Mental Models Research Articles

Artificial Intelligence and the Limits of the Humanities

The complexity of cultures in the modern world is now beyond human comprehension. Cognitive sciences cast doubts on the traditional explanations based on mental models. The core subjects in humanities may lose their importance, but new, interdisciplinary branches of humanities emerge. Humanities have to adapt to the digital age. Instant access to information will be replaced by instant access to knowledge. Artificial intelligence is going to change humanities in a radical way, from art to political sciences and philosophy. Understanding the cognitive limitations of humans and the opportunities opened by the development of artificial intelligence and interdisciplinary research necessary to address global challenges is the key to the revitalization of humanities.

Plinko: Eliciting beliefs to build better models of statistical learning and mental model updating.

Prior beliefs are central to Bayesian accounts of cognition, but many of these accounts do not directly measure priors. More specifically, initial states of belief heavily influence how new information is assumed to be utilized when updating a particular model. Despite this, prior and posterior beliefs are either inferred from sequential participant actions or elicited through impoverished means. We had participants to play a version of the game 'Plinko', to first elicit individual participant priors in a theoretically agnostic manner. Subsequent learning and updating of participant beliefs was then directly measured. We show that participants hold various priors that cluster around prototypical probability distributions that in turn influence learning. In follow-up studies, we show that participant priors are stable over time and that the ability to update beliefs is influenced by a simple environmental manipulation (i.e., a short break). These data reveal the importance of directly measuring participant beliefs rather than assuming or inferring them as has been widely done in the literature to date. The Plinko game provides a flexible and fecund means for examining statistical learning and mental model updating.

Exploring perceptions of genetic risk and the transmission of substance use disorders

BackgroundSubstance use disorders (SUDs) have been consistently shown to exhibit moderate intergenerational continuity (1–3). While much research has examined genetic and social influences on addiction, less attention has been paid to clients’ and lay persons’ perceptions of genetic influences on the heritability of SUD (4) and implications for treatment.MethodsFor this qualitative study, twenty-six structured Working Model of the Child Interviews (WMCI) were conducted with mothers receiving inpatient SUD treatment. These interviews were thematically analyzed for themes related to maternal perceptions around intergenerational transmission of substance use behaviours.ResultsFindings show that over half of the mothers in this sample were preoccupied with their children’s risk factors for addictions. Among this group, 29% spontaneously expressed concerns about their children’s genetic risk for addiction, 54% shared worries about their children’s propensity for addiction without mentioning the word gene or genetic. Additionally, 37% had challenges in even discussing their children’s future when prompted. These concerns mapped onto internal working models of attachment in unexpected ways, with parents who were coded with balanced working models being more likely to discuss intergenerational risk factors and parents with disengaged working models displaying difficulties in discussing their child’s future.ConclusionThis research suggests that the dominant discourse around the brain-disease model of addictions, in its effort to reduce stigma and self-blame, may have unintended downstream consequences for parents’ mental models about their children’s risks for future addiction. Parents receiving SUD treatment, and the staff who deliver it, may benefit from psychoeducation about the intergenerational transmission of SUD as part of treatment.

A Children's Psychological and Mental Health Detection Model by Drawing Analysis based on Computer Vision and Deep Learning

A Children's Psychological and Mental Health Detection Model by Drawing Analysis based on Computer Vision and Deep Learning

Personalized Language Model Selection Through Gamified Elicitation of Contrastive Concept Preferences.

Language models are widely used for different Natural Language Processing tasks while suffering from a lack of personalization. Personalization can be achieved by, e.g., fine-tuning the model on training data that is created by the user (e.g., social media posts). Previous work shows that the acquisition of such data can be challenging. Instead of adapting the model's parameters, we thus suggest selecting a model that matches the user's mental model of different thematic concepts in language. In this article, we attempt to capture such individual language understanding of users. In this process, two challenges have to be considered. First, we need to counteract disengagement since the task of communicating one's language understanding typically encompasses repetitive and time-consuming actions. Second, we need to enable users to externalize their mental models in different contexts, considering that language use changes depending on the environment. In this article, we integrate methods of gamification into a visual analytics (VA) workflow to engage users in sharing their knowledge within various contexts. In particular, we contribute the design of a gameful VA playground called Concept Universe. During the four-phased game, the users build personalized concept descriptions by explaining given concept names through representative keywords. Based on their performance, the system reacts with constant visual, verbal, and auditory feedback. We evaluate the system in a user study with six participants, showing that users are engaged and provide more specific input when facing a virtual opponent. We use the generated concepts to make personalized language model suggestions.

Reasoning From Quantified Modal Premises.

Quantified modal inferences interest logicians, linguists, and computer scientists, but no previous psychological study of them appears to be in the literature. Here is an example of one: All those artists are businessmen. Paulo is possibly one of the artists. What follows? People tend to conclude: Paulo is possibly a businessman (Experiment 1). It seems plausible, and it follows from an intuitive mental model in which Paulo is one of a set of artists who are businessmen. Further deliberation can yield a model of an alternative possibility in which Paulo is not one of the artists, which confirms that the conclusion is only a possibility. The snag is that standard modal logics, which deal with possibilities, cannot yield a particular conclusion to any premises: Infinitely many follow validly (from any premises) but they do not include the present conclusion. Yet, further experiments corroborated a new mental model theory's predictions for various inferences (Experiment 2), for the occurrence of factual conclusions drawn from premises about possibilities (Experiment 3) and for inferences from premises of modal syllogisms (Experiment 4). The theory is therefore plausible, but we explore the feasibility of a cognitive theory based on modifications to modal logic.

Mental health care measures and innovations to cope with COVID-19: an integrative review.

This integrative review aims to identify the mental health care measures that were produced during the COVID-19 pandemic. This research was conducted on three databases (SciELO, PubMed, and LILACS) with the following descriptors in Portuguese, English, and Spanish: "SAÚDE MENTAL" or "SALUD MENTAL" or "MENTAL HEALTH" AND "COVID-19" from 2020 to 2021. In total, 3,451 articles were found, 43 of which were analyzed. Most measures were digital, stemmed from public institutions, focused on the local perspective, and were integrated with the public health care system. This study discusses the models of care in mental health based on measures to cope with the COVID-19 pandemic. It also discusses the Brazilian health care system, reiterating its resilience. In conclusion, digital measures occurred most often. This study suggest the evaluation of the accessibility of this mental health care model for most vulnerable groups. Finally, this research reinforces the importance of the Brazilian health care system for public health and access to information to cope with the COVID-19 pandemic.

Molded by the Ghost: How Physicians Use–and Cease Using–Predictive AI to Learn a Mental Model

Molded by the Ghost: How Physicians Use–and Cease Using–Predictive AI to Learn a Mental Model

A Population Health Approach: An Organizational Case Study of Mental Models Among Hospital Leaders

A Population Health Approach: An Organizational Case Study of Mental Models Among Hospital Leaders

News bylines and perceived AI authorship: Effects on source and message credibility

With emerging abilities to generate content, artificial intelligence (AI) poses a challenge to identifying authorship of news content. This study focuses on source and message credibility evaluation as AI becomes incorporated into journalistic practices. An experiment (N = 269) explored the effects of news bylines and AI authorship on readers’ perceptions. The findings showed that perceived AI contribution, rather than the labeling of the AI role, predicted readers’ perceptions of the source and the content. When readers thought AI contributed more to a news article, they indicated lower message credibility and source credibility perceptions. Humanness perceptions fully mediated the relationships between perceived AI contribution and perceived message credibility and source credibility. This study yielded theoretical implications for understanding readers’ mental model of machine sourceness and practical implications for newsrooms toward ethical AI in news automation and production.

Enhancing Healthcare Accountability for Administrators: Fostering Transparency for Patient Safety and Quality Enhancement.

Transparency in healthcare organizations is essential for creating a culture of patient-centered care where patients are respected, informed, and actively engaged in their health and well-being. Organizational transparency is a crucial element in healthcare, enhancing patient safety and quality improvement. Transparency involves open communication about healthcare organizations' performance, outcomes, and processes, leading to improved accountability, trust, and patient engagement. Transparent organizations prioritize patient-centered care, involving patients in decision-making and fostering shared mental models between healthcare providers and patients. Psychological safety is vital for organizational transparency. Patient safety reporting systems play a key role in transparency, allowing anonymous reporting of safety concerns and incidents. These systems facilitate early risk identification, continuous improvement, and compliance with regulatory requirements. Transparency in reporting encourages a culture of openness, learning from near misses, and addressing systemic issues and human errors. It aligns with ethical principles, potentially mitigating legal challenges. This review synthesizes key themes, including the importance of patient-centered care, the role of psychological safety in fostering transparency, and the effectiveness of patient safety reporting systems.

New tools for learning airway management

INTRODUCTION Game-based learning, also called edutainment, has been promoted as an alternative to the unidirectional, passive teaching of traditional medical education. Solving enigmas and problems through creativity and critical thinking, which is encapsulated in ‘escape rooms’, has been adapted to teach medicine as a way to enhance the mental models of proceeding. We considered an educational escape room as an activity to promote teaching and training in airway management, integrating knowledge, technical and nontechnical skills and collaborative teamwork during crisis situations. METHODS No published experience on this topic was found. Therefore, we created an educational escape room focused on airway management. We describe the steps undertaken from the design and development of the escape room process (as part of the curriculum of an international airway course) to the results of a survey completed by the participants at the end of the escape room process. RESULTS Satisfaction with the experience was rated at least 8 points (0 to 10 numerical rating scale) by 80% of the 147 course participants. Two thirds also rated the experience as at least 8 points (0 to 10 Likert scale) as being helpful in improving behaviour in real cases, and enhance organisational teamwork skills. CONCLUSION The airway escape room was feasible for training in airway management. Participants rated it as valuable to gain team competencies. The experience encourages further development and its possible use in other clinical settings.

EXTERNALIZATION OF TACIT KNOWLEDGE IN THE MENTAL MODEL OF A USER OF AN ARTIFICIAL INTELLIGENCE SYSTEM

The subject of the study is the processes of forming the user's mental model in artificial intelligence systems. The construction of such a model is associated with solving the problem of opacity and incomprehensibility of the decision-making process in such systems for end users. To solve this problem, the system user needs to receive an explanation of the obtained decision. The explanation should take into account the user's perception of the decision and the decision-making process, which is formalized within the user's mental model. The mental model considers the user's use of explicit and implicit knowledge, the latter of which usually lacks formal representation. The externalization of such knowledge ensures its transformation into a formal form. The aim of the work is to develop an approach to the externalization of implicit knowledge based on identifying patterns and causal dependencies for the decision-making process in an intelligent system when constructing the user's mental model. To achieve this goal, the following tasks are solved: developing a user's mental model of an artificial intelligence system that takes into account both explicit and implicit knowledge and developing an approach to the externalization of implicit knowledge of the user of the artificial intelligence system. A user's mental model of an artificial intelligence system that accounts for both explicit and implicit knowledge of the user is proposed. The model considers the connections between the user's explicit and implicit knowledge regarding the artificial intelligence system, the decision-making process, the method of using the decisions, and the general concept of the intelligent system. This creates conditions for the externalization of the user's implicit knowledge and the subsequent use of this knowledge in forming explanations regarding the decision-making process in the artificial intelligence system. An approach to the externalization of knowledge from the statistical and semantic layers of the user's mental model is proposed. In practical terms, the approach makes it possible to translate into explicit form the conditions and constraints regarding the formation and use of decisions in the artificial intelligence system.

Using Mental Modeling to Study the Management of Used Cooking Oil in Kuala Nerus

Recycling of used cooking oil is an effort by collecting, processing and reusing solid waste or materials that have been used for the purpose of environmental conservation. This study was conducted to identify the level of knowledge and awareness of used cooking oil management among the community in the Kuala Nerus district, Terengganu. The study involved 30 respondents in the community, namely traders, used cooking oil wholesalers, households, students and the government. The study used a mixed method, i.e. qualitative and quantitative research using fuzzy cognitive modelling including individual mental model modeling. The results of the study showed that the knowledge of cooking oil waste recycling among the respondents was still at a moderate level. The results of the study found that for the aspect of qualitative analysis, there were four themes that emerged, namely knowledge, awareness, attitude and culture. While descriptive analysis identifies the most dominant relationship strength is the theme of awareness. The recommendations in this study are necessary to improve the management of used cooking oil in Kuala Nerus through a comprehensive and integrated approach. This study proposes a legal approach, encourages the expansion of this study to a higher level and improves the provision of used cooking oil management infrastructure.

Systemic features of the formation of mental models behavior of people in socio-economic relations

The article substantiates the thesis that management of human behavior is the management of each person behavior. In turn, each person behavior depends on the individual mental model formed in his mind. It is shown that the existence of public institutions as rules of conduct and the enforcement of their execution is a systemic necessity and they are established on the basis of values and goals of those people who establish them. The article proposes a hierarchy of behavior attributes in an individual mental model that defines human behavior. It is shown that behavior style of each person is the result of a constant comparison of rules and goals of society development with individual goals. Man as a system strives for stability and self-preservation. The set of values formed in an individual mental model determines the parameters of sustainability and self-preservation in the form of a set of needs, a range of benefits and ways to obtain them. The successful development of the system is possible only with the joint directed development of each system element. It is shown that the systemic goal of socio-economic relations is to increase well-being of each person as a creator of goods and his household, as well as the comprehensive development of each person as a member of society. The systemic need for management consists in forming a set of values based on these goals, which means a set of needs, and changing the rules for the creation, distribution and exchange of goods corresponding to these goals. It is shown that only in this case the common goals underlying the formation of an individual mental model will coincide with the goals of human development as a system and ensure harmonious behavior of people. Otherwise, people use public conformity for self-preservation and stability, or nonconformism as a style of behavior aimed at realizing values in an individual mental model.

Usability Testing Via Simulation: Optimizing the NEAR4PEM Preintubation Checklist With a Human Factors Approach.

To inform development of a preintubation checklist for pediatric emergency departments via multicenter usability testing of a prototype checklist. This was a prospective, mixed methods study across 7 sites in the National Emergency Airway Registry for Pediatric Emergency Medicine (NEAR4PEM) collaborative. Pediatric emergency medicine attending physicians and senior fellows at each site were first oriented to a checklist prototype, including content previously identified using a modified Delphi approach. Each site used the checklist in 2 simulated cases: an "easy airway" and a "difficult airway" scenario. Facilitators recorded verbalization, completion, and timing of checklist items. After each simulation, participants completed an anonymous usability survey. Structured debriefings were used to gather additional feedback on checklist usability. Comments from the surveys and debriefing were qualitatively analyzed using a framework approach. Responses informed human factors-based optimization of the checklist. Fifty-five pediatric emergency medicine physicians/fellows (4-13 per site) participated. Participants found the prototype checklist to be helpful, easy to use, clear, and of appropriate length. During the simulations, 93% of checklist items were verbalized and more than 80% were completed. Median time to checklist completion was 6.2 minutes (interquartile range, 4.8-7.1) for the first scenario and 4.2 minutes (interquartile range, 2.7-5.8) for the second. Survey and debriefing data identified the following strengths: facilitating a shared mental model, cognitively offloading the team leader, and prompting contingency planning. Suggestions for checklist improvement included clarifying specific items, providing more detailed prompts, and allowing institution-specific customization. Integration of these data with human factors heuristic inspection resulted in a final checklist. Simulation-based, human factors usability testing of the National Emergency Airway Registry for Pediatric Emergency Medicine Preintubation Checklist allowed optimization prior to clinical implementation. Next steps involve integration into real-world settings utilizing rigorous implementation science strategies, with concurrent evaluation of the impact on patient outcomes and safety.

Assessing the Mental Model State of Emergency Responders in the Context of Radiological Dispersal Device (RDD) Incidents: A Multi-state Study.

Hazardous Materials (HAZMAT) Technicians' notions of mental model, or cognitive representations of their understanding and beliefs regarding Radiological Dispersal Devices (RDDs) incidents, have not been previously explored. A prior study developed an Expected Mental Model State (EMMS) framework specific to RDD incident response for HAZMAT technicians. The work herein presents the development of a derivative of this framework, the EMMS Diagnostic Matrix, to evaluate the actual Mental Model State (MMS) of HAZMAT technicians in the context of RDD incidents. The EMMS Diagnostic Matrix was administered via a survey and simulation activity in four U.S. states representing the Northeast, West, South, and Midwest regions. Data were collected and coded using grounded theory methodology. Reflexive thematic analysis was employed to identify themes across related areas where the notions of mental model for the HAZMAT technician responders' actual MMS differed from the EMMS. The analysis of the collected data revealed four significant themes representing incomplete notions of the mental model spanning various EMMS conceptual domains: Overestimation of Radiation Dose and Health Effects, indicating misunderstandings about the health impacts of radiation exposure, Acute Radiation Syndrome (ARS), particularly in the lower range of radiation doses; Overreliance on Responder Protection [personal protective equipment (PPE)/self-contained breathing apparatus (SCBA)], highlighting gaps in understanding radiation principles and radioactive material dispersal properties from a radiological dispersal device; Misunderstanding Radiation Detection and Units, signifying confusion about radiation units and differentiation between dose rate and accumulated dose; and Incomplete Understanding of Radiation Characteristics and Dispersal Properties, outlining a limited grasp of inhalation risks from radiation and the dispersal traits of a radiological dispersal device. The interconnectedness of these technical misunderstandings can guide the development of a strategic plan to evaluate and modify existing training, aiming at these specific themes to improve the efficiency of HAZMAT technicians in emergency situations and to identify areas for further research.

Structures and Processes of Grading Committees in Internal Medicine Clerkships: Results of a National Survey.

Clerkship grades are important in the residency selection process but can be influenced by individual bias and grading tendencies. Although clinical competency committees are standard in graduate medical education, in undergraduate medical education, they have not gained widespread traction. This study describes structures and processes of grading committees in internal medicine (IM) clerkships and strategies used to mitigate grading bias. From September to December 2022, the Clerkship Directors in Internal Medicine conducted its annual survey of IM core clerkship directors at 140 U.S. and U.S. territory-based medical schools. This study was based on 23 questions about grading committees in IM clerkships. The survey response rate was 80% (n = 112/140). Forty-seven respondents (42%) reported using grading committees in their IM clerkship (median committee size, 7; range, 3-20) (primarily clerkship leadership and faculty). Responsibilities included determining grades for all students (31 [66%]) and students at borderline of failing (30 [64%]), adjudicating on students with professionalism concerns (25 [53%]), and reconciling discordant clinical evaluations (24 [51%]). To mitigate deliberation bias, committees most frequently used multisource assessments (38 [81%]) and adoption of a shared mental model (36 [77%]). Approximately one-third of grading committees "rarely" discussed gender (14 [30%]) and race or ethnicity (15 [32%]), and 7 committees (15%) "never" discussed gender and race or ethnicity. Clerkship directors perceived developing a shared mental model (60 [92%]), promoting consistency (59 [91%]) and transparency (57 [88%]) in the process, mitigating assessment bias (58 [89%]), improving student satisfaction (54 [83%]), and sharing grading responsibility (44 [68%]) as potential benefits. This study found that grading committees in IM clerkships are not widely used and that existing committees vary in structure and process. These findings highlight an opportunity for medical schools to consider using grading committees to improve grade assignment and address grading inconsistencies.

Innovative outpatient treatment for veterans and service members and their family members.

In 2009, Massachusetts General Hospital and the Red Sox Foundation launched Home Base, a nonprofit dedicated to providing care to veterans, service members, and their loved ones who struggle with the invisible wounds of war free of charge. Significant needs exist for mental health services in each of these populations, and a need for innovative approaches to address shortcomings in existing treatment models. Three inventive components of our programming are highlighted herein: a Veteran Outreach Team, which helps to engage patients in care, programming, and services specifically for family members, and an intensive outpatient substance use treatment program. More than 4,000 patients, 3,031 veterans and service members, and 1,025 family members have engaged in treatment at Home Base. Patients were asked to complete post-treatment self-measures, including a satisfaction questionnaire via an electronic data collection system. The vast majority of individuals who engaged in our treatment model were satisfied with the care they received (>92%) and would refer their peers to the Home Base program (>75%). Data from 78 individuals who completed the dual diagnosis services demonstrated large effect sizes in reductions in alcohol use and comorbid mental health symptoms. These data suggest that novel components to the standard outpatient mental health model might provide substantive benefits for the patients served. While internal data is prone to a lack of generalizability, these additional offerings help ameliorate patients' expressed shortcomings with existing models; present literature that describes the benefits that these additions provide is also reviewed. The lessons learned and limitations are discussed.

The effects of self-questioning on additive word problem solving

This study underscores the critical role of mental representation and advanced reading comprehension in solving mathematical word problems. Proficient problem solvers create nuanced mental models of problem situations, while less successful ones rely on simpler translations. Advanced reading comprehension aids in navigating the complexity of word problems, including element sequencing and semantic relations. The purpose of this study was to assess the impact of a self-questioning strategy on four elementary students’ comprehension of additive problems. These students were trained to ask questions that helped uncover semantic relations in problems. Results showed significant improvement in their ability to interpret these relations and apply the self-questioning method to comprehend two-step additive problems.