In this paper, we describe a code-reading support environment and practical classroom applications using this environment to understand nested loops. Previously, we developed a code-reading support system based on visualization of the relationships among the program code, target domain world, and operations. We implemented the proposed system in exercises with nested loops. The evaluation results suggested that students could frequently fulfill learning objectives using the proposed system. However, we also discovered that some students experienced a learning impasse in the classroom. We attempted to address these students with two supporting approaches: bridging the gap between the generalization structures in the program code and their corresponding operations and enabling learners to predict the behavior of the nested loops. In this paper, we extend our previous system with new functions based on our two supporting approaches. Further, we implement the system in another classroom for nested loops. We describe a correlation between the proposed system and an understanding of nested loops using pre-/post-test comparisons. We discuss how code reading using the proposed system allows learners to cultivate a superior understanding of the program code. With the continued rapid development and spread of information equipment such as smartphones, productivity improvements for program codes have been increasingly required. Software-developing environments have been enhanced, and programming languages have developed their descriptive capabilities. Programming skills are becoming necessary for not only software engineers. In the context of society informatization, increasing numbers of learners require an education in computer programming nth lap of the loop. Students often struggle to generalize a set of concrete operations into an abstract function with variables. They tend to be able to interpret the processing contents of the first lap of the loop, the second lap of that, the third lap of that, and so on, while not to the contents of the Students sometimes fail to grasp how the values of variables change with the execution of each statement. For several years, we have conducted programming classes for a wide variety of students. Through our experience in the classroom, we have paid attention to three fundamental skills that novice programming students tend to find difficult to acquire:Nested loops are a learning target with which novice learners frequently have an initial difficulty. This is because to fully comprehend this concept requires that the learner understands all three of the abovementioned fundamentals. Koppelman and van Dijk  emphasizIn this paper, we describe our code-reading support environment and the classroom applications of using this environment to understand nested loops. Previously, we developed a learning support system for code reading , the system displays the state of the target domain after executing the operation in (b). Thus, the learner can understand the role of a certain sequence of operations by comparing or observing the visualized target domain field before and after execution. Furthermore, the system highlights the code fragment in (a) corresponding to the selected operation in (c) and vice versa when the learner first clicks on a fragment in (a). The correspondence between a code fragment and an operation is therefore apparent to the learner. We believe that important information can be understood and retained using LEPA’s visualization, including what happens in the target domain field when a concrete operation is executed and what kind of code is required to create this effect.The learner can push the “pack” button to pack the selected operation sequence into a package. Packages are permitted in a nested structure.The learner can tag the package with a natural-language description according to its function , then the following two options are available:The resulting packed structure of the operation sequence ideally comes closer to the program code’s structure. The learner will arrive at an understanding of the entire control sequence for the program code by completing a series of these activities.nth lap of a loop . However, the program code for a nested loop is provided throughout the hierarchy. Having generalized the first-level hierarchy into “output kth step of the pyramid” with the variable k, the learner moves on to the deeper levels such as “output N-k spaces” or “output 2k-1 asterisks.” Given generalizations throughout the hierarchy, the learner can realize the meaning of the control statements for the nested loops in the program code.In LEPA1, the target for generalized tagging is only available at the first hierarchical level. This means that the learner tags the nth lap of the inner loops. Further, we have implemented a function that automatically generates a template for the general tag with the following steps:Discriminating variable words from invariable words in the set of tags on the packages to be generalizedReplacing variable words with a series of symbols such as “_”Based on these discussions, we have implemented a function that enables users to generalize a package while retaining the explicit hierarchy. Thus, the learner can tag the For example, in displaying a pyramid, the proposed system generates templates such as “output XXX spaces,” “output ??? asterisks,” and “output ___th step of the pyramid” from the set of tags. By providing these templates, the proposed system encourages learners to formulate “XXX,” “???,” and “___” with loop control variables in the program code. The screenshot in Fig. i in a loop controlled by i. Therefore, the iteration package corresponding to the statement consists of a sequence of operations with different descriptions. Generalization in the proposed system involves two phases: identifying operations that regularly vary in the iterative package of the operation field and formulating this regularity. Nested loops increase the diversity of repetitiveness in the corresponding operations. We must consider not only the inner and outer loops where the control variables are referenced but also loops with references to variables that control the outer loop. This diversity can be regarded as a factor that novice programmers tend to find difficult to comprehend the relationship between the code of a nested loop and its behavior.Programmers implement loops to include both identical operations and a wide variety of repetitive operations by appropriately referencing the loop’s control variables. For example, different values are displayed by iterative execution of a statement to display the value of the variable Ch1. A statement to iterate in the inner loop references control variables from the outer loop.Ch2. A conditional statement in the inner loop references control variables from the outer loop.We constructed the second supporting approach to understand relationships by developing a classification of nested loops. By investigating textbooks and exercises, we have focused on the following two characteristics in nested loop code:A nested loop with Ch1 includes operations of varying representations at each iteration step of the outer loop—that is, for each inner loop. For example, the left side in Fig. Without either Ch1 or Ch2—the operations corresponding to each inner loop and the number of them will never change.With Ch1—the operations corresponding to each inner loop will change in each outer loop step; however, the number will not.With Ch2—the number of operations corresponding to each inner loop will change in each outer loop step; however, the operations themselves will not.With both Ch1 and Ch2—both the operations corresponding to each inner loop and the number of them will change in each outer loop step.We define “changing-step-contents type” as a type of nested loop with Ch1 and “changing-step-counts type” as a type with Ch2. The behavior of a nested loop can be classified into the following four classes based on the absence or presence of each characteristics:In their packing series, learners must appropriately recognize the repetitiveness of an operation sequence as to whether it has these characteristics. Furthermore, to recognize the repetitiveness, learners must anticipate the regularity in the operation field based on the characteristics in the program code field. If learners can classify a nested loop code, they can reproduce the behavior of the nested loop based on the behavior pattern of the class. Moreover, by determining the behavior pattern of an algorithm in the coding, novice programmers can identify the characteristics to incorporate into the program code.Hints related to where in the program code they should focusHints as to what characteristics they should be reading in the code revealed by the above hintsThe characteristics that should have been readBased on these discussions, we attempt to teach students these characteristics, aiming to develop in them a better understanding of nested loops. Furthermore, we have implemented a function that involves requesting users to identify the type of nested loop provided in the program code field and whether it is the changing-step-contents type, the changing-step-counts type, both, or neither. For users who cannot provide an answer, LEPA2 suggests hints:In this subsection, we present an overview of the proposed extended system, LEPA2. Although the external appearance of LEPA2 is similar to that of LEPA1 Ex1—Moreover, if the learners click an operation in the operation field, LEPA2 highlights the statement in the program code field corresponding to the operation. If the learners push the “Store” button, LEPA2 copies the current status of the target domain world displaying in the area (b) into (a). This function support learners to observe the differences between the status of the target domain before and after executing specific statements or operations.Abstraction: Learners pack operations and recognize the abstract function of the package. Packing with nested structures helps learners to understand the nested structures of the entire program. Figure Ex2—Generalization: After completing the packing for all the operations, learners generalize the packages corresponding to the nested loops, following the guidance of LEPA2. LEPA2 generates templates for the general tag based on the approach described in the “Ex3—Auto-complete function to support creating repetitive packages by displaying the learner’s tagging historyFunction to support focusing on repetitive packages by displaying similar tags in the same colorFunction to support searching for the repetitiveness in the tags by hiding the concrete operationsnth lap by providing a generalization templateFunction to support appropriately tagging the In nested loops, the repetitiveness to be discovered during the generalization phase does not appear in the concrete operations. Rather, it appears in the tags to packages packed by the learner. We have implemented the following functions to notify the learner in Ex3:Observing characteristics of the nested loop: Lastly, learners observe the characteristics of the nested loop in the program code field to increase their understanding of nested loops. LEPA2 requests learners to identify the characteristics of nested loops based on the approach described in the “Ex4—Learners could acquire the skills of tracing values of variables in the entire program code through observing the statuses in the target domain field.Learners could understand nested structures in control flows and code descriptions through packing sequences of operations hierarchically.Tags and structures of packages of operation sequences could visualize each learner’s level of understanding and could provide information for better instructions to teachers.We conducted exercise classes to understand nested loops with LEPA2 as described in the previous section. Our previous educational practice  asked for the execution results expected from tracing the entire program by hand, including the nested loop. Question 2 (Q2) asked for the code fragment in the control of the inner loop with the execution results provided; question 3 (Q3) asked for the same for the outer loop. Question 4 (Q4) asked for the characteristics of the nested loops expected to appear in the program code, given the execution results only. Q1, Q2, and Q3 were designed to verify Hypo1; Q4 was designed to verify Hypo2. Table For the control practice, students were first given the same 1-h lecture on nested loops as the experimental group, including an explanation of the characteristics of nested loops. We subsequently conducted the 15-min pre-test. Then, they studied nested loops using textbooks and the lecture material, without using LEPA2. Before studying, the teacher explained that the aim of the study was to understand nested loops using a sample program. The sample program was identical to the one in the experimental practice. The teacher also explained that, in particular, they should study tracing the program. After a 1-h study period, we conducted the 15-min post-test. Both pre- and post-tests were the same as those given to the experimental group.Table We think that the improved results for the control group with regard to Q1 were a consequence of emphasizing tracing as the aim of the study. It is likely that the control group applied a significant portion of their time tracing. Therefore, we consider this group to have an advantage over the experimental group, whose study consisted of four stepwise exercises.The experimental group had an interval of 1 week between pre- and post-tests because of schedule restriction. This was because we incorporated the classroom practice into a series of actual classes. This interval is not short and consequently allowed the experimental group to learn out of class with textbooks and course notes. Although the influences of this possibility on the score of the post-test must be considered, it is difficult to quantify them. However, we infer that the influences are practically trivial because all the experimental subjects had learned nested loops in Programming I classes held in an earlier semester. If the subjects had understood nested loops in that earlier class or by out-of-class learning, they would have tended to score high in the pre-test. Note that we conducted classes for nested loop again because the lack of student’s understanding of nested loop hinders the exercise in Programming II. There was no actual tendency to score high; thus, we consider the influence of out-of-class learning as a negligible factor.If we conducted both the pre- and post-tests in the same class session, the subjects would have a week interval between the pre-test and the classroom lecture because of the schedule restriction. In this case, the possibility of forgetting lecture contents would influence the score of the pre-test.A1. The student consumed sufficient time (more than 3 min) tracing the program (Ex1).A2. The student packed all operation sequences corresponding to the inner loops and tagged all of the packages (Ex2).A3. The student formulated a general tag provided in the form of a template, using the guidance function from the outer loop generalization (Ex3).A4. The student used the function to observe the characteristics of nested loops (Ex4).We carefully reviewed the footage recorded from each student in the experimental group to analyze the learning effects in additional detail. Thereby, we found that the interactions with the learning environment provided by the proposed system differ significantly by student. For some activities made by using functions we expected to use, we classified the students into those who performed the activity (the positive group) and those who did not (the negative group). We rejected the activities that have greater than double times difference between the positive and negative groups to reduce the bias between the numbers of the both groups. Consequently, we focused on the following four activities:In A1, 3 min is the time we supposed to take to trace the entire program code with observing three fields. In actual exercise, there was bipolarization between the time to trace by the positive group, who take much more than 3 min, and the time to trace by the negative group, who take less than 1 min.A1 advances an understanding of the behavior of an entire nested loop from which the student will acquire tracing skills.A2 promotes an understanding of the step contents in the inner loops from which the student will understand the structure of a nested loop.A3 assists the understanding of the step contents in the outer loop from which the student will acquire the skills required to generalize concrete operations.A4 leads to an understanding of the characteristics of nested loops from which the student will understand the relationships between the behavior and the characteristics in the program code.We consider these activities to lead to the following learning effects:We expect that students performing these activities will improve their marks as follows: students who performed A1 will score better on Q1; those who performed A2 will score better on Q2; and likewise for those performing A3 and A4 for Q3 and Q4, respectively.t test, if the difference between the negative and positive groups is statistically significant such that the progress level reached p = 0.05, we placed an asterisk next to the number. As expected, each positive group demonstrated significant progress for their marks on the corresponding question.Table We must consider that a statistically insufficient number of the subjects may influence the accuracy of verification. Our evaluation results do not have sufficient reliability because we could not procure a sufficient number of subjects in the classroom practice. The course we selected for our class is optional for the faculty, and the number of applicants varies from year to year. Whereas practice in actual classes provides practical learning information, the number of subjects is related to the number of applicants. However, we believe that continuous practice will suppress this matter. The progress with regard to Q1, Q2, and Q3 suggests in favor of Hypo1 and that of Q4 for Hypo2. Hence, although preliminarily, the results suggests that the proposed system results in an improved understanding of nested loops provided the user performs the expected activities. We must consider that a statistically insufficient number of the subjects may influence the accuracy of verification. However, we believe that continuous practice will suppress this matter.In general, programming students learn algorithm, code readings, and coding in turn. They attend a lecture and receive algorithm instruction from their teacher. Then, they reproduce the behavior of the algorithm using certain input data and produce a sequence of concrete operations that represents the behavior of the algorithm. Subsequently, they abstract sequences of operations, grasp the relationship between the abstracted operations and the program code, and consequently understand the entire program code. Finally, they perform a coding exercise to confirm their understandings.Thus far, several intelligent tutoring systems have been developed to support programming learners. These include RoboProf  suspected of not appropriately understanding the concept of variables. There is also a tendency of the class not to distinguish between using a constant number from reference variables. This information provided by LEPA allows teachers to make a decision as to the required instruction, especially to make opportunity discovery. In the pilot experiment, we did not evaluate the contribution degree. We plan to conduct further experiments to obtain more information regarding this.In programming education, there are minimal reports available on the learning effect of code reading. In our opinion, this is caused by the difficulty in externalizing learning outcomes. As indicated in Fig. In this paper, we described our learning support system and classroom practices with the proposed system for an improved understanding of nested loops. Nested loops are an appropriate target for learning the fundamental skills of programming. We believe that learning support systems efficiently and effectively contribute to an understanding of fundamental programming concepts and the acquisition of the skills required to utilize them.In the classroom practice with LEPA1, we determined that some students had experienced a learning impasse. We attempted to address this with two supporting approaches: bridging the gap between generalization structures in the program code and their corresponding operations and enabling learners to predict the behavior of nested loops by observing two characteristics in the code. For the former approach, we developed a function for generalizing packages by maintaining an explicit hierarchy. For the latter, a function allowing learners to observe the characteristics of nested loops was provided.We conducted a controlled experiment to evaluate in detail the effect of LEPA2 with the abovementioned functions incorporated. In the experimental practice with 12 students forming an experimental group, we incorporated LEPA2 in an actual classroom. In the controlled experiment with five students forming a control group, we evaluated learning effects using traditional teaching materials such as textbooks. The evaluation results based on the scores calculated from a pre- and post-tests suggest that there was a correlation between using LEPA2 and an understanding of nested loops although preliminarily.Package structures and tags generated in learning with the proposed system can be regarded as an externalized learner understanding that is observable by teachers. Feedback provided by these is useful information for teachers’ instruction. Consequently, qualitative improvements of instruction are expected. Hence, we consider that the proposed system directly and indirectly supports learners to read the program code and cultivate a better understanding of the program code.We can highlight two limitations of the proposed works derived from classroom practices incorporated into a series of actual classes. First, our evaluation results do not have sufficient reliability because we could not procure a sufficient number of subjects in the classroom practice, as described in the “Furthermore, we must allow a 1-week interval between pre- and post-tests in experimental practice because of the schedule restriction. We infer that the influences of this are minimal, as described in the “In future work, we will consider how the proposed system contributes to improve education for programming, as described in the “


Internet gaming disorder and risky online behavior  have emerged as serious problems in the digital age. Prevalence rates range from 4% to 40% across the globe, with Asia being one of the hardest-hit regions. To address these pressing problems, our team designed the Wise IT-use (WIT) program, a universal prevention program that (a) enhances students’ awareness of Internet gaming disorder and an array of common risky online behaviors, and (b) equips them with sufficient knowledge to handle such problems. The WIT program design was based on gamification principles and flow theory to enhance users’ motivation and learning experience. A program evaluation study was conducted to assess the social impact of this program in mitigating symptoms of Internet gaming disorder and risky online behavior, and in bolstering emotional well-being. The participants were 248 students aged 7 to 13 from four primary schools in various regions of Hong Kong. They completed validated questionnaires 1 month before and 2 months after participating in the program to evaluate changes in their symptoms of Internet gaming disorder, the frequency with which they displayed risky online behaviors, and their ratings of emotional well-being across the period. The results revealed that both the symptoms of Internet gaming disorder and the proportion of students at risk of the disorder were reduced after the program. The changes observed in students were related to higher levels of positive affect and lower levels of negative affect. Evidence from this study indicates that Internet gaming disorder and risky online behavior are detrimental to the emotional well-being of Hong Kong primary school students. More importantly, the findings demonstrate that our newly developed WIT program can have a social impact in successfully mitigating the symptoms of Internet gaming disorder and enhancing emotional well-being over time. The implications of these findings for the program’s broader impact on society and culture are discussed. In the digital age, the use of information technology (IT) has brought efficiency and convenience to myriad aspects of daily life e.g., C. . For insAlongside the global concern over the array of problems related to IT use, these problems have also attracted considerable research interest. Investigations into the prevalence of IT addiction and risky online behavior have found that the prevalence rates of Internet gaming disorder and Internet addiction range from 8% to 17% across nations e.g., . Of the Higher prevalence rates have been identified for various types of risky online behavior. For example, a recent meta-analysis revealed cyberbullying victimization to have an overall prevalence rate of 20–40% across age groups . The preThe high incidence rates of IT addiction and risky online behaviors have broader societal implications, prompting researchers to investigate the impacts of these emergent problems on users’ emotional well-being and on society as a whole. With regard to personal problems, a recent meta-analytic review of studies conducted in multiple nations worldwide revealed an inverse association between Internet gaming disorder and emotional well-being . IndividWith regard to interpersonal problems, the aforementioned meta-analytic review also indicated that individuals with Internet gaming disorder encounter more difficulties in their interpersonal relations . Owing tSimilar to Internet gaming disorder, risky online behaviors also elicit a range of personal problems. For instance, cyberbullying victimization is positively associated with depression, substance abuse, and suicidal ideation . More brThe deleterious psychosocial and societal impacts brought about by problematic IT use have led a number of mental health professionals to develop and implement dedicated interventions. A multinational systematic review revealed cognitive behavioral therapy to be the most frequently adopted treatment for Internet gaming disorder . A more In addition to cognitive behavioral therapy, mindfulness meditation and reality therapy have also been found to attenuate the symptoms of Internet gaming disorder and reduce decisional impulsivity, which refers to the tendency to make risky decisions by favoring smaller immediate rewards over larger but postponed rewards . InsteadCompared to Internet gaming disorder, interventions for risky online behavior have received less scholarly attention. Most intervention programs for risky online behavior have specifically targeted the mitigation of cyberbullying, probably due to the high prevalence of this type of risky online behavior . A recenPsychoeducation is a common intervention program for mitigating cyberbullying. For instance, one psychoeducation program for middle-school students was designed with reference to the theory of planned behavior . This prAnother psychoeducation program was developed and implemented for primary school students . In thisAll of the aforementioned programs for Internet gaming disorder are indicated interventions, meaning that they target individuals who manifest early signs of, or have already developed symptoms of, a given psychological problem , which aimed at mitigating the symptoms of Internet gaming disorder and risky online behaviors in the general population of children. For our program, there were no screening of participants prior to program implementation; instead, we adopted a universal impact strategy targeting children without any symptoms of Internet gaming disorder, those at risk of such a disorder, and those who had already developed symptoms. A universal strategy was preferred for children because the incidence of Internet gaming disorder in children is much lower than it is for adolescents and adults . Early iIn our program design, we adopted the novel training approach of gamification, which has been proven to be effective in enhancing children’s motivation and learning engagement e.g., . More spAdopting these theoretical learning approaches, our team constructed a gamified learning system—AIR —to make learning playful, fun, and sustainable for child participants. The WIT program was designed on the basis of the three fundamental components of this system. For the assimilation component, learning principles and materials on safe and healthy online behaviors were designed to be “injected” or assimilated into games such that learners acquire knowledge while being immersed in the games. For the interaction component, students were encouraged to interact with and learn from one another through the play-based activities built in to the learning sessions. For the reflection component, the program ensured that students would be guided by facilitators through various activities that called on them to reflect on their previous online experiences. Such engagement and reflection facilitate deep learning and the long-term retention of knowledge e.g., .The high prevalence of Internet gaming disorder makes it a particularly appropriate target for a universal preventive intervention intended to benefit a whole population, rather than just those subgroups or individuals identified to be at risk . Our proBy adopting a universal preventive approach, the WIT program aimed to meet the needs of Hong Kong society. To tackle the current surge in demand for mental health services, In response to the government’s call, we developed the WIT program to achieve social impact by addressing the emergent needs of society and provide timely solutions to pressing societal issues deriving from problematic IT use and Internet gaming disorder. Our psychoeducation program was the first to incorporate both the gamification approach and flow theory into its design. Adopting these innovative approaches in the program design aimed to enhance the engagement of our beneficiaries, students at upper-primary school levels, in the intervention. The beneficiaries who took part in this program learned and practiced skills that fostered self-regulation, online safety, digital citizenship, and interpersonal communication. Through acquiring and applying such skills in their daily life, the goal was for these students to be able to maintain a healthy balance of Internet use and to bolster their mental well-being accordingly.The effectiveness of our new program was evaluated by a social impact assessment through the use of quantitative methods. Specifically, the social benefits of our new program were measured in three ways: (a) prevention of the development of Internet gaming disorder through a decrease in the risk levels after program participation, (b) reduction of risky online behaviors, and (c) promotion of mental well-being. This study was thus conducted to empirically test these hypothesized effects of the WIT program. Specifically, we predicted that after students had taken part in our program, they would report fewer symptoms of Internet gaming disorder and less risky online behavior. We also expected them to experience better mental health, as indicated by higher levels of positive affect and lower levels of negative affect, social anxiety, and loneliness. If the program evaluation study yielded these desirable findings, we could conclude with confidence that the WIT program could be implemented in a larger number of schools to reach out to more beneficiaries, thus further broadening the program’s impact on society as a whole.a priori statistical power test to estimate the number of participants required to detect a statistically significant effect. We used the commonly adopted power analysis software G∗Power . Letters containing details of the study were distributed to the parents of all students in these schools. Those parents who allowed their children to take part were asked to sign and return the consent forms before a specified time, normally 4 weeks before the first session of the program started.SD = 0.97), with a range of 7–13 years.Eligible students were those who returned parental consent forms and gave their own consent. More than half of the participants were boys (56%). The average age of the sample was 10.16 years  and 2 months after (Time 2) the implementation of the WIT program. As some of the participating students were absent on one or both of the data collection days, 241 (58% boys) and 226 (55% boys) students completed the questionnaires at Time 1 and Time 2, respectively. As the WIT program had a duration of 3 months, the time span between these two data collection sessions was 6 months.strongly disagree (1) to strongly agree (4). The scale demonstrated adequate reliability at both time points in the current study .To assess the symptoms of Internet gaming disorder, we adopted the self-report version of the Korean Internet Addiction Proneness Scale  because The participants were classified into three groups based on the coding scheme used by never, rarely, sometimes, very often, and always. The scale had a high degree of reliability at both time points .As no comprehensive measure of risky online behavior was available, we compiled a questionnaire to assess the six most common types of risky online behavior: cyberbullying perpetration, cyberbullying victimization, exposure to online pornography, exposure to online violent content, meeting strangers online, and sharing online data. Of the 31 items, 28 were extracted from the Risky Online Behavior Inventory developed by very slightly or not at all) to 5 (extremely). The Chinese version for children has been found to have the relevant psychometric properties . The Chinese version has been validated , a research assistant oriented the participants, encouraged them to be open about expressing themselves, and provided them with instructions on how to answer the questions using the rating scales. Special guidance was given to participants who had difficulties in reading, understanding the questions, or both. The participants were reassured that their data would be used strictly for research purposes and would not be shown to their family members or to any school personnel. All participants filled in a set of baseline questionnaires. Three to four weeks later, the participants attended a 3-month training program.Two months after the training program (Time 2), participants were invited to attend a second data collection session during which they filled in the same set of questionnaires. The participants were debriefed at the end of the entire study and thanked for their participation.t-test was used to detect possible sex differences, and Pearson product-moment correlation analysis was performed to detect possible age differences. If demographic differences were found, separate analyses would be conducted for each demographic group. In addition, Pearson product-moment correlation analysis was used to indicate the magnitude of the inter-relationships among the study variables.Before conducting a social impact assessment of the new WIT program, we performed preliminary analyses to explore the potential demographic differences. An independent-samples For the social impact assessment, we adopted the following statistical methods to evaluate the social impact of the WIT program. We first evaluated whether our new program could prevent Internet gaming disorder by detecting the presence of changes in levels of risk before and after the program. Using the scores derived from the measure of Internet gaming disorder, participants were classified into “average gamers,” “at-risk gamers,” or “high-risk gamers” according to a scoring scheme for Asian youngsters . Their st-test was used to assess any significant changes in the scores of the study variables from Time 1 to Time 2. We performed this type of t-test because it was the most powerful method for detecting hypothesized within-participant variations between two assessments of quantitative continuous variables measured at different time points  and follow-up (Time 2) scores for all of the study variables. This analysis was chosen because it was deemed the most stable measure of interdependence among the set of quantitative continuous variables , offerint-tests revealed no significant differences in responses to the study variables according to respondents’ sex and none were significantly correlated with age (ps > 0.05). Hence, the major analyses were performed on the pooled sample. Independent-samples rs > 0.20, ps < 0.002). At Time 2, they were both positively related to negative affect, social anxiety, and loneliness , and inversely related to positive affect .These findings, which were replicated at both time points, are in line with our hypothesis that symptoms of Internet gaming disorder and risky online behavior would tend to compromise the mental health of primary school students.2(4) = 42.89, p < 0.0001.We first assessed the social impact of our new WIT program by examining the changes in the risk of Internet gaming disorder from before (Time 1) to after (Time 2) program participation. We first examined its risk rate before the participants attended the training program (Time 1). According to the aforementioned scoring scheme, 91, 6and 3% of the participants were categorized as “average gamers,” “at-risk gamers,” and “high-risk gamers,” respectively. Then we examined its risk rate after attending the training program (Time 2) to make a comparison of the risk rate between the two time points. A noteworthy result is that 6 months later, the proportion of participants categorized as “average gamers” increased from 91% to 95%, whereas the proportion of those in the “at-risk gamers” group declined from 6% to 2%. However, the proportion of participants classified as “high-risk gamers” remained the same (3%) across the two time points. These changes in group membership are depicted in A more refined crosstabs analysis further revealed that of the 14 participants classified as being at risk of Internet gaming disorder prior to program participation, 12 were categorized as “average gamers” after participation, with only 2 remaining at risk. Taken together, these results provide some empirical support for the efficacy of our newly developed prevention program in shrinking the group at risk for Internet gaming disorder across the period.t-test results similarly indicated that the levels of Internet gaming disorder symptoms significantly decreased from Time 1 to Time 2, t(203) = 5.16, p < 0.0001. However, the reduction in the levels of risky online behavior was only marginally significant across the period, t(205) = 1.72, p = 0.09.We further assessed the social impact of our program by detecting changes in the trajectory of levels of symptoms and mental well-being from before (Time 1) to after (Time 2) program participation. The paired-samples rs = 0.21 and 0.25, respectively, ps < 0.002) and a higher level of positive affect at Time 2 , and vice versa. Moreover, the exhibition of less risky online behavior at Time 1 was found to predict lower levels of negative affect and higher levels of positive affect at Time 2 , and vice versa.Finally, to assess the WIT program’s social impact in relieving the symptoms of Internet gaming disorder and boosting mental well-being, the Pearson correlation analyses further showed that having fewer symptoms of Internet gaming disorder at Time 1 predicted lower levels of negative affect and social anxiety at Time 2  shrinking the group at risk for Internet gaming disorder, (b) mitigating the symptoms of Internet gaming disorder among primary school students over a 6-month period, and (c) bolstering students’ emotional well-being through increasing levels of positive affect while decreasing levels of negative affect across the same period.Our findings corroborate the results of previous studies, which have indicated that reduced problematic IT use is related to mental health improvement e.g., . Taken tTo tackle the societal problems of prevalent problematic IT use and the escalating demands of mental health services, we designed a universal prevention program targeting the general population of primary school students, most of whom had a low to moderate risk of developing Internet gaming disorder. Our prevention program was designed to supplement previous intervention studies, which have focused primarily on tackling mental health issues in individuals who have already developed Internet gaming disorder while neglecting those at risk of the disorder who have manifested some symptoms but not yet developed the condition. As previously noted, the pattern of our findings parallels that of studies examining individuals diagnosed with the disorder. Such empirical consistency indicates that the detrimental mental health and interpersonal consequences of Internet gaming disorder are not limited solely to individuals who have developed the disorder, but are found across a broad spectrum of risk profiles, ranging from very low to very high susceptibility to Internet gaming disorder.Our study provides evidence indicating that the WIT program is an efficacious universal intervention strategy for both primary and secondary prevention. At the primary level, where the aim is to reduce new incidences of a public health problem , the proDespite its effectiveness at both the primary and secondary prevention levels, the WIT program’s psychological benefits are less obvious at the tertiary level, where the aim is to mitigate the symptoms of an existing public health problem . To elabThe universal approach adopted by our WIT program is conducive to serving a general student population with a relatively wide range of vulnerabilities to Internet gaming disorder, and the program also displays practical utility in exerting a social impact on mental health promotion. As Internet gaming disorder is comorbid with depression, anxiety, attention deficit disorder, and alcohol abuse , reducedMental health professionals in Hong Kong face immense workloads and work-related pressures, with a ratio of 1 mental health professional to 50 clients with mental illness . This unLong waiting times for treatment are an inevitable consequence of this inflated demand in the face of a shortage in the supply of mental health services. The average waiting time for various child and adolescent psychiatric services increased by 38% over the 2011–2016 period . ClientsThe surging demand for professional services has also generated higher medical costs. In the 2013–2014 financial year, for example, public expenditure on mental health services stood at HK$3.8 billion, increasing to approximately HK$5.1 billion just 5 years later . HoweverIn this light, the primary and secondary prevention strategies adopted by our WIT program are of great practical value in terms of cost-effectiveness. Cost-benefit analyses of mental health services generally indicate that primary and secondary prevention strategies are relatively cost-effective , as theiTo compile a best practice report for public mental health promotion, it is important to consider the interactions among different ecological systems to meet emergent societal needs. A recent review advocates that “using Bronfenbrenner’s ecological system concepts by clearly considering interactions between and within these systems can result in recommendations that are most useful for guiding public mental health policy and practice” , p. 414.Apart from serving students, our WIT program could be expanded to engage teachers and parents. Such an expansion in the scope of the WIT program would incorporate the principles of “scaffolding,” a form of educational practice derived from the sociocultural theory of learning . AdoptinTo attain these goals, teachers could receive training in how to run the WIT program in their schools, thus allowing the program to reach successive cohorts of student beneficiaries. In addition to the formal program, school administrators could also incorporate healthy Internet use into their school curricula; for instance, regular classes could include discussions on such topics as healthy Internet use and ways of managing risky online behaviors. Parents could also be equipped with knowledge to foster the effective monitoring of their children’s Internet use and gaming behavior, and the provision of Internet safety guidance at home.More broadly, the WIT program may confer further constructive social impacts at the macrosystem level . As the Internet is intrinsically entwined with culture e.g., , the WITThe amelioration of problematic Internet behavior may also facilitate the attenuation of “toxic technocultures;” that is, contemporary cultures of anonymous Internet gangs who gather online to harass persons with particular demographic characteristics, such as ethnic and sexual identities . The WITBefore drawing our conclusions, it is important to raise some caveats about the findings obtained in this pilot study and suggest directions for future research. First, the beneficiaries of our new prevention program were confined to a relatively homogenous group of primary school students residing in Hong Kong. As the resources for this pilot study were limited, the school sample was selected from our team’s list of strategic partners, and participation was entirely voluntary. Once the practical utility of our new program has been established, our team intends to seek extended grants and resources to expand the scope of our community service and research to a much larger pool of schools. To reach out to a greater variety of schools that are more representative of the population, an ideal school sample should be derived from probability sampling based on districts rather than broad regions of Hong Kong .With the empirical support provided by the present study, the WIT program can be further implemented with the involvement of additional stakeholder groups. Extension of the program may involve the family and school systems  in Internet gaming disorder prevention to further benefit vulnerable groups of youngsters. Such an extension would be based on the influential role played by parents and teachers in children’s learning through “scaffolding,” a teaching and learning approach to strengthen socio-emotional learning  and the psychosocial competence of children e.g., . MoreoveThe present social impact assessment yielded encouraging findings for the short- to medium-term benefits conferred by the new WIT program. However, individuals at a high risk of gaming disorder experience the withdrawal symptoms and relapses pertinent to the condition e.g., . A longeTo conclude, the WIT program is a universal prevention program developed in response to the Hong Kong SAR government’s call for mental health service provision with reference to contemporary societal needs, specifically the current prevalence of Internet gaming disorder and the escalation in mental health problems among young people. This evaluation study demonstrates that our newly developed program exerts a desirable social impact by mitigating the risks of Internet gaming disorder, along with its concomitant symptoms, and promoting mental wellness among primary school students over time. As a newly proposed program for universal prevention, the evidence-based WIT program has the potential to contribute to the enhancement of dedicated public health services for Internet gaming disorder and to enrich technocultures and educational practices that promote the furtherance of social welfare and the quality of life of young people.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by the Human Research Ethics Committee of the University of Hong Kong. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.C-LC and CC contributed to the conception and design of the study. CC coordinated the data collection process. C-LC and YT conducted the literature review. YT and CC performed the statistical analysis and wrote the sections of the manuscript. C-LC wrote the first draft of the manuscript. All authors contributed to the editing and revision of the manuscript, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Health Resources and Services Administration recently announced a notice of funding opportunity (NOFO) for the Geriatrics Academic Career Award Program (GACA). The purpose of the GACA program is to support the career development of individual junior faculty in geriatrics as academic geriatrics specialists and to provide clinical training in geriatrics, including the training of interprofessional teams of health care professionals. The GACA program is a mentorship model where the awardee is guided through a faculty career development plan, with required project deliverables, over the course of four years. The GACA supported 222 junior faculty members between 1998 and 2006, when it was discontinued. This initial NOFO provides funding for up to 26 awardees in the schools of allopathic medicine, osteopathic medicine, nursing, social work, psychology, dentistry, pharmacy, and allied health. This presentation will provide an up-to-date overview of the program with awardee demographics and project deliverables.


The Executive Committee of the Academy for Gerontology in Higher Education (AGHE), formerly known as the Association for Gerontology in Higher Education, approved a proposal to establish and implement a voluntary program of evaluation known as the Program of Merit (POM). The POM designation provides gerontology programs with an AGHE “stamp of approval,” which can be used to verify program quality to administrators, to lobby for additional resources to maintain a quality program, to market the program, and to recruit prospective students into the program. In 2014, AGHE Gerontology Competencies for Undergraduate and Graduate Education© were established and have been integrated into this process. This session will outline the Program of Merit process and present the opportunities for gerontology program leaders to advance gerontology education.


Inland crustal earthquakes usually occur in the brittle upper crust (0–20 km depths), but the 6 September 2018 Eastern Iburi earthquake (M 6.7) took place in southern Hokkaido with a focal depth of ~37 km, causing 41 fatalities and serious damage to the local infrastructure. The reason why this event was so deep and its causal mechanism are still unclear. In this work we study the three-dimensional P and S wave seismic attenuation (1/Q) structure in the source zone of the 2018 Iburi earthquake. Our results show that this event occurred at the boundary between the Sorachi-Yezo belt (low Q) and the dipping Northeastern (NE) Japan arc (high Q) that is descending beneath the Kuril arc. The collision between the NE Japan and Kuril arcs as well as fluids from dehydration of the subducting Pacific plate caused this big event and its unusual focal depth. Similar attenuation structures are revealed in source zones of the 1970 Hidaka earthquake (M 6.7) and the 1982 Urakawa-oki earthquake (M 7.1), suggesting that they were caused by similar processes. We think that large earthquakes will take place again on the active thrust faults in southern Hokkaido in the coming decades. Hence, we should pay much attention to the seismic risk and prepare for reduction of earthquake hazards there. Serious and widespread landslides were trigged by the mainshock and its aftershocks. To date, many large earthquakes have occurred in and around southern Hokkaido, including the 1970 Hidaka earthquake (M 6.7) and the 1982 Urakawa-Oki earthquake (M 7.1). All these large events caused serious damage to the local society and infrastructure in Hokkaido. The Eastern Iburi earthquake  scale) occurred in southern Hokkaido Fig.  on 6 Sep2. Inland crustal earthquakes in the Okhotsk plate usually occur within the upper crust down to a depth of ~20 km (ref.3). Hence, the 2018 Eastern Iburi earthquake with a focal depth of ~37 km is quite unusual because it is much deeper than other inland crustal events in the region, and it seems located in the uppermost mantle, considering the Moho depth of ~33 km in the source area5. It is important to investigate the three-dimensional (3-D) structure of the source zone, which may shed new light on seismotectonics and seismogenesis of the region.Earthquakes in and around Hokkaido can be divided into three types, including megathrust earthquakes at depths of ~10–50 km along the upper boundary of the subducting Pacific plate, intra-slab events that occur within the subducting Pacific slab, and earthquakes in the overriding Okhotsk plate8  Japan arc and the Kuril arc, which originated from the interaction of the Eurasian plate with the Okhotsk plate in the Late Eocene8 Fig. . The tec. 7 Fig. . These gs10 Fig. . So far,2 and is proven to be a powerful technique to investigate the seismogenesis and seismotectonics. Compared with seismic velocity, seismic attenuation  is more sensitive to material properties, such as temperature, grain size, and water content in the crust and upper mantle24. Although there have been a few studies of seismic attenuation tomography in Japan (e.g. refs26), such studies are still quite few as compared with seismic velocity tomography, in particular, in source zones of large earthquakes.Seismic velocity tomography has been applied extensively to study the detailed 3-D structure in source areas of large earthquakes in Japan and other regions in the world16, it is a P-wave attenuation model focusing on the relation between seismic attenuation and geological structures. In the present work, to clarify the causal mechanism of the 2018 Eastern Iburi earthquake, we determine both P and S wave attenuation  tomography of the crust and upper mantle in and around the source zone of the 2018 Iburi earthquake. We used a larger number of high-quality waveform data recorded at 136 seismic stations , the high-velocity (high-V) and low-attenuation (high-Q) Pacific slab is considered in the starting model for the tomographic inversion, so that the P and S wave ray paths can be traced more accurately. The Qp and Qs models are correlated with each other  belt exists in central Hokkaido Figs  and 3, w16 and velocity models of the study region (e.g. refs19). Our resolution tests indicate that these features are robust  zone in the SY belt, which corresponds to the low-Q zone imaged by this study. The SY belt is composed of three units: the Sorachi ophiolitic unit that contains the Tithonian radiolarian chert, the Yezo Supergroup of forearc basin sediments, and high P-T metamorphic rocks (the Kamuikotan metamorphic (KM) belt)30. Most parts of the SY belt are filled with sediments and ophiolite, which may contain a large amount of fluid and so exhibit low-Q and low-V9. Micro-earthquakes occur actively in the low-Q and low-V zone along the SY belt  in the crust and uppermost mantle35, which usually has a low temperature as illustrated by a recent numerical simulation study36. In the forearc area, magma cannot be produced because of the low temperature there. The low-Q zone beneath the forearc area may reflect ascending fluids from the slab dehydration, which has been revealed by many previous studies37. We hence argue that the slab dehydration takes place beneath the forearc region and the resulted fluids ascend to the SY belt and thrust faults in the crust, causing the low-Q zone in the SY belt.A clear low-Qs zone is visible in the forearc mantle wedge beneath the Hidaka collision zone Fig. . The man16. The high-Q zone is located in the southwest of the SY belt and represents part of the subducting NE Japan arc. The Ishikari thrust fault zone extends in the N-S direction, which is located between the low-Q and high-Q zones. The focal mechanism of the 2018 Iburi earthquake .Figure ake Fig.  shows a 41. A recent study of the Iburi mainshock and aftershock distribution suggested that the seismogenic fault of this earthquake may be not directly connected with the Ishikari lowland fault system41. In the present study, we cannot clarify this issue due to the limited resolution of our Q tomography. However, on the basis of the present findings and previous results, we deem that the 2018 Iburi earthquake was caused by the concentration of stress from the push and squeeze of the NE Japan-Kuril arc collision, as well as overpressure of fluids from dehydration of the subducting Pacific slab. The arc-arc collision caused the unusual focal depth (~37 km) of the Eastern Iburi earthquake.Whether the 2018 Iburi earthquake was directly associated with the Ishikari lowland fault system or not is one of the fundamental questions9 of velocity tomography suggested that the 1970 Hidaka earthquake and the 1982 Urakawa-oki earthquake took place at material boundaries that correspond to the Hidaka thrust fault and the Ishikari fault, respectively. Another study17 of velocity tomography revealed a northeastward dipping high-V anomaly beneath the Hidaka belt, which was interpreted as a result of delamination of the NE Japan arc. The delamination of brittle lower crustal material could cause earthquakes with deeper hypocenters than the normal crustal events. However, the western boundary of this high-V anomaly is located at the KM belt, which is far from the epicenter of the 2018 Iburi earthquake. A recent study42 of detailed velocity tomography shows that the 2018 Iburi earthquake occurred at the edge of a seismogenic zone with a high P-wave velocity (Vp). This high-Vp zone may reflect a lithospheric fragment and cool down the mantle wedge, which caused the unusually deep hypocenter (~37 km) of the 2018 Iburi earthquake.A previous study43. Its focal depth (~26 km) is also deeper than those of normal crustal events (≤~20  km) in the Japanese inland areas3. Its hypocenter is also located at the boundary between the low-Q and high-Q zones  due to the arc-arc collision and released by the earthquake faulting43.The northeastward descending of the NE Japan arc beneath the Kuril arc may have also caused the 1982 Urakawa-oki earthquake (M 7.1), which was a reverse-faulting event with a compressional axis in the NE-SW direction44  may be also caused by the southwestward migration of the Kuril arc16.The 1970 Hidaka earthquake (M 6.7) with a focal depth of ~25 km took place in the southern part of the Hidaka collision zone44 Fig. , which c3, which are mainly controlled by the NE Japan-Kuril arc collision. This tectonic process leads to a SW-NE compressional stress regime and the thrusting of fold and thrust-fault systems over the Hidaka mountain range47. These large events caused serious hazards to the local society and infrastructure. The generation of the three big earthquakes and high local seismicity in southern Hokkaido indicate that the arc-arc collision is still an ongoing process. The convergence rate between the Eurasian and Okhotsk plates was estimated from the velocity field48, which suggested that there is a high potential for a large event in northern Hokkaido. A recent study49 of the Coulomb stress change due to the 2018 Iburi earthquake suggested that the Ishikari fault is under increasing seismic threat after the Iburi earthquake. It is expected that large earthquakes would occur again on the Ishikari lowland fault system and the Hidaka thrust fault in the coming decades due to the ongoing arc-arc collision. Hence, we need to pay attention to the seismic risk and prepare for the hazard reduction in the region.Thus, all the three large events in southern Hokkaido took place at boundaries between low-Q and high-Q zones. The 1970 Hidaka earthquake occurred on the Hidaka thrust fault, whereas the 1982 Urakawa-oki earthquake and the 2018 Iburi earthquake occurred in the Ishikari lowland fault system. Their focal depths (25–37 km) are all deeper than those of normal crustal events in the Japan IslandsP and S wave attenuation tomography of the source zone of the 2018 Eastern Iburi earthquake (M 6.7) is determined, which sheds new light on the causal mechanism of the Iburi earthquake that occurred at a boundary between low-Q and high-Q zones. The Sorachi-Yezo belt is imaged as a significant low-Q zone, which may indicate the existence of thick sediments, high water content and high crack density there. A northeastward dipping high-Q zone exists beneath the Ishikari lowland, which is interpreted as the subducted NE Japan arc. Low-Qs anomalies are also revealed in the forearc crust and upper-mantle wedge, which reflect the existence of fluids from dehydration of the subducting Pacific slab. When the fluids enter the active faults in the overlying Okhotsk plate, pore pressure will increase and fault zone friction will decrease, which can trigger a large event such as the 2018 Iburi earthquake. Its unusually deep hypocenter (~37 km) reflects a locally lower temperature due to the northeastward subduction of the NE Japan arc and its collision with the Kuril arc. The 1982 Urakawa-oki earthquake (M 7.1) and the 1970 Hidaka earthquake (M 6.7) were probably caused by the same processes. Similar large earthquakes would occur again in the coming decades on the active thrust faults in southern Hokkaido where the arc-arc collision is an ongoing process. Hence, much attention should be paid to the seismic risk there, and actions should be taken to reduce the seismic hazard.50. The seismograms with a sampling rate of 100 Hz have enough bandwidth for our spectral analysis. We selected 924 local shallow and intermediate-depth earthquakes (M > 2.0), which occurred in the study region  and Q(s) are seismic velocity and quality factor, respectively, along a ray path jth event to the ith station, and Δ represents the perturbation of a parameter. A starting 1-D Q model  by previous studies54. Following the previous tomographic studies of the Japan subduction zone56, we set up two 3-D grids with a lateral grid interval of 0.2° in the study volume. One grid is for parameterizing the crust and upper mantle, whereas the other grid is for parameterizing the subducting Pacific slab. Meshes of grid nodes are set at depths of 10, 25, 40, 65, 90, 140, 190 and 240 km in the crust and mantle. The value of a parameter  at any point in the study volume is calculated from its values at eight grid nodes surrounding that point using a linear interpolation scheme55. An efficient 3-D ray tracing technique55 is used to compute theoretical t* and ray paths precisely. In the Q tomographic inversion, lateral depth variations of the Conrad and Moho discontinuities are also taken into account. The damped least-squares method55 is used to solve the large but sparse system of observation equations that relate the observed t* to the unknown VQ parameters. Dividing VQ by V at each grid node, we can obtain a 3-D Q model. The 3-D velocity  model used in this work is the high-resolution model of the Japan subduction zone57. Supplementary Fig. 25.where 56. To perform a CRT, we first assign positive and negative Q perturbations of 40% at the adjacent grid nodes in the input model to calculate the synthetic t*. Then Gaussian noise with a standard deviation of 0.002  is added to the synthetic t* before performing the tomographic inversion. Supplementary Fig. 55. The procedure of the RRT is the same as that of the CRT, except for the input model that is derived from the obtained Q tomographic results (Figs Our study volume is well covered by the ray paths, especially in and around the 2018 Iburi earthquake area (Supplementary Fig. lts Figs . The RRTlts Figs  show thaSupporting information


The U.S. Tax Program for Swiss banks is a very significant part of the recent history of the Swiss financial industry. It has accelerated the transformation of the Swiss banking industry from a system that relied on bank secrecy to a much more compliant one. It was also rather costly for the banks involved. This short paper tries to identify the determinants of the individual penalties that were levied by the DoJ. We find that U.S. assets under management is the most important determinant. However, the average size of the accounts, the behavior of the bank vis-à-vis its American clients, the solvency of the bank, and the point in time when the bank settled with the DoJ also matter. U.S. Tax Program for Swiss Banks (“the program”). This program paved the way for ending the conflict that had emerged between the two countries concerning Swiss bank secrecy  and the Swiss Federal Department of Finance issued a joint statement that created the  secrecy .At the time, the DoJ had collected evidence that several Swiss banks had systematically helped U.S. tax subjects to evade taxation. Several Swiss banks were already under criminal investigation by the DoJ. The largest of these banks, UBS, had settled in 2009 and received a deferred prosecution agreement (DPA) in exchange for full cooperation with the DoJ, including providing names of clients and employees, and a penalty of USD 780 million. One bank (Wegelin) collapsed in 2012 as a consequence of the conflict with the DoJ. Six major banks  and eight smaller banks had also been charged but had not yet settled at the time of the creation of the program. Other banks were at risk of being implicated in the DoJ’s investigation. The whole Swiss banking industry appeared to be under siege.International pressure on Swiss bank secrecy had already been mounting for some time. Before the U.S. came into play, there had been a series of initiatives led by the OECD to increase transparency and induce cooperation among countries on taxation. With respect to bank secrecy, the OECD tried to establish the free exchange of information between tax authorities, or ideally the automatic exchange of information on tax subjects. This amounts to abolishing bank secrecy for tax purposes. The strategy of the OECD relied mainly on blacklisting non-cooperative jurisdictions, thereby hoping that this public shaming would prove effective. In successive negotiations between Switzerland and the EU, a withholding tax on interest income was introduced, and the distinction between tax evasion and tax fraud was removed, thereby easing the way for an EU tax authority to request information on bank accounts in Switzerland about which they were suspicious. However, in all these negotiations, bank secrecy itself was fully preserved.Delaloye et al.  use thisEmmenegger  asks theWe do not find this argument completely convincing. It is obvious that access to the U.S. financial market is vital, but it is not obvious that access to the EU financial market is less vital. So why was the U.S. so much more successful than the EU in its handling of Switzerland? We are not legal or political science scholars, but it is interesting that the EU was negotiating with the Swiss government, whereas the DoJ was attacking Swiss corporations. Its first target was the biggest bank in the country, no less. This is in line with the guidelines set by the DoJ with respect to charging corporations: “[…] corporations are likely to take immediate remedial steps when one is indicted for criminal conduct that is pervasive throughout a particular industry, and thus an indictment often provides a unique opportunity for deterrence on a massive scale […]”  received higher penalties than banks that were less solvent. Fifth, the DoJ seems to have eased the fines as the program evolved. Controlling for the other variables, we find that the fines for the banks that settled last were significantly smaller than the ones that settled early. We have no indication why this is the case.“Each eligible Swiss bank should carefully weigh the benefits of coming forward, and the risks of not taking this opportunity to be fully forthcoming. A bank that has engaged in or facilitated U.S. tax-related or monetary transaction crimes has a unique opportunity to resolve its criminal liability under the Program. Those that have criminal exposure but fail to come forward or participate but are not fully forthcoming do so at considerable risk”. Participation in the program was voluntary, and some banks indeed opted not to participate. The program allowed the industry to resolve the U.S. tax issue in a structured and relatively predictable manner. The last paragraph of the DoJ Tax Division’s comment on the program makes this very clear: The first step for a participating bank is to request permission from the Swiss Federal Department of Finance to participate. Such permission is necessary because cooperating with a foreign government to the extent required by the program without prior permission constitutes a breach of Art. 271 Abs. 1 of the Swiss penal code.letter of intent (LOI). The deadline for this was December 31, 2013. The program divided the banks into four categories, and banks have to indicate to which category they want to belong.The second step is for the banks to declare their willingness to participate in the program by submitting a Category 3 and 4 banks have to provide evidence for their classification, which is then verified by an independent examiner (at the expense of the bank). In exchange, the bank is offered a non target letter (NTL), which is essentially just a document stating that the bank is not, at that time, the target of any criminal investigation authorized by the DoJ’s tax division.Category 2 banks are the focus of the program. Banks that fulfill the requirements of the program are offered a non-prosecution agreement (NPA). An NPA is very similar to a DPA. In both cases, the bank is not convicted of any crime and does not formally admit guilt, but full cooperation and typically the payment of a penalty are required.All category 2, 3, and 4 banks have in the meantime settled with the DoJ and have received NPAs or NTLs. Some category 1 banks, however, have not yet settled. Two of these banks have been liquidated in the meantime (Bank Frey and Neue Zürcher Bank). According to DoJ data, the category 1 banks that have settled so far had an aggregate maximum amount of assets under management (AuM) belonging to U.S. clients of USD 38 billion. They have paid penalties of about USD 4.4 billion. The category 2 banks had in total maximum assets under management belonging to U.S. clients of roughly USD 50 billion and have, in sum, paid penalties of USD 1.37bn.information, it must provide assistance to the DoJ in implicating other individuals, and it must pay a penalty. The process is explained in detail in In order for a bank to be granted an NPA, it has to fulfill three obligations. It must provide detailed Information The bank must disclose the total number of U.S.-related accounts, as well as the maximum balance on these accounts for three periods: on August 1, 2008, between August 1, 2008, and February 28, 2009, and after February 28, 2009.In addition, the bank must provide information about the amount and form of the transfer of funds into and out of the account during the applicable period. In particular, it must show where the funds came from and where they went to . This information is clearly intended so that the DoJ is able to follow the money and implicate other institutions or individuals.The bank must identify further its internal procedures for the handling of U.S. clients and accounts. This information includes the names of employees involved in acquiring, operating, and supervising such accounts. In particular the names of the relationship manager, client advisor, asset manager, financial advisor, trustee, fiduciary, nominee, attorney, or accountant at any time during the relevant period have to be submitted. The information also includes internal reporting and communication with management on such matters.The above information has to be verified (at the expense of the bank) by an independent examiner.Assistance Interestingly, the bank does not disclose the identities of the U.S. account holders themselves. Doing so would violate Swiss bank secrecy law. However, upon request, the bank will provide testimony and assist the USA in any criminal proceedings. In particular, the bank provides all information necessary for the USA to draft treaty requests to seek account information.Furthermore, the banks will close all non-compliant U.S.-related accounts. They will also prevent their employees from assisting U.S. account holders with further concealment. Moreover, the banks will open new U.S.-related accounts only if they can ensure that the account will be declared to the USA and will be subject to disclosure by the Swiss bank. This effectively terminates Swiss bank secrecy for U.S. customers vis-à-vis the U.S. government for category 2 banks.Penalty The program specifies a formula for computing the penalty: for U.S. Related Accounts that existed on August 1, 2008, an amount equal to 20% of the maximum aggregate dollar value of all such accounts during the Applicable Period;for U.S. Related Accounts that were opened between August 1, 2008, and February 28, 2009, an amount equal to 30% of the maximum aggregate dollar value of all such accounts; andfor U.S. Related Accounts that were opened after February 28, 2009, an amount equal to 50% of the maximum aggregate value of all such accounts.“Upon execution of an NPA, the Swiss Bank will agree to pay as a penalty: The determination of the maximum dollar value of the aggregated U.S. Related Accounts may be reduced by the dollar value of each account as to which the Swiss Bank demonstrates, to the satisfaction of the Tax Division, was not an undeclared account, was disclosed by the Swiss Bank to the U.S. Internal Revenue Service, or was disclosed to the U.S. Internal Revenue Service through an announced Offshore Voluntary Disclosure Program or Initiative following notification by the Swiss Bank of such a program or initiative and prior to the execution of the NPA”. .Even though the program prescribes a rigid formula for the penalty, the DoJ clearly had some degree of freedom in determining the fines. On the Tax Program website, they state: “It is indeed essential to remember that banks receive a rebate if, for example, they managed to push clients into the IRS voluntary disclosure program. http://www.ustaxprogram.com/banks/ .Initially, 87 banks were in category 2. Nine of thoseAccording to the program as described in the previous section, the penalty is a function of the maximum amount of assets under management (AuM) in three different periods, minus some potential rebate for extraordinary cooperation. This hypothesis cannot be tested, however, because the DoJ has not published the AuM for the individual banks and the three periods separately. For most participating banks, they only publish the maximum AuM over all three periods together.The DoJ has also published the maximum number of U.S.-related accounts for each bank. According to the program, this data should not affect the penalty. Interestingly, the DoJ was careful to document this information for each bank. This leads us to believe that it did play a role in some way. We will argue that the average assets per account, AuM/accounts, is a useful explanatory variable.The NPAs describe in some detail the DoJ’s findings concerning the activities of each bank relevant to allowing or helping customers avoid taxation. We have collected 30 such practices, see Table Finally, we have collected balance sheet data for as many banks as possible for the year 2013. In particular, we have collected the size of the balance sheets, capital, earnings, and profit of 60 banks. For 18 banks—all specializing in private bankingTable Figure As stated in the program, the determinants of the penalty are the maximum aggregate assets under management in U.S.-related accounts. The difficulty is that the program distinguishes between three points in time, namely August 1, 2008, between August 1, 2008, and February 28, 2009, and after February 28, 2009. However, the data published by the DoJ for most participating banks do not distinguish these three periods; only the maximum over the three periods is published. Moreover, the penalty is levied only on those assets that were unknown to the IRS at the time the program began, but the published data does not reveal the share of assets that were shown by the bank to be tax compliant. As a consequence, our model is necessarily miss-specified.Category 2 banks held, according to the DoJ data, about USD 50 billion U.S. assets under management (AuM). If all these assets were not tax compliant, the total penalty would have to be between 20 and 50% of this value, that is, between USD 10 and USD 25 billion. Yet, the penalties were only USD 1.37 billion, which is between 5.5 and 13.7% of the values we would expect if all AuM were non-compliant. Therefore, apparently, the banks were unable to establish tax compliance for 5.5 to 13.7% of their AuM, or vice versa, between 86.3 and 94.5% of the assets in category 2 banks were indeed tax compliant.Despite the unavoidable miss-specification, a regression pi is bank i’s penalty, is a start. If the complete AuM had evaded U.S. taxation, βi should be between 0.2 and 0.5, according to the definition of the program. In Table where β1 should be 1 according to the definition of the program because the relationship between AuM and penalty ought to be linear, hence exhibiting unit elasticity. Table β1 is indeed close to unity, though statistically slightly smaller.8To account for the highly skewed distribution of the data, we will use the logarithmic specification of . Note thWe now add the activities, as identified by the DoJ in the individual NPAs, as explanatory variables. If we add these activity dummies individually to Eq. (2), activities A4, A9, A19, A20, and A24 turn out to be significant at the 5% level. If we use these five dummies simultaneously, A20 and A24 lose their significance. We therefore keep the remaining three activities in the regression, The results are reported in Table As reported, the DoJ carefully collected and reported the number of U.S.-related accounts, despite the fact that the number of accounts is not a determinant of the penalty according to the definition of the program. However, the (logarithmic) number of accounts indeed turns out to have a statistically significant explanatory power, Table Table We also consider a quadratic specification of the size variable in Table Table One might wonder if the ability of banks to pay penalties might have played a role as well. There is no mention of this in the program, but as a general principle, one purpose of criminal law is the “deterrence of further criminal conduct”  mean of the AuM per account across all banks in our sample is USD 0.83 million. Migrosbank reported USD 273 million U.S.-related AuM, and 898 such accounts. This makes USD 0.3 million per account on average, which is significantly smaller than the average across all banks. Migrosbank paid a fine of about USD 15 million. According to our estimate (regression (11)), if Migrosbank’s accounts had been equal to the average USD 0.83 million, its fine would have been only USD 7.3 million, which is only half of what it paid. Compare this to Rothschild Bank. This bank reported USD 1,500 million U.S.-related AuM in 332 accounts. This makes USD 4.5 million per account on average, so the account balances of Rothschild’s clients were much larger than those of the average bank. Rothschild Bank paid a smaller fine than Migrosbank, namely USD 11.5 million, despite having much more U.S.-related AuM. If it had had the average account size, its penalty would have been much larger, namely about USD 74.4 million according to our estimate.It is possible that large clients were on average more tax compliant than small clients, or maybe it was easier for Rothschild Bank to push its larger clients into voluntary disclosure and establish the tax compliance of these accounts, while Migrosbank was not able to do so for its smaller clients. It is, unfortunately, not possible to test this hypothesis because the amount of delinquent AuM is not available.About the significance of solvency, one possible argument for the influence of this variable is that the DoJ wanted to avoid sending a bank into bankruptcy by charging too large a fine. On closer inspection of the data, this reasoning appears unconvincing, however. Figure do list the maximum assets under management related to U.S. entities. However, for most banks, the DoJ does not publish when these accounts were in operation , and how much of the AuM was shown by the banks to be tax compliant. Our analysis suggests that, overall, between 86 and 95% of the U.S. assets in category 2 banks were tax compliant. With the available data, we do find strong evidence that the amount of U.S.-related assets under management has a strong positive influence on the fines, as is to be expected.The program spells out a rule for determining the penalties. Unfortunately, it is not possible to verify that this rule was applied because the DoJ has not published the data in the necessary detail. For instance, the NPAs The DoJ has collected and published relevant practices that banks were engaged in. We identify a small number of such activities that seem to help explain some of the variance in the fines. The activities we identify have to do with allowing customers to withdraw cash anonymously, or helping them conceal their accounts from U.S. tax authorities.Furthermore, we find that banks with many small accounts paid larger fines than banks with few, but large, accounts. It is not completely clear why this is so. It is possible that larger clients were more tax compliant on average than smaller clients, or it is possible that the banks had more difficulty in proving tax compliance for many small clients compared to few large clients.11In addition, we do find some tentative evidence that the DoJ imposed higher fines on well-capitalized banks. It is not possible to determine whether this was by design or not. It is unlikely that avoiding driving a bank into a solvency crisis was a major consideration for the DoJ; the fines were simply too small for that. However, it is possible that the DoJ felt that it could and should extract more from a well-capitalized bank. Yet, it is also possible that this statistical result stems from the necessarily miss-specified model.Finally, we find evidence that the DoJ over the course of the program significantly reduced the fines. Banks that settled later received a better deal than banks that settled earlier. Again, it is not possible to know whether this was the intention of the DoJ, whether its policy gradually evolved over time, or whether this is connected to the sequence the DoJ set at the outset when it decided to prioritize some dossiers at the expense of others.In conclusion, it is notable that the sums that have been transferred from the Swiss banks in categories 1 and 2 to the U.S. government are substantial. So far, these banks have paid USD 5.8 billion in fines. In addition, the legal cost for the banks must have been very high as well. There are no publicly available data on that, but a legal conflict that lasts several years for high stakes and that involves U.S. law enforcement is bound to be expensive. Moreover, U.S. tax subjects that were identified by the program were also prosecuted and were billed for taxes and fines, although no final account of these payments is publicly available.More broadly, the program has paved the way towards the fall of Swiss bank secrecy with respect to a wide array of jurisdictions. As of today, Switzerland has signed agreements to exchange information automatically about foreign customers of Swiss banks with 41 jurisdictions. The Swiss banking industry has been permanently changed by this program.


Dynamic systems theory suggests that instability can be a key element in the promotion of human change processes. Several studies have confirmed an association between unstable patterns and successful psychotherapeutic outcome. Somewhat similarly, the assimilation model of psychotherapeutic change argues that clinical change occurs through the integration of problematic experiences that initially threaten the stability of the self. This study examined how instability in assimilation levels was related to assimilation progress and change in symptom intensity, within and across sessions, in a good-outcome case of Emotion Focused Therapy. We used the assimilation of problematic experiences scales (APES) to measure assimilation and the outcome-questionnaire (OQ-10) to measure clinical symptom intensity. To assess assimilation instability, we used a fluctuation measure that calculated the amplitude and the frequency of changes in assimilation levels. To analyze the structural relationships between variables we used a dynamic factor model. The results showed that APES level and APES fluctuation tended to increase across treatment, while OQ-10 scores tended to decrease. However, contrary to expectations, the dynamic factor model showed no significant associations between APES fluctuation and OQ-10 scores either within sessions or between adjacent sessions. Dynamic systems theory suggests that psychotherapeutic change requires periods of instability that permit the problematic state of maladaptive and rigid stability of the self to be transformed . Due to assimilated) into aggregates, which can be reactivated. The traces, like the original experiences, incorporate intentions and intended actions as well as perceptions, cognitions, and feelings, so the aggregates can act and speak when they are reactivated, and they are characterized metaphorically as voices. Thus, we say a person is composed of the voices of the people, activities, skill, interests, and so on, that have comprised their life experience. Although most experiences are assimilated unproblematically, some problematic  experiences remain disconnected and liable to cause distress and dysfunctional behavior when they are reactivated. Or to say it another way, the disconnected voices emerge and cause problems when they are addressed by circumstances. Their being disconnected also prevents access to them, depriving the self of potential experiential resources. Psychotherapeutic change occurs through the assimilation of these disconnected, problematic internal voices.A similarly important role for instability can be derived within the assimilation model of psychotherapeutic change . The assThe emergence of the problematic voices in therapy initially jeopardizes the stability of the self’s  state of functioning. The instability, manifested in the often difficult dialog within sessions, begins a progressive transformation of both parts through the creation of mutual understandings. In successful therapy, this process of assimilation promotes a more adaptive and functional self-structure and a return to a state of stability. In this way, instability plays an important role in the assimilation model’s account of change that is congruent with that of dynamic systems theory.Instability during the assimilation process has been studied qualitatively through the analysis of setbacks , and dynThis was a theory-building case study; that is, we aimed to analyze how the observations of this specific case were congruent with the assimilation model or, if not, suggested modifications or elaborations of the theory . I theorStudies within the Dynamic Systems approach have suggested that therapeutic change is associated with fluctuations or discontinuities in clinical symptoms . This is“new, possibly more functional patterns of functioning”  through a dialog that creates semiotic meaning bridges, or mutual understandings, between them . The assTable 1; A series of intensive case studies on a variety different therapeutic models e.g.,  has suggProgress through different assimilation levels is not smooth but is characterized by frequent setbacks, defined as a return from a higher to a lower level of assimilation . Such seSetbacks represent a kind of destabilization or fluctuation. In light of the dynamic systems suggestion that destabilization can be therapeutically valuable, this suggested to us that it may be useful to find quantitative ways to assess this fluctuating pattern of assimilation progress.We explored how fluctuation in APES levels was related to assimilation progress and change in symptom intensity within and across sessions in the case of a single good-outcome client. We used dynamic factor analysis, a technique designed for analyzing time-series data, especially in the analysis of interactions between response variables . As FishAlice (a pseudonym) was a single-26 year old employed woman who was treated for depression at the Maia University Institute (ISMAI), Portugal. She participated in a randomized clinical trial called the ISMAI Depression Study , which cPsychological treatment, as well as the collection and processing of data for research purposes followed principles and standards included in the ethics code . The client of this study, like all other participants, signed an informed consent required in the Standard 3.10 of the ethics code. Previously, the client was informed about the purposes of the research, expected duration and procedures. In addition, it was clarified that participation was voluntary, preserving their right to refuse participation or to give up participating at any time. In this informed consent, Alice also authorized the use of the collected data for process and outcome studies.Alice received 16 weekly sessions of EFT and was considered a good-outcome client, as described later. She lived with her parents, who were catholic and conservative. Her presenting problems concerned her relationships with her boyfriend and with her parents (mainly her father) and problems at work. Mendes and collaborators  previousAlice’s therapist was a Portuguese woman in her early thirties with 8 years of experience as a therapist, including 4 years of experience delivering EFT.Emotion Focused Therapy is an empirically validated humanistic therapy  that vieThe Portuguese version of the BDI-II , indicating reliable improvement  and rated them, independently according to the APES. The passage was the rating unit and was defined as a stretch of discourse delineated by a change in the topic of the conversation or by markers of changes in APES level i = periods between points of returnI = total number of such periods within the windowm = number of measurement points within a moving windowm – 1 = number of intervals between all measurement points of a windows = xmax – xmin with xmin smallest value of the scale, xmax largest value of the scale.In the present study we employed a dynamic factor model  that is A VAR model with a lag of 1 session was tested by creating a block-Toeplitz matrix. The VAR model allowed to analyze intra- and intersession relationships between each variable. All VAR analyses were carried out in LISREL  for each of Alice’s 16 sessions. Alice’s OQ-10 scores were relatively high in the first three sessions, varied a good deal across the next ten sessions, and were relatively low in the final three sessions, consistent with her having achieved reliable and clinically significant improvement on the BDI-II. Her APES levels remained moderate through most of the therapy but were higher in the last four sessions. Her APES fluctuation, similarly, was relatively low until session 12 and then increased for the last five sessions.2 = 6.84, df = 10), the root-mean-square-error of approximation (RMSEA = 0), the standardized root mean square residual (SRMR = 0.16) and the comparative fit index (CFI = 1).The dynamic factor model measures of goodness of fit were satisfactory, including the chi-square value  there was a positive association (0.54) between APES level and APES fluctuation. When the problem was at higher APES levels, APES fluctuation was also higher. Within session t, there was a similar positive association (0.40) between those variables, but also a negative association (-0.27) between OQ-10 scores and APES level. That is, when OQ-10 scores were relatively low, APES level was relatively high. Of particular interest, APES level in session t-1 negatively predicted OQ-10 scores at the following session (-0.62), that is, when a problem was at relatively higher assimilation levels in one session, OQ-10 scores decreased in the following session. Finally, not surprisingly, OQ-10 scores at session t-1 positively predicted OQ-10 scores at the following session (0.66).Table 2). These changes were most apparent in the last four or five sessions of Alice’s 16-session treatment. The inverse associations of APES level with OQ-10 scores in the same session and the preceding session are consistent with assimilation theory. The direct association between APES level and APES fluctuations suggests that, at least in this case, instability increased as degree of assimilation rose. However, the dynamic factor model  showed no significant associations between APES fluctuation and OQ-10 scores either within sessions or between adjacent sessions.In this good-outcome case, APES level and APES fluctuation tended to increase across treatment, while OQ-10 scores tended to decrease  and APES 3 (problem statement/clarification). Theoretically, the psychological rigidity–the denial and avoidance of problems – reflects the danger of powerful negative affect associated with encountering problems at low APES levels . If the More theoretically, perhaps APES fluctuation is not an appropriate measure of the sort of destabilization that is thought to promote change in dynamic systems. The previous work within the dynamic systems approach has focused on fluctuations in symptom intensity or distress. APES levels are related on symptom intensity , but theCase studies such as this one can contribute to theory-building by their detailed correspondence or lack of correspondence with theoretical accounts and by showing where modifications in theory are required or where extensions are possible . But of IB designed and executed the study, assisted with the data coding and analyses, wrote the paper, and made a final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. WS made substantial contributions to the conception and design of the work, collaborated with the design, data analyses, and writing of the study; and editing of the final manuscript and made a final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. TB collaborated with the design, data analyses, and made a final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. PP and IM collaborated with the data coding and analyses, and writing of the study; and editing of the final manuscript and made a final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. DR collaborated in the writing of the study and editing of the final manuscript; and made a final approval of the version to be published; and editing of the final manuscript and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JS collaborated with the design, data analyses, and writing of the study; and made a final approval of the version to be published; and editing of the final manuscript and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer PM and handling Editor declared their shared affiliation at the time of the review.