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The higher education efficiency evaluation model using the data envelopment analysis method has interested many researchers. This paper uses bibliometric analysis on publications extracted from the Scopus database to provide a comprehensive overview of research publications on the measurement of higher education efficiency based on data envelopment analysis: its growth rate, major collaboration networks, the most important and popular research topic. A total of 169 related publications were collected and analyzed from 1988 to 2021. The analysis results show that: Publications published every year have increased sharply in the last six years; The quality of publications is relatively high as publications tend to be published in journals with high-ranking indexes; Countries with the most influence in studies on this topic are: Italy, China, Spain, the USA, and the United Kingdom; Authors with the most influence in this research direction are Agasisti T., Abbott M., Doucouliagos C., Avkiran N.K., and Johnes J.; The research cooperation among countries and among affiliations is not strong. Finally, the paper has provided recommendations for future studies based on the findings.

Introduction: Despite the support for and benefits of data-driven learning, physician engagement is variable. This study explores systemic influences of physician use of data for performance improvement in continuing professional development (CPD) by analyzing and interpreting data sources from organizational and institutional documents., Methods: The document analysis is the third phase of a mixed-methods explanatory sequential study examining cultural factors that influence data-informed learning. A gray literature search was conducted for organizations both in Canada and the United States. The analysis contains nonparticipant observations from professional learning bodies and medical specialty organizations with established roles within the CPD community known to lead and influence change in CPD., Results: Sixty-two documents were collected from 20 Canadian and American organizations. The content analysis identified the following: (1) a need to advocate for data-informed self-assessment and team-based learning strategies; (2) privacy and confidentiality concerns intersect at the point of patient data collection and physician-generated outcomes and need to be acknowledged; (3) a nuanced data strategy approach for each medical specialty is needed., Discussion: This analysis broadens our understanding of system-level factors that influence the extent to which health information custodians and physicians are motivated to engage with data for learning., Competing Interests: Disclosures: The authors declare no conflict of interest., (Copyright © 2022 The Alliance for Continuing Education in the Health Professions, the Association for Hospital Medical Education, and the Society for Academic Continuing Medical Education.)

Objectives of the study: The paper is about evaluating the bibliometric parameters of the documents published in the prominent journal, "Public Library Quarterly" (PLQ) from 1979 to 2021. Research Design: The dataset for this retrospective study was retrieved from the Scopus database. The bibliographic information of all kinds of documents was downloaded in the Comma Separated Value (CSV) file, further converted into Microsoft Excel for analysis. The bibliometric indicators of publications and citations by years, authorship pattern, most contributing countries, productive authors, frequently used keywords and salient appearances of highly cited were examined. Microsoft Excel, VOSviewer and Biblioshiney software were applied to visualize the data. The dataset is limited to papers of PLQ that were indexed in the Scopus data. Key Findings: A total of 1151 documents were found and about 78% were contributed by a single author pattern. The multi-author papers gained a higher citation impact. The analysis of data witnessed that a visible shift from single-author to multi-author was observed and the number of papers was also increased from 2011 to 2021. The majority of papers was fall in the category of articles, followed by editorials. Waters R. L. and United States were found to be the most productive author and the most contributing country, respectively. The "public libraries" and "public library" were the most used keywords. More than one-fifth of the citations were gained by the 15 highly-cited papers. [ABSTRACT FROM AUTHOR]

This paper provides an account of the topological and its description of contemporary culture and use as a research methodology, a topological lens, generally, and in education research specifically. Some commentary is proffered on the relationships between the topological and the topographical, between relations and locations. A critical account is then provided on each of the papers in the special issue on the topological in education research and the specific contributions of each. The editors of the special issue make the important point that the topological is a spatio-temporal phenomenon, not just a spatial one. The topological does not exist in time and space, but rather constructs both and they change in a conjoint manner. As such, a topological lens rejects a construction of space as static and of time (and the temporal) as simply linear and chronological. The topological has been facilitated and articulated by and through practices of commensuration, datafication and digitalisation, flows and scapes, global connectivities and new relations, mobilities of various kinds and multiple networks. The paper argues that much greater emphasis has been given to the spatial in topological research; that is, there has been some neglect of the temporal in the spatio-temporal character of topologies.

This paper discusses empirical comparisons of higher education institutions across world regions. It argues that institutional data systems have the potential for complementing global comparisons promoted by rankings by providing sensible information on institutional size, budgets, staffing, enrolments and activity profiles. With this perspective in hand, this paper tackles three questions. First, how is it feasible to identify Higher Education Institutions (HEIs) given their complex structures? Second, how is it feasible to define the perimeter of HEI sectors? Third, what kinds of data could be used for comparison, and where are the main data gaps? By analysing institutional data systems across the United States, Europe and Asia, the paper concludes that institutional data systems display some remarkable similarities that make them an important resource for global comparisons; however, variation in the context of data production and usage implies differences in the higher education perimeter and on institutional delimitation; sensible comparisons, therefore, require explicit knowledge of the institutional context in which data have been borne.

In the last three decades, a networked global system has emerged in the natural-science-based disciplines, sustained by collegial epistemic relations in universities. Nationally ordered and funded science has expanded alongside the global science system. The common global pool of papers, defined by bibliometric collections, nevertheless excludes large components of knowledge. In the global system, four tendencies are apparent: (1) rapid growth of papers, (2) diversification of scientific capacity to many more countries, (3) expansion of networked international and national collaboration as measured by co-authorship, (4) growing multi-polarity of capacity, outputs and quality, with the rise of China and several middle-sized national systems outside the Euro-American bloc. The paper critiques the interpretation of global science dominant in scientometrics, in which positivist data analyses are applied to performative national comparisons. It argues for a historical-synthetic explanation of the global system that combines data and theorisation, and accounts for relations of power.

The development of efficient and reliable online assessments has become increasingly important in the digital era. We developed a 10-min online word reading assessment of global English based on the existing paper-and-pencil version of our English silent word reading test. The test includes two parts, namely, random word recognition and contextual word reading. A total of 889 participants (437 children and 392 adults; 62.7% female) took part in the study. They were from various regions including mainland China, Hong Kong SAR, Macau SAR, Poland, the United States, and the Philippines. Reliability and validity analyses on various demographics samples (by age and country/region of origin) demonstrated that the WordSword Test is highly reliable and valid (e.g., the correlation of this test with other English reading measures were above.80). Education level was positively correlated with test performance, while the correlations between age and test performance were not consistent. Ninety-seven children participants also took the paper-and-pencil version of the WordSword Test. The correlation between performances on the online and paper-and-pencil versions of the test was.879, one year apart. With more children and adults taking the WordSword Test, we ultimately hope to establish norms by area, grade level, and age. [ABSTRACT FROM AUTHOR]

In this paper we make a case for 'Little Data', which is real-time, self-collected, idiosyncratic datasets maintained by individuals about themselves on myriad topics. We develop and offer a methodology for combining these messy, highly personal insights, to make deductive observations about collective practices. In testing this approach, we use the case study of the 2020-21 stay-at-home orders imposed in the U.S.A., U.K., and Western Europe during the Coronavirus pandemic to operationalise and demonstrate the applicability of this method. Our main finding is to show that whilst stay-at-home orders did have a significant impact on habits during the COVID-19 pandemic, these changes were often counterintuitive, of an insightful nature on topics that would otherwise not be investigated, and always short-lived. Our main contribution is to present Little Data, despite and because of its fragmented and disparate nature, as a viable and useful tool to understand personal habits at finite junctures.

On May 4, 2020, the US Food and Drug Administration (FDA) hosted an online public workshop titled "FY 2020 Generic Drug Regulatory Science Initiatives Public Workshop" to provide an overview of the status of the science and research priorities and to solicit input on the development of Generic Drug User Fee Amendments fiscal year 2021 priorities. This report summarizes the podium presentations and the outcome of discussions along with innovative ways to overcome challenges and significant opportunities related to model-based approaches in bioequivalence assessment for breakout session 4 titled, "Data analysis and model-based bioequivalence (BE)." This session focused on the application of model-based approaches in the generic drug development, with a vision of accelerating regulatory decision making for abbreviated new drug application assessments. The session included both podium presentations and panel discussions with three topics of interest: (i) in vitro study evaluation methods and their clinical relevance, (ii) challenges in model-based BE, (iii) emerging expertise and tools in implementing new BE approaches., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

Background The Florida Keys Mosquito Control District has used dry ice-baited light traps to monitor mosquito populations on Key Largo since 2003. This paper describes the methodology of trapping, the habitat and the dataset of adult mosquito populations from 18 years of weekly monitoring from a single site on Key Largo, Monroe County, FL, USA. New information This data paper provides previously unpublished data from a single trapping location in Key Largo, Florida. Two new species have been added to previously-published data from this trapping site. [ABSTRACT FROM AUTHOR]

As COVID-19 poses a major threat to people's health and economy, there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently. In non-stationary time series forecasting jobs, there is frequently a hysteresis in the anticipated values relative to the real values. The multilayer deep-time convolutional network and a feature fusion network are combined in this paper's proposal of an enhanced Multilayer Deep Time Convolutional Neural Network (MDTCNet) for COVID-19 prediction to address this problem. In particular, it is possible to record the deep features and temporal dependencies in uncertain time series, and the features may then be combined using a feature fusion network and a multilayer perceptron. Last but not least, the experimental verification is conducted on the prediction task of COVID-19 real daily confirmed cases in the world and the United States with uncertainty, realizing the short-term and long-term prediction of COVID-19 daily confirmed cases, and verifying the effectiveness and accuracy of the suggested prediction method, as well as reducing the hysteresis of the prediction results. [ABSTRACT FROM AUTHOR]

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Background: Cough is one of the most common presenting problems for patients in primary care and is largely managed in primary care clinical settings. Family physicians' familiarity with chronic cough guidelines and the extent to which these guidelines translate into everyday practice have not been well described. The objective of this study was to characterize current diagnosis, treatment, and referral practices among family physicians and to identify potentially impactful strategies to optimize chronic cough management in primary care. Methods: We conducted a cross-sectional survey of 5,000 family physicians to explore diagnosis, treatment, and referral practices related to chronic cough management in adults in primary care. Respondents completed the survey via paper or online. The outcome measures were self-reported numeric ratings and responses related to the survey elements. Results: 588 surveys were completed (11.8% response rate). About half (49.6%) of respondents defined chronic cough in a manner consistent with the American College of Chest Physicians (ACCP) chronic cough guidelines, with the rest differing in opinion primarily regarding duration of symptom presentation. Respondents reported trying to rule out most common causes of chronic cough themselves before referring (mean 3.41 on a 4-point scale where 4 is "describes me completely") and indicated a desire for more resources to help them manage and treat chronic cough. Years in practice and rural/urban setting influenced diagnosis and referral practices. Conclusions: Family physicians see chronic cough as a complicated condition that can be and is often diagnosed and treated entirely in a primary care setting. They also value the ability to refer in complex cases. Our results support that family physicians provide evidence-based management of chronic cough. [ABSTRACT FROM AUTHOR]

Visualization skills are now considered a core competency of business and data analytics. This paper provides a detailed analysis of course descriptions, learning outcomes and assessment strategies, textbooks, and visualization software used from a study of thirty-three visualization course syllabi from a diverse set of higher educational institutions in the United States. The results from this survey can be helpful to faculty teaching visualization courses for the first time. It also provides a comparative analysis for faculty who currently teach courses in visualization. [ABSTRACT FROM AUTHOR]

Purpose: This paper presents a re-analysis of the National Child Abuse and Neglect Data System (NCANDS) data presented by Briggs et al. (2022). Methods: We review five components of that article: The aims, variables, analytic strategy, analysis, and conclusions. Results: We conclude that several of the NCANDS variables used are invalid at the national level, and that this is sufficient to call the research into question. We find concerning issues in analytic strategy and analysis as well, many stemming from a failure to account for the serious underreporting of services in NCANDS, and the wide variability in data quality and consistency across states. We also found what we consider to be issues with their statistical analysis. Discussion: The reanalysis presented in this article shows no pattern of disparate within Child Protective Services (CPS) outcomes by race and, therefore, no support for the Briggs et al. claim of pervasive anti-Black racism within the CPS system. [ABSTRACT FROM AUTHOR]

Background: As delays or disorders in early language and communication are the most prevalent symptom in children with disabilities, early screening is crucial to promote prevention, early diagnosis, and intervention. However, to the best of our knowledge, no screening tool is available for the joint assessment of early language and social communication skills in European Portuguese (EP)‐learning children, which is critical for screening, monitoring and enrolment in appropriate early intervention services. Aims: (1) To adapt and validate the EP version of the Communication and Symbolic Behaviour Scales Developmental Profile™ (CSBS DP™) Infant–Toddler Checklist, a parental report for the screening of early language and social communication skills. (2) To conduct a cross‐cultural comparison between the EP adaptation and the original US version. Methods & Procedures: A total of 611 EP‐learning children (ages 6–24 months) were assessed on the CSBS DP Infant–Toddler Checklist. Normative data, psychometric characteristics (i.e., internal consistency and test–retest reliability), and cross‐cultural comparison between the EP and the original version were explored. Outcomes & Results: Internal consistency ranged from good to excellent and the test–retest reliability was excellent. The performance of the EP and US samples matched on almost all scores. However, EP children performed significantly better than their American peers in the Social compositive at 22 months and in the Symbolic composite at 20 months. No further differences were found. Conclusions & Implications: These findings showed that the EP CSBS DP Infant–Toddler Checklist seems to be a reliable screening tool of communicative and symbolic behaviours for EP‐learning children, which can be particularly relevant for decision‐making in clinical practice. WHAT THIS PAPER ADDS: What is already known on the subject: Early communication skills are known to be related to later language outcomes. Thus, screening tools for the early identification of children at risk for language and communication impairments, which may lead to monitoring and early intervention, have the potential to promote better outcomes. However, to the best of our knowledge, no screening tool is available for the assessment of early communication abilities in EP‐learning children. What this paper adds to existing knowledge: This study adapted and validated the EP CSBS DP Infant–Toddler Checklist, the first published parental report checklist for the assessment of early communication skills in EP. It described the psychometric characteristics of the adapted checklist, summarized the newly available normative data for EP‐learning infants and toddlers, and compared the performance of EP‐learning children with the original standardization sample reported for American English. The results demonstrated that this tool is a reliable instrument for the early screening of language, communicative and symbolic behaviours for EP‐learning children between 6 and 24 months of age. What are the potential or actual clinical implications of this work?: Given that early screening is crucial to promote prevention, early diagnosis and intervention, the availability of this tool is particularly relevant for children monitoring and their enrolment in appropriate early intervention services, helping decision‐making in clinical practice, in line with current guidelines regarding early monitoring and intervention to promote and support better outcomes. Thus, the tool and related normative data will be useful for paediatricians, family doctors, primary healthcare providers, developmental psychologists and speech–language therapists, among other professionals in the healthcare and educational fields, concerned with speech, language, and communication development and impairments. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the association of COVID-19 confirmed cases and deaths with mental health, unemployment and financial markets-related search terms for the USA, the UK, India and worldwide using Google Trends. Design/methodology/approach: The authors use Spearman's rank correlation coefficients to assess the relationship between relative search volumes (RSVs) and mental health, unemployment and financial markets-related search terms, with the total confirmed COVID-19 cases as well as deaths in the USA, UK, India and worldwide. The sample period starts from the day 100 cases were reported for the first time, which is 7 March 2020, 13 March 2020, 23 March 2020 and 28 January 2020 for the US, the UK, India and worldwide, respectively, and ends on 25 June 2020. Findings: The results indicate a significant increase in anxiety, depression and stress leading to sleeping disorders or insomnia, further deteriorating mental health. The RSVs of employment are negatively significant, implying that people are hesitant to search for new jobs due to being susceptible to exposure, imposed lockdown and social distancing measures and changing employment patterns. The RSVs for financial terms exhibit the varying associations of COVID-19 cases and deaths with the stock market, loans, rent, etc. Research limitations/implications: This study has implications for the policymakers, health experts and the government. The state governments must provide proper medical facilities and holistic care to the affected population. It may be noted that the findings of this study only lead us to conclude about the relationship between COVID-19 cases and deaths and Google Trends searches, and do not as such indicate the effect on actual behaviour. Originality/value: To the best of the authors' knowledge, this is the first attempt to investigate the relationship between the number of COVID-19 cases and deaths in the USA, UK and India and at the global level and RSVs for mental health-related, job-related and financial keywords. [ABSTRACT FROM AUTHOR]

Aims: This exploratory study, using mixed methods research, aimed to (1) examine the associations among self‐efficacy, social support and regular leisure‐time physical activity of nursing staff, and (2) identify motivators and barriers to leisure‐time physical activity. Background: It is important to engage nursing staff in regular leisure‐time physical activity as a countermeasure against high occupational stress and poor health. Limited research has examined nursing staff's participation in leisure‐time physical activity and associated factors. Methods: Nursing staff employed at a community hospital in the northeastern United States were invited to participate in this cross‐sectional survey with close‐ and open‐ended questions in March 2016. Results: A total of 363 nurses and nursing assistants responded, among whom, 59.8% reported regular leisure‐time physical activity. Poisson regression models suggested that self‐efficacy and social support had an interactive association with increased prevalence of regular leisure‐time physical activity. Conclusion: Self‐efficacy and social support have an important synergistic association with regular leisure‐time physical activity of nursing staff. Effective interventions intending to facilitate nursing staff's leisure‐time physical activity should consider improving their self‐efficacy and social support. Qualitative comments suggested that work‐out areas in the workplace with release time and organized activity may promote regular leisure‐time physical activity of nursing staff. Summary statement: What is already known about this topic? Leisure‐time physical activity is beneficial to both physical and mental health.Self‐efficacy and social support have been reported as independent predictors of leisure‐time physical activity in the general population.There is limited evidence regarding nursing staff's level of participation in leisure‐time physical activity and associated factors. What this paper adds? There is a higher level of participation in leisure‐time physical activity among nursing staff than the general population.Exercise self‐efficacy and social support have a synergistic association with regular leisure‐time physical activity among nursing staff.Support and promoting physical and mental fitness are motivators, whereas lack of time and energy and physical illnesses are barriers to regular leisure‐time physical activity reported by nursing staff. The implications of this paper: Findings indicate effective interventions designed to improve both self‐efficacy and social support might help facilitate nursing staff's participation in regular leisure‐time physical activity.Findings suggest organizational support through installing work‐out areas in the workplace with release time and organized activity might enhance nursing staff's capacity to engage in leisure‐time physical activity. [ABSTRACT FROM AUTHOR]

Collaborative governance ebbs and flows. Partnerships become dormant or extinct, only to resurface with new members, and names, forms, or boundaries. This paper uses a systematic qualitative analysis of data from 4 watershed governance efforts in the United States––Delaware Inland Bays, Narragansett Bay, Tampa Bay, and Tillamook Bay. The study's objective is to develop theory grounded in these data by examining the developmental trajectories associated with collaborative partnerships. The paper begins by summarizing a four-stage life-cycle model. Each stage identifies a cluster of developmental challenges related to sustaining the health and useful life of a collaborative partnership. The paper identifies 31 partnerships across the four watersheds that were self- or externally-initiated. They experienced many different developmental trajectories. Some remained relatively healthy for a considerable period while others declined quite rapidly. Some partnerships had reorientations involving minor and rapid changes to the partnership structure. Some involved recreations with more profound shifts in core values and purposes. Some partnerships lasted for a considerable period while others ended when their work was done. Healthy partnerships also ended prematurely while unhealthy partnerships endured for a considerable period after their useful life ended. The paper concludes with a discussion of the implications for theory and practice. [ABSTRACT FROM AUTHOR]

Research background: Most transactions in world trade are invoiced in several international currencies. The changes in the distribution of the great economic powers and the strengthening of the position of developing countries make it necessary to consider the factors determining the choice of trade invoicing currency and to assess the prospects of the dollar as an invoicing currency and the possibility of strengthening the position of developing countries' currencies in this function. Purpose of the article: The aim of the paper is to assess the factors influencing the choice of invoicing currency for international trade in 2000-2019. Methods: The analysis of factors influencing the choice of international trade invoicing currency is based on panel data modelling. The study is conducted for a group of 55 countries. It is assumed that the following variables may influence the currency position in the trade invoicing function: the share of the issuer's country in the bilateral trade, inflation and exchange rate. Findings & value added: The analysis showed that despite the decreasing share of the United States in world trade, the U.S. dollar remains the most important export invoicing currency. The main factors influencing the dollar's dominance are the U.S. share of countries' exports, inflation in developing countries, and the exchange rate in advanced economies. The great significance of trade share as a determinant of the position of the trade invoicing currency is an important indication of the strengthening position of developing country currencies, particularly the Chinese yuan. The obtained results confirm, with the use of more complete data, the validity of the dominant currency paradigm and enrich the still underdeveloped analysis in the area of international macroeconomics using panel data analysis. [ABSTRACT FROM AUTHOR]

During virus outbreaks in the recent past, web behavior mining, modeling, and analysis have served as means to examine, explore, interpret, assess, and forecast the worldwide perception, readiness, reactions, and response linked to these virus outbreaks. The recent outbreak of the Marburg Virus disease (MVD), the high fatality rate of MVD, and the conspiracy theory linking the FEMA alert signal in the United States on 4 October 2023 with MVD and a zombie outbreak, resulted in a diverse range of reactions in the general public which has transpired in a surge in web behavior in this context. This resulted in "Marburg Virus" featuring in the list of the top trending topics on Twitter on 3 October 2023, and "Emergency Alert System" and "Zombie" featuring in the list of top trending topics on Twitter on 4 October 2023. No prior work in this field has mined and analyzed the emerging trends in web behavior in this context. The work presented in this paper aims to address this research gap and makes multiple scientific contributions to this field. First, it presents the results of performing time-series forecasting of the search interests related to MVD emerging from 216 different regions on a global scale using ARIMA, LSTM, and Autocorrelation. The results of this analysis present the optimal model for forecasting web behavior related to MVD in each of these regions. Second, the correlation between search interests related to MVD and search interests related to zombies was investigated. The findings show that there were several regions where there was a statistically significant correlation between MVD-related searches and zombie-related searches on Google on 4 October 2023. Finally, the correlation between zombie-related searches in the United States and other regions was investigated. This analysis helped to identify those regions where this correlation was statistically significant. [ABSTRACT FROM AUTHOR]

The OLMAR method, which stands for the on-line moving average reversion method, is reported to be one of the most powerful among portfolio selection algorithms in the stock markets. In this research, we use intensive statistical and simulation analyses of long-term data on stock market changes to uncover the secrets of why and when the superiority appears. We find that there have been long-lasting fluctuations in the stock markets and that the OLMAR method actively makes use of such characteristics. In this paper, we analyze long-term stock data from Japan and the United States. The analyses confirm the following points. 1) The OLMAR method yields superior returns. 2) By using the moving average divergence rate provided by the OLMAR method, it is possible to detect specific fluctuation characteristics in long-term stock data from Japan and the United States. 3) Superior returns cannot be obtained from data in which specific fluctuation characteristics have been corrected. [ABSTRACT FROM AUTHOR]

Previous research has found that music brings back more vivid and emotional autobiographical memories than various other retrieval cues. However, such studies have often been low in ecological validity and constrained by relatively limited cue selection and predominantly young adult samples. Here, we compared music to food as cues for autobiographical memories in everyday life in young and older adults. In two separate four‐day periods, 39 younger (ages 18–34) and 39 older (ages 60–77) adults recorded their music‐ and food‐evoked autobiographical memories in paper diaries. Across both age groups, music triggered more frequent autobiographical memories, a greater proportion of involuntary memories, and memories rated as more personally important in comparison to food cues. Age differences impacted music‐ and food‐evoked memories similarly, with older adults consistently recalling older and less specific memories, which they rated as more positive, vivid, and rehearsed. However, young and older adults did not differ in the number or involuntary nature of their recorded memories. This work represents an important step in understanding the phenomenology of naturally occurring music‐evoked autobiographical memories across adulthood and provides new insights into how and why music may be a more effective trigger for personally valued memories than certain other everyday cues. [ABSTRACT FROM AUTHOR]

The contemporary Religious Left (RL) in the United States has proven to be somewhat of an enigma, both for academics and for the activists and voters who desire such a movement to thrive. In this paper, I look at one piece of the puzzle: is the RL able to mobilize supporters to political activity? Combining data from both the individual and movement level, this paper tests whether activity at the movement level of the RL can translate into individual supporters' political activity. Using existing data for 2008 and newly collected data on the RL in the 2016 election cycle, I find that the movement was successful in mobilizing constituents in 2008, but not in 2016. This can be linked to the Democrats' effort to engage religious voters in 2008, and its inability to do so in 2016. [ABSTRACT FROM AUTHOR]

INTRODUCTION The majority of decisions on electronic nicotine delivery system (ENDS) premarket tobacco product applications (PMTAs) were made from October 2020 to February 2023; 99% (>25 million) had determinations by March 2023 and just twenty-three received marketing granted orders. We examined the unique devices and liquids used among US adults frequently using ENDS before, during, and after a majority of PMTA decisions were made. METHODS Data are from waves 1-5 (W1: May-Oct 2020, n=1179; W5: Feb-Apr 2023, n=1290) of a longitudinal survey of US adults (≥21 years) using ENDS ≥5 days/week. User-submitted photos of participants' most used devices and liquids were coded. Descriptive analyses and Wilcoxon signed-rank tests were used to understand the number and types of unique devices and liquids used in W1-W5, and the top brands in each wave. RESULTS From W1-W5, the number of unique ENDS device models and liquid products used by participants increased from 279 to 357 (p<0.001) and 546 to 695 (p<0.001), respectively. More unique devices in W5 versus W1 were disposable (W1: 16.5%; W5: 36.1%); fewer were disposable pod (W1: 6.5%; W5: 3.1%) or tank (W1: 53.8%; W5: 30.8%) devices. Liquids were primarily sweetflavored (W1: 81.1%; W5: 82.0%). The median liquid nicotine concentration increased from 12 to 50 mg/mL. In W5, few participants used FDA-approved devices (n=17; 1.3%) or liquids (n=6; 0.5%), and Elf Bar was the most commonly used device and liquid brand. Results for all waves are reported. CONCLUSIONS Despite PMTA decisions, an increase in the number of unique device models and liquid products used among adults who frequently use ENDS was observed from 2020 to 2023. Few participants in 2023 were using FDA-approved devices or liquids. Further research and monitoring are needed to inform how FDA prioritizes enforcement actions and what types of enforcement actions are effective. [ABSTRACT FROM AUTHOR]

Background: Valuable safeguards against fast‐spreading conjectures about learning in times of fear and uncertainty are evidence‐based approaches to the assessment of the impact of sudden and unforeseen disruptions on learning practices. The present research focused on physics learning in such times because conceptual and computational literacy in physics is critical to the development of a scientifically and technologically literate society. Objectives: The present research aimed (a) to offer an objective assessment of whether performance differences in a physics course of the general education curriculum existed between the face‐to‐face medium (familiar mode of instruction) and the online medium (unfamiliar mode of instruction) for both male and female students, and then (b) to develop a response to the evidence collected to ensure a quality education for all parties involved. The research intended to fill two critical gaps in the extant literature: mixed findings concerning students' performance in the face‐to‐face and online mediums as well as scarce coverage of specific domains of knowledge that are critical to STEM learners. Methods: Students' performance was examined as a function of the type of assessment (formative and summative), instructional mode (online and face‐to‐face), and gender. An understudied student population of STEM students of Middle Eastern descent without prior formal exposure to online instruction was targeted. Results and Conclusions: In both formative and summative assessments, male students performed better online than face‐to‐face, whereas the performance of female students was either higher online or equivalent between instructional mediums. The evidence collected suggested that consideration be given to remedies that foster academic success in the face‐to‐face instructional medium, particularly for male students. Takeaways: An evidence‐based approach to learning dismantled emotion‐driven expectations regarding the impact of the online medium on physics learning, and encouraged new perspectives about instruction. Lay Description: What is already known?: Ongoing debates on the impact of the pandemic on students' learning shape decisions regarding future reliance on the online medium for instruction. What this paper adds: The extant literature is mixed concerning performance in the face‐to‐face and online mediums, including particular domains of knowledge critical to STEM learning.This study focused on physics learning in an understudied population of STEM students who were unaccustomed to online instruction.Performance was higher online than face‐to‐face, but gender differences emerged. Implications for practice: Lessons learned focused on the flexibility of online learning and on the need to develop materials to enhance learning in males enrolled in face‐to‐face or hybrid/blended classes. [ABSTRACT FROM AUTHOR]

The COVID-19 global pandemic has significantly impacted every aspect of life all over the world. The United States is reported to have suffered more than 20% of the global casualties from this pandemic. It is imperative to investigate the growth dynamics of the disease in the US based on varying geographical and governmental factors that best manifest itself in each State of the Country. This paper utilizes a hybrid machine learning and continuum deformation-based approach for analyzing the stability and growth rate of the pandemic. To this end, principal stress values of the pandemic continuum body are obtained using Mohr's Circle method and overlapping, moving windows of data are analysed successively. This helps in finding the correlations between the growth rate and Governments' action/Public's reaction. Government actions include "state of emergency", "shelter at place", and "phase declarations". We also consider the vaccination rate milestones, which shows us the coordinated Governments' action/Public's reaction. Finally, a number of recommendations are made to the Governments and people for better management of future pandemics. [ABSTRACT FROM AUTHOR]

The difference, average risk-neutral and physical volatility, is substantial and translates into a large return premium for sellers of index options. This paper studies a general equilibrium model based on long-run risk in an effort to explain the premium. In estimating the model using data on stock returns and volatility (VIX), the model captures the premium and also the large negative correlation between shocks to volatility and stock prices. Numerical simulations verify that writers of index options earn high rates of return in equilibrium and that the return patterns are similar to that seen in the S&P 500 index options data. [ABSTRACT FROM AUTHOR]

The sweep of the coronavirus pandemic across the world and the United States offers an almost unparalleled opportunity to study how social systems cope with the threat and opportunities for collective action. In this paper, we draw on survey data collected as the United States flailed in response and before a general consensus among executive officeholders developed in the following weeks. In particular, we assess how holding prosperity gospel views strongly shaped perceptions of the virus and reactions to state responses to the virus. Research on the prosperity gospel is slowly expanding and this paper helps to highlight some missing dimensions. At a time when concerted action for the social good could be uniting the country, prosperity gospel beliefs systematically undermine that possibility by augmenting threat, raising outgroup barriers, and decreasing social trust. [ABSTRACT FROM AUTHOR]

Increased electronic filing, or e-filing, of nonprofit data in the United States and abroad quickens public availability, eliminates dependence on third-party proprietary datasets, and broadens access to information offering insight into previously neglected topics. On the other hand, increasingly open data require researchers to independently ensure data quality, understand limitations, and consider how data availability shapes research questions. As electronic filing becomes mandatory in the United States and more widespread elsewhere, this research considers how expanded e-filer data impact nonprofit research approaches and opportunities while assessing the generalizability and limits of existing e-filed data in the United States. While the data suggest increasing compliance with e-filing, analyses show that older nonprofits with greater capacity and sophisticated financial characteristics are historically more likely to e-file. Further, particular subsectors are more likely to e-file than others. Therefore, using existing e-filed IRS Form 990s for panel data analysis presents some generalizability concerns, although this will improve over time. Moving forward, e-filing and machine-readable access requirements bode well for both quantitative and qualitative nonprofit research, while the United States' experience provides helpful lessons for other research settings. [ABSTRACT FROM AUTHOR]

Study Objectives Fear of sleep contributes to insomnia in some individuals with posttraumatic stress disorder (PTSD) but remains uncharacterized in first responders, a population with high rates of insomnia and PTSD. We evaluated the clinical relevance of fear of sleep in first responders by (1) examining its relationship with trauma types and clinical symptoms and (2) assessing differences in fear of sleep severity between those reporting provisional PTSD, insomnia, or both. Methods A cross-sectional study of 242 first responders across the United States (59.2% male, 86.4% white, 56.2% law enforcement officers, 98.7% active duty, and M years of service = 17). Participants completed the Fear of Sleep Inventory-Short Form and measures of trauma history, psychopathology (e.g. PTSD), and sleep disturbances (insomnia and trauma-related nightmares). Results Fear of sleep was associated with trauma types characterized by interpersonal violence and victimization, as well as symptoms of PTSD, depression, anxiety, stress, alcohol use problems, insomnia, and trauma-related nightmares. Fear of sleep was most pronounced among first responders reporting provisional PTSD comorbid with insomnia compared to those with PTSD or insomnia only. Post hoc analyses revealed PTSD hyperarousal symptoms and trauma-related nightmares were independently associated with fear of sleep, even after adjusting for the remaining PTSD clusters, insomnia, sex, and years of service. Conclusions Fear of sleep is a clinically relevant construct in first responders that is associated with a broad range of psychopathology symptoms and is most severe among those with cooccurring PTSD and insomnia. Fear of sleep may merit targeted treatment in first responders. This paper is part of the Sleep and Circadian Health in the Justice System Collection. [ABSTRACT FROM AUTHOR]

Shiftwork leads to myriad negative health and safety outcomes. Lighting countermeasures can benefit shiftworkers via physiological effects of light (e.g. alerting, circadian adjustment), and short-wavelength light is the most potent for eliciting those responses; however, limited work indicates it may not be required for alerting. We developed similar-appearing light boxes (correlated color temperature: 3000–3375 K; photopic illuminance: 260–296 lux), enriched (SW+, melanopic EDI: 294 lux) or attenuated (SW-, melanopic EDI: 103 lux) in short-wavelength energy, and implemented them on a high-security watchfloor. Efficacy and feasibility of these two novel lighting interventions were assessed in personnel working 12-hour night shifts (n  = 47) in this within-participants, crossover study. For each intervention condition, light boxes were arranged across the front of the watchfloor and illuminated the entire shift; blue-blocking glasses were worn post-shift and before sleep; and sleep masks were used while sleeping. Comparisons between baseline and intervention conditions included alertness, sleep, mood, quality of life (QOL), and implementation measures. On-shift alertness (Karolinska Sleepiness Scale) increased in SW− compared to baseline, while changes in SW+ were more limited. Under SW+, both mood and sleep improved. Psychomotor vigilance task performance did not vary by condition; however, perceived performance and QOL were higher, and reported caffeine consumption and sleep onset latency were lower, under SW−. For both interventions, satisfaction and comfort were high, and fewer symptoms and negative feelings were reported. The addition of spectrally engineered lights to this unique work environment improved sleep, alertness, and mood without compromising visual comfort and satisfaction. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection. [ABSTRACT FROM AUTHOR]

Background: Students' tendencies to seek feedback are associated with improved learning. Yet, how soon this association becomes robust enough to make predictions about learning is not fully understood. Such knowledge has strong implications for early identification of students at‐risk for underachievement via digital learning platforms. Objectives: We sought to understand how early in the academic year students' end‐of‐year learning outcomes could be predicted by their performance and feedback‐seeking behaviours within a digital learning platform. We analysed data collected at different time points in the academic year and across different cohorts of students within the context of high school advanced placement (AP) Statistics courses. Methods: High school students enrolled in AP Statistics spanning three academic years between 2017 and 2020 (N = 726; Mage = 16.72 years) completed 3 or 4 homework assignments, each 2 and 3 months apart. Results and conclusions: Across the three cohorts, and even as early as the first assignment, a model consisting of demographic variables (gender, race/ethnicity, parental education), assignment performance, and interaction with the digital score report explained significant variation in students' final course grades (R2 = 0.314–0.412) and AP exam scores (κ = 0.583–0.689). Students' assignment performance was positively associated with end‐of‐year learning outcomes. Students who more frequently checked their digital score reports tended to receive better learning outcomes, though not consistently across cohorts. Implications: These findings further an understanding of how students' early performance and feedback‐seeking behaviours within a digital learning platform predict end‐of‐year learning outcomes. Lay Description: What is already known about this topic: Students' early academic performance predicts end‐of‐year success.Students' self‐regulated learning behaviours are another predictor of academic success.Clickstream data have been used as an indicator of the application of self‐regulated learning strategies, particularly behaviours associated with seeking feedback.Indicators of feedback‐seeking behaviours reflected via clickstream data have been shown to predict student learning.Yet, how soon associations between early performance and such indicators of self‐regulated learning as feedback‐seeking are robust across different groups of learners, different learning circumstances, and different types of learning outcomes has yet to be more fully understood. What this paper adds: We investigated whether performance and feedback‐seeking behaviours predict end‐of‐year learning outcomes at different points during the academic year across multiple cohorts of learners (2017–2018, 2018–2019, and 2019–2020) and using two different learning outcomes (class grades, AP exam scores).One cohort was affected by COVID‐19 during the 2019–2020 academic year, allowing us to examine whether differences emerge amidst unprecedented circumstances.We used assignment scores and online feedback‐seeking to predict end‐of‐year learning outcomes.Assignment scores were positively associated with end‐of‐year grades.First assignment performance predicted AP exam scores.Use of feedback (an indication of self‐regulated learning behaviours) tended to predict learning outcomes, though not consistently across cohorts. Implications for practice and/or policy: The findings from this study could improve understanding of how digital learning platform measurements predict end‐of‐year learning outcomes though also highlight the importance of context differences.Such findings hold implications for early identification of at‐risk students and appreciation for differences between learners and contexts.These findings also contribute to a growing understanding of the impact of the COVID‐19 pandemic on student engagement and learning. [ABSTRACT FROM AUTHOR]

The development of a new type of international relations is the advancement and improvement of diplomatic thinking among contemporary nations. It also serves as a crucial yardstick for assessing the future global pattern and the direction of order changes. Proper interaction between major powers can foster the growth of new international relations and has a significant impact on advancing global cooperation and the promotion of human peace. The goal of this essay is to examine how friendly interactions between major powers have affected the development of new international relations. A deep learning network model is presented for this purpose. The deep learning model was used to identify the emotions of the survey results, analyze each person's emotional tendencies, and summarize and compare the data. Relevant questionnaire surveys were conducted using the online questionnaire survey method on individuals in various countries. The survey results in this paper demonstrate that 96.5 percent of Chinese, 89.3 percent of Russians, and 81.6 percent of Americans support friendly relations between major nations. Only a very small percentage of the investigators supported hostile relations, with their support being 1.06 percent, 3.11 percent, and 2.94 percent, respectively. Therefore, creating a win-win partnership between major powers is exactly what the people of all nations are calling for. In contrast to the past, it is no longer hostile and violent. People anticipate that more great powers will coexist peacefully. [ABSTRACT FROM AUTHOR]

Some macroeconomic dimensions like the economic business cycle, the exchange rate movements when the degree of country openness is significant, or the level of inflation are often considered to explain measured-inflation dynamics. However, inflation volatility may also be affected by statistical agencies methodological changes. This paper explores both potential explanations in a panel data for 100 United States CPI-U subcategories. Using both unconditional and conditional variances, we find that crucial changes in how agencies consider quality adjustment in products, together with the macroeconomic variables help to understand CPI volatility over time, both in the short-run and in the long-run. [ABSTRACT FROM AUTHOR]

The paper explores how paid and unpaid labor history over the life course influence women's cardiovascular disease. U.S. women comprise about 50% of the paid workforce and perform the majority of unpaid labor. However, the influence of women's work on their health is under-researched. Our sample was drawn from the Women's Health Initiative Observational Study, a cohort of post-menopausal women in the U.S. aged 50–79 at recruitment. Women were categorized into five groups according to paid labor history: worked in paid jobs consistently throughout adult life; left the workforce early; entered the workforce later; discontinuous work history; never worked outside the home. Live birth history (none, at least one, missing) served as a proxy for unpaid labor in prime age. Cox proportional hazard models were used to estimate the hazard ratio of CVD associated with different paid work histories. We then assessed the effect of unpaid labor on the relation between paid labor and CVD. Paid labor participation was not associated with CVD risk among women without unpaid labor after adjusting for age, education, and birth cohort. Among those with unpaid demands, leaving the workforce early or having discontinuous work history was protective. In this U.S. sample, the association between paid work participation history and CVD risk depends on the presence of unpaid labor. Our results demonstrate the necessity of including work – paid and unpaid – in consideration of women's health. [ABSTRACT FROM AUTHOR]

This research paper studies second-generation Bosnians in the United States, to understand the identity formation of this population after the Bosnian War through the lenses of home, belonging and borders. Through archival research and extended interviews, second-generation Bosnian-Americans were asked questions about their dual/hybrid identity and their sense of home and belonging. Analysis of the data shows that the second generation has had relatively weak acculturation, by some measures, due to close identification with their heritage. Yet, the second generation's view of the Bosnian War is different from that of the first generation, who prefer to distance themselves from memories of war. The second generation would like to preserve their parents' experiences as a part of their lives and pass it on to the next generation of Bosnian-Americans. [ABSTRACT FROM AUTHOR]

INTRODUCTION E-cigarette use is disparately high among sexual minoritized populations. As e-cigarette advertising may influence product appeal, this study tested sexual orientation- and gender-based differences in response to e-cigarette advertisement exposure on advertisement perceptions and product appeal. METHODS We recruited 497 adults (mean age=31.9 years, 45.1% women, 54.3% heterosexual, 71.2% Non-Hispanic White) living in the United States via the crowdsourcing platform Prolific. Participants viewed two randomly selected e-cigarette advertisements (from n=173 advertisements). Post-exposure, participants rated the perceived advertisement effectiveness, relevance, and product use intention. Associations between sexual orientation and outcomes were estimated using multivariable linear mixed-effects models. We tested interaction effects between sexual orientation, gender, and advertisement feature (e.g. presence of humans, flavors, and product packaging), and ran Tukey post hoc tests for pairwise comparisons. RESULTS Post-exposure, heterosexual women, sexual minoritized men, and sexual minoritized women (reference group: heterosexual men) rated perceived advertisement effectiveness and relevance lower after viewing advertisements featuring flavors (vs no flavors; all p<0.001). Sexual minoritized men and sexual minoritized women rated perceived advertisement relevance lower after viewing advertisements featuring humans (all p<0.001) or fruit (all p<0.001). Heterosexual women, sexual minoritized men, and sexual minoritized women reported lower product use intention after viewing advertisements featuring an e-liquid bottle (vs no e-liquid bottle; all p<0.05). CONCLUSIONS Sexual minoritized women and men reported lower e-cigarette advertisement appeal and product use intentions than heterosexual men. More evidence is needed to understand advertisement perceptions and product appeal in this group to inform e-cigarette advertising regulations and anti-tobacco messaging campaigns that aim to reduce tobacco-related health inequities. [ABSTRACT FROM AUTHOR]

Background: The majority of gun violence in the United States does not result in physical injury and therefore cannot be completely measured using hospital data. To measure the full scope of gun violence, the nation's crime reporting systems that collect police reports of crimes committed with a firearm are vital. However, crime data reporting conventions may underestimate gun violence in the U.S. This paper compares crime data sources to assess underestimation of gun violence. Findings: The Federal Bureau of Investigation's Summary Reporting System (SRS) and National Incident Based Reporting System (NIBRS) measures of gun violence were compared in 2019 for states comprehensively reporting data to both systems. Gun violence is underestimated in the SRS compared to NIBRS. Within the sample, 18.8% more aggravated assaults with a firearm are recorded and 2.1% more robberies with a firearm are recorded in NIBRS. The proportion of assaults and robberies committed with a firearm measured in both sources did not differ. If the additional gun violence events recorded in the NIBRS sample are consistent with national crime reporting, the number of additional gun violence events per year captured using NIBRS totals approximately 65,071 additional events, or an additional 178 gun violence events per day. Of the additional gun violence events, approximately 31% are due to omitted crime categories, with the remaining variation driven mostly by aggravated assaults with a firearm. Conclusions: Police data are important data sources for estimating the full scope of gun violence. Comparisons between police data sources suggest that the proportion of crimes committed with a firearm is unchanged. Due to crime reporting conventions, however, the number of gun violence events may be substantially understated. Despite advantages in measuring gun violence, agency participation in NIBRS is alarmingly low and jeopardizes accurate and reliable national crime data. [ABSTRACT FROM AUTHOR]

Epidemic diseases can be extremely dangerous with its hazarding influences. They may have negative effects on economies, businesses, environment, humans, and workforce. In this paper, some of the factors that are interrelated with COVID-19 pandemic have been examined using data mining methodologies and approaches. As a result of the analysis some rules and insights have been discovered and performances of the data mining algorithms have been evaluated. According to the analysis results, JRip algorithmic technique had the most correct classification rate and the lowest root mean squared error (RMSE). Considering classification rate and RMSE measure, JRip can be considered as an effective method in understanding factors that are related with corona virus caused deaths. [ABSTRACT FROM AUTHOR]

In the Eastern Snake Plain of Idaho, increasing rates of groundwater extraction for irrigation have corresponded with the adoption of more efficient irrigation technologies; higher use and lower incidental recharge have led to increasing groundwater scarcity. This paper assesses farmer vulnerability to a water resource policy that responds to that scarcity by reducing availability of groundwater for irrigation by 4–20%. Using results from a household survey of impacted farmers, we examine vulnerability in two stages, contributing to theorization of farmer vulnerability in a changing climate as well as producing important regional policy insights. The first stage, multimodel selection and inference, analyzes the primary predictors of two forms of vulnerability to groundwater scarcity among this population of farmers. The second stage, a segmentation analysis, highlights policy-relevant variation in adaptive capacity and in vulnerability predictors across the population. Individual-level results indicate that key indicators of vulnerability include several dimensions of adaptive capacity and sensitivity. At the population level, we find that reductions in sensitivity may play an important role in reducing farmer vulnerability. Accelerating global environmental change will require agriculture in arid and semi-arid regions to adapt to shifts in water availability. As water resources shift, institutional contexts and policy landscapes will shift in parallel, as seen with the reduction in groundwater availability in our case study. These institutional shifts may change the face of adaptation and farmer vulnerability in unexpected ways. Our results indicate that such institutional shifts could lean on efforts to enhance farmer adaptive capacity or reduce farmer sensitivity as mechanisms for reducing farmer vulnerability to adaptation policy changes. [ABSTRACT FROM AUTHOR]

Accessible Summary: What is already known about this topic?: Individuals with severe mental illness (SMI) have elevated risks for physical health problems and low screening rates.No previous studies have compared the physical health promotion needs of people with SMI using the same screening tool across different international settings. What this paper adds to existing knowledge?: It appears feasible to use the HIP to profile and compare physical health‐related risks in people with SMI across different international settings.The HIP tool identified significant differences in areas of risk across the four countries. What are the implications for practice?: The HIP could be used to identify unique clusters of health promotion needs in different countries.Use of HIP health checks may support implementation of individualized interventions. Introduction: To date, no studies have contrasted physical health profiles of people with severe mental illness (SMI) in different countries. Aim: To evaluate feasibility of using the Health Improvement Profile (HIP) to compare and contrast physical health and health behaviours of people with SMI from four countries. Method: An observational feasibility study using secondary analysis of pooled health state and lifestyle data. Physical health checks using modified versions of HIP were administered in four countries. Results: Findings suggest feasibility of HIP screening to profile and compare physical health and health behaviours of people with SMI across international settings. High overall numbers of risk items (red flags) were identified in all but the Thailand sample. Despite some commonalities, there were important differences in health profiles across countries. Discussion: This is the first study to demonstrate feasibility of the HIP to compare health risks in individuals with SMI across countries. Future multi‐national HIP studies should recruit a fully powered stratified random sample of people with SMI that is representative of each setting. Implications for practice: It appears feasible to utilize the HIP to identify specific areas of health risk in different countries, which may help to better focus nursing interventions and use of resources. [ABSTRACT FROM AUTHOR]

This paper empirically examines how the opening of K--12 schools is associated with the spread of COVID-19 using county-level panel data in the United States. As preliminary evidence, our event-study analysis indicates that cases and deaths in counties with in-person or hybrid opening relative to those with remote opening substantially increased after the school opening date, especially for counties without any mask mandate for staff. Our main analysis uses a dynamic panel data model for case and death growth rates, where we control for dynamically evolving mitigation policies, past infection levels, and additive countylevel and state-week "fixed" effects. This analysis shows that an increase in visits to both K--12 schools and colleges is associated with a subsequent increase in case and death growth rates. The estimates indicate that fully opening K--12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the association of K--12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These findings support policies that promote masking and other precautionary measures at schools and giving vaccine priority to education workers. [ABSTRACT FROM AUTHOR]

The response process of problem‐solving items contains rich information about respondents' behaviours and cognitive process in the digital tasks, while the information extraction is a big challenge. The aim of the study is to use a data‐driven approach to explore the latent states and state transitions underlying problem‐solving process to reflect test‐takers' behavioural patterns, and to investigate how these states and state transitions could be associated with test‐takers' performance. We employed the Hidden Markov Modelling approach to identify test takers' hidden states during the problem‐solving process and compared the frequency of states and/or state transitions between different performance groups. We conducted comparable studies in two problem‐solving items with a focus on the US sample that was collected in PIAAC 2012, and examined the correlation between those frequencies from two items. Latent states and transitions between them underlying the problem‐solving process were identified and found significantly different by performance groups. The groups with correct responses in both items were found more engaged in tasks and more often to use efficient tools to solve problems, while the group with incorrect responses was found more likely to use shorter action sequences and exhibit hesitative behaviours. Consistent behavioural patterns were identified across items. This study demonstrates the value of data‐driven based HMM approach to better understand respondents' behavioural patterns and cognitive transmissions underneath the observable action sequences in complex problem‐solving tasks. Lay Description: What is already known about this topic?: Process data of interactive problem‐solving tasks contains rich information about test‐takers.To extract underlying information from process data is a big challenge. ​ What this paper adds?: The hidden Markov model helps identify latent states underlying problem‐solving process.Different performance groups displayed different behaviour characteristics.A consistent behavioural pattern was observed across problem‐solving items. ​ Implications for practitioners: The use of HMM holds promise in better visualize and understand behaviour patterns in response process.HMM is potential in understanding cognitive transmissions underneath the observable action sequences. ​ [ABSTRACT FROM AUTHOR]

While record linkage can expand analyses performable from survey microdata, it also incurs greater risk of privacy-encroaching disclosure. One way to mitigate this risk is to replace some of the information added through linkage with synthetic data elements. This paper describes a case study using the National Hospital Care Survey (NHCS), which collects patient records under a pledge of protecting patient privacy from a sample of U.S. hospitals for statistical analysis purposes. The NHCS data were linked to the National Death Index (NDI) to enhance the survey with mortality information. The added information from NDI linkage enables survival analyses related to hospitalization, but as the death information includes dates of death and detailed causes of death, having it joined with the patient records increases the risk of patient re-identification (albeit only for deceased persons). For this reason, an approach was tested to develop synthetic data that uses models from survival analysis to replace vital status and actual dates-of-death with synthetic values and uses classification tree analysis to replace actual causes of death with synthesized causes of death. The degree to which analyses performed on the synthetic data replicate results from analysis on the actual data is measured by comparing survival analysis parameter estimates from both data files. Because synthetic data only have value to the degree that they can be used to produce statistical estimates that are like those based on the actual data, this evaluation is an essential first step in assessing the potential utility of synthetic mortality data. [ABSTRACT FROM AUTHOR]