dataesr/scientific-paragraphs-categorization huggingface dataset:
Hydroxychloroquine and COVID-19 Meta-Analysis HCQ and chloroquine (CQ) have been used for decades to manage and treat malaria and several autoimmune conditions. At the beginning of the pandemic, preliminary studies  (18) (19) (20)  suggested that HCQ might have a positive effect on the treatment of COVID-19 patients. This led the U. S. Food and Drug Administration (FDA) to issue an emergency-use (EUA) authorization on March 28, 2020 allowing for HCQ sulfate and CQ phosphate to be donated to the Strategic National Stockpile for use in hospitalized COVID-19 patients. Given its multiple antiviral effects, it is plausible that HCQ could be beneficial in COVID-19 patients  (21). In vitro data have shown that HCQ/CQ blocks viral infection by inhibiting virus/cell fusion through increasing endosomal pH  (22)  and by reducing the production of inflammatory cytokines  (23) (24) (25).
The covariate 'number of contacts per day' was forced into the model as it was considered to be a relevant variable. We tested the assumption of proportional hazards using Schoenfeld residuals. Then, we used the stepwise selection function in R, which starts with an empty model and adds/removes predictors according to Akaike Information Criterion (AIC) criteria. Unadjusted and adjusted HRs and 95% CI were given. All of the statistical analyses were carried out using R software, and differences with p values of <0. 05 were considered statistically significant. Seroprevalence data of our study were compared with data from a representative sample of the general population living in Marseille, which were derived from a national seroprevalence survey (EpiCov). 19 Results of seroprevalence in the general population were obtained from home self-samples of dried blood spots, in order to detect IgG antibodies (Euroimmun ELISA-S).
Acknowledgements We would like to thank all the homeless people who participated in this study by providing their samples and questionnaires. We would also like to thank also the nurses and mediators involved in the 'COVID homeless' project:  Maud Landreau ,  Anne Ranise  and  Nathalie Vuagniaux ,  Grâce Inegbeze ,  Snjezana Huette ,  Marko Sava ,  Lisa Hasse ,  Mathieu Ledu ,  Alejandro Vernet  and  Drisse Mekkaoui ; the ASSAb network; the homeless outreach teams: ADDAP13, AMPIL, ASUD, Bus  31/32 ,  Equipe Mobile d'Aide (EMA) Saralogisol, Equipe Mobile santé ADJ Marceau, Equipe Mobile Gare et Connexion ADJ Marceau, MARSS-APHM ,  Nouvelle Aube ,  Mission Bidonville Médecins  du monde, PASS adulte APHM,  Réseau Santé Marseille Sud  (RSMS); the emergency shelters:  UHU La Madrague-ville ,  St Louis , Sleep'in (groupe  SOS Solidarité) ,  Forbin  ( Fondation St Jean de Dieu ),  Marius Macias  (AAJT); and the people involved in providing collective accommodation for homeless people:  Marius Macias  (AAJT);  William Booth  ( Armée du Salut );  Le Marabout ,  le Mascaret  ( Habitat Alternatif Social );  Foyer Honorat (Hospitalité pour les Femmes) ;  Jane Pannier  ( Maison de la Jeune Fille );  SHAS (Saralogisol) Coco Velten ,  La Selonne  (groupe  SOS Solidarité) ;  Forbin (St Jean de Dieu) ;  Village Club du Soleil , and  Prospective Coopération  for their work in this study and improving the care management of homeless people in Marseille.
Sample Size Because of lack of literature, sample size calculation could not be performed on association between theories of mind and prematurity. Because of link between verbal skills and TOM has been shown in several studies that highlighted the impact of verbal skills on TOM task performance  (47, 48) , the calculation of the number of subjects required was performed for association between prematurity and WISC VCI with the following hypotheses: an average VCI score for "control" patients of 103. 2 ± 12. 6  (49)  and an average VCI score for "preterm" patients of 92. With an alpha risk of 5%, a power of 90%, and a bilateral test, the number of patients required was 28 per group (NQuery software version 4. 0).
Data Management The study will make use of two separated databases for storing research data and contact information. The contact information of patients, such as the participant's name, phone number, and address, will be stored in a separate database unrelated to the research database. In the research database, all participants will receive an ID number. Electronic data will be saved on a secure server with restricted access. In accordance with the national regulations in France, the data will be stored for 15 years after termination of the trial.
10 by univariate analysis included). The association between the executive functions, evaluated using the TEA-CH, and the development of the theories of mind will be studied using univariate analysis (Wilcoxon tests for qualitative variables and Spearman's correlation tests for quantitative variables) and multivariate analysis (linear regression with variables with a p < 0. 10 by univariate analysis included). A p < 0. 05 will be considered significant. Statistical analysis will be performed using SAS (Version 9. 4, SAS Institute, Cary, NC, USA).
ACKNOWLEDGMENTS Ms. Vincine Bertot  and  Mr. Clément Planchou  who was involved in the choice of the executive function tasks. Pr. Arthur Kaladjian  who coordinates the  Cognition Sociale et Maladies NeuroDéveloppementales project. Pr. Nathalie Bednarek  who coordinates the  Prématurité et Cognition sociale: impact des fonctions exécutives et de l'anxiété parentale project with Pr A-CR and Pr SC within the Cognition Sociale et Maladies NeuroDéveloppementales  project.
Data collection Data were collected from AAJT's available databases and from a standardized questionnaire based on the French National Authority for Health recommendations which was specifically modified to match with the study objectives  [16]. This pseudonymised questionnaire collected the following data: socio-demographic characteristics, recent life history, medical history and comorbidities, treatments, clinical-biological and medical follow-up data. [Additional file 1] The questionnaires were completed by the AAJT healthcare team to ensure a familiar environment for study participants and to minimize social desirability bias  [17]. Following the Covid-19 mitigation policy adopted by France in 2020, each AAJT service user presenting symptoms suggestive of the disease had to quarantine for 14 days and received both remote (e.
Biological analysis An RT-PCR (nasopharyngeal swab) for SARS-CoV2 screening campaign ran in all the eight AAJT services listed above between 4 May and 15 May 2020, and was open to all the organisation's users. RT-PCR samples were taken by a medical team comprising nurses and doctors. During three of the campaign's numerous sessions, the healthcare team submitted the questionnaire to several randomly selected users. Rapid diagnostic orientation serological tests (BIOSYNEX®) for SARS-CoV2 were also performed in all AAJT structures in two screening sessions organized on 24 June and 1 July 2020. Data on study participants who had a rapid test were also collected.
Open access iii. Severe hearing or visual impairment. iv. An identification of a genetic anomaly which may impact on their ability to participate in the intervention or on data validity (determined by the principal investigator on a case-by-case basis). Exclusion criteria for the referred parents (at least one parent with) will include: i. Severe hearing or visual impairment. ii. Severe psychiatric disorder. iii. Unstable somatic disorders preventing participation in the intervention. iv. Lack of internet provision. v. Not available for regular intervention and follow-up. vi. Opposition of one parent to the child's participation in the study. vii. Currently undertaking PACT therapy. Intervention conducted in the experimental group Eligibility criteria for PACT therapist and adherence Therapists delivering the intervention will include speech language pathologist (SLP), occupational therapists, clinical nurses, psychologists or child and adolescent psychiatrists, all specialised in ASD.
Data management The study data will be collected on a secure electronic case report form (eCRF) that will be available at each centre through an internet portal. No personal identifying information will be mentioned on the eCRF. Each subject included in the study will be assigned a unique identification number. All study data will be stored securely in the Academic Hospital of Lyon. All electronic data will be secured on a password-protected laptop. Paper-based study documents will be stored in a secure filing cabinet at each centre. Access to these files will be limited to research staff involved in the study. The eCRF will only include the data necessary for the analysis to be reported in a scientific publication.
Statistical analysis A full statistical analysis plan will be finalised prior to database lock. Statistical analysis and results will be reported at the 12-month endpoint in accordance with the CONSORT 2010 statement. No interim analysis will be scheduled. All the statistical analysis will be carried out according the intention to treat principle using SAS statistical software (SAS Institute). Baseline characteristics will be presented in each group. Summary statistics will be presented for process variables (number of PACT sessions, quality of videoconferencing per session, acceptability and satisfaction of PACT intervention, number of hours declared to be realised with the child) to show the feasibility and acceptability of PACT implementation in the intervention group. The pattern of missing data will be investigated (number and mechanism of missingness).
Missing data strategies can be applied, and sensitivity analysis of different strategies (simple or multiple imputation) will be conducted. A repeated measures analyses will be used to test the effect of PACT intervention on overall ADOS module 1 score over the 12-month study period. A linear mixed model will be run with the overall ADOS score as the dependent variable and including time (baseline, month 12), treatment (TAU or TAU+PACT) and the interaction between treatment and time as fixed effects and patient as random effect. Model will be adjusted for stratification factors (centre, age, level of language (item A1 ADOS-2) and gender) and baseline variables that show evidence of treatment group imbalance. Time will be represented by dummy variable. Model assumption will be verified according to residual analysis.
Tobit models will be used to address potential floor effects. We will finally explore the parent's and children's characteristics, moderating the implementation and efficacy of this therapy. We will also test the previously described mediators implicated in the efficacy of this therapy. 14 alitative analysis of barriers and facilitators of implementation Based on parents and of the therapist's reports, we will describe the facilitators and barriers of the implementation of video-conferencing PACT. The data will be collected through semistructured interview and will be analysed with the classical technique of Interpretative Phenomenological Analysis. 36 Population selection will follow the rules of the purposive sampling and will allow a maximal variation of the sample. 37 9] [40]  The total number of therapists (around 7-8) will be interviewed.
During the 40-60 min interview, we will explore the barriers and facilitators to implementing PACT by videoconferencing. A guide for the interview will be elaborated in the initial phase of the project based on first interviews. Interviews will be recorded and transcribed before analyses. Data from the quantitative and qualitative sources in the process evaluation will be analysed separately. The results of the qualitative study will be integrated with the quantitative results to optimise the findings. 41 nitoring M-MG (IP) investigators associated, methodologists, statistician, parent representatives and associate researcher composed the trial steering committee (TSC). The TSC is independent of sponsor and funders and have no.
Therefore, we carried out a random-effects meta-analysis  53, 54  using regression estimates (and the associated standard errors) across measures for each study and assessed if the meta-analytic effect was significantly different than 0. In addition to providing details from null hypothesis significance testing (NHST) approach, we also compute Bayes Factors for random-effects meta-analysis using default priors from metaBMA R package  55. Data reporting. Statistical analysis was carried out in R programming language  56  using easystats  [57] [58] [59] [60]  packages. For the sake of brevity, results from statistical analyses are included in the figures rather than the main text (an approach adopted in the R package ggstatsplot  61, 62  ). Similarly, details about demographics and experimental design for the studies are provided in Table  1.
Participants also reported information about the individuals they have been in contact with and their characteristics. These included age and the setting/type of contact, for example if the contact happened at the workplace, in public transport, during a medical appointment, during physical activity practices, during shopping, or during the assistance to a person in need on the previous day. A contact was defined as either a physical contact such as a kiss or a handshake, or a close contact such as face-to-face conversation at less than 1 m distance. Data regarding childcare arrangements, lifestyle habits (such as shopping frequency, mode of transport, etc. ) and individual protective behaviours including hand washing and mask wearing were also collected. Participants were asked to provide this information for the previous day, which was during lockdown and on a typical day before the lockdown.
Sources of data used for population correction In order to limit bias attributable to the study design and potential lack of representativeness of the study A. Mean number of contacts depending on the age of participant. For each age group (x-axis), the bars represent the mean and 95% confidence interval (CI) of the number of contacts reported by participants, whatever the setting. The orange line represents the mean number of contacts for the COMES-F study  [10]. To compare the two datasets, individuals with more than 40 contacts per day were not considered. B. Mean number of contacts depending on the setting. For each age group (x-axis), bars represent the mean number of contacts for each setting reported by participants. C. Light blue and yellow curves show the cumulative distributions of the number of contacts for participants in the COMES-F dataset aged 18-60 years and older than 60 years, respectively.
Orange and red curves represent the cumulative distributions of the number of contacts for participants in the SocialCov study for participants aged 18-60 years and older than 60 years, respectively. To compare the two datasets, individuals with more than 40 contacts per day were not considered. D. Distribution of the number of contacts at work before lockdown (grey), and during lockdown (red) only using observations up to the 95 percentile. The inset shows the change in the number of contacts before and during lockdown at the workplace for participants working outside their home during the lockdown (orange). population, estimates were corrected using metrics from two data sources. We used demographic data of the French population reported by the French National Institute for Statistics and Economic Studies (Insee) to compute weighted estimates and reproduce the age and sex distribution in the French population of those aged 18 years and older  [8].
Weighting was achieved for all estimates related to professional situation and lockdown-associated behaviours. No weighting was done to compute descriptive statistics related to the survey population. We also used data from the COVID-19 Barometer  [9] , which is a separate survey carried out during the same study period (i. e. April 2020) by the non-profit organisation DataCovid. In this survey, weekly online polls were administered by the company Ipsos with samples of 5,000 people representative of the French metropolitan population aged 18 years and older established by the quota method (Supplement, Section B). Estimated professional activity distributions by sex were used as a reference measure to compute corrected estimates of the global matrix. When presenting unweighted data, we use the term participant.
Comparison of contact frequency during lockdown with pre-lockdown We compared the frequency of contacts during the lockdown with the frequency during pre-lockdown period (a non-epidemic period). To do so, we used reports related to participants' contacts on a day preceding the national lockdown in the SocialCov survey and data from the COMES-F survey  [10]. Participants of the SocialCov survey were also asked to fill an additional pre-lockdown survey and to depict their usual number of contacts at the workplace for a day preceding the national lockdown. A total of 35,982 participants completed this second questionnaire. We used the full dataset to compute the distribution of the number of contacts. We considered only the participants who declared that they work outside home both in the pre-lockdown period and during lockdown (3,186 participants) to assess the individual change between the number of contacts before and during the lockdown.
The COMES-F study was the first French large-scale population survey performed by Ipsos in 2012  [10]. The aim of the study was to describe the mixing pattern by age in the French population. In total 2,033 participants reported their contacts over 2 days: on 1 weekday and on 1 weekend day. To match and compare the two datasets, individual contacts in SocialCov were censored at 40 daily contacts to comply with COMES-F constraints and we removed them from this specific analysis. In addition, only contacts during weekdays were considered for the COMES-F survey. Censoring all contacts ≥ 40 generated a reduction of 0. 2 in the average number of contacts in our survey, from 3. 3 without censoring to 3. 1 with censoring. Data sources used in the study are summarised in Table  1.
Ethical statement Data were collected in accordance with the regulations in force in France and in the European Union for the protection and security of personal data. In this study, no directly identifying data was collected and it is not possible to re-identify individuals through cross-checking. Aggregated data are accessible online (https:// zenodo. org/record/5704755#. YaEkLdDMKUl). The complete dataset can be provided on demand, subject to prior determination of the terms and conditions of the request and in respect of the compliance with the applicable regulation.
The data and results presented here should be considered in the light of the following limitations. First, participants were recruited online. As a consequence, the study population may not be a representative sample of the French population. Second, as frequently observed in these types of studies, two-thirds of survey participants were women. However, the work situation (Supplementary Figure  S9 ) and contact matrices (Supplementary Figure  S10 ) did not differ substantially between males and females. After the reweighting step, the distribution of household sizes (Supplementary Figure  S3 ) globally matched the one reported by Insee in 2019  [27]. The survey population might be over-represented by employees, executives and individuals who had the opportunity to work from home. It also excluded populations less connected to social networks, smartphones or Internet.
Funding Open access funding provided by  Università degli Studi di Roma Tor Vergata  within the  CRUI-CARE Agreement. This work was supported by the  Italian Ministry of Health  (Ricerca corrente,  IRCCS Fondazione Santa Lucia) ,  Italian Space Agency  (Grants  I/006/06/0  and  ASI-MARS-PRE DC-VUM-2017-006 ), and  Italian University Ministry  ( PRIN grant   2017CBF8NJ_005 ).
g. , imagery) than less-autonomous patients. All data were collected through semi-standardized interviews. The authors concluded that the ability to successfully compensate for memory deficits was a relevant predictor of everyday independent functioning following brain injury. In the same vein,  Prigatano and Kime (2003)  investigated the use of memory compensation strategies through the Memory Compensation Questionnaire (de Frias and  Dixon, 2005)  in 29 patients with memory complaints following heterogeneously-acquired brain disorders (i. e. , TBI, ruptured aneurysms, arteriovenous and cavernous malformations, cerebrovascular accidents, tumors, hydrocephalus, cerebral anoxia). Their study was specifically based on patients' self-reports following memory compensation training. They found that, post-training, compared to  Dixon et al.
Participants had no history of motor or cognitive impairment, or any neurological or psychiatric disease (i. e. , epilepsy, stroke, brain injury, tumor, or cancer). As no medical records were available, and data were exclusively self-reported, a cognitive impairment screening test (the clockdrawing test) was administered  (Paganini-Hill et al. , 2001; Paganini-Hill and Clark, 2007; van der Elst et al. , 2011). All members of the CG scored normally on this test. The two groups were matched for age [t(79) = 0. 04, p = 0. 97] and education [t(79) = 1. 69, p = 0. 10]. Although the male population was slightly bigger in the clinical condition, the difference was not significant [χ 2 = 12. 50, NS].
Materials The first set of questionnaires were administered to all participants in the same order, either at local meetings or at home, during a session that lasted approximately 1 h. The first page outlined the aim of the study and the procedure in detail. Participants were asked to read and sign the included consent form prior to participation. Once sociodemographic data had been recorded (date and location of testing, date of birth, gender (forced binary choice), current or last employment, educational level, and marital status), participants completed several selfadministered questionnaires in the following order: The French Memory Compensation Questionnaire The Memory Compensation Questionnaire (MCQ) is a valuable and sensitive tool designed to evaluate individuals' beliefs concerning their compensatory behaviors in naturalistic settings  (Dixon et al.
Statistical Analyses All data were analyzed with R software (R Core Team, 2013) using the R package lavaan  (Oberski, 2014)  in order to test for each of the five compensation strategies. Models that included the dummy Group variable were assumed to influence compensation strategies through several mediators (Perceived Stress, Success, and Change). Dummy variables Age and Gender were included as covariates. Each model comprised several regressions (Figure  1 ). Although the number of subjects per variable is satisfactory  (Austin and Steyerberg, 2015) , our sample size was small (N = 160). Therefore, we used the Maximum Likelihood Robust estimator to calculate a robust R 2 statistic and Huber-White's robust standard errors  (Maronna et al. , 2006). By definition, a robust standard error is a reliable estimate of the true standard error even for non-independent and non-identically distributed (i.
For this purpose, in our preliminary analyses, we used the lmer function in the R package lme4 to estimate the fit of mixed-effects models  (Bates et al. , 2015). Mixed-effects models included both fixed and random effects. We tested random effects for the factor "pathology" (i. e. , type of brain injury) because the  values we observed represent a random sample from the set of all possible values. We herein estimated between-levels variance for "pathology" in the mean of the dependent variable (i. e. , random intercepts) by adding random effects to the intercept. The intercept was modeled using a fixed effect parameter. For each factor of the MCQ, we subsequently competed models incorporating only the intercept as a fixed-effect with models where "pathology" was added as a random effect using Akaike Information Criterion (AIC) values.