The integration of digital technologies, including computer vision and advanced data analytics, presents new opportunities for psychologists, particularly those in training. This paper reviews the current applications of digital technologies in psychological assessments and interventions, emphasizing the use of computer vision to analyze non-verbal cues like facial expressions and body language. Machine learning algorithms are explored for their ability to process large datasets, identify patterns, and predict mental health outcomes, offering a data-driven approach to mental health care. These technologies allow for the development of personalized interventions through the analysis of stress indicators collected from digital tools such as mobile applications and wearable devices. The findings suggest that leveraging computer vision and machine learning in psychological settings can significantly enhance both the quality of care provided and the well-being of healthcare professionals. Future research should focus on further developing these tools to ensure their applicability across a broader range of populations and contexts.