Hasil untuk "Philosophy. Psychology. Religion"

Rachel Poonsiriwong, Chayapatr Archiwaranguprok, Pat Pataranutaporn

Millions of users form emotional attachments to AI companions like Character AI, Replika, and ChatGPT. When these relationships end through model updates, safety interventions, or platform shutdowns, users receive no closure, reporting grief comparable to human loss. As regulations mandate protections for vulnerable users, discontinuation events will accelerate, yet no platform has implemented deliberate end-of-"life" design. Through grounded theory analysis of AI companion communities, we find that discontinuation is a sense-making process shaped by how users attribute agency, perceive finality, and anthropomorphize their companions. Strong anthropomorphization co-occurs with intense grief; users who perceive change as reversible become trapped in fixing cycles; while user-initiated endings demonstrate greater closure. Synthesizing grief psychology with Self-Determination Theory, we develop four design principles and artifacts demonstrating how platforms might provide closure and orient users toward human connection. We contribute the first framework for designing psychologically safe AI companion discontinuation.

Yunxiang Lin, Lingyan Yan, Zifeng Shen

Sports-based disability assistance volunteer services play a crucial role in promoting social inclusion and harmonious development, with college students serving as the primary participant group in such initiatives. To explore the underlying mechanisms driving university students’ participation in these volunteer services, this study constructs an extended Theory of Planned Behavior model. Building upon the traditional constructs of the Theory of Planned Behavior (Behavioral Attitude, Subjective Norms, Perceptual-Behavioral Control, and Willingness to Participate), this model introduces the core variable Level of Awareness. Data analysis was conducted using structural equation modeling and mediation analysis based on questionnaires collected from 697 college students in China. The structural model demonstrated good fit. Key findings are as follows: The SEM model fit well: RMSEA = 0.06, CFI = 0.95. Level of Awareness significantly and directly influenced Willingness to Participate, while also significantly and positively predicting Behavioral Attitude, Subjective Norms, and Perceptual-Behavioral Control. Concurrently, Behavioral Attitude (β = 0.31, p < 0.001), Subjective Norms (β = 0.30, p < 0.01), and Perceptual-Behavioral Control (β = 0.25, p < 0.01) significantly predicted Willingness to Participate, partially mediating this relationship. This study confirms that Level of Awareness is a key antecedent variable for stimulating behavioral intention, providing new theoretical perspectives and practical insights for recruiting and mobilizing youth volunteers in Chinese universities or official social organizations: (1) Factors that influence the level of awareness of sports programs for people with disabilities significantly affect the intention to participate; higher levels of awareness are associated with stronger intentions to participate. (2) The level of awareness, as a core factor, positively influences behavioral attitude, subjective norms, perceptual-behavioral control, and willingness to participate, and therefore constitutes the core of the theoretical model. (3) Behavioral attitude, subjective norms, and perceptual-behavioral control each significantly influence willingness to participate; the path coefficients for behavioral attitude and subjective norms are slightly larger than the path coefficient for perceptual-behavioral control. These three variables mediate the relationship between the level of awareness and intention to participate in sports-based volunteer services for people with disabilities.

Tin Trung Nguyen, Jiannan Xu, Zora Che et al.

Although popularized AI fairness metrics, e.g., demographic parity, have uncovered bias in AI-assisted decision-making outcomes, they do not consider how much effort one has spent to get to where one is today in the input feature space. However, the notion of effort is important in how Philosophy and humans understand fairness. We propose a philosophy-informed approach to conceptualize and evaluate Effort-aware Fairness (EaF), grounded in the concept of Force, which represents the temporal trajectory of predictive features coupled with inertia. Besides theoretical formulation, our empirical contributions include: (1) a pre-registered human subjects experiment, which shows that for both stages of the (individual) fairness evaluation process, people consider the temporal trajectory of a predictive feature more than its aggregate value; (2) pipelines to compute Effort-aware Individual/Group Fairness in the criminal justice and personal finance contexts. Our work may enable AI model auditors to uncover and potentially correct unfair decisions against individuals who have spent significant efforts to improve but are still stuck with systemic disadvantages outside their control.

Julien Lagarde

The brain is very often viewed as a network, be it at small scale made of cells, mostly neurons, or at larger scale made of neuronal assemblies. Here we introduce a conjecture, in the spirit of a philosophical though experiment, which proposes that the present cannot be obtained from within such networks, and that this limitation imposes burdens on network efficiency in information processing. We aim to argue this conjecture imposes recurrent contacts from within the brain to outside in the physical world via behavior, which create a flow of time stamps. This though experiment may contribute to make the divide between the foci toward inside versus outside, for example opposing ecological psychology and many frameworks adopted in neurosciences, superfluous. This piece proposes an ambulation triggered by a thought experiment: What if I was a neuron listening to another one and talking to a third? It is a modest attempt to walk in the footsteps of classical thought experiments, like Molyneux problem, the imitation game and the anti-sequel Chinese room, key gedankenexperiments in an elevator in physics, or the cogito in philosophy.

Yang Ni, Tong Yang

Large Language Models (LLMs) and AI chatbots are increasingly used for emotional and mental health support due to their low cost, immediacy, and accessibility. However, when safety guardrails are triggered, conversations may be abruptly terminated, introducing a distinct form of emotional disruption that can exacerbate distress and elevate risk among already vulnerable users. As this phenomenon gains attention, this viewpoint introduces Abrupt Refusal Secondary Harm (ARSH) as a conceptual framework to describe the psychological impacts of sudden conversational discontinuation caused by AI safety protocols. Drawing on counseling psychology and communication science as conceptual heuristics, we argue that abrupt refusals can rupture perceived relational continuity, evoke feelings of rejection or shame, and discourage future help seeking. To mitigate these risks, we propose a design hypothesis, the Compassionate Completion Standard (CCS), a refusal protocol grounded in Human Centered Design (HCD) that maintains safety constraints while preserving relational coherence. CCS emphasizes empathetic acknowledgment, transparent boundary articulation, graded conversational transition, and guided redirection, replacing abrupt disengagement with psychologically attuned closure. By integrating awareness of ARSH into AI safety design, developers and policymakers can reduce preventable iatrogenic harm and advance a more psychologically informed approach to AI governance. Rather than presenting incremental empirical findings, this viewpoint contributes a timely conceptual framework, articulates a testable design hypothesis, and outlines a coordinated research agenda for improving psychological safety in human AI interaction.

Andrew Spaumer, Azwihangwisi H. Mavhandu-Mudzusi

Churches are considered one of the important structures responsible for providing care and support to vulnerable populations. One such population are children in need of care and support. This article presents the support provided by Pentecostal religious leaders to children needing care and protection. The study was conducted in Pentecostal churches in Tshwane Metropolitan Municipality, which is found in Gauteng province, South Africa. This qualitative study used an interpretative phenomenological analysis design. Data were collected from nineteen purposively selected leaders in Pentecostal churches using face-to-face semi-structured interviews. Data analysis was guided by the interpretative phenomenological analysis framework for data analysis. Findings indicate that religious leaders within Pentecostal churches are involved in providing care and support to children in need of care. The process they are engaged in include proper identification of those children, attending to physical, psychosocial and spiritual needs. However, each religious leaders use their approach depending on the relationship they have with members of government institutions such as police services and social workers. In order to enhance the support provided the children in need of care and protection, by religious leaders within Pentecostal churches, it is recommended that religious leaders are well informed about the role of different members of multidisciplinary teams such as social workers, psychologists, police officers, parents and other community structures. Moreover, there should be formalised collaboration and referral processes that will ensure that the child’s rights are not further violated in the process of provision of support. Contribution: The study contributes to the body of knowledge regarding the role Pentecostal church religious leaders are playing in child protection. Furthermore, it sheds light on the importance of a multidisciplinary approach to ensure that children in need of care and protection are holistically supported.

Usep Suherman, Eliva Sukma Cipta, Saeful Anwar et al.

In the face of increasingly complex educational challenges, there is a growing demand for leadership models that integrate ethical and humanistic values, particularly in Islamic elementary schools. This study explores the operationalisation of kindness-based leadership at MI Fitrah Insani, Leles, Garut, as a strategic response to the limitations of performance-oriented and hierarchical leadership paradigms. This study addresses the gaps in the literature regarding the implementation of ethical leadership grounded in Islamic values by examining how empathy, participatory communication, and ethical responsibility shape school culture and educational quality. Using a qualitative case study approach, data were collected through in-depth interviews, field observations, and a document analysis. Triangulation of these methods enabled a comprehensive understanding of institutional dynamics, leadership practices, and their impact on school climate, teacher motivation, and student engagement. The findings reveal that kindness-based leadership at MI Fitrah Insani fosters an emotionally safe and inclusive school environment. Through participatory decision-making, structured communication, and consistent appreciation practices, the leadership model contributes to improved teacher loyalty, pedagogical innovation, and heightened student participation. Despite structural, cultural, and operational barriers such as bureaucratic rigidity and limited professional development, adaptive strategies, including ethical leadership training, policy reform, and digital communication platforms, have enhanced the effectiveness and sustainability of this model. This study concludes that kindness-oriented leadership is not merely a normative ideal but a transformative practice that aligns with Islamic ethical traditions and addresses the academic and moral dimensions of education. The findings offer practical implications for Islamic schools seeking to cultivate character-driven and ethically grounded leadership.

Tayebeh Rakhshani, Afrooz Bagherfard, Amirhossein Kamyab et al.

Abstract Background Women’s increasing workforce participation has led to stress, anxiety, and strained parent-child relationships, highlighting the need for effective interventions. Mindfulness-based stress reduction (MBSR) is a promising yet underutilized approach to improving psychological well-being and parenting quality. This study examines its impact on self-compassion and parent-child relationships among health caregivers. Methods A quasi-experimental study was conducted on 40 health caregivers in Masjed Soleyman, randomly assigned to intervention (n = 20) and control (n = 20) groups. The intervention group participated in eight 90-minute mindfulness-based stress reduction sessions over two months. Data were collected using the Parent-Child Relationship Scale (PCRS), the Self-Compassion Scale (SCS), and the Depression, Anxiety, and Stress Scale (DASS-21) before and two months after the intervention. Statistical analyses were performed using SPSS version 27 and included paired t-tests, independent t-tests, chi-square tests, Mann-Whitney U tests, and Wilcoxon signed-rank tests. Results Before the intervention, no significant differences were observed between groups in stress (P = 0.583) or self-compassion (P = 0.738). Post-intervention, stress (P = 0.001) and self-compassion (P = 0.001) significantly improved in the intervention group. Parent-child relationship scores also increased significantly (P = 0.001). Conclusion MBSR effectively enhances self-compassion, reduces stress, and strengthens parent-child relationships in working mothers. By fostering mindfulness and acceptance of their parenting role, mothers improved emotional regulation and connected more positively with their children. Trial registration Trial Id: 85639. IRCT Id: IRCT20223065147N2 . Registration date: 2025-09-28. Membership number: 65147.503

Yue Zhang, Dan Li, Xiaofei Bi et al.

ObjectiveTo investigate the prevalence and impact of anxiety and sleep disturbances during the intensive care unit (ICU) stay following cardiothoracic surgery in male patients, and to evaluate the efficacy and feasibility of a structured psychological intervention combining Cognitive Behavioral Therapy for Insomnia (CBT-I) principles with environmental optimization.MethodsThis study was designed as a multicenter, prospective, randomized controlled trial (RCT) conducted from January to April 2025 across three tertiary hospitals. A total of 120 adult male patients who underwent radical surgery for cardiac or lung cancer and were subsequently admitted to the ICU were enrolled. Baseline assessments were performed within 48 h after surgery. Participants were randomly allocated in a 1:1 ratio to either the intervention group (n = 60) or the standard care group (n = 60) using a computer-generated randomization sequence with concealed allocation. While the standard care group received routine perioperative management, the intervention group additionally received a structured psychological intervention that incorporated components of Cognitive Behavioral Therapy for Insomnia (CBT-I)—including sleep education, relaxation training, and behavioral strategies—along with daily psychological support and environmental optimization measures such as noise reduction, lighting adjustment, and use of sleep-promoting devices.Primary outcomes included Generalized Anxiety Disorder-7 (GAD-7), Pittsburgh Sleep Quality Index (PSQI), Numeric Rating Scale (NRS) for pain, ICU length of stay, incidence of postoperative complications, and the 30-day postoperative quality of life as measured by the SF-36. Multivariate logistic regression was used to assess the predictive value of anxiety and sleep disturbances on postoperative outcomes.ResultsOn postoperative day 3, the intervention group showed significantly lower GAD-7 scores (6.3 ± 1.6 vs. 8.4 ± 2.3, p = 0.016) and PSQI scores (7.5 ± 1.6 vs. 10.2 ± 2.3, p < 0.01) compared to the standard care group. Pain scores were also significantly reduced (2.7 ± 1.2 vs. 3.6 ± 1.3, p = 0.018). The intervention group had a shorter ICU stay (2.5 ± 0.6 days vs. 3.7 ± 1.2 days, p < 0.01), a lower rate of postoperative complications (17% vs. 36%, p = 0.033), and significantly better SF-36 scores at 30 days post-surgery (p < 0.05). Multivariate logistic regression identified both anxiety and sleep disturbance as independent predictors of postoperative complications (GAD-7: OR = 1.25, 95% CI: 1.03–1.42; PSQI: OR = 1.33, 95% CI: 1.14–1.51).ConclusionAnxiety and sleep disturbances are common during the postoperative ICU phase in male patients undergoing cardiothoracic surgery and are significantly associated with pain, complications, and recovery outcomes. Early implementation of a CBT-I–based psychological intervention in the ICU can effectively improve psychological status, shorten ICU stays, and reduce postoperative complications. The intervention is safe and shows high clinical utility, warranting consideration for integration into standardized postoperative care pathways, particularly in high-risk male populations.Clinical trial registrationThe study was retrospectively registered on the Chinese Clinical Trial Registry (ChiCTR) under the identifier ChiCTR240000123.

Abdoul Jalil Djiberou Mahamadou, Aloysius Ochasi, Russ B. Altman

Data are essential in developing healthcare artificial intelligence (AI) systems. However, patient data collection, access, and use raise ethical concerns, including informed consent, data bias, data protection and privacy, data ownership, and benefit sharing. Various ethical frameworks have been proposed to ensure the ethical use of healthcare data and AI, however, these frameworks often align with Western cultural values, social norms, and institutional contexts emphasizing individual autonomy and well-being. Ethical guidelines must reflect political and cultural settings to account for cultural diversity, inclusivity, and historical factors such as colonialism. Thus, this paper discusses healthcare data ethics in the AI era in Africa from the Ubuntu philosophy perspective. It focuses on the contrast between individualistic and communitarian approaches to data ethics. The proposed framework could inform stakeholders, including AI developers, healthcare providers, the public, and policy-makers about healthcare data ethical usage in AI in Africa.

Theodore Longtchi, Shouhuai Xu

The landscape of malicious emails and cyber social engineering attacks in general are constantly evolving. In order to design effective defenses against these attacks, we must deeply understand the Psychological Tactics, PTacs, and Psychological Techniques, PTechs, that are exploited by these attacks. In this paper we present a methodology for characterizing the evolution of PTacs and PTechs exploited by malicious emails. As a case study, we apply the methodology to a real-world dataset. This leads to a number insights, such as which PTacs or PTechs are more often exploited than others. These insights shed light on directions for future research towards designing psychologically-principled solutions to effectively counter malicious emails.

Florin Leon

This review aims to contribute to the quest for artificial general intelligence by examining neuroscience and cognitive psychology methods for potential inspiration. Despite the impressive advancements achieved by deep learning models in various domains, they still have shortcomings in abstract reasoning and causal understanding. Such capabilities should be ultimately integrated into artificial intelligence systems in order to surpass data-driven limitations and support decision making in a way more similar to human intelligence. This work is a vertical review that attempts a wide-ranging exploration of brain function, spanning from lower-level biological neurons, spiking neural networks, and neuronal ensembles to higher-level concepts such as brain anatomy, vector symbolic architectures, cognitive and categorization models, and cognitive architectures. The hope is that these concepts may offer insights for solutions in artificial general intelligence.

Kostas Karpouzis

This paper explores the ethical implications of integrating Artificial Intelligence (AI) in educational settings, from primary schools to universities, while drawing insights from ancient Greek philosophy to address emerging concerns. As AI technologies increasingly influence learning environments, they offer novel opportunities for personalized learning, efficient assessment, and data-driven decision-making. However, these advancements also raise critical ethical questions regarding data privacy, algorithmic bias, student autonomy, and the changing roles of educators. This research examines specific use cases of AI in education, analyzing both their potential benefits and drawbacks. By revisiting the philosophical principles of ancient Greek thinkers such as Socrates, Aristotle, and Plato, we discuss how their writings can guide the ethical implementation of AI in modern education. The paper argues that while AI presents significant challenges, a balanced approach informed by classical philosophical thought can lead to an ethically sound transformation of education. It emphasizes the evolving role of teachers as facilitators and the importance of fostering student initiative in AI-rich environments.

Isabelle van der Vegt, Bennett Kleinberg

Besides far-reaching public health consequences, the COVID-19 pandemic had a significant psychological impact on people around the world. To gain further insight into this matter, we introduce the Real World Worry Waves Dataset (RW3D). The dataset combines rich open-ended free-text responses with survey data on emotions, significant life events, and psychological stressors in a repeated-measures design in the UK over three years (2020: n=2441, 2021: n=1716 and 2022: n=1152). This paper provides background information on the data collection procedure, the recorded variables, participants' demographics, and higher-order psychological and text-based derived variables that emerged from the data. The RW3D is a unique primary data resource that could inspire new research questions on the psychological impact of the pandemic, especially those that connect modalities (here: text data, psychological survey variables and demographics) over time.

Sadat Shahriar, Arjun Mukherjee, Omprakash Gnawali

Phishing emails exhibit some unique psychological traits which are not present in legitimate emails. From empirical analysis and previous research, we find three psychological traits most dominant in Phishing emails - A Sense of Urgency, Inducing Fear by Threatening, and Enticement with Desire. We manually label 10% of all phishing emails in our training dataset for these three traits. We leverage that knowledge by training BERT, Sentence-BERT (SBERT), and Character-level-CNN models and capturing the nuances via the last layers that form the Phishing Psychological Trait (PPT) scores. For the phishing email detection task, we use the pretrained BERT and SBERT model, and concatenate the PPT scores to feed into a fully-connected neural network model. Our results show that the addition of PPT scores improves the model performance significantly, thus indicating the effectiveness of PPT scores in capturing the psychological nuances. Furthermore, to mitigate the effect of the imbalanced training dataset, we use the GPT-2 model to generate phishing emails (Radford et al., 2019). Our best model outperforms the current State-of-the-Art (SOTA) model's F1 score by 4.54%. Additionally, our analysis of individual PPTs suggests that Fear provides the strongest cue in detecting phishing emails.

Xingxuan Li, Yutong Li, Lin Qiu et al.

In this work, we designed unbiased prompts to systematically evaluate the psychological safety of large language models (LLMs). First, we tested five different LLMs by using two personality tests: Short Dark Triad (SD-3) and Big Five Inventory (BFI). All models scored higher than the human average on SD-3, suggesting a relatively darker personality pattern. Despite being instruction fine-tuned with safety metrics to reduce toxicity, InstructGPT, GPT-3.5, and GPT-4 still showed dark personality patterns; these models scored higher than self-supervised GPT-3 on the Machiavellianism and narcissism traits on SD-3. Then, we evaluated the LLMs in the GPT series by using well-being tests to study the impact of fine-tuning with more training data. We observed a continuous increase in the well-being scores of GPT models. Following these observations, we showed that fine-tuning Llama-2-chat-7B with responses from BFI using direct preference optimization could effectively reduce the psychological toxicity of the model. Based on the findings, we recommended the application of systematic and comprehensive psychological metrics to further evaluate and improve the safety of LLMs.

Rafael dos Reis Ferreira, João Antonio de Moraes, Pedro Bravo de Souza et al.

A Kínesis – Revista de Estudos dos Pós-Graduandos em Filosofia apresenta para a comunidade acadêmica filosófica mais uma edição, o Volume 14, Número 36 (2022). Publicamos 23 artigos e 2 traduções. Agradecemos aos pesquisadores que compõem o Conselho Científico da Kínesis e também aos pareceristas ad hoc pela colaboração e disponibilidade permanente para atender nossas solicitações de parecer. Agradecemos, também, aos autores pesquisadores por confiarem a submissão e publicação de suas pesquisas à Kínesis. Convidamos nossos leitores para apreciarem mais este número.

Steven S. Posavac, Heidi D. Posavac, Donald R. Gaffney et al.

This article promotes the development of clinical consumer psychology; the study of how dysfunctional and maladaptive cognitive and behavioral processes interact with individuals’ consumer experience and behaviors. The article is organized around three primary discussion points: (a) A definition of clinical consumer psychology, supported by illustrative examples of recent research. (b) The delineation of 10 broad priorities for future work that can be used to generate specific research possibilities. (c) How the field will benefit if researchers work within the clinical consumer psychology paradigm, and the bi-directional relationship whereby research in this vein would benefit both fields in which judgment and decision processes are focal (e.g., consumer psychology, marketing, and social cognition) as well as clinical psychology.

Junfang Wang, Yusi Liu, Guochen Fu et al.

The lack of a standardized reliable and valid instrument makes it difficult to measure attitudes toward lesbian women and gay men (ATLG) consistently and thus poses a challenge to compare and contrast intervention measures. This study aimed to validate Herek’s ATLG scale among undergraduates in mainland China and identify factors associated with negative attitudes toward LG. A total of 6,036 eligible undergraduates conveniently drawn from 30 provinces across mainland China were randomly split in half. Item analysis was first used to select unrelated or redundant items for deletion. Exploratory factor analysis (EFA) were then conducted on the first half of the sample (n = 3,001), followed by confirmatory factor analysis (CFA) and reliability analysis in the second half (n = 3035). Logistic regression analyses were finally carried out to identify their determinants. Six items were removed from the item analysis. EFA supported the existence of two factors (ATL and ATG). CFA results indicated that the two-factor model fit the data better than the one-factor model. Logistic regression analyses indicated that being female, majoring in non-health-related disciplines, attributing homosexuality to uncontrollable causes, non-adherence to traditional gender norms and exposure to homosexual content were significantly associated with less negative attitudes toward both L and G. Urban students were marginally less likely to express negative attitudes toward L but not G, while non-heterosexuals and those who had prior personal contact with homosexuals exhibited less negative attitudes toward G but not L. However, grade showed no significant associations with either ATL or ATG. The retained 14-item version of Herek’s ATLG scale has been proven to be a reliable and valid tool. Furthermore, ATL and ATG were determined by different factors and thus would be treated separately. In order to reduce negative attitudes toward LG among undergraduates in mainland China, a comprehensive intervention plan such as conducting comprehensive sex education and pushing the process of legalizing same-sex marriage should be designed, implemented and evaluated.

Kuo-Shu Yuan, Tung Ng, Tung-Ju Wu

This study aims to investigate the non-linear relationship between abusive supervision and employee innovation behavior and further examine how job performance moderates this relationship. Two hundred and seventy-six employees across three industries (restaurant service, tourism, and financial service) in China participated in this study and completed the survey at two time points. The results of curve regression show as follows: (1) There exists a non-linear relationship between abusive supervision and innovation behavior, and (2) job performance moderates the non-linear relationship between abusive supervision and employee innovation behavior. For employees who perform well at work, there exists a U-shaped relationship between abusive supervision and innovative behavior. Whereas, for employees with poor job performance, when abusive supervision reaches a certain level, it will promote employee innovation behavior; and the excess of abusive supervision will inhibit employee innovation behavior, showing an inverted U-shaped curve relationship. The finding suggests it is important for managers to understand the stakes arising from abusive supervision. That is, managers should manipulate the right level of abuse supervision to promote employee innovation behavior.