Cognitive Model Research Articles

Stakeholder perceptions of mangrove ecosystem services across scales of conservation focus.

Conservation faces a chronic shortage of resources, including time, funding, mental capacity, and human capital. Efforts to make the expenditure of these resources more efficient should, therefore, support more equitable and effective conservation prioritization. To achieve this, it is necessary to ensure the integration of the knowledge and perceptions of local stakeholders into larger scale conservation decisions. We used fuzzy cognitive mental modeling to assess the perceptions of mangroves and the prioritization of ecosystem services across 3 groups of stakeholders: representatives from 3 coastal Fijian villages, the national office of an international nongovernmental organization (NGO), and the US office of that same NGO. We found different topologies and valuations among the resultant mental models, with the US NGO office having the most terms. However, when comparing models from local villages with the US NGO office, scale-dependent perceptions shifted, including the relative devaluation of locally important cultural valuations of mangroves. Despite these variations in perceptions, however, 3 key components of the mental models-women's livelihoods, men's livelihoods, and fisheries supplementation-all appeared as consistently important in multiple models, suggesting areas around which potential collaboration among stakeholders could be forged. By focusing on system-wide, rather than stakeholder-specific, optimal solutions within the system, new opportunities for collaboration may emerge. In doing so, these system-wide solutions may increase efficiency and collaboration. Moreover, we found that boundary-spanning organizations, such as the national-level conservation organizations, played a role in facilitating information transfer and mediating conservation goals in a culturally appropriate fashion. Finally, although the specific example used here is mangrove conservation, our methodologies and findings are broadly applicable across a variety of conservation scenarios.

COGNITIVE DIAGNOSTIC MODELING ON ASSESSMENT IN HEALTHCARE PROFESSIONS EDUCATION: A RAPID SCOPING REVIEW PROTOCOL

Background: The fast-rising supply of healthcare professional schools imposes improvement on assessment methodologies/strategies as to ensures achievement of sufficient healthcare professional competency, professional’s own health and wellbeing, and patient safety. Ascertain which learner has or has not reached sufficiency in a specific healthcare profession must be determined. Objective: The primary objective of this article is to present the protocol of a rapid scoping review to map the literature regarding the use of Cognitive Diagnostic Modeling (CDM) on assessment in healthcare professions education. Methods: This rapid scoping review protocol is registered on Open Science Framework (OSF) and followed Joanna Brigg Institute’s (JBI) updated manual for scoping reviews, Arksey and O’Malley’s framework and adhered to STructured apprOach to the Reporting In healthcare education of Evidence Synthesis (STORIES) and Best Evidence Medical Education (BEME) guidelines. A systematic and comprehensive search across MEDLINE/PubMed, Embase, Scopus, Web of Science, ERIC, LILACS, MedEdPublish and the grey literature will be conducted without date, language and study design restrictions. This review will include studies on assessment of undergraduate, graduate, and continuing medical and health professions’ education. Study selection and data extraction will be undertaken by two independent authors and synthesized into various strategies as to ensure representation of the state of the art on the use of CMD in assessment of healthcare professional education. Results: This rapid scoping review is anticipated to map CMD applications in healthcare professional education, including for admissions, progress test, assessment, and clinical reasoning. Conclusion: The findings of this rapid scoping review protocol will contribute to ensure relevance and understanding of and gap identification on the use of CDM in assessment of healthcare professions education. Futhermore, they might help academic staff, administration, and researchers in healthcare education.

Understanding mental health in breast cancer from screening to Survivorship: an integrative phasic Model and tool

ABSTRACT Integrative models of mental illness and health in psycho-oncology are aimed at all types of cancer, although the patients’ experiences and issues may vary. This review summarizes the different theories and models of mental illness and health pertaining to the breast cancer experience and proposes an integrative phasic model applicable to the breast cancer trajectory. Five databases were searched for studies related to breast cancer mental health and illness theories and models. The PRISMA checklist form was used to extract the essential information from the included studies. Eleven theories and models on the experience of breast cancer were found. The integrative model based on these theories and models illustrates that the breast cancer experience is conceptualized as a trajectory with seven landmark ‘events’, each associated with a pathogenic ‘challenge’ leading to six possible ‘symptoms’, 1) psychological distress with anxious features, 2) psychological distress with depressive features, 3) non-specific distress 4) psychological distress with trauma-related features 5) low health-related quality of life, and 6) fear of recurrence. The Breast Cancer Psychological Integrative Phasic Model is supported by a simple clinical tool (BreastCancerPsych – Integrative Clinical Tool) that serves as a valuable resource throughout the care trajectory. These integrative phasic model and clinical tool are designed to help mental health clinicians formulate treatments that are tailored to the needs of their patients, especially for trajectories that are not marked by resilience.

Moral Association Graph: A Cognitive Model for Automated Moral Inference.

Automated moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach typically relies on language models to infer moral relevance or moral properties of a concept. This approach demands complex parameterization and costly computation, and it tends to disconnect with existing psychological accounts of moralization. We present a simple cognitive model for moral inference, Moral Association Graph (MAG), inspired by psychological work on moralization. Our model builds on word association network for inferring moral relevance and draws on rich psychological data. We demonstrate that MAG performs competitively to state-of-the-art language models when evaluated against a comprehensive set of data for automated inference of moral norms and moral judgment of concepts, and in-context moral inference. We also show that our model yields interpretable outputs and is applicable to informing short-term moralchange.

Neuropsychology of social cognition: culture, display rules, and emotional expressivity

ABSTRACT Introduction We investigated the roles of group ethnicity and display rules of emotions in the neuropsychology of social cognition in Asian American and White participants recruited from a majority-minority college campus. Method 128 participants (mean age = 24.9 years) completed: 1) Advanced Clinical Solutions-Social Perception (ACS-SP), which includes separate measures of affect naming of facial expressions and emotional prosody interpretation of audio statements; 2) Display Rule Assessment Inventory (DRAI), a self-report measure of emotional expressivity across four settings (family, close friends, colleagues, and strangers) and in two distinct domains (should/actual) that asks participants what they believe people should do (social value) and what they would actually do (behavioral self-report). Results ACS-SP revealed evidence of cultural bias, as reflected by group ethnicity differences, for recognition of emotional prosody but not emotional facial expressions for Asian American versus White participants. The DRAI showed significant cultural differences only for family relationships with White participants endorsing stronger belief in the social value of expressing negative emotions of sadness, aversion, and fear. These AC-SP and DRAI group differences remained significant when covarying for spoken English language, as measured by an oral word reading test. Hierarchical regression results indicated that group ethnicity and family display rules each made specific and significant contributions to neuropsychological performance but did so in very different and distinct ways. Group ethnicity exerted its greatest effect on prosody interpretation whereas family display rules had its most pronounced influence on affect naming. Conclusions The current results may help inform and advance culturally responsive neuropsychological models of social cognition.

Implicit to explicit: A Framework for Supporting Blended Design Education with Microlearning

Design is an iterative process involving cycles of divergent and convergent thinking. To navigate these cycles effectively, designers need a range of competencies. These include information gathering, sense-making, imagination, ideation, shape-giving, iterative reflection, critical evaluation, collaboration, and discipline-specific knowledge. To develop these competencies, design education typically occurs in a studio environment that follows a learning-by-doing approach, simulating industry practices. However, the tacit knowledge—unspoken insights and intuitions—that informs the application of domain knowledge is often not visible, making it difficult for students to connect theory with practice and potentially hindering their learning. The cognitive apprenticeship model is a pedagogical approach that enhances learning-by-doing by integrating theory and practice throughout the design process, making tacit knowledge explicit and accessible. Within the context of blended learning, where face-to-face classes are complemented by technology-enabled learning, microlearning emerges as an innovative teaching and learning approach that delivers activities in structured, bite-sized pieces. This method is designed to minimise cognitive load and to help students grasp complex implicit concepts. In this paper we explore how microlearning, an innovative teaching and learning approach, might be integrated into learning by doing approaches within blended learning settings in the design studio to make tacit knowledge explicit. The paper is the first part of a larger study exploring how microlearning activities might support learning-by-doing within blended learning environments during the various phases of the design process. An integrative review of literature on the design process and related design competencies, cognitive apprenticeship and microlearning, theoretically informed the development of a conceptual framework outlining the dynamics between learning-by-doing and microlearning activities to foster connections between theory and practice. The framework will be used in subsequent research to inform the design and trialling of microlearning activities to support learning-by-doing in practical design modules. This research contributes to existing understanding of educational approaches that support learning-by-doing in design education and lays the foundation for further research to inform the design of appropriate and meaningful microlearning activities.

Digital Psychology: Introducing a Conceptual Impact Model and the Future of Work

AbstractThe present review is the first of its kind to form a conceptual discussion about a novel field, here referred to as digital psychology. The result is a conceptual impact model of digital psychology (in short: CIMDP) highlighting the bidirectional relationship between human psychology (consisting of affect, cognition, and behavior) and digital transformation (driven by datafication, algorithmization, and platformization). The findings of the CIMDP are applied to a relevant field in economy and business development, namely, to the digital future of work, which appears to be mediated by organizational behavior and governed by managerial decisions. The resulting model may be used to provide orientation in a new research domain and to guide future studies in psychology, cognitive science, digital transformation, human–computer interactions, organizational behavior, and business management.

Persistent negative self-referent thinking in the context of depression: examining the role of temperament and emotion regulation.

Cognitive models of depression posit that persistent negative self-referent thinking (PNSRT) is an important vulnerability factor for depressive symptoms. The mechanisms involved are still understudied, especially in adolescence. PNSRT has been assessed by a behavioural decision-making task, namely the emotional reversal learning task (ERLT). Within the ERLT, PNSRT is operationalised as the learning rate for negative self-reference. The first aim of the current study is to examine the association between PNSRT and depressive symptoms at baseline and follow-up. Second, the current study investigated associations of PNSRT with temperamental and emotion regulation variables. We found no significant effect between PNSRT and baseline depressive symptoms, although the small effect size pointed in the expected direction. No significant prospective effect was found. Additionally, adolescents with greater capacity for response inhibition and better attentional control exhibited less PNSRT. No other significant associations were found with other temperamental dimensions or emotion regulation variables. In conclusion, while the small effect size of the cross-sectional association between PNSRT and depressive symptoms points in the expected direction, no significant evidence was found that PNSRT acts as either a concomitant or precursor to depressive symptomatology. However, the current study did find a relation between low effortful control and PNSRT.

Structural Coupling System for Cognitive Modeling in Immersive VR Assessment Tasks

Unilateral spatial neglect (USN) is a disorder characterized by the inability to attend to the space opposite the cerebral hemisphere lesion, significantly hindering daily activities. Due to the complex neural circuitry of the brain, understanding the mechanisms of USN has proven challenging. In clinical settings, the Behavioral Inattention Test (BIT), a paper-based examination, is commonly used to assess USN. However, improved scores on this test do not necessarily guarantee functional improvement, as it solely evaluates performance in a two-dimensional space. To address this limitation, various approaches utilizing information and communication technology (ICT) and measurement devices in rehabilitation engineering have been proposed. However, related studies have focused on analyzing motor responses to specific sensory stimuli, and the assessment measures often fail to capture a patient’s symptoms in dynamic environments. Therefore, this study proposes a methodology for modeling human spatial cognition. This cognitive architecture utilizes a structural coupling system that integrates parameters from multiple computational intelligence subsystems. In this study, we constructed a simulation environment capable of replicating the movements of patients with USN using empirical data collected from actual experiments. Furthermore, in this simulation environment, we developed patient agents that incorporated the proposed cognitive architecture. The experimental results suggest that hypothesis testing concerning attention mechanisms can be applied through the performance of patient agents within the simulation environment.

Worry and rumination elicit similar neural representations: neuroimaging evidence for repetitive negative thinking.

Repetitive negative thinking (RNT) captures shared cognitive and emotional features of content-specific cognition, including future-focused worry and past-focused rumination. The degree to which these distinct but related processes recruit overlapping neural structures is undetermined, because most neuroscientific studies only examine worry or rumination in isolation. To address this, we developed a paradigm to elicit idiographic worries and ruminations during an fMRI scan in 39 young adults with a range of trait RNT scores. We measured concurrent emotion ratings and heart rate as a physiological metric of arousal. Multivariate representational similarity analysis revealed that regions distributed across default mode, salience, and frontoparietal control networks encode worry and rumination similarly. Moreover, heart rate did not differ between worry and rumination. Capturing the shared neural features between worry and rumination throughout networks supporting self-referential processing, memory, salience detection, and cognitive control provides novel empirical evidence to bolster cognitive and clinical models of RNT.

Facets of security and safety problems and paradigms for smart aerial mobility and intelligent logistics

AbstractThe use of unmanned aerial vehicles (UAVs) for smart and speedy logistics is still relatively nascent compared to traditional delivery methods. However, it is witnessing sporadic and steady growth due to booming demands, technological advancement, and regulatory support. The intelligence and integrity of UAV systems depend largely on the underlying cognitive and cybersecurity models, which serve as both eyes and brains to perceive and respond to the myriad of scenarios around them. Smart mobility and intelligent logistic ecosystems (SMiLE) are complex and advanced technological networks which are exposed to several issues. The incorporation of UAVs for priority logistics, thereby extending the coverage and capacity of SMiLE, further heightens these vulnerabilities and questions its security, safety, and sustainability. This review scrutinizes the significant security disruptions, smartness dynamics, and sundry developments for the sustainable deployment of UAVs as an aerial logistics‐based vehicle. Using the PRISMA‐SPIDER methodology, 157 articles were selected for quantitative analysis and 20 review articles for qualitative evaluation. Security and safety issues in UAVs cut across all the layers of logistics operations: components, communication, network architecture, navigation, supply chain etc. Expanding the capacity of SMiLE using UAV demands an intentional and incremental convergence‐based integration of an agile explainable artificial framework for reliable and safety‐conscious smart mobility, a scalable and tamperproof blockchain for multi‐factor authentication, and a zero trust cybersecurity paradigm for inclusive enterprise‐based authorization.

Emotional Risk Factors, Rumination, and Self-Criticism in Relation to Suicidal Ideation Among Chinese Depressive Outpatients.

Previous studies indicated that individuals with major depressive disorder (MDD) are at high risk of suicide, making the identification of risk factors in suicidal depressive outpatients essential for developing effective prevention and treatment strategies. This study aims to (1) identify emotional risk factors and (2) examine the relationship between cognitive markers-including rumination and self-criticism-and suicidal ideation among depressive outpatients. A total of 165 Chinese clinical outpatients with depression were recruited from local hospitals in Hong Kong. In our sample, 68% of patients with moderate depression and 87.5% of patients with severe depression reported experiencing suicidal thoughts. The results from the logistic regression revealed a significant interaction between rumination and self-critical thoughts in relation to suicidal ideation. Specifically, the ruminative patients with self-critical thoughts were more likely to have suicidal thoughts than those without self-critical thoughts. These findings align with the cognitive model of suicide, suggesting that maladaptive information processing and negative cognitive content are associated with an increased risk of suicide. The current findings have clinical implications for the future development of more specific and accurate mental health assessment, preventive programs, and psychotherapies for depressive outpatients.

Development, Validation, and Visualization of a Web-Based Nomogram to Predict the Risk of Psychological Distress in Patients Undergoing Chemotherapy After Breast Cancer Surgery

Background Psychological distress of postoperative chemotherapy patients with breast cancer is significant and has a serious impact on their quality of survival. Risk prediction models can efficiently assess patients’ psychological distress and risk factors. Objectives To investigate the factors influencing psychological distress in postoperative chemotherapy patients with breast cancer and construct a nomogram model to predict the occurrence of psychological distress in patients. Methods Two hundred forty-seven women in treatment for breast cancer who were postoperative and receiving chemotherapy were recruited. Participants completed a distress management screening measure, a numerical rating scale, the Pittsburgh Sleep Quality Index, and demographic and clinical items. Results Experiencing significant psychological distress was reported by 65.6% of participants. The psychological distress risk prediction model included 5 variables: financial problems, appearance/shape, distant metastases, the Numerical Rating Scale Pain score, and fatigue. A web calculator was designed based on the model (https://77nomogram.shinyapps.io/dynnomapp/). Conclusions This study found that financial and appearance/shape problems, distant metastases, pain scores, and fatigue were predictors of greater psychological distress in women undergoing chemotherapy after breast cancer surgery. The model constructed in this study has good predictive efficacy. Implications for practice This web-based nomogram model can help healthcare professionals quickly assess the likelihood of psychological distress in patients and screen for risk factors for psychological distress.

The Concept of Cognitive Space in the Context of Cognitive Securitology

Introduction. The article discusses the conceptual foundations of a new field of knowledge – cognitive securitology. The relevance of the study is due to the fact that the main means of cognitive warfare are modern digital technologies, while the object of influence of technical systems is mental systems, therefore there is a need to combine technical and humanitarian conceptual apparatus. The purpose of the article is to clarify the concept of “cognitive space” and distinguish between the concepts of information and cognitive spaces. Methodology and sources. One of the basic concepts of cognitive security is the concept of cognitive space, which has already been developed in linguistics, but due to the interdisciplinary nature of cognitive securitology needs to be clarified. Placing the category of cognitive space in the field of linguistic analysis narrows its content and does not make it possible to determine its semantic boundaries. The novelty of the analysis of the category “cognitive space” lies in the fact that the conceptual analysis of the category of cognitive space is based on the concept of self-organizing systems and the structural-functional approach. The concept of autopoiesis assumes that all elements and structures of the system, including cognitive ones, arise in order to ensure self-preservation, and the structural-functional approach allows us to determine the content and functions of the object. Results and discussion. Information space and cognitive space are intersecting but not coinciding fields, differing in their domains, but having one common task – ensuring the stability of the social system. Conclusion. The modern era is characterized by a global confrontation between civilizational systems and the transition of the confrontation into the phase of proxy wars, in which the main role is given to cognitive-psychological influence. Cognitive-psychological influence on the enemy is not only carried out at the preventive and preemptive stages of confrontation, but also often replaces other forms of war. Cognitive-psychological influence becomes possible and is carried out through the destruction of the cognitive space in which meanings and ideals that are specific to the social system function, which form goals and models of activity.

Exploring Interrelationships Among L2 Writing Subskills: Insights from Cognitive Diagnostic Models

ABSTRACT The purpose of this study was to explore the nature of interactions among second/foreign language (L2) writing subskills. Two types of relationships were investigated: subskill–item and subskill–subskill relationships. To achieve the first purpose, using writing data obtained from the writing essays of 500 English as a foreign language (EFL) students, the fit of the G-DINA model as general cognitive diagnostic model (CDM) was compared against a Wald-selected model (i.e., a model in which different CDMs such as DINA, DINO, A-CDM, LLM, and RRUM were selected for each item). To study cross-subskill impacts, two-way interactions between the subskills were estimated, and lens and scatter plots were checked. Subskill–item relationships showed that the subskills of L2 writing contribute additively and independently to the probability of successful performance. Furthermore, the loglinear analysis revealed that some of the subskills draw information from the other subskills. The plots showed that neglecting inter-subskill relationships would lead to misclassification of students.

Enhancing performance factor analysis through skill profile and item similarity integration via an attention mechanism of artificial intelligence

IntroductionFrequent formative assessment is essential for accurately evaluating student learning, enhancing engagement, and providing personalized feedback. In STEM education, understanding the relationship between skills that students have internalized (mastered) and those they are developing (emergent) is crucial. Traditional models, including item response and cognitive diagnosis models, primarily focus on emergent skills, often overlooking internalized skills. Moreover, new tools like large language models lack a complete approach for tracking knowledge and capturing complex skill relationships.MethodsThis study incorporates artificial intelligence, specifically attention mechanisms, into educational assessment to evaluate both emergent and internalized skills. We propose a modified version of Performance Factor Analysis (PFA), which assesses student abilities by analyzing past responses and comparing them with peer performance on the same items, using parameters from a sigmoid function. This model leverages attention mechanisms to capture item order-based similarity and decay principles, providing a nuanced view of student skill profiles.ResultsThe Modified Performance Factor Analysis model significantly improved discriminative power, accuracy, precision, recall, and F1 scores across various skill areas compared to traditional PFA models.DiscussionThese results indicate that the Modified Performance Factor Analysis model allows for a more accurate and comprehensive evaluation of student performance, effectively identifying both emergent and internalized skills. By integrating AI into assessment, educators gain deeper insights, enabling them to refine teaching strategies and better support students' mastery of both types of skills.

From practice to theory: characterizing the gap in surgical simulation

PurposeSimulation curricula continue to struggle with adequately preparing trainees for the operating room. One reason for this phenomenon may be the lack of application and enactment of learning and instructional theories into simulation curricular design and practice. Few educators have taken a reflective approach to understand how surgical simulation succeeds and fails to incorporate best practices for learning based on theory. As such, this study aims to examine simulation sessions to identify gaps in practice by nesting two key frameworks from general education into surgical simulation: learning integration and the cognitive apprenticeship model.MethodsWe conducted an observational qualitative study in which we recorded simulation sessions with fifteen trainees and surgeons and deductively applied components of the above frameworks to transcripts. Subsequently, we analyzed gaps in the transcripts with regard to the application of these frameworks as theoretical concepts informing the analysis and interpretation.ResultsWe organized results around the four fundamental tenets of learning integration, with principles of the cognitive apprenticeship model explored to provide further units of analysis. In doing so, we identified that simulation instructors adequately modeled, coached, and scaffolded to enable early phases of learning integration. However, instructors less aptly enabled reflection and self-guided exploration, which are critical components of learning integration.ConclusionsWe found areas in which instruction diverged from ideal standards as informed by our theoretical frameworks, thus highlighting the importance of regular simulation review to ensure that well-designed and intentioned simulation curricula continue to reflect the best educational principles when enacted in practice.

The Impact of Employee Benefits on Job Satisfaction in the Sales Industry: An Analytical Study Using Maslow's Hierarchy of Needs and Herzberg's Two-Factor Theory

Abstract: This study aims to explore the relationship between employee benefits and job satisfaction in the sales industry and analyze how improving employee benefit programs can affect employee job satisfaction. Through literature review and in-depth interviews with employees of sales companies of different sizes, this paper analyzed various types of employee benefits and their potential impact on employee satisfaction. The study utilized psychological and social theoretical models, such as Maslow's Hierarchy of Needs and Herzberg's Two-Factor Theory, to construct an analytical framework. The research findings indicate that certain key elements in employee benefit programs, such as health insurance, training and development opportunities, and work-life balance policies, have a significant effect on improving sales personnel's job satisfaction. Furthermore, through a case study of Starbucks Corporation, this paper further verified that implementing comprehensive and competitive employee welfare strategies in a sales environment can significantly enhance employee loyalty and reduce turnover rates. The study provides specific management recommendations for enterprises in the sales industry, emphasizing the importance of establishing or improving employee benefit plans to enhance employee satisfaction and business performance.

Formiranje novih pravaca historiografije: Aktuelna konceptualizacija modernosti

The article deals with the modern problems of archival science, historiography, source studies in the post-Soviet space of science of the Russian Federation, summarizes the results of the science of the past century, determines the prospects of future relevant concept ology of modernity. The author examines the state of archival affairs in the Republic of Kalmykia on the problems of regional history, shows the main characteristics of modern historical science in the region, legitimate interests in the development of archeography. For the first time in the history of the state, a systemic failure of archival science as a form of manifestation of record keeping, the need to rebuild the archival system is shown, the urgency of the problem of the unified state archival fund (EGAF) is indicated: its formation, formation, preservation, responsibility for its preservation. One of the features of archival funds is their classification, the modern correct structure of preservation and their origin allows us to determine the place and their role in the history of the archival service, to show their genres and fields of knowledge. The author emphasizes the importance and world practice of modern archival science in the field of cognitive space, opens up the possibility of analyzing new facts in the history of Russian statehood, concluding that the actualization translation concluding that the actualization of modern conceptology makes it possible to form new directions in the science of historical knowledge of the past. With the historical development, the problems of knowledge aimed at its humanization are increasingly being considered.

Human-like dissociations between confidence and accuracy in convolutional neural networks.

Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect, derived from cognitive modeling, is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice. However, an alternative explanation is the signal-and-variance-increase hypothesis, according to which these dissociations arise from changes in the separation and variance of perceptual representations. Because artificial neural networks lack built-in confidence heuristics, they can serve as a test for the necessity of confidence heuristics in explaining confidence-accuracy dissociations. Therefore, we tested whether confidence-accuracy dissociations induced by stimulus energy manipulations emerge naturally in convolutional neural networks (CNNs). We found that, across three different energy manipulations, CNNs produced confidence-accuracy dissociations similar to those found in humans. This effect was present for a range of CNN architectures from shallow 4-layer networks to very deep ones, such as VGG-19 and ResNet-50 pretrained on ImageNet. Further, we traced back the reason for the confidence-accuracy dissociations in all CNNs to the same signal-and-variance increase that has been proposed for humans: higher stimulus energy increased the separation and variance of evidence distributions in the CNNs' output layer leading to higher confidence even for matched accuracy. These findings cast doubt on the necessity of the positive evidence heuristic to explain human confidence and establish CNNs as promising models for testing cognitive theories of human behavior.