The rapid rise of ChatGPT has introduced a transformative tool that enhances productivity, communication, and task automation across industries. However, concerns are emerging regarding the addictive potential of AI large language models. This paper explores how ChatGPT fosters dependency through key features such as personalised responses, emotional validation, and continuous engagement. By offering instant gratification and adaptive dialogue, ChatGPT may blur the line between AI and human interaction, creating pseudosocial bonds that can replace genuine human relationships. Additionally, its ability to streamline decision-making and boost productivity may lead to over-reliance, reducing users' critical thinking skills and contributing to compulsive usage patterns. These behavioural tendencies align with known features of addiction, such as increased tolerance and conflict with daily life priorities. This viewpoint paper highlights the need for further research into the psychological and social impacts of prolonged interaction with AI tools like ChatGPT.

An emerging body of evidence indicates that short-term immersion in cold water facilitates positive affect and reduces negative affect. However, the neural mechanisms underlying these effects remain largely unknown. For the first time, we employed functional magnetic resonance imaging (fMRI) to identify topological clusters of networks coupled with behavioural changes in positive and negative affect after a 5 min cold-water immersion. Perceived changes in positive affect were associated with feeling more active, alert, attentive, proud, and inspired, whilst changes in negative affect reflected reductions in distress and nervousness. The increase in positive affect was supported by a unique component of interacting networks, including the medial prefrontal node of the default mode network, a posterior parietal node of the frontoparietal network, and anterior cingulate and rostral prefrontal parts of the salience network and visual lateral network. This component emerged as a result of a focal effect confined to few connections. Changes in negative affect were associated with a distributed component of interacting networks at a reduced threshold. Affective changes after cold-water immersion occurred independently, supporting the bivalence model of affective processing. Interactions between large-scale networks linked to positive affect indicated the integrative effects of cold-water immersion on brain functioning.

There is growing interest in understanding how people interact with large language models (LLMs) and whether such models elicit dependency or even addictive behaviour. Validated tools to assess the extent to which individuals may become dependent on LLMs are scarce and primarily build on classic behavioral addiction symptoms, adapted to the context of LLM use. We view this as a conceptual limitation, as the LLM-human relationship is more nuanced and warrants a fresh and distinct perspective. To address this gap, we developed and validated a new 12-item questionnaire to measure LLM dependency, referred to as LLM-D12. The scale was based on the authors' prior theoretical work, with items developed accordingly and responses collected from 526 participants in the UK. Exploratory and confirmatory factor analyses, performed on separate halves of the total sample using a split-sample approach, supported a two-factor structure: Instrumental Dependency (six items) and Relationship Dependency (six items). Instrumental Dependency reflects the extent to which individuals rely on LLMs to support or collaborate in decision-making and cognitive tasks. Relationship Dependency captures the tendency to perceive LLMs as socially meaningful, sentient, or companion-like entities. The two-factor structure demonstrated excellent internal consistency and clear discriminant validity. External validation confirmed both the conceptual foundation and the distinction between the two subscales. The psychometric properties and structure of our LLM-D12 scale were interpreted in light of the emerging view that dependency on LLMs does not necessarily indicate dysfunction but may still reflect reliance levels that could become problematic in certain contexts.

Background: Outdoor swimming in lakes, lidos (outdoor pools), rivers, and the sea has grown in popularity in many countries, including the United Kingdom. Many anecdotal accounts indicate improvements in medical conditions, which are considered a consequence of outdoor swimming. Objective: The aim of this study is to better understand outdoor swimmers’ perceptions of their health and the extent to which participation impacted their existing self-reported symptoms. Methods: A survey was conducted to investigate outdoor swimming behaviors and reports of any diagnosed medical conditions. Medical conditions were coded into categories, and descriptive statistics were generated regarding the outdoor swimmers’ behaviors and the effect that outdoor swimming had on their medical symptoms if any. The medical categories were clustered into five larger categories based on their prevalence in the current sample: mental health; musculoskeletal and injury; neurological; cardiovascular and blood disease; and other, which comprises inflammatory, immune, endocrine, and respiratory conditions. Results: In total, 722 outdoor swimmers responded, of whom 498 (68.9%) were female. The probability of outdoor swimming having some positive impact on health across all medical categories was 3.57 times higher compared with no impact (B=1.28, 95% CI 0.63-1.91; P<.001), 44.32 times higher for the mental health category (B=3.79, 95% CI 2.28-5.30; P<.001), 5.25 times higher for musculoskeletal and injury category (B=1.66, 95% CI 0.52-2.79; P=.004), and 4.02 times higher for the other category (B=1.39, 95% CI 0.27-2.51; P=.02). Overall, outdoor swimming was associated with perceived reductions in symptoms of poor mental health (χ22=25.1; P<.001), musculoskeletal and injury (χ22=8.2; P=.04), cardiovascular and blood (χ22=14.7; P=.006), and other conditions (χ22=18.2; P<.001). Conclusions: Physical activity in the form of outdoor swimming is perceived to have positive impacts on health and is associated with perceived symptom reductions in mental health, musculoskeletal and injury, and cardiovascular and blood conditions. This study cannot provide causal relationships or provide mechanistic insights. However, it does provide a starting point for more targeted prospective intervention research into individual conditions or categories of conditions to establish the impact in those who choose to start outdoor swimming.

Self and emotions are key motivational factors of a person strivings for health and well-being. Understanding neural mechanisms supporting the relationship between these factors bear far-reaching implications for mental health disorders. Recent work indicates a substantial overlap between self-relevant and emotion information processing and has proposed the medial prefrontal cortex (MPFC) as one shared neural signature. However, the precise cognitive and neural mechanisms represented by the MPFC in investigations of self- and emotion-related processing are largely unknown. Here we examined whether the neural underpinnings of self-related processing in the MPFC link to positive or negative emotions. We collected fMRI data to test the distinct and shared neural circuits of self- and emotion-related processing while participants performed personal (self, friend, or stranger) and emotion (happy, sad, or neutral) associative matching tasks. By exploiting tight control over the factors that determine the effects of self-relevance and emotions (positive: Happy vs. neutral; negative: Sad vs. neutral), our univariate analysis revealed that the ventral part of the MPFC (vmPFC), which has established involvement in self-prioritisation effects, was not recruited in the negative emotion prioritisation effect. In contrast, there were no differences in brain activity between the effects of positive emotion- and self-prioritisation. These results were replicated by both region of interest (ROI)-based analysis in the vmPFC and the seed- to voxel functional connectivity analysis between the MPFC and the rest of the brain. The results suggest that the prioritisation effects for self and positive emotions are tightly linked together, and the MPFC plays a large role in discriminating between positive and negative emotions in relation to self-relevance.