Importance Generative artificial intelligence (AI) has rapidly entered mainstream use in the US, but its association with mental health has not been characterized. Objective To examine the associations of the extent and type of generative AI use among US adults with negative affective symptoms in a large, nationally representative sample. Design, Setting, and Participants This survey study used data from a 50-state US internet nonprobability survey conducted between April and May 2025. Survey respondents were aged 18 years and older. Data were analyzed in August 2025. Exposure Participants self-reported generative AI and social media use. Main Outcomes and Measures The outcome of interest, negative affect, was measured using the Patient Health Questionnaire 9-item (PHQ-9). Results There were 20 847 unique participants, with mean (SD) age 47.3 (17.1) years and 10 327 (49.5%) female, 10 386 (49.8%) male, and 134 (0.6%) nonbinary participants; 2152 participants (10.3%) reported using AI at least daily, including 1053 participants (5.1%) who reported daily use and 1099 participants (5.3%) who reported use multiple times per day. Among participants who used daily or more frequently, 1033 (48.0%) reported use for work, 246 (11.4%) for school, and 1875 (87.1%) for personal applications. In survey-weighted regression models, daily or more frequent AI use was significantly more common among men, younger adults, those with higher education and income, and those in urban settings. Greater AI use was associated with greater levels of depressive symptoms in sociodemographic-adjusted regression models: (daily use: β = 1.08 [95% CI, 0.55-1.62]; multiple times per day: β = 0.86 [95% CI, 0.35-1.37]) compared with nonuse, and with greater likelihood of reporting at least moderate depressive symptoms (odds ratio [OR], 1.29 [95% CI, 1.15-1.46]); similar patterns were observed for anxiety and irritability. The highest estimates were observed among individuals using AI for personal use (β = 0.31 [95% CI, 0.10-0.52]) and those aged 25 to 44 years (β = 1.22 [95% CI, 0.70-1.74]) or 45 to 64 years (β = 1.38 [95% CI, 0.72-2.05]). Conclusions and Relevance This survey study found that AI use was significantly associated with greater depressive symptoms, with magnitude of differences varying by age group. Further work is needed to understand whether these associations are causal and explain heterogeneous effects.
Generative AI Use and Depressive Symptoms Among US Adults
This survey study examines the associations of generative artificial intelligence (AI) use with negative affective symptoms in a large nationally representative sample of US adults.
Americans are increasingly concerned about AI exacerbating mental health problems
One in 10 Americans (10%) say they definitely (2%) or probably (8%) could form a deep emotional bond with an AI chatbot companion.
Using AI for advice or other personal reasons is linked to depression and anxiety
A new survey found that people who spend more time with chatbots for social interactions or emotional support were likelier to report mental health symptoms.
“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health
The global mental health crisis underscores the need for accessible, effective interventions. Chatbots based on generative artificial intelligence (AI), like ChatGPT, are emerging as novel solutions, but research on real-life usage is limited. We interviewed nineteen individuals about their experiences using generative AI chatbots for mental health. Participants reported high engagement and positive impacts, including better relationships and healing from trauma and loss. We developed four themes: (1) a sense of ‘emotional sanctuary’, (2) ‘insightful guidance’, particularly about relationships, (3) the ‘joy of connection’, and (4) comparisons between the ‘AI therapist’ and human therapy. Some themes echoed prior research on rule-based chatbots, while others seemed novel to generative AI. Participants emphasised the need for better safety guardrails, human-like memory and the ability to lead the therapeutic process. Generative AI chatbots may offer mental health support that feels meaningful to users, but further research is needed on safety and effectiveness.
“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health
The global mental health crisis underscores the need for accessible, effective interventions. Chatbots based on generative artificial intelligence (AI), like ChatGPT, are emerging as novel solutions, but research on real-life usage is limited. We interviewed nineteen individuals about their experiences using generative AI chatbots for mental health. Participants reported high engagement and positive impacts, including better relationships and healing from trauma and loss. We developed four themes: (1) a sense of ‘emotional sanctuary’, (2) ‘insightful guidance’, particularly about relationships, (3) the ‘joy of connection’, and (4) comparisons between the ‘AI therapist’ and human therapy. Some themes echoed prior research on rule-based chatbots, while others seemed novel to generative AI. Participants emphasised the need for better safety guardrails, human-like memory and the ability to lead the therapeutic process. Generative AI chatbots may offer mental health support that feels meaningful to users, but further research is needed on safety and effectiveness.
The gen AI gender gap
Data from the Survey of Consumer Expectations shows that 50% of men use generative AI tools, compared to 37% of women. Privacy concerns and perceived opportunities and risks explain a quarter of the gender gap. Respondents’ self-assessed knowledge emerges as the most important factor.
Gender differences in artificial intelligence: the role of artificial intelligence anxiety
IntroductionArtificial intelligence (AI) is having a significant impact on people's lives. Despite the benefits associated with this technological advancement, there may be gender-related inequalities in accessing and using AI systems. The present study aimed to test gender differences in factors likely to influence AI adoption, in particular, the moderating role of gender in the relationship between AI anxiety and positive attitudes toward AI.MethodParticipants were 335 adults (52.2% women; mean age = 29.96, SD = 13.88) who filled in an online self-report anonymous questionnaire. To test the hypotheses, both a MANOVA and a moderation model were adopted.ResultsResults revealed significant gender differences in AI adoption dimensions, with women reporting higher AI anxiety, lower positive attitudes toward AI, lower use of AI, and lower perceived knowledge of AI. A significant negative relationship was found between AI anxiety and positive attitudes toward AI. An interaction between gender and AI anxiety was found: At low levels of anxiety, women showed lower levels of positive attitudes toward AI than men, while at high levels of AI anxiety, gender differences were less evident.DiscussionThese findings suggest that AI anxiety works as a “gender differences leveler.” The present study contributes to expanding knowledge about gender differences in technology, which will underpin practical interventions for reducing the gender digital gap. Limitations and future research directions are discussed.
Anthropomorphism in AI Companion Communities: Age, Gender, and Emotional Correlates
Artificial intelligence (AI) systems are increasingly integrated into daily life, with millions now using AI chatbots built on Large Language Models (LLMs) for companionship. Both humanlike AI qualities and user predispositions to anthropomorphize relate to social consequences, such as increased trust, social health benefits, and psychological harms. Populations such as children, older adults, or those with mental health vulnerabilities may be particularly susceptible to anthropomorphism and its detriments, but mixed findings complicate the role of demographics. We used publicly available Reddit data from three popular AI companion subreddits to assess relationships between gender, age, anthropomorphism, and elicited emotions, to better understand how different people perceive and are affected by AI companions. We investigated three questions: How do age and gender relate to anthropomorphization of AI?, How does emotional expression relate to anthropomorphization?, and How do age and gender moderate emotion-anthropomorphization relationships? We found that adults and women anthropomorphize AI chatbots more than teens and men, and that positive emotional expression, particularly joy, is positively associated with anthropomorphization, while neutrality is negatively associated with anthropomorphism. Both relationships were stronger in adults than teens. Our findings suggest that the tendency to anthropomorphize may be more broadly distributed across age groups than previously expected, thereby prompting the reevaluation of existing digital safety norms.
Gender differences in artificial intelligence: the role of artificial intelligence anxiety
INTRODUCTION: Artificial intelligence (AI) is having a significant impact on people's lives. Despite the benefits associated with this technological advancement, there may be gender-related inequalities in accessing and using AI systems. The present study aimed to test gender differences in factors likely to influence AI adoption, in particular, the moderating role of gender in the relationship between AI anxiety and positive attitudes toward AI. METHOD: Participants were 335 adults (52.2% women; mean age = 29.96, SD = 13.88) who filled in an online self-report anonymous questionnaire. To test the hypotheses, both a MANOVA and a moderation model were adopted. RESULTS: Results revealed significant gender differences in AI adoption dimensions, with women reporting higher AI anxiety, lower positive attitudes toward AI, lower use of AI, and lower perceived knowledge of AI. A significant negative relationship was found between AI anxiety and positive attitudes toward AI. An interaction between gender and AI anxiety was found: At low levels of anxiety, women showed lower levels of positive attitudes toward AI than men, while at high levels of AI anxiety, gender differences were less evident. DISCUSSION: These findings suggest that AI anxiety works as a "gender differences leveler." The present study contributes to expanding knowledge about gender differences in technology, which will underpin practical interventions for reducing the gender digital gap. Limitations and future research directions are discussed.
How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study
As people increasingly seek emotional support and companionship from AI chatbots, understanding how such interactions impact mental well-being becomes critical. We conducted a four-week randomized controlled experiment (n=981, >300k messages) to investigate how interaction modes (text, neutral voice, and engaging voice) and conversation types (open-ended, non-personal, and personal) influence four psychosocial outcomes: loneliness, social interaction with real people, emotional dependence on AI, and problematic AI usage. No significant effects were detected from experimental conditions, despite conversation analyses revealing differences in AI and human behavioral patterns across the conditions. Instead, participants who voluntarily used the chatbot more, regardless of assigned condition, showed consistently worse outcomes. Individuals' characteristics, such as higher trust and social attraction towards the AI chatbot, are associated with higher emotional dependence and problematic use. These findings raise deeper questions about how artificial companions may reshape the ways people seek, sustain, and substitute human connections.
We Need to Know More About How AI is Affecting Mental Health
The public, mental health practitioners, and policymakers don’t know enough about the impacts of AI use on the human psyche, writes Chris Mills Rodrigo.
Investigating Affective Use and Emotional Well-being on ChatGPT
As AI chatbots see increased adoption and integration into everyday life, questions have been raised about the potential impact of human-like or anthropomorphic AI on users. In this work, we investigate the extent to which interactions with ChatGPT (with a focus on Advanced Voice Mode) may impact users' emotional well-being, behaviors and experiences through two parallel studies. To study the affective use of AI chatbots, we perform large-scale automated analysis of ChatGPT platform usage in a privacy-preserving manner, analyzing over 3 million conversations for affective cues and surveying over 4,000 users on their perceptions of ChatGPT. To investigate whether there is a relationship between model usage and emotional well-being, we conduct an Institutional Review Board (IRB)-approved randomized controlled trial (RCT) on close to 1,000 participants over 28 days, examining changes in their emotional well-being as they interact with ChatGPT under different experimental settings. In both on-platform data analysis and the RCT, we observe that very high usage correlates with increased self-reported indicators of dependence. From our RCT, we find that the impact of voice-based interactions on emotional well-being to be highly nuanced, and influenced by factors such as the user's initial emotional state and total usage duration. Overall, our analysis reveals that a small number of users are responsible for a disproportionate share of the most affective cues.
Measuring Usage in the Age of AI - Research Information
Tasha Mellins-Cohen outlines COUNTER Metrics' new guidance for usage metrics associated with generative and agentic AI
Americans Turning to AI to Supplement Healthcare Visits
One in four Americans use AI for health information. Most do so to supplement care, but some are using AI in place of a provider visit when barriers arise.
Generative artificial intelligence reliance and executive function attenuation: Behavioral evidence of cognitive offload in high-use adults.
Women Worry, Men Adopt: How Gendered Perceptions Shape the Use of Generative AI
Generative artificial intelligence (GenAI) is diffusing rapidly, yet its adoption is strikingly unequal. Using nationally representative UK survey data from 2023 to 2024, we show that women adopt GenAI substantially less often than men because they perceive its societal risks differently. We construct a composite index capturing concerns about mental health, privacy, climate impact, and labor market disruption. This index explains between 9 and 18 percent of the variation in GenAI adoption and ranks among the strongest predictors for women across all age groups, surpassing digital literacy and education for young women. Intersectional analyses show that the largest disparities arise among younger, digitally fluent individuals with high societal risk concerns, where gender gaps in personal use exceed 45 percentage points. Using a synthetic twin panel design, we show that increased optimism about AI's societal impact raises GenAI use among young women from 13 percent to 33 percent, substantially narrowing the gender divide. These findings indicate that gendered perceptions of AI's social and ethical consequences, rather than access or capability, are the primary drivers of unequal GenAI adoption, with implications for productivity, skill formation, and economic inequality in an AI enabled economy.