Yoxas/statistical_literacy huggingface dataset:
We recently found headache disorders to be highly prevalent among children (aged 6-11 years) and adolescents (aged 12-17) in Iran (gender- and age-adjusted 1-year prevalences: migraine 25.2%, tension-type headache 12.7%, undifferentiated headache [UdH] 22.1%, probable medication-overuse headache [pMOH] 1.1%, other headache on ≥ 15 days/month [H15+] 3.0%). Here we report on the headache-attributed burden, taking evidence from the same study. In a cross-sectional survey, following the generic protocol for the global schools-based study led by the Global Campaign against Headache, we administered the child and adolescent versions of the Headache-Attributed Restriction, Disability, Social Handicap and Impaired Participation (HARDSHIP) structured questionnaire in 121 schools, purposively selected to reflect the country's diversities. Pupils self-completed these in class, under supervision. Headache diagnostic questions were based on ICHD-3 criteria but for the inclusion of UdH (defined as mild headache with usual duration < 1 h). Burden enquiry was across multiple domains. The analysed sample (N = 3,244) included 1,308 (40.3%) children and 1,936 (59.7%) adolescents (1,531 [47.2%] male, 1,713 [52.8%] female). The non-participating proportion was 3.4%. Mean headache frequency was 3.9 days/4 weeks, and mean duration 1.8 h. Estimated mean proportion of time in ictal state was 1.1% (1.4% for migraine, 16.5% for pMOH). Symptomatic medication was consumed on a mean of 1.6 days/4 weeks. Lost school time averaged 0.4 days/4 weeks overall (2%, assuming a 5-day week), but was eleven-fold higher (4.3 days; 22%) for pMOH. For most headache types, days of reported limited activity were several-fold more than days lost from school (45% for pMOH, 25% for other H15+). Almost one in 12 parents (7.9%) missed work at least once in 4 weeks because of their son's or daughter's headache. Emotional impact and quality-of-life scores reflected these measures of burden. Headache, common in children and adolescents in Iran, is associated with symptom burdens that may be onerous for some but not for most. However, there are substantial consequential burdens, particularly for the 1.1% with pMOH and the 3.0% with other H15+, who suffer educational disturbances and potentially major life impairments. These findings are of importance to educational and health policies in Iran.
We recently reported strong, replicable (i.e., replicated) evidence for lexically mediated compensation for coarticulation (LCfC; Luthra et al., 2021), whereby lexical knowledge influences a prelexical process. Critically, evidence for LCfC provides robust support for interactive models of cognition that include top-down feedback and is inconsistent with autonomous models that allow only feedforward processing. McQueen, Jesse, and Mitterer (2023) offer five counter-arguments against our interpretation; we respond to each of those arguments here and conclude that top-down feedback provides the most parsimonious explanation of extant data.
We report a novel proposal for reducing the digital divide in rural multigrade schools, incorporating knowledge of robotics with a STEM approach to simultaneously promote curricular learning in mathematics and science in several school grades. We used an exploratory qualitative methodology to implement the proposal with 12 multigrade rural students. We explored the contribution of the approaches to the promotion of curricular learning in mathematics and science and the perceptions of using robotics to learn mathematics and science. As data collection techniques, we conducted focus groups and semi-structured interviews with the participants and analyzed their responses thematically. We concluded that the proposal could contribute to meeting the challenges of multigrade teaching. Our findings suggest that the proposal would simultaneously promote the development of curricular learning in mathematics and science in several school grades, offering an alternative for addressing various topics with different degrees of depth.
We report findings from a survey of elementary teachers regarding reading instruction. The purpose was to examine teachers' beliefs about how children in the first 7 years of schooling develop reading comprehension skills and to characterize the self-reported practices and strategies they use to support children to comprehend connected text. A web-based survey was used to collect data from 284 Australian elementary teachers about their beliefs and practices regarding reading comprehension instruction. Selected Likert-scale items were aggregated to determine the degree to which participants held "child-centered" or "content-centered" views of reading instruction. Australian elementary school teachers hold a wide range of beliefs about reading instruction, some of which are in direct opposition to each other. Our findings indicate low consensus about what elements of instructional practice are useful in classrooms or how time should be apportioned to different tasks. Commercial programs had significant penetration in schools, and many participants reported using multiple commercial programs, with varying degrees of pedagogical harmony. Participants indicated that their most common source of knowledge about reading instruction was their own personal research, with few nominating university teacher education as a primary source of knowledge or expertise. Little agreement exists within the Australian elementary teacher community regarding the ways that reading skills can and should be taught. There is significant room for teacher practice to have improved theoretical underpinnings and to develop a consistent repertoire of classroom practices aligned with these.
We report the results of one visual-world eye-tracking experiment and two referent selection tasks in which we investigated the effects of information structure in the form of prosody and word order manipulation on the processing of subject pronouns er and der in German. Factors such as subjecthood, focus, and topicality, as well as order of mention have been linked to an increased probability of certain referents being selected as the pronoun's antecedent and described as increasing this referent's prominence, salience, or accessibility. The goal of this study was to find out whether pronoun processing is primarily guided by linguistic factors (e.g., grammatical role) or nonlinguistic factors (e.g., first-mention), and whether pronoun interpretation can be described in terms of referents' "prominence" / "accessibility" / "salience." The results showed an overall subject preference for er, whereas der was affected by the object role and focus marking. While focus increases the attentional load and enhances memory representation for the focused referent making the focused referent more available, ultimately it did not affect the final interpretation of er, suggesting that "prominence" or the related concepts do not explain referent selection preferences. Overall, the results suggest a primacy of linguistic factors in determining pronoun resolution.
We review four established scales for measuring individual differences in trait-level nostalgia: the Nostalgia Inventory, the Southampton Nostalgia Scale, the Nostalgia Prototype Scale, and the Personal Inventory of Nostalgic Experiences. To examine their convergent validity, we re-analyzed data from a published study in which all four scales were administered simultaneously. Multi-group confirmatory factor analyses demonstrated that a one-factor model accurately described the interrelations among the four scales, and supported full metric and partial scalar invariance across U.S. and Chinese samples. When measuring trait nostalgia, we recommend that researchers also consider potential confounders. Specifically, we discuss the importance of controlling for other ways in which individuals habitually reflect on their past, including brooding rumination and upward self-referent counterfactual thinking.
We review some powerful new algorithms that build on the intuitive biological interpretation techniques for statistical analysis of functional genomics experiments. Although they were originally designed for transcriptomics, we argue that these algorithms are applicable to any type of -omics study (transcriptomics, proteomics, metabolomics). Rank Products (RP), a strictly non-parametric test statistic to detect differentially regulated elements (genes, proteins, metabolites) in genome-wide screens. RP is particularly powerful for noisy data and low numbers of replicates and makes full use of the availability of a large number of parallel measurements that is typical of modern large-scale experiments. Iterative Group Analysis (iGA), a statistical method that makes the transition from regulated single elements to significant classes of elements, and thus provides an automatic functional annotation of an experiment. Graph-based iGA (GiGA), an extension of iGA that combines experimental data with a broad variety of biological annotations to highlight physiologically relevant regions in a given "evidence graph" (e.g., metabolic networks, signaling pathway diagrams, protein interaction maps). The sequential application of these techniques yields an increasingly abstract interpretation of experimental data that is at the same time quantitative, statistically rigorous, and biologically significant. The results can be used either as helpful tools to guide data visualization and exploration, or as the input for downstream computational applications in a systems biology framework.
We sought in-depth understanding on the evolution of factors influencing COVID-19 booster dose and bivalent vaccine hesitancy in a longitudinal semi-structured interview-based qualitative study. Serial interviews were conducted between July 25th and September 1st, 2022 (Phase I: univalent booster dose availability), and between November 21st, 2022 and January 11th, 2023 (Phase II: bivalent vaccine availability). Adults (≥18 years) in Canada who had received an initial primary series and had not received a COVID-19 booster dose were eligible for Phase I, and subsequently invited to participate in Phase II. Twenty-two of twenty-three (96%) participants completed interviews for both phases (45 interviews). Nearly half of participants identified as a woman (n = 11), the median age was 37 years (interquartile range: 32-48), and most participants were employed full-time (n = 12); no participant reported needing to vaccinate (with a primary series) for their workplace. No participant reported having received a COVID-19 booster dose at the time of their interview in Phase II. Three themes relating to the development of hesitancy toward continued vaccination against COVID-19 were identified: 1) effectiveness (frequency concerns; infection despite vaccination); 2) necessity (less threatening, low urgency, alternate protective measures); and 3) information (need for data, contradiction and confusion, lack of trust, decreased motivation). The data from interviews with individuals who had not received a COVID-19 booster dose or bivalent vaccine despite having received a primary series of COVID-19 vaccines highlights actionable targets to address vaccine hesitancy and improve public health literacy.
We sought to assess trends in emergency medicine residency program director (PD) length of service over the past 40 years and evaluate relationships between duration of service and important factors such as PD start year, geographic region, and year of program initial accreditation. We retrospectively analyzed program data from the American Medical Association Graduate Medical Education Directory and Emergency Medicine Residents' Association Match database. We calculated descriptive statistics and used linear regression to assess the impact of PD start year, region, and year of program initial accreditation on PD duration of service. We gathered data on 783 unique PDs between 1983 and 2023. The overall mean ± SD PD duration of service was 6.19 ± 4.72 years (range 1-29 years). The mean duration of service by decade of start date was 6.49 years in the 1980s, 7.39 years in the 1990s, 5.92 years in the 2000s, 4.08 years in the 2010s, and 2 years in the 2020s. Both PD start year (p = 0.002) and program initial accreditation year (p = 0.001) significantly predicted duration of PD service. Region did not significantly predict duration of PD service (p = 0.225). Duration of service as a PD is decreasing in recent decades. Both PD start year and year of initial program accreditation significantly predict duration of service as PD. Future research must be done to better understand this phenomenon and uncover strategies to promote PD longevity.
We sought to characterise the role of hospital infection pharmacists in the UK and to understand the core challenges being faced, future role development desires and the required support to address these. We developed a questionnaire underpinned by the theoretical domains framework exploring the barriers and enablers to pharmacists fulfilling their perceived roles and responsibilities. Any pharmacist whose role included 'specialist antimicrobial' or 'infectious diseases' was invited to complete a questionnaire sent via national infection and pharmacy groups/networks. Descriptive statistics were used to report responses to each item, and a content analysis was undertaken to summarize the key messages from an extended response option. Of the 102 respondents, 91 (89.2%) were from English hospitals. Fifty-three (52%) were from district general hospitals and 45 (45.1%) from teaching hospitals. Most (97, 95%) respondents were of a senior grade. The need for a comprehensive educational programme, recognition of research as core to the role and integration with infection/microbiology departments were key requirements along with protected time to engage with the activities. Highlights of the role were opportunities to teach, making a significant contribution to patient care and scope to contribute to strategy and vision. The COVID-19 pandemic negatively impacted on respondents' capacity to undertake their perceived roles and responsibilities. Our study delineates the need for UK infection and pharmacy policy makers to review hospital infection pharmacist developmental pathways and roles. Joint learning, and closer working, with infection/microbiology departments may be an efficient strategy to address the issues raised.
We sought to identify the impact of the COVID-19 pandemic on the Oman Dental College (ODC) students' management of their educational and student life. We conducted a quantitative cross-sectional online survey study using SurveyMonkey. During the 2019-2020 academic year, 383 ODC students across six levels of education were invited to participate in the survey. Descriptive statistics were applied to the students' demographic profiles, and other characteristics of the participants' data were analyzed. Cronbach's alpha was calculated for internal consistency. A univariate analysis was carried out to identify the differences between genders and between the Bachelor of Dental Surgery levels in relation to the questionnaire themes. A Pearson's correlation test evaluated the association between students' perception of risks due to the pandemic and the other relevant themes. A 50.9% response rate revealed that five of the themes showed internal reliability ranging from excellent to acceptable, namely: performance of exercise, effect of the pandemic on their families, use of a facemask, college's online services, and students' mental health (0.51, 0.59, 0.70, 0.78, and 0.90, respectively). More than half of the participants felt encouraged to engage in self-directed learning using online resources. They felt some level of nervousness, worry, anxiety, or tension as well as stress during the pandemic. Statistical differences between levels of education were noted in the ODC's-online teaching services (p < 0.001) and students' mental health (p = 0.03). There was no difference between female and male students. The ODC's online services theme positively related to the students' mental health theme (r = 0.22, p < 0.001). ODC students experienced some mental health issues during the pandemic, including anxiety, stress, and sleeping issues. However, the majority of them were healthy. Most students were satisfied with the online teaching provided by ODC. It was also evident that faculty were always connected with the students. A positive relationship was noted between the management of online lectures and students' mental health.
We sought to measure patient portal satisfaction with patient portals and characterize its relationship to attitude towards computers, health literacy, portal usage, and patient demographics. We invited 13 040 patients from an academic medical center to complete a survey measuring satisfaction, perceived control over computers, and health literacy using validated instruments (End User Computing Satisfaction, Computer Attitude Measure, and Brief Health Literacy Screen). We extracted portal usage and demographic information from the medical center data warehouse. A total of 6026 (46.2%) patients completed the survey. The median (IQR) scores for satisfaction, computer control, and health literacy were 87% (20%), 86% (22%), and 95% (15%), respectively. The normalized mean (SD) usage of messaging, lab, appointment, medication, and immunization functions were 6.6 (2.6), 4.6 (2.4), 3.1 (1.7), 1.5 (1.2), and 0.88 (0.91) times, respectively. Logistic regression yielded significant odds ratios [99% CI] for computer control (3.6 [2.5-5.2]), health literacy (12 [6.9-23]), and immunization function usage (0.84 [0.73-0.96]). Respondents were highly satisfied and had high degrees of computer control and health literacy. Statistical analysis revealed that higher computer control and health literacy predicted higher satisfaction, whereas usage of the immunization function predicted lower satisfaction. Overall, the analytical model had low predictive capability, suggesting that we failed to capture the main drivers of satisfaction, or there was inadequate variation in satisfaction to delineate its contributing factors. This study provides insight into patient satisfaction with and usage of a patient portal. These data can guide the development of the patient portal, with the ultimate goal of increasing functionality and usability to enhance the patient experience.
We studied how brain volume loss in old age is affected by age, the APOE gene, sex, and the level of education completed. The quantitative characterization of brain volume loss at an old age relative to a young age requires-at least in principle-two MRI scans, one performed at a young age and one at an old age. There is, however, a way to address this problem when having only one MRI scan obtained at an old age. We computed the total brain losses of elderly subjects as a ratio between the estimated brain volume and the estimated total intracranial volume. Magnetic resonance imaging (MRI) scans of 890 healthy subjects aged 70 to 85 years were assessed. A causal analysis of factors affecting brain atrophy was performed using probabilistic Bayesian modelling and the mathematics of causal inference. We found that both age and sex were causally related to brain atrophy, with women reaching an elderly age with a 1% larger brain volume relative to their intracranial volume than men. How the brain ages and the rationale for sex differences in brain volume losses during the adult lifespan are questions that need to be addressed with causal inference and empirical data. The graphical causal modelling presented here can be instrumental in understanding a puzzling scientific area of study-the biological aging of the brain.
We study parametric inference on a rich class of hazard regression models in the presence of right-censoring. Previous literature has reported some inferential challenges, such as multimodal or flat likelihood surfaces, in this class of models for some particular data sets. We formalize the study of these inferential problems by linking them to the concepts of near-redundancy and practical nonidentifiability of parameters. We show that the maximum likelihood estimators of the parameters in this class of models are consistent and asymptotically normal. Thus, the inferential problems in this class of models are related to the finite-sample scenario, where it is difficult to distinguish between the fitted model and a nested nonidentifiable (i.e., parameter-redundant) model. We propose a method for detecting near-redundancy, based on distances between probability distributions. We also employ methods used in other areas for detecting practical nonidentifiability and near-redundancy, including the inspection of the profile likelihood function and the Hessian method. For cases where inferential problems are detected, we discuss alternatives such as using model selection tools to identify simpler models that do not exhibit these inferential problems, increasing the sample size, or extending the follow-up time. We illustrate the performance of the proposed methods through a simulation study. Our simulation study reveals a link between the presence of near-redundancy and practical nonidentifiability. Two illustrative applications using real data, with and without inferential problems, are presented.
We study two approaches for predicting an appropriate pose for a robot to take part in group formations typical of social human conversations subject to the physical layout of the surrounding environment. One method is model-based and explicitly encodes key geometric aspects of conversational formations. The other method is data-driven. It implicitly models key properties of spatial arrangements using graph neural networks and an adversarial training regimen. We evaluate the proposed approaches through quantitative metrics designed for this problem domain and via a human experiment. Our results suggest that the proposed methods are effective at reasoning about the environment layout and conversational group formations. They can also be used repeatedly to simulate conversational spatial arrangements despite being designed to output a single pose at a time. However, the methods showed different strengths. For example, the geometric approach was more successful at avoiding poses generated in nonfree areas of the environment, but the data-driven method was better at capturing the variability of conversational spatial formations. We discuss ways to address open challenges for the pose generation problem and other interesting avenues for future work.