Identifying subgroups with differential levels of service response to a digital screening and service navigation program for unmet social care needs

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Abstract Background Digital tools are increasingly integrated into health systems to identify and support needs, yet their effectiveness remains unclear among priority communities. We hypothesise that responses to the digital intervention might vary based on sociodemographic and psychosocial characteristics. Methods Data were analysed from 288 participants in a randomised controlled trial evaluating Watch Me Grow-Electronic – a digital screening and service navigation model to identify psychosocial needs, parental wellbeing, and child developmental needs in South Western Sydney and Murrumbidgee, New South Wales, Australia. Latent class analysis was used to identify subgroups based on clinical and sociodemographic factors. A zero-inflated negative binomial regression was conducted to assess changes in unmet needs, stratified by class and intervention group. Results Three distinct classes were identified. Class 1 ( n =134) included people who were entirely non-culturally and linguistically diverse (CALD) background, in good mental health, with higher education and socioeconomic status (SES), and from a regional/rural site. Class 2 ( n =94) included people who were predominantly non-CALD, of low education and SES, had poor mental health, and from a regional/rural site. Class 3 ( n =56) included people of CALD, high SES and education, and good mental health, who were from an urban site. Compared to the Class 3, participants in Class 2 showed significantly higher needs, indicating that the intervention was not effective in this vulnerable group. Discussion Digital navigation tools might support families that experience lower psychosocial adversity but are insufficient for families that experience higher levels of adversity, highlighting the need for tiered approaches to ensure equity.

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