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Evaluation of a Guided Chatbot Intervention for Young People in Jordan: Feasibility Randomized Controlled Trial

Evaluation of a Guided Chatbot Intervention for Young People in Jordan: Feasibility Randomized Controlled Trial

All STARS completers said the 15-minute call duration was suitable. Reasons for not completing the intervention included factors such as technical difficulties; concerns about the privacy of the chatbot lessons; the intervention being too “simple” to address problems; and external factors, such as feeling too stressed and having a health issue.

Anne Marijn de Graaff, Rand Habashneh, Sarah Fanatseh, Dharani Keyan, Aemal Akhtar, Adnan Abualhaija, Muhannad Faroun, Ibrahim Said Aqel, Latefa Dardas, Chiara Servili, Mark van Ommeren, Richard Bryant, Kenneth Carswell

JMIR Ment Health 2025;12:e63515

Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy–Added Federated Learning Settings: Quantitative Study

Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy–Added Federated Learning Settings: Quantitative Study

Having said that, the paper is not without limitations. Although we tested our algorithms with state-of-the-art datasets (WESAD 15 participants and VERBIO 55 participants), especially for the biometric task, larger datasets with a more heterogenous and higher number of participants should be used. Furthermore, these datasets were recorded in a controlled environment. Real-life or in-the-wild datasets will create more challenges and might require more advanced and complex architectures.

Mohamed Benouis, Elisabeth Andre, Yekta Said Can

JMIR Ment Health 2024;11:e60003