Beyond calories: evaluating how tailored communication reduces emotional load in diet-coaching
Dieting is a behaviour change task that is difficult for many people to conduct successfully. This is due to many factors, including stress and cost. Mobile applications offer an alternative to traditional coaching. However, previous work on apps evaluation only focused on dietary outcomes, ignoring users’ emotional state despite its influence on eating habits. In this work, we introduce a novel evaluation of the effects that tailored communication can have on the emotional load of dieting. We implement this by augmenting a traditional diet-app with affective NLG, text-tailoring and persuasive communication techniques. We then run a short 2-weeks experiment and check dietary outcomes, user feedback of produced text and, most importantly, its impact on emotional state, through PANAS questionnaire. Results show that tailored communication significantly improved users’ emotional state, compared to an app-only control group.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical Modelling Approach
Community parks play a crucial role in promoting physical activity and overall well-being. This study introduces DLICP (Deep Learning Integrated Community Parks), an innovative approach that combines deep learning techni…
Deep LearningFace RecognitionThe Overthinker's DIET: Cutting Token Calories with DIfficulty-AwarE Training
Recent large language models (LLMs) exhibit impressive reasoning but often over-think, generating excessively long responses that hinder efficiency. We introduce DIET ( DIfficulty-AwarE Training), a framework that system…
Reinforcement Learning (RL)Token ReductionHuman Activity Recognition using Smartphones
Human Activity Recognition is a subject of great research today and has its applications in remote healthcare, activity tracking of the elderly or the disables, calories burnt tracking etc. In our project, we have create…
Activity RecognitionDimensionality ReductionHuman Activity RecognitionEdgeAgentX: A Novel Framework for Agentic AI at the Edge in Military Communication Networks
This paper introduces EdgeAgentX, a novel framework integrating federated learning (FL), multi-agent reinforcement learning (MARL), and adversarial defense mechanisms, tailored for military communication networks. EdgeAg…
Adversarial DefenseDecision MakingFederated LearningMulti-agent Reinforcement Learning+2Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models
Recent advancements in visual generative models have enabled high-quality image and video generation, opening diverse applications. However, evaluating these models often demands sampling hundreds or thousands of images …
Video Generation