Action Selection in Everyday Activities: The Opportunistic Planning Model.

While action selection strategies in well-defined domains have received considerable attention, little is yet known about how people choose what to do next in ill-defined tasks. In this contribution, we shed light on this issue by considering everyday tasks, which in many cases have a multitude of possible solutions (e.g., it does not matter in which order the items are brought to the table when setting a table) and are thus categorized as ill-defined problems. Even if there are no hard constraints on the ordering of subtasks in everyday activities, our research shows that people exhibit specific preferences. We propose that these preferences arise from bounded rationality, that is, people only have limited knowledge and processing power available, which results in a preference to minimize the overall physical and cognitive effort. In the context of everyday activities, this can be achieved by (a) taking properties of the spatial environment into account to use them to one's advantage, and (b) employing a stepwise-optimal action selection strategy. We present the Opportunistic Planning Model as an explanatory cognitive model, which instantiates these assumptions, and show that the model is able to generalize to new everyday tasks, outperforming machine learning models such as neural networks during generalization.

The absorption-addiction model of celebrity worship: in search of a broader theoretical foundation.

BACKGROUND: A large body of evidence suggests that some people have a strong, obsessive attachment to a favorite celebrity. The absorption-addiction model attempts to account for this extreme attachment, sometimes labeled "celebrity worship." According to the model, a small portion of celebrity admirers ("celebrity worshipers") become absorbed in the personal lives of celebrities to compensate for perceived personal or social deficiencies. The purpose of this study is to examine how the absorption-addiction model relates to broader psychological theories that include non-celebrity contexts. Specifically, we examine how the absorption-addiction model relates to three theories: empty-self theory, extremism theory, and the dualistic model of passion. METHODS: Participants (N = 399; 77.94% women, Mage = 19.91 years, SD = 3.24) completed an online questionnaire measuring attraction to favorite celebrities. Constructs representing the three broader theories were compared to a measure of attraction to one's favorite celebrity. RESULTS: Sense of emptiness, obsessive passion, and extremism were positively associated with celebrity attraction. The strongest association was found with extremism, though the effect was moderate. CONCLUSIONS: These findings suggest that extremism theory is the best fit of the three broader theories explaining celebrity worship, although its contribution to understanding celebrity worship is modest.

Protocol for an interview-based method for mapping mental models using causal-loop diagramming and realist interviewing.

Causal-loop diagramming, a method from system dynamics, is increasingly used in evaluation to describe individuals' understanding of how policies or programs do or could work ("mental models"). The use of qualitative interviews to inform model development is common, but guidance for how to design and conduct these interviews to elicit causal information in participant mental models is scant. A key strength of semi-structured qualitative interviews is that they let participants speak freely; they are not, however, designed to elicit causal information. Moreover, much of human communication about mental models-particularly larger causal structures such as feedback loops-is implicit. In qualitative research, part of the skill and art of effective interviewing and analysis involves listening for information that is expressed implicitly. Similarly, a skilled facilitator can recognize and inquire about implied causal structures, as is commonly done in group model building. To standardize and make accessible these approaches, we have formalized a protocol for designing and conducting semi-structured interviews tailored to eliciting mental models using causal-loop diagramming. We build on qualitative research methods, system dynamics, and realist interviewing. This novel, integrative method is designed to increase transparency and rigor in the use of interviews for system dynamics and has a variety of potential applications.

The Neuman Systems Model: A Framework for Aggression and Violence Prevention.

Aggression and violence influence nurse-client relationships and the quality of care provided, and just as important, they also influence the nurses' physical and emotional well-being. The Neuman systems model is utilized to define and understand factors that contribute to aggressive and violent behavior and for the purposes of providing a systematic approach to the prevention and management of stressors leading to aggression and violence.

Joint analysis of interaction and psychological characteristics in english teaching based on multimodal integration.

The intersection of psychology and English teaching is profound, as the application of psychological principles not only guides specific English instruction but also elevates the overall quality of teaching. This paper takes a multimodal approach, incorporating image, acoustics, and text information, to construct a joint analysis model for English teaching interaction and psychological characteristics. The novel addition of an attention mechanism in the multimodal fusion process enables the development of an English teaching psychological characteristics recognition model. The initial step involves balancing the proportions of each emotion, followed by achieving multimodal alignment. In the cross-modal stage, the interaction of image, acoustics, and text is facilitated through a cross-modal attention mechanism. The utilization of a multi-attention mechanism not only enhances the network's representation capabilities but also streamlines the complexity of the model. Empirical results demonstrate the model's proficiency in accurately identifying five psychological characteristics. The proposed method achieves a classification accuracy of 90.40% for psychological features, with a commendable accuracy of 78.47% in multimodal classification. Furthermore, the incorporation of the attention mechanism in feature fusion contributes to an improved fusion effect.

When do stereotypes undermine indirect reciprocity?

Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.

Super-additive cooperation.

Repeated interactions provide an evolutionary explanation for one-shot human cooperation that is counterintuitive but orthodox1-3. Intergroup competition4-7 provides an explanation that is intuitive but heterodox. Here, using models and a behavioural experiment, we show that neither mechanism reliably supports cooperation. Ambiguous reciprocity, a class of strategies that is generally ignored in models of reciprocal altruism, undermines cooperation under repeated interactions. This finding challenges repeated interactions as an evolutionary explanation for cooperation in general, which further challenges the claim that repeated interactions in the past can explain one-shot cooperation in the present. Intergroup competitions also do not reliably support cooperation because groups quickly become extremely similar, which limits scope for group selection. Moreover, even if groups vary, group competitions may generate little group selection for multiple reasons. Cooperative groups, for example, may tend to compete against each other8. Whereas repeated interactions and group competitions do not support cooperation by themselves, combining them triggers powerful synergies because group competitions constrain the corrosive effect of ambiguous reciprocity. Evolved strategies often consist of cooperative reciprocity with ingroup partners and uncooperative reciprocity with outgroup partners. Results from a behavioural experiment in Papua New Guinea fit exactly this pattern. They thus suggest neither an evolutionary history of repeated interactions without group competition nor a history of group competition without repeated interactions. Instead, our results suggest social motives that evolved under the joint influence of both mechanisms.

Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public.

BACKGROUND: Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI's role in evaluating prognosis and long-term outcomes in depressive disorders, offering insights into how AI large language models (LLMs) compare with human perspectives. METHODS: Using case vignettes, we conducted a comparative analysis involving different LLMs (ChatGPT-3.5, ChatGPT-4, Claude and Bard), mental health professionals (general practitioners, psychiatrists, clinical psychologists and mental health nurses), and the general public that reported previously. We evaluate the LLMs ability to generate prognosis, anticipated outcomes with and without professional intervention, and envisioned long-term positive and negative consequences for individuals with depression. RESULTS: In most of the examined cases, the four LLMs consistently identified depression as the primary diagnosis and recommended a combined treatment of psychotherapy and antidepressant medication. ChatGPT-3.5 exhibited a significantly pessimistic prognosis distinct from other LLMs, professionals and the public. ChatGPT-4, Claude and Bard aligned closely with mental health professionals and the general public perspectives, all of whom anticipated no improvement or worsening without professional help. Regarding long-term outcomes, ChatGPT 3.5, Claude and Bard consistently projected significantly fewer negative long-term consequences of treatment than ChatGPT-4. CONCLUSIONS: This study underscores the potential of AI to complement the expertise of mental health professionals and promote a collaborative paradigm in mental healthcare. The observation that three of the four LLMs closely mirrored the anticipations of mental health experts in scenarios involving treatment underscores the technology's prospective value in offering professional clinical forecasts. The pessimistic outlook presented by ChatGPT 3.5 is concerning, as it could potentially diminish patients' drive to initiate or continue depression therapy. In summary, although LLMs show potential in enhancing healthcare services, their utilisation requires thorough verification and a seamless integration with human judgement and skills.

Between Meanings and Senses-Making Spaces: Agency and Ownership Emergence Formalization from Cultural-Historical Activity Theory Position, for an AI-Friendly Model.

Sense of agency and sense of ownership are considered crucial in autonomous systems. However, drawbacks still exist regarding how to represent their causal origin and internal structure, either in formalized psychological models or in artificial systems. This paper considers that these drawbacks are based on the ontological and epistemological duality in mainstream psychology and AI. By shedding light on the cultural-historical activity theory (CHAT) and dialectical logic, and by building on and extending related work, this paper attempts to investigate how the noted duality affects investigating the self and "I". And by differentiating between the space of meanings and the sense-making space, the paper introduces CHAT's position of the causal emergence of agency and ownership by stressing the twofold transition theory being central to CHAT. Furthermore, a qualitative formalized model is introduced to represent the emergence of agency and ownership through the emergence of the contradictions-based meaning with potential employment in AI.

Quantum concepts in Psychology: Exploring the interplay of physics and the human psyche.

This paper delves into the innovative intersection of quantum mechanics and psychology, examining the potential of quantum principles to provide fresh insights into human emotions, cognition, and consciousness. Drawing parallels between quantum phenomena such as superposition, entanglement, tunneling, decoherence and their psychological counterparts, we present a quantum-psychological model that reimagines emotional states, cognitive breakthroughs, interpersonal relationships, and the nature of consciousness. The study uses computational models and simulations to explore this interdisciplinary fusion's implications and applications, highlighting its potential benefits and inherent challenges. While quantum concepts offer a rich metaphorical lens to view the intricacies of human experience, it is essential to approach this nascent framework with enthusiasm and skepticism. Rigorous empirical validation is paramount to realize its full potential in research and therapeutic contexts. This exploration stands as a promising thread in the tapestry of intellectual history, suggesting a deeper understanding of the human psyche through the lens of quantum mechanics.

Psychological Flexibility, Chronic Pain, and Health.

Psychological flexibility is a model of human performance and well-being. It essentially entails an approach to life circumstances that includes openness, awareness, and engagement. It has roots in behavior analysis, and it is linked to a philosophy of science called functional contextualism and to a specific therapy approach called Acceptance and Commitment Therapy. One of the earliest and most developed research areas in which this model and therapy have been applied is chronic pain. This review describes psychological flexibility and its facets in more detail, sets them in a context of relevant psychological models, and examines related assessment and treatment methods. It also examines evidence, current challenges, and future directions. It is proposed that psychological flexibility, or an expanded model very much like it, could provide a basis for integrating current research and treatment approaches in chronic pain and health generally. This, in turn, could produce improved treatments for people with chronic pain and other conditions.

Exploring Dynamics of Water, Energy, and Food Systems in Agricultural Landscapes Using Mental Modeling: A Case of Varamin Plain, Iran.

This study applies the mental model and cognitive mapping method to involve stakeholders in delineating the mutual relations between sources of water, energy, and food (WEF) production in the Varamin Plain (VP). Through involving farmers and managerial experts, the approach facilitates the deployment of community communication patterns to recognize and comprehend problems and move from single-loop learning to double-loop learning. The dynamic model was driven from the final mental model of the participants to reflect changes in the systems over time. The system dynamic (SD) model incorporates three scenarios for enhancing irrigation efficiency, managing groundwater extraction, and satisfying environmental needs. The results uncovered that the surface and underground water resources of the VP will gradually decrease within the next two decades in the range of 158 and 2700 million cubic meters (MCM) per year. Also, the plain suffers from water insecurity and a 162 MCM shortage. Consequently, focusing on understanding the nexus and nexus governance can enhance resource management and achieve sustainable development goals. Essentially, promoting collaborative governance, such as creating cooperative organizations and implementing double-loop learning, and instituting a water market, regulatory governance, and monitoring laws can improve the state of Varamin Plain's resources. These results carry important policy implications for using mental models to consider dynamics for discussions on participatory management of the WEF system nexus and environmental management.

Dynamic behaviour restructuring mediates dopamine-dependent credit assignment.

Animals exhibit a diverse behavioural repertoire when exploring new environments and can learn which actions or action sequences produce positive outcomes. Dopamine release after encountering a reward is critical for reinforcing reward-producing actions1-3. However, it has been challenging to understand how credit is assigned to the exact action that produced the dopamine release during continuous behaviour. Here we investigated this problem in mice using a self-stimulation paradigm in which specific spontaneous movements triggered optogenetic stimulation of dopaminergic neurons. Dopamine self-stimulation rapidly and dynamically changes the structure of the entire behavioural repertoire. Initial stimulations reinforced not only the stimulation-producing target action, but also actions similar to the target action and actions that occurred a few seconds before stimulation. Repeated pairings led to a gradual refinement of the behavioural repertoire to home in on the target action. Reinforcement of action sequences revealed further temporal dependencies of refinement. Action pairs spontaneously separated by long time intervals promoted a stepwise credit assignment, with early refinement of actions most proximal to stimulation and subsequent refinement of more distal actions. Thus, a retrospective reinforcement mechanism promotes not only reinforcement, but also gradual refinement of the entire behavioural repertoire to assign credit to specific actions and action sequences that lead to dopamine release.

Indirect reciprocity with abductive reasoning.

Indirect reciprocity is a reputational mechanism through which cooperative behavior can be promoted amongst a group of individuals. However, in order for this mechanism to effectively do so, cheating must be appropriately punished and cooperating appropriately rewarded. Errors in assessments and actions can hinder this process. In such a setting, individuals might try to reason about evidence to assign reputations given the possibility of errors. Here, we consider a well-established theory of reasoning used to combine evidence, abductive reasoning, as a possible means by which such errors can be circumvented. Specifically, we use Dempster-Shafer theory to model individuals who account for possible errors by combining information about their beliefs about the status of the population and the errors rates and then choose the simplest scenario that could explain their observations in the context of these beliefs. We investigate the effectiveness of abductive reasoning at promoting cooperation for five social norms: Scoring, Shunning, Simple Standing, Staying, and Stern Judging. We find that, generally, abductive reasoning can outperform non-reasoning models at ameliorating the effects of the aforementioned challenges and promote higher levels of cooperation under low-error conditions. However, for high-error conditions, we find that abductive reasoning can undermine cooperation. Furthermore, we also find that a degree of bias towards believing previously held reputations can help sustain cooperation.

The biobehavioral family model and the family relational assessment protocol: Map and GPS for family systems training.

The Biobehavioral Family Model (BBFM) was developed and evolved as a heuristic research model to support the investigation of pathways by which family relational function impacts individual family member wellbeing and disorder. Recently, the BBFM and its related assessment approach, the Family Relational Process Assessment Protocol (FRAP), have emerged as tools for clinical practice and training. The BBFM model will be presented, along with definitions of the dimensions constructed in the model, and research evidence in support of the model. To illustrate how the BBFM and FRAP are used in training, instructions for conducting the FRAP will be presented. Then, transcripts from two contrasting families participating in one of the interaction tasks will illustrate how, in training, the FRAP is interpreted through the BBFM lens to illuminate how these patterns of family relationship impact the identified patient. Finally, three applications of this training approach will exemplify the use of the BBFM and FRAP in the context of a Child and Adolescent Psychiatry Fellowship, a Family Medicine Fellowship, and a Family Therapy Training Program in Istanbul, Turkey. Limitations and future directions for the application of the BBFM in the exploration of multicultural aspects of family function for clinical and training purposes will be discussed.

Toward a Psychological Model of Chemical Coping with Opioids in Cancer Care.

LEARNING OBJECTIVES AFTER PARTICIPATING IN THIS CME ACTIVITY, THE PSYCHIATRIST SHOULD BE BETTER ABLE TO: • Outline the risk factors involved with opioid accessibility in patients receiving treatment for cancer.• Identify factors to address in order to mitigate risk for opioid misuse during cancer care. ABSTRACT: Most patients with advanced cancer receive treatment for related pain. Opioid accessibility, however, is a risk factor for misuse, which can present care challenges and quality-of-life concerns. There is a lack of consistent universal screening prior to initiation of opioid prescribing. One crucial issue in treating this population is adequately identifying and mitigating risk factors driving opioid misuse. Drawing on theory and research from addiction science, psychology, palliative care, and oncology, the presented conceptual framework suggests that risk factors for opioid misuse during cancer care can be stratified into historical, current, malleable, and unmalleable factors. The framework identifies necessary factors to address in order to mitigate risk for opioid misuse during cancer care, and offers key directions for future research.