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We analyze here how pre-service teachers explicate their views about the wave-particle duality of photons and what role it plays in their arguments supporting the quantum nature of light. The data for the analysis is provided by 12 written reports about the double-slit experiment with feeble light. The analysis is based on constructing semantic networks corresponding to pre-service teachers' written texts. Contingency-like associative correlation between word-pairs is used to differentiate between word-pairs, where associations of two terms or words is systematic. Such associations indicate connections, which are significant for key term vocabularies in construction of inferences and arguments. Based on that information of the key vocabulary we then construct the structure of pre-service teachers' argument for the nature of the photon and its wave-particle duality, in the form of directed argument graphs (DAGs). The results show that argument structures in four to six out of 12 cases meet the goals set for pre-service teacher education. In these cases, experimental aspects and wave-particle duality play an important role in the pre-service teachers' argument and its structure.

PURPOSE: Population-based studies on the associations of plant-based foods, red meat or dairy with gut microbiome are scarce. We examined whether the consumption of plant-based foods (vegetables, potatoes, fruits, cereals), red and processed meat (RPM) or dairy (fermented milk, cheese, other dairy products) are related to gut microbiome in Finnish adults. METHODS: We utilized data from the National FINRISK/FINDIET 2002 Study (n = 1273, aged 25-64 years, 55% women). Diet was assessed with 48-hour dietary recalls. Gut microbiome was analyzed using shallow shotgun sequencing. We applied multivariate analyses with linear models and permutational ANOVAs adjusted for relevant confounders. RESULTS: Fruit consumption was positively (beta = 0.03, SE = 0.01, P = 0.04), while a dairy subgroup including milk, cream and ice-creams was inversely associated (beta=-0.03, SE 0.01, P = 0.02) with intra-individual gut microbiome diversity (alpha-diversity). Plant-based foods (R2 = 0.001, P = 0.03) and dairy (R2 = 0.002, P = 0.01) but not RPM (R2 = 0.001, P = 0.38) contributed to the compositional differences in gut microbiome (beta-diversity). Plant-based foods were associated with several butyrate producers/cellulolytic species including Roseburia hominis. RPM associations included an inverse association with R. hominis. Dairy was positively associated with several lactic producing/probiotic species including Lactobacillus delbrueckii and potentially opportunistic pathogens including Citrobacter freundii. Dairy, fermented milk, vegetables, and cereals were associated with specific microbial functions. CONCLUSION: Our results suggest a potential association between plant-based foods and dairy or their subgroups with microbial diversity measures. Furthermore, our findings indicated that all the food groups were associated with distinct overall microbial community compositions. Plant-based food consumption particularly was associated with a larger number of putative beneficial species.

Teaching and learning the language of science is an important part of science education. Learning the vocabulary of science plays a key role in learning the language of science. The meaning of abstract scientific terms builds on their connections with other terms and how they are used. In this research, we study pre-service physics teachers' physics-related vocabularies and investigate how rich a vocabulary they use and what similarities and differences there are in their vocabularies regarding electrons and photons. We investigate the connectedness of physics terms by categorizing them according to their role in explaining quantum physics and carry out a lexical network analysis for N=60 written reports. The analysis shows that vocabularies do not share much similarity and the reports reflect narrow images of photons and electrons. We conclude that science teacher education needs to pay attention to explicit teaching of the language of science for pre-service teachers.

BACKGROUND: Dyslipidemia is treated effectively with statins, but treatment has the potential to induce new-onset type-2 diabetes. Gut microbiota may contribute to this outcome variability. We assessed the associations of gut microbiota diversity and composition with statins. Bacterial associations with statin-associated new-onset type-2 diabetes (T2D) risk were also prospectively evaluated. METHODS: We examined shallow-shotgun-sequenced fecal samples from 5755 individuals in the FINRISK-2002 population cohort with a 17+-year-long register-based follow-up. Alpha-diversity was quantified using Shannon index and beta-diversity with Aitchison distance. Species-specific differential abundances were analyzed using general multivariate regression. Prospective associations were assessed with Cox regression. Applicable results were validated using gradient boosting. RESULTS: Statin use associated with differing taxonomic composition (R2, 0.02%; q=0.02) and 13 differentially abundant species in fully adjusted models (MaAsLin; q

Background: Electromagnetic forces in transcranial magnetic stimulation (TMS) coils generate a loud clicking sound that produces confounding auditory activation and is potentially hazardous to hearing. To reduce this noise while maintaining stimulation efficiency similar to conventional TMS coils, we previously developed a quiet TMS double containment coil (qTMS-DCC). Objective: To compare the stimulation strength, perceived loudness, and EEG response between qTMS-DCC and a commercial TMS coil. Methods: Nine healthy volunteers participated in a within-subject study design. The resting motor thresholds (RMTs) for qTMS-DCC and MagVenture Cool-B65 were measured. Psychoacoustic titration matched the Cool-B65 loudness to qTMS-DCC pulsed at 80, 100, and 120 % RMT. Event-related potentials (ERPs) were recorded for both coils. The psychoacoustic titration and ERPs were acquired with the coils both on and 6 cm off the scalp, the latter isolating the effects of airborne auditory stimulation from body sound and electromagnetic stimulation. The ERP comparisons focused on a centro-frontal region that encompassed peak responses in the global signal while stimulating the primary motor cortex. Results: RMT did not differ significantly between the coils, with or without the EEG cap on the head. qTMS-DCC was perceived to be substantially quieter than Cool-B65. For example, qTMS-DCC at 100 % coil-specific RMT sounded like Cool-B65 at 34 % RMT. The general ERP waveform and topography were similar between the two coils, as were early-latency components, indicating comparable electromagnetic brain stimulation in the on-scalp condition. qTMS- DCC had a significantly smaller P180 component in both on-scalp and off-scalp conditions, supporting reduced auditory activation. Conclusions: The stimulation efficiency of qTMS-DCC matched Cool-B65 while having substantially lower perceived loudness and auditory-evoked potentials.

We examined the associations of cognitive skills, math-related emotions and beliefs, and gender with responses to an arithmetic fluency intervention. Elementary school children with dysfluent arithmetic skills (N=69) participated in an arithmetic fluency intervention (with and without self-efficacy support) implemented in small groups in schools for 12 weeks. Hierarchical regression models including cognitive skills or math-related emotions and beliefs predicted 21% to 50% of the variation in the intervention response, i.e., improvement in arithmetic fluency. Cognitive skills were associated with the response mainly among boys, whereas math-related emotions and beliefs explained more among girls. Thus, both cognitive and non-cognitive factors and their interaction with gender should be considered when identifying non-responders who may need more individually tailored support at school.

The early prediction of math difficulties (MD) is important as it facilitates timely support. MD are multifaceted, and several factors are involved in their manifestation. This makes the accurate early prediction of MD particularly challenging. In the present study, we aim to predict MD in Grade 6 with kindergarten-age (age 6) measures by applying a neural networks model. We use a set of 49 variables assessed during kindergarten from the domains of early arithmetic skills, cognitive skills, the home learning environment, parental measures, motivation, behavioral problems, and gender, which have been shown to have associations with mathematical development and/or MD. A two-step approach was used: First, we examined early whether the neural networks approach can provide a solution for the effective early identification of MD based on all 49 variables and, then, by using the most important predictors as identified by the initial model. The initial model achieved an area under the curve (AUC) of 0.818, demonstrating excellent performance. The most important predictors of Grade 6 MD came from the domains of arithmetic and cognitive skills (arithmetic skills, rapid automatized naming, number concepts, spatial skills, counting) and behavioral problems (attention-orientation). The model with only the most important predictors achieved an AUC of 0.776, indicating good performance. Our results provided proof of concept for using neural networks in MD prediction in Grade 6 using information already available in kindergarten. In schools, these results could be used to identify children at potential risk of developing MD and to provide access to early support.

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants that are detectable in the serum of most U.S. adults. Some studies of highly-exposed individuals have suggested positive associations between PFAS and B-cell non-Hodgkin lymphoma (B-NHL). To investigate whether associations exist at lower exposure levels, we conducted a nested case-control study investigating serum PFAS concentrations and B-NHL within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. We measured pre-diagnostic serum concentrations of five PFAS among 706 cases (age at diagnosis = 55–93 years, median 73 years) and 706 controls individually matched on age at blood draw, sex, self-reported race and ethnicity, study center, and year of blood collection (the median follow-up years = 10). We estimated odds ratios (ORs) and 95 % confidence intervals (CIs) for PFAS concentrations in relation to B-NHL, both overall and for selected histologic subtypes [diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), and marginal zone lymphoma (MZL)] using conditional logistic regression. We found no evidence of a positive association with B-NHL for any of the five PFAS. In analyses of histologic subtypes, perfluorohexane sulfonate (PFHxS) was significantly associated with DLBCL in a model adjusting for all other PFAS (OR for highest vs. lowest quintile = 2.19, 95 % CI = 1.21, 3.95; Ptrend = 0.02), but not in a model without mutual adjustment (OR = 1.37, 95 % CI = 0.82, 2.29; Ptrend = 0.26). We also observed an inverse association between perfluorononanoate and DLBCL (mutually-adjusted OR = 0.83, 95 % CI = 0.69, 0.99 per doubling in concentration), although the association was null among participants with blood drawn prior to 1997 (OR

Liquefied natural gas (LNG) use as shipping fuel has increased in recent years. While LNG results in lower carbon dioxide (CO2) emissions as well as benefits in terms of air pollutants, the slip of unburned methane, the main component of LNG, has remained a concern. In this study, methane together with other climate warming agents, CO2 and black carbon (BC), as well as other emission compounds were characterized from 4-stroke low-pressure dual fuel engine on-board a newly build cruise ship utilizing LNG as well as marine gas oil (MGO). The brake specific methane slip was found to vary according to engine load, being 2.3–3.0 g/kWh at 54–80% loads, but increasing to 10 g/kWh at 25% load and 21 g/kWh at 12% load. The LNG combustion also resulted in higher formaldehyde emissions compared to MGO, but reduction in formaldehyde levels was observed over the SCR catalyst present in the exhaust line of the dual-fuel engine, without urea injection, suggesting it may provide a pathway for formaldehyde mitigation. In terms of particle emissions, LNG use reduced particle mass (PM) by 87–93% and BC by 94–99% compared to MGO combustion. Non-volatile particle number above 23 nm (PNnv,>23nm) and 10 nm (PNnv,>10nm) were reduced by 88–97% and 97–99%, except at lowest engine load where PNnv,>10nm increased by 26% compared to MGO utilization. When total greenhouse gas (GHG) emissions including CO2 and BC were considered, LNG use resulted in 13–15% lower GHG at high loads, but the benefit was undermined by the escaping methane at low load conditions. Following the engine activity profile during 8-months of vessel operation on the Mediterranean suggested, however, that in a diesel-electric cruise ship, low load conditions are used mainly during arrivals and departures from harbors, as the engine was operated at loads above 40% for 90% of the operation time. Weighted emission factor, representing the actual engine operation, resulted in methane slip of 2.8 g/kWh or 1.7% of the fuel use, which is below the value considered in the FuelEU Maritime. The results suggest that load specific methane slip, together with engine load profile should be considered when evaluating methane slip on vessel or fleet level.

This study aimed to identify differences among body mass index (BMI) categories of older family caregivers (≥60 years) and their care recipients (≥65 years). Secondly, this study aimed to examine group differences and factors associated with weight change during a nutrition and oral health intervention. This secondary analysis of a randomized controlled trial (ClinicalTrial.gov (NCT04003493)) involved individually tailored nutritional guidance from a clinical nutritionist and oral health guidance from a dental hygienist. Baseline BMI differences were analyzed, followed by further analyses of group differences and associated factors of weight change over a 6-month period using generalized estimating equations. Among the participants (113 family caregivers and 107 care recipients), 36.3% and 35.1% were overweight (BMI >29 kg/m2), while 18.6% and 21.6% were underweight (BMI

The purpose of this study is to increase the understanding about undergraduate life science students' conceptions concerning the role of photosynthesizing plants in the ecosystem, utilizing a network analysis method. Science learning requires the integration and linking of abstract and often counterintuitive concepts successfully into multifaceted networks. The quality of these networks, together with their abilities to communicate via the language of science, influences students' success in academic, verbal problem-solving tasks. This study contributes to investigating students' understanding, utilizing a modern network analysis method in exploring first-year university life science students' written answers. In this study, a total of 150 first-year life science students answered two open-ended tasks related to the role of photosynthesizing plants in the ecosystem. A network analysis tool was used in exploring the occurrence of different-level science concepts and the interrelatedness between these concepts in students' verbal outputs. The results showed that the richness of concept networks and students' use of macro-concepts were remarkably varied between the tasks. Higher communicability measures were connected to the more abundant existence of macro-concepts in the task concerning the role of plants from the food-chain perspective. In the answers for the task concerning the role of plants regarding the atmosphere, the students operated mainly with single facts, and there were only minor interconnections made between the central concepts. On the basis of these results, the need for more all-encompassing biology teaching concerning complex environmental and socio-economic problems became evident. Thus, methodological and pedagogical contributions are discussed.

Understanding about nature of science is important topic in science education as well as in pre-service science teacher education. In science education, Nature of Science (NOS), in its different forms of educational scaffoldings, seeks to provide with students an understanding of features of scientific knowledge and science in general, how scientific knowledge changes and becomes accepted, and what factors guide scientific activities. For a science teacher, deep and broad enough picture of sciences is therefore of importance. This study attempts to show that the research field called Science of Science (SoS) can significantly support building such a panoramic picture of sciences, and through that, significantly support NOS. The SoS approaches the structure and dynamics of science quantitatively, using scientific documents (e.g., publications, reports, books and monographs and patent applications) as trails to map the landscape of sciences. It is argued here that SoS may provide material and interesting cases for NOS, and in so doing enrich NOS in a similarly significant way as history, philosophy and sociology of science (HPSS) scholarship has done thus far. This study introduces several themes based on SoS that are of relevance for NOS as they were introduced and discussed in a pre-service science teachers' course. The feedback from pre-service teachers shows that introducing SoS, with minimal additional philosophical interpretations and discussions, but simply as evidential facts and findings, sparks ideas and views that come very close to NOS themes and topics. Discussions related to nature of science, and specific educational NOS scaffoldings for it, can find a good companion in SoS; the latter providing facts and evidence of thee structure and dynamics of sciences, the former providing perspectives for interpretations.

Particle aggregation is essential in many industrial processes, spanning the pharmaceutical and food industries, polymer production, and the environment, among others. However, aggregation can also occur, in some processes, as a non-desired side effect. Thus, to be able to monitor aggregation in industrial processes is of high importance to guarantee that the final, required product characteristics are obtained. In this paper, we present an extensive review of the different techniques available for monitoring particle characteristics in industrial processes involving particulate materials, with special emphasis on aggregation processes. These methods include both off-line and on-line techniques, based either on image acquisition techniques or different radiation scattering techniques (light-scattering and ultrasound spectroscopy). The principles behind each technique are addressed, together with their relevant applications, advantages, and disadvantages.

Using cognitive diagnostic modeling (CDM), this study identified subtypes of mathematics learning disability (MLD) based on children's numerical skills and examined the language and spatial precursors of these subtypes. Participants were 99 MLD children and 420 low achievers identified from 1839 Finnish children (966 boys) who were followed from preschool (age 6) to fourth grade (2007-2011). Five subtypes were identified: "the arithmetic fluency deficit only subtype, the counting deficit subtype, the pervasive deficit subtype, the symbolic deficit subtype, and the counting and concept deficit subtype." Different subtypes depended on different constellations of language and spatial deficits. Findings highlight the effectiveness of CDM in identifying MLD subtypes and underscore the importance of understanding the specific deficits and antecedents of the subtypes.

Self-regulatory efficacy (SRE) among elementary school children is of interest because pupils' self-regulation capacities and SRE influence in managing learning situations. This study investigated variations in the four sources of SRE and how these variations were related to SRE, reading skills and arithmetic skills. The participants were 1284 pupils in Grades 2 to 5. SRE and the sources of SRE were explored via questionnaires completed by the pupils. Latent profile analysis was used to search for subgroups with similar combinations of sources. Five distinguishable and informative profile groups emerged with differences in SRE levels and basic academic skills. The greatest variations were in mastery experiences and emotional states, which were the most sensitive sources for detecting interindividual differences in the domain of self-regulation. Multiple positive sources contributed to higher SRE, while low exposure to sources was related to both lower SRE and low basic academic skills.

As modern business-to-business (B2B) sales have become more complex; recruiters are turning to business schools to find educated and motivated sales professionals to fill the employment demand gap that has risen. This study provides important information about business students' intentions regarding pursuing careers in B2B sales, as there are no up-to-date studies investigating the phenomenon. The purpose of this study is to investigate how business students' attitudes and perceptions of personal sales competence affect their intentions to apply to B2B sales positions. The empirical data for the present study was collected by an online survey from business school students (n = 243). The conceptual framework was constructed by integrating the theory of reasoned action (TRA) and self-determination theory (SDT) and therefore this study contributes to aforementioned research. The results from structural equation modelling (SEM) indicate that the students were not eager to apply for B2B sales jobs. However, students' attitudes positively influenced their intentions to apply for B2B sales jobs. The students' intentions to apply for B2B sales jobs were also positively influenced by their perceptions of personal sales competence. The results of the study show that the industry and the business educators still have work to do to increase the appeal of professional sales jobs to attract business students to work in B2B sales jobs. Furthermore, the results inform companies' human resource management to enhance B2B sales force recruitment.

The aim of the present study was to examine the kinds of developmental profiles of arithmetic fluency skills that can be identified across Grades 1-9 (ages 7-16) in a large Finnish sample (n = 2,518). The study also examined whether membership in the developmental profiles could be predicted using a comprehensive set of kindergarten-age factors, including information on cognitive skills; motivational, parental, and home environment factors; and gender. Four profiles of arithmetic fluency skills development were identified using a factor mixture model: persistent arithmetic difficulties (12.23%), precocious onset (50.24%), delayed onset (36.96%), and precocious onset with a Grade 7 drop (.06%). The Cholesky models predicting membership in the three largest profiles suggested that overall, the strongest kindergarten-age predictors were cognitive skills (especially counting, number concepts, spatial relations, rapid automatized naming [RAN], phonological awareness, and letter knowledge), but motivational, parental, and home environment factors were also significant. Membership in the profile with precocious onset was predicted by most of the kindergarten-age measures, suggesting that the strengths in early skills, as well as motivational, parental, and home environment factors, are reflected in the advanced start in arithmetic development at school. The profiles with delayed onset and persistent difficulties were similar in most kindergarten-age measures but differed in task avoidance and four cognitive skills (letter knowledge, counting, number concepts, and RAN), suggesting that these factors predict differential development over the longer term.

In this article, graduated physics teachers' views about their teacher education program and professional needs are evaluated. With respect to teacher knowledge, Physical Knowledge for Teaching (PKT) framework consisting of six domains related to content knowledge and pedagogical content knowledge was developed based on the framework of Mathematical Knowledge for Teaching. PKT was utilized in the design of a Likert scale instrument that aims to discover teachers' views concerning these six domains from two separate viewpoints: to what extent the domains were covered in their teacher education program concerning the domains, and how important is that theme for their profession. Results revealed that teachers see that the domains related to common content knowledge and structures of physics have been addressed adequately in their teacher education but characteristics of other domains, such as teaching methods, evaluation, and motivating learners, received less favorable evaluations. With respect to the importance of different domains for teacher profession, teachers valued the importance of every domain of teacher knowledge highly. These findings suggest that the greatest deficiencies in this physics teacher education program lie on addressing pedagogical content knowledge with its various sub-domains. Our PKT framework offers a promising base for evaluating physics teacher knowledge. We suggest that a framework for teacher knowledge should be explicitly introduced for pre-service teachers in their education so that they could evaluate their knowledge and professional needs better.

Learning the wave-particle dualism of electrons and photons plays a central role in understanding quantum physics. Teaching it requires that the teacher is fluent in using abstract and uncommon terms. We inspect the lexical structures of pre-service teachers' declarative knowledge about the wave-particle dualism of electrons and photons in the context of double-slit interference. The declarative knowledge is analyzed in the form of a lexical network of terms. We focus on lexical structures because, in teaching and learning, knowledge is communicated mostly through lexical structures, i.e., by speaking and writing. Using the lexical networks, we construct the lexicons used by pre-service teachers to express their knowledge of electrons and photons in the context of double-slit interference. The lexicons consist of eight different key terms, each representing a set of closely-related or synonymous terms. The lexicons by 14 pre-service teachers reveal remarkable variation and differences, and are strongly context-dependent. We also analyzed lexicons corresponding to two didactically-oriented research articles on the same topic and found that they also differ. Lexicons paralleling both texts are found among the pre-service teachers' lexicons. However, only some of the pre-service teachers use such rich vocabulary as would indicate multi-faceted understanding of quantum entities.

Nature of science (NOS) has been a central theme in science education and research on it for nearly three decades, but there is still debate on its proper focus and underpinnings. The focal points of these debates revolve around different ways of understanding the terms "science" and "scientific knowledge". It is suggested here that the lack of agreement is at least partially related to and reflected as a lack of common vocabulary and terminology that would provide a shared basis for finding consensus. Consequently, the present study seeks motivation from the notions of centrality of lexicons in recognizing the identity of disciplinary communities and different schools of thought within NOS. Here, by using a network approach, we investigate how lexicons used by different authors to discuss NOS are confluent or divergent. The lexicons used in these texts are investigated on the basis of a network analysis. The results of the analysis reveal clear differences in the lexicons that are partially related to differences in views, as evident from the debates surrounding the consensus NOS. The most divergent views are related to epistemology, while regarding the practices and social embeddedness of science the lexicons overlap significantly. This suggests that, in consensus NOS, one can find much basis for converging views, with common understanding, where constructive communication may be possible. The basic vocabulary, in the form of a lexicon, can reveal much about the different stances and the differences and similarities between various disciplinary schools. The advantage of such an approach is its neutrality and how it keeps a distance from preferred epistemological positions and views of nature of knowledge.

Objective: We aimed to evaluate the impact of an individually tailored preventive oral health intervention on the use of oral health care services by older family caregivers (FCs) and their care recipients (CRs). Material and methods: A randomized controlled six and 12-month oral health intervention study included FCs and CRs aged ≥65 years living in Eastern Finland. The participants were randomly assigned to an intervention (FCs n = 53, CRs n = 47) and a control (FCs n = 39, CRs n = 35) group. Individually tailored oral health interventions for the FCs provided by a dental hygienist focused on oral hygiene and self-care. Generalized estimating equations were used to analyze the impact of intervention on the change in the use of oral health care services. Results: The intervention had no significant effect on the use of oral health care services by the FCs or their CRs. Traditional factors such as female gender, a higher number of teeth, toothache, no dental fear, and higher morbidity were significantly (p < 0.05) associated with an increased use of oral health care services in the FCs, but not among the CRs. Conclusions: Individually tailored preventive oral health intervention showed no effect on the use of oral health care services. To promote oral health among the elderly, specific interventions focusing on use of oral health care services are needed. Trial registration: clinicaltrials.gov/study/NCT04003493

Barad’s agential realism has recently been evoked as a theoretical viewpoint for science education and science education research in approaches that emphasize the role of materiality and matter as a key aspect of learning science. Barad’s agential realism is underpinned by their specific ways of reading quantum physics, its interpretations and, in general, contemplations of the quantum nature of existence. Agential realism is an ontological as well as an epistemological (onto-epistemological) metaphysical position that strives to dissolve the boundaries between subjects and objects, and leaves little room for traditional subject-centered epistemological views (like constructivism) of learning. A closer look is warranted at how the quantum physics underpinnings of agential realism, which are clearly very important for it, appear in its current applications in new materialism within science education research. This critical commentary claims that, in such a context, the conceptualization of learning and educational phenomena derives little if any advantage or practical utility from the quantum physics-inspired metaphysics of agential realism; only metaphorical talk remains. Consequently, we need to be aware of the limited power and plausibility of the quantum-inspired contemplations contained in agential realism if it is adopted as a theoretical viewpoint for science education and science education research.

Daniel Hsiang-Te Tsai,1,2 J Simon Bell,3 Shahab Abtahi,4 Brenda N Baak,5 Marloes T Bazelier,4 Ruth Brauer,6 Adrienne YL Chan,6– 9 Esther W Chan,9– 12 Haoqian Chen,13 Celine SL Chui,9,14,15 Sharon Cook,16 Stephen Crystal,16 Poonam Gandhi,13 Sirpa Hartikainen,17 Frederick K Ho,18 Shao-Ti Hsu,1 Jenni Ilomäki,3 Ju Hwan Kim,19 Olaf H Klungel,4 Marjaana Koponen,17 Wallis CY Lau,6,8,9 Kui Kai Lau,20,21 Terry YS Lum,22 Hao Luo,22 Kenneth KC Man,6,8,9 Jill P Pell,18 Soko Setoguchi,13,23 Shih-Chieh Shao,1,24 Chin-Yao Shen,1 Ju-Young Shin,19,25,26 Patrick C Souverein,4 Anna-Maija Tolppanen,17 Li Wei,6,9 Ian CK Wong,6,8,9,27 Edward Chia-Cheng Lai1 1School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 2Centre for Neonatal and Paediatric Infection, St George’s University of London, London, UK; 3Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia; 4Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; 5PHARMO Institute for Drug Outcomes Research, Utrecht, the Netherlands; 6Research Department of Practice and Policy, UCL School of Pharmacy, London, UK; 7Groningen Research Institute of Pharmacy, Unit of Pharmacotherapy, ‐Epidemiology and ‐Economics, University of Groningen, Groningen, the Netherlands; 8Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 9Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, Special Administrative Region, People’s Republic of China; 10Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 11Department of Pharmacy, the University of Hong Kong-Shenzhen Hospital, Shenzhen, People’s Republic of China; 12The University of Hong Kong Shenzhen Institute of Research and Innovation, Shenzhen, People’s Republic of China; 13Center for Pharmacoepidemiology and Treatment Science (PETS), Institute for Health, Rutgers University, New Brunswick, NJ, USA; 14School of Nursing, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 15School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 16Center for Health Services Research, Rutgers University, New Brunswick, NJ, USA; 17Kuopio Research Centre of Geriatric Care and School of Pharmacy, University of Eastern Finland, Kuopio, Finland; 18School of Health and Wellbeing, University of Glasgow, Glasgow, UK; 19School of Pharmacy, Sungkyunkwan University, Suwon, South Korea; 20Division of Neurology, Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 21State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 22Department of Social Work and Social Administration, University of Hong Kong, Hong Kong, Special Administrative Region, People’s Republic of China; 23Department of Medicine, Rutgers Robert Wood Johnson Medical School and Pharmacoepidemiology and Treatments Science, Institute for Health, Rutgers University, New Brunswick, NJ, USA; 24Department of Pharmacy, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan; 25Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea; 26Department of Biohealth Regulatory Science, Sungkyunkwan University, Seoul, South Korea; 27Aston Pharmacy School, Aston University, Birmingham, UKCorrespondence: Edward Chia-Cheng Lai, School of Pharmacy and Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan, Email edward_lai@mail.ncku.edu.twPurpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN).Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives.Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK.Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.Keywords: meta-data, data repository, Neurological and Mental Health Global Epidemiology Network, NeuroGEN