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Abstract This study presents a novel standardized rating instrument for observing and measuring effective classroom management (ECM) as part of the teaching and learning environments in primary school. The instrument comprises eight high-inferent items on organizational aspects (lack of disruptions/discipline problems, withitness, effective time use, clear rules, clear routines, appreciation) and instructional aspects (structuring, goal clarity). It was applied in second grade classrooms of German primary school teachers (n = 35) providing early reading and writing instruction. Pairs of trained raters (student teachers) observed one to three lessons in each classroom over 3–4 months, reaching acceptable interrater agreement. The instrument showed acceptable internal consistency. Factor analyses revealed structures with good to acceptable fit indices, with confirming the differentiation into organizational and instructional ECM aspects. Correlations between observed ECM and facets of teacher knowledge (that were directly assessed by using paper–pencil tests) provide divergent and convergent validity evidence: Whereas no significant correlations could be found between pedagogical content knowledge for early reading and writing instruction and ECM, findings show significant correlations between general pedagogical knowledge and the ECM. The added value of the study is therefore to provide a novel instrument that can be applied in future empirical research on primary school classroom management.

Background: Sexual minority individuals experience discrimination, leading to mental health disparities. Physical health disparities have not been examined to the same extent in systematic reviews so far. Objectives: To provide a systematic review and, where possible, meta-analyses on the prevalence of physical health conditions in sexual minority women (i.e. lesbian- and bisexual-identified women) compared to heterosexual-identified women. Design: The study design is a systematic review with meta-analyses. Data Sources and Methods: A systematic literature search in MEDLINE, EMBASE, CENTRAL, CINAHL, and Web of Science databases was conducted on epidemiologic studies on physical health conditions, classified in the Global Burden of Disease project, published between 2000 and 2021. Meta-analyses pooling odds ratios were calculated. Results: In total, 23,649 abstracts were screened and 44 studies were included in the systematic review. Meta-analyses were run for arthritis, asthma, back pain, cancer, chronic kidney diseases, diabetes, headache disorders, heart attacks, hepatitis, hypertension, and stroke. Most significant differences in prevalence by sexual identity were found for chronic respiratory conditions, especially asthma. Overall, sexual minority women were significantly 1.5–2 times more likely to have asthma than heterosexual women. Furthermore, evidence of higher prevalence in sexual minority compared to heterosexual women was found for back pain, headaches/migraines, hepatitis B/C, periodontitis, urinary tract infections, and acne. In contrast, bisexual women had lower cancer rates. Overall, sexual minority women had lower odds of heart attacks, diabetes, and hypertension than heterosexual women (in terms of diabetes and hypertension possibly due to non-consideration of pregnancy-related conditions). Conclusion: We found evidence for physical health disparities by sexual identity. Since some of these findings rely on few comparisons only, this review emphasizes the need for routinely including sexual identity assessment in health research and clinical practice. Providing a more detailed picture of the prevalence of physical health conditions in sexual minority women may ultimately contribute to reducing health disparities.

Additive and multiplicative regression models of habituation were compared regarding the fit to looking times from a habituation experiment with infants aged between 3 and 11 months. In contrast to earlier studies, the current study considered multiple probability distributions, namely Weibull, gamma, lognormal and normal distribution. In the habituation experiment the type of contrast between the habituation and the test trial was varied (luminance, color or orientation contrast), crossed with the number of habituation trials (1, 3, 5, or 7 habituation trials) and crossed with three age cohorts (4, 7, 10 months). The initial mean LT to dark stimuli (around 3.7 s) was considerably shorter than the mean LT to green and gray stimuli (around 5 s). Infants showed the strongest dishabituation to changes from dark to bright (luminance contrast) and weak-to-no dishabituation to a 90-degrees rotation of the gray stimuli (orientation contrast). The dishabituation was stronger after five and seven habituation trials, but the result was not statistically robust. The gamma distribution showed the best fit in terms of log-likelihood and mean absolute error and the best predictive performance. Furthermore, the gamma distribution showed small correlations between parameters relative to other models. The normal additive model showed an inferior fit and medium correlations between the parameters. In particular, the positive correlation between the initial looking time (LT) and the habituation rate was likely responsible for a different interpretation relative to the multiplicative models of the main effect of age on the habituation rate. Otherwise, the additive and multiplicative models provided similar statistical conclusions. The performance of the model versions without pooling and with partial pooling across participants (also called random-effects, multi-level or hierarchical models) were compared. The latter type of models showed worse data fit but more precise predictions and reduced correlations between the parameters. The performance of model variants with auto-regressive time structures were explored but showed considerably worse fit. The performance of quadratic models that allowed non-monotonic changes in LTs were investigated as well. However, when fitted with LT data, these models did not produce non-monotonic change in LTs. The study underscores the utility of partial-pooling models in terms of providing more accurate predictions. Further, it agrees with previous research in that a multiplicative LT model is preferable. Nevertheless, the current results suggest that the impact of the choice of an additive model on the statistical inference is less dramatic then previously assumed.

We investigated young infants’ object encoding and processing in response to isolated eye gaze cues on the neural and behavioral level. In two experiments, 4-month-old infants watched a pair of isolated eyes gazing towards or away from novel objects. Subsequently, the same objects were presented alone (i.e., without eyes). We measured event-related potentials (ERP) in response to object-directed and object-averted eye gaze as well as to the subsequently presented isolated objects. Using eye-tracking methods, we additionally measured infants’ looking behavior in reaction to the subsequently presented isolated objects. The ERP data revealed an enhanced slow wave positivity for object-directed eye gaze, indicating increased encoding of observed gaze cues. Regarding the objects, we found an enhanced Nc amplitude and increased looking times in response to previously uncued objects, indicating a novelty response on the neural and behavioral level. The results suggest that isolated eye gaze stimuli are sufficient to trigger object encoding and facilitate further object processing. Keywords: Infants, Eye tracking, Event-related potentials (ERP), Eye gaze, Isolated eyes

Goals and methodsA simulation study investigated how ceiling and floor effect (CFE) affect the performance of Welch's t-test, F-test, Mann-Whitney test, Kruskal-Wallis test, Scheirer-Ray-Hare-test, trimmed t-test, Bayesian t-test, and the "two one-sided tests" equivalence testing procedure. The effect of CFE on the estimate of group difference and on its confidence interval, and on Cohen's d and on its confidence interval was also evaluated. In addition, the parametric methods were applied to data transformed with log or logit function and the performance was evaluated. The notion of essential maximum from abstract measurement theory is used to formally define CFE and the principle of maximum entropy was used to derive probability distributions with essential maximum/minimum. These distributions allow the manipulation of the magnitude of CFE through a parameter. Beta, Gamma, Beta prime and Beta-binomial distributions were obtained in this way with the CFE parameter corresponding to the logarithm of the geometric mean. Wald distribution and ordered logistic regression were also included in the study due to their measure-theoretic connection to CFE, even though these models lack essential minimum/maximum. Performance in two-group, three-group and 2 × 2 factor design scenarios was investigated by fixing the group differences in terms of CFE parameter and by adjusting the base level of CFE.Results and conclusionsIn general, bias and uncertainty increased with CFE. Most problematic were occasional instances of biased inference which became more certain and more biased as the magnitude of CFE increased. The bias affected the estimate of group difference, the estimate of Cohen's d and the decisions of the equivalence testing methods. Statistical methods worked best with transformed data, albeit this depended on the match between the choice of transformation and the type of CFE. Log transform worked well with Gamma and Beta prime distribution while logit transform worked well with Beta distribution. Rank-based tests showed best performance with discrete data, but it was demonstrated that even there a model derived with measurement-theoretic principles may show superior performance. Trimmed t-test showed poor performance. In the factor design, CFE prevented the detection of main effects as well as the detection of interaction. Irrespective of CFE, F-test misidentified main effects and interactions on multiple occasions. Five different constellations of main effect and interactions were investigated for each probability distribution, and weaknesses of each statistical method were identified and reported. As part of the discussion, the use of generalized linear models based on abstract measurement theory is recommended to counter CFE. Furthermore, the necessity of measure validation/calibration studies to obtain the necessary knowledge of CFE to design and select an appropriate statistical tool, is stressed.

We explore the role of eye movements in a chase detection task. Unlike the previous studies, which focused on overall performance as indicated by response speed and chase detection accuracy, we decompose the search process into gaze events such as smooth eye movements and use a data-driven approach to separately describe these gaze events. We measured eye movements of four human subjects engaged in a chase detection task displayed on a computer screen. The subjects were asked to detect two chasing rings among twelve other randomly moving rings. Using principal component analysis and support vector machines, we looked at the template and classification images that describe various stages of the detection process. We showed that the subjects mostly search for pairs of rings that move one after another in the same direction with a distance of 3.5–3.8 degrees. To find such pairs, the subjects first looked for regions with a high ring density and then pursued the rings in this region. Most of these groups consisted of two rings. Three subjects preferred to pursue the pair as a single object, while the remaining subject pursued the group by alternating the gaze between the two individual rings. In the discussion, we argue that subjects do not compare the movement of the pursued pair to a singular preformed template that describes a chasing motion. Rather, subjects bring certain hypotheses about what motion may qualify as chase and then, through feedback, they learn to look for a motion pattern that maximizes their performance.

How infants acquire knowledge about animate beings and physical objects has been of interest to developmental psychologists for many years. In this article, we provide evidence suggesting that by 7 months, infants have formed a global animate-inanimate distinction that seems to be based on previously acquired knowledge. This knowledge may allow infants to analyze triadic social interactions involving another animate being and a physical object in more complex ways. Whereas 3- to 4-month-olds respond to object-directed social cues such as eye gaze or facial expressions more or less automatically, 9- to 12-month-olds seem to integrate social and object knowledge to allocate their attentional resources. Twelve-month-olds can even detect person-specific preferences for an entire category of objects. Based on this evidence, we conclude that infants' learning about social beings and physical objects is closely related, but changes substantially in preverbal children. [ABSTRACT FROM AUTHOR]