Despite skepticism and distrust in artificial intelligence (AI), it is increasingly integrated into daily life, with its potential benefits drawing interest. Yet little is known about the attitudinal and psychological effects of human–AI interactions, and whether consistent interactions with AI chatbots can change users’ attitudes and perceptions. Our within-subjects experiment (N = 52) investigated how five days of socially oriented, friendlike interactions with an AI chatbot, versus a journaling control, influenced changes in attitudes and perceptions of AI. Participants’ attitudes towards AI, trust, perceived empathy, anthropomorphism, animacy, likeability, perceived intelligence and safety, dependency, and exploratory well-being indicators were recorded. Results indicated that consistent friendlike interaction with AI chatbots led to significant increases in perceived empathy and animacy of technology, but no changes in global attitudes and perceptions of anthropomorphism. Participants also reported higher self-esteem levels after journaling, compared to after AI interaction. This suggests that although friendly engagement with AI chatbots may lead to perceptions of empathy and lifelikeness, where users interpret it to be genuinely understanding and supportive, this comes with trade-offs for self-esteem. Concurrently, empathy and perceived lifelikeness increased without corresponding increases in anthropomorphism, indicating that users may regard AI chatbots as separate living entities rather than having human-like qualities.

We provide a step-by-step guide on conducting a quantitative systematic review (i.e., meta-analysis) using the open-source programming language R , as well as conducting a multilevel meta-analysis, in contexts where effect sizes are non-independent (e.g., multiple studies from the same lab). Quantitative systematic reviews offer researchers a method for synthesizing large bodies of literature, helping clarify inconsistent findings, identify research gaps, and refine theoretical models. However, existing tutorials often assume prior knowledge and/or experience, often overlooking foundational concepts. To address this gap, a comprehensive walkthrough of the systematic review process is presented, covering pre-registration, literature search and retrieval, screening, risk of bias assessment, and data extraction following the PRISMA framework. We then present detailed guidance on how to conduct both traditional and multilevel meta-analyses in R . Specifically, the tutorial explains how to estimate overall meta-analytic effect sizes when effect sizes are independent (traditional meta-analysis) and when effect sizes are nested within labs (multilevel meta-analysis). Procedures for assessing heterogeneity, testing for publication bias, and conducting moderation analyses are also covered. To accompany this tutorial, we supplement annotated R scripts and R notebooks to support transparency, reproducibility, and accessibility for researchers of all levels of experience.

Background: Cognitive and behavioral interventions have risen in popularity both as an adjunctive treatment to antipsychotic medication and as an alternative treatment for schizophrenia. With the growing number of such interventions, we performed an umbrella review to provide a comprehensive summary comparing the effectiveness of the different interventions among populations with schizophrenia. Methods: This umbrella review included meta-analyses evaluating cognitive and behavioral interventions for schizophrenia. Following PRISMA guidelines, the initial search yielded 4888 records, and after a three-stage screening procedure, 33 meta-analyses met the inclusion criteria for the final analysis. Results: Our findings from the 33 meta-analyses support the efficacy of cognitive and behavioral interventions in reducing total symptoms (Median g = −0.38; Range g = −1.56 to −0.08), positive symptoms (Median g = −0.30; Range g = −0.84 to 0.00), and negative symptoms (Median g = −0.39; Range g = −0.66 to −0.09) of schizophrenia. Cognitive Behavioral Therapy, being the most common intervention studied, exhibited small to medium effects on total and positive symptom alleviation. In addition, there is evidence supporting the effectiveness of family psychoeducation combined with patient behavioral and skills training, exercise therapy, horticultural therapy, and music therapy. Conclusions: While our umbrella review solidifies the current evidence supporting cognitive and behavioral interventions as effective treatments for schizophrenia, it also reveals that treatment efficacy is highly dependent on the type of intervention used.

Background: Mindfulness has been shown to enhance emotional well-being and cognitive performance, yet much of this evidence stems from interventions requiring prolonged practice, making them time-consuming and less accessible. Recent studies suggest that brief mindfulness sessions may also yield positive outcomes, but the effectiveness of such interventions in virtual reality (VR) and mixed reality (MR) remains underexplored. Objective: This study investigates the effects of brief mindfulness breathing exercises delivered through VR and MR on attentional and emotional restoration and self-control capacity. Methods: Using a within-subjects experimental design, 102 undergraduate participants (n=83, 81.4% female; mean age 20.87, SD 1.89 ) completed a brief (approximately 15 min) VR and MR mindfulness breathing intervention delivered via a head-mounted display and a duration-matched mind-wandering audio control condition. Participants were undergraduates recruited via convenience sampling from psychology courses in a local university in Singapore. These conditions were separated by a 1-week washout period. Emotional well-being and self-control capacity were measured at baseline and post treatment, using self-report measures, whereas working memory capacity was measured at both time points, using operation span at baseline and rotation span post treatment. Results: Repeated-measures ANOVAs (α=.05) indicated that VR and MR mindfulness breathing conditions significantly enhanced positive affect ( P <.001, η _p ²=0.366), reduced negative affect ( P <.001, η _p ²=0.279), and improved self-control capacity ( P <.001, η _p ²=0.219), compared with the mind-wandering control condition. In contrast, no significant differences were observed for working memory, and Bayesian analyses provided moderate evidence in support of the null hypothesis for both the main effect of condition and the time×condition interaction (BF ₀₁ =7.42 and BF ₀₁ =5.55, respectively). Participants reported significantly greater absorption in the VR and MR conditions than in the control condition (Cohen’s d =−1.61, 95% CI −1.91 to −1.32). Conclusions: These findings suggest that a brief VR and MR mindfulness breathing exercise improves emotional well-being and self-control capacity relative to a mind-wandering control but does not yield short-term benefits for working memory. In contrast to existing studies that typically emphasize stress reduction or rely on multisession digital interventions, this study highlights that a single brief VR or MR session can enhance key emotional and self-regulatory outcomes. As such, these results underscore the potential of VR and MR mindfulness interventions as scalable and accessible tools for promoting mental well-being, while also pointing to the need for further research to optimize their cognitive impact.