dataesr/scientific-paragraphs-categorization huggingface dataset:
Measure and Instruments Data were collected via 20-minute face-to-face interviews conducted by trained interviewers at a small private counseling room in order to protect their confidentiality. The purpose of the study, benefits, and drawbacks when participating in the study were introduced to participants, and then they were asked to join the study. We conducted a pilot survey on 20 participants of different ages and genders, and only minor changes to the wording were made in order to meet participants' preferences and culture. Data concerning socio-economic characteristics, working conditions, depression level, health risk behavior, health-related quality of life, and social support situation of participants were collected, in particular:.
Methods: Design: a prospective multicenter comparative cohort study with a follow up to 1 year after the acute episode. Participant centers: 13 hospitals in the Aquitaine region (France). Study population: patients diagnosed with a confirmed ischemic or hemorrhagic stroke included in the Aquitaine Observatory of Stroke (ObA2) cohort and voluntary to participate. Data sources are existing databases (ObA2 database and the French National Health Data System -SNDS) to collect information about care pathways, patient characteristics and stroke characteristics and Ad hoc surveys to collect information about life pathways and post-stroke sequelae. The endpoints of the study are post-stroke activity limitations evaluated by the modified Rankin score, other post-stroke sequelae (Cognitive disorders, anxiodepressive disorders, fatigue, restriction of participation) assessed by standardized and validated scales and Clusters of patients responding to pathways with common or similar characteristics.
It is also used to develop research projects around stroke management. It is a tool to provide information to decision-makers to build a regional health strategy on the organization and care chain to help them structure the care pathways. The PAPASéPA (Parcours des Patients victimes d'accident vasculaire cérébral et Séquelles Post-Accident vasculaire cérébral) project was built to address the lack of information on the components of the downstream life course and the link between these components and sequelae. In the ObA2 cohort dynamic, detailed data on the components of the life pathways, on the link between life pathway and sequelae could be used to better identify the needs to improve the health care system. We are in a global perspective of analysis of the life pathway of stroke patients, pre-hospital, hospital and post-hospital phases, and this for 1 year after acute care.
Study design The study design is an observational prospective cohort of stroke patients included in ObA2 with a patient follow up period for 1 year following stroke. Continuous data collection of care pathways will be carried out from stroke throughout the year of follow-up from existing databases (the ObA2 data base and the French National Health Data System (Système National des Données de Santé -SNDS); moreover, ad hoc collection of sequelae, pathways and socio-economic and environmental data is planned at three times (initial episode, at 3 months and 1 year after initial episode) (Fig. 1 ). The cohort is divided into three strata based on the severity of the patient's initial clinical condition, as measured by the NIHSS score (≤6,  [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] , > 16) at the end of the hospital stay (Fig.
Data sources and data collection Data sources Three types of data sources are considered (Table  1 ): Extraction of data from two existing databases: the ObA2 cohort and the French National Health Data System (Système National des Données de Santé -SNDS). The extractions from existing databases will provide the main information about care pathways, patient characteristics and stroke characteristics. The extraction from the ObA2 database will provide information about patient socio-demographic characteristics (date of birth, sex, place of residence), clinical (medical history, risk factors, medical treatment before hospital, type of stroke) and acute phase pathways (prehospital: date/time start of symptoms, date/time call to general practitioner, date/time call to emergency medical services, place of occurrence of the stroke, mode of transport, date/time of admission to hospital; hospital stay: initial stroke management, complementary investigations, in-hospital complications, hospital rehabilitation and medico-social care; at discharge: NIHSS, medical treatment at discharge, patient referral) (Table  1 ).
The National Health Data System regroups healthcare reimbursement data from in-patient and outpatient care, as well as causes of death. It provides data on claims paid for each patient by the French National Social Security System and is therefore the main source of information on healthcare costs. This database contains  Anxiety-depressive disorders (HADS**)(Self-assessment) 6  ✓ ✓ Fatigue (FSS***) (Self-assessment) 6  ✓ ✓ Activity limitations (BI ǂ) (Self-assessment)  3 Number / type / duration of hospitalization in medicine or surgery, rehabilitation, psychiatry departments. Hospitalization at home; Number / type of medical and paramedical consultations at hospital; Medical ambulatory care: number / type of medical consultations (general practitioner, neurologist, functional rehabilitation physician, cardiologist) and number of care periods, total duration of each care period / type of paramedical consultations (physiotherapy; speech therapy; orthopsy); Quantity of drug deliveries (antiaggregant, antihypertensive, statin or anticoagulant treatment, analgesic), external medical consultations for neurology, rehabilitation, cardiology in health institutions; Vital status of patients 4 Patient referral (admission to the hospitalization area of the institution, transfer to another institution), Level of education (INSEE classification); Marital status (Married -Accessed -Partner; Separated -Divorced -Widowed; Single); Cohabitation status (couple; in family-friends; institution), Ability to drive (yes, no); Place of life (home, institution, medico-social structure), Medical-social care (services to support social life, services to help and support at home, services to provide nursing care at home, services to provide medical and social support), Family/Caregiver (yes, no); Development and technique to improve autonomy (yes, no); Legal background (Curatorship, Guardianship) 5 Data collected by telephone by the nurse 6 Postal delivery to the participant's home patient data (age, sex, place of living, long-term and chronic diseases, date of birth, date of death, health insurance scheme, benefit of free complementary insurance for lower-income people), all consultations and visits to General Practitioners (GPs) and ambulatory care specialists (but nothing about their content), all medical technical procedures, all dispensed medical devices and drugs, all lab and diagnostics tests but not their results, and providers' level data (their activity and sales turnover, geography, prescribing behaviour).
In addition, mortality and cause of death data are also available in this database. Extractions from the SNDS will cover the time period from September 2019 to August 2020 and provide information about the post-stroke care pathway (Table  1 ): • Number / type / duration of hospitalization in medicine or surgery departments, rehabilitation department, psychiatry department and hospitalization at home. Hospitalisations will be classified into three categories corresponding to hospital stays with different clinical meanings with regard to the evolution of stroke (readmission for management of stroke recurrence and post-stroke complications, readjustment for post-stroke follow-up and secondary prevention of stroke and re-hospitalizations to manage a clinical situation not related to stroke); • Number / type of medical and paramedical consultations at hospital; • Medical ambulatory care: number / type of medical consultations (general practitioner, neurologist, functional rehabilitation physician, cardiologist) and of paramedical consultations (physiotherapy, speech therapy, orthopsy), number of care periods, total duration of each care period; • Quantity of drug deliveries (antiaggregant, antihypertensive, statin or anticoagulant treatment, analgesic); Vital status of patients.
Sample size selection The primary endpoint is the mRS, measured at 3 months and 1 year after the stroke. Based on data from a pilot study, we assume a prevalence of independence of 51%, dependence of 30% and death of 19%. Several simulations were performed by varying the frequency of exposure to the risk factor studied (very rare to very common). By fixing the risk of first species at 5% and the power of the association test at 80%, to show an odds ratio of at least 2 (odds ratios to move to a higher class: independence to dependence or death, dependence on death), 368 patients should be included to cover a change in exposure to the risk factor studied, ranging from 20% (rare exposure) to 80% (frequent exposure). The study is stratified on the NIHSS score assessed at inclusion (at the end of the hospital stay for acute episode management) in 3 categories (≤6, 7-16, > 16) and needs to include 368 patients per category of NIHSS or 1104 patients in total (software R v3.
Statistical analysis Analysis strategy The analysis of the assessment criteria will be carried out on available data, i. e. without any replacement of missing data. For the analysis of the primary endpoint, a sensitivity analysis of missing data, using a multiple imputation method, may be considered. The analysis will be carried out using the SAS 9. 3 software (or later version) considering a risk of first species fixed at α = 5%. A statistical analysis plan will be defined blind data. Statistical methods Qualitative variables will be described in terms of numbers, percentages, and 95% confidence intervals according to the exact binomial distribution. Comparisons will be made by the Chi-square, corrected Chi-square or exact Fisher test. A logistic or polytomial regression model will be used to take into account the adjustment variables.
Ethics All patients will be informed of the objectives of the study and invited to voluntarily participate at the first contact and at the 3 months and 1 year follow-up visit. Patients who will agree to participate will provide oral consent. All information will be kept confidential. The ObA2 observatory has received the French authority in charge of data protection (CNIL -authorization n°911, 201) authorizations necessary for the processing of nominative medical data. Authorizations with the Comité de Protection des Personnes (CPP-number 2018-A01919  -46)  and CNIL (authorization n°918,423 (DR 2019-088) have been specifically received for the PAPASépa project.
Feasibility of the proposed approach In order to help develop and ensure its feasibility, all the necessary teams and skills are involved in the project: neurologist clinicians, researchers in health services research who know the databases and have the skills in the SNDS data processing, an operational team from the ObA2 cohort, and finally medical informatics teams who will be able to develop data-visualization methods for pathway analysis. Moreover, the ad hoc collection of sequelae has been tested in a pilot survey and showed its feasibility, its acceptability for patients and caregivers. Concerning the technical and ethical conditions of the links between the existing databases, respective reconciliations of these databases have already been tested and will be carried out in a secure manner after prior approval by the CNIL (Commission Nationale Informatique et Libertés).
Justification of methodological choices Study design Research on pathways must integrate a longitudinal dimension and rely as much as possible on large cohorts. Our project is based on a prospective multicenter cohort (ObA2 cohort), following the life pathway and sequelae of stroke patients for 1 year after the acute episode. Such a design will allow to approaching the place and the role of the temporal and spatial pathway dimensions on the functional prognosis of patients with stroke. The project relies on data from ad hoc collection and extraction of data from three existing databases. The combination of these sources of information will allow the understanding of the heterogeneity of the life pathway of stroke patients as a whole, in all its dimensions, temporal and spatial, from the acute episode up to 1 year of follow-up.
The cohort will be divided into three strata according to the severity of the patient's initial clinical condition, as measured by the NIHSS score at hospital discharge. The initial severity of stroke is one of the variables most strongly associated with functional prognosis after stroke and influences the type of life pathway of stroke patients. Thus, it constitutes a potential major confounding factor in the relationship between stroke and sequelae. The NIHSS score at the exit was preferred to the NIHSS at entry because the patient's pathway is more strongly influenced by the level of hospital dependence at discharge than at entrance, major progress being potentially made during the acute phase of stay. Other major potential confounding factors, including clinical patient characteristics and elements of the acute phase care pathway, already identified as predictive factors on functional prognosis, are collected and considered in the data analysis (variables related to the patient's previous condition, variables related to stroke and variables related to the patient's care pathway prior to hospitalization).
Management of the evolving character of the events collected The three times ad hoc collection and the continuing and prospective collection of pathway events from existing databases will allow the analysis and the management of the evolving nature of the main study issues: sequelae, socioeconomic environment and health events during the year after stroke. This evolutional process is major to describe because it modifies the patient pathway itself. The evolving character of the sequelae throughout the post-hospital journey requires the use of adapted statistical model. This polyptic regression model will analyze the factors associated with sequelae at 1 year, while taking into account the degree of these sequelae at 3 months.
Life pathways: perimeter Despite a collective awareness, as to the inadequacy of the organization of the health system, different realities exist regarding the notion of pathways  [38, [44] [45] [46]. In the PAPASéPA project, we adopt the global conception of the life pathway of stroke patients. All the elements of care but also the context of life in which the patient evolves (family and social environment, financial aid, income, adaptation of lifestyle and environment, etc. …) will be taken into account. However, life pathway data are mainly collected during phone interviews using closed-ended questions. Responses may lack of precision and could be not exact. In order to obtain a more precise description of these life pathways access to databases such as the CDAPH (Commission for the rights of disabled persons to independence) would be necessary.
Representativeness of cohort compared to stroke occurring in the Aquitaine region A total of 13 health facilities are actively involved in the PAPASéPA project. They include all types of stroke facilities: 5 stroke units, 2 hospitals with neurologist and 6 hospitals without a neurologist. They are spread throughout the Aquitaine region (former Aquitaine region). Their annual stroke patients queue ranges from 70 to more than 1000. In 2016, these 13 centers cared for 5230 stroke patients, which represented 68% of strokes registered in the 2016 regional PMSI Aquitaine database. The comparison between the 2016 ObA2 cohort of these 13 centers and the 2016 PMSI stroke database showed similar age and type characteristics of stroke. Everything suggests that these 13 centers make it possible to constitute a cohort of stroke patients representative of the population of patients treated in Aquitaine for stroke.
Objective: The objective of this review was to analyse how researchers conducting studies about mobile health applications (MHApps) effectiveness assess the conditions of this effectiveness. Study design: A scoping review according to PRIMSA-ScR checklist. Methods: We conducted a scoping review of efficacy/effectiveness conditions in high internal validity studies assessing the efficacy of MHApps in changing physical activity behaviours and eating habits. We used the PubMed, Web of Science, SPORTDiscus and PsycINFO databases and processed the review according to the O'Malley and PRISMA-ScR recommendations. We selected studies with high internal validity methodologies (randomised controlled trials, quasi-experimental studies, systematic reviews and metaanalyses), dealing with dietary and/or physical activity behaviours; covering primary, secondary or tertiary prevention and dealing with behaviour change (uptake, maintenance).
Full electronic search strategy We performed a literature search using the following keywords: BEHAVIOR AND 'NUTRITION OR DIET' AND 'SMART OR EHEALTH OR MHEALTH' AND 'HEALTH PATHWAY OR COACHING OR E-COACHING' AND CARE. The keywords were chosen during a meeting with all the authors. We searched in the PubMed, Web of Science, SPORTDiscus and PsycINFO databases. These databases were chosen because they are multidisciplinary, including human sciences. They fit our research objective of selecting experimental studies. We searched for all original (referring to original research) and methodological articles indexed between January 2005 and January 2017 in English or in French and selected relevant articles according to the following criteria: assessing the effectiveness of patient-focused smart devices and applications; evaluation with high-internal validity methodologies (randomised controlled trial, quasi-experimental study, systematic review, meta-analysis); dealing with dietary and/ or physical activity behaviours; covering primary, secondary or tertiary prevention; and dealing with behaviour change (uptake, maintenance).
Data analysis Our aim was to understand how researchers assess effectiveness conditions in their studies. First, we conducted a description of articles covering eight dimensions defining the scope of assessment of apps: characteristics of the population, state of health of this population, health determinant targeted, design, tools used, activities included in MHApps, level of action and outcomes in terms of behaviour change. Table  1  shows the eight scoping dimensions with subcategories and objects for analysis. Second, we analysed how the mechanisms of effectiveness were reported. We considered the mechanisms as per Michie's definition. 18 In the articles, we looked more specifically for: The behaviour change techniques (BCTs) used, according to the taxonomy by Michie et al. 18  and Cane et al.
Acknowledgements Pr  R emi Gagnayre ,  Laboratoire Educations  et  Pratiques de Sant e (LEPS) ,  EA3412 ,  Universit e Paris13-Sorbonne Paris Cit e. Pr Pierre Lombrail, Laboratoire Educations et Pratiques de Sant e (LEPS) ,  EA3412 ,  Universit e Paris13-Sorbonne Paris Cit  e.
The EUREQUA project raises the issue of the definition and evaluation of the environmental quality of neighbourhoods. The approach consists of integrating and cross-referencing observable data characterising the physical environment and people's perception of their quality of life. The study area is a neighbourhood in Toulouse (France) with high social and typomorphological diversity, subject to noise and air pollution nuisances. Three 3-day field campaigns were organised in January, April, and June 2014. Instrumented and commented walks took place three times per day. For each one, measurements of physical environmental parameters and surveys were performed simultaneously at six locations in the neighbourhood. The study focuses on microclimate and thermal comfort issues. It aims to compare in situ meteorological data of air temperature, humidity, wind speed, and mean radiant temperature, with quantitative results rating human perception of heat, humidity, wind, and thermal comfort.
The present study examines the link between the perception and measurement of meteorological conditions through the analysis of experimental data combining surveys and measurements. From data collected in a single neighbourhood in the city of Toulouse (France), but in several outdoor spaces and at different seasons, we specifically investigate to what extent people are sensitive to local variations in temperature, humidity, and wind conditions from one place to another, how this can influence their perception of thermal comfort and, finally, if other perceptive dimensions come into play. This is part of a more holistic approach that aims to define and qualify environmental quality at the neighbourhood scale, especially for the purpose of enriching the diagnostic phase in urban requalification programs, and ultimately providing a simplified protocol to stakeholders in charge of urban development.
Statistical methods for data analysis Data were analysed using R. 3. 2. 3. software  (R Core Team 2015). Two principal component analyses (PCA) were performed using the ade4 R package  (Dray et al. 2007 ) in order to explore the effect of seasonality and sites (stop points) on micrometeorological measurements and microclimate perceptions. Then, a co-inertia analysis (CIA) was carried out between the two PCA to investigate which microclimate measurements and perceptions are correlated, considering that the CIA provides co-inertia axes with the maximum possible covariance with variables in each of the two data sets (measurements and perceptions). The strength of co-inertia is assessed using the RV coefficient, which is the coefficient of correlation between the two datasets, ranging from 0 to 1 (high correlation).
2011; Maras et al. 2016; Chow et al. 2016) , and then, at a secondary level, by the site effect, i. e. by the heterogeneity of the urban landscape (e. g. land cover properties, morphological parameters, materials) characterising the six stop points. Seasonal distinctions are made in the same way in both PCA, i. e. June and January IOPs are opposed, with April IOP being intermediate. Stop points are also distinguished in the same way in both PCA within a given IOP, according to wind, except for T4 and T5, for which it is assumed that factors other than microclimate are involved. These findings are reinforced by the co-inertia analysis (CIA) performed between the two PCA related to perceptions and measurements (Fig. 3c ). CIA highlights a strong correspondence between the two datasets (RV = 0.
In the Framework of the IEA EBC Annex68 Subtask 1 working subject, we aimed at defining an indoor air quality index for residential buildings based on long-and short-term exposure limit values. This paper compares 8 indoor air quality indices (IEI, LHVP, CLIM2000, BILGA, GAPI, IEI Taiwan, QUAD-BBC and DALY) by using the French IAQ Observatory database that includes pollutant concentration measurements performed in 567 dwellings between 2003 and 2005. This comparison allows to make a relevant analysis of each index and determines their pros and cons i. e. the calculation method, selected pollutants, threshold concentrations, subindices and their aggregation. From this analysis, a new index is proposed in order to be as consistent as possible in regards of health impacts by taking both long-and short-term exposure limit values into account.