Machine Learning Approaches to Identify Influential Factors of the Comorbid Psychiatric Symptoms and Hypertension Among Rural Adults in Bangladesh: A Cross-Sectional Study.

An estimated 2.6 billion people globally experience difficulties with functioning and would benefit from rehabilitation (, ), and more than 2.5 billion people need assistive technology (AT) (). Rehabilitation and AT can be fundamental for facilitating independence and participation for people with functioning difficulties and improving their well-being (). Diverse groups, including people with disabilities, older people, and people with chronic conditions, can benefit from these services (, ). However, the unmet need for rehabilitation and AT remains high and continues to increase (, ). Currently, there is a lack of reliable data on population need to inform policy development and service provision. Such data are particularly needed in low- and middle-income country (LMIC) settings, where access to both rehabilitation and assistive products (AP) is often limited (, ). In response to these gaps and challenges, in collaboration with the AT2030 consortium () and the Computer Science Department at the University College London (UCL), the International Centre for Evidence in Disability (ICED) at the London School of Hygiene and Tropical Medicine (LSHTM) developed the Functional Needs Assessment Tool (FNAT), a new multi-domain survey methodology and bespoke tablet-based mobile data collection application. FNAT aims to estimate the (i) prevalence of functional difficulties/impairments and (ii) the need for related health and rehabilitation services and AP in people aged 2 years and older. The survey uses a two-stage cluster random sampling methodology to identify participants and a two-stage assessment process: an initial screening (day 1), followed by clinician-led assessments (day 2) for those who screen positive. The tool includes a combination of self-report, clinical impairment and functional assessments to identify service and AP needs across seven domains: vision, hearing, mobility, communication, cognition, self-care, and mental health.