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Concept: Noun class


The objective of this study was to determine whether kinematic data collected by the Microsoft Kinect 2 (MK2) could be used to quantify postural stability in healthy subjects. Twelve subjects were recruited for the project, and were instructed to perform a sequence of simple postural stability tasks. The movement sequence was performed as subjects were seated on top of a force platform, and the MK2 was positioned in front of them. This sequence of tasks was performed by each subject under three different postural conditions: “both feet on the ground” (1), “One foot off the ground” (2), and “both feet off the ground” (3). We compared force platform and MK2 data to quantify the degree to which the MK2 was returning reliable data across subjects. We then applied a novel machine-learning paradigm to the MK2 data in order to determine the extent to which data from the MK2 could be used to reliably classify different postural conditions. Our initial comparison of force plate and MK2 data showed a strong agreement between the two devices, with strong Pearson correlations between the trunk centroids “Spine_Mid” (0.85 ± 0.06), “Neck” (0.86 ± 0.07) and “Head” (0.87 ± 0.07), and the center of pressure centroid inferred by the force platform. Mean accuracy for the machine learning classifier from MK2 was 97.0%, with a specific classification accuracy breakdown of 90.9%, 100%, and 100% for conditions 1 through 3, respectively. Mean accuracy for the machine learning classifier derived from the force platform data was lower at 84.4%. We conclude that data from the MK2 has sufficient information content to allow us to classify sequences of tasks being performed under different levels of postural stability. Future studies will focus on validating this protocol on large populations of individuals with actual balance impairments in order to create a toolkit that is clinically validated and available to the medical community.

Concepts: Validation, Artificial intelligence, Biomechanics, Pearson product-moment correlation coefficient, Measuring instrument, Noun class, Force platform, Center of mass


While there is substantial evidence that adults who violate gender stereotypes often face backlash (i.e. social and economic penalties), less is known about the nature of gender stereotypes for young children, and the penalties that children may face for violating them. We conducted three experiments, with over 2000 adults from the US, to better understand the content and consequences of adults' gender stereotypes for young children. In Experiment 1, we tested which characteristics adults (N = 635) believed to be descriptive (i.e. typical), prescriptive (i.e. required), and proscriptive (i.e. forbidden) for preschool-aged boys and girls. Using the characteristics that were rated in Experiment 1, we then constructed vignettes that were either ‘masculine’ or ‘feminine’, and manipulated whether the vignettes were said to describe a boy or a girl. Experiment 2 (N = 697) revealed that adults rated stereotype-violating children as less likeable than their stereotype-conforming peers, and that this difference was more robust for boys than girls. Experiment 3 (N = 731) was a direct replication of Experiment 2, and revealed converging evidence of backlash against stereotype-violating children. In sum, our results suggest that even young children encounter backlash from adults for stereotype violations, and that these effects may be strongest for boys.

Concepts: Female, Gender, Childhood, Girl, Boy, Noun class, Grammatical gender, Norwegian language


Few studies have examined therapist effects and therapeutic alliance (TA) in treatments for chronic fatigue syndrome (CFS). Therapist effects are the differences in outcomes achieved by different therapists. TA is the quality of the bond and level of agreement regarding the goals and tasks of therapy. Prior research suffers the methodological problem that the allocation of therapist was not randomized, meaning therapist effects may be confounded with selection effects. We used data from a randomized controlled treatment trial of 296 people with CFS. The trial compared pragmatic rehabilitation (PR), a nurse led, home based self-help treatment, a counselling-based treatment called supportive listening (SL), with general practitioner treatment as usual. Therapist allocation was randomized. Primary outcome measures, fatigue and physical functioning were assessed blind to treatment allocation. TA was measured in the PR and SL arms. Regression models allowing for interactions were used to examine relationships between (i) therapist and therapeutic alliance, and (ii) therapist and average treatment effect (the difference in mean outcomes between different treatment conditions). We found no therapist effects. We found no relationship between TA and the average treatment effect of a therapist. One therapist formed stronger alliances when delivering PR compared to when delivering SL (effect size 0.76, SE 0.33, 95% CI 0.11 to 1.41). In these therapies for CFS, TA does not influence symptomatic outcome. The lack of significant therapist effects on outcome may result from the trial’s rigorous quality control, or random therapist allocation, eliminating selection effects. Further research is needed.

Concepts: Medicine, Therapy, Psychotherapy, Chronic fatigue syndrome, Noun class


Although sexist attitudes are generally thought to undermine support for employment equity (EE) policies supporting women, we argue that the effects of benevolent sexism are more complex. Across 4 studies, we extend the ambivalent sexism literature by examining both the positive and the negative effects benevolent sexism has for the support of gender-based EE policies. On the positive side, we show that individuals who endorse benevolent sexist attitudes on trait measures of sexism (Study 1) and individuals primed with benevolent sexist attitudes (Study 2) are more likely to support an EE policy, and that this effect is mediated by feelings of compassion. On the negative side, we find that this support extends only to EE policies that promote the hiring of women in feminine, and not in masculine, positions (Study 3 and 4). Thus, while benevolent sexism may appear to promote gender equality, it subtly undermines it by contributing to occupational gender segregation and leading to inaction in promoting women in positions in which they are underrepresented (i.e., masculine positions). (PsycINFO Database Record

Concepts: Gender, Discrimination, Noun class, Sexism, Femininity, Feminism, Gender-specific job title, Sex segregation


Most of the tools and diagnosis models of Masticatory Efficiency (ME) are not well documented or severely limited to simple image processing approaches. This study presents a novel expert system for ME assessment based on automatic recognition of mixture patterns of masticated two-coloured chewing gums using a combination of computational intelligence and image processing techniques. The hypotheses tested were that the proposed system could accurately relate specimens to the number of chewing cycles, and that it could identify differences between the mixture patterns of edentulous individuals prior and after complete denture treatment. This study enrolled 80 fully-dentate adults (41 females and 39 males, 25 ± 5 years of age) as the reference population; and 40 edentulous adults (21 females and 19 males, 72 ± 8.9 years of age) for the testing group. The system was calibrated using the features extracted from 400 samples covering 0, 10, 15, and 20 chewing cycles. The calibrated system was used to automatically analyse and classify a set of 160 specimens retrieved from individuals in the testing group in two appointments. The ME was then computed as the predicted number of chewing strokes that a healthy reference individual would need to achieve a similar degree of mixture measured against the real number of cycles applied to the specimen. The trained classifier obtained a Mathews Correlation Coefficient score of 0.97. ME measurements showed almost perfect agreement considering pre- and post-treatment appointments separately (κ ≥ 0.95). Wilcoxon signed-rank test showed that a complete denture treatment for edentulous patients elicited a statistically significant increase in the ME measurements (Z = -2.31, p < 0.01). We conclude that the proposed expert system proved able and reliable to accurately identify patterns in mixture and provided useful ME measurements.

Concepts: Sample, Mathematics, Measurement, Metrology, Artificial intelligence, Test method, Image processing, Noun class


Visual pursuit is a key marker of residual consciousness in patients with disorders of consciousness (DOC). Currently, its assessment relies on subjective clinical decisions. In this study, we explore the variability of such clinical assessments, and present an easy-to-use device composed of cameras and video processing algorithms that could help the clinician to improve the detection of visual pursuit in a clinical context. Visual pursuit was assessed by an experienced research neuropsychologist on 31 patients with DOC and on 23 healthy subjects, while the device was used to simultaneously record videos of both one eye and the mirror. These videos were then scored by three researchers: the experienced research neuropsychologist who did the clinical assessment, another experienced research neuropsychologist, and a neurologist. For each video, a consensus was decided between the three persons, and used as the gold standard of the presence or absence of visual pursuit. Almost 10% of the patients were misclassified at the bedside according to their consensus. An automatic classifier analyzed eye and mirror trajectories, and was able to identify patients and healthy subjects with visual pursuit, in total agreement with the consensus on video. In conclusion, our device can be used easily in patients with DOC while respecting the current guidelines of visual pursuit assessment. Our results suggest that our material and our classification method can identify patients with visual pursuit, as well as the three researchers based on video recordings can.

Concepts: Evaluation, Research, Assessment, Artificial intelligence, Clinical psychology, Objective pronoun, Noun class, Exploratory research


We examined sources of morphological variability in second language (L2) learners of Spanish whose native language (L1) is English, with a focus on L1-L2 similarity, morphological markedness, and knowledge type (receptive vs. expressive). Experiment 1 uses event-related potentials to examine noun-adjective number (present in L1) and gender agreement (absent in L1) in online sentence comprehension (receptive knowledge). For each feature, markedness was manipulated, such that half of the critical noun-adjective combinations were feminine (marked) and the other half were masculine; half were used in the plural (marked) and the other half were used in the singular. With this setup, we examined learners' potential overreliance on unmarked forms or “defaults” (singular/masculine). Experiment 2 examines similar dependencies in spoken sentence production (expressive knowledge). Learners (n = 22) performed better with number than gender overall, but their brain responses to both features were qualitatively native-like (i.e., P600), even though gender was probed with nouns that do not provide strong distributional cues to gender. In addition, variability with gender agreement was better accounted for by lexical (as opposed to syntactic) aspects. Learners showed no advantage for comprehension over production, and no systematic evidence of reliance on morphological defaults, although their online processing was sensitive to markedness in a native-like manner. Overall, these results suggest that there is facilitation for L2 properties that exist in the L1 and that markedness impacts L2 processing, but in a native-like manner. These results also speak against proposals arguing that adult L2ers have deficits at the level of the morphology or the syntax. (PsycINFO Database Record

Concepts: Linguistics, English language, Noun class, Inflection, Morphology, Grammatical number, Grammatical conjugation, Grammatical gender


This study evaluated a gender-specific, school-based program to promote positive body image and address risk factors for body dissatisfaction. In total, 652 children aged 8-10 years participated (335 intervention, 317 wait-list control). Children participated in four 60min sessions and a recap session at three months post-intervention. The broad content areas were body image, peer relationships, media awareness, healthy diet, and exercise. The activities and examples for each session were gender specific. The recap session was an overview of the four sessions. Assessment measures were completed at pre-intervention, post-intervention, and after the recap. Boys and girls in the intervention demonstrated higher muscle esteem and vegetable intake at post-intervention, compared to children in the control condition. Boys and girls demonstrated higher body esteem, muscle esteem and fruit and vegetable intake at the recap. Boys in the intervention demonstrated less investment in masculine gender norms at post-intervention and at recap.

Concepts: Nutrition, Gender, Man, Noun class, Norwegian language, Gender-specific job title, Gender-specific pronoun


Children acquiring languages with noun classes (grammatical gender) have ample statistical information available that characterizes the distribution of nouns into these classes, but their use of this information to classify novel nouns differs from the predictions made by an optimal Bayesian classifier. We use rational analysis to investigate the hypothesis that children are classifying nouns optimally with respect to a distribution that does not match the surface distribution of statistical features in their input. We propose three ways in which children’s apparent statistical insensitivity might arise, and find that all three provide ways to account for the difference between children’s behavior and the optimal classifier. A fourth model combines two of these proposals and finds that children’s insensitivity is best modeled as a bias to ignore certain features during classification, rather than an inability to encode those features during learning. These results provide insight into children’s developing knowledge of noun classes and highlight the complex ways in which statistical information from the input interacts with children’s learning processes.

Concepts: Scientific method, Latin, Noun class, Grammatical number, Grammatical gender


Objective: To investigate stigmatizing attitudes towards cancer patients in the general population and to examine their association with socio-structural characteristics and perceived causes of disease. Methods: We recruited a representative sample from the German general population (n=2420; mean age: 52 years; 54% women). Stigmatizing attitudes were assessed with a 9-item scale. Predictors of stigmatizing attitudes were identified using a regression analysis. Results: Agreement with stigmatization items ranged from 3.6% (item: work together with a cancer patient) to 18.9% (item: use the same dishes as a cancer patient). Perceived causes of disease with a high levels of personal responsibility showed only weak correlations with stigmatizing attitudes (all r<0.31) and were partially statistical significant (e. g. food intake) or not significant (e. g. alcohol). The strongest predictors of stigmatizing attitudes were lack of cancer-related experiences (Beta=-0,26), age <60 years (Beta=0,1) and the assumption that one cannot protect oneself from cancer (Beta=0,11) (all p<0.001). Further predictors were male gender and living in rural area (p<0.01). Conclusion: The results demonstrate a need for further research and the development of valid methodological instruments to assess stigmatization towards cancer patients.

Concepts: Sample, Regression analysis, Oncology, Statistics, Population, Gender, Rural area, Noun class