dataesr/scientific-paragraphs-categorization huggingface dataset:
Results In total, 93,351 hospitalizations of patients with COVID-19 were recorded in the SI-VIC registry, of which 18,348 (19. 6%) were ICU admissions. Complete data were available for 17,351 ICU admissions (95. 6%), including 2228 transfers (12. 7%). The flowchart of the study population is shown in Fig. 1. The mean age of patients admitted to the ICU was 63 ± 15. 2 years; 69% were men. Transferred patients were younger than non-transferred patients (intra-regional patients 61. 0 ± 13. 2 years, interregional patients 61. 7 ± 10. 9, vs non-transferred patients 63. 0 ± 15. 5, p > 0. 0001). Patient characteristics are detailed in Table  1. The highest number of ICU admissions was during the week from 23 to 29 March 2020, and this week accounted for 46. 5% of inter-regional transfers and 33% of intraregional transfers during the study period.
Further studies are warranted to investigate the factors driving the LOS. An increased LOS in the ICU exposes the patient to a higher risk of healthcare-associated infection and this needs further exploration  [29]. Conversely, patients transferred intra-regionally were readmitted to the ICU more often than other patients which may be explained by premature discharge, where the care was not optimal, or was subsequently worsening (associated with co-morbidities or complications)  [30]. The main strengths of this study resided in the quality of the data used. Data were collected from the only national database containing all prospectively recorded COVID-19 cases in France with standardized case definitions. Additionally, all transfers were recorded in the database, limiting the risk of selection bias in comparing the two groups.
Patient and outbreak characteristics in this study are similar to those reported in the literature and epidemiological reports from Public Health France, particularly concerning the peak surge in ICU-bed occupancy on April 8, 2020  [31, 32]. The main limitation of our analysis was the lack of clinical, socio-demographic and management data for the study population. Collection of this information is currently ongoing as part of the TRANSCOV project (ClinicalTrials. gov Identifier: NCT04930120) and should enable more detailed comparison of transferred vs. non-transferred patients and enhance our understanding of the variations of mediumterm outcomes.
Methods This review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for scoping reviews  (30). Article searches were initially conducted in November 2018, and updated in January 2019 and March 2019. The following electronic databases were reviewed: MEDLINE, Scopus, JSTOR, Web of Science, Pubmed, Psycinfo and Science Direct. Searches were limited to English-language articles, published over 12 years (January 2008-March 2019). This period was selected as it re ected recent/current efforts in delivering customized care. The search was focused on articles that included "care customization", "personalized service and healthcare", individualized care" and "targeting population" in the title or abstract. Following the principle of "narrowing" the topic  (31) , we instigated a second Boolean search strategy on Web of Science using the following keywords: (1) care customization OR personalized medicine OR personalized service OR targeting populations OR individualized care AND (2) segmentation analysis OR pro ling patients OR categorizing patients AND (3) patient needs OR patient characteristics OR patient preferences OR population characteristics OR patient demands (see appendix 1 for an example of an entire search strategy).
Study Outcomes The primary outcome was an overall "sustainability score. " This was calculated by summing the scores assigned to the 40 consolidated framework for sustainability constructs for each study and DSD intervention type (see calculation details below). In addition, the median of the scores was estimated for the 6 domains per intervention. All construct and domain names are present in this article in italics. The secondary outcomes included (1) a descriptive summary of the main study outcome measures (eg, retention in care, viral suppression, loss-to-follow-up, and client-related or providerrelated costs), (2) narrative synthesis of qualitative outcomes (eg, clients and HCW perspectives about DSD interventions and challenges), and (3) sensitivity of sustainability scores per intervention to the cut-off points (see data synthesis section below) with variations in definitions of individuals established on ART used across studies.
ACKNOWLEDGMENTS The authors thank  Rene Spijker  of the  Amsterdam UMC  library for his contribution in conducting both the initial and final search for articles included in this review. Although this research was funded by the  Erasmus Mundus Joint Doctorate (EMJD)   Fellowship program  of the  European Union (EU) , the views expressed in this article are those of the author(s) and not necessarily those of the EMJD or EU. This research was supported by the  NIHR  Applied Research Collaboration Northwest, London. The views expressed in this publication are those of the author(s) and not necessarily those of the  NIHR  or the  Department of Health and Social Care.
In October 2020, the StopCovid app was updated and renamed "TousAntiCovid"  [5]. When app users indicate that they have been infected with COVID-19, the app uses Bluetooth technology to recover information of all close contacts (ie, all other TousAntiCovid users who have spent more than 15 minutes within a distance of 1 meter of the said user, as recorded over a period of 14 days) and alerts them with generic notifications, recommending them to quarantine themselves and to take a COVID-19 screening test. There have been numerous criticisms focused on data privacy  [6, 7]  and technical limitations of the app software  [8]. Because downloading and using the TousAntiCovid app is voluntary in France, its effectiveness is dependent on acceptability and adoption among users. Beyond the technical considerations, such contact tracing apps require high adherence rates among the population to be effective.
Methods The data analyzed here has been sourced from the French Health Literacy Survey 2019 (HLS19), which was set up as part of France's participation in the World Health Organization Action Network project Measuring Population and Organizational Health Literacy (M-POHL)  [12]. HLS19 was administered to a sample of the adult French population 2 weeks after the end of the first lockdown in France (ie, between May 27 and June 5, 2020) at the time of the official launch of the TousAntiCovid app (June 2, 2020). After this complete lockdown, several other national or regional lockdown periods were announced in France in 2020-2021. The sample of 1000 internet users aged 18-75 years was drawn from an access panel, respecting the French population structure for sex, age, regions, and area of residence (urban or rural).
After informed consent was obtained, the web-based survey collected information on respondents' sociodemographic characteristics (gender, age, level of education, and region of residence), perception of health, health literacy, and navigation in the health system. In addition, the survey collected additional national items such as communication with caregivers through new technologies, perception of medical research, trust in institutions, as well as data about the COVID-19 pandemic. The study methodology was reviewed and approved by the Ethics Evaluation Committee of the French National Health and Medical Research Institute (CEEI, IRB 00003888). In this study, we focused on analyzing the sociodemographic data of the survey respondents. A financial deprivation score was calculated by combining 3 questions related to financial abilities:  (1)  to pay all bills at the end of the month, (2) to buy drugs if needed, and (3) to pay for medical examinations and treatments that are not covered by health insurance (response scale: very easy, easy, difficult, and very difficult).
Chi-square tests and analysis of variance (ANOVA) were used for descriptive analyses, depending on the type of variables. A multinomial logistic model was used to identify the factors associated with the acceptability of a mobile app to study close contact between people during an epidemic. After adjustment for age, a stepwise procedure was performed to select significant factors in the model (entry threshold; P<. 20). The significance threshold in multivariate analyses was set at 5%. All analyses were performed using the STATA software program (version 14. 0; StataCorp LLC).
Acknowledgments We thank the  Réseau Francophone de la Littératie en Santé (REFLIS) network  for their collaboration in the European  HLS19  survey. This work was funded by  Santé Publique France and La Ligue Contre le Cancer (Equipe CANBIOS Labellisée). SH's collaboration with SESSTIM was supported through  Institut Paoli-Calmettes/IMéRA (Aix-Marseille Univ) Chair.
Population PTCs were proposed by the referring HCPs (RHCPs) to adolescents  (15-25 years) , with any CC or disability managed at the R. Debré hospital, due to be transferred to adult healthcare within the following 2 years. Adolescents were informed about the research through an information letter. We recruited the rst adolescents attending a PTC from May 2017 (launch of AD'venir), including participants until data saturation achievement, meaning that patients' discourses had become redundant and no new theme would arise with supplemental inclusions  [16]. We also recruited each adolescent's RHCP.
Data analysis The qualitative approach was developed to gain insight into the conduct of the PTC, because they are relevant methods to understand how health services work and to provide detailed understandings of intervention functioning on a small scale  [21]. PTCs were audio-recorded, transcribed by a professional, and contextualized by a form stating the schedule and the adolescent's psychological condition. A twostep qualitative analysis was performed. As a rst step, two parallel analyses consisting in an inductive identi cation of themes  [22]  were performed by two AD'venir TPs (HM, PJ) and two sociologists (AD, CG), respectively. Emerging themes and the analytical framework were discussed together to present a report to a dedicated multidisciplinary working group, including the two sociologists, the four AD'venir TPs, one researcher in public health (ELR) and one psychologist (MM).
Statistical analysis Demographic data including sex, status, role in local CPG development, assignment, semester of training (for residents only) were summarized and compared using the Fisher exact test. Continuous variable (age and duration of use) and coded Likert scales (-2: strongly disagree and 2: strongly agree) were expressed as medians with interquartile ranges [25p, 75p] and compared with the Wilcoxon rank sum test. We chose an odd-numbered Likert scale of 5 points in order to offer a neutral mid-point. This avoids a forced choice and therefore a random response of one of the two points framing the omitted mid-point  [11]. To identify groups of similar questions, we used a hierarchical clustering analysis on the Euclidean distance matrix formed by participant responses to the Likert-type questions.
This method uses an agglomerative approach based on dissimilarity (Euclidean distance) measure between each pair of answers. We supposed an equal distance between scale points. We measured within-cluster similarity using the average silhouette width. Then, we selected k = 15 clusters of questions because of their high internal consistency based on a Cronbach's α above 0. 7  [12]. P < 0. 05 was considered statistically significant for all the analysis. Data were analysed using the software R Core Team ® (2018).
Data collection Semi-structured interviews were conducted in French by two paediatric residents (ID and JD). Data collection spanned from May 2019 to February 2020. Each interviewer carried out repeated interviews with researchers specialised in qualitative method. These interviews were not included in the data collection. Sessions were semistructured, with a pre-defined list of open-ended questions focused first on the current uses of the local CPGs and then on desired improvements, ease of use and openended suggestions. The discussion guide was developed by all authors (NG, ID, JD, NM, GC, PP and AB) after a review of the literature before starting the study. Interviews were conducted in person at a private office space located in the participants' hospital workplace. Participants were contacted through email or face-to-face.
We coded data from transcripts using the Saldaña method  [14]  and evaluated the frequency of each theme using the qualitative data management software NVivo ® 12 Plus (QSR International). To ensure the reliability of the coding and analysis of the data, findings were discussed among the authors. Data were then analysed based on the participants' status and assignment. Still using NVivo ® 12 Plus (QSR International), we imported participants' demographic characteristics and compared their responses according to these attributes. In the last phase of the analysis, data from the quantitative survey and the interviews were interpreted together. The interviews were used to explore and complete the quantitative data or to find differences between the two datasets.
Phase 2: qualitative study Twenty-four physicians participated in the interviews. Almost all of them (n = 22) were women, 19 used local CPGs very often and 5 used it maximum once a week or less. "Very often" was defined by responders themselves as "daily" or "several times a week". Table  2  shows the characteristics of participants. Each interview lasted between 12 and 24 min. Data saturation was obtained because we did not find a new theme after several analyses of the data. Analysis revealed five emergent themes: improvement of local CPGs, patterns of use, reasons for non-implementation, alternative sources and perspectives (Table  3 ). In the second part, we analysed qualitative data based on participants' status and assignment.
No reference point-of-care, web-based medical compendium is available in general practice in France. We have then conducted the experimentation of EBMPracticeNet, a Belgian website of guidelines translated and adapted from the Finnish EBM Guidelines. We collected data from three sources: (i) the website logbook; (ii) a search-specific assessment questionnaire; (iii) a global assessment questionnaire. A cumulative number of 262 (62. 8%) physicians performed at least one search on the website and clicked on average 5. 9 times per month. Physicians globally got an accurate answer (74. 2%). They found the information provided by the website reliable (92. 2%) and useful for practice (78. 6%). They perceived the website ergonomics as good. The main reported barriers were the time and effort required to find an accurate answer and the uneven relevance of the information retrieved.
Data collection At their first connection, the participating physicians were asked to complete profile data. A personal login identification password was assigned to each in order to analyse their frequency of use and search behaviour. Each search was recorded in the website logbook, which contained the following fields: user ID, timestamp(s), queries (words or phrases), title(s) of the guidelines opened. In their assessment of the EBM Guidelines in Finland, Jousimaa et al. 22  collected log files from users to measure the frequency of their searches. During the 7-month study, search-specific, self-developed, assessment questionnaires were periodically activated online to assess physicians' clinical search effectiveness (see Appendix 1). In addition, at the mid-point and end of the study, participants were asked by email and by post to complete a global assessment questionnaire, self-developed.
Data analysis From the logbook, we calculated the frequency of use per participant, as an objective indicator of participation. It was defined as the number of specific clicks performed monthly on the website, either for entering a query or for opening a guideline. From search specific assessments, we calculated the proportion of accurate answers provided by the website to searches. From the logbook, we distinguished inaccurate answers with no guideline opened from guideline(s) opened but no answer found by the physician. We calculated the mean SUS score and interpreted it according to the adjective rating scale designed by Bangor et al. 24  We compared the number of clicks of the physicians who responded, and those who did not, to the search-specific and global assessments, using the Student t-test.
According to the mean SUS score, the website ergonomics was perceived as good, but not enough to recommend it to a colleague. 23, 27 The main barriers to using the website were the effort and time required to find accurate information, especially during the consultation. This is consistent with the literature, which identified time issues as the main barrier to the seeking of information by physicians. 1, 25, 28, 29 The participating physicians also reported difficulties selecting appropriate search terms and retrieving relevant guidelines. Physicians are increasingly aware of the various sources of medical information, but not specifically trained to search within medical databases. 28, 30 In addition, guidelines indexation was probably incomplete and sometimes inappropriate in this version of EBMPracticeNet.
To fit the website to the French context, the Finnish translated guidelines should be adapted to improve their applicability and their appropriation by physicians. Among several processes developed worldwide for that purpose,  34  we may conform to the ADAPTE method  35  as used for the Belgian EBMPracticeNet. 16 In addition, French guidelines should also be integrated into the website, which implies their design adaptation and XML-formatting. French physicians are increasingly trained in evidence-based medicine. Specific training for postgraduate students in medical database searching may improve their skills and the frequency of use of the website. 36 In Finland and Belgium, access to the EBM Guidelines database is free for physician users. The economic model for France should be well thought-out, as the imposition of access fees to the website could impede its use by physicians.
Conclusion French physicians who tested the Belgian EBMPracticeNet website had a limited use of it, apart from persistent physicians. A majority of searches led to an accurate answer, and website ergonomics was perceived as good. Almost all respondents wished to continue using the website. The main reported barriers were the time and effort required to seek information, and the uneven relevance of information retrieved. To implement EBMPracticeNet on a large scale in France, improvements should mainly focus on indexing guidelines and adapting them to the national context, and training physicians to search medical databases. Since the present evaluation, a French website called ebmfrance. net, based on the EBM Guidelines collection translated into French, has been launched thanks to funding from the French Public health insurance system.
Acknowledgements We would like to thank the physicians who participated to this study. We are grateful to  Prs Cyrille Colin  and  François Gueyffier  for their useful comments on the manuscript. We are indebted to the  Collège de la Médecine Générale (CMG)  and to the  Collège Lyonnais des Généralistes Enseignants (CLGE)  for funding the English editing of the manuscript.
Normality Test Not all populations are categorized as normal. Therefore, the normality test is required, the nor-mality test aims to assess the distribution of data in a data group, whether the data is distributed normally or taken from a normal population. This study used the Jarque-Bera Test to test the normality of the sample. In the Jarque-Bera test, the measures used are skewness and kurtosis. Based on the Jarque-Bera Test, the residues are normally distributed. The heteroscedasticity test aims to see the variance inequality of the residual value from one observation to another in regression model. Based on the test, test =0. 1560 > 0. 05 so H0 is accepted and residuals are homoscedasticity. MARCH 2021.
Therefore, it is delicate to distinguish if non-operation is due to self-withdrawal or medical contraindications. The preoperative program lasts about one year. Significantly longer preparations often reflect the need or wish for external follow-up, without definitive withdrawal from the OC. All consecutive patients referred for primary bariatric surgery at the OC were retrospectively included from January 1, 2016, to June 30, 2017. Socio-demographic data such as age, gender, marital status, parenthood, country of birth, education level, and employment status, as well as BMI, preoperative psychological and dietary evaluations were manually extracted from patients' medical records in June 2019, with a hindsight of at least 2 years or until the patient's operation or dropout. For the present study, patients who had left the program or who had not undergone surgery after more than 2 years of follow-up were considered temporary or definitive dropouts for surgery.
Strength and limits The main limitation of this study lies in the high percentage of missing values and its non-random distribution, missing values being more common among non-operated patients (Fisher's exact test; p < 0. 05). Data were extracted from consultation reports. However, non-operated patients may drop out before getting the entire gamut of consultations and their medical record was less complete as compared to patients following the whole program. However, when performed only in patients without missing values, the analysis of nonoperation factors retrieved similar results to the ones presented here. It was decided to keep all patients to remain coherent with the retrospective study design and to allow for a more informative clustering. Another limit is the use of non-standardized dietary and psychological evaluations.
Acknowledgements We especially thank  Samuel Colin  from the  University of Geneva  for his precious statistical inputs. Authors also are grateful to  Coralie Khellouf ,  Solenne Nguyen  and  Julie Ballester , OC secretaries, for their dedicated work and to  Jean-Luc Richard ,  Guy Temporal  and  Christopher Burel  for their kind external lecture and assistance in the language revision of the manuscript. We acknowledge that reprints will not be available from the author(s).
Data Collection Socio Demographic Characteristics Data were collected on gender, type of academic course (law, literature, healthcare, humanities, and sciences), type of academic degree (bachelor, master, doctorate and if the student was a fresher). Participants were further categorized according to their year of study (year 1, years 2 and 3, years 4 and 5, and year 6 plus). Students reported data on their living accommodation, classified in four groups: (1) Students living with parents before and during COVID-19; (2) students not living with parents before and during COVID-19; (3) students living with parents before but not during COVID-19; and (4) students not living with parents before but living with parents during COVID-19. Students reported whether they had more or less contact with family and friends since the implementation of COVID-19 measures (more, the same or less).