dataesr/scientific-paragraphs-categorization huggingface dataset:
Thus there is an emerging database of studies examining the relationships between technical skills, non-technical skills, error and safety or other performance metrics. These generally indicate positive, if patchy, relationships  (Hull et al. 2012 ) but there is an emerging message that focussing on improving the non-technical skills required for both routine and abnormal task activities can improve safety. In the following section, I consider a second approach that is being adopted by some companies which is not just to consider behaviours but also to foster particular attitudes or 'mind sets' that will drive the choice of behaviours that should enhance safety. This is another approach to building safety professionalism into everyday task activities, and the mental state in question is called 'chronic unease'.
These methods sit alongside formal company systems such as risk assessment and influence outcomes, yet they are not acknowledged. The third way in which we found professionals sharing stories was directly in the form of technical lessons learned about the system that they operate. Even these stories are not what organisations typically think of as incidents to be reported, recorded in a database and analysed for future learning. Rather, they are stories of small anomalies in system behaviour that are of particular interest to a specific group of people. In all three cases it is clear that a story is much more than simply an accumulation of facts. Stories link human actions and events into an integrated composite  (Polkinghorne 1988 ). As such, they have protagonists, a narrative and causal relationships.
'Professional development' has become a euphemism for more formal training courses. As described earlier, professional learning is a profoundly social activity. Many organisations are reluctant to allow time for such activities. • Ensure that learning from incidents includes story-based learning, not just recording facts in a database. Storytelling and action-oriented social learning are key factors in identity construction. What we do is who we are. As  Gautherau and Hollnagel (2005)  describe it, becoming an expert is not only about learning new skills … it is also about constructing an identity of a master practitioner. • Give senior technical professionals more formal access to senior levels of management and reward bad news. In this chapter, we have focused primarily on decisions made by professionals that they then have the power to enact.
Lessons learned derived from an analysis of accidents are a form of hindsight bias, usually towards a normative model of safety. They are intended to encourage people to think of safety in their own work context and usually specified in terms of failures e. g. see ARIA 3 accident database of technological accidents (BARPI 4 n. d. ) and lessons learned from the eMARS 5 major accidents database (European Commission n. d. ). Little lessons learned attention is given to successful recoveries (Resilience Success Consortium 2015). One aspect of biased thinking is that it can lead to depreciation of successful recoveries by attributing them to luck. In fact, professionals with a role in dealing with high risk tend not to show much interest in learning from success, and even suggest that this could be potentially dangerous because of certain heuristic traps  (Van Galen and Bellamy 2015).
Currently there are around 25,000 occupational accidents (around 44% with no breach of the law found) and 270 loss of containment accidents (around 50% with no breach of the law found) analysed in the Dutch tool Storybuilder. The software and databases can be freely downloaded at: http://www. rivm. nl/en/Topics/S/Storybuilder. 9 Doing What Is Right or Doing What Is Safe.
A total of 1,144 older participants completed the follow-up examination and were used as a study population for the present study. The NU-AGE study is registered at ClinicalTrials. gov, identifier NCT01754012. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The study protocol was approved by ethics committees in each country. More details on the NU-AGE study are given elsewhere  (Santoro et al. , 2014).
Data Collection Information on socio-demographics (i. e. , age, sex, education, marital status, living area, and financial situation), lifestyle (i. e. , smoking, alcohol consumption, physical activity, number of usual meals), and health conditions were collected by means of standardized questionnaires. Age was categorized into two groups: ≤ 75 and > 75 years of age. Education was categorized into elementary, secondary, and college/university based on years of education. Physical activity was assessed by the Physical Activity Scale for the Elderly (PASE),  (Washburn et al. , 1993)  and grouped into quartiles. Participants' self-reported levels of physical activity and knowledge about healthy food and healthy eating as well as number of meals eaten daily were used. Body Mass Index (BMI) was calculated on the basis of measured values of weight and height, as weight in kilogram divided by height in meter square.
Assessment of Nutrition-Related Knowledge and Attitudes NRK data were collected using the Nutrition Knowledge Questionnaire (adapted from the Food Labelling to Advance Better Education for Life project), which included 15 items on general nutrition knowledge (e. g. , recommendations on calories, fluids, and selected nutrients intake, as well as sources of selected nutrients). All items were closed-ended, four were dichotomous and 11 were multiple choice with four, five or six options to choose from. A score of 1 was assigned to a good response and 0 otherwise. The score of NRK was computed as the sum of the correctly answered items ranging from 0 to 15 points. Higher score indicated better nutritional knowledge. NRAs were assessed by five statements, related to everyday diet and food choices, on a seven-point Likert scale (range = 1-7; response options ranged from "strongly disagree" to "strongly agree").
With respect to France in particular, data on the humanistic and economic burden of specific types of pain have been reported. For instance, according to a cross-sectional observational study of adults diagnosed with fibromyalgia, patients' Brief Pain Inventory scores indicated that pain interfered with daily activities, work, sleep, and enjoyment of life. 6 In that study, work productivity loss contributed almost 90% of the total costs incurred by patients with fibromyalgia; HCP visits and prescription medications accounted for most of the direct costs. In a cross-sectional survey of the general adult population in France, those with neuropathic pain reported lower HRQoL on the MCS and PCS and higher HRU than controls and adults with non-neuropathic pain. 7 Adults with chronic lower back pain reported poor HRQoL (MCS and PCS scores), with physical therapy and hospitalizations accounting for the largest proportion of direct costs, in a retrospective observational cohort study of French patients who visited general practitioners.
8 s noted previously, most studies in this area have focused on specific pain conditions, whereas research is lacking on the broader impact of pain in France. The few prior largescale surveys on this topic were based on data collected in 2008 or earlier. 9, 10 In one of these studies, data from French participants were aggregated together with respondents from four other EU nations and then categorized by pain severity level, which precluded a determination of the prevalence and burden of pain unique to the general adult population in France. Whether the impact of pain on outcomes varies by demographic subgroups is not well understood. Further clarification regarding the aforementioned issues is necessary to facilitate the ability of HCPs and policymakers in France to develop more effective strategies to address the health and economic burden attributed to pain.
Data source For the current study, data were analyzed from the 2015 France National Health and Wellness Survey (NHWS; Kantar Health, NY, USA; N=19,173), which is a self-report, internetbased survey of adults aged ≥18 years. The NHWS employs a stratified random sampling framework to ensure a representative sample. Specifically, participants are selected to match the age and sex distributions of the general adult population in France using estimates from the International Database of the US Census Bureau. Potential NHWS respondents are identified using Lightspeed Research and affiliated opt-in online survey research panels. A total of 176,242 invitations were sent for the France 2015 NHWS, yielding a response rate of roughly 11%. All participants provided their informed consent online, prior to completing the NHWS.
Discussion The purpose of this study was to estimate the prevalence of pain according to age group and assess the burden of pain in terms of HRQoL, employment, daily activity impairment, and HRU, among the general adult population in France. The current study was able to fill important gaps in the available literature. Specifically, the few studies that have evaluated the prevalence and impact of pain in France were not based on recent data. 9, 10 In contrast, this study used data collected in 2015 from a large-scale population survey. Furthermore, by considering a broad array of relevant outcomes, the present study was able to more comprehensively clarify the nature of the burden ascribed to pain in this region. Overall, the prevalence of pain in France was high. Particularly, results revealed that approximately 1 in 5 adults in France reported experiencing pain in the prior 12 months.
Limitations The present analysis had a number of limitations to consider. First, this study was cross-sectional, thereby precluding causal relationships from being established. All data were self-reported, and responses could not be independently validated. Furthermore, due to the self-reported nature of the data, the possibility that inaccuracies in recall or other response biases were introduced cannot be excluded. While the NHWS was designed to reflect the age and sex distribution of the general adult population in France, it is unknown whether the study sample was representative of the subpopulation of adults who experience pain. For example, respondents who were in better health and/or in less pain may have been more likely to participate. If so, the current study may have underestimated the prevalence of pain and the magnitude of any differences between those who do and do not experience pain.
Acknowledgments The authors wish to acknowledge the assistance of  Jeff Vietri, PhD , with data analyses,  Martine C Maculaitis, PhD , with literature review and editing, and  Amir Goren, PhD , with editing. The assistance of JV, MCM, and AG was provided on behalf of  Kantar Health , which received fees from  Mundipharma SAS. The study reported on in this manuscript was funded by  Mundipharma SAS.
Methods IS research will be conducted at DeWorm3 baseline (i. e. formative research), midline (i. e. process research), and endline (i. e. summative research). The purpose of conducting formative research is to strengthen DeWorm3 implementation by preemptively identifying implementation barriers and facilitators, seeking support from influential "gatekeepers," and building consensus. Stakeholder analysis, qualitative data collection, and readiness assessments will contribute to formative research, as described below. Process research will provide important information regarding the contextual factors such as intervention acceptability, uptake, and penetration that influence observed DeWorm3 trial outcomes. Qualitative data collection and process mapping activities will contribute to process research.
Stakeholder analysis Stakeholder analyses will be conducted in each DeWorm3 trial site at baseline (pre-launch), following trial launch, and at study endline. The purpose of the stakeholder analysis is to identify the individuals who influence or are influenced by effective targeted MDA and community-wide transmission interruption efforts and understand how the network dynamics may influence study outcomes and future policy development. A social network analysis strategy will be used to characterize the relationships between stakeholders in order to (1) describe and map members of the network, (2) characterize the relationship between the network members, and (  3 ) analyze the network using standard network measures such as density, centrality, and homophily  [12]. Data collection and analysis.
Qualitative research Qualitative research will be conducted at trial baseline, midline, and endline to identify factors influencing implementation quality, feasibility, and sustainability by site. Qualitative research will utilize the Consolidated Framework for Implementation Research (CFIR) as a guide for data collection and analysis. The CFIR is a validated tool utilized in the United States and increasingly in low-and middle-income countries  [14, 15]. The CFIR is built upon a number of preexisting implementation theories to provide a comprehensive meta-theoretical framework of 39 "constructs" that influence implementation  [16]. Application of the CFIR helps guide theory development and verify whether and why interventions work through the identification of core and modifiable intervention characteristics  [17].
e. national, district, etc. ). Baseline qualitative research will help refine CFIR construct selection for use during process and summative research as well. Data collection and analysis. Focus group discussions (FGDs) and individual interviews will be conducted with stakeholders from all levels of the health system. FGDs with clusterlevel stakeholders will take place in four randomly selected clusters per site, including community members, CDDs, and health center staff or CDD supervisors. FGD participants will be selected using random purposive sampling  [19]. Interviews will take place with individuals at higher levels of the health system. These individuals will be selected using purposive quota sampling of mutually exclusive key informant groups (i. e. stakeholder levels)  [20]. Trained interviewers who are fluent in local language and customs will conduct one-onone interviews and small FGDs in private locations with consenting individuals.
The interviews will be semi-structured key informant interviews with a mix of respondent and informant style questions. In each site, we use pragmatic criterion to determine the sample size, influenced by the number of levels of the site's health system. If it is deemed that data saturation has been achieved and redundancy criterion are met within a given stakeholder group after 80% of interviews have been conducted in that group, the sample size may be reduced. All interviews will be audio recorded and transcribed. Transcriptions will be translated to English. Two primary coders will independently code the site-specific transcripts using CFIR sub-constructs as analysis guides and coordinate their coding to create a comprehensive codebook and thematic analysis. Analyses will be based upon a deductive approach  [21].
Economic research The financial and economic costs and incremental cost-effectiveness of community-wide and targeted MDA for STH will be ascertained at the end of the DeWorm3 trial (following three years of the intervention and two years of surveillance). Using mathematical models, costs and cost-effectiveness will also be evaluated over a longer time horizon appropriate for an elimination scenario. Data collection and analysis. Inputs required to assess the financial and economic costs of community-wide and targeted MDA for STH will be collected in all DeWorm3 study sites using a standardized cost collection tool. Aligned with economic evaluation guidelines  [25] [26] [27] , the tool follows an ingredients-based micro-costing approach for estimating cost of health interventions; this methodology entails identification and measurement of all inputs required for the intervention, followed by their conversion into monetary value terms to produce a cost estimate.
The data will be collected throughout the implementation of the DeWorm3 trial. Data collection rounds will be triggered by site completion of specific trial activities (ex. completing a cross-sectional survey). Aligning data collection with trial activities and routine financial reporting will enhance the quality of the cost data collected by minimizing recall bias and limiting duplication of tasks within the project. The costs will be assessed from multiple perspectives, namely: individual (i. e. participant), societal, and health systems (i. e. government). Full incremental costs will be derived. Resource use will be valued both in terms of financial and economic costs, including time demanded by community members and Ministry of Health staff to participate in different aspects of the intervention.
A range of outcomes including the percent reduction from baseline to endline prevalence and the total number of prevalent infection case-years averted will be considered to both fully capture the impact of the interventions and allow for comparisons with other studies. The ultimate goal of DeWorm3 cost-effectiveness research is to provide policy makers and implementers with information regarding the efficiency of community-wide MDA for STH elimination in endemic settings. To this end, the trial will generate key epidemiological and cost data to populate mathematical models of STH epidemiology and control that can also be used to assess the impact of elimination strategies  [28, 29]. The models will produce estimates of the incremental impact of community wide MDA for STH for settings outside of the DeWorm3 trial and longer time horizons or 5, 10, 15, 25, and 50 years to appropriately capture STH elimination scenarios.
Acknowledgments We would like to thank all members of the DeWorm3 study teams and affiliated institutions who have provided feedback or contributed to the planning of implementation science activities, with special thanks to DeWorm3 Implementation Science team members  Dr. Euripide Avokpaho ,  Felicien Chabi ,  Alvin Chisambi ,  Dr. Laila Garda ,  Lazarus Juziwelo ,  Zachariah Kamwendo ,  Rutuja Patil ,  Dr. Sudipto Roy ,  James Simwanza ,  Dr. Ankita Shrivastava ,  Innocent Togbevi , and  Stefan Witek-McManus.
MEthods And AnAlysIs The DETECT study is a multicentre, open label, cluster randomised controlled trial, comparing an intervention arm (TM) to a control arm (usual care). The unit of randomisation was the LTCF. It is registered on ClinicalTrials. gov since 1 June 2015 ( ClinicalTrials. gov: NCT02472015). The protocol version is V. 8, 28 June 2017. LTCFs in the intervention group benefit from a TM programme for the management of NPS and the LTCFs in the control group benefit from usual care. Patients with NPS in usual care can be referred to inappropriate care (use of emergency facilities) or to appropriate care (memory consultations and specialised inpatient units), who also face their own limits and important delays. Twenty LTCFs were recruited and randomised in clusters after their consent: 10 LTCFs in the intervention group ('TM group') and 10 in the control group ('usual care group').
A second follow-up TM consultation takes place at 1 month (T1) in a similar way. randomisation Randomisation was done with STATA V. 11. 2. A cluster randomisation was performed with a 1:1 ratio from an anonymised LTCF research network database after their consent (excluding LTCFs that did not provide prior consent or with a number of beds under 60). 1  The randomisation was stratified on two LTCF characteristics: the region (around Toulouse or around Limoges) and the presence of an Alzheimer unit in the facility. The allocation procedure was conducted by the Department of Epidemiology of the Toulouse University Hospital in Toulouse, France. At enrolment, a fax is sent by the DETECT study group to this department, together with the LTCF code and information regarding assignment.
The secondary outcome measures are based on the measure (at the individual level) and comparison of both arms with regard to: ► The rate of hospitalisations and/or consultations due to disruptive NPS. ► Psychotropic drug use, as collected on the basis of the last medical prescription. ► Health costs. ► Patient's QOL. ► The cluster effect ('design effect'). These data are collected in both arms at baseline, 1 month and 2 months, with the exception of the medical and economic data that are collected at baseline and 2 months.
Follow-up visits Participants in both groups receive a follow-up visit at 1 month and at 2 months, including the assessment of secondary endpoints. The 1-month follow-up visit (T1) in the intervention group is led by the LTCF coordinator physician and a second TM session is then proposed under the same conditions. In the usual care group, the CRA simply collect data (T1). The third visit at 2 months (T2) involves both groups. In this visit (T2), assessments are performed and data from secondary outcomes are collected by the CRA. The inclusion and follow-up procedures are illustrated in figure  1.
Data collection The patients' outcomes are assessed in both groups. Sociodemographic data (age, sex, date of birth), length of stay in the facility, dementia diagnosis, patient parameters such as hospitalisations and/or consultations due to disruptive NPS, psychotropic drugs use, physical restraints use, falls…). Physical disability is based on the Activity of Daily Living scale. 35 NPS assessment is based on the Neuropsychiatric Inventory-Clinician rating scale. 36 QOL of patients is based on quality of life in Alzheimer's Disease (QoL-AD). 37 Health costs are evaluated at baseline (T0) and at 2-month visit (T1) (see economic assessment below). The outcomes in both groups are presented in table  1. The study is monitored by a clinical research technician, acting for the coordinating investigator and who is responsible for: the logistics and monitoring of the study, regular reports concerning its state of progress, update of the case report forms (eg, request for additional information), collecting and reporting adverse events.
Economic evaluation An economic study involving cost comparison will be performed to analyse possible cost differences between patients presenting NPS and receiving TM and those receiving usual care, at 2 months. This evaluation will focus on patients enrolled in the general scheme for employees of the French National Health Insurance (FNHI). Cost analysis will be performed from the FNHI's (paying agent) perspective, and more widely from society's perspective including the family's point of view. Costs taken into account are: direct medical costs including hospitalisation costs, ambulatory care costs and medical treatment costs; direct non-medical costs including transportation costs. Intangible costs, particularly pain, anxiety and lost QOL will not be assessed. Data will be collected from the FNHI regional agency database and hospitals when appropriate.
Data related to informal caregiver time will be collected using the Resource Use of Dementia questionnaire. 38 Hospital stays will be valued from the French diagnosis-related group. Ambulatory and transportation costs (ie, visits, medical and paramedical acts) will be valued from the appropriate reimbursement rate given by the FNHI. Informal care time will be valued using the replacement cost approach. 39 atistical analysis In a first descriptive stage, we will describe baseline characteristics of the facilities and of the included patients for each group. The main analysis will be carried out among the included patients in the intervention group. The proportion of TM solicitation for NPS management in the intervention group will be estimated during the 24 months of inclusions with a 95% CI.