Anat Shoshani

Conversational AI is emerging as a scalable tool for psychological support, yet its clinical effectiveness and the relational factors underlying user benefit remain underexplored. This pre-registered randomized controlled trial ( N = 977 university students; ages 18–32) compared an AI-based conversational intervention, integrative group therapy, and a waitlist control over 12 weeks, with a 3-month follow-up. The AI intervention produced greater reductions in generalized anxiety symptoms and stronger gains in well-being and life satisfaction than both comparators at post-intervention and follow-up and reduced depression relative to control. Group therapy improved depression at post-intervention and enhanced well-being and life satisfaction, with well-being maintained at follow-up. PTSD symptoms showed no group differences. Relational factors, including loneliness, low perceived social support, and insecure attachment, predicted greater improvement and higher engagement with the AI system, particularly among participants with anxious or avoidant attachment. Participants with high loneliness engaged approximately twice as much with the AI intervention as those with low loneliness, and the association between relational vulnerability and reductions in generalized anxiety symptoms was fully mediated by engagement. Findings suggest that adaptive conversational AI can complement traditional care while addressing relational vulnerability.

Introduction: Behavioral addictions in childhood and adolescence remain understudied, particularly beyond digital media use. The COVID-19 pandemic introduced substantial disruptions to youths' daily routines, social functioning, and emotional well-being, potentially increasing vulnerability to maladaptive behavioral patterns. This three-wave longitudinal study examined trajectories and correlates of gambling, shopping, exercise, and eating addiction symptoms among children and adolescents across the pandemic period. Methods: The study included 1,665 Israeli students aged 9-16.7 years assessed before the COVID-19 pandemic (October 2019), after the first wave (November 2020), and after the fifth wave and return to regular schooling (April 2022). Participants completed validated measures of behavioral addiction symptoms, psychiatric symptoms, negative and positive affect, sensation seeking, life satisfaction, social support, secure attachment, hope, future orientation, grit, and gratitude. Structural equation modeling tested indirect effects of protective factors on behavioral addictions via risk factors at baseline, and linear growth-curve models estimated change in addiction symptoms over time. Results: Symptoms of exercise, gambling, and shopping addictions increased significantly across the three time points, whereas eating addiction symptoms remained stable. Negative affect, psychiatric symptoms, and sensation seeking predicted higher levels of behavioral addiction, and social support was unexpectedly associated with higher exercise, gambling, and eating addiction symptoms. In contrast, future orientation, life satisfaction, hope, positive emotions, and secure attachment were linked to fewer symptoms. Protective factors were related to lower behavioral addiction symptoms only indirectly, through their associations with reduced negative affect and psychiatric symptoms, indicating full mediation. Girls reported more shopping and eating addiction symptoms, whereas boys reported more gambling and exercise symptoms; older age was linked to fewer shopping, exercise, and eating symptoms but more gambling symptoms. Discussion: These findings suggest that youth behavioral addictions intensified during and after the pandemic, even when most symptoms remained subclinical. Emotional and social resources functioned as resilience factors primarily by shaping mental health, highlighting negative affect and psychiatric distress as key intervention targets to prevent behavioral addictions in children and adolescents.

Importance: Accessible, scalable interventions for psychiatric symptoms are needed to address global mental health care gaps. Conversational artificial intelligence (AI) may extend access by providing personalized support, yet rigorous evidence of efficacy and therapeutic mechanisms remains scarce. Objectives: To evaluate the efficacy of a conversational AI–based mental health platform for psychiatric symptoms, and to assess how perceived therapeutic alliance contributes to user engagement and psychological outcomes. Design, Setting, and Participants: This 3-arm randomized clinical trial was conducted in Israel from April 1 to October 27, 2025, including the 12-week intervention and 3-month follow-up period. Participants were university students who reported psychological distress. Interventions: Participants were randomly assigned 1:1:1 to a 12-week AI-based conversational platform, face-to-face group therapy, or waiting list control. Main Outcomes and Measures: The primary outcomes were anxiety (Generalized Anxiety Disorder-7), depression (Patient Health Questionnaire-9), posttraumatic stress disorder (PTSD; PTSD Checklist for DSM-5 ), well-being (World Health Organization-5 Well-Being Index), and life satisfaction (Brief Multidimensional Students’ Life Satisfaction Scale) measures at the end of the 12-week intervention. Analyses followed the intention-to-treat principle. Results: In total, 995 participants (mean [SD] age, 23.1 [2.4] years; 504 [50.7%] female) were included in analyses, with 336 randomized to the AI intervention, 331 to group therapy, and 328 to waiting list control. After the intervention, participants in the AI group showed greater anxiety reduction than those in group therapy (mean difference [MD], −2.17 [95% CI, −2.67 to −1.67]) or control (MD, −2.15 [95% CI, −2.65 to −1.65]) and greater depression reduction than control (MD, −1.99 [95% CI, −2.63 to −1.35]). PTSD symptoms did not differ among groups. The AI group also showed greater improvements in well-being than group therapy (MD, 5.72 [95% CI, 2.71 to 8.73]) and control (MD, 9.16 [95% CI, 6.14 to 12.18]). Structural equation modeling indicated that perceived therapeutic alliance was associated with engagement (β = 0.31 [95% CI, 0.16 to 0.43]; P < .001) and symptom improvement (β = –0.58 [95% CI, –0.69 to –0.46]; P < .001). Conclusions and Relevance: In this randomized clinical trial of university students with psychological distress, the use of a conversational AI agent was associated with improvements in anxiety, depression, well-being, and life satisfaction, and its perceived therapeutic alliance was associated with engagement and psychological improvement. These findings suggest that conversational AI may serve as a scalable resource within mental health frameworks. Trial Registration: ISRCTN Registry Identifier: ISRCTN61075527

Objective: This longitudinal study investigated the associations between exposure to political violence and screen and substance use in 1646 Israeli adolescents (aged 12–17) from southern Israel, an area significantly impacted by an ongoing war and conflict. Methods: The data were collected at two time points: shortly after the outbreak of the war (October 2023) and at the end of the school year (June 2024). It examined changes in digital engagement, including internet and social media use, trends in substance use (tobacco, alcohol, vaping, and cannabis), and how political life events and psychiatric symptoms influenced these behaviors. Results: The findings revealed significant increases in screen time, particularly internet and social media use, that correlated with heightened exposure to political violence and worsening psychiatric symptoms. Tobacco use decreased slightly, while alcohol consumption increased. Older participants engaged less in gaming but more in social media. Boys reported higher levels of gaming but lower social media, alcohol and vaping use than girls. Conclusions: These findings underscore the urgent need for interventions addressing the interrelated challenges of digital media consumption and substance use in youth exposed to war‐related conflicts.

The COVID-19 pandemic has heightened children's and adolescents' risk of experiencing long-term mental health problems and a decline in subjective well-being. To better understand the longitudinal impact of COVID-19, this study explored the role of demographic variables and the potential moderating effects of social support and daily routines as resilience factors. A nationally representative, longitudinal cohort of 5,217 Israeli children and adolescents aged 10-15 at baseline completed measures of mental health symptoms, life satisfaction, positive and negative emotions, gratitude, social support, and daily routines. Data were collected in school at four measurement points: September 2019 (before the outbreak of COVID-19; N = 5,127), May 2020 (after the first lockdown; N = 4,698), May 2021 (after the third wave lockdown; N = 4,813), and May 2022 (after the fourth and fifth waves of the pandemic; N = 4,897). The data were analyzed using multilevel mixed models. Significant increases in depression, anxiety, and panic along with decreases in psychological well-being were found as a function of time. These effects were moderated by age and gender. Participants with high social support and structured daily routines reported smaller increases in mental health symptoms than students with low social support or irregular daily routines. There is a critical need for clinical and educational interventions for young people during this period to promote the resilience factors that can moderate well-being and counter the decline in mental health. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

This longitudinal study examined the long-term effects of the COVID-19 pandemic on social media use and its impact on psychiatric symptoms and well-being of 3,697 Israeli children and adolescents aged 8 to 14. Data were collected from October 2019 to June 2023, covering four school years and five measurement points prior to, throughout and post- COVID-19. Social media usage, psychiatric symptoms (depression, anxiety, somatization, and general distress), as well as subjective well-being (positive and negative emotions, and life satisfaction) were assessed. The analysis also probed the extent to which social support and extracurricular activities moderated the associations between social media use and mental health outcomes. The results of the growth mixed-effects models indicated a significant increase in social media use and psychiatric symptoms, and a significant decrease in subjective well-being over time. Greater social media use was related to more psychiatric symptoms and negative emotions, but also to more positive emotions and life satisfaction. Social support buffered the negative effects of excessive social media use on mental health, whereas extracurricular activities increased positive emotions, but also psychiatric symptoms related to social media use. These findings highlight the need for targeted interventions to regulate social media usage, given its lasting consequences on the mental health of children and adolescents in the wake of the COVID-19 pandemic.