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Many Management (sub-)disciplines, from Organizational Behavior and Marketing to Accounting and Strategy, are interested in antecedents and consequences of individual attitudes and traits. A key aspect of personality profiles are explicit and implicit motives. Yet, Management scholars mainly focus on explicit motives, with limited attention to implicit motives. We argue that this state of affairs probably came into being because current Management researchers mainly rely on implicit motive measures that are either difficult to apply or to develop, hampering researchers from applying implicit motive measures. To overcome the downsides of available instruments, we develop a Brief Implicit Association Test (BIAT) as an efficient, reliable and valid measure of implicit motives, particularly the needs for achievement, affiliation and power. To explore our BIAT's predictive validity, we apply this measure to a specific research domain within Management: Entrepreneurship. We examine implicit motives' association with entrepreneurial self-efficacy, business founding, and financial profitability. Our results show that the introduction of implicit motives can unlock stranded discussions in this research domain. Overall, we argue that implicit motives can help to push the boundaries of the study of deep-level attributes in a wide range of organizational and managerial settings.

China’s basic education and higher education are currently facing policies aimed at reducing and increasing the academic burden, respectively. In this context, we first review and assess the methods of measuring students’ academic burden and then apply the implicit association test for the first time to the academic burden of Chinese students from primary school to university under a unified framework. The results demonstrates that students’ academic burden increases with the school stage, and thus university students face a greater burden than primary and high school students, and that learning attitude fully mediates the relationship between objective and subjective views of academic burden. These results suggest the three policy approaches of implementing a management system for classifying academic burden, considering how to improve students’ learning quality, and developing their mental health education, thus providing a reference and inspiration for research and practice in the field of academic burden.

Objectives: This study examined syntactic development of auditory comprehension of sentences in Japanese-speaking school-age children with and without hearing impairment. Methods: In total, 592 preschool and school-age children (421 normal-hearing and 171 hearing-impaired) were included in this cross-sectional observation study conducted using the Syntactic Processing Test for Aphasia for Japanese language users. Linear regression analysis was used to determine the estimated age at which each syntactic structure was acquired. Results: Acquisition of syntactic structures was observed in hearing-impaired and normal-hearing children. Basic word order sentences of agent-object-verb and the goal benefactive construction were acquired at preschool age (earlier group), whereas reverse word order sentences of object-agent-verb, source benefactive construction, passive voice, and relative clauses were acquired at school age (later group). The results showed that many hearing-impaired children may not acquire Japanese grammatical structures until the age of 12 years. Conclusions: Adequate screening for language development for school-age hearing-impaired children is required for an effective intervention.

Objective: To assess apathy in patients with Parkinson’s disease and its relation to disability, mood, personality, and cognition. Methods: Levels of apathy in 45 patients with Parkinson’s disease were compared with a group of 17 similarly disabled patients with osteoarthritis. Additional neuropsychiatric data were collected concerning levels of depression, anxiety, and hedonic tone. Personality was assessed with the tridimensional personality questionnaire. Cognitive testing included the mini-mental state examination, the Cambridge examination of cognition in the elderly, and specific tests of executive functioning. Results: Patients with Parkinson’s disease had significantly higher levels of apathy than equally disabled osteoarthritic patients. Furthermore, within the Parkinson sample, levels of apathy appear to be unrelated to disease progression. The patients with Parkinson’s disease with the highest levels of apathy where not more likely to be depressed or anxious than those with the lowest levels of apathy, though they did show reduced hedonic tone. No differences in personality traits were detected in comparisons between patients with Parkinson’s disease and osteoarthritis, or between patients in the Parkinson group with high or low levels of apathy. As a group, the patients with Parkinson’s disease tended not to differ significantly from the osteoarthritic group in terms of cognitive skills. However, within the Parkinson’s disease sample, the high apathy patients performed significantly below the level of the low apathy patients. This was particularly evident on tests of executive functioning. Conclusions: Apathy in Parkinson’s disease is more likely to be a direct consequence of disease related physiological changes than a psychological reaction or adaptation to disability. Apathy in Parkinson’s disease can be distinguished from other psychiatric symptoms and personality features that are associated with the disease, and it is closely associated with cognitive impairment. These findings point to a possible role of cognitive mechanisms in the expression of apathy.

Information about the affective meanings of words is used by researchers working on emotions and moods, word recognition and memory, and text-based sentiment analysis. Three components of emotions are traditionally distinguished: valence (the pleasantness of a stimulus), arousal (the intensity of emotion provoked by a stimulus), and dominance (the degree of control exerted by a stimulus). Thus far, nearly all research has been based on the ANEW norms collected by Bradley and Lang ( 1999 ) for 1,034 words. We extended that database to nearly 14,000 English lemmas, providing researchers with a much richer source of information, including gender, age, and educational differences in emotion norms. As an example of the new possibilities, we included stimuli from nearly all of the category norms (e.g., types of diseases, occupations, and taboo words) collected by Van Overschelde, Rawson, and Dunlosky (Journal of Memory and Language 50:289-335, 2004 ), making it possible to include affect in studies of semantic memory.

Functional coupling across distributed brain regions varies across task contexts, yet there are stable features. To better understand the range and central tendencies of network configurations, coupling patterns were explored using functional MRI (fMRI) across 14 distinct continuously performed task states ranging from passive fixation to increasingly demanding classification tasks. Mean global correlation profiles across the cortex ranged from 0.69 to 0.82 between task states. Network configurations from both passive fixation and classification tasks similarly predicted task coactivation patterns estimated from meta-analysis of the literature. Thus, even across markedly different task states, central tendencies dominate the coupling configurations. Beyond these shared components, distinct task states displayed significant differences in coupling patterns in response to their varied demands. One possibility is that anatomical connectivity provides constraints that act as attractors pulling network configurations towards a limited number of robust states. Reconfigurable coupling modes emerge as significant modifications to a core functional architecture.

Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests. Yet, their complexity makes it difficult to explain and predict their functioning. We examined a state-of-the-art language model (GPT-3) using lexical decision tasks widely used to study the structure of semantic memory in humans. The results of four analyses showed that GPT-3’s patterns of semantic activation are broadly similar to those observed in humans, showing significantly higher semantic activation in related (e.g., “lime–lemon”) word pairs than in other-related (e.g., “sour–lemon”) or unrelated (e.g., “tourist–lemon”) word pairs. However, there are also significant differences between GPT-3 and humans. GPT-3’s semantic activation is better predicted by similarity in words’ meaning (i.e., semantic similarity) rather than their co-occurrence in the language (i.e., associative similarity). This suggests that GPT-3’s semantic network is organized around word meaning rather than their co-occurrence in text.

Objectives: Japanese-speaking children in a standard sample were subjected to a test battery (ALADJIN: Assessment Package for Language Development in Japanese Hearing-Impaired Children) to evaluate the effect of language development on both interpersonal communication skills and academic achievement. Methods: A total of 414 preschool and school-age children without hearing impairment were included in this study. The following tests make up the ALADJIN: The Test of Question-Answer Interaction Development (TQAID), the Japanese Language by Criterion Referenced Test–II (CRT-II) for measuring academic achievement, the Picture Vocabulary Test–Revised (PVT-R), the Standardized Comprehension Test of Abstract Words (SCTAW), both parts of the Syntactic Processing Test for Aphasia (STA), and the Word Fluency Test (WFT). Means and standard deviations at each academic grade level were calculated, and a multiple regression analysis was performed. Results: A ceiling effect was observed for the TQAID and the STA in children in grade 3 of elementary school, and the scores for the PVT-R, SCTAW, and WFT increased incrementally according to grade level. Multiple regression analysis revealed that the PVT-R, WFT, and STA (production) have predictive power for the results of the TQAID (R = 0.59; R2 = 0.58; p < 0.0001), whereas the SCTAW and STA (comprehension) have predictive power for the results of the CRT-II. Conclusions: Both vocabulary and syntax are important in communication development among children. The results of our multiple regression analysis suggest that different language domains may play different roles in the development of interpersonal communication skills and in academic achievement. The development of interpersonal communication skills is largely based on productive vocabulary and syntax abilities, whereas academic achievement is largely based on comprehensive vocabulary and syntax abilities. Children who have difficulties in either area should be evaluated with detailed language assessment tools such as the ALADJIN in an effort to aid in the selection of appropriate intervention.

In this article, we describe the most extensive set of word associations collected to date. The database contains over 12,000 cue words for which more than 70,000 participants generated three responses in a multiple-response free association task. The goal of this study was (1) to create a semantic network that covers a large part of the human lexicon, (2) to investigate the implications of a multiple-response procedure by deriving a weighted directed network, and (3) to show how measures of centrality and relatedness derived from this network predict both lexical access in a lexical decision task and semantic relatedness in similarity judgment tasks. First, our results show that the multiple-response procedure results in a more heterogeneous set of responses, which lead to better predictions of lexical access and semantic relatedness than do single-response procedures. Second, the directed nature of the network leads to a decomposition of centrality that primarily depends on the number of incoming links or in-degree of each node, rather than its set size or number of outgoing links. Both studies indicate that adequate representation formats and sufficiently rich data derived from word associations represent a valuable type of information in both lexical and semantic processing.