Hasil untuk "Psychology"

S. Saei, N. Tajik

A key principle in resilience thinking is Embracing Change because change is, indeed, inevitable. In the face of a growing number of disasters, natural and human-made disasters, our critical infrastructures (CIs) are being challenged like never before. This recent trend has sparked a wave of interest among both practitioners and researchers in understanding and delving deeper into the concept of resilience across multiple disciplines. This paper provides an accessible review of these new insights, exploring various frameworks, guidebooks, and methodologies that define resilience through the lens of ecology, engineering, psychology, social science, community, and disaster management during crisis.

Marcel Valovy

As artificial intelligence transforms software development, a critical question emerges: how can developers and AI systems collaborate most effectively? This dissertation optimizes human-AI programming roles through self-determination theory and personality psychology, introducing the Role Optimization Motivation Alignment (ROMA) framework. Through Design Science Research spanning five cycles, this work establishes empirically-validated connections between personality traits, programming role preferences, and collaborative outcomes, engaging 200 experimental participants and 46 interview respondents. Key findings demonstrate that personality-driven role optimization significantly enhances self-determination and team dynamics, yielding 23% average motivation increases among professionals and up to 65% among undergraduates. Five distinct personality archetypes emerge: The Explorer (high Openness/low Agreeableness), The Orchestrator (high Extraversion/Agreeableness), The Craftsperson (high Neuroticism/low Extraversion), The Architect (high Conscientiousness), and The Adapter (balanced profile). Each exhibits distinct preferences for programming roles (Co-Pilot, Co-Navigator, Agent), with assignment modes proving crucial for satisfaction. The dissertation contributes: (1) an empirically-validated framework linking personality traits to role preferences and self-determination outcomes; (2) a taxonomy of AI collaboration modalities mapped to personality profiles while preserving human agency; and (3) an ISO/IEC 29110 extension enabling Very Small Entities to implement personality-driven role optimization within established standards. Keywords: artificial intelligence, human-computer interaction, behavioral software engineering, self-determination theory, personality psychology, phenomenology, intrinsic motivation, pair programming, design science research, ISO/IEC 29110

Saptati Datta, Riana Guha, Rachael Shudde et al.

We describe Bayes factors functions based on the sampling distributions of \emph{z}, \emph{t}, $χ^2$, and \emph{F} statistics, using a class of inverse-moment prior distributions to define alternative hypotheses. These non-local alternative prior distributions are centered on standardized effects, which serve as indices for the Bayes factor function. We compare the conclusions drawn from resulting Bayes factor functions to those drawn from Bayes factors defined using local alternative prior specifications and examine their frequentist operating characteristics. Finally, an application of Bayes factor functions to replicated experimental designs in psychology is provided.

Litian Zhang, Xiaoming Zhang, Bingyu Yan et al.

The exponential growth of social media and generative AI has transformed information dissemination, fostering connectivity but also accelerating the spread of misinformation. Understanding information propagation dynamics and developing effective control strategies is essential to mitigate harmful content. Traditional models, such as SIR, provide basic insights but inadequately capture the complexities of online interactions. Advanced methods, including attention mechanisms and graph neural networks, enhance accuracy but typically overlook user psychology and behavioral dynamics. Large language models (LLMs), with their human-like reasoning, offer new potential for simulating psychological aspects of information spread. We introduce an LLM-based simulation environment capturing agents' evolving attitudes, emotions, and responses. Initial experiments, however, revealed significant gaps between LLM-generated behaviors and authentic human dynamics, especially in stance detection and psychological realism. A detailed evaluation through Social Information Processing Theory identified major discrepancies in goal-setting and feedback evaluation, stemming from the lack of emotional processing in standard LLM training. To address these issues, we propose the Social Information Processing-based Chain of Thought (SIP-CoT) mechanism enhanced by emotion-guided memory. This method improves the interpretation of social cues, personalization of goals, and evaluation of feedback. Experimental results confirm that SIP-CoT-enhanced LLM agents more effectively process social information, demonstrating behaviors, attitudes, and emotions closer to real human interactions. In summary, this research highlights critical limitations in current LLM-based propagation simulations and demonstrates how integrating SIP-CoT and emotional memory significantly enhances the social intelligence and realism of LLM agents.

Sebastian Crutch, Claire Waddington, Emma Harding et al.

Rarer dementias are associated with atypical symptoms and younger onset, which result in a higher burden of care. We provide a review of the global literature on longitudinal decline in activities of daily living (ADLs) in dementias that account for less than 10% of dementia diagnoses. Published studies were identified through searches conducted in Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (Embase), Excerpta Medica Care (Emcare), PsycINFO, and Cumulative Index in Nursing and Allied Health Literature (CINAHL). The search criteria included terms related to ‘rarer dementias’, ‘activities of daily living’ and ‘longitudinal or cross-sectional studies’ following a predefined protocol registered. Studies were screened, and those that met the criteria were citation searched. Quality assessments were performed, and relevant data were extracted. 20 articles were selected, of which 19 focused on dementias within the frontotemporal dementia/primary progressive aphasia spectrum, while one addressed posterior cortical atrophy. Four studies were cross-sectional and 16 studies were longitudinal, with a median duration of 2.2 years. The Disability Assessment for Dementia was used to measure decline in 8 of the 20 studies. The varied sequences of ADL decline reported in the literature reflect variation in diagnostic specificity between studies and within-syndrome heterogeneity. Most studies used Alzheimer’s disease staging scales to measure decline, which cannot capture variant-specific symptoms. To enhance care provision in dementia, ADL scales could be deployed postdiagnosis to aid treatment and planning. This necessitates staging scales that are variant-specific and span the disease course from diagnosis to end of life. PROSPERO registration number: CRD42021283302.

Daniel J. Schad, Martin Modrák, Shravan Vasishth

Bayes factor null hypothesis tests provide a viable alternative to frequentist measures of evidence quantification. Bayes factors for realistic data sets in areas like psychology cannot be calculated exactly and require numerical approximations to complex integrals. Crucially, the accuracy of these approximations, i.e., whether an approximate Bayes factor corresponds to the exact Bayes factor, is unknown, and may depend on data, prior, and likelihood. We have recently developed a novel statistical procedure, namely marginal simulation-based calibration (SBC) for Bayes factors, to test whether the computed Bayes factors for a given analysis are accurate. Here, we use marginal SBC for Bayes factors and calibration plots to test for some common cognitive designs, whether Bayes factors are calculated accurately. We use the bridgesampling/brms packages in R. We run analyses for three commonly used designs in psychology and psycholinguistics: (a) a design with random effects for subjects only, (b) a Latin square design with crossed random effects for subjects and items, but a single fixed-factor, and (c) a Latin square 2x2 design with crossed random effects for subjects and items. We find that Bayes factor estimates turn out accurate in cases when the bridgesampling algorithm does not issue a warning message, but can be biased and liberal when a warning message is shown. These results support the use of brms/bridgesampling for null hypothesis Bayes factor tests in commonly used factorial designs. They also suggest that when a warning message is issued, Bayes factor results should not be trusted. The results show that it is practical to check whether Bayes factors are computed correctly.

Ryan Liu, Jiayi Geng, Addison J. Wu et al.

Chain-of-thought (CoT) prompting has become a widely used strategy for improving large language and multimodal model performance. However, it is still an open question under which settings CoT systematically reduces performance. In this paper, we seek to identify the characteristics of tasks where CoT reduces performance by drawing inspiration from cognitive psychology, focusing on six representative tasks from the psychological literature where deliberation hurts performance in humans. In three of these tasks, state-of-the-art models exhibit significant performance drop-offs with CoT (up to 36.3\% absolute accuracy for OpenAI o1-preview compared to GPT-4o), while in others, CoT effects are mixed, with positive, neutral, and negative changes. While models and humans do not exhibit perfectly parallel cognitive processes, considering cases where thinking has negative consequences for humans helps identify settings where it negatively impacts models. By connecting the literature on human verbal thinking and deliberation with evaluations of CoT, we offer a perspective for understanding the impact of inference-time reasoning.

Lucas Gren, Christian Jacobsson

From 2019 to 2022, Volvo Cars successfully translated our research discoveries regarding group dynamics within agile teams into widespread industrial practice. We wish to illuminate the insights gained through the process of garnering support, providing training, executing implementation, and sustaining a tool embraced by approximately 700 teams and 9,000 employees. This tool was designed to empower agile teams and propel their internal development. Our experiences underscore the necessity of comprehensive team training, the cultivation of a cadre of trainers across the organization, and the creation of a novel software solution. In essence, we deduce that an automated concise survey tool, coupled with a repository of actionable strategies, holds remarkable potential in fostering the maturation of agile teams, but we also share many of the challenges we encountered during the implementation.

Aziz Sarhani-Robles, María Guillot-Valdés, Cristina Lendínez-Rodríguez et al.

<i>Backgroud and Objective:</i> The aim of this study was to evaluate the psychometric properties of SAVE-6 in the medical student population and assess its gender invariance. <i>Subjects and Methods:</i> The sample consisted of 320 medical students aged 18–23 years (153 men and 167 women) who completed an anonymous online questionnaire. Data collection took place in June 2024. To assess the scale structure, a descriptive analysis of the items was carried out, followed by a confirmatory factor analysis (CFA). To analyze whether there were differences in the invariance of the measure by gender, a multigroup CFA was performed. <i>Results:</i> SAVE-6 showed high internal consistency, α = 0.89 and ω = 0.92, a minimum score of 12, a maximum score of 22, an unifactorial structure, and adequate convergent validity. Specifically, the following were found: the positive and significant relationship with HADS was 0.98 for the full scale, 0.76 for depression, and 0.91 for anxiety, and there was a negative and significant convergent validity with resilience (−0.82) and resilience to suicide attempts (−0.88). Regarding the gender invariance, relevant data is that the factor loadings between each item and the SAVE-6 factor were not the same, so women present a higher level of anxiety than men (Δχ 2 (6) = 42.53). <i>Discussion:</i> The results showed good internal reliability of SAVE-6 and good suitability. Data also revealed that they were not equal in relation to gender. Specifically, the scalar invariance revealed significant differences by items between men and women in anxiety. <i>Conclusions:</i> This scale can be applied to medical students as a reliable and valid instrument to assess the anxiety response to disease contagion in future health professionals.

Robert J. Goddard, Wim P. Krijnen, Vincent Roelfsema et al.

Introduction: Bruxism is a repetitive masticatory muscle activity that may cause substantial morbidity and reduce the quality of life in children with profound intellectual and multiple disabilities. Assessment methods most commonly used were caregiver reporting and dental examination, This systematic review with meta-analysis aims to determine the prevalence of bruxism in children with profound intellectual and multiple disabilities and to describe the currently used assessment methods for bruxism in this population. Methods: We conducted a systematic review and meta-analysis using a multi-component search strategy. We used a random effects model to calculate the prevalence and 95 % confidence intervals for each study, for all studies combined, and specifically for Rett syndrome (RS), cerebral palsy (CP), Down syndrome (DS), and “other disorders (primarily Angelman syndrome and Prader–Willi syndrome).” Results: The prevalence for the entire group based on a random effects model was found to be 49 % (95 %CI 41–57 %) with high heterogeneity (I2 = 93 %, p < 0.01), for RS 74 % (95 %CI 53–88 %, I2 = 84 %, p < 0.01), CP 48 % (95 %CI 38–57 %, I2 = 86 %, p < 0.01), DS 40 % (95 %CI 33–47 %, I2 = 60 %, p < 0.01) and “other disorders” 40 % (95 %CI 18–67 %, I2 = 98 %, p < 0.01). The group prevalences were not equal, indicating a significant difference (P-value = 0.03), with a notably higher likelihood of RS. Conclusion: We observed a five-fold increased likelihood of bruxism in children with profound intellectual and multiple disabilities. The disorder with the highest prevalence was Rett syndrome, with a seven-fold increased likelihood of bruxism. The increased likelihood of bruxism in this vulnerable group of children demands clinicians pay heed to this substantial morbidity.

Risza Subiantoro, Margarita M Maramis, Nining Febriana et al.

Introduction: Postoperative depression is a condition of depressive effects in patients without symptoms of depressive mood that occurs a few weeks after surgery and persists for at least 2 weeks. It generally possesses the same symptoms as major depressive disorder. Review: Their difference is that surgery is the trigger of depression in postoperative depression cases. Postoperative depression is associated with increased patients’ morbidity and mortality, increased the risk of disease complications, reduced postoperative healing process, prolonged the duration of treatment, and reduced patients’ quality of life. Therefore, mental health conditions should always be assessed on patients after undergoing surgery. Postoperative depression therapy needs to consider the benefits of antidepressants and adequate pain management. Antidepressant considerations also need to consider interactions with other drugs. Psychotherapy and cognitive behavioral therapy are also useful in postoperative depression management. Conclusion: This review is aimed to give insight about postoperative depression, its importance, and how to treat it.

Toygar Tanyel

The aim of this study is to determine the perceived stress levels of 150 individuals and analyze the responses given to adapted questions in Turkish using machine learning. The test consists of 14 questions, each scored on a scale of 0 to 4, resulting in a total score range of 0-56. Out of these questions, 7 are formulated in a negative context and scored accordingly, while the remaining 7 are formulated in a positive context and scored in reverse. The test is also designed to identify two sub-factors: perceived self-efficacy and stress/discomfort perception. The main objectives of this research are to demonstrate that test questions may not have equal importance using artificial intelligence techniques, reveal which questions exhibit variations in the society using machine learning, and ultimately demonstrate the existence of distinct patterns observed psychologically. This study provides a different perspective from the existing psychology literature by repeating the test through machine learning. Additionally, it questions the accuracy of the scale used to interpret the results of the perceived stress test and emphasizes the importance of considering differences in the prioritization of test questions. The findings of this study offer new insights into coping strategies and therapeutic approaches in dealing with stress. Source code: https://github.com/toygarr/ppl-r-stressed

Andrei Khrennikov

We develop the contextual measurement model (CMM) which is used for clarification of the quantum foundations. This model matches with Bohr's views on the role of experimental contexts. CMM is based on contextual probability theory which is connected with generalized probability theory. CMM covers measurements in classical, quantum, and semi-classical physics. The CMM formalism is illustrated by a few examples. We consider CMM framing of classical probability, the von Neumann measurement theory, the quantum instrument theory. CMM can also be applied outside of physics, in cognition, decision making, and psychology, so called quantum-like modeling.

Richard Naud, André Longtin

Neuroscience and artificial intelligence are closely intertwined, but so are the physics of dynamical system, philosophy and psychology. Each of these fields try in their own way to relate observations at the level of molecules, synapses, neurons or behavior, to a function. An influential conceptual approach to this end was popularized by David Marr, which focused on the interaction between three theoretical 'levels of analysis'. With the convergence of simulation-based approaches, algorithm-oriented Neuro-AI and high-throughput data, we currently see much research organized around four levels of analysis: observations, models, algorithms and functions. Bidirectional interaction between these levels influences how we undertake interdisciplinary science.

Mohit Chandra, Anush Mattapalli, Munmun De Choudhury

The proliferation of online misinformation has emerged as one of the biggest threats to society. Considerable efforts have focused on building misinformation detection models, still the perils of misinformation remain abound. Mitigating online misinformation and its ramifications requires a holistic approach that encompasses not only an understanding of its intricate landscape in relation to the complex issue and topic-rich information ecosystem online, but also the psychological drivers of individuals behind it. Adopting a time series analytic technique and robust causal inference-based design, we conduct a large-scale observational study analyzing over 32 million COVID-19 tweets and 16 million historical timeline tweets. We focus on understanding the behavior and psychology of users disseminating misinformation during COVID-19 and its relationship with the historical inclinations towards sharing misinformation on Non-COVID domains before the pandemic. Our analysis underscores the intricacies inherent to cross-domain misinformation, and highlights that users' historical inclination toward sharing misinformation is positively associated with their present behavior pertaining to misinformation sharing on emergent topics and beyond. This work may serve as a valuable foundation for designing user-centric inoculation strategies and ecologically-grounded agile interventions for effectively tackling online misinformation.

Cheng Li, Jindong Wang, Yixuan Zhang et al.

Emotion significantly impacts our daily behaviors and interactions. While recent generative AI models, such as large language models, have shown impressive performance in various tasks, it remains unclear whether they truly comprehend emotions. This paper aims to address this gap by incorporating psychological theories to gain a holistic understanding of emotions in generative AI models. Specifically, we propose three approaches: 1) EmotionPrompt to enhance AI model performance, 2) EmotionAttack to impair AI model performance, and 3) EmotionDecode to explain the effects of emotional stimuli, both benign and malignant. Through extensive experiments involving language and multi-modal models on semantic understanding, logical reasoning, and generation tasks, we demonstrate that both textual and visual EmotionPrompt can boost the performance of AI models while EmotionAttack can hinder it. Additionally, EmotionDecode reveals that AI models can comprehend emotional stimuli akin to the mechanism of dopamine in the human brain. Our work heralds a novel avenue for exploring psychology to enhance our understanding of generative AI models.

Péter Simonik

A dolgozat a tatai Esterházy-uradalomhoz tartozó Alsógalla, Bánhida, Felsőgalla, valamint Tatabánya községek területén élt zsidó közösség történetén keresztül kívánja megragadni a modernizáció, a polgárosodás és az asszimiláció folyamatát egy olyan térségben, amely a 19. század második felében, a szénbányászat megjelenését követően, jelentős gazdasági átalakuláson ment keresztül. A zsidóság helyi társadalomban betöltött szerepének, valamint a zsidó és nem zsidó népesség viszonyának vizsgálata révén beazonosításra kerültek azon tényezők, amelyek hozzájárultak az izraelita felekezetű népesség társadalmi beilleszkedéséhez, továbbá kijelölésre kerültek azon mérföldkövek is, amelyek az asszimiláció egyes szakaszaihoz köthetők.

Florin Bösch, Markus A. Landolt, Matthias R. Baumgartner et al.

Background: Living with a non-acute (phenylketonuria) or acute (e.g. urea cycle disorders, organic acidurias) intoxication-type inborn error of metabolism (IT-IEM) can have a substantial impact on health-related quality of life (HrQoL) of paediatric patients and their families. Parents take primary responsibility for treatment monitoring and experience worry and fear about their child's health status. Quantitative evidence on parental psychological factors which may influence the HrQoL of patients with IT-IEM are sparse to non-existent. Methods: In this multicenter survey study 50 parents of IT-IEM patients (ages 5–19) assessed the severity of their child's disease, reported on caregiver burden, and proxy-rated their child's HrQoL. Additionally, 35 patient self-reports on HrQoL were obtained (n = 16 female patients, n = 19 male patients). Multiple linear regressions were conducted to examine the predictive power of child age, sex, medical diagnosis type (acute / non-acute), parental perceived disease severity and caregiver burden on patients' HrQoL. Mediation analyses were used to investigate the relation of caregiver burden and parental ratings of disease severity with patients' HrQoL. Results: Significant regression models for self-reported [F(5,34) = 10.752, p < .001, R2 adj.. = 0.59] and parent proxy reported HrQoL [F(5,49) = 20.513, p < .001, R2 adj.. = 0.67] emerged. High caregiver burden and perceived disease severity predicted significantly lower patient self- and proxy-reported HrQoL while type of diagnosis (acute versus non-acute) did not. Female sex predicted significantly lower self-reported HrQoL. High caregiver burden was the mediating factor between high perceived severity of the child's disease and lower proxy- by parent rated HrQoL. Conclusion: Detecting elevated burden of care and providing support for parents seems crucial to prevent adverse consequences for their children's HrQoL. Intervention studies are needed, to assess which support programs are most efficient.

Mengmeng Liu

Celebrity influence plays a significant role in fostering the consumers’ impulse buying tendency and purchase intention. In the modern advertising era, the celebrity endorsement characteristics have driven the firms’ promotion campaigns, stimulating consumer purchasing behavior through celebrity branding. The study signifies the relationship between celebrity’s traits of trustworthiness, attractiveness, credibility, and expertise influence consumers’ impulse behavior. The data was collected from the 371 customers of the fast fashion industry by using the convenient-sampling technique. SMART-PLS was used for data analysis by applying structural equation modeling. The study results show that celebrity trustworthiness, the attractiveness of a celebrity endorser, the credibility of a celebrity endorser, and celebrity expertise positively impact purchase intention and impulse buying tendency. Purchase intention plays a mediating role between independent and dependent variables.

Mehreen Liaqat, Muhammad Naveed Riaz, Humaira Yasmin

Objective: The study examined the impact of personality types on sadism and schadenfreude in adults. Study type, settings & duration: This descriptive study was conducted at Sargodah District from October 2019 to December 2020.   Methodology: New Five Factors Inventory, short sadistic Impulse Scale and schadenfreude scale were used for data collection from university students (N = 300). Results: Findings revealed that neuroticism has positive correlation with sadism and schadenfreude while extroversion, agreeableness, and conscientiousness have negative correlation with sadism and schadenfreude. Openness to experience as a personality trait was not significantly correlated with sadism and schadenfreude. Additionally, regression analyses revealed that neuroticism and conscientiousness significantly predicted sadism while only agreeableness come out as a significant predictor of schadenfreude. Conclusion: The findings have important implications in the field of personality and human relations. The findings can be used for understating the nature of different personalities having tendencies of negative emotions of sadism and schadenfreude.