dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion The MOVING physical activity framework and database are innovative tools that support reporting, categorising and monitoring of physical activity policy actions that will work alongside the NOURISHING framework and database. These physical activity policy tools allow stakeholders such as researchers, civil society organizations and policy makers to quickly identify both gaps and strengths in government action and therefore assess where there is scope for improvement within and across countries. Keywords: Physical activity policy, policy database, policy actions, policy framework Abstract citation ID: ckac095. 006 P01-06 Physical activity and non communicable diseases in France Roxane Berjaoui 1 , Christele Gautier 2 , Nathalie Joannard 1 1 European and international affairs, French Ministry of Health and Prevention, Paris, France 2 Sports direction, French Ministry of Sports and the Olympic and Paralympic Games, Paris, France Corresponding author: christele.
Methods We assessed the SWETT-Football program -a communitybased walking football exercise program for middle-aged and older male patients with T2D. The program was tested in Portugal through a scientific project (NCT03810846) funded by FIFA (FIFA Research Scholarship 2018). One season of this program consists of three sessions per week (60 minutes per session) during nine months (October to June). For the calculations, we considered a total of 40 patients (two groups of 20). We calculated the direct costs of one season for the host institution: 216 hours of renting a sports hall and hiring human resources (a football coach and a nurse); cardiac stress tests and sports insurance for the participants; sports equipment (balls, cones, vests); vital signs monitoring equipment (blood pressure, heart rate and capillary blood glucose); logistical equipment (disposable and non-disposable); and technical training.
Background There is an emerging body of knowledge regarding beneEts of outdoor activity on well-being, restoration and mood enhancement. This pre-post study explored psychological outcomes in groups carrying out exercise classes in outdoor and indoor settings. An aim looks to environment in group classes for physical activity programs for population health. Research Questions: (1) What are the psychological outcomes after a green exercise session (2) Is there a difference in psychological scores between indoor and outdoor exercise programs? Methods Two groups of subjects undertaking similar exercises for one hour, in two settings: a Etness studio (N = 19) and a city park (N = 15), subjects completed the Subjective Exercise Experience Scale (SEES) prior to and post classes. Paired t-tests for dependent groups identiEed differences in the three categories of SEES, computed by IMB SPSS Statistics 20.
Methods A longitudinal observational study of patients with ischemic heart disease, heart failure, cardiac arrhythmia, valvular heart disorder and inflammatory heart diseases treated on cardiac wards  (2015) (2016)  in Stockholm, Sweden. Data on PA-levels and SED prior to admission were collected by validated questionnaires during inpatient care. PA level a regular week was calculated by an index (3-19 points) including everyday PA and exercise. The cut-off of insufficiently physically active was set to > 9 points. Individuals' reporting !7 hours of sitting a normal day were categorised as high SED. Differences in PAlevel and SED between different diagnose groups were ii88 European Journal of Public Health, Volume 32 Supplement 2, 2022 Downloaded from https://academic. oup. com/eurpub/issue/32/Supplement_2 by guest on 12 September 2022 explored by Benjamini-Hochberg procedure.
Methods We analyzed data of 981 workers in a Danish cohort  (DPHACTO 2012 (DPHACTO -2014)). We assessed physical behaviors at work at baseline using thigh-worn accelerometers, and classified behaviors at work as sitting, standing, LIPA, and MVPA. Over 1 year follow-up, workers reported sick leave days due to musculoskeletal pain using text messages at 4-week intervals (14 waves). We used Latent class growth analysis to distinguish sub-groups with different trajectories of sick leave. We analyzed associations between time-use in physical behaviors and sick leave trajectories using multinomial regression analysis with adjustment for age, gender, BMI, smoking, and accelerometry-measured physical activity during leisure. Compositional data analysis was used to account for the co-dependency of different behaviors.
Methods In this longitudinal study, data were collected in the autumn 2019 and in follow-up measurements in the spring 2021. Physical activity and sedentary time were measured for seven consecutive days by accelerometry (Actigraph). The mental health outcomes, health-related quality of life (HRQoL) and psychosomatic health were measured with questionnaires (KIDSCREEN-10 and PSP). ANCOVA analyses were applied to estimate the associations between change in physical activity patterns and mental health outcomes.
Methods The study comprised 593 participating adults (248 males and 345 females). The data was collected during February-May 2019 using quota sampling by age and gender representing the Hungarian adult (18+) population. The physical activity was measured by RM 42 hip-worn triaxial accelerometer for 7 consecutive days using vigorous, moderate to vigorous activities and daily steps scores. The walkability was measured by walking and cycling facilities subscale (10 questions) of NEWS-Hungarian questionnaire. The subscale measured the environment's possibilities and quality for walking and cycling. Data were presented as mean AE standard deviation, Spearman's rank correlation was used to analyse data using SPSS 24. program, where level of significance was set at p > 0. 05.
Despite the accumulating evidence on their effectiveness, there are currently no international guidelines available to inform the design of such interventions. The key elements and processes employed vary both within and between countries. This systematic review aims to address this frequently overlooked topic by identifying elements that are predominant in international ERS. Methods Scientific databases (PubMed, Scopus) and grey literature sources were systematically searched. In order to collect the information relevant for understanding and visualizing all ERS models, a broad spectrum of document types was considered eligible for inclusion, i. e. randomized controlled or pragmatic trials, cohort studies, case-control studies, case series, case reports, qualitative studies, economic evaluations, mixed designs, policy documents, and official governmental reports.
Results As result of the co-creation process, the following key elements were defined to be part of the ERS: Screening, short counselling and provision of a referral form by a physician; initial assessment, counselling, individual PA recommendations, re-assessment and follow-up by exercise professionals. Additional aspects considered important for the implementation of the ERS were ensuring good communication and feedback between all participating health professionals, as well as an overview of all local physical activity offers and exercise professionals (database). These preliminary findings were combined into a draft of the ERS.
Background The extent to which people are physically inactive is dependent upon social gradients. Numerous studies have proven that individuals with social disadvantages are not active enough. Parallel to this, several researchers have raised concerns that public health interventions may increase inequalities in the population. However, little is known about the success of community-based physical activity promotion among individuals with social disadvantages. Hence, our goal was to identify the characteristics of successful interventions within this field. Methods From March 2015 to March 2019, a search for systematic reviews dealing with community-based physical activity promotion was carried out using the databases PubMed, Scopus, PsycInfo/SPORTDiscus (via Ebscohost), ERIC and IBSS (via ProQuest).
Methods During April-May 2021, 107 people (76 men, 31 women) from city of Jijel (Algeria) participated in the study (Purposive Sample). Participants were provided with a mobile application (APK file) linked to a database that collects and arranges data and mapped with ArcGIS software. The experiment lasted for 30 consecutive days. Where the application was programmed to start automatically at 06:00 am to 09. 00 am. The application maps participants' track, and identifying places where deceleration occurs.
This study aimed to investigate to what extent office workers changed their temporal pattern of sedentary behavior during days WFH compared to WAO, considering age and gender as potential moderators. Methods Data were collected from May to December 2020 in office workers (n = 199). Their mean age was 42 (SD 10) years and 55% were women. Physical behaviors were measured using a thigh-worn accelerometer (AxivityAX3) for seven consecutive days. A diary identified working hours, time-in-bed and days WFH or WAO. Time-use was classified as short (0-5 min), moderate (5-30 min) and long bouts (>30 min) of sedentary behavior (SB), non-SB, and time-in-bed during workdays (WAO and WFH) and non-workdays. We used Compositional data analysis to express data as 24-hour compositions and linear mixed models to estimate difference in 24-hour compositions between day types (within worker), including age and gender as covariates and moderators.
Keywords: Working from home, sitting, time-in bed, compositional data analysis area is the lack of accessibility to PA offers. The use of videoconferencing is a promising solution in terms of acceptability and efficiency to promote PA. However, the acceptability (initial stage of the technology adoption process) of the videoconferencing is still underexplored, as well as its role in promoting PA in rural areas. The purpose of this study was to explore, through the perceptions of the elderly and policymakers, the mechanisms of acceptability of the development of PA interventions using videoconferencing for elderly living in rural areas. Methods Elderly (n = 10) and policymakers (n = 12) from 11 different rural town of the South of France participated in the study. Semi-structured individual interviews were conducted, where a video presentation of PA interventions using videoconferencing was played as support.
Results Completed questionnaires were received from 133 students. Although the majority of the students (67%) have a positive attitude towards m-Health applications, only half of them (47%) believe that m-Health applications have affected (better and much better) their health-promoting behavior. Data about the use of m-Health applications into their future clinical practice shows that medical students will recommend these applications to their patients (60%), but less than half of them (39%) feel confident with the protection of their patients' personal data.
Increasing and maintaining physical activity (PA) can be challenging. The aim of this study was to evaluate the effects of a pedometer-based intervention on PA, with a compositional data analysis (CoDA) approach, in individuals with prediabetes or type 2 diabetes. Methods Longitudinal data on 188 participants with prediabetes and type 2 diabetes (40% female, mean age = 64. 1 years) from a three-armed randomized controlled trail, the Sophia Step Study, was used. The three groups were a multi?component group (self?monitoring of steps with a pedometer, together with group (12 occasions) and individual counselling (10 occasions)), a single?component group (self?monitoring of steps with a pedometer, without counselling) and a standard care group. PA (moderate-to-vigorous PA (MVPA), lightintensity PA (LIPA) and sedentary behaviour (SB)) during the awake time were measured with ActiGraph GT1M accelerometer at baseline, 6, 12, 18 and 24 months.
Acknowledgments The conference is jointly organized by  UniversiteCote d'Azur and WHO/Europe  under the patronage and with the funding support of the Acknowledgements This study was performed with the support of the  International Atomic Energy Agency  ( CRP E4. 30. 24 ; RAF 6042 ). Keywords: BMI z-score, physical activity, accelerometer, children, adolescent Acknowledgements This project is financially co-funded by the  Erasmus+ Sport Acknowledgements  Acknowledgements This study was performed with the support of the  International Atomic Energy Agency  ( CRP E4. 30. 24 ; RAF 6042 ).
Methods In June-November 2021, we searched for Gasteranthus extinctus in three large Ecuadorian herbaria (QCNE, QCA, GUAY) and in GBIF (https://www. gbif. org) data from Ecuador, Colombia and Peru (DOIs: https://doi. org/10. 15468/dl. x7j8cj, https://doi. org/10. 15468/dl. 3anwv6 and https://doi. org/10. 15468/dl. ajrxp3, respectively). Those searches revealed no records beyond those mentioned in the species protologue. On 13-15 November 2021, we visited the Centinela Region to search for G. extinctus and other putative Centinela endemics (see Appendix 1 for notes on geographic names). Over three days of fieldwork, our 10-person team travelled the extensive network of rural roads by truck, searching for remnants of primary forest above 500 m. We observed > 20 such remnants (Fig. 2 ), most of them strips of forest along ravines or small (< 5 ha) patches on slopes too steep for the most common land uses in the region: dairy farming or plantations (mostly banana, balsa, Gmelina arborea and cacao).
Dodson in the 1980s, he confirmed that the plants were G. extinctus. These populations were vouchered via five herbarium specimens under five different collector series (Appendix 1). The majority of these sheets will be deposited at four Ecuadorian herbaria (GUAY, QCA, QCNE and QUSF); duplicates will be deposited at herbaria outside of Ecuador (likely F, SEL, US, WAG and P). For all specimens, 1-3 leaves were stored in silica gel desiccant for genetic analysis; these were deposited at QUSF. Permits for herbarium voucher and DNA collection are listed in the acknowledgements section of this paper. Field photographs will be linked with herbarium specimen databases and made available on GBIF. We have also posted three field photographs of G. extinctus on the community science platform iNaturalist (https://www.
Conservation status Gasteranthus extinctus is currently considered Critically Endangered, both globally  (Clark et al. 2004 ) and in Ecuador  (León-Yánez et al. 2011). The newly-discovered populations necessitate a reassessment of the species' threat status. We analysed our six unique occurrences with the R package ConR  (Dauby et al. 2017 ) and identified two subpopulations and four locations, based on a 10-km radius for equal impact. We estimated an area of occupancy (AOO) of 106 km 2 and an extent of occurrence (EOO) of 20 km 2 (grid resolution = 2 km). However, the species' habitat is severely fragmented within this area. These values would place G. extinctus in the Endangered (EN) category (AOO < 500 km 2 , EOO < 5000 km 2 , locations < 5). The massive scale of the habitat loss since its discovery and the lack of formal protection means that the 'B' criterion applies, resulting in a new proposed assessment of EN B1(a,b(ii,iii,iv)) +B2  (a,b(ii,iii,iv) ).
Acknowledgements We thank local landowners and Ecuador's  Ministry of the Environment  for their permission to visit the remaining forests at  Centinela  and collect plant specimens there. Leaf samples and herbarium vouchers were collected under permit  MAE-DNB-CM-2018-106  and TLPC under Number  MAE-ARSFC-2020-0-0473. We thank  Carolina Reyes-Puig  for assistance with these permits. We are grateful to the  National Herbarium of Ecuador (QCNE) of Ecuador's National Biodiversity Institute (INA-BIO ) for facilitating herbarium work and specimen processing and offer special thanks to  Dr Marcia Peñafiel  and  Dr Francisco Prieto. We thank the  Pontificia Universidad Católica del Ecuador (QCA)  and  Universidad de Guayaquil (GUAY) Herbaria  for facilitating herbarium work, especially  Susan León-Yánez  at  QCA.
Most clinical texts including breast cancer patient summaries (BCPSs) are elaborated as narrative documents difficult to process by decision support systems. Annotators have been developed to extract the relevant content of such documents, e. g. , MetaMap and cTAKES, that work with the English language and perform concept mapping using UMLS, SIFR and ECMT, that work for the French language and provide concepts using various terminologies. We compared the four annotators on a sample of 25 French BCPSs, pre-processed to manage acronyms and translated in English. We observed that MetaMap extracted the largest number of UMLS concepts  (15, 458), followed by SIFR (3,784), ECMT (1,962), and cTAKES (1,769). Each annotator extracted specific valuable information, not proposed by the other annotators.
Introduction Multidisciplinary tumor boards (MTBs) provide a collaborative and multidisciplinary approach to cancer care, bringing together surgery, oncology, radiology, and pathology specialists to optimize decision making and care coordination. But, the benefits of tumor boards, which have long been taken for granted, are recently being challenged. Positive outcomes from MTBs depend on the presence of qualified and effective faculty, good preparation of patient cases, format and structure of the meeting, efficient leadership, and contributive interactions among MTB physicians  [1]. Clinical decision support systems (CDSSs) are software components that aim to support clinicians in their decision-making process. CDSSs have been used in many medical areas. They have proven to improve the quality of patient care by increasing the compliance of clinician decisions with clinical practice guidelines (CPGs)  [2].
This system is expected to be used at MTBs of the Tenon hospital (AP-HP, Paris, France). Decision support systems usually rely on structured clinical data processing. However, breast cancer patient summaries (BCPSs) used to orally present a patient history during MTBs are expressed as natural language clinical notes. Because, we were lacking an annotated corpus of BCPSs, we decided to use automatic semantic annotators and indexers to structure the relevant content of natural language BCPSs. Currently, two systems  [6]  are widely used in the biomedical field for the English language, MetaMap  [7]  and cTAKES  [8]. Since we will work on a corpus of French BCPSs, we considered two systems that work for the French language, i. e. , SIFR  [9]  and ECMT  [10]. We implemented the four annotators and compared the structured data produced by each of them on a sample of BCPSs used in French with the annotators able to process French summaries, and with the same sample of BCPSs translated beforehand in English for the annotators able to process English summaries.
Annotator tools MetaMap  [7]  was developed by the National Library of Medicine to map biomedical texts to concepts in the Unified Medical Language System (UMLS). The tool uses a hybrid approach combining natural language processing, knowledge-intensive approach, and computational linguistic techniques  [11]. cTAKES  [8]  (Clinical Text Analysis and Knowledge Extraction System) uses rule-based and machine learning techniques to extract information from clinical text. Both MetaMap and cTAKES use UMLS to extract and standardize medical concepts. ECMT (Extracteur de Concepts Multi-Terminologiquehttp://ecmt. chu-rouen. fr) is a web service inspired by the CISMef algorithm for information retrieval with the Doc'CISMeF search engine and F-MTI  [10]  which is a multiterminology automatic indexer.
ECMT works for the French language. There are two query modules: one default module based on a bag of words algorithm  [10]  and one expanded module based on textual indexing, using Oracle text indexing. ECMT does not allow one to choose the ontology to be used by the annotation process. The annotator works with seven terminologies, and supports semantic expansion features  [12]. SIFR (Semantic Indexing of French Biomedical Data Resources -http://bioportal. lirmm. fr/annotator) Annotator  [9]  is an openly available web service enabling both recognition and contextualization of concepts from 30 medical terminologies and ontologies. The annotator service processes textual descriptions, tags them with relevant biomedical ontology concepts including UMLS, expands the annotations using the knowledge embedded in ontologies, and contextualizes the annotations before returning them to the users in several formats.
Executing the annotators on the BCPS corpus Many components bundled in cTAKES are available and can be used in multiple ways. We used the Default Clinical Pipeline, which produced the most commonly desired output. This includes annotations for anatomical sites, signs and symptoms, procedures, diseases and disorders, and medications. For each annotation, normalized UMLS CUIs are provided, as well as markers for negation, uncertainty, and subject. MetaMap maps text parts to concepts from the UMLS Metathesaurus. Text is processed through a series of modules and broken down into components that include sentences, phrases, lexical elements, and tokens. Variants are generated from the re-sulting phrases, and candidate concepts from the UMLS Metathesaurus are retrieved and evaluated against their phrases, taking into account negation.
ECMT is licensed by the University Hospital of Rouen, France and it was possible to process data locally. The ECMT output is an XML file that contains the identified concepts in the seven terminologies used by ECMT. The current version does not provide UMLS CUIs directly nor contextual information (such as negativity). SIFR bioportal is openly accessible and offers docker packaging. The annotator can be used via a REST-API, the workflow generates a final json-ld output or converts it to different formats (e. g. , BRAT). The result contains UMLS CUIs for each extracted concept and includes a module for identifying negations  [14]. Post-treatment of the outputs of each system cTAKES outputs are XMI files, readable using the UIMA CAS Visual Debugger (CVD). We processed the files using a Python parser and generated a table with four columns: extracted concept, UMLS CUI, negation, and subject.
For MetaMap, we used the Python wrapper Pymm for extracting candidate and mapping concepts. Pymm parses the XML output of MetaMap. Extracted information included matched word, UMLS CUI, negation, semantic type. For the two French annotators, we implemented a script that takes the output of each system and processes it: x SIFR: the UMLS CUI, the matched concept, and negation were extracted from the json files x ECMT: the matched concept, the terminology from which it was retrieved, and its code in that terminology were extracted from the XML output. In order to compare the results by using the UMLS CUIs to avoid problems in the translation of the matched text, we reused SIFR on the words and phrases matched by ECMT so we could obtain, if available, the UMLS CUIs for the concepts extracted by ECMT.
Results The four annotators were compared on a sample of 25 BCPSs randomly extracted from the corpus. Results are shown in Table  1  for four random BCPSs among the 25. On the 25 BCPS-selection, we observed that MetaMap was the system that extracted the largest number of UMLS concepts  (15, 458) , SIFR is the annotator with the second higher number of concepts extracted (3,784), followed by ECMT (1,962), and cTAKES  (1, 769). Coverage intersections between systems for the same language (e. g. ECMT + SIFR, or cTAKES + MetaMap) are more frequent than in case of "multilingual" intersection (e. g. ECMT + cTAKES, or SIFR + MetaMap, etc. ) (See Table  1 ). Within the sample of 25 BCPS , a total of 184 different UMLS CUIs were detected by all four systems. Figure  2  shows the distribution of these 184 concepts grouped by their UMLS semantic type.