Cheeseburger Therapy is an text-based emotional support service that uses peer-to-peer connections to offer clarity and assistance for those struggling with life’s challenges. The service is built around Cognitive Behavioral Therapy (CBT) techniques, and aims to create a more accessible, affordable way to support mental health.
In this model, individuals seeking support can connect with trained “Helpers” who have completed a 25-40 hour training program. The training focuses on active listening, empathy, and CBT-based techniques designed to help clients reframe negative thoughts and cope with emotional difficulties. The service operates on a pay-what-you-can basis, with users only paying for the session if they find it helpful, ensuring that cost is not a barrier to getting support.
Read more about the research at (Iftikhar et al., 2023), (Syed* et al., 2024), (Iftikhar, 2024) and (Iftikhar et al., 2024)! Or visit the website
References
2024
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Machine and Human Understanding of Empathy in Online Peer Support: A Cognitive Behavioral Approach
Sara Syed*, Zainab Iftikhar*, Amy Wei Xiao, and Jeff Huang
In Proceedings of the CHI Conference on Human Factors in Computing Systems , 2024
Online peer support provides space for individuals to connect with others and seek support. However, while empathy is critical for effective support, studies have found that highly empathetic support on these platforms can be rare. Using data from online peer support platforms, we conducted a mixed-methods analysis to study the factors that lead to support seekers’ perceived empathy. We found that CBT techniques like active listening and reflective restatements, along with fostering a space for exploration, increase perceived empathy, whereas rigid adherence to structure, misalignment of concerns, and lack of emotional validation can contribute to low perceived empathy. In addition, despite the high levels of empathy reported by most support seekers (85%), computational models reported low averaged empathy (1.69/6). Lastly, we propose that empathy is not a quantifiable metric and that future algorithmic empathy measurements require human perspectives.
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Re-imagining Mental Health Access: The Role of Human, AI and Design
Zainab Iftikhar
In Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing , 2024
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Therapy as an NLP Task: Psychologists’ Comparison of LLMs and Human Peers in CBT
Zainab Iftikhar, Sean Ransom, Amy Xiao, and Jeff Huang
arXiv preprint arXiv:2409.02244, 2024
2023
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“Together but not together”: Evaluating Typing Indicators for Interaction-Rich Communication
Zainab Iftikhar, Yumeng Ma, and Jeff Huang
In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems , 2023
Messaging is a ubiquitous digital communication medium. It is also a minimal medium of communication because of its inability to convey immediate feedback, tone, facial expressions, hesitations, and pauses, or follow the train of the other person’s thoughts. This paper combines quantitative and qualitative approaches for analyzing richer forms of typing indicators in messaging interfaces, such as showing text as it is typed. By assessing users’ subjective workload and interpreting these findings in the context of users’ experiences, we found that more expressive typing indicators were perceived as “rich in communication”, as they helped people communicate more allowing for closer connections. These indicators also increased users’ perceived co-presence. In addition, our research suggests there may be benefits of designing customized typing indicators for relationship maintenance and task-based communication.
