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Combining existing datasets to investigate key questions in developmental cognitive neuroscience brings exciting opportunities and unique challenges. However, many data pooling methods require identical or harmonized methodologies that are often not feasible. We propose Integrative Data Analysis (IDA) as a promising framework to advance developmental cognitive neuroscience with secondary data analysis. IDA serves to test hypotheses by combining data of the same construct from commensurate (but not identical) measures. To overcome idiosyncrasies of neuroimaging data, IDA explicitly evaluates if measures across studies assess the same construct. Moreover, IDA allows investigators to examine meaningful individual variability by de-confounding source-specific differences. To demonstrate IDAs potential, we explain foundational concepts, outline necessary steps, and apply IDA to volumetric measures of hippocampal subfields from 443 4- to 17-year-olds across three independent studies. We identified commensurate measures of Cornu Ammonis (CA) 1, dentate gyrus (DG)/CA3, and Subiculum (Sub). Model testing supported use of IDA to create IDA factor scores. We found age-related differences in DG/CA3, not but CA1 and Sub volume in the integrated dataset. By successfully demonstrating IDA, our hope is that future innovations come from the combination of existing neuroimaging data to create representative integrated samples when testing critical developmental questions.

Background: Health data sharing is important for monitoring diseases, policy and practice, and planning health services. If health data are used for secondary purposes, information needs to be provided to assist in reuse. Objectives: To review government health information asset websites to ascertain the extent of readily available, explanatory documentation for researcher sharing and reuse of these data. Method: Documentary analysis was undertaken on selected Victorian Government health information assets' websites in Australia. Data were obtained on nine information-categories: data custodian; data context; data dictionary; quality controls; data quality; limitations; access process; privacy/confidentiality/security and research requests/outputs. Information-categories were compared by dataset type (administrative or population-health) and by curating organisation (government or other agency). Descriptive statistics were used. Results: The majority of the 25 websites examined provided information on data custodian (96%) and data context (92%). Two-thirds reported access process (68%) and privacy/confidentiality/security information (64%). Compared with population-health websites, administrative dataset websites were more likely to provide access to a data dictionary (67% vs 50%) and information on quality controls (56% vs 44%), but less likely to provide information on the access process (56% vs 75%) and on research requests/outputs (0% vs 56%, p = 0.024). Compared with government-curated websites, other agency websites were more likely to provide information on research requests/outputs (80% vs 7%, p < 0.001). Conclusion: There is inconsistent explanatory documentation available for researchers for reuse of Victorian Government health datasets. Importantly, there is insufficient information on data quality or dataset limitations. Research-curated dataset websites are significantly more transparent in displaying research requests or outputs. [ABSTRACT FROM AUTHOR]

Paraeducators are critically important members of school communities, but there is little statewide research on the characteristics of paraeducators. We therefore use over 25 years of longitudinal data from Washington state to provide a descriptive portrait of the paraeducator workforce. Paraeducators are more racially and ethnically diverse than special education teachers, particularly in the last decade, and tend to be less experienced. Their full-time salaries are about half of the average for special education teachers. Finally, and perhaps most importantly, paraeducator attrition rates from the state's workforce have increased dramatically over time; for example, the paraeducator attrition rate after the 2021–2022 school year (23%) was over twice as high as the that in the 2008–2009 school year (8%). These findings have implications for how policymakers and school leaders should approach decision-making related to the paraeducator workforce, as well as how researchers might approach further research with this group of educators. [ABSTRACT FROM AUTHOR]

This secondary analysis of the National Youth Risk Behavior Survey (years 2015–2019) examines associations between school-based protective factors (i.e., safe school environments and academic achievement) and HIV risk behaviors among sexually experienced adolescent gay and bisexual men (n = 644), a population with the highest prevalence of undiagnosed HIV infections. Demographics included Hispanics/Latinos (25%, n = 158), Other race/ethnicity (14%, n = 88), and non-Hispanic Blacks/African Americans (13%, n = 81). Adjusted models showed that protective factors reduced odds for early sexual debut, multiple sexual partners, sex under the influence of drugs/alcohol, and condomless sex, with an additive effect demonstrated when two protective factors were present. Hispanics/Latinos had greater odds of reporting multiple sexual partners and HIV testing, indicating opportunities for school-based HIV prevention and further research. Our findings provide support for school-based programs that aim to improve social and structural determinants of health and ultimately reduce adolescent HIV burdens. [ABSTRACT FROM AUTHOR]

AbstractThe study of road traffic injuries (RTIs) is crucial for understanding the unique challenges faced by West Asia and North Africa (WANA) states. This research evaluates road safety practices in the WANA region, comparing them to global standards, and employs secondary data analysis from sources such as the Global Road Safety Status Report, Global Road Safety Facility, and the World Health Organization. The analysis examines epidemiological data, preventive measures like seatbelt and child-restraint use, and policy development, including national action plans, to estimate road traffic death rates per 10,000 vehicles and per 100,000 population. Data from 23 countries are analyzed, focusing on road traffic injury rates by user type, road safety laws, and global safety targets. Overall, WANA states account for 10.5% of global RTI fatalities, exceeding both world and European averages. Most pedestrian fatalities occur in Ethiopia (40.0%) and Afghanistan (34.0%). This indicates that low enforcement scores (averaging 5 out of 10) in most WANA countries contribute to the insufficient effectiveness of road safety laws in reducing injuries and deaths. Achieving the Sustainable Development Goal (SDG) to reduce global road traffic deaths by 50% by 2030 requires commitment and cooperation from governments, communities, and stakeholders in the WANA region. [ABSTRACT FROM AUTHOR]

Engineering study abroad programs are a novel setting for students to develop systems thinking, which has primarily been taught in formal learning environments. Through a situated learning perspective, we examined the impact of two engineering-focused study abroad experiences on developing students’ systems thinking skills. We conducted secondary data analysis to examine how first-year engineering students (n = 47) at a technical university in the United States (US) connect technical and contextual aspects of engineering in China and the UK/Ireland. The students on the China track drew connections more frequently (81% of excerpts) than those on the UK/Ireland track (49% of excerpts). Students interpreted these connections at the macrosystems level, microsystems level, personal level, and career level. Our study offers a theoretical contribution to the systems thinking framework by offering nuance to the connections students drew between contextual and technical engineering dimensions, while showing that systems thinking can be an important outcome for engineering study abroad programs. [ABSTRACT FROM AUTHOR]

Objectives The goal of this case report is to detail experiences and challenges experienced in the training of Primary Care residents in secondary analysis using All of Us Researcher Workbench. At our large, urban safety net hospital, Primary Care/Internal Medicine residents in their third year undergo a research intensive block, the Research Practicum, where they work as a team to conduct secondary data analysis on a dataset with faculty facilitation. In 2023, this research block focused on use of the All of Us Researcher Workbench for secondary data analysis. Materials and Methods Two groups of 5 residents underwent training to access the All of Us Researcher Workbench, and each group explored available data with a faculty facilitator and generated original research questions. Two blocks of residents successfully completed their research blocks and created original presentations on "social isolation and A1C" levels and "medical discrimination and diabetes management." Results Departmental faculty were satisfied with the depth of learning and data exploration. In focus groups, some residents noted that for those without interest in performing research, the activity felt extraneous to their career goals, while others were glad for the opportunity to publish. In both blocks, residents highlighted dissatisfaction with the degree to which the All of Us Researcher Workbench was representative of patients they encounter in a large safety net hospital. Discussion Using the All of Us Researcher Workbench provided residents with an opportunity to explore novel questions in a massive data source. Many residents however noted that because the population described in the All of Us Researcher Workbench appeared to be more highly educated and less racially diverse than patients they encounter in their practice, research may be hard to generalize in a community health context. Additionally, given that the data required knowledge of 1 of 2 code-based data analysis languages (R or Python) and work within an idiosyncratic coding environment, residents were heavily reliant on a faculty facilitator to assist with analysis. Conclusion Using the All of Us Researcher Workbench for research training allowed residents to explore novel questions and gain first-hand exposure to opportunities and challenges in secondary data analysis. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to develop a fall prediction model for community-dwelling older adults using machine learning. Methods: The present study was conducted with a secondary data analysis that used data from the 2020 national survey of older Koreans. Among 10,097 participants, data 177 were excluded due to incompleteness and 9,920 were included in the final analysis. Because of data imbalance, upsampling was performed to increase the number of individuals who fell. Forty-five independent variables for fall prediction were selected based on the fall risk factors from previous studies and univariate statistical analysis. The data were split into training and testing sets at an 80:20 ratio. Three machine learning algorithms-logistic regression, random forest, and artificial neural network-were used to develop a fall prediction model. Results: The random forest model outperformed the others, with an area under the curve of .91, accuracy of .94, precision of .94, recall of .74, and F1 score of .83. An analysis of feature importance revealed that satisfaction with health condition, visual difficulty, instrumental activities of daily living, performance of 400m walk, and cognitive ability were the top five features for fall prediction. Conclusion: The fall prediction model developed using machine learning demonstrated high model performance, implying its suitability for use as a primary screening tool for fall risk. Subjective satisfaction with one’s health should be considered as an important factor in predicting falls in community-dwelling older adults. It is necessary for community health nurses to reinforce positive health awareness by continuous disease management and physical function improvement for older adults to prevent falls. [ABSTRACT FROM AUTHOR]

Introduction Providing effective treatment for debilitating chronic pain is a challenge among many populations including military service members. Cognitive behavioral therapy for chronic pain (CBT-CP) is a leading psychological pain treatment. Pain catastrophizing is a pivotal mediator of pain-related outcomes. The purpose of this study was (1) to identify patient subgroups who differ in response to CBT-CP and (2) to explore the characteristics that define these patient subgroups. The overall goal was to obtain a better understanding of factors that may influence response to CBT-CP. Materials and Methods This study was a secondary analysis of data from a clinical trial of 149 U.S. active duty service members with chronic pain. Participants underwent group-based CBT-CP for 6 weeks and completed pre- and posttreatment assessments. Finite mixture models were employed to identify subgroups in treatment response, with pain impact score as the primary outcome measure. Results We identified two classes of nearly equal size with distinct pain impact responses. One class reported improved pain impact scores following CBT-CP. This improvement was significantly associated with lower (better) baseline depression scores and greater improvement in posttreatment pain catastrophizing. In contrast, the other class reported slightly worse mean pain impact scores following CBT-CP treatment; this response was not related to baseline depression or change in pain catastrophizing. Conclusions Our findings demonstrate that a sizable proportion of individuals with chronic pain may not respond to group-based CBT-CP and may require a more individualized treatment approach. [ABSTRACT FROM AUTHOR]

Background: Evidence describing the types and annual costs of biological treatments for psoriasis in Latin America is scarce. This study aimed to estimate the frequency of use and costs of biologic therapy for psoriasis in Colombia in 2019. Methods: This secondary data analysis uses the International Classification of Diseases terms associated with psoriasis, excluding those related to psoriatic arthritis, based on data from the registry of the Colombian Ministry of Health. We estimated the prevalence of psoriasis per 100,000 inhabitants; then, we retrieved the frequency of use of biologic therapy in patients with psoriasis and estimated the cost per year of each and overall therapies in 2019 in US dollars (USD). Results: There were 100,823 patients with psoriasis in Colombia in 2019, which amounts to a prevalence of 0.2% in the general population. Of those patients, 4.9% received biologic therapy, most frequently males (60%). The most commonly used biological therapies for psoriasis in Colombia in 2019 were ustekinumab (35.2%), with an annual cost per patient of $12,880 USD; adalimumab (26%), with a yearly cost per patient of $7130 USD; and secukinumab (19.8%), with an annual cost per patient of $6825 USD. Conclusion: This is the first study to describe the use and cost of biological therapy for psoriasis in Colombia. It provides valuable cost‐awareness information for the Colombian health system. [ABSTRACT FROM AUTHOR]

Copyright of Zentralblatt fuer Arbeitsmedizin, Arbeitsschutz und Ergonomie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses the SHARE framework for secondary qualitative data analysis in engineering education research. The authors advocate for SDA due to its benefits, such as reduced time to publication and increased data transparency. They emphasize the importance of ethical considerations, especially when working with data from marginalized populations. The article provides practical guidance for researchers conducting SDA and addresses frequently asked questions about the legitimacy, practicality, and ethics of SDA. The authors envision the SHARE principles as a dynamic tool to reshape the future of engineering education research through collaborative data analysis. [Extracted from the article]

Systematic reviews have witnessed significant growth across many fields, including education. In this article, we outline the background of this growth, highlight the tendency to focus on methodological considerations, and propose a framework to support education researchers in preparing systematic reviews with broad impact. We draw on our experience working with education stakeholders in Singapore and on international scholarship to propose a framework that supports education researchers in clarifying and specifying their aims and audiences and crafting syntheses of appropriate types. Our aim is that this framework, which includes examples illustrating four categories of reviews, acts as a reflective tool which researchers can use to maximize the utility, value, and potential impact of education research. [ABSTRACT FROM AUTHOR]

The circular economy (CE) has recently emerged as an innovative business model for firms to transform corporate social responsibility (CSR) into actions. Existing research tends to examine the CSR advantages of short-term CE practice adoptions, remaining silent on the benefits and drivers of their long-term implementation. This study fills the gaps by investigating the impact of the long-term adoption of eco-design (ECO) and reverse logistic (RL) practices on firm CSR performance and exploring the moderating roles of four sense-giving activities. Using a balanced panel dataset of 132 manufacturing public firms in China and a fixed-effects model, we find that: 1) the frequency of ECO and RL practice adoptions significantly improves firm CSR performance; 2) goal setting for CE performance, CE education and training, and employee feedback on CE practices positively moderate the RL-CSR relationship, while employee feedback on CE practices positively moderates the ECO-CSR relationship. This study has significant implications for both research and practice in the increasingly important domains of CE and CSR management. [ABSTRACT FROM AUTHOR]

BACKGROUND: Vulnerable older adults living with Alzheimers disease or Alzheimers disease and related dementia (AD/ADRD) and chronic pain generally receive fewer pain medications than individuals without AD/ADRD, especially in nursing homes. Little is known about pain management in older adults with AD/ADRD in the community. The aim of the study was to examine opioid prescribing patterns in individuals with chronic pain by levels of cognitive ability in ambulatory care. METHODS: We used the Medical Expenditure Panel Survey (MEPS), years 2002-2017, and identified three levels of cognitive impairment: no cognitive impairment (NCI), individuals reporting cognitive impairment (CI) without an AD/ADRD diagnosis, and individuals with a diagnosis of AD/ADRD. We examined any receipt of an opioid prescription and the number of opioid prescriptions using a logistic and negative binomial regression adjusting for sociodemographic and health characteristics and stratifying by three types of chronic pain (any chronic pain, severe chronic pain, and chronic pain identified through ICD 9/10 chronic pain diagnoses). RESULTS: Among people with any chronic pain, adjusted odds of receiving an opioid for people with CI (OR 1.41, 95% confidence interval 1.31-1.52) and AD/ADRD (OR 1.23, 95% confidence interval 1.04-1.45) were higher compared to NCI. Among people with chronic pain ICD 9/10 conditions, the odds of receiving an opioid were also higher for those with CI (OR 1.43, 95% confidence interval 1.34-1.56) and AD/ADRD (OR 1.48, 95% confidence interval 1.23-1.78) compared to NCI. Among those with severe chronic pain, people with CI were more likely to receive an opioid (OR 1.17, 95% confidence interval 1.07-1.27) relative to NCI (OR 0.89, 95% confidence interval 0.75-1.06). People with AD/ADRD experiencing severe chronic pain were not more likely to receive an opioid compared to the NCI group. Adjusted predicted counts of opioid prescriptions showed more opioids in CI and AD/ADRD in all chronic pain cohorts, with the largest numbers of opioid prescriptions in the severe chronic pain and ICD 9/10 diagnoses groups. CONCLUSIONS: The results suggest increased opioid use in people living with CI and AD/ADRD in the ambulatory care setting and potentially indicate that these individuals either require more analgesics or that opioids may be overprescribed. Further research is needed to examine pain management in this vulnerable population.

This article presents methods for using extant data to improve the properties of estimators of the standardized mean difference (SMD) effect size. Because samples recruited into education research studies are often more homogeneous than the populations of policy interest, the variation in educational outcomes can be smaller in these samples than is reflective of the true variation in the population. This affects effect size estimation since the sample standard deviation is used in the denominator of the SMD. We propose leveraging extant data on sample variance estimates from multiple studies, made available via clearinghouse databases such as the What Works Clearinghouse, to standardize a mean difference. This allows effect sizes to be benchmarked across a common and broad population, thus enabling better comparability across studies and interventions. We derive the new estimators of the population variance and the corresponding SMD, which pool sample variances from multiple studies using both an analysis of variance and a meta-analytic framework. We demonstrate the properties of these estimators via analytic and simulation results and offer recommendations for when these estimators are appropriate in practice. [ABSTRACT FROM AUTHOR]

Bu çalışmada, 93 ülkede 2500 üniversiteden elde edilen verileri birçok kritere göre sıralayan Times Higher Education World University Rankings (THE) tarafından yapılan değerlendirme sonuçlarının Türkiye’de faaliyet gösteren üniversiteler odağında analiz edilmesi amaçlanmıştır. Bu kapsamda THE’nin sıralamasında eğitim bilimleri alanında dünya genelindeki ilk 10 üniversite ile Türkiye’de faaliyet gösteren üniversitelerin aktif öğrenci sayılarının, akademik personel başına düşen öğrenci sayılarının, uluslararası öğrenci oranlarının, kadın/erkek öğrenci oranlarının ve bu değişkenler bağlamında genel sıralamalarının son beş yıl içerisindeki değişiminin belirlenmesi amaçlanmıştır. Bunun yanında ilgili değişkenler odağında Türkiye’deki üniversitelerin farklılaşma düzeylerinin belirlenmesi de amaçlanmıştır. Çalışmada ikincil veri analizi yönteminden yararlanılmıştır. Bu çalışmanın verileri THE internet sayfasından edinilmiştir. Araştırma sorularının çözümlenmesinde betimsel istatistiksel yöntemler ile parametrik olmayan fark testlerinden yararlanılmıştır. Çalışma sonucunda eğitim bilimleri alanında Türkiye’de değerlendirmeye alınan üniversiteler ile Dünya genelindeki ilk 10 üniversitenin aktif öğrenci sayılarının, akademik personel başına düşen öğrenci sayılarının ve uluslararası öğrenci oranlarının istatistiksel açıdan farklılaştığı sonucuna ulaşılmıştır. Ancak kadın/erkek öğrenci oranları açısından istatistiksel açıdan bir fark olmadığı sonucuna ulaşılmıştır.

Qualitative research is important to advance health equity as it offers nuanced insights into structural determinants of health inequities, amplifies the voices of communities directly affected by health inequities, and informs community-based interventions. The scale and frequency of public health crises have accelerated in recent years (e.g., pandemic, environmental disasters, climate change). The field of public health research and practice would benefit from timely and time-sensitive qualitative inquiries for which a practical approach to qualitative data analysis (QDA) is needed. One useful QDA approach stemming from sociology is flexible coding. We discuss our practical experience with a team-based approach using flexible coding for qualitative data analysis in public health, illustrating how this process can be applied to address multiple research questions simultaneously or asynchronously. We share lessons from this case study, while acknowledging that flexible coding has broader applicability across disciplines. Flexible coding provides an approachable step-by-step process that enables collaboration among coders of varying levels of experience to analyze large datasets. It also serves as a valuable training tool for novice coders, something urgently needed in public health. The structuring enabled through flexible coding allows for prioritizing urgent research questions, while preparing large datasets to be revisited many times, facilitating secondary analysis. We further discuss the benefit of flexible coding for increasing the reliability of results through active engagement with the data and the production of multiple analytical outputs. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to measure trajectories of craving for methamphetamine during the course of pharmacotherapy trials for methamphetamine use disorder. Design, setting and participants: Craving trajectories were identified using Group‐Based Trajectory Modeling. The association of craving trajectories with drug use trajectories was examined using a dual trajectory model. Association of craving trajectories with other health and social outcomes was also examined. The study used pooled data from five randomized controlled pharmacotherapy trials for methamphetamine use disorder. A total of 866 adults with methamphetamine use disorder participated in randomized controlled pharmacotherapy trials. Measurement: Craving was assessed weekly using the Brief Substance Craving Scale. Drug use was assessed using urine toxicology. Alcohol‐ and drug‐related problems, as well as psychiatric, medical, legal, employment and relationship problems, were measured using the Addiction Severity Index. Findings: A three‐trajectory model with high, medium and low craving trajectories was selected as the most parsimonious model. Craving trajectories were associated with methamphetamine use trajectories in the course of trial; 88.4% of those in the high craving trajectory group had a consistently high frequency of methamphetamine use compared with 18.7% of those in the low craving group. High craving was also associated with less improvement in most other outcomes and higher rate of dropout from treatment. In turn, low craving was associated with a rapidly decreasing frequency of methamphetamine use, greater improvement in most other outcomes and a lower rate of dropout. Participants on modafinil daily and ondansetron 1 mg twice daily were less likely to be in the high craving group compared with those on placebo. Conclusions: Trajectories of methamphetamine craving in the course of clinical trials for methamphetamine use disorder appear to be both highly variable and strongly associated with greater frequency of drug use, other drug‐related outcomes and dropout from trials. Two medications, modafinil daily and ondansetron at a dose of 1 mg two times daily, appear to be associated with greater reduction in craving in the course of treatment compared with placebo. A decrease in methamphetamine craving shows promise as an early indicator of recovery from methamphetamine use disorder. [ABSTRACT FROM AUTHOR]

The intellectually gifted have been found to have higher levels of many prosocial dispositions, but there is limited evidence of increased prosocial behavior. The present research used existing and original datasets to examine relations between intellectual giftedness and prosocial behavior and dispositions. In Study 1, those identified as intellectually gifted engaged in more political and helping behaviors than those not identified as intellectually gifted. In Study 2, gifted-identified undergraduate students reported more prosocial behavior (e.g., volunteering and giving) than nonidentified students; however, there were no clear differences in dispositions (e.g., personality and motivation) between gifted-identified and nonidentified students. Implications of these consistent linkages between intellectual giftedness and engaging in prosocial behavior for future research and practical applications are discussed. [ABSTRACT FROM AUTHOR]

We present data from the Schools and Staffing Survey and the National Teacher and Principal Survey to document the prevalence of instructional coaching programs (ICPs) and consider how ICPs are distributed by school level, urbanicity, new teachers in a school, student enrollment, school poverty levels, student achievement levels, and state. We show that ICPs are most common in elementary schools, schools located in cities, schools with larger proportions of new teachers, larger schools, schools enrolling larger fractions of economically disadvantaged students, and schools with lower student achievement levels. Additionally, more affluent and higher achieving schools experienced the sharpest increase in ICPs over time. [ABSTRACT FROM AUTHOR]

Adolescents' physical activity (PA) and sports participation declined due to the COVID-19 pandemic. This study aimed to determine the critical socio-ecological factors for PA and sports participation using a machine learning approach. We did a cross-sectional secondary data analysis utilising the 2021 National Survey of Children's Health (NSCH) dataset (N=16,166; 49.0% female). We applied an interpretable machine learning approach (e.g. decision tree-based models) that examined the critical factors associated with PA and sports participation. The factors related to the intrapersonal, interpersonal, organisational, and community levels of the socio-ecological model. Out of the 25 factors examined, our findings unveiled the 11 critical factors associated with PA and the 10 critical factors associated with sports participation. Factors at the intrapersonal levels (e.g. age, screen time, and race) held greater importance to PA than those at the other three levels. While interpersonal factors (e.g. parent participation in children's events/activities, family's highest educational level, and family income level) were most important for sports participation. This study identified that the common critical factors of physical activity and sports participation during the COVID-19 pandemic mainly relied on intrapersonal and interpersonal levels. Unique factors were discussed. Summary: In this study, we identified 11 critical factors for PA, with the top five being age, neighbourhood amenities, screen time, missed school days, and family income level. Additionally, we identified 10 critical factors for sports participation, with the top five factors being parent participation in a child's events/activities, family's highest educational level, family income level, screen time, and school engagement. These findings emphasise the shared significance of intrapersonal and interpersonal factors as common determinants of both PA and sports participation. Notably, PA appears to be primarily influenced by intrapersonal factors (e.g. age, screen time, and race), reflecting its more internally driven nature. In contrast, sports participation appears to be more externally driven, primarily shaped by interpersonal factors (e.g. parent participation in the child's events/activities, family's highest educational level, and family income level). This distinction underscores the need for educators and policymakers to carefully consider these common and unique factors when devising promotion strategies during the COVID-19 pandemic. By recognising these distinctions, interventions can be better tailored to encourage both PA and sports participation among adolescents. [ABSTRACT FROM AUTHOR]

Background: Hypertensive patients with high-risk comorbidities require medications for each condition, leading to greater burden. The number of chronic conditions can affect patients' concurrent medication adherence. Objective: We aimed to compare the characteristics of groups based on their concurrent medication adherence and investigate the association between the number of high-risk comorbidities and concurrent medication adherence for patients with hypertension and high-risk comorbidities. Methods: A secondary data analysis was performed with the 2018 Korea Health Panel Survey, including 2230 patients with hypertension and at least 1 high-risk comorbidity who were prescribed medications for at least 2 conditions. Using medication adherence for each condition, we identified 3 concurrent medication adherence groups: adherent, suboptimal, and nonadherent groups. Multinominal logistic regression was used to determine the association between the number of high-risk comorbidities and the concurrent medication adherence groups. Results: Adherent, suboptimal, and nonadherent groups included 85%, 11%, and 4% of the patients, respectively. Whereas having more high-risk comorbidities was associated with belonging to the suboptimal group compared with the adherent group (adjusted odds ratio, 1.46), having fewer high-risk comorbidities was associated with belonging to the nonadherent group compared with the adherent group (adjusted odds ratio, 0.52). Conclusions: We identified 3 groups based on their concurrent medication adherence. Our results indicated that the relationship of the number of high-risk comorbidities with the concurrent medication adherence group was inconsistent. [ABSTRACT FROM AUTHOR]

As part of a research project on the lived and everyday temporal experiences of British people in the Covid-19 pandemic, a Mass Observation directive was commissioned that asked volunteers about their changing rhythms, feelings, and imagined futures. The responses were rich and raw. Some of these reflections, however, expressed a risk of harm that raised ethical issues that were not anticipated beforehand. These issues were complicated by the interstitial character of the data, being not primary and not quite secondary. This Sociology in Action paper reflects on one diary that expressed risk of harm to think through the slipperiness of the data as well as the ethical responsibility researchers have towards the well-being of participants and that of their own. I suggest a proactive ethical framework for such interstitial data that includes an ethics of care towards the participants and stimulates ethical reflexivity that prepares the researcher for potential emotional ties and investments. [ABSTRACT FROM AUTHOR]

Copyright of Gefaesschirurgie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of University Research / Üniversite Araştırmaları Dergisi is the property of Journal of University Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Children and young people's mental health services have been under increasing pressure following COVID-19. Understanding, for which channels help is sought from, will highlight services needing support. This study aims to explore the professional services that parents of children, and young people get help from when they have a concern for the child's/their mental health. Secondary analysis of data is taken from Mental Health of Children and Young People in England Survey, 2017. 7608 reports of mental health-related contact with professional services from parents of 5–16 year-olds and self-reports from young people aged 17–19 were available. Service contact was reported by Diagnostic and Statistical Manual of Mental Disorders (DSM-V) diagnosis, age, gender and ethnicity. Less than two-thirds of children and young people with a DSM-V diagnosis (63.5% (95% CI 58.6–68.1) aged 5–10, and 64.0% (95% CI 59.4–68.4) aged 11–16) reported contact with any professional services. The figure was lower for those aged 17–19; 50.1% (95% CI 42.8–58.2), p = 0.005. Children and young people aged 5–16 from Black (11.7%; 95% CI 2.4–41.4), Asian (55.1%; 95% CI 34.7–73.9) and Mixed (46.0%; 95% CI 32.4–60.3) ethnic groups reported less contact with professional services compared to those from the White group (66.9%; 95% CI 63.5–70.2). Patterns of service access during the three main educational stages aid with understanding service need during childhood. These lower levels of reported service access for young people aged 17–19 with a DSM-V diagnosis and those in ethnic minority groups demand further investigation. [ABSTRACT FROM AUTHOR]

Despite reliable evidence of adverse drug effects, the substantially increased prescription rates of proton pump inhibitors (PPIs) remain at a high level. This study analyzed the appropriateness of PPI prescriptions among residents of nursing homes in three regions of Germany. Baseline data of a cluster-randomized controlled trial were used to determine the prevalence of PPI prescriptions, the validity of indications, and the adequacy of the prescribed dosages according to 1. their drug approvals and 2. valid recommendation guidelines. Regression analyses were conducted to assess associated factors. A total of 437 residents in 37 nursing homes were included (mean age 83 ± 9.2 years, 72% women). The PPI prescription prevalence was 44% (n = 193). In 52/193 (27%) there was no adequate indication, and in 54 (39%) of 138 indicated PPI prescriptions it was overdosed. Yet, in only less than one-third (28%) of "adequate" prescriptions, the indication was according to the PPI approvals, whereas the majority (72%) were off-label indications in line with valid guideline recommendations. Non-indicated PPI prescription was associated with the total number of prescribed drugs (OR 1.32; 95% CI 1.18–1.62; p = 0.013). There were no associations with age, level of care dependency, cognitive impairment, prescription of psychotropic drugs, number of chronic diseases, number of physicians' consultations, or study region. To conclude, in 55%, the high prescription prevalence among residents was either not indicated or overdosed. In total, only 20% (39/193) of cases of PPI use complied with the approved indications. There is a need for quality control of 1. PPI administration in German nursing homes, and 2. of guideline recommendations expanding the off-label PPI use by 72% within the indication scale, predominantly from wide prescription for low-dose ASA. [ABSTRACT FROM AUTHOR]

Students with mental health needs, behavioral support needs, and/or emotional disturbance can engage in internalizing behaviors, externalizing behaviors, or both. Preservice and induction phase elementary general education teachers are reported to have limited education in providing evidence-based behavior management strategies, especially for students who engage in internalizing and/or externalizing behaviors. There is little understanding as to the differences in elementary general education teachers' knowledge, application, and self-efficacy in applying evidence-based behavior management strategies between preservice teachers, first-year teachers, second-year teachers, and third-year teachers. The purpose of this preliminary secondary data analysis was to examine differences in U.S. elementary general education teacher knowledge, application, and self-efficacy in evidence-based behavior management strategies from preservice to induction phase teaching. Results indicated third-year teachers had significantly less behavior management knowledge than preservice teachers. All other results were nonsignificant; however, there were practical differences when comparing the four groups on the knowledge and application measures. Implications for findings indicate the need for induction programs to focus on evidence-based behavior management strategies to support the development of behavior management for induction phase elementary education teachers as they progress through their first 3 years of teaching. [ABSTRACT FROM AUTHOR]

Background: Research on temporomandibular disorder (TMD) responsiveness is scarce and limited regarding patients' representativeness. Objective(s): This study aimed to estimate minimum clinically important difference (MCID) and substantial clinical benefit (SCB) among a large and diverse patient population regarding sex and age. Methods: In this study, 162 patients participated from five hospitals. MCID and SCB in pain, functional disability and quality of life were examined with anchor‐based methods. Patients' global impression of change was used as the anchor. Area under the curve (AUC) values were determined for testing accuracy. Changes from baseline and coefficient of variation by responsiveness status were calculated to explain the results of accuracy. Results: SCB was estimated to be 2.18 for the numeric rating scale (NRS) for pain (AUC: 0.80 [95% CI: 0.72–0.88]) in all patients and 2.50 in women (AUC: 0.81 [95% CI: 0.71–0.89]). The estimated SCB of NRS for discomfort (1.50) and Jaw Functional Limitation Scale for mastication (1.35) had wide CIs for AUCs. Likewise, the estimated MCIDs of NRS for pain (0.80) and NRS for discomfort (1.50) had wide CIs for AUCs. Among non‐responders who did not achieve the MCID of NRS for pain, the coefficient of variation was very high for all outcomes other than the NRS for pain. Conclusion: This study investigated the responsiveness of patients with TMD using a large and diverse patient sample. SCB in pain decrease can be used to assess the responsiveness of patients with TMD. Composite outcomes should be developed to estimate MCID. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to determine the level of cardiopulmonary resuscitation (CPR) training among Korean older adults in a community and the factors associated with CPR training. Methods: A total of 51,939 elders were selected and analyzed using the 2022 Community Health Survey. The collected data were analysed using the Rao-Scott test and logistic regression via the SAS 9.4 program. Results: A total of 7.3% of older adults received CPR training. Factors influencing CPR training were age (odds ratio [OR]=4.76, 95% confidence interval [CI]=2.55~8.90), level of education (OR=2.43, 95% CI=1.77~3.33), region (OR=1.16, 95% CI=1.05~1.27), working (OR=3.68, 95% CI=3.33~4.07), and subjective health status (OR=1.57, 95% CI=1.37~1.79). Conclusion: Based on the results of this study, there is a need to explore various ways to improve CPR training for community older adults who are vulnerable to emergency situations. [ABSTRACT FROM AUTHOR]

This brief analyzes 4-year graduation rates among students ever classified as English learners (ever-ELs) and those never classified as English learners (never-ELs) at the intersections of gender, race/ethnicity, and neighborhood income. We follow two cohorts of New York City students who entered ninth grade in 2013–2014 and 2014–2015 (N = 127,931). We find substantial variations in 4-year graduation among these subgroups, with differential predicted probabilities depending on the student's ever-EL status, race/ethnicity, and neighborhood income. These findings reveal important intersectional disparities in this diverse group of ELs—nuances that are lost when analyzing across a single social dimension and that push us to adopt an intersectional lens in quantitative research on ELs. [ABSTRACT FROM AUTHOR]

Inequity in education is a worldwide concern and there is a growing need to investigate educational achievement inequality in a nuanced and contextual manner. This study aims to elucidate the growing educational achievement inequality within Pakistan by addressing two key questions: What can be revealed about the influence of family socioeconomic condition and household characteristics on children's disparate educational achievement in Pakistan? And what role do private schools and paid tuition play in exacerbating disparity in learning outcomes? In this study, we applied the concept of Equity in Education, particularly the impartiality approach, to consider disadvantaged conditions among children. We have analyzed the Annual Status of Education Report (ASER) Pakistan household-based survey data (N = 247,978) conducted in 2021. Our analysis involved both descriptive and logistic regression techniques. Students' achievement in the local language, arithmetic, and English language served as a dependent variable, while household factors remained a predictable variable. The results revealed that family socioeconomic factors including parents' education and income, household facilities, and school types have a significant influence on children's learning achievement and contribute to educational inequality. This study provides further insights for researchers and policymakers to better understand and address educational inequality in its specific context. [ABSTRACT FROM AUTHOR]

Background: Frozen fruits and vegetables (FV) are convenient, cost-effective, reduce food waste, and can be just as nutritious as their fresh counterparts. Despite these numerous advantages, it is unclear which consumer segments are more likely to purchase frozen FV, especially compared with fresh, canned, or dried FV, which could help inform targeted nutrition education interventions. Objective: The objective of this study is to explore sociodemographic factors associated with increased or decreased odds of purchasing frozen, fresh, canned, and dried FV in a nationally representative sample. Methods: A secondary data analysis was conducted using publicly available data from the nationally representative 2021 United States Bureau of Labor Statistics Consumer Expenditure Diary Surveys, in which participants were instructed to record all household expenditures during a 2-wk timeframe. Chi-square analyses and unadjusted and adjusted logistic regressions were used to explore the associations between the included sociodemographic variables and FV purchasing. Results: Of the final sample (n = 6028), 230 purchased frozen fruits and 1163 purchased frozen vegetables during the study period. Households with higher income, higher educational attainment, and more children

Combining existing datasets to investigate key questions in developmental cognitive neuroscience brings exciting opportunities and unique challenges. However, many data pooling methods require identical or harmonized methodologies that are often not feasible. We propose Integrative Data Analysis (IDA) as a promising framework to advance developmental cognitive neuroscience with secondary data analysis. IDA serves to test hypotheses by combining data of the same construct from commensurate (but not identical) measures. To overcome idiosyncrasies of neuroimaging data, IDA explicitly evaluates if measures across studies assess the same construct. Moreover, IDA allows investigators to examine meaningful individual variability by de-confounding source-specific differences. To demonstrate IDA’s potential, we explain foundational concepts, outline necessary steps, and apply IDA to volumetric measures of hippocampal subfields from 443 4- to 17-year-olds across three independent studies. We identified commensurate measures of Cornu Ammonis (CA) 1, dentate gyrus (DG)/CA3, and Subiculum (Sub). Model testing supported use of IDA to create IDA factor scores. We found age-related differences in DG/CA3, not but CA1 and Sub volume in the integrated dataset. By successfully demonstrating IDA, our hope is that future innovations come from the combination of existing neuroimaging data to create representative integrated samples when testing critical developmental questions.

Abstract Background Insurance databases contain valuable information related to the use of dental services. This data is instrumental in decision-making processes, enhancing risk assessment, and predicting outcomes. The objective of this study was to identify patterns and factors influencing the utilization of dental services among complementary insured individuals, employing a data mining methodology. Methods A secondary data analysis was conducted using a dental insurance dataset from Iran in 2022. The Cross-Industry Standard Process for Data Mining (CRISP-DM) was employed as a data mining approach for knowledge extraction from the database. The utilization of dental services was the outcome of interest, and independent variables were chosen based on the available information in the insurance dataset. Dental services were categorized into nine groups: diagnostic, preventive, periodontal, restorative, endodontic, prosthetic, implant, extraction/surgical, and orthodontic procedures. The independent variables included age, gender, family size, insurance history, franchise, insurance limit, and policyholder. A multinomial logistic regression model was utilized to investigate the factors associated with dental care utilization. All analyses were conducted using RapidMiner Version 2020. Results The analysis encompassed a total of 654,418 records, corresponding to 118,268 insured individuals. Predominantly, restorative treatments were the most utilized services, accounting for approximately 38% of all services, followed by diagnostic (18.35%) and endodontic (13.3%) care. Individuals aged between 36 and 60 years had the highest rate of utilization for any dental services. Additionally, families comprising three to four members, individuals with a one-year insurance history, people contracted with a 20% franchise, individuals with a high insurance limit, and insured individuals with a small policyholder, exhibited the highest rate of service usage compared to their counterparts. The regression model revealed that all independent variables were significantly associated with the use of dental services. However, the patterns of association varied among different service categories. Conclusions Restorative treatments emerged as the most frequently used dental services among insured individuals, followed by diagnostic and endodontic procedures. The pattern of service utilization was influenced by the characteristics of the insured individuals and attributes related to their insurance.

Background Employee mental health and well-being (MH&WB) is critical to the productivity and success of organizations. Training line managers (LMs) in mental health plays an important role in protecting and enhancing employee well-being, but its relationship with other MH&WB practices is under-researched. Aims To determine whether organizations offering LM training in mental health differ in the adoption of workplace- (i.e. primary/prevention-focused) and worker-directed (including both secondary/resiliency-focused and tertiary/remedial-focused) interventions to those organizations not offering LM training and to explore changes in the proportions of activities offered over time. Methods Secondary analysis of enterprise data from computer-assisted telephone interview surveys. The analysis included data from organizations in England across 4 years (2020: n  = 1900; 2021: n  = 1551; 2022: n  = 1904; 2023: n  = 1902). Results Offering LM training in mental health was associated with organizations' uptake of primary-, secondary-, and tertiary-level MH&WB activities across all 4 years. The proportion of organizations offering primary-, secondary- and tertiary-level interventions increased over time. On average, tertiary-level activities were most adopted (2020: 80%; 2021: 81%; 2022: 84%; 2023: 84%), followed by primary-level activities (2020: 66%; 2021: 72%; 2022: 72%; 2023: 73%) and secondary-level activities (2020: 62%; 2021: 60%; 2022: 61%; 2023: 67%). Conclusions Offering LM training in mental health is associated with the adoption of other MH&WB practices by organizations. Suggesting that organizations that are committed to the mental health agenda are more likely to take a holistic approach (including both worker and workplace strategies) to promoting workforce mental health, rather than providing LM training in isolation. [ABSTRACT FROM AUTHOR]

This article is methodological in nature, addressing and discussing the challenges the research team encountered in constructing a new international well-being index called the World Love Index. This index represents the first quantitative operationalization of the concept of Social Love, which seeks to capture actions or social relationships characterized by excess and care for the benefit of individuals outside the primary circle, loved for their irreducibility. Starting with a discussion of the project's objective rooted in the Beyond GDP debate, the article first analyzes the theoretical definition of Social Love and its semantic dimensions for operationalization. It then focuses on the methodological construction of the index through secondary data analysis, particularly examining the transition from the first wave to the second wave. Through the first wave of the WLI, this concept was systematically investigated on a transnational level. However, the first wave faced criticism for its weaknesses due to decisions made during the index's construction. This paper, from a purely methodological perspective, demonstrates how the second wave of the WLI aims to address these challenges and turn them into strengths. [ABSTRACT FROM AUTHOR]

Research either focused on self‐interest or left–right ideology to explain support for demanding active labour market policies (ALMPs). This article focuses instead on how attitudes towards these policies are rooted in the underlying policy paradigm. We link attitudes towards ALMPs to two pillars of the activation paradigm: distributive justice and unemployment attributions. Structural equational modeling is employed on the Belgian National Election Study data of 2014 (N = 1901). Individuals supporting the principles of need and equity and who blame the unemployed are more in favour of demanding activation. These frameworks and hence the policy paradigm thus have substantial predictive power. [ABSTRACT FROM AUTHOR]

Introduction Tobacco use in women of reproductive age group (15–9 years) may contribute to poor maternal and child health outcomes. We estimated the prevalence of smokeless tobacco (ST), cigarette, and waterpipe use among these women in Pakistan and explored associations with socio-economic differences and birth weights after recent childbirths (past 2 years). Aims and Methods We used the Multiple Indicator Cluster Surveys datasets from three provinces in Pakistan. Prevalence was generated for current use of tobacco among women with recent childbirth (WWRC) and without recent childbirth (WWoRC). We further compared socio-economic status and birth weights between tobacco users and non-users. Results The prevalence of current ST use was 1.4% and 2.5%, and waterpipe smoking was 1.2% and 1.8%, in WWRC and WWoRC, respectively. ST use varied across Pakistan's provinces by 13 percentage points in WWRC and WWoRC while waterpipe smoking by 10 and 15 percentage points, respectively. The odds of using any form of tobacco were significantly lower with higher levels of education or wealth index. Compared to children born to mothers who did not use tobacco, the birth weight of children born to mothers who smoked waterpipe was on average 0.83 kg (95% CI −1.6 to −0.1) lower whereas it was 0.33 kg (95% CI −0.9 to 0.3) higher for ST users. Conclusions Tobacco use among women of reproductive age in Pakistan varied significantly based on province and tobacco type. Waterpipe smoking was associated with a reduction in birth weight. Raising awareness of the harms of tobacco use among women of reproductive age and targeting interventions in high-burden regions of Pakistan should be prioritized. Implications The prevalence of current smokeless tobacco use and waterpipe smoking varied significantly in Pakistan (~13 and ~15 percentage points, respectively) among women of reproductive age, and there seems to be little change in tobacco use behavior around pregnancy and early motherhood. The study highlights a need to better understand the prevalence of tobacco use in Pakistan, and further contextual research is warranted to understand the reasons for such high tobacco use in certain areas. This information highlights the need for improving current tobacco control interventions and policies, including measures that could help reduce its use and prevent its uptake. Furthermore, compared to children born to mothers who did not use any form of tobacco, we found a statistically significant difference (830 g) in birth weight for babies born to mothers who at the time of the interview smoked waterpipe and a non-statistically significant difference of about 330 g for children born to mothers who at the time of the interview used smokeless tobacco. In addition to our findings, some literature suggests the association of waterpipe smoking with low birth weight. A possible explanation could be the exposure to smoke that contains toxicants from the tobacco product itself in addition to the burning of charcoal, which is required when using waterpipe. Waterpipe smoking also results in high exposures to carbon monoxide and polycyclic aromatic hydrocarbons, which are known to be carcinogenic and teratogenic. In terms of smokeless tobacco use, further research is warranted to understand its impact on birth outcomes through longitudinal studies accounting for diverse products, its constituents and the amount of consumption. [ABSTRACT FROM AUTHOR]

Secondary data analysis is a cost-effective, accessible, and efficient means of utilizing existing data to answer new research questions. The manuscript provides an overview of the secondary data analysis process, as well as benefits and limitations inherent in the research method. An exemplar of pediatric focused research using a publicly available dataset is presented to facilitate understanding of the process. Novice and experienced researchers benefit from exploring the quantitative and qualitative secondary data analysis options available. [ABSTRACT FROM AUTHOR]

• The majority of older adult caregivers experience moderate caregiver burden. • Caregiver burden has an inverse relationship with quality of life. • SEM showed spirituality influenced quality of life through caregiver burden. • Enhancing spirituality may be an easy, low-cost way to decrease caregiver burden. Caregiver burden (CB) reduces quality of life (QOL) and causes poor health outcomes. Spirituality impacts this relationship. To determine prevalence of CB and investigate relationships among CB, spirituality, and QOL in older U.S. adult informal caregivers (n = 754). This was a cross-sectional, descriptive secondary analysis of data from the 2020 Health and Retirement Study using GLM and SEM. Caregiver mean age was 65.93 (SD=8.37). Caregivers were primarily female (n = 456, 54.0%), White (n = 500, 79.5%), and married (n = 469, 65.3%). Most caregivers had moderate CB (n = 369, 49.8%). Black caregivers who were spiritual (p =.031) and caregivers with a high school diploma/GED who were spiritual (p =.021) had lower CB. Lower CB was correlated with higher QOL (p =< 0.001). SEM depicting an influencing effect of spirituality revealed good model fit (NFI=0.988; IFI=0.993; TLI=0.983; PCFI=0.397, RMSEA=0.043; χ2=9.577, p =.048, DF=4) Fostering spirituality in older adult caregivers could reduce CB and improve QOL. [ABSTRACT FROM AUTHOR]

Background: Insurance databases contain valuable information related to the use of dental services. This data is instrumental in decision-making processes, enhancing risk assessment, and predicting outcomes. The objective of this study was to identify patterns and factors influencing the utilization of dental services among complementary insured individuals, employing a data mining methodology. Methods: A secondary data analysis was conducted using a dental insurance dataset from Iran in 2022. The Cross-Industry Standard Process for Data Mining (CRISP-DM) was employed as a data mining approach for knowledge extraction from the database. The utilization of dental services was the outcome of interest, and independent variables were chosen based on the available information in the insurance dataset. Dental services were categorized into nine groups: diagnostic, preventive, periodontal, restorative, endodontic, prosthetic, implant, extraction/surgical, and orthodontic procedures. The independent variables included age, gender, family size, insurance history, franchise, insurance limit, and policyholder. A multinomial logistic regression model was utilized to investigate the factors associated with dental care utilization. All analyses were conducted using RapidMiner Version 2020. Results: The analysis encompassed a total of 654,418 records, corresponding to 118,268 insured individuals. Predominantly, restorative treatments were the most utilized services, accounting for approximately 38% of all services, followed by diagnostic (18.35%) and endodontic (13.3%) care. Individuals aged between 36 and 60 years had the highest rate of utilization for any dental services. Additionally, families comprising three to four members, individuals with a one-year insurance history, people contracted with a 20% franchise, individuals with a high insurance limit, and insured individuals with a small policyholder, exhibited the highest rate of service usage compared to their counterparts. The regression model revealed that all independent variables were significantly associated with the use of dental services. However, the patterns of association varied among different service categories. Conclusions: Restorative treatments emerged as the most frequently used dental services among insured individuals, followed by diagnostic and endodontic procedures. The pattern of service utilization was influenced by the characteristics of the insured individuals and attributes related to their insurance. [ABSTRACT FROM AUTHOR]