresis.

When fit indices and residuals are incompatible.

Standard chi-square-based fit indices for factor analysis and related models have a little known property: They are more sensitive to misfit when unique variances are small than when they are large. Consequently, very small correlation residuals indicating excellent fit can be accompanied by indications of bad fit by the fit indices when unique variances are small. An empirical example of this incompatibility between residuals and fit indices is provided. For illustrative purposes, an artificial example is provided that yields exactly the same correlation residuals as the empirical example but has larger unique variances. For this example, the fit indices indicate excellent fit. A theoretical explanation for this phenomenon is provided using relationships between unique variances and eigenvalues of the fitted correlation matrix.

Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective.

A central problem in the application of exploratory factor analysis is deciding how many factors to retain (m). Although this is inherently a model selection problem, a model selection perspective is rarely adopted for this task. We suggest that Cudeck and Henly's (1991) framework can be applied to guide the selection process. Researchers must first identify the analytic goal: identifying the (approximately) correct m or identifying the most replicable m. Second, researchers must choose fit indices that are most congruent with their goal. Consistent with theory, a simulation study showed that different fit indices are best suited to different goals. Moreover, model selection with one goal in mind (e.g., identifying the approximately correct m) will not necessarily lead to the same number of factors as model selection with the other goal in mind (e.g., identifying the most replicable m). We recommend that researchers more thoroughly consider what they mean by "the right number of factors" before they choose fit indices.