dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analyses All data analyses were completed using IBM SPSS Statistical Software version 26. The data were screened for normality, outliers, and missing values. To evaluate the effectiveness of randomization to groups, one-way ANOVAs were carried out using each of the background measures and key outcome measures (single-and dual-task gait speed and 2-back accuracy) collected prior to the training phase. To evaluate the dual-task manipulation at baseline, paired sample t-tests were carried out on single-and dual-task gait speed and cognitive accuracy using the pre-training assessment data. Two 2 × 3 Mixed Factorial ANOVAs were then conducted on each of the DTC scores (Cognitive, Walking) to assess change from pre-to post-training across training arms, where the within-subjects effect was Time (pre-vs.
e. , n = 78; Pothier et al. , 2021) , results show similar improvements in TUG walking speed regardless of training Frontiers in Aging Neuroscience 13 frontiersin. org modality. We found consistent results in TUG improvements in the current sub-sample of 33 participants, suggesting that the training effects are representative of the full dataset. As such, while the small sample size is an important limitation to consider, we provide moderate evidence that may suggest similar improvements in cognitive DTCs across training modalities. Importantly, our findings are consistent with a number of other studies which have revealed comparable improvements in dual-task walking speed and balancing  (Desjardins-Crepeau et al. , 2016; Fraser et al. , 2017) , as well as functional mobility  (Pothier et al.
Statistical Analyses Identical statistical analyses were performed in both subsamples. The Grubbs test was used to investigate possible outliers. No outliers were detected in the present data. The normality of the data was then examined using the Kolmogorov-Smirnov test. Next, a two-step cluster analysis was performed on the z-scores of the variables included in the present study to identify the psychological profiles of women and men with overweight or obesity. The packages used for these analyses were {FactoMineR} and {factorextra}. Since the number of clusters was not known beforehand, an agglomerative hierarchical clustering based on the results of the principal components analysis was performed using Ward's method  [82]. The agglomerative technique considers each observation as a separate cluster.
In order to investigate the internal validity of the clusters, nonparametric tests for mean comparisons were carried out using the Kruskal-Wallis test, followed by the Wilcoxon test for post-hoc analyses comparing the mean levels of the following clustering variables: External Stimuli and Internal Stimuli subscales from the WEL-Fr-C and Appearance, Social and Performance state self-esteem subscales, Physical hunger, BIQ and PSS-11. The external validity of the clusters was examined by comparing the mean levels of depression, wellbeing, BMI and age across different clusters. Statistical analyses were performed using RStudio software (RStudio Inc. , Boston, MA, USA) for Windows, version 3. 4. 2.
Acknowledgments: The authors would like to give special thanks to  Michel Dubourdeaux  (R&D Innovation Director at PiLeJe),  Emmanuelle Bocandé  (Medical Director at PiLeJe) and  Christophe Guyomar  ( Chief Digital Officer at PiLeJe ) for their administrative and technical support and  Claude Blondeau  ( Head of Scientific Communication at PiLeJe ) for editing the manuscript, as well as to  Eve Villemur  and  Gérard Ostermann  for creating the Physical Hunger scale. Distinctive thanks are addressed to  Solenne Roux  ( Design Engineer at the Laboratory of Psychology, University of Bordeaux ) and  Maxime Larrieu  ( University of Bordeaux ) for their advice and help on the data analysis methods. Thanks are also addressed to  Dominique Périn Calvão  for the translation of the MDI and  Marilou Bruchon-Schweitzer ,  Eve Villemur  and  Gérard Ostermann  for their contribution to the translation of the WEL and SSES scales.
Data production The fieldwork was carried out between 2012 and 2015. A female researcher, with experience in qualitative research and fluent in Spanish, French and Portuguese, conducted the interviews following an interview guide in French, Spanish and Portuguese (approved by native speakers). The guide addressed their personal norms, representations and practices concerning eating and body. For example: "Do you believe that there is an ideal/normal weight for your health? Why? Which one is it?", "In your opinion, what are the causes of obesity?". In the case of dietitians, additional questions were included about their professional activity (supplementary material). Images of women with different body shapes were used to support the interviews. The interviews lasted between 50 min and 2 h.
Background: The MyPeBS study is an ongoing randomised controlled trial testing whether a risk-stratified breast cancer screening strategy is non-inferior, or eventually superior, to standard age-based screening at reducing incidence of stage 2 or more cancers. This large European Commission-funded initiative aims to include 85,000 women aged 40 to 70 years, without prior breast cancer and not previously identified at high risk in six countries (Belgium, France, Italy, Israel, Spain, UK). A specific work package within MyPeBS examines psychological, socio-economic and ethical aspects of this new screening strategy. It compares women's reported data and outcomes in both trial arms on the following issues: general anxiety, cancer-related worry, understanding of breast cancer screening strategy and information-seeking behaviour, socio-demographic and economic characteristics, quality of life, risk perception, intention to change health-related behaviours, satisfaction with the trial.
This shift might affect individuals (e. g. , anxiety, misunderstanding) but also society (overestimation of cancer risk in the population, stigmatisation and discrimination according to level of risk or non-participation to the screening programme). With these issues in mind, a specific work package within the MyPeBS project aims to examine the ethical, psychological and socio-economic impact of the new screening proposition. This paper describes the research protocol of this work package, including justification of its specific objectives. Objectives and corresponding analytical tools are summarised in Appendix 2.
Design of the methodology In order to meet the described objectives, this work package was designed with two complementary methodologies: a quantitative approach with questionnaires administered to each woman participating in MyPeBS, and a qualitative study consisting of 48 semi-structured interviews conducted with women randomised in the risk-stratified arm in France and in the UK. The use of qualitative methods, in addition to quantitative measures, is recommended in guidance on process evaluation  [26] , as the two kinds of methods have contrasting strengths. The quantitative questionnaires will provide measures for the previously stated objectives, at various time points during the trial. Qualitative methods will help further investigate perceptions of risk-stratified screening and collect feedback on the trial from the participants.
Participants Women from the general population (no prior breast cancer and not already identified at high risk) aged 40 to 70 are eligible if they live in a participating area from one of the six participating countries. Women are either invited to participate by the organised breast screening programme structures in each participating country or by a healthcare professional, or she can self-volunteer; indeed, information about the study was disseminated in healthcare providers' premises (private offices, public screening centres, hospitals), in the media, and through health insurances' newsletters. Candidates who are interested in participating in the trial and who are eligible with respect to the inclusion and exclusion criteria are registered and randomised via an online dedicated web platform (Eonix, Belgium), and receive a unique identification code that ensures anonymity of data treatment.
For the qualitative study, the research team will conduct 48 semi-structured interviews with women in the risk-stratified arm of the trial, both in France (n = 24) and in the UK (n = 24). The aim is to recruit six women per risk group (low, average, high and very high), in order to reach data saturation for each of those. Recruitment in France will be carried out with the help of Haut-de-France's and Ile-de-France's Regional centres for coordinating cancer screening (CRCDC). Recruitment in the UK will be carried out with help from the Manchester University NHS Foundation Trust (MFT). The interviews will provide an in-depth account of women's views and experiences of the breast cancer screening programme and allow investigation of how healthcare systems and cultural differences affect acceptability of the proposition.
When necessary, the questionnaires were translated to English, Italian, French, Spanish, Dutch, Arabic, Hebrew and Russian, which are the languages commonly used in the six countries of the trial. Translation and reverse translation to English were performed by an official sworn translator. The three versions (English, target language and back translation into English) were then proofread by bilingual professionals involved in the MyPeBS trial. A review of the online versions by the professionals involved in MyPeBS allowed for a final adjustment in the wording. The following subsections give more details on methodological aspects of these questionnaires.
Qualitative interview guide Participants will be asked about how acceptable they found the risk-stratified process, their understanding of the purpose of each phase, how they experienced receiving their risk category, if they would recommend this type of screening to their friends or family, and how the process could be improved. Demographic information to describe the sample of participants will be collected on the same occasion as the main interview. Interviews will last approximately one hour and will be conducted face-to-face, via telephone or video call, according to the Covid-19 sanitary situation and restriction measures. With the consent of participants, interviews will be audio-recorded and transcribed in the languages in which they were conducted, using an accredited transcription company, to ensure data security.
Analyses The quantitative analysis plan (see Appendix 1) includes: 1) descriptive statistics (description of categorical and quantitative variables, tests and estimation of confidence intervals); 2) bivariate analyses, subgroups comparisons and analysis of variations in time (baseline, three months, one year and four years), with appropriate tests to assess differences in groups (e. g. chi-square, Fisher and Student, Q Cochran); 3) multivariate regression models (cross-sectional and longitudinal) to model different patient reported outcomes such as comprehension of the information provided, general anxiety or cancer worry, and information-seeking behaviours. The data management and statistical analyses will be performed using Stata (StataCorp LP) and SPSS (IBM Corp). The main endpoint of this study will be measured at the end of the four years of intervention.
The qualitative data will support the interpretation of findings from the quantitative data. It will use framework analysis, a form of thematic analysis that facilitates the handling of large qualitative datasets  [53]. It involves examining qualitative data to produce themes that summarise and interpret patterns of results. The analysis will take an explicit comparative approach, to investigate differences between England and France, and will also consider how the level of estimated risk affects reactions to risk-stratified screening and how acceptable the women found this. Coding will continue until the team is satisfied that codes and themes adequately describe and capture the data and that saturation has been achieved. Data will be stored and organised within Nvivo software (QSR International Pty Ltd.
Adjustments for multiple comparisons (Bonferroni correction) do not appear to be required. According to the literature, no method for managing missing data is unanimously accepted. As a result, automatic replacement of missing data will not be used  [56]. The analyses will be conducted on all patients included with no missing data. In case of no answer, we will assume that the data are missing at random. This assumption will be tested by comparing the characteristics of respondents and nonrespondents using the Chi-square statistic. Another source of missing data will likely come from women not answering subsequent waves of the survey (for instance, questionnaires at one year, two years or four years). In other words, we may face an attrition issue. First, we will test whether attrition is non exogenous (i.
d. 2. Longitudinal models In order to analyse the changes of an outcome variable with time, longitudinal (or panel) data models will be estimated. The estimated models belong to the family of generalised linear mixed models (GLMMs). The link function and distribution of error terms will be defined depending on the nature of the dependent variable. In the GLMMs models, only the intercept will be specified as random in order to capture repetition of data across individuals. It will also be possible to account for various levels of heterogeneity across countries by including country specific random effects (multilevel model). Time-fixed effects will be included in the model to assess changes of a dependent variable over time, and interactions between time-fixed effects and regressors of interest will be included to test for changes in the impact of a variable over time.
Potential attrition bias will be assessed and accounted for using the methods described above (missing data management). MyPeBS project is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement N°755394 and underwent a full external peer review process at this step. MyPeBS has received funding from the PHRC-K research-funding programme  for the conduct of the study in France. DPF is supported by the NIHR Biomedical Research Centre in Manchester (IS-BRC-1215-20007). FJG is supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. XC is supported by grants from Instituto de Salud Carlos III FEDER (PI19/00007).
Acknowledgements We are grateful to all women participating in this study, to all 27 partners involved in the  MyPeBS  project  and  Consortium, and to all investigators, radiographers, physicians from organised screening regional structures, and research nurses. We express our thanks to  Rhiannon Hawkes  and  Lucile Hervouet , for carrying out preparatory work on the qualitative sub-study. We are also grateful to  Patient and Public Involvement and Engagement (PPI/E)  groups in Manchester, the review committee of the French national cancer league and the group of French women that reviewed questionnaires and interview guides and some methodological aspects of the protocol.
Investigated parameters Upon admission, patient data such as age, gender, cause of burn, and percentage of TBSA burnt as well as time to treatment (TTT) have been obtained. We investigated the amount of healed burns at day 15 (D15), the time to healing, and the rate of additional treatment, the duration of the hospitalisation (length-of-stay LOS), the pain level and the occurrence of infections. Pain level was obtained at the application and removal of the epicite hydro in the intervention group, and daily during the antiseptic treatment in the control group using the EVENDOL  [11]  or VAS score, whereas the average for every patient was calculated. Occurrence of infection was obtained with an initial swab and afterwards by clinical assessment. Additionally, the overall satisfaction with the treatment of the patient and/or the family was evaluated with nominal question (yes/no).
Study population In total, 60 patients have been included in the retrospective data analysis (30 per group). The mean age was 3. 4 years (+/-3. 0 years) and the mean TBSA was 4. 0% (+/-1. 94%). The TTT was 1. 5 days on average (+/-1. 5 days) and the cause of burn was scald in 95% (57/60) and contact burn in 5% (3/60) of cases. The differences between the age (p =. 147) and the TBSA (p =. 444) were not statistically significant; neither were the differences in ttt (p =. 738) or cause of burn (p =. 561). Details of the study population can be found in Table  1.
Data on sugar and was available only at baseline and five years later in 2017. Hence, a total of 100,612 participants were included for studying tobacco and cannabis use and 75,414 for studying alcohol use and diet rich in sugar and fat (Fig. 1 , Supplementary Table  S1 ). Assessment of physical exertion. Physical exertion was assessed using the Rating Perceived Exertion (RPE) Borg scale at baseline. The RPE Borg scale is a scale ranging from 6 to 20 with 6 'No effort at all' and 20 'Exhausting' that assesses the perceived physical exertion by asking the volunteers to rate their intensity of physical effort during a typical working day  19. The distribution of the RPE Borg scale by year of enrollment is shown in Supplementary Fig. S1  and Supplementary Table  S2. Volunteers with a score of ≥ 12 were considered to be exposed to high physical exertion according to the 'French National Research and Safety Institute for the Prevention of Occupational Accidents and Disease'  20.
Type of job contract and type of work were assessed as binary measures: temporary versus permanent contract and part time versus full-time, respectively. Lastly, although each of educational level, household income and occupational grade has different relationships with health, and it is well known that there is a significant decoupling between education and income as well no collinearity between these three covariates was found in this study, we run additional analyses by replacing them by socioeconomic status. Missing data were handled by multiple imputations. All P-values were two-sided with an α = 0. 05. All statistical analyses were undertaken using the SAS system software (version 9. 4, SAS Institute, Cary, NC).
Acknowledgements The authors thank the team of the " Population-based Epidemiologic Cohorts Unit " (Cohortes en population) that designed and manages the Constances Cohort Study. They also thank the  National Health Insurance Fund  (" Caisse nationale d'assurance maladie ", CNAM) and its  Health Screening Centres ("Centres d' examens de santé "), which are collecting a large part of the data, as well as the  National Old-Age Insurance Fund  ( "Caisse nationale d'assurance vieillesse", Cnav ) for its contribution to the constitution of the cohort, ClinSearch, Asqualab and Eurocell, which are conducting the data quality control.
Funding Nadine Hamieh  was supported by a Grant from " Direction de la recherche, des études, de l' évaluation et des statistiques", DREES, Ministry of Labour, France. The  CONSTANCES Cohort Study  was supported and funded by the  French National Health Insurance Fund  (" Caisse nationale d'assurance maladie ", CNAM). The  CONSTANCES Cohort Study is an "Infrastructure nationale en Biologie et Santé " and benefits from a Grant from the  French National Agency for Research  ( ANR-11-INBS-0002 ). CONSTANCES is also partly funded by  Merck Sharp & Dohme (MSD) ,  AstraZeneca ,  Lundbeck  and  L'Oréal. None of these funding sources had any role in the design of the study, collection and analysis of data or decision to publish.
Shortly after the trial, Oxford Brookes researchers invited Oxford participants to take part in a focus group at Oxford Brookes University to investigate shared cycling experiences. Seven were able to take part. Biographical, diary and focus group analysis was undertaken by authors Jones and Spencer. This involved compiling biographical summaries, separate accounts of individual DoCE entries from all 38 diaries, and transcription and analysis of the focus group discussion. The act of analysis involved complete immersion in the data by the authors and a process of constant comparison. This closeness to participant data allowed discussion, reflection, and convergence upon what were identified as shared definitions and significant key themes. Adopting an idiographic approach that recognizes the unique and subjective experiences of participants, we selected six participants who provided significant insight into their e-bike experience.
Limitations and future research This trial focused on an adult population aged 50 and above living in the Oxford and Reading areas. Findings are therefore not generalisable to the adult population across the whole of the UK, but they do provide important insights and an opportunity for comparison with how similar e-biking trials may be received. The Diary of Cycling Experience (DoCE) was primarily used as a tool to capture participant experience and meaning through written narratives. This meant we only obtained a general sense of where, when, and how people cycled and sometimes this data was incomplete. Future studies could place emphasis on capturing the 'brute facts' of travel such as the specifics (and logic) of the routes taken and distance travelled through participant mapping exercises and the inclusion of tracking through GPS and mobile phone applications.
Acknowledgements This research was part of the cycle  BOOM  project (www. cycleboom. org), funded by the  Engineering and Physical Sciences Research Council  (EPSRC; https://www. epsrc. ac. uk/) under the  UK Research Councils' Lifelong Health and Wellbeing Programme : [Grant Number  EP/K037242/1 ]. We would like to thank the participants in the cycle BOOM study, the research team and funders. Thanks to  Carlos Cámara-Menoyo  for support with the production of mapping.
We elected to utilize semistructured focus groups to allow participants to provide more spontaneous and detailed responses. The focus groups included sensitizing questions about their emotions surrounding climate change, their understanding of and beliefs about climate change, actions taken to address climate change, and various barriers and supports encountered when engaging in climate action. Focus groups with a small number of parents of younger participants (under 10 years old) helped us to better understand how their views and actions aligned with the perceptions of their children. We recorded, anonymized, and transcribed all focus groups. Three researchers (IT, LB, AW) independently analyzed the data using grounded theory and symbolic interactionism approaches. First theorized by sociologists Glaser and Strauss in 1967, grounded theory is an inductive research methodology that attempts to generate theoretical frameworks that are "grounded" in data that has been systematically collected and analyzed  (7).
Data and Methods The Eurostat-OECD PPP programme was established in the early 1980s to compare on a regular and timely basis the GDPs of the member states of the European Union and the member countries of the OECD. In the context of work on PPPs, Eurostat and OECD work with national statistical offices to gather and validate price data on a regular basis PPPs are conversion rates that show the ratio of prices for a basket of goods in one currency relative to the same goods in another. When PPPs are used to convert expenditures into a common unit, the results are valued at a uniform price level and the comparison of expenditures across countries reflect only the differences in the volume of goods and services consumed. PPPs are calculated by first gathering price information for a representative basket of the aggregate in study.