Exploring open science practices in behavioural public policy research.

In their book 'Nudge: Improving Decisions About Health, Wealth and Happiness', Thaler & Sunstein (2009) argue that choice architectures are promising public policy interventions. This research programme motivated the creation of 'nudge units', government agencies which aim to apply insights from behavioural science to improve public policy. We closely examine a meta-analysis of the evidence gathered by two of the largest and most influential nudge units (DellaVigna & Linos (2022 Econometrica 90, 81-116 (doi:10.3982/ECTA18709))) and use statistical techniques to detect reporting biases. Our analysis shows evidence suggestive of selective reporting. We additionally evaluate the public pre-analysis plans from one of the two nudge units (Office of Evaluation Sciences). We identify several instances of excellent practice; however, we also find that the analysis plans and reporting often lack sufficient detail to evaluate (unintentional) reporting biases. We highlight several improvements that would enhance the effectiveness of the pre-analysis plans and reports as a means to combat reporting biases. Our findings and suggestions can further improve the evidence base for policy decisions.

Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics.

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine.

Children Value Animals More Than Adults Do: A Conceptual Replication and Extension.

Recent psychological research finds that U.S. American children have a weaker tendency than U.S. American adults to value humans more than animals. We aimed to conceptually replicate and extend this finding in a preregistered study (N = 412). We investigated whether 6- to 9-year-old Polish children (Study 1a) are less likely to prioritize humans over animals than Polish adults are (Studies 1b and 1c). We presented participants with moral dilemmas where they had to prioritize either humans or animals (dogs or chimpanzees) in situations that involved harming (i.e., a trolley problem) or benefiting (i.e., giving a snack). We found that Polish children prioritized humans over animals less than Polish adults did. This was the case both in dilemmas that involved preventing harm and in dilemmas that involved providing snacks. Both children and adults prioritized humans over chimpanzees more than humans over dogs.

Meta-analyses in psychology often overestimate evidence for and size of effects.

Adjusting for publication bias is essential when drawing meta-analytic inferences. However, most methods that adjust for publication bias do not perform well across a range of research conditions, such as the degree of heterogeneity in effect sizes across studies. Sladekova et al. 2022 (Estimating the change in meta-analytic effect size estimates after the application of publication bias adjustment methods. Psychol. Methods) tried to circumvent this complication by selecting the methods that are most appropriate for a given set of conditions, and concluded that publication bias on average causes only minimal over-estimation of effect sizes in psychology. However, this approach suffers from a 'Catch-22' problem-to know the underlying research conditions, one needs to have adjusted for publication bias correctly, but to correctly adjust for publication bias, one needs to know the underlying research conditions. To alleviate this problem, we conduct an alternative analysis, robust Bayesian meta-analysis (RoBMA), which is not based on model-selection but on model-averaging. In RoBMA, models that predict the observed results better are given correspondingly larger weights. A RoBMA reanalysis of Sladekova et al.'s dataset reveals that more than 60% of meta-analyses in psychology notably overestimate the evidence for the presence of the meta-analytic effect and more than 50% overestimate its magnitude.

Comparing theories with the Ising model of explanatory coherence.

Theories are among the most important tools of science. Lewin (1943) already noted "There is nothing as practical as a good theory." Although psychologists discussed problems of theory in their discipline for a long time, weak theories are still widespread in most subfields. One possible reason for this is that psychologists lack the tools to systematically assess the quality of their theories. Thagard (1989) developed a computational model for formal theory evaluation based on the concept of explanatory coherence. However, there are possible improvements to Thagard's (1989) model and it is not available in software that psychologists typically use. Therefore, we developed a new implementation of explanatory coherence based on the Ising model. We demonstrate the capabilities of this new Ising model of Explanatory Coherence (IMEC) on several examples from psychology and other sciences. In addition, we implemented it in the R-package IMEC to assist scientists in evaluating the quality of their theories in practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Unrestricted weighted least squares represent medical research better than random effects in 67,308 Cochrane meta-analyses.

OBJECTIVES: To evaluate how well meta-analysis mean estimators represent reported medical research and establish which meta-analysis method is better using widely accepted model selection measures: Akaike information criterion (AIC) and Bayesian information criterion (BIC). STUDY DESIGN AND SETTING: We compiled 67,308 meta-analyses from the Cochrane Database of Systematic Reviews (CDSR) published between 1997 and 2020, collectively encompassing nearly 600,000 medical findings. We compared unrestricted weighted least squares (UWLS) vs. random effects (RE); fixed effect was also secondarily considered. RESULTS: The probability that a randomly selected systematic review from the CDSR would favor UWLS over RE is 79.4% (95% confidence interval [CI95%]: 79.1; 79.7). The odds ratio that a Cochrane systematic review would substantially favor UWLS over RE is 9.33 (CI95%: 8.94; 9.73) using the conventional criterion that a difference in AIC (or BIC) of two or larger represents a 'substantial' improvement. UWLS's advantage over RE is most prominent in the presence of low heterogeneity. However, UWLS also has a notable advantage in high heterogeneity research, across different sizes of meta-analyses and types of outcomes. CONCLUSION: UWLS frequently dominates RE in medical research, often substantially. Thus, the UWLS should be reported routinely in the meta-analysis of clinical trials.

Robust Bayesian meta-analysis: Model-averaging across complementary publication bias adjustment methods.

Publication bias is a ubiquitous threat to the validity of meta-analysis and the accumulation of scientific evidence. In order to estimate and counteract the impact of publication bias, multiple methods have been developed; however, recent simulation studies have shown the methods' performance to depend on the true data generating process, and no method consistently outperforms the others across a wide range of conditions. Unfortunately, when different methods lead to contradicting conclusions, researchers can choose those methods that lead to a desired outcome. To avoid the condition-dependent, all-or-none choice between competing methods and conflicting results, we extend robust Bayesian meta-analysis and model-average across two prominent approaches of adjusting for publication bias: (1) selection models of p-values and (2) models adjusting for small-study effects. The resulting model ensemble weights the estimates and the evidence for the absence/presence of the effect from the competing approaches with the support they receive from the data. Applications, simulations, and comparisons to preregistered, multi-lab replications demonstrate the benefits of Bayesian model-averaging of complementary publication bias adjustment methods.

Robust Bayesian meta-analysis: Addressing publication bias with model-averaging.

Meta-analysis is an important quantitative tool for cumulative science, but its application is frustrated by publication bias. In order to test and adjust for publication bias, we extend model-averaged Bayesian meta-analysis with selection models. The resulting robust Bayesian meta-analysis (RoBMA) methodology does not require all-or-none decisions about the presence of publication bias, can quantify evidence in favor of the absence of publication bias, and performs well under high heterogeneity. By model-averaging over a set of 12 models, RoBMA is relatively robust to model misspecification and simulations show that it outperforms existing methods. We demonstrate that RoBMA finds evidence for the absence of publication bias in Registered Replication Reports and reliably avoids false positives. We provide an implementation in R so that researchers can easily use the new methodology in practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

DE-PASS Best Evidence Statement (BESt): modifiable determinants of physical activity and sedentary behaviour in children and adolescents aged 5-19 years-a protocol for systematic review and meta-analysis.

INTRODUCTION: Physical activity among children and adolescents remains insufficient, despite the substantial efforts made by researchers and policymakers. Identifying and furthering our understanding of potential modifiable determinants of physical activity behaviour (PAB) and sedentary behaviour (SB) is crucial for the development of interventions that promote a shift from SB to PAB. The current protocol details the process through which a series of systematic literature reviews and meta-analyses (MAs) will be conducted to produce a best-evidence statement (BESt) and inform policymakers. The overall aim is to identify modifiable determinants that are associated with changes in PAB and SB in children and adolescents (aged 5-19 years) and to quantify their effect on, or association with, PAB/SB. METHODS AND ANALYSIS: A search will be performed in MEDLINE, SportDiscus, Web of Science, PsychINFO and Cochrane Central Register of Controlled Trials. Randomised controlled trials (RCTs) and controlled trials (CTs) that investigate the effect of interventions on PAB/SB and longitudinal studies that investigate the associations between modifiable determinants and PAB/SB at multiple time points will be sought. Risk of bias assessments will be performed using adapted versions of Cochrane's RoB V.2.0 and ROBINS-I tools for RCTs and CTs, respectively, and an adapted version of the National Institute of Health's tool for longitudinal studies. Data will be synthesised narratively and, where possible, MAs will be performed using frequentist and Bayesian statistics. Modifiable determinants will be discussed considering the settings in which they were investigated and the PAB/SB measurement methods used. ETHICS AND DISSEMINATION: No ethical approval is needed as no primary data will be collected. The findings will be disseminated in peer-reviewed publications and academic conferences where possible. The BESt will also be shared with policy makers within the DE-PASS consortium in the first instance. SYSTEMATIC REVIEW REGISTRATION: CRD42021282874.

High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells.

In recent years, low-temperature polymer electrolyte fuel cells have become an increasingly important pillar in a zero-carbon strategy for curbing climate change, with their potential to power multiscale stationary and mobile applications. The performance improvement is a particular focus of research and engineering roadmaps, with water management being one of the major areas of interest for development. Appropriate characterisation tools for mapping the evolution, motion and removal of water are of high importance to tackle shortcomings. This article demonstrates the development of a 4D high-speed neutron imaging technique, which enables a quantitative analysis of the local water evolution. 4D visualisation allows the time-resolved studies of droplet formation in the flow fields and water quantification in various cell parts. Performance parameters for water management are identified that offer a method of cell classification, which will, in turn, support computer modelling and the engineering of next-generation flow field designs.

Using selection models to assess sensitivity to publication bias: A tutorial and call for more routine use.

In meta-analyses, it is critical to assess the extent to which publication bias might have compromised the results. Classical methods based on the funnel plot, including Egger's test and Trim-and-Fill, have become the de facto default methods to do so, with a large majority of recent meta-analyses in top medical journals (85%) assessing for publication bias exclusively using these methods. However, these classical funnel plot methods have important limitations when used as the sole means of assessing publication bias: they essentially assume that the publication process favors large point estimates for small studies and does not affect the largest studies, and they can perform poorly when effects are heterogeneous. In light of these limitations, we recommend that meta-analyses routinely apply other publication bias methods in addition to or instead of classical funnel plot methods. To this end, we describe how to use and interpret selection models. These methods make the often more realistic assumption that publication bias favors "statistically significant" results, and the methods also directly accommodate effect heterogeneity. Selection models have been established for decades in the statistics literature and are supported by user-friendly software, yet remain rarely reported in many disciplines. We use a previously published meta-analysis to demonstrate that selection models can yield insights that extend beyond those provided by funnel plot methods, suggesting the importance of establishing more comprehensive reporting practices for publication bias assessment.

Spatially resolved ultrasound diagnostics of Li-ion battery electrodes.

The importance of reliable battery diagnostic systems has grown substantially in recent years as a result of the use of high power Li-ion battery packs in an increasingly diverse range of applications. Here, spatially resolved ultrasound acoustic measurements are used to analyse the condition of Li-ion electrodes. Ultrasonic measurements are performed on a commercial mobile phone battery over the full operating voltage window with the lithiation and delithiation of electrodes observed at 36 locations on the surface of the cell. X-ray computed tomography was performed on the cell to ascertain the internal architecture and features that enabled the architecture of the battery to be correlated with the acoustic signature. Analyses of the acoustic signals obtained suggest that the anode and cathode layers can be identified by examining the change in attenuation associated with the charging process. It is also seen that expansions of the electrode layers are inhibited by the presence of the anode current collecting tab in the battery which leads to spatial inhomogeneities in the expansion of the electrode layer examined within the cell.

Inactivation of non-proteolytic Clostridium botulinum type E in low-acid foods and phosphate buffer by heat and pressure.

The effect of high pressure thermal (HPT) treatments on the inactivation of spores of non-proteolytic type E Clostridium botulinum TMW 2.990 was investigated at high pressures (300 to 600 MPa) and elevated temperatures (80 to 100 °C) in four low-acid foods (steamed sole, green peas with ham, vegetable soup, braised veal) and imidazole phosphate buffer (IPB). In addition, corresponding conventional thermal treatments at ambient pressure were performed to expose possible synergisms of pressure and temperature on spore inactivation. In general, spore count reduction was more efficient by combining pressure and temperatures < 100 °C and the overall process duration could be shortened due to accelerated heating rates (adiabatic effect). Processing at 90 °C and 600 MPa resulted in inactivation below the detection limit after 5 min in all foods except steamed sole. Traditional thermal processing of spores at 90 °C for 10 min, on the other hand, did not result in an estimated 6-log reduction. Additional HPT treatments in steamed sole and IPB did not reveal pronounced food matrix dependent protective effects. Here, varying pressure levels did not appear to be the driving force for spore count reduction in steamed sole at any temperature. By applying a Weibull distribution on destruction kinetics of isobaric/isothermal holding times, 6D-values were calculated. Compression and decompression phase (1 s pressure holding time) had a considerable impact on spore count reduction (max. -2.9 log units) in both, foods and buffer. Hence, compression and decompression phases should directly be included into the total lethal effect of HPT treatments to avoid prolonged holding times and overprocessing.

Non-linear pressure/temperature-dependence of high pressure thermal inactivation of proteolytic Clostridium botulinum type B in foods.

The effect of high pressure thermal (HPT) processing on the inactivation of spores of proteolytic type B Clostridium botulinum TMW 2.357 in four differently composed low-acid foods (green peas with ham, steamed sole, vegetable soup, braised veal) was studied in an industrially feasible pressure range and temperatures between 100 and 120°C. Inactivation curves exhibited rapid inactivation during compression and decompression followed by strong tailing effects. The highest inactivation (approx. 6-log cycle reduction) was obtained in braised veal at 600 MPa and 110°C after 300 s pressure-holding time. In general, inactivation curves exhibited similar negative exponential shapes, but maximum achievable inactivation levels were lower in foods with higher fat contents. At high treatment temperatures, spore inactivation was more effective at lower pressure levels (300 vs. 600 MPa), which indicates a non-linear pressure/temperature-dependence of the HPT spore inactivation efficiency. A comparison of spore inactivation levels achievable using HPT treatments versus a conventional heat sterilization treatment (121.1°C, 3 min) illustrates the potential of combining high pressures and temperatures to replace conventional retorting with the possibility to reduce the process temperature or shorten the processing time. Finally, experiments using varying spore inoculation levels suggested the presence of a resistant fraction comprising approximately 0.01% of a spore population as reason for the pronounced tailing effects in survivor curves. The loss of the high resistance properties upon cultivation indicates that those differences develop during sporulation and are not linked to permanent modifications at the genetic level.

Highly reactive, liquid diacrylamides via synergistic combination of spatially arranged curing moieties.

Six polymerizable N,N'-diacylamides containing spatially arranged N-acryl, N-allyl and/or N-alkyl groups were prepared via two-step syntheses and characterized by 1H/13C NMR-spectra, refractive index (RI) and viscosity measurements. Photo DSC measurements on activated samples provided reactivity parameters ∆Hp, Rp,max and tmax, while FTIR spectra before and after curing elucidated the underlying polymerization mechanism. Mechanical testing of the obtained polymers exhibited gradual differences in network densities, depending on the intramolecular arrangement and number of functional groups. Overall, a general building principle for highly reactive, liquid diacrylamides via synergistic combination of optimally arranged functional groups could be identified. The highest possible level of intramolecular synergism was found for low viscous N,N'-diacryloyl-N,N'-diallyl-1,4-but-2-enediamine.

Development of Novel Photoinitiators as Substitutes of Camphorquinone for the LED Induced Polymerization of Methacrylates: A Bis-Silyl Ketone.

A new photoinitiator based on a bis-silylketone (BSK) structure is proposed as a novel compound leading to highly efficient initiating silyl radicals for the polymerization of methacrylates (e.g., a bisphenol A-glycidyl methacrylate/triethyleneglycol dimethacrylate blend (70%/30% w/w)) upon exposure to a blue light emitting diode and a green laser diode. The polymerization profiles are recorded by real time Fourier transform IR (FTIR) spectroscopy. Absorption, fluorescence, electron spin resonance (ESR), and steady state experiments are used to investigate the involved chemical mechanisms. Molecular orbital calculations are also carried out. Remarkably, BSK efficiently works in the presence of an iodonium salt. The overall mechanism for the initiation step is clarified. This novel class of silyl radical generating photoinitiators is really promising for the photopolymerization of methacrylates, e.g., in dental materials.

A novel photoinitiating system producing germyl radicals for the polymerization of representative methacrylate resins: Camphorquinone/R3GeH/iodonium salt.

OBJECTIVES: The aim of our study is to find an amine free photoinitiating system (PIS) for the polymerization of representative dental methacrylate resins. A photoinitiating system (PIS) based on camphorquinone (CQ)/triphenylgermanium hydride/diphenyl iodonium hexafluorophosphate is proposed and compared to the conventional CQ/amine couple. The polymerization monitoring of thin (∼20µm) and thick (1.4mm) samples of a bisphenol A-glycidyl methacrylate (Bis-GMA)/triethyleneglycol dimethacrylate (TEGDMA) blend (70%/30% w/w) and of a urethane dimethacrylate (UDMA) upon exposure to a commercial blue LED centered at 477nm under air or in laminate is described. Finally, the impact of the photoinitiating system composition on the final polymer color is evaluated in detail. METHODS: FTIR and DSC experiments are used to record the photopolymerization profiles. ESR spectrometry and steady state photolysis are used to detect the produced radicals. Color measurements are carried out to determine the key parameters in the bleaching of the different dental formulations. RESULTS: The efficiency of the newly proposed PISs for the photopolymerization of BisGMA/TEGDMA and UDMA for thin (20µm) or for thick (1.4mm) samples upon exposure to a dental blue LED under air is excellent. It is noticeably higher than that of the CQ/amine reference couple. Excellent bleaching properties are also observed under irradiation in presence of the new PISs. A good correlation is found between the sample bleaching and the amount of Ph3GeH in the formulation. The excited state processes could be established. The overall chemical mechanisms for the initiation step were also clarified.

Tooth sensitivity during and after vital tooth bleaching: A systematic review on an unsolved problem.

OBJECTIVE: To review the current literature, and to evaluate the occurrence, severity, and duration of tooth sensitivity during and after vital tooth bleaching as well as to identify possible sources and risk factors of bleaching sensitivity (BS). The inclusive analysis should allow the clinician to get an overview about today's evidence based results concerning BS. SEARCH STRATEGY: The search included Cochrane Central Register of Controlled Trials, Ebsco, Embase, PubMed, and Scopus from February 1991 to February 2015. Studies published in English and German were considered. SELECTION CRITERIA: Randomized controlled trials including placebo or control groups, with statistical analysis of BS interventions, and with a study sample size of at least 30 participants at baseline were selected. DATA COLLECTION AND ANALYSIS: Screening of titles and abstracts, data extraction, and quality assessment of full texts were undertaken. RESULTS: A total of 136 articles were identified, with 18 papers meeting the inclusion criteria and presenting data that could be used in the analysis. Included trials provided some details on occurrence, severity, or duration of BS, but papers did not focus solely on BS. The majority of the studies were judged to be at a high risk of bias according to their study design. Investigation methods and outcomes concerning severity of BS and duration varied significantly. Evidence-based explanations for BS could not be found. CONCLUSION: BS still remains an unsolved phenomenon that needs further follow-up with high-quality studies following the well-accepted CONSORT guidelines.