Objectives: Chatbots, transcending the limitations of space and time while reducing user resistance, offer a personalized and autonomous approach potentially enhancing digital health interventions. This systematic review aims to quantitatively evaluate the effectiveness of chatbot-based exercise interventions (EIs) in randomized controlled trials (RCTs), emphasizing physical activity (PA), exercise habits (EH), and sedentary behavior (SB). Methods: A comprehensive search was carried out across Embase, Web of Science, PubMed, and Cochrane databases for studies published from January 2010 to October 2024. The characteristics of the included studies and the employed chatbots were analyzed. A meta-analysis was performed to synthesize the impact of chatbot-based EIs on PA, EH, and SB. We carried out subgroup analyses (SAs) for investigating potential modifying effects. Results: This review includes 12 studies conducted between 2013 and 2024, encompassing 2446 participants and 240 parent-child dyads, with participant ages ranging from 8 to 71 years. The chatbot-based EIs significantly enhanced PA compared to control groups (SMD = 0.20, 95% CI = 0.04–0.37, p = 0.02; I² = 51%, p = 0.04). However, these interventions did not significantly impact EH (SMD = 0.29, 95% CI = −0.48–1.06, p = 0.46) or reduce SB (SMD = 0.32, 95% CI = −0.54–1.19, p = 0.46). Notably, SAs revealed a small but significant short-term increase in EH (SMD = 0.29, 95% CI = 0.08–0.50, p = 0.006). Conclusion: Chatbot-based EIs appear promising in improving PA, particularly moderate to vigorous PA (MVPA). Nonetheless, further RCTs with diverse chatbot designs, larger sample sizes, low-resource settings, objective measures of SB (e.g., accelerometers), and extended follow-ups are essential to corroborate these findings. Future research should also explore the adaptation of chatbots to various socioeconomic and cultural contexts and the integration of technologies like ChatGPT into EIs. Trial Registration: Meta-analysis PROSPERO: CRD42024609852

Objective: This study aimed to investigate the role of the gut microbiome in androgenetic alopecia (AGA) among obese individuals using Mendelian randomization (MR), and to identify potential therapeutic targets for mitigating AGA in this population. Methods: Genomic data for 412 gut microbiomes, AGA, and obesity were obtained from genome-wide association studies (GWAS). Bidirectional MR was performed using inverse variance weighted (IVW) as the primary analysis method, complemented by sensitivity analyses. Potential therapeutic targets within the gut microbiome associated with AGA in obese individuals were identified. Results: Two gut microbiomes were identified as having a significant impact on obese individuals with AGA. Specifically, the abundance of the sulfoglycolysis pathway in gut bacteria was found to significantly increase the risk of both obesity and AGA. In contrast, the abundance of the de novo biosynthesis of the adenosine ribonucleotide pathway in gut bacteria was associated with a significant increase in the risk of obesity but a significant decrease in the risk of AGA. Conclusions: The abundance of gut bacterial pathways, including sulfoglycolysis and the de novo biosynthesis of adenosine ribonucleotides, can serve as potential therapeutic targets for managing obesity-associated AGA. These findings offer a novel research direction for the development of innovative diagnostic and treatment strategies for patients with obesity and AGA.