Differences in adverse drug events and medication errors among pediatric inpatients aged <3 and ≥3 years: The JADE study

Background Adverse drug events (ADEs) are defined as any injuries due to medication use. We hypothesized that the incidences of ADEs and medication errors (MEs) could be associated with linguistic skills of pediatric patients. Methods We analyzed data from the Japan Adverse Drug Events study on pediatric inpatients. This study included inpatients aged one months and older and less than seven years old. We compared the primary outcome of ADEs and MEs between patients aged under three years and three years and older as children typically do not acquire sufficient linguistic skills until around three years of age. Results This study included 639 patients; 412 (64%) patients aged under three years and 227 (36%) patients aged three years and older. We identified 241 ADEs in 639 patients; 152 ADEs among patients aged under three years (37 ADEs per 100 patients) and 89 ADEs among those aged three years and older (39 ADEs per 100 patients). ADEs among patients aged under three years were less likely to be found (49 ADEs) during their hospital stay than those aged three years and older (20 ADEs) ( P = 0.02). Among 172 MEs identified in 639 patients, 25 MEs (15%) resulted in ADEs; 23 (92%) occurred to those aged under three years and two (8%) occurred to those aged three years and older ( P = 0.0008). Conclusion ADEs were less likely to be found and MEs resulted in ADEs more frequently in patients under three years old, and these differences could be explained by differences in their linguistic skill levels.

Heuristic Feature Selection for Wind Power Anomaly Events Study

Wind power ramp events are typical harmful anomaly events in wind engineering, which bring new threat to the safety operation of power systems. To in-depth understand ramps and mitigate their harms, suitable ramp characteristics are crucial in many studies, e.g., ramp definition, classification, prediction and so on. However, due to ramps’ specificity on event feature, more profound characteristics are needed besides basic ramp morphological characteristics. In this paper, an approach for extracting and selecting ramp characteristics is proposed for ramp study. First, according to ramps’ causation on energy change, wavelet transformation is introduced to analyze ramp categories, and used to extract ramp energy characteristics. Then, heuristic feature selection methods are proposed to select ramp characteristics based on specific ramp application contexts. The objective of feature selection is to remove redundant characteristics, and to improve ramp studies’ performance. Finally, combining basic ramp characteristics and wavelet characteristics, ramp studies on category classification and prediction of appointed characteristics are implemented on industrial data. The computational results validate the usefulness of wavelet characteristics, the feasibility of the proposed approach, and that performance of ramp study could be improved by using ramp characteristics in this paper.

It Wasn’t Sheer Luck After All

Evidence suggests that chance plays an important role in careers. Instead of describing such events through “sheer luck,” the authors propose in this theoretical and empirical chapter that opportunity and preparation helps explain the occurrence, perception, and selection of chance events. Study 1 used longitudinal data on 390 emerging adults who reported the occurrence of chance events in their school-to-work transition. Supporting the hypotheses, participants who had prepared better for the school-to-work transition and had better opportunities (in terms of their social network) experienced more chance events. Study 2 examined the perception and selection of chance events in a lab setting. Sixty-seven emerging adult applicants for an actual position were exposed to the same chance events. Consistent with hypotheses, better prepared job applicants were more likely to select these events. Instead of sheer luck, the authors suggest that job seekers can create serendipity by capitalizing on chance events.

Comparative analysis of between trading volume activities pre with post event tax amnesty

This study aims to determine the difference of Trading Volume Activity that exceed before and after the determination of tax amnesty policy and to figure out the existence of abnormal return formed before and after the determination of the tax amnesty. This study uses the Events Study method with 100 days observation for the estimation period and 15 days for event period. The study used a group of perception banks that listed in BEI in 2016 period as population and 22 selected stocks to be sampled by using saturated sampling method. During the observation period, positive and negative abnormal returns with fluctuating movements were formed. Trading Volume Activity changes between before and after-tax amnesty policy. From these two results, it can be concluded that there was leakage of information before the event published that indicates the form of market efficiency of Indonesia is half strong (semi strong form). Further research is suggested to use the calculation method and time different from this research to obtain more accurate results.

Tail Risk and Extreme Events: Connections between Oil and Clean Energy

Do tail events in the oil market trigger extreme responses by the clean-energy financial market (and vice versa)? This paper investigates the relationship between oil price and clean-energy stock with a novel methodology, namely extreme events study. The aim is to investigate an asymmetry effect between the response to good versus bad days. The results show how the two markets influence each other more negatively, i.e., extreme negative events significantly impact the other market. Furthermore, we document how the impact of the shock transmitted by oil prices to clean-energy stocks is less than the amount of shock transmitted oppositely. These findings have important implications for investor and renewable energy policies.

Does the “surprisingly popular” method yield accurate crowdsourced predictions?

The “surprisingly popular” method (SP) of aggregating individual judgments has shown promise in overcoming a weakness of other crowdsourcing methods—situations in which the majority is incorrect. This method relies on participants’ estimates of other participants’ judgments; when an option is chosen more often than the average metacognitive judgments of that option, it is “surprisingly popular” and is selected by the method. Although SP has been shown to improve group decision making about factual propositions (e.g., state capitals), its application to future outcomes has been limited. In three preregistered studies, we compared SP to other methods of aggregating individual predictions about future events. Study 1 examined predictions of football games, Study 2 examined predictions of the 2018 US midterm elections, and Study 3 examined predictions of basketball games. When applied to judgments made by objectively assessed experts, SP performed slightly better than other aggregation methods. Although there is still more to learn about the conditions under which SP is effective, it shows promise as a means of crowdsourcing predictions of future outcomes.

Comparative Analysis Between Pre-Trading Volume Activities with Post Event Tax Amnesty

This study aims to determine the difference of Trading Volume Activity that exceed before and after the determination of tax amnesty policy and to figure out the existence of abnormal return formed before and after the determination of the tax amnesty. This study uses the Events Study method with 100 days observation for the estimation period and 15 days for event period. The study used a group of perception banks that listed in BEI in 2016 period as population and 22 selected stocks to be sampled by using saturated sampling method. During the observation period, positive and negative abnormal returns with fluctuating movements were formed. Trading Volume Activity changes between before and after-tax amnesty policy. From these two results, it can be concluded that there was leakage of information before the event published that indicates the form of market efficiency of Indonesia is half strong (semistrong form). Further research is suggested to use the calculation method and time period different from this research in order to obtain more accurate results.

Occurrence of and Reasons for “Missing Events” in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies

Background Establishing a methodology for assessing nutritional behavior comprehensively and accurately poses a great challenge. Mobile technologies such as mobile image-based food recording apps enable eating events to be assessed in the moment in real time, thereby reducing memory biases inherent in retrospective food records. However, users might find it challenging to take images of the food they consume at every eating event over an extended period, which might lead to incomplete records of eating events (missing events). Objective Analyzing data from 3 studies that used mobile image-based food recording apps and varied in their technical enrichment, this study aims to assess how often eating events (meals and snacks) were missed over a period of 8 days in a naturalistic setting by comparing the number of recorded events with the number of normative expected events, over time, and with recollections of missing events. Methods Participants in 3 event-based Ecological Momentary Assessment (EMA) studies using mobile image-based dietary assessments were asked to record all eating events (study 1, N=38, 1070 eating events; study 2, N=35, 934 eating events; study 3, N=110, 3469 eating events). Study 1 used a basic app; study 2 included 1 fixed reminder and the possibility to add meals after the actual eating events occurred instead of in the moment (addendum); and study 3 included 2 fixed reminders, an addendum feature, and the option to record skipped meals. The number of recalled missed events and their reasons were assessed by semistructured interviews after the EMA period (studies 1 and 2) and daily questionnaires (study 3). Results Overall, 183 participants reported 5473 eating events. Although the momentary adherence rate as indexed by a comparison with normative expected events was generally high across all 3 studies, a differential pattern of results emerged with a higher rate of logged meals in the more technically intensive study 3. Multilevel models for the logging trajectories of reported meals in all 3 studies showed a significant, albeit small, decline over time (b=−.11 to −.14, Ps<.001, pseudo-R²=0.04-0.06), mainly because of a drop in reported snacks between days 1 and 2. Intraclass coefficients indicated that 38% or less of the observed variance was because of individual differences. The most common reasons for missing events were competing activities and technical issues, whereas situational barriers were less important. Conclusions Three different indicators (normative, time stability, and recalled missing events) consistently indicated missing events. However, given the intensive nature of diet EMA protocols, the effect sizes were rather small and the logging trajectories over time were remarkably stable. Moreover, the individual’s actual state and context seemed to exert a greater influence on adherence rates than stable individual differences, which emphasizes the need for a more nuanced understanding of the factors that affect momentary adherence.