Mobile technology is increasingly leveraged for mental health interventions, with users expressing overall satisfaction and finding the apps helpful and user-friendly. While the apps offer diverse features for symptom management, self-help, and treatment support, evidence regarding their effectiveness remains limited, suggesting a need for further research. Usability, engagement, and tailoring to user preferences emerge as critical factors, emphasizing the importance of customization for different populations. This research presented a systematic literature review aimed at evaluating studies specifically focusing on post-traumatic stress disorder (PTSD) apps, with a subsequent quality assessment using the MARS scale. Additionally, the research involves an in-depth analysis of user reviews for these PTSD apps through thematic, and path analysis. The technology acceptance model (TAM) model serves as the framework for path analysis, and the performance of VADER, Flair, and TextBlob is evaluated. Sentiment analysis is then employed to explore relationships among TAM model factors and additional factors derived from the systematic literature review and thematic analysis. In conclusion, this dissertation contributes to the understanding of PTSD apps, their usability, and their potential for mental health support. It underscores the need for further research, customization, and ongoing collaboration to optimize the effectiveness of these applications in managing PTSD symptoms and supporting individuals in their mental health journey.