Explore the vast range of titles available.

Background Phenomenological literature describes borderline personality disorder (BPD) as marked by instantaneous and immediate temporal experience. Meanwhile, qualitative clinical findings suggest that BPD lived experience is dominated by a negatively biased, disorganised past and an overintense present, yet systematic research remains limited. Methods Cross-sectional study, with 52 inpatients diagnosed with BPD compared to a healthy control group ( N  = 98). To examine temporal experience in individuals with BPD quantitatively, this study uses the Transdiagnostic Assessment of Temporal Experience (TATE), a novel, structured, phenomenological interview tool. Data were analysed using factor analysis to identify underlying temporal constructs; group differences were tested using Mann-Whitney U tests. The interpretative framework is phenomenological psychopathology. Results The most pronounced features in the BPD group included past-negative intrusions, flashbacks, a sense of present paralysis, and anxiety about the future. The BPD group scored overall higher than controls ( p  < 0.001), and, in particular, significantly higher in the dimensions related to explicit anomalous experiences of the past, present, and future. The temporal disturbances were also felt as more intense, regardless of the actual scores. Crucially, one reliable factor emerged, indicating an underlying structure of disrupted temporal continuity, in line with the existing theory of phenomenological psychopathology. Conclusions The findings suggest that temporal fragmentation – especially in the form of past-negative intrusions and flashbacks – may be a core feature of BPD lived experience and relevant for future diagnostic and therapeutic frameworks. Trial registration Not applicable. Clinical trial number Not applicable.

Altered temporal experience lies at the core of various psychiatric conditions, including borderline personality disorder (BPD). Mainstream research in psychopathology tends to explore BPD with scrutiny while neglecting other personality disorders (PD). At the same time, the dimensional approach to PD proposes looking through the disorders' subtypes and tracing lived experience-based commonalities. This study is the first to explore the temporality of PD by investigating the relationship between symptom severity and lived time and combining objectified measures of time perception with phenomenological interpretation. A total of 63 participants of various educational backgrounds, with personality disorders (36.5% male), following ICD-10 coding diagnosed with paranoid (3.2%), borderline (41.3%), narcissistic (33.3%), avoidant (4.8%), dependent (1.6%) and unspecified (15.9%) personality disorder. Levels of personality functioning and intensity of maladaptive trait domains were controlled with Level of Personality Functioning-Brief Scale 2.0 and Personality Inventory for ICD-11, respectively, resulting in the overall sample classification as comprising nine subclinical, 13 mild, 20 moderate, 16 severe, and five extremely severe conditions. Polish Short Version of the Zimbardo Time Perspective Inventory (PS-ZTPI) and Cottle's Circles Test (CT) were used to assess the temporal experience. In comparison to healthy individuals, those with PD are more oriented toward past negative (4.01 . 2.98) and less toward past positive (2.31 . 3.71) and future (3.04 . 3.47), as measured with PS-ZTPI; their pre-reflective temporal experience, as measured with CT, is dominated either by the past or the future, while the present remains marginalized. BPD distinctiveness among other PD lies in higher orientation toward hedonistic present and lower orientation toward the future. While the general temporal profile of PD is independent of age and duration of hospitalization, it is related to the severity of the condition. The more severe the impairments in self-functioning, the higher the negative past perspective and pre-reflective past dominance, and the lower the positive and future perspective. The results of this study highlight temporality as an essential aspect of lived experience in PD, being possibly related to disturbed self-experience.

While it is well known that illnesses such as cancer modify the experience of time, the impact of the rhythm and length of treatment on patients' time perspectives remains unknown. A short version of Zimbardo Time Perspective Inventory and Transcendental Future Perspective Questionnaire as well as a demographic questionnaire on a convenience sample of 259 patients (66.8% female, mean age 52.36) with various cancers and undergoing chemotherapy with different frequencies (1, 2, 3 weeks) and mean time in treatment 23.4 months. The temporal perspectives mean scores of cancer patients are: positive past 3.69, negative past 3.13, present hedonism 3.08, future 3.77, transcendental future 3.40. Patients tend only slightly to lose faith alongside the course of oncological treatment regardless of their age (  =  - 0.210,  < 0.01). The frequency of chemotherapy mildly differentiates temporal perspectives of patients regarding present hedonism and transcendental future: a weekly treatment is more disturbing than the triweekly one and no treatment in terms of hedonism, while patients not in chemo score significantly higher in transcendental future than patients in biweekly and triweekly chemo. The variations of treatment rhythm are less significant than predicted, although still relevant. Since most sociodemographic variables are of no relevance, cancer experience likely unifies temporal perspectives among people of different backgrounds.

The increasing deployment of conversational artificial intelligence (AI) in mental health interventions necessitates an evaluation of their efficacy in rectifying cognitive biases and recognizing affect in human-AI interactions. These biases are particularly relevant in mental health contexts as they can exacerbate conditions such as depression and anxiety by reinforcing maladaptive thought patterns or unrealistic expectations in human-AI interactions. This study aimed to assess the effectiveness of therapeutic chatbots (Wysa and Youper) versus general-purpose language models (GPT-3.5, GPT-4, and Gemini Pro) in identifying and rectifying cognitive biases and recognizing affect in user interactions. This study used constructed case scenarios simulating typical user-bot interactions to examine how effectively chatbots address selected cognitive biases. The cognitive biases assessed included theory-of-mind biases (anthropomorphism, overtrust, and attribution) and autonomy biases (illusion of control, fundamental attribution error, and just-world hypothesis). Each chatbot response was evaluated based on accuracy, therapeutic quality, and adherence to cognitive behavioral therapy principles using an ordinal scale to ensure consistency in scoring. To enhance reliability, responses underwent a double review process by 2 cognitive scientists, followed by a secondary review by a clinical psychologist specializing in cognitive behavioral therapy, ensuring a robust assessment across interdisciplinary perspectives. This study revealed that general-purpose chatbots outperformed therapeutic chatbots in rectifying cognitive biases, particularly in overtrust bias, fundamental attribution error, and just-world hypothesis. GPT-4 achieved the highest scores across all biases, whereas the therapeutic bot Wysa scored the lowest. Notably, general-purpose bots showed more consistent accuracy and adaptability in recognizing and addressing bias-related cues across different contexts, suggesting a broader flexibility in handling complex cognitive patterns. In addition, in affect recognition tasks, general-purpose chatbots not only excelled but also demonstrated quicker adaptation to subtle emotional nuances, outperforming therapeutic bots in 67% (4/6) of the tested biases. This study shows that, while therapeutic chatbots hold promise for mental health support and cognitive bias intervention, their current capabilities are limited. Addressing cognitive biases in AI-human interactions requires systems that can both rectify and analyze biases as integral to human cognition, promoting precision and simulating empathy. The findings reveal the need for improved simulated emotional intelligence in chatbot design to provide adaptive, personalized responses that reduce overreliance and encourage independent coping skills. Future research should focus on enhancing affective response mechanisms and addressing ethical concerns such as bias mitigation and data privacy to ensure safe, effective AI-based mental health support.

Growing reliance on LLMs for psychiatric self-assessment raises questions about their ability to interpret qualitative patient narratives. We present the first direct comparison between state-of-the-art LLMs and mental health professionals in diagnosing Borderline (BPD) and Narcissistic (NPD) Personality Disorders utilizing Polish-language first-person autobiographical accounts. We show that the top-performing Gemini Pro models surpassed human professionals in overall diagnostic accuracy by 21.91 percentage points (65.48% vs. 43.57%). While both models and human experts excelled at identifying BPD (F1 = 83.4 & F1 = 80.0, respectively), models severely underdiagnosed NPD (F1 = 6.7 vs. 50.0), showing a reluctance toward the value-laden term \"narcissism.\" Qualitatively, models provided confident, elaborate justifications focused on patterns and formal categories, while human experts remained concise and cautious, emphasizing the patient's sense of self and temporal experience. Our findings demonstrate that while LLMs are highly competent at interpreting complex first-person clinical data, they remain subject to critical reliability and bias issues.

Background: The increasing deployment of Conversational Artificial Intelligence (CAI) in mental health interventions necessitates an evaluation of their efficacy in rectifying cognitive biases and recognizing affect in human-AI interactions. These biases, including theory of mind and autonomy biases, can exacerbate mental health conditions such as depression and anxiety. Objective: This study aimed to assess the effectiveness of therapeutic chatbots (Wysa, Youper) versus general-purpose language models (GPT-3.5, GPT-4, Gemini Pro) in identifying and rectifying cognitive biases and recognizing affect in user interactions. Methods: The study employed virtual case scenarios simulating typical user-bot interactions. Cognitive biases assessed included theory of mind biases (anthropomorphism, overtrust, attribution) and autonomy biases (illusion of control, fundamental attribution error, just-world hypothesis). Responses were evaluated on accuracy, therapeutic quality, and adherence to Cognitive Behavioral Therapy (CBT) principles, using an ordinal scale. The evaluation involved double review by cognitive scientists and a clinical psychologist. Results: The study revealed that general-purpose chatbots outperformed therapeutic chatbots in rectifying cognitive biases, particularly in overtrust bias, fundamental attribution error, and just-world hypothesis. GPT-4 achieved the highest scores across all biases, while therapeutic bots like Wysa scored the lowest. Affect recognition showed similar trends, with general-purpose bots outperforming therapeutic bots in four out of six biases. However, the results highlight the need for further refinement of therapeutic chatbots to enhance their efficacy and ensure safe, effective use in digital mental health interventions. Future research should focus on improving affective response and addressing ethical considerations in AI-based therapy.

Building on a human-led thematic analysis of life-story interviews with inpatients with Borderline Personality Disorder, this study examines the capacity of large language models (OpenAI's GPT, Google's Gemini, and Anthropic's Claude) to support qualitative clinical analysis. The models were evaluated through a mixed procedure. Study A involved blinded and non-blinded expert judges in phenomenology and clinical psychology. Assessments included semantic congruence, Jaccard coefficients for overlap of outputs, multidimensional validity ratings of credibility, coherence, and the substantiveness of results, and their grounding in qualitative data. In Study B, neural methods were used to embed the theme descriptions created by humans and the models in a two-dimensional vector space to provide a computational measure of the difference between human and model semantics and linguistic style. In Study C, complementary non-expert evaluations were conducted to examine the influence of thematic verbosity on the perception of human authorship and content validity. Results of all three studies revealed variable overlap with the human analysis, with models being partly indistinguishable from, and also identifying themes originally omitted by, human researchers. The findings highlight both the variability and potential of AI-augmented thematic qualitative analysis to mitigate human interpretative bias and enhance sensitivity.

Background: Commonly, intramedullary nails are made of nondegradable materials, and hence they need to be removed once the bone fracture is healed. We propose a novel composite material consisting of poly-L-lactide matrix modified with carbon and alginate fibers to be used for biodegradable intramedullary fixation. The aim of this study was to make in vitro and in vivo biocompatibility assessments. Methods: In the in vitro conditions, biocompatibility of biomaterials was compared using normal human osteoblasts. After 3 and 7 days, cytotoxicity, viability and proliferation tests were performed, as well as cell morphology and adhesion observations. In the in vivo experiments, Californian rabbits (approx. 9 months old) were used. The composite nails and controls (Kirschner wires) were used for fixation of distal femoral osteotomy. The evaluation was made on the basis of clinical observations, radiographs taken after 2, 4, 6 and 8 weeks post implantation, and macroscopic and histological observations. Results: Cell tests indicated that both modifiers had a positive influence on cell viability. Biodegradable composite nails led to bony union when used for fixation of distal diaphysis osteotomy in rabbits. Histological analysis showed that the initial focal necrosis should be fully compensated for by the osteoblast proliferation and trabeculae formation. Conclusions: Both in vitro and in vivo tests confirmed biocompatibility and potential applicability of novel biodegradable intramedullary nails modified with long carbon and alginate fibers for osteosynthesis of bone epiphysis.