82 FEATURE
The new role of technology in mental and behavioural healthcare
T he mental health sector has historically lagged in adopting technology compared to fields like cardiology or radiology, constrained by factors like data sensitivity, restrictive legislation, and early consumer skepticism toward AI. However, digital health is now fundamentally reshaping mental and behavioural healthcare, offering powerful solutions to longstanding systemic barriers like capacity constraints and workforce shortages. Digital tools can foster stronger therapeutic relationships, provide individualised care, and improve clinical outcomes. As consumer sentiment shifts and the internet becomes the first port of call for many seeking support, technology can improve accessibility, affordability, and flexibility, bridging the gap for millions globally who lack access to traditional mental health treatment. Crucially, technology can offer a safe, low-stigma entry point for vulnerable populations, including youth and members of cultures who may feel hesitant about in-person care. The success and trustworthiness of this transformation depend
on addressing critical ethical considerations, particularly data privacy, security, and algorithmic transparency. Shifting to chronic care and early intervention
interventions can be delivered early and at a low threshold, preventing crises from escalating. For instance, digital phenotyping uses real-time, passive data (e.g., heart rate, app usage) collected from smart devices to detect subtle behavioural shifts and predict symptom exacerbation. This enables just-in-time adaptive interventions, delivering targeted support precisely when analytics indicate the person needs it most. Personalisation, inclusion, and workforce empowerment Equitable digital mental health demands solutions that are applicable to diverse populations and address their specific social determinants of health and barriers to care. This means ensuring interventions are culturally and linguistically appropriate and sensitive to factors like age, gender, and socioeconomic background. Modern mental health applications move beyond clinical data, embracing holistic data models that better reflect the person and their needs. This commitment to inclusion requires addressing critical issues like Indigenous data sovereignty and privacy, and incorporating
Technology supports a paradigm shift: managing mental health as a chronic, lifelong condition rather than a crisis-response mode, with a system that prioritizes preventive,
sustained, and supportive care within the community.
Digital mental health complements conventional care by offering a spectrum of options. Individuals with lower-intensity needs can self-manage with convenient tools, freeing up scarce professional resources for those with more complex, acute needs. For individuals requiring higher-level intervention, technology ensures seamless care coordination, facilitating referrals, transfers of care, and logistical management of multi-channel services through integrated care plans. A key advantage is the ability to identify and intervene in the “moments that matter.” By leveraging data-driven insights, particularly through AI,
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