The Outcomes of Physical Punishment are Typical of All Corrective Actions: A Response to Heilmann et al's (2021) Narrative Review

The reputation of psychological science depends on the adequacy of the science underlying its policy recommendations. This commentary raises concerns about the science used by Heilman et al. (2021) in their recent narrative (not meta-analytic) review that encourages spanking bans worldwide. By reviewing controlled longitudinal studies, Heilmann et al. provided stronger causal evidence than the two meta-analyses of unadjusted correlations most frequently cited to support spanking bans. However, the two previously published meta-analyses of controlled longitudinal studies of spanking do not support spanking bans, due to the trivial size of the average adverse-looking effect of customary spanking in those studies. Moreover, several lines of evidence indicate that this trivial average effect is likely due to inadequate statistical controls rather than an actual adverse causal effect of typical spanking. We need stronger causal evidence for policy recommendations for both the welfare of children and the reputation of psychological science.

Participant Characteristics Predicting Communication Outcomes in AAC Implementation for Individuals with ASD and IDD: A Systematic Review and Meta-analysis

This meta-analysis examined social communication outcomes in augmentative and alternative communication (AAC) interventions, or those that involved aided (e.g., speech generating devices, picture point systems) or unaided AAC (e.g., gestures, manual sign language) as a component of intervention, and the extent to which communication outcomes were predicted by participant characteristics. Variables of interest included chronological age, communication mode used prior to intervention, number of words produced and imitation skills of participants prior to intervention. Investigators identified 117 primary studies that implemented AAC interventions with school-aged individuals (up to 22 years) with autism spectrum disorder and/or intellectual disability associated with complex communication needs and assessed social-communication outcomes. All included studies involved single-case experimental designs and met basic study design quality standards. We synthesized findings across studies using two complementary effect size indices, Tau(AB) and the log response ratio, and multi-level meta-analysis with robust variance estimation. With Tau(AB), the overall average effect across 338 participants was 0.72, 95% CI [0.67, 0.76], with a high degree of heterogeneity across studies. With the log response ratio, the overall average effect corresponded to a 538% increase from baseline levels of responding, 95% CI [388%, 733%], with a high degree of heterogeneity across studies and contrasts. Moderator analyses detected few differences in effectiveness when comparing across diagnoses, ages, the number and type of communication modes the participants used prior to intervention, the number of words used by the participants prior to intervention, and imitation use prior to intervention.

Integrating informative hypotheses into the EffectLiteR framework

Using the EffectLiteR framework, researchers can test classical null hypotheses about effects of interest via Wald and F-tests, while taking into account the stochastic nature of group sizes. This paper aims at extending EffectLiteR to test informative hypotheses, assuming for example that the average effect of a new treatment is greater than the average effect of an old treatment, which in turn is greater than zero. We present a simulated data example to show two methodological novelties. First, we illustrate how to use the Fbar- and generalized linear Wald test to assess informative hypotheses. While the classical test did not reach significance, the informative test correctly rejected the null hypothesis, indicating the need to take into account the order of the treatment groups. Second, we demonstrate how to account for stochastic group sizes in informative hypotheses using the generalized non-linear Wald statistic. The paper concludes with a short data example.

Do Women Respond Less to Performance Pay? Building Evidence from Multiple Experiments

Existing empirical work raises the hypothesis that performance pay—whatever its output gains—may widen the gender earnings gap because women may respond less to incentives. We evaluate this possibility by aggregating evidence from existing experiments on performance incentives with male and female subjects. Using a Bayesian hierarchical model, we estimate both the average effect and heterogeneity across studies. We find that the gender response difference is close to zero and heterogeneity across studies is small, while performance pay increases output by 0.36 standard deviations on average. The data thus support agency theory for men and women alike. (JEL C11, C90, J16, J31, J33)

Changes over time in inflammatory and structural lesions at the sacroiliac joint in children with spondyloarthritis exposed and unexposed to tumor necrosis factor inhibitor

Background The objective of this work was to describe magnetic resonance imaging (MRI) changes over time in inflammatory and structural lesions at the sacroiliac joint (SIJ) in children with spondyloarthritis (SpA) exposed and unexposed to tumor necrosis factor inhibitor (TNFi). Methods This was a retrospective, multicenter study of SpA patients with suspected or confirmed sacroiliitis who underwent at ≥2 pelvic MRI scans. Images were reviewed independently by 3 radiologists and scored for inflammatory and structural changes using the Spondyloarthritis Research Consortium of Canada (SPARCC) SIJ inflammation score (SIS) and structural score (SSS). Longitudinal, quantitative changes in patient MRI scans were measured using descriptive statistics and stratified by TNFi exposure. We used an average treatment effects (ATE) regression model to explore the average effect of TNFi exposure over time on inflammatory and structural lesions, adjusting for baseline lesion scores. Results Forty-six subjects were evaluated using the SIS (n = 45) and SSS (n = 18). Median age at baseline imaging was 13.6 years, 63% were male and 71% were white. Twenty-three subjects (50%) were TNFi exposed between MRI studies. The median change in SIS in TNFi exposed and unexposed subjects with a baseline SIS ≥0 was − 20.7 and − 14.3, respectively (p = 0.09). Eleven (85%) TNFi exposed and 8 (89%) unexposed subjects with a baseline SIS ≥0 met the SIS minimal clinically important difference (MCID; ≥2.5). Using the ATE model adjusted for baseline SIS, the average effect of TNFi on SIS in patients with a baseline SIS ≥2 was − 14.5 (p < 0.01). Unadjusted erosion change score was significantly worse in TNFi unexposed versus exposed subjects (p = 0.03) but in the ATE model the effect of TNFi was not significant. Conclusion This study quantitatively describes how lesions in the SIJs on MRI change over time in patients exposed to TNFi versus unexposed. Follow-up imaging in TNFi exposed patients showed greater improvement than the unexposed group by most metrics, some of which reached statistical significance. Surprisingly, a majority of TNFi unexposed children with a baseline SIS≥2 met the SIS MCID. Additional studies assessing the short and long-term effects of TNFi on inflammatory and structural changes in juvenile SpA are needed.

No Strong Evidence of Stereotype Threat in Females: A Reassessment of the Meta-Analysis

Recently, Picho-Kiroga (2021) published a meta-analysis on the effect of stereotype threat on females. Their conclusion was that the average effect size for stereotype threat studies was d = .28, but that effects are overstated because the majority of studies on stereotype threat in females include methodological characteristics that inflate the apparent effect size. In this response, I show that Picho-Kiroga et al. (2021) committed fundamental errors in their meta-analysis that undermine confidence in the article and warrant major corrections. But even if the data were not flawed, the conclusion that Picho-Kiroga et al. (2021) should have reached is that their results are most consistent with a population effect size of zero. There is no compelling evidence that stereotype threat is a real phenomenon in females.

Using Mobile Device Data to Understand the Effect of Stay-at-Home Orders on Residents’ Mobility

Problem definition: This study addresses three important questions concerning the effectiveness of stay-at-home orders and sociodemographic disparities. (1) What is the average effect of the orders on the percentage of residents staying at home? (2) Is the effect heterogeneous across counties with different percentages of vulnerable populations (defined as those without health insurance or who did not attend high school)? (3) If so, why are the orders less effective for some counties than for others? Academic/practical relevance: To combat the spread of coronavirus disease 2019 (COVID-19), a number of states in the United States implemented stay-at-home orders that prevent residents from leaving their homes except for essential trips. These orders have drawn heavy criticism from the public because whether they are necessary and effective in increasing the number of residents staying at home is unclear. Methodology: We estimate the average effect of the orders using a difference-in-differences model, where the control group is the counties that did not implement the orders and the treatment group is the counties that did implement the orders during our study period. We estimate the heterogeneous effects of the orders by interacting county features with treatment dummies in a triple-difference model. Results: Using a unique set of mobile device data that track residents’ mobility, we find that, although some residents already voluntarily stayed at home before the implementation of any order, the stay-at-home orders increased the number of residents staying at home by 2.832 percentage points (or 11.25%). We also find that these orders are less effective for counties with higher percentages of uninsured or less educated (i.e., did not attend high school) residents. To explore the mechanisms behind these results, we analyze the effect of the orders on the average number of work and nonwork trips per person. We find that the orders reduce the number of work trips by 0.053 (or 7.87%) and nonwork trips by 0.183 (or 6.50%). The percentage of uninsured or less educated residents in a county negatively correlates with the reduction in the number of work trips but does not correlate with the reduction in the number of nonwork trips. Managerial implications: Our results suggest that uninsured and less educated residents are less likely to follow the orders because their jobs prevent them from working from home. Policy makers must take into account the differences in residents’ socioeconomic status when developing new policies or allocating limited healthcare resources.

Embedding non-rigid solutes in an averaged environment: a case study on rhodopsins

Many simulation methods concerning solvated molecules are based on the assumption that the solvated species and the solvent can be characterized by some representative structure of the solute and some embedding potential corresponding to this structure. This assumption is re-examined and generalized for conformationally flexible solutes. In the proposed and investigated generalization, the solute is characterized by a set of representative structures and the corresponding embedding potentials. The representative structures are identified by means of subdividing the statistical ensemble, which in this work is generated by a constant-temperature molecular dynamics simulation. The embedding potential defined in Frozen-Density Embedding Theory is used to characterize the average effect of the solvent in each subensemble. The numerical examples concern vertical excitation energies of protonated retinal Schiff bases in protein environments. It is comprehensively shown that subensemble averaging leads to huge computational savings compared to explicit averaging of the excitation energies in the whole ensemble while introducing only minor errors.

META ANALISIS PENGARUH MODEL DISCOVERY LEARNING TERHADAP PENGUASAAN KONSEP DAN PENGETAHUAN PESERTA DIDIK FISIKA SMA

ABSTRAKTujuan penelitian ini adalah untuk mengetahui pengaruh Model discovery learning terhadap penguasaan konsep dan pengetahuan fisika SMA. Metode yang digunakan dalam penelitian ini adalah meta-analisis. Teknik analisis data dalam penelitian ini menggunakan perhitungan nilai effect size untuk setiap artikel. Berdasarkan meta analisis yang dilakukan, dapat dinyatakan bahwa hasil penelitian ini yaitu : 1) pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan fisika SMA ditinjau dari tahun terbit artikel memberikan efek yang Sangat Tinggi terdapat pada tahun 2017,2018, dan 2020 dengan masing-masing rata-rata effect size yaitu 1,6; 1,15; dan 1,62. 2) pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan fisika SMA ditinjau dari tingkatan kelas memberikan efek Sangat Tinggi terdapat pada kelas XI dengan rata-rata effect size 1,25. 3) pengaruh discovery learning terhadap penguasaan konsep fisika SMA memberikan efek Sangat Tinggi terdapat pada artikel keenam (J6) dengan nilai effect size 2,38. 4) pengaruh discovery learning terhadap pengetahuan fisika SMA memberikan efek Sangat Tinggi terdapat pada artikel kesepuluh (J10) dengan nilai effect size 3,95. Hal ini menunjukkan bahwa terdapat pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan fisika SMA. Kata kunci: Discovery Learning; Penguasaan Konsep; Pengetahuan. ABSTRACTThe purpose of this study was to determine the effect of the discovery learning model on mastery of high school physics concepts and knowledge. The method used in this research is meta-analysis. The data analysis technique in this study uses the calculation of the effect size value for each article. Based on the meta-analysis carried out, it can be stated that the results of this study are: 1) the effect of the discovery learning model on mastery of concepts and knowledge of high school physics in terms of the year the article was published gave a Very High effect in 2017,2018, and 2020 with each the average effect size is 1.6; 1.15; and 1.62. 2) the influence of the discovery learning model on the mastery of concepts and knowledge of high school physics in terms of grade level gives a very high effect in class XI with an average effect size of 1.25. 3) the effect of discovery learning on mastery of high school physics concepts gives a Very High effect found in the sixth article (J6) with an effect size value of 2.38. 4) the effect of discovery learning on high school physics knowledge gives a very high effect in the tenth article (J10) with an effect size value of 3.95. This shows that there is an influence of the discovery learning model on the mastery of high school physics concepts and knowledge. Keywords: Discovery Learning; Concept Mastery; Knowledge.