Yoxas/statistical_literacy huggingface dataset:
Aiming at being part of the discussion about the cognitive functioning of patients with arachnoid cysts (AC) and the value of neuropsychological testing in these patients, we present our study in which we investigated the cognitive functioning of 32 children with ACs of the middle cranial fossa. We compared the Stanford Binet 5 (SB 5) results obtained by the patients with the population mean values and analysed the relation between the patients' clinical details and the results of SB 5. The main conclusions of this research are: (1) In SB 5 tasks, the tested group performed worse than the population mean, which could be related to AC of the middle cranial fossa. Deficits concern especially visuospatial reasoning, quantitative reasoning, and knowledge. The obtained results indicate the coexistence of cognitive impairment and AC of the middle cranial fossa. (2) In patients with AC, neuroimaging information has only limited predictive ability regarding cognitive syndromes. (3) The complaints reported in the interview are not necessarily objectively reflected in the clinical assessment. Neuropsychological assessment should be part of the management of all patients with AC. (4) Cognitive deficits in patients with AC may become more pronounced with age. Accordingly, increasing school difficulties in these patients should be expected. In light of the above, there is a clear indication of the need for neuropsychological support and support in school functioning for patients with AC. (5) Neuropsychological control in patients with AC is crucial not only with regard to treatment decisions but primarily for monitoring school performance and providing these patients with adequate neuropsychological and psychological support.
Aiming at the problem that ultra-wide band (UWB) cannot be accurately localized in environments with large noise variations and unknown statistical properties, a combinatorial localization method based on improved cubature (CKF) is proposed. First, in order to overcome the problem of inaccurate local approximation or even the inability to converge due to the initial value not being set near the optimal solution in the process of solving the UWB position by the least-squares method, the Levenberg-Marquardt algorithm (L-M) is adopted to optimally solve the UWB position. Secondly, because UWB and IMU information are centrally fused, an adaptive factor is introduced to update the measurement noise covariance matrix in real time to update the observation noise, and the fading factor is added to suppress the filtering divergence to achieve an improvement for the traditional CKF algorithm. Finally, the performance of the proposed combined localization method is verified by field experiments in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios, respectively. The results show that the proposed method can maintain high localization accuracy in both LOS and NLOS scenarios. Compared with the Extended Kalman filter (EKF), unbiased Kalman filter (UKF), and CKF algorithms, the localization accuracies of the proposed method in NLOS scenarios are improved by 25.2%, 18.3%, and 11.3%, respectively.
Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is used to eliminate the data noise of college dance teaching resource database, so as to obtain the missing value and complete the filling of incomplete data of college dance teaching resource database. Taking the preprocessed data as the basic element of transmission object statistics and analysis, establish the data transmission self-service channel of college dance teaching resource database, calculate the similarity of the data according to the unequal length sequence, and use the partial least square method to complete the feature extraction of the resource database data. According to the feature extraction results, particle swarm optimization algorithm is adopted to share the data of college dance teaching resource database. The simulation results show that the accuracy, recall, and F1 value of the data sharing method of college dance teaching resource database based on PSO algorithm are high, and the sharing time is short.
Aims This study aimed to assess the quality of life (QoL) of older adults in rural Odisha, India, exploring its multidimensional nature across physical, psychological, social, and environmental domains. The impact of depression and various sociodemographic factors on QoL was also investigated. Methods The research was conducted in the Tangi block of Khordha district, Odisha, encompassing 468 older adults. The World Health Organization Quality of Life Brief Version (WHOQOL-BREF) questionnaire, Geriatric Depression Scale (GDS-15), and sociodemographic questionnaire were used in data collection. Sampling employed a multistage approach, with statistical analysis utilizing Statistical Package for the Social Sciences (SPSS) version 20 (IBM SPSS Statistics, Armonk, NY), including t-tests for normally distributed data and the Mann-Whitney U test for non-normally distributed data. Results The QoL of older adults in rural Odisha showed variability, with physical and social domains exhibiting relatively positive scores compared to psychological and environmental domains. Depression significantly impacted all QoL dimensions, with the most profound effect observed in global QoL and global health. Sociodemographic factors such as employment, substance use, elder abuse, adverse life events, and poverty were identified as significant determinants of global QoL. Additionally, recreational activity, elder abuse, education, and employment significantly affected all QoL domains. Conclusions This study reveals the complex landscape of QoL of older adults in rural Odisha. The findings emphasize the need for comprehensive interventions targeting mental health, social support, and environmental conditions to enhance the overall well-being of this population. Policymakers and healthcare professionals should consider these multidimensional factors to develop effective strategies for improving the QoL of older adults in similar contexts.
Aims: The aim of this study was to test a Child-Centred Health Dialogue model for primary prevention of obesity for 4-year-old children in Child Health Services, for its feasibility and the responsiveness of its outcomes. Methods: A feasibility study was set up with a non-randomised quasi-experimental cluster design comparing usual care with a structured multicomponent Child-Centred Health Dialogue consisting of two parts: (1) a universal part directed to all children and (2) a targeted part for families where the child is identified with overweight. Results: In total, 203 children participated in Child-Centred Health Dialogue while 582 children received usual care. Nurses trained in the model were able to execute both the universal health dialogue and the targeted part of the intervention. Tutorship enabled the nurses to reflect on and discuss their experiences, which strengthened their confidence and security. One year after the intervention fewer normal-weight 4-year-olds in the intervention group had developed overweight at the age of five compared with the control group, and none had developed obesity. The difference in overweight prevalence at follow-up did not reach statistical significance. Conclusions: This study demonstrates that a child-centred, multicomponent, interactive intervention for the promotion of healthy lifestyles and primary prevention of obesity for all 4-year-old children participating in Child Health Services is feasible on a small scale. As almost all caregivers make use of Child Health Services in Sweden, the findings should be confirmed in a randomised controlled trial before the intervention can be implemented on a larger scale.
Aims: To identify, appraise and describe studies of cognitive interventions to improve diagnostic decision making (DDM) amongst medical professionals, assess their effectiveness and identify methodological limitations in existing studies. Methods: We systematically searched for studies (publication date 2000-2016) in multiple databases including Cochrane Controlled Trials, EMBASE, ERIC, Medline, PubMed and PsycINFO, and used additional strategies such as hand searching and snowballing. Included studies evaluated cognitive interventions to enhance DDM amongst medical professionals, using defined outcomes such as diagnostic accuracy. A meta-analysis assessed the impact of "reflection". Results: Forty-four studies out of 10,114 screened citations, involving 4380 medical professionals, were included. Studies evaluated reasoning workshops/curricula, de-biasing workshops, checklists, reflection, feedback, and instructions to induce analytical thinking. Guided reflection was demonstrated to improve DDM [effect size 0.38(95%CI 0.23-0.52), p < 0.001]. Immediate feedback and modeling reflection using contrasting examples also appeared to improve diagnostic accuracy, however underlying methodological issues prevented a quantitative assessment of any strategies other than reflection. Conclusions: Educational interventions incorporating practising deliberate reflection on a formulated diagnosis, modeled reflection on contrasting examples and immediate feedback are promising strategies for improving DDM. The effectiveness of other strategies is unknown, with more methodological refinements required in future research.
Air pollution (AP) is linked up to 20% of cardiovascular deaths. The aim of this nationwide study was to investigate subpopulations vulnerable to AP for non-ST- (NSTEMI) and ST-elevation myocardial infarction (STEMI) incidence. We analysed short- (lags up to seven days) and mid-term (0-30 days moving average) influence of particulate matter (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2) and benzo(a)pyrene (BaP) on hospitalizations due NSTEMI and STEMI in 2011-2020. Data on AP concentrations were derived using GEM-AQ model. Study included residents of five voivodeships in eastern Poland, inhabited by over 8,000,000 individuals. Higher NO2 and PM2.5 concentrations increased mid-term risk of NSTEMI in patients aged < 65 years by 1.3-5.7%. Increased SO2 and PM2.5 concentration triggered STEMI in the short- (SO2, PM2.5) and mid-term (PM2.5) amongst those aged ≥ 65 years. In the short- and mid-term, women were more susceptible to PM2.5 and BaP influence resulting in increased STEMI incidence. In rural regions, STEMI risk was triggered by SO2, PM2.5 and BaP. Income-based stratification showed disproportions regarding influence of BaP concentrations on NSTEMI incidence based on gross domestic product (up to 1.4%). There are significant disparities in the influence of air pollution depending on the demographic and socio-economic factors. AP exposure is associated with the threat of a higher risks of NSTEMI and STEMI, especially to younger people, women, residents of rural areas and those with lower income. National Science Center and Medical University of Bialystok, Poland.
Air pollution contributes to a large disease burden and some populations are disproportionately exposed. We aimed to evaluate ethnic and socioeconomic differences in exposure to air pollution in the Netherlands. We did a nationwide, cross-sectional analysis of all residents of the Netherlands on Jan 1, 2019. Sociodemographic information was centralised by Statistics Netherlands and mainly originated from the National Population Register, the tax register, and education registers. Concentrations of NO2, PM2·5, PM10, and elemental carbon, modelled by the National Institute for Public Health and the Environment, were linked to the individual-level demographic data. We assessed differences in air pollution exposures across the 40 largest minority ethnic groups. Evaluation of how ethnicity intersected with socioeconomic position in relation to exposures was done for the ten largest ethnic groups, plus Chinese and Indian groups, in both urban and rural areas using multivariable linear regression analyses. The total study population consisted of 17 251 511 individuals. Minority ethnic groups were consistently exposed to higher levels of air pollution than the ethnic Dutch population. The magnitude of inequalities varied between the minority ethnic groups, with 3-44% higher exposures to NO2 and 1-9% higher exposures to PM2·5 compared with the ethnic Dutch group. Average exposures were highest for the lowest socioeconomic group. Ethnic inequalities in exposure remained after adjustment for socioeconomic position and were of similar magnitude in urban and rural areas. The variability in air pollution exposure across ethnic and socioeconomic subgroups in the Netherlands indicates environmental injustice at the intersection of social characteristics. The health consequences of the observed inequalities and the underlying processes driving them warrant further investigation. The Gravitation programme of the Dutch Ministry of Education, Culture, and Science, the Netherlands Organization for Scientific Research, the Netherlands Organisation for Health Research and Development, and Amsterdam University Medical Center.
Air pollution is a pervasive global environmental challenge that presents substantial and differential risk across populations. Individual-level pollution exposure is a function of varying factors, including but not limited to geographic location, proximity to point sources, ventilation, and behavioral patterns. Mounting evidence suggests that informational interventions can play a substantial role in mediating exposures for specific population subgroups and reduce downstream adverse health outcomes. The literature has yet to address whether access to air quality information is sociodemographically stratified, and whether such access correlates with increased uptake of exposure reducing behaviors at the population level. This study represents a first step in answering these questions by analysing responses from the "Clean Air Public Insight Tracker" nationally representative survey (n = 1,993) of the UK population, administered by UK charity Global Action Plan. Results from logistic regression and zero-inflated negative binomial models estimate 28% of the population have accessed air pollution information, while the odds of younger individuals (ages 18-36), men, and non-white individuals of accessing digitally available air quality information are greater that those outside these categories. Additionally, the odds of behavior uptake is greater if an individual accesses digital information sources like the internet, mobile apps or social media, has a higher education qualification or cares for someone with a health condition. These findings contribute to the growing literature surrounding which population groups engage with environmental and health-relevant information channels, and what connects engagement with air quality channels and uptake of exposure reducing behaviors. These results reinforce the need for additional research around air pollution informational alerts and exploring causal links between specific exposure reducing behaviours and improved health outcomes. It can also help inform the flow of resources and targeting of informational campaigns towards sociodemographic groups that are less likely to engage with air quality information.
Air pollution is considered the most prominent public health. Economically, air pollution imposes additional costs on governments. This study aimed to quantify health effects and associated economic values of reducing PM2.5 air pollution using BenMAP-CE in Qom in 2019. The air quality data were acquired from Qom Province Environmental Protection Agency, and the population data were collected from Qom Province Management and Planning Organization website. The number of deaths due to Stroke, Chronic Obstructive Pulmonary Disease, Lung Cancer, and Ischemic Heart Disease attributable to PM2.5 were estimated using BenMAP-CE based on two control scenarios, 2.4 and 10 μg/m3, known as scenarios I and II, respectively. The associated economic effect of premature deaths was assessed by value of a statistical life (VSL) approach. The annual average of PM2.5 concentration was found to be 16.32 μg/m3 (SD: 9.93). A total of 4694.5 and 2475.94 premature deaths in scenarios I and II were found to be attributable to PM2.5 in overall, respectively. The total associated cost was calculated to be 855.91 and 451.40 million USD in scenarios I and II, respectively. The total years of life lost due to PM2.5 exposure in 2019 was 158,657.06 and 78,351.51 in scenarios I and II, respectively. The results of both health and economic assessment indicate the importance of solving the air pollution problem in Qom, as well as other big cities in Iran. The elimination of limitations, such as insufficient local data, should be regarded in future studies.
Airlines' fleet assignment heavily affects the economic and ecological performance of the global air transportation system (ATS). Consequently, it is inevitable to include potential changes of the fleet assignment when modeling and assessing future global ATS scenarios. Therefore, this article presents a novel explanatory approach to modeling the fleet assignment in the global ATS. The presented approach is based on formulating and solving an optimization problem, which describes the fleet assignment in the ATS through a suitable combination of objective function and constraints. While the objective function combines both the airline and the passenger perspective on the fleet assignment, the constraints include additional operational and technological aspects. In comparison to the available global fleet assignment models in the literature, which rely on statistical approaches, the advantages of the presented approach via an optimization problem lie in the overall scenario capability and the consideration of explicit aircraft types instead of simplifying seat categories. To calibrate and validate our model, we use 10 years of historic flight schedule data. The results underline the strengths and weaknesses of the presented approach and indicate potential for future improvement.
Airport security screening is a visual inspection task comprising search and decision. Problem solving is used to support decision making. However, it is not well understood. This study investigated how airport security screeners employ problem solving during x-ray screening, and how strategies change with experience. Thirty-nine professional security screeners were observed performing x-ray screening in the field at an Australian International Airport. Video and eye-tracking data were collected and analysed to explore activity phases and problem-solving strategies. Less-experienced screeners performed more problem solving and preferred problem-solving strategies that rely on visual examination without decision support or that defer decision making, compared to more-experienced screeners, who performed efficient and independent strategies. Findings also show that screeners need more time to develop problem-solving skills than visual scanning skills. Screeners would benefit from problem-solving support tools and intensified training and mentorship within the first six months of experience to advance problem-solving competencies.
AirRater is a free environmental health smartphone app developed and available in Australia that collects individual health data and disseminates environmental hazard information to populations. Following previous evaluations with app users, the aim of this study was to better understand how clinicians, government agency and non-government advocacy group representatives perceive an app designed to reduce the impacts of environmental hazards on individual and public health. Nine government agency and non-government advocacy group representatives, along with 11 clinicians based in Australia participated in a semi-structured interview or focus group to explore perspectives on AirRater. Interview and focus group data were transcribed and analysed using the qualitative data analysis software NVivo. Results indicate that for clinicians, apps like AirRater can add value as an educational, patient self-management and diagnostic tool. For government and peak bodies, apps can add value by addressing environmental health literacy and monitoring and forecasting gaps, as well as supporting advocacy efforts and public health surveillance. We conclude that environmental health smartphone apps can support a range of stakeholders to achieve shared goals and priorities related to individual and public health outcomes. Further research is needed to better understand how apps could be embedded into clinical practice and policy settings.
Alarm fatigue among nurses working in the intensive care unit has garnered considerable attention as a national patient safety priority. A viable solution for reducing the frequency of alarms and unnecessary noise is intensive care unit alarm monitor customization. A 24-bed cardiovascular and thoracic surgery intensive care unit in a large academic medical center identified a high rate of alarms and associated noise as a problem contributing to nurse alarm fatigue. An alarm monitor quality improvement project used both alarm frequency and nurse surveys before and after implementation to determine the effectiveness of interventions. Multimodal interventions included nurse training sessions, informational flyers, organizational policies, and an alarm monitor training video. Unexpected results inspired an extensive investigation and secondary analysis, which included examining the data-capturing capabilities of the alarm monitors and the impact of context factors. Alarm frequencies unexpectedly increased after the intervention. The software data-capturing features of the alarm monitors for determining frequency did not accurately measure nurse interactions with monitors. Measured increases in patient census, nurse staffing, and data input from medical devices from before to after the intervention substantially affected project results. Alarm frequencies proved an unreliable measure of nurse skills and practices in alarm customization. Documented changes in context factors provided strong anecdotal evidence of changed circumstances that clarified project results and underscored the critical importance of contemporaneous collection of context data. Designs and methods used in quality improvement projects must include reliable outcome measures to achieve meaningful results.