dataesr/scientific-paragraphs-categorization huggingface dataset:
Study setting {9} This study involves 8 hemodialysis centers in a French district, the Normandy. We called for volunteers to take part in the study. Among participating centers, there are the community centers of Dieppe, Mémorial France Etats-Unis of Saint-Lô, Lisieux; the nonprofit centers "ANIDER" of Alençon, Hérouville Saint-Clair, Flers and Dieppe; and a private hospital Saint Martin of Caen. There will be approximately 140 nurses participating in this study. They will complete a data collection on the occurrence of adverse events. An anonymity number will be assigned to each participating nurse. The start of the study for each center will be staggered by 1 month to allow for the distribution of training. Data are collected in each hemodialysis centers and then centralized in the Caen University Hospital.
Plans for assessment and collection of outcomes {18a} Data will be managed in a database administered by the sponsor. Data entry will be performed by the investigators at each center and may be performed by any person on the task delegation list. The system used for the computerized database will be in accordance with the regulations in force, particularly MR-01. Access to the database will be limited to authorized persons only (sponsor team, investigation team, principal investigator), and rights (read, write, specific pages of the case report form, patients of the center or all patients, etc. ) will be assigned according to their role in the study and their center. Authentication of users will be assured by means of a username and a password personalized for each user. Connections to the database will be recorded in the connection history.
Consistency tests may be scheduled depending on the level of risk and/or impact of the study as defined by the sponsor. Following the execution of these tests, requests for clarification (queries) may be sent to the investigators to correct or confirm data entered in the database. Depending on the level of risk and/or impact of the study, a preanalysis committee may meet before the data are exported to qualify the deviations identified during the study and to decide whether or not to include the data collected in the study.
Data management {19} Database development and administration are ensured by the North-West Canceropole Data Processing Centre (DPC) and under Caen University Hospital responsibility. Access is allowed to authorized people only through a highly secured system (VPN/SSL mode up to 128 bits; transmitted data encrypted). Its web interface allows study management via standard data entry in client/server and/or via the internet. Daily backup is made using two independent servers. Data protection is based on (i) the definition of authorization profiles, defining the functions or types of information available to a user; (ii) control of access to the Fig. 3  Randomization software by a username issued by the administrator and a password; (iii) electronic signature of the data; (iv) secure access to data by the "owner" only; (v) the audit trail that tracks all access, modification, and deletion of data; (vi) exported files archived within the system; (vii) all plotted transfers and uploads and downloads; and (viii) the possibility of automatic identification of patients without nominative data (creation of a unique patient identification number (alphanumeric) to enable interoperability of the data recorded and preserve anonymity).
Data quality is assured by pretesting and consistency checks during data entry. The software also includes a data management system of "queries. " Storage: The Ennov Clinical© application is made available in SaaS mode by ENNOV ™ , which outsources its server installation and hosting services (software and data) to OVH ™. Backups are made daily (databases and servers). This is an incremental backup without overwriting data. A history is created allowing, if necessary, the recovery of previous data. Data management/quality: The data processing center has quality procedures relating to Good Clinical Practice (GCP) guidelines and the use of the software.
The pain score (numeric scale) at the time of puncture will be analyzed between the two groups by Student's t test. All the parameters collected will be analyzed. Multivariate analyses will be considered according to the results of univariate analyses such as logistic regression comparing the two groups and mixed models. The adjustments described above will also be applied to the secondary objectives. The collection of the nurses' feelings of expertise will be synthesized. All analyses will be based on a first species error of 5% and will be two-tailed. The IBM ® -SPSS ® data analysis software (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23. 0. Armonk, NY: IBM Corp. ) will support all analyses.
MATERIALS AND METHODS: Data: To conduct our analyses, we used representative samples of micro-census data extracted from the IPUMS-International (Integrated Public Use Microdata Series-International) database (Minnesota Population Center, 2020): micro-census data are anonymized individual-level data  (Ruggles et al. , 2015). IPUMS-International currently disseminates data from 547 censuses and surveys in 103 countries worldwide (Minnesota Population Center, 2020). The Botswana dataset consists of representative 10% samples from the original censuses, and includes anonymized individual-level data on age, gender, and residence (current, as well as 12 months prior). The data also includes individual survey weights that allow for population-level estimation  (Ruggles et al. , 2015). To examine historical trends in internal migration networks and urbanization, we analyzed data collected in  the 1981, 1991, 2001, and 2011  censuses.
Estimating the incidence of internal migration: We estimated the incidence of internal migration by calculating the CMI. This statistic represents the overall incidence, or level of internal migration (between district plus within district), per hundred residents over a year. The mathematical definition of the CMI is given in Equation  1 : Constructing gender-stratified age structure pyramids: 𝐶𝑀𝐼 = 100 • 𝑀 𝑃 ( We aggregated the migration data from each census by gender and age (using 5-year age groupings) to construct population pyramids; these pyramids show the age-gender demographics of all individuals internally migrating in the 12 months prior to each census.
Data availability statement: All data needed to evaluate the conclusions in the paper are presented in the paper, or freely available for registered users at the IPUMS International website: https://doi. org/10. 18128/D020. V7. 3. We note that we did not collect these data, nor are they permitted to be posted to other repositories. All code needed to reproduce all parts of this analysis are available from the first author's GitHub page: https://github. com/janetsong80/pop-mobilitybotswana-hiv (copy archived at: https://zenodo. org/badge/latestdoi/594401539).
Search strategy and eligibility criteria Studies on response shift were identified by searching the following library databases: (a) MEDLINE, PSYCINFO, and CINAHL using the EBSCO interface; (b) EMBASE using the OVID interface; (c) Social Science Citation Index using the Web of Science interface; and (d) Dissertations & Theses Global using the ProQuest interface (see Fig. 2 ). All searches were conducted using the same combination of the following terms and corresponding abbreviations in all indexed fields: "response shift" OR "longitudinal measurement invariance" OR "retrospective bias" OR "longitudinal differential item" OR "longitudinal DIF. " The searches were limited to English language and a date of publication before January 1, 2021. For the Social Science Citation Index, an additional limit was applied to exclude meeting abstracts.
No other filters were applied to any of the searches. Duplicate records were identified and removed using the duplicate screening tool in the EPPI Reviewer Platform  [21]. Manuscripts that reported on errata or on the same study as reported in another manuscript were identified as duplicates during the data extraction process after confirming that no additional relevant information could be extracted. We retained the manuscripts that reported the most detailed results. We aimed to include all longitudinal quantitative studies that examined response shift using a PROM. Exclusion criteria were sequentially applied in the order shown in Fig. 2. The titles and abstracts of each citation were randomly assigned for independent screening by two team members (RS, LR, MEGV, VS, MAGS), all of whom were thoroughly familiar with response shift, using the EPPI Reviewer platform  [21].
Identification of studies via databases and registers Identification Screening Included ple (or group) of an overall sample reported in the same manuscript or the same or overlapping sample from another study. Fig. 2 PRISMA flow dia- gram. RS response shift, PROM patient-reported outcome measure, HRQOL Health-related quality of life. a Rea-sons are ranked by the first identified reason for exclusion. Hoffmann TC, Mulrow CD, JE, Bossuyt PM, Boutron I, From: Page MJ, McKenzie Records identified from databases (n = 3357): WEB OF SCIENCE (n = 1240) PSYCHINFO (n = 484) CINAHL (n = 287) EMBASE (n = 712) MEDLINE (n = 524) PROQUEST (n = 110) Records removed before screening: Duplicate records (n = 1451) et al. The PRISMA 2020 state- ment: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71.
Psoriasis is one of the most common immune-mediated inflammatory diseases (IMIDs). Living in a rural environment during childhood is associated with a decreased risk of certain IMIDs, like asthma, in adulthood. However, its role in other IMIDs, such as psoriasis is still unclear. To evaluate the relationships between different factors related to the environment during childhood and the risk of psoriasis in adulthood we conducted a study in E3N, a French prospective cohort composed of 98 995 women. During the 1990-2018 follow-up of 72 154 study participants, we identified 1 967 incident cases of psoriasis from self-reports in self-administered structured questionnaires. During the 2004-2018 follow-up of 67 917 study participants, 188 moderate-to-severe cases of psoriasis were identified through self-reports and from data from a drug reimbursement database.
E3N cohort The E3N ( Étude Épidémiologique auprès de femmes de l' Éducation Nationale) cohort is a French prospective cohort set up to investigate risk factors for major non-communicable diseases in women. It includes 98 995 women affiliated to the Mutuelle Générale de l' Éducation Nationale (MGEN), the French health insurance scheme covering workers in the national education system, mostly teachers, that were aged between 40 and 65 years and residing in metropolitan France at the time of their inclusion in the study in 1990. The collection of information on health, nutrition and lifestyle was done through self-administered questionnaires sent to participants every two to three years. Linkage to the drug reimbursement database provided by the MGEN allowed access to data on all extra hospital drug reimbursements (i.
Identification of psoriasis cases Psoriasis cases were defined as women that self-reported a diagnosis of psoriasis in at least one of the follow-up questionnaires in which questions about psoriasis were included: questionnaire 9 (Q9) sent in 2008, questionnaire 10 (Q10) sent in 2011, and questionnaire 12 (Q12) sent in 2018. In such questionnaires participants were also asked to report the age at diagnosis. When the age at diagnosis of the disease self-reported in different questionnaires was discordant (23% of psoriasis cases included in the present study), we retained the age reported in the first completed questionnaire. We defined moderate-to-severe psoriasis cases as self-reported cases of psoriasis with at least one drug reimbursement in the MGEN database for one of the classes of systemic drugs used to treat psoriasis (i.
Assessment of childhood exposures We used five exposure variables, four individual and one ecological, all derived from data collected in questionnaire 7 (Q7) completed in 2002 and in which questions on the environment during childhood were included. The four individual variables were all binary and included factors related to exposure to a rural environment during childhood like having lived on a farm at least 3 consecutive months during childhood, having lived in contact with farm animals at least 3 consecutive months during childhood and having had farming parents as well as having had pets (dog or cat) during childhood. The ecological binary indicator of a rural birthplace was created using self-reported birthplace at baseline and the general agricultural census of 1970 and by defining as rural a birthplace with less than 5000 inhabitants as done previously  (Varraso et al.
Assessment of covariates We used data on putative confounders such as tobacco smoking, height and weight, these latter two used to determine body mass index (BMI), collected in all questionnaires. Education level and marital status were both collected at the baseline questionnaire in 1990. In our analyses we also included data on diseases that may be associated with psoriasisi. e. hypertension, depression requiring a pharmacological treatment and type 2 diabetes. Self-reported diagnoses of hypertension and depression were collected in each questionnaire from baseline to Q12 except for hypertension for which no data was collected in Q10. Type 2 diabetes cases and their corresponding date of diagnosis were defined throughout the duration of the follow-up using an algorithm based on self-reported information and drug reimbursement data as described previously  (Mancini et al.
Study population The process of selection of the study population is described in Fig. 1. From the initial population of women that completed the baseline questionnaire in 1990 (N = 98 995), we excluded 17 543 participants that did not answer Q7, 6 232 participants for whom it was not possible to assign the urban-rural category for the birthplace mostly because they were born abroad, and 30 participants who died during follow-up but for whom no valid date of death was retrieved. We further excluded participants who reported psoriasis in free text included in each questionnaire (to allow the report of additional health conditions) but who answered negatively to the specific questions about psoriasis (N = 29) and those who declared a date of psoriasis diagnosis after 2004 but for whom no reimbursement for drugs used in psoriasis was found in the MGEN database (N = 124).
For analyses on moderate-to-severe psoriasis follow-up started on January 1st, 2004, and ended when an event of moderate-to-severe psoriasis occurred (date of first systemic drug reimbursement available from the MGEN database in a self-reported case of psoriasis), at the last answered questionnaire, at the date of death or on December 31st, 2018 (date of the most recent available data on drug reimbursement) whichever occurred first. We first estimated age-adjusted hazard ratios (uHRs) from models including only one of the five childhood exposure at a time. We then estimated multivariable adjusted hazard ratios (aHRs) from models including BMI (categorical variable: <25, 25-30[, and ≥30 kg/m2; time-varying), marital status (unmarried, married; baseline), smoking status (never, current, former smoker; time-varying), level of education (undergraduate or less, graduate, postgraduate or more; baseline), and three binary variables about medical conditions: history of diabetes, depression, and hypertension (all time-varying); hormonal and reproductive variables included were age at menarche (<12 years, 12-15 years, >15 years; baseline), menopausal status (premenopausal, postmenopausal; time-varying), parity (nulliparous, parous; baseline), and ever use of a contraceptive pill (no, yes; baseline), together with one of the five exposure variable at a time.
Finally, we performed a sensitivity analysis by using logistic regression to include all cases irrespective of whether they were prevalent or incident as well as all cases with unknown age at diagnosis. In this sensitivity analyses, based on a population of 75 218 women including 5 004 with psoriasis, univariate and multivariable logistic models were fitted from which odds ratios (OR) and 95% confidence intervals (CI) were estimated. The proportional hazards assumption was verified through the analysis of Schoenfeld residuals. Descriptive analyses were carried using PROC FREQ procedure while Cox regression models were fitted using the PHREG procedure from SAS software version 9. 4 Copyright © 2013 SAS Institute Inc. , Cary, NC, USA.
, 2018; Setty et al. , 2007). While full validation of self-reported diagnoses through the acquisition of medical reports or specific questionnaires to collect clinical information was not possible, we complemented self-reported data with data from the MGEN drug reimbursement database. In particular, our case definition was supported by the observation that 97% of cases had reimbursements of drugs used to treat psoriasis (i. e. , derivatives of vitamin D, cytokine receptor modulators, immunosuppressants, psoralens, and topical steroids). In general, the positive predictive value of self-reported diagnosis of psoriasis may be sub-optimal in a general population setting  (Modalsli et al. , 2016) , but the higher level of education of the women in the cohort and the use of the drug reimbursement database to complement self-reported information for moderate-to-severe cases in our study have likely increased the reliability of our classification of cases and non-cases.
Funding This work was realized with data of the E3N cohort ( Inserm)  and supported by the  Mutuelle Générale de l'Education Nationale (MGEN) ,  Gustave Roussy Institute , and  French League Against Cancer  for the constitution and maintenance of the cohort. This work has benefited from state aid managed by the  National Research Agency (ANR)  under the program " Investment in the future " bearing the reference  ANR-10-COHO-0006 , as well as a subsidy from the  Ministry of Higher Education, Research and Innovation  for public service charges bearing the reference no. 2102918823 ,  2103236497 , and  2103586016. M. Conte  was funded for this work by a doctoral grant from the  French Ministry of Research  through the  University Paris-Saclay Doctoral School of Public Health (EDSP).
Data Analysis Data were analyzed using Microsoft Excel 16. 16. 27 and IBM SPSS Statistics 28. 0. Variables were summarized using frequencies and descriptive statistics. Chi square tests were used for statistical comparisons. An alpha level of 0. 05 was considered to be statistically significant. All calculations were based on participants' reports. Age, height and weight were calculated in total and separately for male and female, indicating means, maximum and minimum. The BMI was calculated by dividing participants' weight by height in metres squared. Preferred wingfoiling-locations (lake, sea, wave), years of wingfoiling experience and skills (self-assessment as "beginner", "advanced" (wingfoiling with tack and jibe) and "expert" (jumps, freestyle-tricks)) were asked. Previous experience in other surfing sports (windsurfing, kitesurfing, stand-up-paddling, surfing), main sporting motivation and the compilation of the wingfoil-sports equipment could be answered by multiple options per question.
In addition, sport-specific physical training, warming up immediately before wingfoiling and the participation in competitions were surveyed. Number of injuries in the past twelve months, injury mechanism, location (on the beach/in the water), time of injury (at the beginning of the session/after one hour/after two hours/later), injured body part and type of injuries could be answered and frequencies were calculated. The participants were asked about the number and duration of wingfoiling-sessions per month and per year in order to calculate the incidence of injury. For athletes who had been practicing the sport for less than one year at that time, the data were extrapolated to one year or not included (two separate calculations were made). Finally, participants were grouped by sex, wingfoiling-location, wingfoiling-skills, performing warm-ups, fitness-routines, participation in competitions and the use of sports specific safety equipment.
Discussion According to our knowledge, this is the first study on wingfoiling injuries so far. A strength of this study is that the sample consisted of a relatively large group of athletes (with, according to our personal experience, a realistic distribution of men and women that provides a typical representation of this sport). However, there are some methodological limitations. First, the outcome measures were self-reported rather than by a more valid approach such as getting data from medical records. There was some degree of recall bias, consequently affecting the validity of results regarding injury history. Second, selection bias is also a concern, and injured athletes could have been more likely to participate in the survey compared to uninjured athletes. Therefore, it is difficult to assess whether injuries are underestimated or overestimated.
Data Analyses Data analyses proceeded in three steps. First, we performed confirmatory factor analyses to test the structural validity of the SOI-R. Three models were specified and tested: (a) a single-factor model that assumes that sociosexuality is unidimensional, (b) a three-factor oblique model (i. e. , behavior, attitude, and desire), and (c) a bifactor model that includes a general factor "g", in which all the items load, as well as the three specific factors underlying the SOI-R (i. e. , behavior, attitude, and desire) on which respective items load  (Gana & Broc, 2019). Second, we tested gender invariance of the SOI-R. Third, we examined descriptive statistics for scale sum scores (e. g. , correlations, gender differences). Finally, a path analysis was performed to test our specified model (Figure  1 ).
Strengths and limitations When interpreting our main results, several limitations should be considered. First, data on types of infant feeding was based on reported data by parents. This may lead to misclassification due to recall bias, regression dilution bias, and underestimation of the magnitude of true association  32. However, in Korea, physicians do interact with the parents using the questionnaire during medical consultations, which may reduce this concern. Second, the data on types of infant feeding was obtained at a single point of a nationwide health examination in infants aged 6 months. This single-point examination can lead to an overestimate of breastfeeding than average with variations in possible effects and a longer period of recall bias. Further, it is difficult to verify the long-term effect of breast milk intake over 6 months.
Data source This study was based on the National Health Insurance Service in the Republic of Korea. We selected the dataset of all infants born between 1 January 2009 and 31 December 2015, and who had records of receiving the first National Health Screening Program for Infants and Children. According to birth statistics, our birth cohort covered approximately 80% of national births  33. The dataset was linked and consisted of data on first general health examination results, death records, health insurance data including insurance eligibility data, personal sociodemographic data, inpatient and outpatient healthcare records, and medication records. The data were anonymized to ensure the confidentiality required by the South Korean government  36. The study was approved by the Institutional Review Board of Sejong University (Seoul, South Korea; SJU-HR-E-2021-001) and Seoul National University (Seoul, South Korea; E-2108-134-1246).