Uncertainty and flexibility of fertility intentions.

Large-scale survey data is widely used to study the intention to have a(nother) child. However, there are further opportunities to understand how these intentions are revised over the life course and the uncertainty surrounding them. We aim to further outline the importance of simultaneously considering change and uncertainty in fertility decision-making. Specifically, we identify uncertainty in the "probably not" and "probably yes" responses to questions on whether an individual intends to have a(nother) child, and compare the differences in individuals' stated intention between survey waves. Using panel data from the Generations and Gender Survey (GGS) for Austria, France, Hungary, Italy, and Poland, we study short-term followed by long-term (overall) fertility intentions. First, descriptive analyses compare and visualise the prevalence of uncertainty intentions at first and second wave using Sankey diagrams. Next, multivariate analyses on transitions in intentions focus on partnership and employment context. The results reveal that for both short-term and overall intentions, four in ten respondents are uncertain about intending a (further) child. Further, one in two report a different intention between waves, with changes mainly occurring from one "probably" response to another (e.g., "probably not" to "probably yes") or through a shift in increasing or lessening certainty (e.g., "probably yes" to "definitely yes"). The childless exhibit by far the greatest uncertainty and revision. Multivariate analyses show that partnership and employment are associated with gradual transitions and larger changes in intentions. Our results also show that fertility intentions form to a large extent along a spectrum of certainty-from "definitely not," to "probably not," to "probably yes," to "definitely yes," and finally to the birth of a child.

Longitudinal Transition Patterns of Tobacco Use Among Youth and Young Adults Never Tobacco Product Users: Findings From the Population Assessment of Tobacco and Health Study, 2014-2019.

Aims: To identify, visualize, and describe the prevalence of within-product patterns of tobacco use behaviors for e-cigarettes, cigarettes, and hookah (TP) by 3 age groups (ie, 12-14-year-old, 15-17-year-old, and 18-20-year-old) with U.S. nationally representative data. Methods: In 2014-2015, never users of each (TP) and age group were followed-up longitudinally between 2015-2019 using five transition states: non-susceptible to (TP) use, susceptible to (TP) use, ever (TP) use, past 30-day (TP) use, and discontinued past 30-day (TP) use. Sankey diagrams were used to graphically visualize patterns in tobacco use behaviors across time. Results: Among 12-14-year-old who were never users and susceptible to each TP from 2014-2017, 7% initiated ever e-cigarette use and 9.4% first reported past 30-day use by 2018-2019; 5.8% initiated ever cigarette use and 3% first reported past 30-day cigarette use by 2018-2019; and, 4.5% initiated ever hookah use and 1.0% first reported past 30-day hookah use by 2018-2019. Among 15-17-year-old who were never users and susceptible to each TP from 2014-2017, 4.2% initiated ever e-cigarette use and 9.0% first reported past 30-day use by 2018-2019; 4.5% initiated ever cigarette use and 3% first reported past 30-day cigarette use by 2018-2019; and, 4.5% initiated ever hookah use and 2.4% first reported past 30-day hookah use by 2018-2019. Among 18-20-year-old who were never users and susceptible to each TP from 2014-2017, 3.2% initiated ever e-cigarette use and 3.6% first reported past 30-day e-cigarette use by 2018-2019; 3.0% initiated ever cigarette use and 2.3% first reported past 30-day cigarette use; and, 2.8% initiated ever hookah use and 1.0% first reported past 30-day hookah use by 2018-2019. Conclusions: From 2014 to 2019, onset and progression of e-cigarette, cigarette, and hookah use occurred more frequently in 12-14 and 15-17-year-old than in young adults 18-20-year-old.

Analysis and visualization of the course and burden over time of adverse drug reactions (ADRs) attributed to TNFα-inhibitors in patients with inflammatory rheumatic diseases (IRDs).

BACKGROUND: We aimed to investigate course and burden over time of ADRs attributed to TNFα-inhibitors in IRD-patients, and whether Sankey diagrams and polar plots can visualize this. RESEARCH DESIGN AND METHODS: Data on ADRs experienced during the Dutch Biologic Monitor (January 2017 till December 2022) were used in this study. We selected IRD-patients using a TNFα-inhibitor, reporting skin reactions/infections/injection site reactions and completing ≥3 questionnaires (i.e. the initial report and ≥2 follow-ups). Course was scored as worsening/improving/remaining stable/resolving and as (non-)recurrent. Patients scored burden from 1 (no burden) to 5 (very high burden). Sankey diagrams and polar plots visualized this. RESULTS: 202 patients were included, reporting 353 ADRs. Most skin reactions were stable (25.0%). Most infections resolved (50.8%). Injection site reactions were mostly recurrent (72.3%). Skin reactions and infections tended to decrease in burden . Infections had highest burden at start, which mostly decreased over time. Injection site reactions had a low and stable burden. CONCLUSIONS: Skin reactions attributed to TNFα-inhibitors by IRD-patients are stable with a slightly decreasing burden over time. Infections have highest burden at start but resolved mostly. Injection site reactions have a low and stable burden. Sankey diagrams and polar plots are suitable to visualize this.

Sankey diagrams can clarify 'evidence attrition': A systematic review and meta-analysis of the effectiveness of rapid diagnostic tests for antimicrobial resistance.

OBJECTIVES: To demonstrate, using the example of a new systematic review of rapid diagnostic tests, how Sankey diagrams, alongside the PRISMA guidelines, can (i) facilitate reporting of the quality of the evidence base and (ii) help assess evidence syntheses when studies use heterogeneous outcomes. METHODS: Systematic review and meta-analysis of experimental and observational studies which included at least one prescribing or clinical outcome of RDTs in hospital in-patients. Sub-group analysis was used to assess heterogeneity in summary effect estimates. A Sankey diagram was then used to show the pattern and quality of evidence on RDT outcomes. RESULTS: 57 studies from 14 countries were included. The introduction of RDTs did not significantly reduce in-hospital mortality (RR 0.83, 95% CI 0.60 - 1.15) or length of stay (weighted mean difference = -0.36, 95% CI -1.67 to 0.96). There was high heterogeneity in outcomes. CONCLUSION: There is no clear evidence that the routine use of RDTs for bacterial identification and antibiotic susceptibility testing improves clinical outcomes in hospital in-patients. Sankey diagrams may be a useful further way succinctly to present the pattern and quality of evidence in systematic reviews, especially when it is heterogeneous and not easily amenable to meta-analysis.

Using Sankey diagrams to visualize drag and drop action sequences in technology-enhanced items.

We propose a Sankey diagram-based visualization method to illustrate test-takers' action sequences in technology-enhanced, drag-and-drop items. This method extends existing studies focusing only on initial or last attempt(s) of answer formulation, and extracts, at the item level, comprehensive information of test-takers' drag-and-drop actions. Using the process data from three mathematical items in the National Assessment of Educational Progress, we exemplify how to develop Sankey diagrams, discover frequent actions at each stage of problem solving, deduce test-takers' response strategies, and discuss the relationship among domain (i.e., mathematics) knowledge, response strategy, and item performance. The applications and future extensions of this method can contribute to process-based problem-solving research in educational assessments.

Assessment of alkaline stabilization processes in industrial waste streams using a model-based approach.

Chemical conditioning prior to disposal is a common practice in biotech companies to stabilize the biological waste generated during production. Nevertheless, the state of the art models used to analyze management strategies in water treatment systems (WTS) do not include the effect of high alkaline conditions during bio-solids processing. In this paper, the prediction capabilities of a novel model-based approach describing the effect of quicklime addition (CaO) on the waste streams of an industrial WTS is assessed. Two measuring campaigns were carried out taking samples of TSS, VSS and total/soluble COD, N, P, S and multiple metals before and after chemical stabilization, and dewatering under and overflow. Mass balances were set up and Sankey diagrams were generated to represent the occurrence, transformation and fate of the major compounds within the studied facility. A simulation model was used to predict plant at different locations. Next, a scenario analysis was carried out in order to assess potential alternatives to the current operational practice. The resulting mass balances show a mismatch between the system's input and output up to 17%. It was also possible to identify different types of compound-behavior depending on the effect that high pH induced on the soluble and particulate fractions: hydrolysis, precipitation and unaltered. Model predictions and measurements differed 9.6% (steady state) and 12.4% (dynamic state) respectively. Finally, in the scenario analysis, the model suggested that the change from quicklime to sodium hydroxide (NaOH) would increase the quantity of organics in the dewatered cake (+23%), but with a considerable increase in chemical consumption (+50%). The selective stabilization of the incoming streams has the lowest use of chemicals (-30%) and reduces the load of CODsol (-13%) and TNsol (-14%) recirculated to the water line of the WWTP.