Is lower intelligence in early life an overlooked risk factor for later physical and mental illness? Intelligence shapes decision-making, career paths, and other health-relevant factors. However, our understanding of its association with health remains limited because there is no quantitative synthesis of the literature. Here, we conducted a comprehensive systematic review and meta-analysis of associations between intelligence test scores and mental and physical health. We included studies reporting standardized intelligence test scores obtained in childhood, adolescence, or early adulthood (<21 years of age) and their association with later-life health outcomes. We excluded studies limited to clinical populations without healthy controls. Our three-level multiverse analyses of 49 studies (N > 2,900,000) showed a 15-point IQ disadvantage in early life was associated with a 22 percent higher risk of later mental and physical illness (logHR = 0.20, 95% CI [0.13, 0.26]). Lower IQ predicted disease risk across various conditions, including schizophrenia, depression, dementia, and diabetes. Notably, the association between IQ and future health diminished with improved healthcare quality and when education was statistically held constant. Nevertheless, a meaningful effect of intelligence remained after adjusting for these variables. Multiple methods for detecting dissemination bias indicated that risk of bias was low. While our summary effect estimates are precise, all included data were collected in highly developed nations. Further, samples were predominantly male, potentially limiting generalizability. We show that lower IQ scores in early life are linked to a higher risk of later physical and mental illness. Improving education and healthcare quality appears as potential measures to address the issue. This research received no specific funding.

The integration of artificial intelligence (AI) into chest radiography (CXR) has greatly impacted both human and veterinary medicine, enhancing diagnostic speed, accuracy, and efficiency. In human medicine, AI has been extensively studied, improving the identification of thoracic abnormalities, diagnostic precision in emergencies, and the classification of complex conditions such as tuberculosis, pneumonia, and COVID-19. Deep learning-based models assist radiologists by detecting patterns, generating probability maps, and predicting outcomes like heart failure. However, AI is still supplementary to clinical expertise due to challenges such as data limitations, algorithmic biases, and the need for extensive validation. Ethical concerns and regulatory constraints also hinder full implementation. In veterinary medicine, AI is still in its early stages and is rarely used; however, it has the potential to become a valuable tool for supporting radiologists in the future. However, challenges include smaller datasets, breed variability, and limited research. Addressing these through focused research on species with less phenotypic variability (like cats) and cross-sector collaborations could advance AI in veterinary medicine. Both fields demonstrate AI's potential to enhance diagnostics but emphasize the ongoing need for human expertise in clinical decision making. Differences in anatomy structure between the two fields must be considered for effective AI adaptation.

Early life is a critical period for neurodevelopment, where factors such as maternal nutrition and breastfeeding duration significantly impact the growth of head circumference and cognitive development in children. Our study aimed to explore the associations between maternal dietary patterns during pregnancy, duration of breastfeeding, and their impacts on child head circumference and cognitive outcomes.

Our study utilised data from the Copenhagen Prospective Studies on Asthma in Childhood 2010 cohort, which enrolled 700 mother-child pairs between 2008 and 2010 with 86% clinical follow-up at age 10. Pregnancy dietary patterns, described as 'Varied' and 'Western,' were derived from food frequency questionnaires and used to model quantitative metabolite scores via sparse partial least squares modelling of blood metabolome data. Cognitive development was assessed using the Bayley Scales of Infant Development at 2.5 years and the Wechsler Intelligence Scale for Children at age 10. Head circumference was measured from 20 weeks gestation to 10 years, and calibrated using related anthropometric measures. Growth trajectories were evaluated using linear mixed models and latent class trajectory models. Parental and child genetic influences for cognition and head circumference were controlled by including polygenic risk scores derived from genomic data. We found that a Western dietary pattern during pregnancy was associated with lower cognitive scores at age 2.5 (β -1.24 [-2.16, -0.32], p = 0.008) and reduced head circumference growth (p-interaction < 0.0001). We found that a Varied dietary pattern during pregnancy was associated with higher estimated intelligence quotient (IQ) at age 10 (β 1.29 [0.27, 2.3], p = 0.014). Additionally, head circumference growth was associated with higher cognitive scores at age 10 (β 3.40 [1.21, 5.60], p = 0.002), and it partly mediates the association between the Varied dietary pattern and estimated IQ (proportion mediated 13.5% [0.01, 0.71], p = 0.034). Extended breastfeeding duration was also independently associated with increased head circumference growth (p-interaction < 0.0001). These patterns and correlations were consistent even after adjusting for potential confounders and accounting for genetic influences.

Our findings reveal that a Western dietary pattern during pregnancy is associated with lower cognitive scores at age 2.5 and decreased head circumference growth, suggesting potential adverse impacts on early neurodevelopment. Conversely, a Varied dietary pattern is linked with a higher estimated IQ at age 10, with head circumference growth contributing to this positive outcome. These findings highlight the critical role of maternal nutrition during pregnancy, and duration of breastfeeding, in promoting optimal neurodevelopmental outcomes. Effective public health strategies should therefore focus on enhancing maternal dietary practices to support better cognitive and physical development in children.

Observational studies have revealed associations between levels of plasma and cerebrospinal fluid (CSF) proteins and cognition-related traits. However, these associations may be influenced by confounding factors inherent in observational research. This study aims to identify plasma and CSF proteins associated with intelligence, fluid intelligence score, and cognitive performance through the application of Mendelian randomization (MR). Proteomic quantitative trait locus (pQTL) data for plasma and CSF proteins were sourced from existing genome-wide association study (GWAS). Intelligence, fluid intelligence score, and cognitive performance GWAS summary statistics provided comprehensive data for two-sample MR analysis. Extensive sensitivity analyses, including Steiger testing, reverse MR analysis, and Bayesian co-localization, were conducted to validate associations and identify shared genetic variants. Phenotype scanning explored potential pleiotropic effects. MR analysis identified several proteins in plasma and CSF significantly associated with intelligence, fluid intelligence scores, and cognitive performance. For intelligence, negatively associated proteins in plasma include endoplasmic reticulum aminopeptidase 2 (ERAP2) and secretogranin III (SCG3), while positively associated proteins are myeloperoxidase (MPO), signal regulatory protein alpha (SIRPA), regulator of microtubule dynamics 1 (RMDN1), and endoplasmic reticulum lectin 1 (ERLEC1). In CSF, C1-esterase inhibitor and carboxypeptidase E (CBPE) both exhibited positive associations with intelligence. For fluid intelligence scores, negatively associated proteins in plasma are copine 1 (CPNE1) and SCG3, while positively associated proteins are nudix hydrolase 12 (NUDT12) and RMDN1. In CSF, Macrophage Stimulating Protein (MSP) demonstrated a significant negative impact. For cognitive performance, negatively associated proteins in plasma include ERAP2, tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1), and SCG3, while positively associated proteins are NUDT12, RMDN1, ERLEC1, and ectonucleotide pyrophosphatase/phosphodiesterase family member 5 (ENPP5). In CSF, C1-esterase inhibitor was positively associated, while MSP and soluble tyrosine kinase with immunoglobulin-like and EGF-like domains 1(sTie-1) showed a negative association. Bayesian co-localization analysis revealed significant genetic overlaps between SIRPA, RMDN1, and ERLEC1 in plasma with intelligence; NUDT12 and SCG3 in plasma with fluid intelligence scores; and TIE1, NUDT12, RMDN1, ERLEC1, and ENPP5 in plasma with cognitive performance. Additionally, significant co-localization was identified between C1-esterase inhibitor and CBPE in CSF with intelligence, as well as between C1-esterase inhibitor and sTie-1 in CSF with cognitive performance. Reverse causality analysis confirmed the causal direction from proteins to cognitive traits. This study identifies specific plasma and CSF proteins that significantly impact intelligence, fluid intelligence scores, and cognitive performance. These proteins could serve as biomarkers and targets for future research and therapeutic interventions aimed at sustaining cognitive abilities and reducing impairment risks.

Human cognitive architecture represents an intelligent natural information processing system that is described by six operational principles: information store, randomness as genesis, borrowing and reorganizing, narrow limits of change, environmental organizing and linking, and explicit intention to learn principles. The last principle, added recently, is critical, as it distinguishes this system from other, lower-level natural information-processing systems and is responsible for controlled information processing and explicit learning as opposed to implicit cognitive mechanisms of lower-level systems. The paper provides a theoretical overview of the updated model of intelligent natural information processing systems. In this model, the explicit intention to learn principle affects the operation of other principles and is directly related to intelligence as an emergent characteristic of such systems. Human intelligence and explicit, intentional learning (and motivation that is required for such learning to happen) caused the emergence of human culture on a distinct, grand scale in the process of transition from biological to cultural evolution. The paper concludes with some important educational implications emanating from the new model focusing on strengthening human intelligence.

Intelligence is defined as general mental capacity, which includes the abilities to reason, solve new problems, think abstractly, and learn quickly. Genetic factors explain a considerable fraction of inter-individual differences in intelligence. For many years, research on intelligence was limited to estimating the relative importance of genetic and environmental factors, without identifying any individual causal factors.

This review of the literature is based on pertinent original publications and reviews.

Genome-wide association studies (GWAS) have shown that certain gene loci are associated with intelligence, as well as with educational attainment, which is known to be correlated with intelligence. As each individual gene locus accounts for only a very small part of the variance in intelligence ( < 0.02%), so-called "polygenic scores" (PGS) have been calculated in which thousands of genetic variants are summarized together. On the basis of the largest GWAS performed to date, it is estimated that 7-15% of inter-individual differences in educational attainment and 7-10% in intelligence among persons of European descent can be explained by genetic factors. These genetic effects are partly indirect. At the same time, the relative importance of genetic factors in determining complex features such as intelligence and educational attainment must always be seen against the background of individual environmental conditions. In the presence of difficult social conditions, for example, the influence of genetic factors is typically lower.

At present, the polygenic scores generated from genome-wide association studies are primarily of scientific interest, yet they are becoming increasingly informative and valid for individual prediction. There is, therefore, a need for broad social discussion about their future use.

Different from previous studies on the motives of compensatory consumption, this review focuses on the strategies of compensatory consumption. This literature review aims to introduce two main strategies for compensatory consumption, within-domain and across-domain compensation. Within-domain compensation is a consumption strategy to repair a self-discrepancy in a specific domain, while across-domain compensation refers to a consumption strategy that consumers restore their global self-worth by affirming themselves in other important domains yet unrelated to the self-discrepancies. Based on the SPAR-4-SLR protocol to assemble, arrange and assess literature published from 2008 to 2023 Q1, we chose 65 articles to review. In order to gain a deeper understanding of within-domain and across-domain compensation, we systematically review the existing literature in the field and propose a framework based on the ADO models. Lastly, we discuss the various research directions for within-domain and across-domain compensation from the viewpoint of theory, context, characteristics, and methodology according to the TCCM framework. Researchers, marketers, and advertisers can learn about the latest research related to compensatory consumption strategies in this article.

We still know relatively little about how the human brain supports intelligence. I this personal view I argue that adopting the framework of neurocognitive component processes (NCP) might advance the current state of knowledge. Integration of information processing across distributed brain regions is proposed as a potential NCP, and some possible clinical implications of adopting the NCP framework are outlined.

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient care and operational efficiency. ML algorithms can analyze vast amounts of data from electronic health records, physiological monitoring systems, and other medical devices, providing real-time insights and predictive analytics to assist clinicians in decision-making. ML has shown promising results in predictive modeling for patient outcomes, early detection of sepsis, optimizing ventilator settings, and resource allocation. For instance, predictive algorithms have demonstrated high accuracy in forecasting patient deterioration, enabling timely interventions and reducing mortality rates. Despite these advancements, challenges such as data heterogeneity, integration with existing clinical workflows, and the need for transparency and interpretability of ML models persist. The deployment of ML in ICUs also raises ethical and legal considerations regarding patient privacy and the potential for algorithmic biases. For clinicians interested in the early embracing of AI-driven changes in clinical practice, in this review, we discuss the challenges of integrating AI and ML tools in the ICU environment in several steps and issues: (1) Main categories of ML algorithms; (2) From data enabling to ML development; (3) Decision-support systems that will allow patient stratification, accelerating the foresight of adequate individual care; (4) Improving patient outcomes and healthcare efficiency, with positive society and research implications; (5) Risks and barriers to AI-ML application to the healthcare system, including transparency, privacy, and ethical concerns.

The present exploratory study aimed to examine the potential impact of culture on cognitive skills and intelligence by comparing the Japanese Wechsler Adult Intelligence Scale-IV (WAIS-IV) (JW) subtests, IQs, and index scores to those of the U.S. WAIS-IV (USW).

JW raw scores corresponding to a scaled score of 10 for each subtest were scored with USW norms. Subtest, index, and IQ scores were then calculated for each age range. The impact of education on scores was evaluated through ratio of educational attainment for each cohort of the Japanese and US samples. Japanese and US data were compared using one-sample t-tests. Correlations between subtest, index, and IQ scores and education were calculated.

The USW sample performed higher than the JW sample on verbal comprehension subtests, while the JW sample demonstrated stronger performances in processing speed and perceptual reasoning subtests. However, all scores with the exception of Block Design, Matrix Reasoning, and Figure Weights were significantly associated with differential educational attainment between the two countries. Educational differences were linearly associated with age with the higher educational attainment for younger Japanese age groups and higher attainment for the older US cohorts.

The present study demonstrates cognitive differences between Japan and the USA. Performance on the WAIS-IV subtest and composite measures are highly correlated with education. Cultural factors impacting the cognitive profile of the Japanese sample such as differences in worldview, customs, educational systems, and writing system, were proposed. Clinical neuropsychologists should take these aspects into account when administering and interpreting test results.

This special series of exploratory studies compared WAIS-IV performances in five Asian countries: Japan, South Korea, Taiwan, India, and Indonesia with the U.S. The studies examined cognitive profiles across age groups to develop hypotheses on how culture can impact cognition. This summary article integrates the findings from each study to determine similarities and differences across Asian countries and proposes possible underlying cultural factors impacting cognition.

In each study, raw scores corresponding to a subscale score of 10 were scored with U.S. norms across all age groups. Index scores were calculated with the adjusted scale scores. The impact of education on test performances was determined by correlating WAIS-IV scores with a ratio of educational attainment for each country with the U.S. for each age group. Findings from each country were then integrated to develop hypotheses on cultural factors that impacted cognitive profiles.

East Asian countries (Japan, South Korea, Taiwan) demonstrated weaker Verbal Comprehension Index scores and stronger Processing Speed Index scores than the U.S. sample, although the latter was moderated by age. East Asian countries demonstrated stronger performances on Perceptual Reasoning versus Verbal Comprehension tests. East Asians and the Java subset of the Indonesian sample demonstrated a pattern of stronger performances in younger versus older cohorts which was significantly correlated with educational attainment.

Cultural factors impacting cognition were proposed. Clinical implications of the findings were discussed and directions for future studies to examine the relationship between culture and cognition were recommended.

The current paper reports four consecutive studies that were conducted to link sexual health with a new construct of sexual intelligence by developing and validating a new scale to measure sexual intelligence. Sexual intelligence was defined as "the ability to perceive, understand and respond to sexual needs and desires in a personal and social context." Sexual Intelligence Scale (SIS), comprising of 8 items in English and 2 factors (sexual knowledge & sexual behavior), was developed and validated by involving 959 respondents in the process of 4 consecutive studies. The validity of SIS was tested step by step for its face, content, factorial, convergent, discriminant, and predictive validities. The reliability was measured through internal consistency and item-total & item-scale correlations. The study found significantly higher levels of sexual intelligence in men as compared to women. Sexual intelligence, moreover, had significant positive correlations with age, education, emotional intelligence, social intelligence, sexual health, and satisfaction with life. Sexual health was linked with sexual intelligence and the SIS was accepted as a reliable and valid tool to measure sexual intelligence.

This essay questions the framing of socioemotional development as a separate concomitant of cognitive development in gifted individuals. Rather, it argues, first, that socioemotional development of the gifted is not separate from giftedness. Second, socioemotional development is not even cleanly and clearly separable from cognitive development. Third, giftedness and even intelligence do not reside inside the person-they are not personal properties but rather interactions of persons with tasks and situations. In sum, giftedness needs to be viewed in a holistic context that encompasses integrated cognitive, socio-emotional, task, and situational contextual elements.

When students with high cognitive abilities disengage from school, this implies a severe loss of talent to students themselves and to society. Hence, it is important to understand how teachers can prevent disengagement and underachievement in high-ability students. Whereas a large body of research has demonstrated that need-supportive teaching (i.e., the provision of autonomy support, involvement, and structure) and differentiated instruction relate positively to students' academic development, it remains unclear whether such practices would be equally, more, or less beneficial for high-ability students. Drawing on data from a longitudinal four-wave study among early adolescents from Flanders (N = 3586), this study showed that need-supportive teaching in math classes was positively associated with intrinsic motivation, behavioral engagement, and math performance in high-ability students, both at the level of between-student differences and at the level of changes in students over time. Standardized estimates were typically between 0.05 and 0.20 at the between-person level, indicating small effect sizes, with more modest effect sizes at the within-person level. Importantly, these associations were found to be generally equivalent across high- and average-ability students. Comparing the provision of need-supportive teaching to either high- or average-ability students, high-ability students particularly reported more autonomy support from their math teachers than average-ability students, with small effect sizes (i.e., Cohen's d between 0.16 and 0.27). These findings underline the importance of need-supportive teaching to support the motivational and academic development of both high- and average-ability students.

We were interested in how people in a romantic relationship would perceive the intelligence of their partners who have high or low trait anger. Specifically, we referred to the tension between compassion (low anger) and competence (high intelligence) in mate choice. Some evolutionary theories suggest that mating might be considered a bargaining process between these two higher-order attributes. Our study involved 148 heterosexual couples in romantic relationships. We measured the relationship between relationship satisfaction, trait anger, objective intelligence, self-assessed intelligence, and subjectively assessed partners' intelligence. We found that angrier men were less satisfied in their romantic relationship than those men who were less angry, and their partners were also less satisfied in the relationship. Additionally, women perceived angrier men as less intelligent, an effect that remained after controlling for men's objective intelligence. Lastly, we found that women's perception of their partner's intelligence mediated the link between men's anger and relationship satisfaction for both sexes. Our findings suggest that both anger and intelligence play important roles in romantic relationship functioning, consistent with evolutionary theories that emphasize the value of competence (i.e., intelligence) and compassion (i.e., low anger) in romantic partners. Furthermore, our study highlights the importance of women's perception of their partner's intelligence in determining the quality of the relationship.

Intelligence and personality are both key drivers of learning. This study extends prior research on intelligence and personality by adopting a behavioral-process-related eye-tracking approach. We tested 182 adults on fluid intelligence and the Big Five personality traits. Eye-tracking information (gaze patterns) was recorded while participants completed the intelligence test. Machine learning models showed that personality explained 3.18% of the variance in intelligence test scores, with Openness and, surprisingly, Agreeableness most meaningfully contributing to the prediction. Facet-level measures of personality explained a larger amount of variance (7.67%) in intelligence test scores than the trait-level measures, with the largest coefficients obtained for Ideas and Values (Openness) and Compliance and Trust (Agreeableness). Gaze patterns explained a substantial amount of variance in intelligence test performance (35.91%). Gaze patterns were unrelated to the Big Five personality traits, but some of the facets (especially Self-Consciousness from Neuroticism and Assertiveness from Extraversion) were related to gaze. Gaze patterns reflected the test-solving strategies described in the literature (constructive matching, response elimination) to some extent. A combined feature vector consisting of gaze-based predictions and personality traits explained 37.50% of the variance in intelligence test performance, with significant unique contributions from both personality and gaze patterns. A model that included personality facets and gaze explained 38.02% of the variance in intelligence test performance. Although behavioral data thus clearly outperformed "traditional" psychological measures (Big Five personality) in predicting intelligence test performance, our results also underscore the independent contributions of personality and gaze patterns in predicting intelligence test performance.

While the impact of depression on cognition is well-documented, the relationship between feelings and cognition has received limited attention.

To explore the potential association between feelings and cognition with a two-sample Mendelian randomization (MR) analysis.

Our analysis utilized genome-wide association data on various feelings (fed-up feelings, n = 453071; worrier/anxious feelings, n = 450765; guilty feelings, n = 450704; nervous feelings, n = 450700; sensitivity/hurt feelings, n = 449419; miserableness, n = 454982; loneliness/isolation, n = 455364; happiness, n = 152348) in the European population and their impact on cognitive functions (intelligence, n = 269867). Conducting a univariable MR (UVMR) analysis to assess the relationship between feelings and cognition. In this analysis, we applied the inverse variance weighting (IVW), weighted median, and MR Egger methods. Additionally, we performed sensitivity analysis (leave-one-out analysis), assessed heterogeneity (using MR-PRESSO and Cochran's Q test), and conducted multiple validity test (employing MR-Egger regression). Subsequently, a multivariable MR (MVMR) analysis was employed to examine the impact of feelings on cognition. IVW served as the primary method in the multivariable analysis, complemented by median-based and MR-Egger methods.

In this study, UVMR indicated that sensitivity/hurt feelings may have a negative causal effect on cognition (OR = 0.63, 95%CI: 0.43-0.92, P = 0.017). After adjustment of other feelings using MVMR, a direct adverse causal effect on cognition was observed (ORMVMR = 0.39, 95%CI: 0.17-0.90, PMVMR = 0.027). While a potential increased risk of cognitive decline was observed for fed-up feelings in the UVMR analysis (ORUVMR = 0.64, 95%CI: 0.42-0.97, PUVMR = 0.037), this effect disappeared after adjusting for other feelings (ORMVMR = 1.42, 95%CI: 0.43-4.74, PMVMR = 0.569). These findings were generally consistent across MV-IVW, median-based, and MR-Egger analyses. MR-Egger regression revealed pleiotropy in the impact of worrier/anxious feelings on cognition, presenting a challenge in identifying the effect. Notably, this study did not demonstrate any significant impact of guilty feelings, nervous feelings, miserableness, or loneliness/isolation on cognition. Due to a limited number of instrumental variables for happiness, this study was unable to analyze the relationship between happiness and cognition.

This MR study finds that sensitivity/hurt feelings are associated with cognitive decline, while the link between worrier/anxious feelings and cognition remains inconclusive. Insufficient evidence supports direct associations between happiness, guilty feelings, nervous feelings, miserableness, loneliness/isolation, and cognition.

Artificial intelligence (AI) is routinely mentioned in journals and newspapers, and non-technical outsiders may have difficulty in distinguishing hyperbole from reality. We present a practical guide to help non-technical neurologists to understand healthcare AI. AI is being used to support clinical decisions in treating neurological disorders. We introduce basic concepts of AI, such as machine learning and natural language processing, and explain how AI is being used in healthcare, giving examples its benefits and challenges. We also cover how AI performance is measured, and its regulatory aspects in healthcare. An important theme is that AI is a general-purpose technology like medical statistics, with broad utility applicable in various scenarios, such that niche approaches are outpaced by approaches that are broadly applicable in many disease areas and specialties. By understanding AI basics and its potential applications, neurologists can make informed decisions when evaluating AI used in their clinical practice. This article was written by four humans, with generative AI helping with formatting and image generation.

The aim of this study was to assess the size of the corpus callosum in members of Mensa International, which is the world's largest and oldest high-intelligence quotient (IQ) society.

We performed T2-weighted magnetic resonance imaging (Repetition Time, TR = 3200 ms, Time of Echo, TE = 409 ms) to examine the brain of members of Mensa International (Polish national group) in order to assess the size of the corpus callosum. Results from 113 male MENSA members and 96 controls in the age range of 21-40 years were analyzed.

The comparative analysis showed that the mean length of the corpus callosum and the thickness of the isthmus were significantly greater in the Mensa members compared to the control groups. A statistically significant difference was also identified in the largest linear dimension of the brain from the frontal lobe to the occipital lobe. The mean corpus callosum cross-sectional area and its ratio to the brain area were significantly greater in the Mensa members.

The results show that the dimensions (linear measures and midsagittal cross-sectional surface area) of the corpus callosum were significantly greater in the group of Mensa members than in the controls.

Executive functions (EFs) play a key role in cognitive and behavioral functioning. Their multiple forms and implications for daily life behaviors mean they are sometimes equated with intelligence. Several elements even suggest that intellectually gifted children (IGC) may present better executive functioning than typical developing children (TDC, children with intelligence in the average range). However, no study has ever completely tested this hypothesis by a comprehensive assessment of EFs in IGC.

Results of 30 IGC and 35 TDC aged from 6 to 16 years old were compared through a comprehensive assessment of EFs (inhibition, flexibility, and planning), comprising performance-based and daily life measures.

IGC did not differ from TDC in EF performance-based measures. However, they scored higher in parents' and some teachers' ratings, suggesting higher indicators of difficulties in daily life.

Contrary to expectations, high intellectual level does not appear to be associated with superior EFs. Surprisingly, parents and teachers of IGC reported more complaints about their executive functioning in everyday life. We put forward different hypotheses to explain this contrast. Further research is needed to better understand this phenomenon, in which neuropsychology has a fundamental role to play.

Autobiographical reasoning is a process by which an individual creates a coherent life account. The degree of coherence in autobiographical reasoning has been related to psychological health correlates such as depression and self-esteem in previous studies, but with inconsistent findings. Similarly, the basic psychological processes required to achieve coherence have been previously studied with regard to intelligence, but infrequently, and also with mixed findings. In the present study, we first developed and evaluated a German version of the Awareness of Narrative Identity Questionnaire (ANIQ) as an established measure of self-reported coherence. Second, we tested for cognitive dependencies on intelligence and memory indices. Third, we analysed its associations with psychological health correlates. We assessed a sample of 272 participants and thereof 189 participants again two-weeks later. Results supported the assumptions of the German ANIQ's psychometric qualities (factor structure, test-retest reliability, invariance) and validity (with regard to self-consciousness, self-concept clarity, and written accounts of personal turning points). We found coherence to be independent of intelligence and verbal memory, but partially dependent on figural memory. Coherence was related to depression, positivity, self-esteem, and self-esteem stability, but not to anxiety, substantiating its salutogenic effects.

There is a host of research on the structure of working memory (WM) and its relationship with intelligence in adults, but only a few studies have involved children. In this paper, several different WM models were tested on 170 Japanese school children (from 7 years and 5 months to 11 years and 6 months). Results showed that a model distinguishing between modalities (i.e., verbal and spatial WM) fitted the data well and was therefore selected. Notably, a bi-factor model distinguishing between modalities, but also including a common WM factor, presented with a very good fit, but was less parsimonious. Subsequently, we tested the predictive power of the verbal and spatial WM factors on fluid and crystallized intelligence. Results indicated that the shared contribution of WM explained the largest portion of variance of fluid intelligence, with verbal and spatial WM independently explaining a residual portion of the variance. Concerning crystallized intelligence, however, verbal WM explained the largest portion of the variance, with the joint contribution of verbal and spatial WM explaining the residual part. The distinction between verbal and spatial WM could be important in clinical settings (e.g., children with atypical development might struggle selectively on some WM components) and in school settings (e.g., verbal and spatial WM might be differently implicated in mathematical achievement).

The purpose of the current study is to explore listeners' perception of accented speech in terms of confidence and intelligence. To this end, three groups of listeners were asked to rate speakers of English with various accent strengths based on a 9-point scale in terms of accent magnitude, confidence and intelligence. Results show that the two Jordanian listener groups, unlike the English listeners, reacted similarly toward Jordanian-accented speakers of English. Overall, the three groups tended to link accentedness with perceptions of confidence and intelligence. The findings of this study have significant implications for advocating a tolerant attitude toward speakers of English as a foreign language in the fields of education, employment opportunities, and social justice. It is suggested that stereotyping speakers as inferior in terms of qualities such as confidence and intelligence reflects established listener's bias rather than lack of speaker's intelligibility.

Observational studies suggest physical activity (PA) enhances intelligence, while sedentary behavior (SB) poses a risk. However, causality remains unclear.

We extracted genetic instruments from large genome-wide association studies summary data and employed an inverse-variance weighted (IVW) approach within a random-effects model as the primary method of Mendelian randomization (MR) analysis to estimate the overall effect of various physical activity statuses on intelligence. To assess IVW stability and MR sensitivity, we also utilized supplementary methods including weighted median, MR-Egger, and MR-PRESSO. Furthermore, multivariable MR analysis was conducted to examine the independent effects of each physical activity trait on intelligence.

The MR primary results indicated that LST was negatively associated with intelligence (β = -0.133, 95%CI: -0.177 to -0.090, p = 1.34×10-9), while SBW (β = 0.261, 95% CI: 0.059 to 0.463, p = 0.011) may have a positive effect on intelligence; however, MVPA and SC did not show significant effects on intelligence. Inverse causality analyses demonstrated intelligence significantly influenced all physical activity states.

Our study highlights a bidirectional causal relationship between physical activity states and intelligence.

The increasing complexity of the modern financial landscape presents significant challenges for individuals' financial well-being. In this study, we aim to investigate the relationship between cognitive ability and financial well-being by utilizing data from the British Cohort Study, which follows a sample of 13,000 individuals from birth in 1970 to the present day. Our objective is to examine the functional form of this relationship while controlling for factors such as childhood socio-economic status and adult income. Previous research has established a correlation between cognitive ability and financial well-being, but has implicitly assumed a linear relationship. Our analyses indicate that the majority of the relationships between cognitive ability and financial variables are monotonic. However, we also observe non-monotonic relationships, particularly for credit usage, suggesting a curvilinear relationship where both lower and higher levels of cognitive ability are associated with lower levels of debt. These findings have important implications for understanding the role of cognitive ability in financial well-being and for financial education and policy, as the complexity of the modern financial landscape poses significant challenges for individuals' financial well-being. As financial complexity is increasing and cognitive ability is a key predictor of knowledge acquisition, misspecifying the true relationship between cognitive ability and financial outcomes leads to an undervaluation of the role of cognitive ability for financial well-being.

The Roberts Apperception Test for Children (RATC) is a projective method developed by McArthur and Roberts (1982) to assess children and adolescents' behavioural, social and emotional functioning, concerns, conflicts and emotional management strategies through their perceptions of common interpersonal situations of everyday life. The aim of the present study is to contribute to the validation of the RATC in a forensic sample (N = 75) [constituted by a group of juvenile delinquents detained in educational centres (n = 40, 12-17 years old, 1-10 years of schooling) and a group of maltreated adolescents integrated in residential care (n = 35, 11-16 years old, 5-10 years of schooling)], studying its psychometric properties, such as reliability and criterion validity (convergent and discriminant validity), considering the results obtained in other instruments as external validation criteria: Wechsler Intelligence Scale for Children - Third Edition (WISC-III) and Youth Self-Report (YSR). It also aims to search for some indicators based on means and standard deviations to interpret the scores obtained in RATC for these forensic contexts, through the comparisons within forensic groups and the comparisons of the forensic groups with a community sample. The RATC showed minimally acceptable reliability and adequate validity indices, considering that this instrument is a projective method. This limitation is compensated by the clinical value of the data obtained from the projection of individuals' thoughts, concerns, conflicts and problem-solving styles, which are useful to assess their emotional and behavioural characteristics and psychological functioning. The results also show statistically significant differences between the two forensic groups on RATC scales, as well as between them and the community sample, as expected, underlining their different characteristics.

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

We carried out an exploratory study of the association between exposure to violence, intelligence, and executive functions in Brazilian preadolescents. The study included 56 participants (31 males) aged 8 to 14 years old (mean = 11.3, SD = 1.0). We administered neuropsychological tests to evaluate executive functions and the Juvenile Victimization Questionnaire (JVQ) to evaluate exposure to violence. We used the following neuropsychological instruments: Wechsler Abbreviated Scale of Intelligence (WASI), Stroop Color-Word Interference task, digits subtest of the Wechsler Intelligence Scale for Children, and an N-back task. We generated a composite score from neuropsychological test scores and investigated the association of that score, and individual test scores, with exposure to violence and socioeconomic status (SES). Results suggest, first, that exposure to violence is associated with a 0.5-point lower intelligence quotient score for every reported victimization event in the Juvenile Victimization Questionnaire. Results also show that the digits backward subtest scores showed a significant negative correlation with exposure to violence (JVQ; rho = -0.29, p < 0.05); both analyses were adjusted for the level of schooling of parents or guardians, which was also found to be significantly associated with lower intelligence quotient scores. We discuss results in the light of the existing literature on the effects of exposure to violence on adolescent development, and the amounting evidence that suggests an association of exposure to violence, and of victimization, with tests that evaluate constructs of executive functions. The study struggled with low compliance from participants, and we underscore the challenges of carrying out empirical studies aimed at better understanding the development of underrepresented youths, such as those from Central and Latin America.

Most of the work examining the relationship between intelligence and job performance has conceptualized intelligence as g. Recent findings, however, have supported the claim that more specific factors of intelligence contribute to the prediction of job performance. The present study builds upon prior work on specific cognitive abilities by investigating the relationship between ability tilt, a measure representing differential strength between two specific abilities, and job performance. It was hypothesized that ability tilt would differentially relate to job performance based on whether or not the tilt matched the ability requirements of the job, and that ability tilt would provide incremental validity over g and specific abilities for predicting performance when the tilt matched job requirements. Hypotheses were tested using a large sample from the General Aptitude Test Battery (GATB) database. Ability tilt related with job performance in the expected direction for 27 of the 36 tilt-job combinations examined, with a mean effect size of .04 when the tilt matched job requirements. The mean incremental validities for ability tilt were .007 over g and .003 over g and specific abilities, and, on average, tilt explained 7.1% of the total variance in job performance. The results provide limited evidence that ability tilt may be a useful predictor in addition to ability level, and contribute to our understanding of the role of specific abilities in the workplace.

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

The COVID-19 pandemic has affected schooling worldwide. In many places, schools closed for weeks or months, only part of the student body could be educated at any one time, or students were taught online. Previous research discloses the relevance of schooling for the development of cognitive abilities. We therefore compared the intelligence test performance of 424 German secondary school students in Grades 7 to 9 (42% female) tested after the first six months of the COVID-19 pandemic (i.e., 2020 sample) to the results of two highly comparable student samples tested in 2002 (n = 1506) and 2012 (n = 197). The results revealed substantially and significantly lower intelligence test scores in the 2020 sample than in both the 2002 and 2012 samples. We retested the 2020 sample after another full school year of COVID-19-affected schooling in 2021. We found mean-level changes of typical magnitude, with no signs of catching up to previous cohorts or further declines in cognitive performance. Perceived stress during the pandemic did not affect changes in intelligence test results between the two measurements.

Theorists have constructed emotional intelligence differently, based on which the literature reveals different diversified scales to measure emotional intelligence. These scales are quite lengthy to respond and have been criticized for producing varying results. The current paper projects the findings of 3 consecutive studies carried out to summarize and simplify the existing models of emotional intelligence and to produce a brief measure in this regard.

Based on the review of the earlier models of emotional intelligence, emotional intelligence was comprehended as an "ability to express and regulate emotions for intrinsic and extrinsic emotional satisfaction". "Emotional Intelligence Scale (EIS)", comprising 12 items in English, was developed and validated through principal component analysis, exploratory factor analysis, and confirmatory factor analysis through a series of 3 consecutive studies which involved 1894 participants from Pakistan. The validity of EIS was tested step by step for its face, content, factorial, convergent, and discriminant validity. The reliability was measured through internal consistency and item-total and item-scale correlations.

EIS was revealed to be a valid and reliable scale to measure emotional intelligence through 4 core factors, ie, emotional expression, emotional regulation, intrinsic emotional satisfaction, and extrinsic emotional satisfaction. The additional findings revealed significantly higher levels of emotional intelligence among men as compared to women; significantly positive correlation of emotional intelligence with social intelligence, positive emotional effects, age, and education; and a significantly inverse correlation between emotional intelligence and the negative emotional effects.

The current paper reported the development and validation of a new scale on emotional intelligence by comprehending and summarizing the earlier models of emotional intelligence.

Thanks to the rapid development of computer-based systems and deep-learning-based algorithms, artificial intelligence (AI) has long been integrated into the healthcare field. AI is also particularly helpful in image recognition, surgical assistance and basic research. Due to the unique nature of dermatology, AI-aided dermatological diagnosis based on image recognition has become a modern focus and future trend. Key scientific concepts of review: The use of 3D imaging systems allows clinicians to screen and label skin pigmented lesions and distributed disorders, which can provide an objective assessment and image documentation of lesion sites. Dermatoscopes combined with intelligent software help the dermatologist to easily correlate each close-up image with the corresponding marked lesion in the 3D body map. In addition, AI in the field of prosthetics can assist in the rehabilitation of patients and help to restore limb function after amputation in patients with skin tumors.

For the benefit of patients, dermatologists have an obligation to explore the opportunities, risks and limitations of AI applications. This study focuses on the application of emerging AI in dermatology to aid clinical diagnosis and treatment, analyzes the current state of the field and summarizes its future trends and prospects so as to help dermatologists realize the impact of new technological innovations on traditional practices so that they can embrace and use AI-based medical approaches more quickly.

This article examines the duality of the Black psychology movement in the United States as both a distinctly American and a postcolonial approach to mental health. The Westside Community Mental Health Center in San Francisco served as the organizational hub for the Association for Black Psychologists (ABPsi) in the 1970s. The Westside clinicians understood forensic psychology as a kind of preventative care as California, more so than any other state, was seduced by the eugenic dream of human improvement through therapeutic interventions in schools and prisons intended to correct the wayward deviant. Their community's mental wellbeing required dismantling the interlinked disciplinary apparatus which disproportionately surveyed, tracked, and confined young Black men. These psychologists mounted a legal challenge to the use of intelligence testing to sort Black children in schools, seeking to replace standardized tests with "dynamic assessments" inspired by Israeli psychologist Reuven Feuerstein's work with refugee children. They consulted on the voir dire process in the highly politicized Angela Davis trial to minimize the presence of racially prejudiced jurors. They offered expert testimony on the psychological damage of solitary confinement on behalf of prison activists. The Westside team artfully developed and deployed the psychological concept of "bias" in their confrontations with local manifestations of the American carceral state. In their theoretical writings, these psychologists reflected upon their historical positionality, understanding themselves as products of the decolonial moment. Bay Area encounters with Third World internationalism, the Black Panther Party (BPP), the Nation of Islam, and community-led substance abuse programs shaped clinical care at Westside and inspired the Afrocentric consciousness many came to espouse. ABPsi initially had a significant impact on the historically white American Psychological Association's training practices. However, the two organizations split over the IQ controversy at a moment when psychologists became increasingly enmeshed in the criminal justice system.