Using Automated Psychological Tools for Understanding and Improving Mental Health Outcomes in Aotearoa

Aotearoa New Zealand has one of the highest rates of anxiety and depression globally, with Māori and Pacific groups carrying the greatest burden. We need to better understand the driving factors to improve the availability and flexibility of our treatment pathways. Underlying emotional needs and values can influence our personality traits and mental health and are influenced by cultural perspectives and practices. While questionnaires and therapeutic discussions can help identify emotional needs, technology‐assisted techniques (e.g., machine learning) provide a platform for identifying these traits from media such as free text, offering a more accessible and flexible format to better understand contributors to mental health. Here, we used this novel technology with an online sample ( n = 423) to conduct a preliminary analysis of differences in emotional needs, personality and mental health metrics across different cultural groups in Aotearoa. We observed Māori (indigenous people of Aotearoa) to place lower value on self‐assertion alongside greater anxiety sensitivity symptoms, and Pacific people to have the highest levels of depression. We explored these results in light of the current euro‐centric origins of the current tools and make suggestions for how technology assistance could be utilised for maximal benefit across all population groups in Aotearoa.