General Intelligence Research Articles

Visual impairment and cognitive performance: A nationwide study of 1.4 million adolescents.

Previous research highlights the adverse effects of visual impairment (VI) on academic achievement in children, yet its impact on cognitive performance among adolescents and young adults remains under-studied. Therefore, this investigation aimed to analyse this association in a nationwide sample of Israeli adolescents. A retrospective population-based cross-sectional study was conducted among 1,410,616 Israeli-born adolescents aged 16-19 years, who were assessed before mandatory military service between 1993 and 2017. The definition of VI was based on best-corrected visual acuity (BCVA) measurements using a standard Snellen chart. Adolescents with BCVA worse than 6/9 in either or both eyes were classified as having unilateral or bilateral VI, respectively. Cognitive performance was measured using the General Intelligence Score (GIS), based on a validated four-domain test. Relationships were analysed using regression models yielding adjusted odds ratios (ORs) for low (<-1 standard deviation [SD]) and high (≥1 SD) cognitive Z-scores. Of 1,410,616 adolescents (56.1% men), 13,773 (1.0%) had unilateral and 3980 (0.3%) had bilateral VI. Unilateral VI was associated with adjusted ORs for low and high cognitive Z-scores of 1.24 (1.19-1.30) and 0.84 (0.80-0.89), respectively. ORs were accentuated for bilateral VI, reaching 1.62 (1.50-1.75) and 0.81 (0.74-0.90) for low and high cognitive Z-scores, respectively. Cognitive performance subscores mirrored these results, with the visual-spatial functioning subtest demonstrating the greatest effect size. These associations persisted in sub-analyses restricted to adolescents with amblyopia-related VI, mild VI and unimpaired health status. Visual impairment, including mild and unilateral cases, is associated with reduced cognitive performance scores assessed in late adolescence. Further research is required to gain a comprehensive understanding of the dynamics underlying this relationship.

A Social Self-Awareness Agent with Embodied Reasoning

In the realm of multi-agent systems, establishing social self-awareness in agents stands as a critical challenge within the broader scope of artificial general intelligence research. Addressing this challenge, in this paper, we draw upon Tomasello’s social self-awareness theory as a foundational framework, and employ Non-Axiomatic Reasoning System (NARS), an artificial general intelligence model, to simulate analogical and recursive reasoning methods used by socially embodied agents. In this paper, we assume that an agent can possess sensorimotor capabilities and physical common sense, it explores the process of constructing a “core self” through embodied reasoning. On this basis, we explore deeper into the construction process of social self-awareness. As a result, we clarify how agents generate common knowledge about themselves through recursive reasoning regarding the mental states of others and communication dynamics. Following this initial step, metaphors are generated utilizing analogical reasoning, intertwining public knowledge with these metaphors to facilitate mutual comprehension between humans and machines. This paper delves into the simulation of perspective representation and recursive reasoning within social embodied agents, employing NARS– an overarching artificial intelligence platform. The experimental results substantiate the viability of constructing a social self-agent within a machine framework grounded in embodied reasoning.

The Correlation between Definitions of General and Social Intelligence in the Empirical Study on Teachers of Preschool Educational Institutions

The purpose of our article is to analyze the Phenomenological Scientific Approach to the characteristics of general intelligence of a personality; to consider Intelligence structure as a basic general category, to describe the problem of its origin and essence as one concept of the “eternal”, “planetary” problems; to show Measuring (or Testological) Scientific Approach to characterize the general intelligence of a person; to propose the characteristics of Associated-systems theory; to study the problem of general and social intelligence, to analyze correlation of these definitions according to the thoughts of teachers of preschool educational establishments. Methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, methods of the analysis, systematization, modeling, generalization. Also, in our research we used empirical methods, like statement study. The results of the research. We proved that in the paradigm of Cognitive Psychology the study of social cognitions and social intelligence has greatly enriched in the Psychology by the essence and the content of social intelligence, which previously had been developed in the psychometric tradition. Thanks to Cognitive Psychology, the actualization of the concepts of social representation was intensified. However, the analysis of existing models of representations of social knowledge suggests that the greatest attention in the history of Cognitive Psychology was given to abstract representations, and existing mental models (which relate to both verbal and figurative presentation formats of information) were not systematically checked. In addition, the functioning of these models, as a rule, plays a leading role in such a field of social cognition, as actualization of processes of social categorization and stereotyped thinking, in the field of perception of psychological features, the formation of the first impression, understanding of subjects of interpersonal interaction, etc. This situation, we deal with, sets the prospect of further empirical research on the development of social intelligence. Conclusions. So, Intellect (from the Latin Intellectus – feeling, perception, understanding, concept, mind) is a quality of the psyche of a personality, which is based on the ability to adapt to new situations, the ability to learn on the basis of acquired personally significant experience, understanding and application of both specific and abstract concepts to use their knowledge in order to influence and manage the environment. Intelligence is defined as the general ability of an individual to know and solve problems and tasks, which unite all cognitive processes and present human cognition: feelings, perception, memory, representation, imagination and thinking.

Inconclusive evidence for an increasing effect of maternal supportiveness on childhood intelligence in Dunkel et al. (2023): A simulated reanalysis

In a recent study (N = 1075), Dunkel et al. (2023) concluded that maternal supportiveness is important for children's general intelligence. Maternal supportiveness was measured at ages 14, 24, and 36 months while children's intelligence was measured at ages 14, 24, and 36 months and at 4 and 10 years. The effects of maternal supportiveness at time T (β = 0.12), of maternal supportiveness at time T + 1 (β = 0.08), and of the child's intelligence at T + 1 (β = 0.49) on the child's intelligence at T + 2, were all positive and statistically significant when adjusting for one another. However, it is known that such adjusted cross-lagged effects may be biased due to residual confounding and regression to the mean. In the present study, we fitted various models, including latent change score models, on data simulating the data used by Dunkel et al. We found discrepant effects. For example, a positive effect of supportiveness on subsequent increase in children's intelligence (β = 0.04) was accounted for by maternal intelligence (β = 0.01 after adjustment). Another effect indicated that low supportiveness may compensate for having a mother with low intelligence and allow children to achieve the same intelligence as children to more intelligent and supportive mothers (β = 0.34). These divergent findings suggested that it may be premature to assume an increasing effect of maternal supportiveness on children's intelligence. It is important for researchers to bear in mind that correlations, also in superficially more advanced forms like cross-lagged effects, do not prove causality.

Mitochondrial complex I density is associated with IQ and cognition in cognitively healthy adults: an in vivo [18F]BCPP-EF PET study.

Mitochondrial function plays a key role in regulating neurotransmission and may contribute to general intelligence. Mitochondrial complex I (MC-I) is the largest enzyme of the respiratory chain. Recently, it has become possible to measure MC-I distribution in vivo, using a novel positron emission tomography tracer [18F]BCPP-EF, thus, we set out to investigate the association between MC-I distribution and measures of cognitive function in the living healthy brain. Analyses were performed in a voxel-wise manner and identified significant associations between [18F]BCPP-EF DVRCS-1 in the precentral gyrus and parietal lobes and WAIS-IV predicted IQ, WAIS-IV arithmetic and WAIS-IV symbol-digit substitution scores (voxel-wise Pearson's correlation coefficients transformed to Z-scores, thresholded at Z = 2.3 family-wise cluster correction at p < 0.05, n = 16). Arithmetic scores were associated with middle frontal and post-central gyri tracer uptake, symbol-digit substitution scores were associated with precentral gyrus tracer uptake. RAVLT recognition scores were associated with [18F]BCPP-EF DVRCS-1 in the middle frontal gyrus, post-central gyrus, occipital and parietal regions (n = 20). Taken together, our findings support the theory that mitochondrial function may contribute to general intelligence and indicate that interindividual differences in MC-I should be a key consideration for research into mitochondrial dysfunction in conditions with cognitive impairment.

Introduction for the special issue of “Ideologies of AI and the consolidation of power”: Naming power

This introductory essay for the special issue of First Monday, “Ideologies of AI and the consolidation of power,” considers how power operates in AI and machine learning research and publication. Drawing on themes from the seven contributions to this special issue, we argue that what can and cannot be said inside of mainstream computer science publications appears to be constrained by the power, wealth, and ideology of a small cohort of industrialists. The result is that shaping discourse about the AI industry is itself a form of power that cannot be named inside of computer science. We argue that naming and grappling with this power, and the troubled history of core commitments behind the pursuit of general artificial intelligence, is necessary for the integrity of the field and the well-being of the people whose lives are impacted by AI.

The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence

The stated goal of many organizations in the field of artificial intelligence (AI) is to develop artificial general intelligence (AGI), an imagined system with more intelligence than anything we have ever seen. Without seriously questioning whether such a system can and should be built, researchers are working to create “safe AGI” that is “beneficial for all of humanity.” We argue that, unlike systems with specific applications which can be evaluated following standard engineering principles, undefined systems like “AGI” cannot be appropriately tested for safety. Why, then, is building AGI often framed as an unquestioned goal in the field of AI? In this paper, we argue that the normative framework that motivates much of this goal is rooted in the Anglo-American eugenics tradition of the twentieth century. As a result, many of the very same discriminatory attitudes that animated eugenicists in the past (e.g., racism, xenophobia, classism, ableism, and sexism) remain widespread within the movement to build AGI, resulting in systems that harm marginalized groups and centralize power, while using the language of “safety” and “benefiting humanity” to evade accountability. We conclude by urging researchers to work on defined tasks for which we can develop safety protocols, rather than attempting to build a presumably all-knowing system such as AGI.

Primary Arterial Hypertension Associated with Cognitive Dysfunction in Young Adults: Results from a Cross-Sectional Controlled Study.

Despite evidence of primary hypertension (PH)-associated cognitive dysfunction in pediatric, middle-aged, and older adult populations, respective data in young adults remains scarce. We aimed to define differences in cognitive performance between individuals with PH and healthy controls in early adulthood. A convenience sample of young adults (age 18-45 years) with PH and their healthy sex, age, education, and household income matched counterparts were cross-sectionally tested for verbal fluency, verbal memory, general intelligence, reaction speed, attention, visual memory, and executive functioning. Between-group differences were determined using Student's t and Mann-Whitney U tests. Sensitivity analysis was performed by adjusting for body mass index (BMI) in analysis of covariance (ANCOVA) and regression models. Thirty-three adults with PH (22, 66.7% male, median age 38.8, interquartile range (IQR) = 33.2-41.6 years) and twenty-two healthy controls (9, 40.9% male, median age 36.1, IQR = 27.5-39.8 years) completed the neuropsychological assessment. Participants with PH performed worse on computerized tasks of reaction time (median response time (Z = -2.019, p = 0.044), median time for release of response button (Z = -2.509, p = 0.012)) and sustained attention (signal detection measure, RVPA (t = 2.373, p = 0.021), false alarms ÷ (false alarms + correct rejections), RVPPFA (Z = -2.052, p = 0.040)). The group variable was not a statistically significant predictor of performance in these domains after adjustment for BMI (p > 0.05). In regression analyses, high office systolic blood pressure (oSBP) was independently associated with poor sustained attention (βSBP(st.) = -0.283, multiple R2 = 0.252 (RVPA), βSBP(st.) = 0.551, multiple R2 = 0.386 (RVPPFA)). Young adults with PH were found to perform worse in tasks of response speed and sustained attention. While the difference between neuropsychological evaluation results in PH and control groups was confounded by BMI, oSBP measures were independently related to sustained attention. The selectivity of PH-associated cognitive profile in young adults has to be confirmed in larger trials.

Meta predictive learning model of languages in neural circuits.

Large language models based on self-attention mechanisms have achieved astonishing performances, not only in natural language itself, but also in a variety of tasks of different nature. However, regarding processing language, our human brain may not operate using the same principle. Then, a debate is established on the connection between brain computation and artificial self-supervision adopted in large language models. One of most influential hypotheses in brain computation is the predictive coding framework, which proposes to minimize the prediction error by local learning. However, the role of predictive coding and the associated credit assignment in language processing remains unknown. Here, we propose a mean-field learning model within the predictive coding framework, assuming that the synaptic weight of each connection follows a spike and slab distribution, and only the distribution, rather than specific weights, is trained. This meta predictive learning is successfully validated on classifying handwritten digits where pixels are input to the network in sequence, and moreover, on the toy and real language corpus. Our model reveals that most of the connections become deterministic after learning, while the output connections have a higher level of variability. The performance of the resulting network ensemble changes continuously with data load, further improving with more training data, in analogy with the emergent behavior of large language models. Therefore, our model provides a starting point to investigate the connection among brain computation, next-token prediction, and general intelligence.

Large-scale photonic chiplet Taichi empowers 160-TOPS/W artificial general intelligence.

The pursuit of artificial general intelligence (AGI) continuously demands higher computing performance. Despite the superior processing speed and efficiency of integrated photonic circuits, their capacity and scalability are restricted by unavoidable errors, such that only simple tasks and shallow models are realized. To support modern AGIs, we designed Taichi-large-scale photonic chiplets based on an integrated diffractive-interference hybrid design and a general distributed computing architecture that has millions-of-neurons capability with 160-tera-operations per second per watt (TOPS/W) energy efficiency. Taichi experimentally achieved on-chip 1000-category-level classification (testing at 91.89% accuracy in the 1623-category Omniglot dataset) and high-fidelity artificial intelligence-generated content with up to two orders of magnitude of improvement in efficiency. Taichi paves the way for large-scale photonic computing and advanced tasks, further exploiting the flexibility and potential of photonics for modern AGI.

Analyze and Evaluate the Method Used as Well as the Fallout of OpenAI's Board of Directors Decision to Remove Sam Altman as CEO of the Company

Formed in December of 2015 by such leading lights as Elon Musk and Sam Altman, OpenAI has become a major player on the AI research stage. The OpenAI is committed to developing and Artist, researching investing in creating a technology beneficial for all of mankind. As such, the organization's primary visionaries are working creatively on artificial General Intelligence This latter type refers to systems which would be able perform better than humans at economically significant tasks. OpenAI and my future This study focuses on the course of this endeavor to develop artificial general intelligence, but more important than that is emphasis which Security matters the most fundamental consideration in infusing ethical principles into AI technologies is safety. The most recent in the line--GPT 3.5 -- has been offering impressive abilities related to a wide range of language processing tasks and is reflected by improvements in fields like computer-assisted translation services, automated content generation applications or even virtual assistants. Not only do the GPT models promise a transformative change for natural language processing, their announcement and reception--both within the community of artificial intelligence researchers, as well by people in various sectors of technology industry -- deserve an academic examination.

Relationship between Emotional Intelligence and Depression in Teaching Faculty of Basic Sciences at a Private Medical College: A Cross Sectional Correlational Study

Background: Emotional Intelligence (EI) spans five basic principles including awareness and management of self-emotions, ability to motivate oneself, awareness, and management of other’s emotions. EI takes a person to high level of professional as well as academic success by improving one’s cognitive performance far above the level attained by general intelligence (GI). In addition, EI enables one to control negative attributes such as anxiety, anger, and stress and highlight pragmatic and constructive feelings like congeniality, self-confidence and empathy. Objective: The current study was designed to estimate the level of emotional intelligence (EI) in teaching faculty of basic sciences at a private medical college and to check its correlation with depression. Study Design: Cross sectional correlational study. Settings: Lahore Medical &amp; Dental College, Lahore Pakistan. Duration: December 2021- April 2022. Methods: Two questionnaires including “Leadership Toolkit Emotional Intelligence Questionnaire” and “Patient Health Care Questionnaire 9 were used to collect the data. After approval from Institutional Review Board, informed written consent was taken from the participants. Data was collected by using convenient sampling technique from faculty of basic science departments. SPSS 22 was utilized for analysis of the data. Results: In the current study a total number of 72 faculty members participated. Out of total 72 participants, 69.4% (50) were in the average EI range and 23.6% (17) had good EI with only 6.9% (5) falling in the poor EI range. The mean score for overall EI was higher in senior faculty as compared to junior members with a value of 189.7 but the difference was not statistically significant. Similarly, no significant difference was found among male and female participants regarding overall EI as well as its constructs. The sub-sections managing emotions, motivating one-self and social skills showed significant difference with a higher value in the senior faculty. Overall, EI was found to be inversely correlated with depression with a p value &lt; 0.01. Conclusion: The score of Emotional Intelligence is reasonably good in the faculty of basic science departments. Moreover, EI has been found to be inversely correlated with depression.

A Comprehensive Review of Vision-Based 3D Reconstruction Methods.

With the rapid development of 3D reconstruction, especially the emergence of algorithms such as NeRF and 3DGS, 3D reconstruction has become a popular research topic in recent years. 3D reconstruction technology provides crucial support for training extensive computer vision models and advancing the development of general artificial intelligence. With the development of deep learning and GPU technology, the demand for high-precision and high-efficiency 3D reconstruction information is increasing, especially in the fields of unmanned systems, human-computer interaction, virtual reality, and medicine. The rapid development of 3D reconstruction is becoming inevitable. This survey categorizes the various methods and technologies used in 3D reconstruction. It explores and classifies them based on three aspects: traditional static, dynamic, and machine learning. Furthermore, it compares and discusses these methods. At the end of the survey, which includes a detailed analysis of the trends and challenges in 3D reconstruction development, we aim to provide a comprehensive introduction for individuals who are currently engaged in or planning to conduct research on 3D reconstruction. Our goal is to help them gain a comprehensive understanding of the relevant knowledge related to 3D reconstruction.

The Application of Large Language Models Reducing Cultural Barriers in International Trade: A Perspective from Cultural Conflicts, Potential and Obstacles

Large Language Models (LLMs) are powerful Artificial General Intelligence (AGI) software that generate natural language texts on various topics and domains. They have great potential to reduce cultural barriers in international trade by facilitating machine translation and cross-cultural communication. However, they also face cultural conflicts, challenges and risks, such as cultural misreading, bias, and ethical issues. This paper provides a comprehensive analysis of the current state and future prospects of LLMs in international trade, and discusses the cultural differences, opportunities and obstacles that they encounter. It also proposes some possible solutions and directions for improving the cultural sensitivity and performance of LLMs, such as incorporating cultural knowledge, enhancing cultural awareness, and ensuring cultural diversity and inclusivity. To illustrate the practical implications of LLMs in international trade, this paper provides some examples of how LLMs have been used or could be used in various trade scenarios, such as ChatGPT,NewBing and Ernie Bot. This paper aims to offer some insights and suggestions for researchers, practitioners, and policymakers who are interested in or involved in the development and application of LLMs in international trade, and to demonstrate how LLMs can contribute to the advancement and innovation of international trade.

Talking existential risk into being: a Habermasian critical discourse perspective to AI hype

AbstractRecent developments in Artificial Intelligence (AI) have resulted in a hype around both opportunities and risks of these technologies. In this discussion, one argument in particular has gained increasing visibility and influence in various forums and positions of power, ranging from public to private sector organisations. It suggests that Artificial General Intelligence (AGI) that surpasses human intelligence is possible, if not inevitable, and which can—if not controlled—lead to human extinction (Existential Threat Argument, ETA). Using Jürgen Habermas’s theory of communicative action and the validity claims of truth, truthfulness and rightness therein, we inspect the validity of this argument and its following ethical and societal implications. Our analysis shows that the ETA is problematic in terms of scientific validity, truthfulness, as well as normative validity. This risks directing AI development towards a strategic game driven by economic interests of the few rather than ethical AI that is good for all.

Processing speed and executive attention as causes of intelligence.

Individual differences in processing speed and executive attention have both been proposed as explanations for individual differences in cognitive ability, particularly general and fluid intelligence (Engle et al., 1999; Kail & Salthouse, 1994). Both constructs have long intellectual histories in scientific psychology. This article attempts to describe the historical development of these constructs, particularly as they pertain to intelligence. It also aims to determine the degree to which speed and executive attention are theoretical competitors in explaining individual differences in intelligence. We suggest that attention is the more fundamental mechanism in explaining variation in human intelligence. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

What Large Language Models Know

Abstract The strengths and weaknesses of generative applications built on large language models are by now well-known. They excel at the production of discourse in a variety of genres and styles, from poetry to programs, as well as the combination of these into novel forms. They perform well at high-level question answering, dialogue, and reasoning tasks, suggesting the possession of general intelligence. However, they frequently produce formally correct but factually or logically wrong statements. This essay argues that such failures—so-called hallucinations—are not accidental glitches but are instead a by-product of the design of the transformer architecture on which large language models are built, given its foundation on the distributional hypothesis, a nonreferential approach to meaning. Even when outputs are correct, they do not meet the basic epistemic criterion of justified true belief, suggesting the need to revisit the long neglected relationship between language and reference.

Implementation in the Motek Caren system with virtual reality of an existing motor rehabilitation programme for people with Down’s syndrome in order to increase its effectiveness

IntroductionDown’s syndrome often requires specialized rehabilitation methods in order to effectively improve cognitive and motor functioning. The growing interest in technologies to support rehabilitation is opening up new and promising perspectives for improving the quality of life of people diagnosed with this syndrome. One of these technologies is the Computer Assisted Rehabilitation Environment (CAREN) system from Motek.ObjectivesThe aim of the planned research project is to explore the potential of using the CAREN system in the rehabilitation of people with Down’s syndrome.MethodsThe study included 10 participants with Down’s syndrome (men and women aged 18 to 50 years) without the presence of organic musculoskeletal disease or other somatic causes impairing motor performance. Before the training test, the participants were assessed by two psychological tests: 1) ACE III - Addenbrooke’s Cognitive Examination III Scale (ACE-III), which assesses attention and orientation, memory, verbal fluency, language and visuospatial functions and 2) the TONI 4 Non-Verbal Intelligence Test, which is a test used to measure general intelligence. The tests were carried out using the MOTEK CAREN device, which consists of a treadmill for motor training and a virtual reality screen on which different scenes are displayed for the participant to see during the test. Integrated motion capture technology was used to assess movement capabilities of the patients.. The screen displayed different types of applications in the form of virtual reality, in which the participant had to cope with various tasks accommodating different psychomotor skills, for example:crossing a virtual bridge, walking through a forest. The test took about 45 minutes per person. Two training sessions were conducted for each of the 10 patients with a one-month interval between them.ResultsThe Motek Caren System has proven to be a promising rehabilitation method for people with Down’s syndrome, compared to previous experience with different rehabilitation methods and existing research in the field.ConclusionsResults emphasize the necessity for further investigations and future research should involve more participants. The project has the potential to integrate modern technology with traditional forms of therapy to improve the quality of life and functioning of people affected by this syndrome.Disclosure of InterestNone Declared

The Ethics of (Generative) AI

Abstract The clamor for AI-based applications involving generative models for text and images has fueled wild speculation about the risks and opportunities for society and humanity at large. The potential “existential” threat as a precursor to artificial general intelligence has provoked wide-ranging debates in the public, politics, and the corporate world involving technologists and ethicists from a range of academic disciplines. This thinkpiece proposes a metaperspective to reflect critically and constructively upon the current state of the field of AI ethics, arguing that scholars working in the domain of ethics should focalize conceptual, substantive, and procedural issues as integral elements of an ethical assessment of given technologies and their applications. It suggests that the ethics of generative AI is conceptually still underexplored and overly propagating technological fixes to problems of all kinds (technosolutionism). Procedurally, it needs to be clarified who can, who ought to, and who ultimately will be considered and heard as an expert on AI ethics, a question of relevance for the trust in, and reliance on, AI.

The stability of cognitive abilities: A meta-analytic review of longitudinal studies.

Cognitive abilities, including general intelligence and domain-specific abilities such as fluid reasoning, comprehension knowledge, working memory capacity, and processing speed, are regarded as some of the most stable psychological traits, yet there exist no large-scale systematic efforts to document the specific patterns by which their rank-order stability changes over age and time interval, or how their stability differs across abilities, tests, and populations. Determining the conditions under which cognitive abilities exhibit high or low degrees of stability is critical not just to theory development but to applied contexts in which cognitive assessments guide decisions regarding treatment and intervention decisions with lasting consequences for individuals. In order to supplement this important area of research, we present a meta-analysis of longitudinal studies investigating the stability of cognitive abilities. The meta-analysis relied on data from 205 longitudinal studies that involved a total of 87,408 participants, resulting in 1,288 test-retest correlation coefficients among manifest variables. For an age of 20 years and a test-retest interval of 5 years, we found a mean rank-order stability of ρ = .76. The effect of mean sample age on stability was best described by a negative exponential function, with low stability in preschool children, rapid increases in stability in childhood, and consistently high stability from late adolescence to late adulthood. This same functional form continued to best describe age trends in stability after adjusting for test reliability. Stability declined with increasing test-retest interval. This decrease flattened out from an interval of approximately 5 years onward. According to the age and interval moderation models, minimum stability sufficient for individual-level diagnostic decisions (rtt = .80) can only be expected over the age of 7 and for short time intervals in children. In adults, stability levels meeting this criterion are obtained for over 5 years. (PsycInfo Database Record (c) 2024 APA, all rights reserved).