Modeling the Influence of Language Input Statistics on Children's Speech Production

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child–caregiver interactions in English to test whether one proposed statistical learning mechanism—backward transitional probability—is able to predict children's speech productions with stable accuracy throughout the first few years of development. We predicted that the model less accurately reconstructs children's speech productions as they grow older because children gradually begin to generate speech using abstracted forms rather than specific “chunks” from their speech environment. To test this idea, we trained the model on both recently encountered and cumulative speech input from a longitudinal child language corpus. We then assessed whether the model could accurately reconstruct children's speech. Controlling for utterance length and the presence of duplicate chunks, we found no evidence that the CBL becomes less accurate in its ability to reconstruct children's speech with age.     

Semantic interference in the picture-word interference task: Is there a pre-lexical,conceptual contribution to the effect?

Psychonomic Bulletin & Review - Picture naming takes longer in the presence of a semantic-categorically related distractor word compared to an unrelated distractor word. This semantic...     

Possession and Applicability of Signature Character Strengths: What Is Essential for Well-Being,Work Engagement,and Burnout?

Signature character strengths can foster health-related outcomes in work and private life, thus being particularly important for endangered occupational groups like physicians. However, situational circumstances need to allow character strengths demonstration (applicability) first to enable their application. Therefore, this study addresses the role of (1) applicability of signature character strengths in work and private life beyond their possession and (2) relationships with well-being, work engagement, and burnout dimensions (emotional exhaustion, depersonalization, and reduced personal accomplishment). Hospital physicians (N = 274) completed an online survey examining their signature character strengths and applicability, well-being, work engagement, and burnout dimensions. The top-five individual signature character strengths were fairness, honesty, judgment, kindness, and love. Hierarchical multiple linear regressions revealed that the possession as well as the applicability of signature character strengths was important in work and private life, but to different degrees. Possessing fairness, honesty, or kindness indicated significant positive relations with subjective well-being, whereas judgment and kindness seemed to negatively interact with reduced personal accomplishment. Hospital physicians’ applicability of fairness, honesty, judgment, and love was particularly essential for their psychological well-being and work engagement, whereas the applicability of fairness (reduced personal accomplishment) and judgment (emotional exhaustion, depersonalization) at work interacted negatively with the respective outcomes. Therefore, creating awareness for individual signature character strengths as well as providing applicability in hospitals and private life could be a promising approach to improve physicians’ well-being and consequently patient care as well as the performance of the health-care system in general.

     

Psychometric Characteristics of the German Values in Action Inventory of Strengths 120-Item Short Form

The original Values in Action Inventory of Strengths (VIA-IS) is an international 240 item validated self-report questionnaire measuring character strengths. A validated and reliable English 120-item short form (VIA-120) is available. However, there is limited information about the psychometric properties of the German VIA-120. This article addresses this gap and reports the reliability, validity and comparability of the German VIA-120 with the German VIA-240 version. Two independent samples were recruited: a general population sample (N = 1073, Sample 1) and a sample consisting of medical students and physicians (N = 685, Sample 2). Internal consistency of the VIA-120-scales ranged from α = .58 (modesty) to α = .87 (spirituality) in Sample 1 and α = .63 (honesty) to α = .90 (spirituality) in Sample 2. Intercorrelations between the scales of the 120-item version and the original 240-Items version (Sample 1) ranged from r = .52 (hope) to r = .89 (prudence). Criterion validity with the Satisfaction with Life Scale (SWLS) and the Brief Inventory of Thriving (BIT) was demonstrated. The comparison of the factor structure between the original and the short form showed a good convergence (Tucker’s Phi .93–.99 Sample 1, .95–.98 Sample 2). Overall, the German VIA-120 was reliable, showed good convergence with the German VIA-240 and thus presents a similar level of validity for the assessment of character strengths. This study provides the first indication that the VIA 120 short form is comparable regarding the validity and reliability of the original VIA 240-item version indicating its potential to be used in large scale research studies.

     

Remembering changes: repetition effects in face recollection.

Two experiments examined effects of repetition and change on states of awareness in face recognition. Participants studied repeatedly presented photographs of faces, with the second presentation following either immediately after the first presentation (massed repetition) or following six intervening items (spaced repetition). To manipulate perceptual change, each repeated face was either identical or a mirror image of the first presentation. Subsequently, when recognising a face, participants indicated whether they consciously recollected its prior occurrence ("remembering") or recognised it on the basis of familiarity ("knowing"). Changes in appearance between repeated faces enhanced remember, but not know, responses, and these effects were accentuated for spaced, rather than massed, repetition. These findings suggest that distinctiveness of encoding supports the phenomenological experience of conscious remembering.     

On normal theory based inference for multilevel models with distributional violations

Data in social and behavioral sciences are often hierarchically organized though seldom normal, yet normal theory based inference procedures are routinely used for analyzing multilevel models. Based on this observation, simple adjustments to normal theory based results are proposed to minimize the consequences of violating normality assumptions. For characterizing the distribution of parameter estimates, sandwich-type covariance matrices are derived. Standard errors based on these covariance matrices remain consistent under distributional violations. Implications of various covariance estimators are also discussed. For evaluating the quality of a multilevel model, a rescaled statistic is given for both the hierarchical linear model and the hierarchical structural equation model. The rescaled statistic, improving the likelihood ratio statistic by estimating one extra parameter, approaches the same mean as its reference distribution. A simulation study with a 2-level factor model implies that the rescaled statistic is preferable.This research was supported by grants DA01070 and DA00017 from the National Institute on Drug Abuse and a University of North Texas faculty research grant. We would like to thank the Associate Editor and two reviewers for suggestions that helped to improve the paper.