A recent study featuring PISC Senior Scholar George Demiris, PhD, FACMI, tests the precision of an automated speech recognition tool (ASR) when evaluating hospice family caregivers’ anxiety and quality of life. One hundred and twenty-four participants in therapy sessions were comparatively evaluated through an ASR and a self-reported paper assessment. Results indicate that automated speech-to-text transcription tools significantly outperform self-reported assessment. The ASR predicts anxiety and quality of life with a 92% precision rate, while the self-reported assessment has a precision rate of 86%. Automated classifiers have incredible potential to aid mental health support for patients; further design will be necessary to improve content accuracy, voice technology, and conversational context.