dataesr/scientific-paragraphs-categorization huggingface dataset:
The FondaMental cohort is the first prospective cohort on patients with TRD in France. In addition to collecting data on clinical measures, health status questionnaires were completed, and healthcare resource use was evaluated. Relevant health states were also identified, and utility values were obtained for these patients, both globally and by health state. Utility values, which measure health status in a single common metric, make it possible to compare patients' health across populations and diseases. The use of health states also provided more detailed analyses on TRD, which used proxy variables to identify relapse, recurrence, and recovery. This approach made it possible to obtain more robust estimates by health state by taking into account events that characterise relapse or recurrence.
Finally, patients in this cohort were followed up for four years, with 78 patients (31%) having at least two years of follow-up. Healthcare resource use and utility values have also been analysed among patients with depression, but the literature is still sparse on patients with TRD. Amos et al. [16]  identified patients with TRD from a U. S. commercial claims database and found that patients with TRD had twice the number of hospitalisation days when compared to non-TRD MDD patients. The Prospective Epidemiological Research on Functioning Outcomes Related to Major depressive disorder (PERFORM) study  [37]  followed European patients that were initiating antidepressant treatment their general practitioners. Among these patients, 2. 5% with a depressive episode longer than 8 weeks were hospitalised within 12 weeks of the baseline visit.
Conclusions This is the first prospective observational study to describe and evaluate patients with TRD managed within expert centres in France. This study documented patterns in healthcare resource consumption, quality of life, and other characteristics in patients with TRD, both globally and by health state and severity of depression. These findings add useful information to the limited available evidence on patients with TRD, and highlight the need for better prognoses and more well-adapted treatment plans. These results can also provide valuable material for health authorities to help populate cost-effectiveness models with real-world evidence. However, it should be noted that the care of these patients is specific to expert centres and may not be generalisable to all practitioners. As such, it would be beneficial to link this data to the French national health insurance information system (SNIIRAM), to obtain more complete information on the healthcare resource use and medical history of these patients.
RESEARCH IN CONTEXT Evidence before this study: We referred to a living systematic review that is evaluating mental health changes from pre-COVID-19 to COVID-19 by searching 7 databases, including 2 Chinese language databases, plus preprint servers, with daily updates (https://www. depressd. ca/covid-19-mental-health). As of June 13, 2020, only 5 studies had compared mental health symptoms prior to and during COVID- 19. In 4 studies of university students, there were small increases in depression or general mental health symptoms but minimal or no increases in anxiety symptoms. A general population study from the United Kingdom reported a small increase in general mental health symptoms but did not differentiate between types of symptoms. No studies have reported changes from pre-COVID-19 among people vulnerable due to pre-existing medical conditions.
Role of the Funding Source Funders had no role in any aspect of study design; data collection, analysis and interpretation; manuscript drafting; or the decision to submit for publication. The corresponding author had access to all data and final responsibility for the decision to submit for publication. Cohort and were included in the present study. See Figure  1  for participant flow and Supplementary Table  1  for number of participants from recruitment sites. Table  1  shows participant characteristics. Mean age was 56. 9 years, and 88. 5% of participants were female.
Nonetheless, data were collected at a time when social isolations were generally at their most conservative. Finally, different MCID values may be chosen. The 4-point MCID we used for anxiety symptoms was conservative; others have recommended MCIDs of 2 to 3 points,  30  and it is possible that we may have underestimated the degree of patient-important change. In sum, this was the first study to compare mental health symptoms prior to and during the COVID-19 outbreak. We found that anxiety symptoms increased substantially and that the magnitude was associated with country; increases were highest in the United States and United Kingdom and more moderate in France and Canada. There were minimal differences in depressive symptoms during COVID-19 compared to pre-COVID-19. An important finding was that people who received mental health care prior to COVID-19 experienced substantially smaller anxiety symptom increases than other participants.
Data Sharing: De-identified individual participant data with a data dictionary and analysis codes that were used to generate the results reported in this article will be made available upon request to the corresponding author and presentation of a methodologically sound proposal that is approved by the Scleroderma Patient-centered Intervention Network Data Access and Publications Committee. The study protocol and analysis plan are available at https://osf. io/kbncx/. Data will be available beginning 12 months after publication. Data requesters will need to sign a data transfer agreement.
03) 0. 05 (-0. 38 to 0. 48) 0. 08 (-0. 19 to 0. 35) Change of ³ 1 MCID: N worsening (%, 95% CI) 82 23 24 11 24 (21. 1%, 17. 4% to 25. 5%) (25. 3%, 17. 5% to 35. 1%) (16. 4%, 11. 3% to 23. 3%) (25. 6, 14. 9% to 40. 2%) (22. 2%, 15. 4% to 30. 9%) N improving (%, 95% CI) 80 18 40 9 13 (20. 6%, 16. 9% to 24. 9%) (19. 8%, 12. 9% to 29. 1%) (27. 4%, 20. 8% to 35. 1%) (20. 9%, 11. 4% to 35. 2%) (12. 0%, 7. 2% to 19. 5%) Change of ³ 1 MCID and reaches cutoff threshold a N of N initially < cutoff 27 of 284 8 of 61 5 of 103 6 of 30 8 of 90 worsening (%, 95% CI) (9. 5%, 6. 6% to 13. 5%) (13. 1%, 6. 8% to 23. 8%) (4. 9%, 2. 1% to 10. 9%) (20. 0%, 9. 5% to 37. 3%) (8. 9%, 4. 6% to 16. 6%) a a Results based on imputed datasets.
Stimuli Stimuli consisted of nonverbal affective vocalisations from the Montreal Affective Voices database  (Belin et al. , 2008)  produced by two actors (one male, one female). Each actor produced five emotional expressions using the vowel /a/: anger, disgust, fear, pleasure and neutral. From these five vocalisations, stimuli were generated by morphing between each vocalisation and the neutral stimulus from the same speaker (see Fig. 1 ). Voice morphing was performed using STRAIGHT  (Kawahara & Matsui, 2003)  in Matlab (Mathworks, Inc. , Natick, USA). STRAIGHT performs an instantaneous pitch-adaptive spectral smoothing in each stimulus for separation of contributions to the voice signal arising from the glottal source versus supralaryngeal filtering. STRAIGHT allows modifying voice stimuli along five dimensions -f0, frequency, duration, spectrotemporal density, and aperiodicitythat can be manipulated and combined across stimuli independently of one another.
On each trial, they were presented with one of the possible 741 pairs of sounds, and were asked to rate how similar they were on a scale of "very similar" to "very dissimilar. " They could listen to the pair of stimuli as many times as necessary before giving a response. Participants were given 10 practice trials using a set of 10 vocalisations that were not included in the main experiment. The total duration of each session was approximately 120 min. Participants performed the emotional ratings and speeded categorisation tasks in alternating blocks in the same (final) session. In the ratings task, participants rated each stimulus on arousal (low to high), valence (negative to positive), and emotional intensity for four emotions (anger/disgust/fear/pleasure, low to high). In all ratings tasks, data were coded on a scale of 0 (low) to 1 (high).
In the categorisation task, participants were instructed to identify as quickly as possible the emotion expressed for each stimulus as being anger, disgust, fear, or pleasure. The association between a particular emotion and a particular response button was randomised for each block. Before the session began, participants were given 10 practice trials for both the rating and categorisation task. Participants were familiarised to the entire stimulus set before the first block for each speaker. The emotion ratings and categorisation session consisted of 12 blocks, incorporating 6 blocks of each task (rating and categorisation). Each task was repeated three times for each of the two speakers (1 male, 1 female), and data were averaged across the three repetitions. One block contained all 39 stimuli for one speaker, and stimulus order was randomised for each participant.
Statistical analysis For the caricature analysis, we assessed the relationship between morphing level and the behavioural measures with a linear mixed-effects analysis as implemented in the lme4 R package  (Bates, Maechler, Bolker, & Walker, 2014). Ratings and reaction times were included as dependent variables (in separate analyses), with morphing level (25% to 125%), speaker gender, and the interaction between morphing level and speaker gender as predictors. Subjects were modelled as random effects, with by-subject random intercepts and slopes for morphing level. The Satterthwaite approximation for degrees of freedom  (Satterthwaite, 1946)  was used as implemented in the lmerTest R package  (Kuznetsova, Brockhoff, & Christensen, 2015). In the categorisation task, RTs above 2. 5 s were discarded (5.
8% of total responses). For the similarity ratings analysis, comparing prototype-and exemplar-based accounts of emotion recognition, we considered data from the similarity ratings and speeded emotion categorisation tasks. For each speaker and participant, we extracted the similarity rating between each pair of stimulicoded between 0 ("very similar") and 1 ("very dissimilar")and the mean reaction time for each stimulus (averaged across the three repetitions) from the emotion categorisation task. From the similarity ratings we defined two measures: stimulus (exemplar) density, a measure of how similar each stimulus is to the entire stimulus set; and similarity to the average, a measure of the distance to the prototypical or average voice stimulus. For the exemplar density measure, we extracted the mean similarity value for each stimulus compared to all other stimuli, with 0 indicating higher similarity to other stimuli (and higher density).
Acknowledgements This research was supported by the  Biotechnology and Biological Sciences Research Council ,  United Kingdom  ( BBSRC ,  BB/M009742/1 ). PB was supported by grant  AJE201214  by the  Fondation pour la Recherche Médicale, France , and  Labex Brain & Language Research Institute, France  ( BLRI ,  ANR-11-LABX-0036 ), supported by the  French National Research Agency (ANR) , under the program " Investissements d'Avenir"  ( ANR-11-IDEX-0001-02 ). The authors report no financial conflict of interest.
The last stage involved producing a coherent and orderly presentation of the themes  [55] , that is, summarizing the set of experiences described and moving from a local theory of each interview to a general theory of the research question. Results were analyzed as data collection continued. One author (EC), aided by NVivo 12 software, analyzed all of the interviews. Her analysis was triangulated by the other authors who are experts in qualitative method. The divergences were discussed in meetings with a team of experienced researchers. This triangulation made it possible to ensure that the themes identified accurately reflected the data. Discussing, clarifying, and, if necessary, modifying the themes contributed to improving the study's validity  [55]. We reported our study in accordance to the Consolidated criteria for reporting qualitative research (COREQ) checklist (S2 File).
Acknowledgments Jo Ann;  Amalini Simon ;  Nelly Massari  et  Marion Le Goas ; ASENSI Helène; BAUBET Thierry; JOURNOT-REVERBEL Katia; MESTRE Claire; MSELLATI Annie; MOULIN Jean-Claude; RADJACK Rahmeth; ROUCHON Jeanne-Flore; STURM Gesine; BONNET Sylvie; CAMARA Hawa; DI Charles; JALENQUES Isabelle; GIOAN Estelle; KOUASSI Kouakou; LKHADIR Aicha; LLORCA Pierre-Michel; LUDOT Maude; MINASSIAN Sevan; NOTON-DURAND Francoise; PREMAT Laura; RAYNAUD Jean-Phillipe; REAL Isabelle; QUATTONI Berenice; REZZOUG Dalila; RIZZI Alice Titia; TOUHAMI Fatima;  DE BOISSIEU Paul  and all the members of the transcultural consultation.
Data collected In addition to background socio-economic variables (gender, age, educational level), we computed each respondent's equivalized household income per month, taking the size and composition of the household into account  [13] , and using the Organization for Economic Cooperation and Development's scale. Then we built a three-item indicator: 'Low income' refers to the first quartile of the equivalized household income, 'medium income' to the second and third quartiles, 'high income' to the last quartile. Regarding potential consequences of the lockdown on daily life, we collected information about self-reported financial difficulties experienced because of it, as well as the current occupation status: still working out of home, teleworking, unemployed due to the lockdown, unemployed or out of work before the lockdown.
Acknowledgements We thank the IFOP team. Other members of the COCONEL Group:  Valérie Seror 1 , PhD ,  Sébastien Cortaredona 1 , PhD ,  Jocelyn Raude 4 , PhD  (research consortium),  François Beck 5 , PhD ,  Stéphane Legleye 5 , PhD ,  Olivier L'Haridon 6 , PhD ,  Jeremy Ward 1,7 , PhD  ( Steering Committee ).
This research was supported by a grant funded by the National Natural Science Foundation of China, awarded to the second author Zhi-Xue Zhang  (Grant No. 71632002). Both laboratory studies and real-world cases suggest that creative agreements widely exist, helping negotiators create values  (Kray & Haselhuhn, 2007) , resolve conflicts  (Deutsch, Coleman, & Marcus, 2011) , and establish rapports  (Goldberg, 2005). However, little is known in the literature about what contributes to and how to reach creative agreements. As a real-world example, the Good Friday Agreement did not resolve the geographic dispute between the U. K. and Ireland over Northern Ireland due to the two countries' presumed resistance points, but it addressed both parties' underlying concerns by creating a form of co-sovereignty that allowed people in Northern Ireland to identify as British, Irish, or both  (Cox, Guelke, & Stephen, 2006).
Study population This study utilised data from the French-based, longitudinal ESPRIT (Enquête de Sante´ Psychologique-Risques, Incidence et Traitement) study of neuropsychiatric disorders in geriatric populations  (Ritchie et al. , 2004). Eligible participants who were non-institutionalised and aged over 65 years were randomly drawn from electoral rolls of the Montpellier district between 1999 and 2001. Following recruitment, participants were administered numerous questionnaires and underwent extensive assessment by trained personnel, including nurses and neurologists with experience in psychogeriatrics, at Gui de Chauliac Neurology Hospital over the course of half a day. Ethical approval for the study was granted by the Ethical Committee of University Hospital of Kremlin-Bicêtre, France, and written consent was obtained from each participant.
Comparison to previous literature There have been several recent studies which have sought to address the relationship between PTSD and dementia in older people, mainly in male dominated veteran populations. All but two of these studies  (Roughead et al. , 2017; Weiner et al. , 2017)  found that older veterans with PTSD, compared to those without PTSD, had a two-fold increased risk of dementia  (Mawanda et al. , 2017; Qureshi et al. , 2010; Yaffe et al. , 2010). Similar positive trends were also observed in the only two civilian-based studies identified; men and women from a national health insurance database in Taiwan  (Wang et al. , 2016) , and members of a large integrated healthcare delivery system in Northern California  (Flatt et al. , 2018). Both of these studies used a physician's diagnosis of PTSD within a limited period of 5-8 years, obtained from electronic medical records.
However, normative data from controls were not provided for this procedure. The Montpellier procedure lasts in total 80 h and starts with a classical nighttime PSG followed by MSLT (Figure  1 , bottom)  [30]. Then, depending on clinical features, patients may be referred for a second procedure lasting 58 h. It starts with a nighttime PSG, followed by a modified MSLT. The five tests of the modified MSLT are interrupted after 1 min of sleep, in order to avoid decreasing the homeostatic sleep pressure. The sleep is then monitored during a 32-h bed rest procedure, including a second night, a second day, and then a third night. Participants are invited to sleep as long as possible, ad libitum. Daylight, television, computer, newspapers, phones, watches, and visits from family or friends are forbidden.
Participants and setting This study was based on a longitudinal analysis of data from the SUBstance Users Satisfaction and Quality Of Life (SUBUSQOL) cohort. This is a prospective cohort of outpatients aged over 18 years who began care at French specialized addiction treatment centers and met the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV)  [33]  criteria for alcohol dependence or opioid dependence (ClinicalTrials. gov ID: NCT02894476). The participants were recruited by clinicians who were certified in addiction pathologies. The treatment wards had multidisciplinary staff, including psychiatrists, psychologists, social workers and specialized nurses. Treatment included individual motivation enhancement, supportive therapy, pharmacotherapy and assessments of somatic and mental health.
Data collection Upon entry into the SUBUSQOL study, sociodemographic and clinical data were collected at the time of inclusion (T0) and 3 months after inclusion (T2) through medical interviews and clinical testing. HRQoL and anxiety-depression were assessed with self-reported questionnaires at T0 and T2. Satisfaction was assessed with a self-administered questionnaire to be completed at home 15 days after the first visit (T1). Outpatients who returned the satisfaction with care questionnaire comprised the cohort for the present set of analyses.
Sociodemographic and clinical factors, the influence of anxiety or depression and the early satisfaction with care score were investigated. Factors with p-values< 0. 2 in the unadjusted analysis were candidates for inclusion in the multivariable models. No selection procedure was applied in the multivariable analysis. The correlations between the variables retained in the models were also tested. Assumptions (e. g. , normality, linearity) were verified before making comparisons between groups and building regression models. Analyses were performed using SAS 9. 4 (SAS Inst. , Cary, NC, USA).
Discussion This study showed low HRQoL at baseline and positive changes in both the physical and mental health domains of HRQoL at the 3-month follow-up among outpatients with substance dependence who were seeking treatment. These results were consistent with previous studies that showed that QoL was low among individuals with SUDs  [41] [42] [43]  and that significant improvements in both the mental and physical dimensions of QoL were found at the three-month follow-up  [44] [45] [46] [47]. Interestingly, the positive change in the physical Fig. 1  Time points of collection of SUBUSQOL data domain of HRQoL was smaller than the change in the mental domain. Previous authors have suggested that the lack of improvement within the physical health domain might be due to a shortage of time for allowing substantial improvements or to the intractability of some somatic health problems  [48].
Main experimentapparatus Stimuli were presented on a 13 in. screen (DELL) and on a Braille Display (BraillePen 12 Touch 12, Harpo, Poznan, Poland, http://www. harpo. com. pl/) using Presentation Software (a stimulus delivery and experiment control program for neuroscience, Neurobehavioral Systems, Berkley, USA, https://www. neurobs. com/).
Acknowledgments Supported by grant no  2016/21/B/HS6/03703  from the  Polish National Science Centre  to M. S. We would like to thank all our participants for their effort and for participating in the study,  Paweł Hańczur  for programming the Braille Display and  Jochen Laubrock  for helpful comments. We would like to acknowledge the  Maria Grzegorzewska University in Warsaw  for organizational help. We thank the  Laboratory of Brain Imaging in Warsaw  for assistance and hospitality during data collection, and  Karolina Dukała  for administrative assistance.
This will allow us to explore the relationship between sourcemonitoring deficits and OCD's related checking symptoms. To achieve our goal, a systematic review was conducted according to the recommendations from the Cochrane group and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines  [16]. Details of methods are given in the Supplementary material 1  [17, 18]. The primary electronic search in the PubMed, ScienceDirect and psycINFO databases identified 102 articles, and cross-referencing provided 6 additional articles. Removal of duplicate records yielded 100 articles. After reading the titles and abstracts, 24 articles were retained. Eleven records were excluded because they did not use source-monitoring tasks. This process resulted in a total of 13 full-text articles, comprising 10 studies in patients with OCD and 3 studies in a subclinical population of checkers.
At work,  Asrar-ul-Haq et al. (2017)  have shown that emotional self-awareness, selfconfidence, success, the development of others, and conflict management have a positive and meaningful relationship with work performance. Using data from a questionnaire to calculate the emotional intelligence and CSR categories variables, we empirically tested our theoretical predictions that R&D is significantly associated with CSR categories. We also investigated the moderating role of CEO emotional intelligence attributes in the relation between R&D and CSR categories. Consistent with our predictions, we found that the studied behavioural finance could play the role of moderator between R&D and CSR categories. The results indicate that the independent variable has a positive and significant effect on CSR categories.
The responding managers used a 5-point scale, from "no agreement" to «total agreement". EI: Emotional Intelligence, R&D: research and development Linear regression of four models with MCG method by SPSS17. *, **, ***, Respective significance at 10%, 5% and 1% The main question of this paper was: how the CEO emotional intelligence moderates the CSR-R&D sensitivity? This study validates our hypothesis. This can be explained by the fact that the emotionally intelligent CEOs decide to invest in R&D, which, in turn, allows creating some opportunities  (Alam et al. , 2019). A CEO with a high level of emotional intelligence chooses liable strategies to solve the most complex tasks relying on his inter-interpersonal confidence. The CEO here is interested in developing new studies, ideas and in R&D, which affects the business performance  (Yew et al.