## 4 Conclusions  
Interactions with PANDORA's conversational agent foster patient autonomy by providing choices and support while enhancing competence through guidance and assistance. This empowers patients to make informed decisions and manage their exercise programs effectively, ensuring their well-being remains a top priority. The Technical Performance Assessment results demonstrate that the CA performed well in delivering accurate exercise-related information, maintaining coherent responses, and achieving comprehensive domain coverage. However, areas for improvement include handling non-understandable inputs and enhancing dialogue management capabilities, which are critical for providing a more robust and reliable conversational experience. These findings highlight opportunities for refining and optimizing the agent's performance. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Metrics/Users** & **P1** & **P2** & **P3** & **P4** & **P5** & **P6** & **P7** & **P8** & **Average** \\ \hline Speech Recognition Satisfaction & 4 & 4 & 4 & 5 & 4 & 5 & 5 & 3 & 4.3 \\ \hline Speech Generation Satisfaction & 5 & 4 & 4 & 5 & 5 & 5 & 4 & 3 & 4.4 \\ \hline Message Buttons Satisfaction & 5 & 4 & 4 & 5 & 5 & 4 & 3 & 5 & 4.4 \\ \hline Aesthetics & 5 & 5 & 5 & 5 & 5 & 5 & 5 & 5 & 5.0 \\ \hline Information Quality & 5 & 4 & 4 & 5 & 5 & 4 & 1 & 5 & 4.1 \\ \hline Subjective Quality & 5 & 4 & 4 & 5 & 5 & 5 & 4 & 4 & 4.5 \\ \hline Ease of Use & 5 & 4 & 5 & 5 & 5 & 5 & 5 & 4.9 \\ \hline Perception of Usefulness & 5 & 5 & 4 & 4 & 4 & 5 & 5 & 4 & 4.5 \\ \hline Interaction Satisfaction & 5 & 4 & 4 & 5 & 5 & 5 & 5 & 4.8 \\ \hline Satisfaction with Answers Given & 5 & 4 & 4 & 5 & 5 & 5 & 5 & 4.8 \\ \hline
**User Average** & **4.9** & **4.2** & **4.9** & **4.8** & **4.8** & **4.2** & **4.4** & **4.6** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: User Experience Results. Future research should prioritize enhancing PANDORA's natural language understanding (NLU) by training the Dialogflow engine on a more diverse and comprehensive dataset, including examples of non-understandable elements to improve input recognition. Leveraging Large Language Models (LLMs), known for their advanced capabilities in handling language variations such as misspellings, grammatical errors, and colloquialisms, could significantly enhance PANDORA's ability to interpret user inputs accurately. Moreover, incorporating contextual understanding through the consideration of the user's interaction history and current task could further refine the agent's ability to handle ambiguous or unclear inputs effectively. These advancements, combined with LLM integration, hold the potential to elevate PANDORA's dialogue management and overall user experience. Moreover, incorporating sensors to measure steps, guide users through exercises, and provide virtual rewards for completing exercises or achieving goals can help keep patients motivated to perform therapeutic exercises and continue their treatment. Sensors enable the CA to adapt its behavior to fit the context, providing alerts and assistance when patients encounter difficulties while performing tasks. This context-aware support enhances patient engagement and motivation. Additionally, using a virtual avatar to embody PANDORA increases user acceptance [54]. Additionally, according to [55], virtual rewards increase motivation. Using behavioral reinforcement with virtual rewards while supporting positive behavioral reinforcement plays an important role in motivation. In addition, mindfulness helps maintain the patient's psychological well-being, increasing their motivation to continue therapy. PANDORA was developed for the Portuguese language but designed to be language-independent, integrating motivational theory for adaptability across linguistic and cultural contexts. Powered by Google Cloud's Dialogflow, which supports over 40 languages, the system offers technical ease for language localization.