Digital screening and navigation interventions may support families with lower psychosocial adversity but are insufficient for families experiencing higher levels of adversity, highlighting the need for tiered approaches to ensure equity.
Key Findings
Results
Latent class analysis identified three distinct subgroups of families based on parental and child clinical and sociodemographic factors.
Class 1 (n=134) included people who were entirely non-CALD background, in good mental health, with higher education and socioeconomic status (SES), and from the 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 the regional/rural site.
Class 3 (n=56) included people of CALD background, high SES and education, and good mental health, who were from the urban site.
Total sample size was 288 participants drawn from a randomised controlled trial evaluating the Watch Me Grow-Electronic (WMG-E) digital screening and service navigation model.
The study was conducted across two sites: South Western Sydney (urban) and Murrumbidgee (regional/rural), New South Wales, Australia.
Results
Participants in Class 2 (low SES, poor mental health, regional/rural) showed significantly higher unmet needs compared to Class 3, indicating the intervention was not effective in this vulnerable group.
Zero-inflated negative binomial regression was used to assess changes in unmet needs, stratified by class and intervention group.
Class 2 participants were predominantly non-CALD, of low education and SES, and had poor mental health.
Compared to Class 3, Class 2 participants showed significantly higher needs, suggesting the digital navigation tool failed to adequately address needs in this subgroup.
The authors conclude the intervention was 'not effective in this vulnerable group.'
Results
The Watch Me Grow-Electronic digital screening and service navigation model appeared more beneficial for families experiencing lower psychosocial adversity than for those with higher adversity.
The intervention evaluated was Watch Me Grow-Electronic (WMG-E), designed to identify psychosocial needs, parental wellbeing, and child developmental needs.
Digital navigation tools were found to 'support families that experience lower psychosocial adversity but are insufficient for families that experience higher levels of adversity.'
Class 1 (non-CALD, good mental health, higher SES/education) and Class 3 (CALD, high SES/education, good mental health) appeared to respond differently than Class 2.
The study hypothesised that responses to digital interventions might vary based on sociodemographic and psychosocial characteristics.
Results
The study identified that CALD background, SES, mental health status, education level, and geographic location (urban vs. regional/rural) were key differentiating factors among subgroups.
CALD status was a defining characteristic: Class 1 was entirely non-CALD, Class 2 was predominantly non-CALD, and Class 3 was CALD.
Mental health status varied by class: Class 1 and Class 3 had good mental health, while Class 2 had poor mental health.
Classes 1 and 2 were both from the regional/rural site (Murrumbidgee), while Class 3 was from the urban site (South Western Sydney).
SES and education distinguished Class 2 (low) from Classes 1 and 3 (higher), despite geographic and cultural differences between the latter two.
Conclusions
The authors conclude that tiered approaches to digital health interventions are needed to ensure equity for families with varying levels of psychosocial adversity.
Standard digital navigation tools were described as insufficient for families experiencing higher levels of adversity.
The findings highlight 'the need for tiered approaches to ensure equity' in service delivery.
The study notes that the effectiveness of digital screening and navigation interventions 'remains unclear among priority population communities.'
The results suggest that more intensive or different forms of support may be required for subgroups such as Class 2, characterized by low SES, poor mental health, and low education.
What This Means
This research suggests that a digital tool designed to screen families for unmet social needs and connect them with services does not work equally well for all families. Researchers analyzed data from 288 parents participating in a trial of the 'Watch Me Grow-Electronic' program in Australia, and used statistical methods to group families by their characteristics. They found three distinct groups: one with higher income and education, good mental health, and no culturally or linguistically diverse (CALD) background from rural areas; one with lower income and education and poor mental health from rural areas; and one with CALD background, higher income, good mental health from an urban area. The digital program appeared to be least effective for the middle group — those with lower socioeconomic status and poorer mental health — who continued to have significantly higher unmet needs even after using the intervention.
This research suggests that digital health tools, while potentially useful for some families, may not be sufficient on their own for those facing multiple layers of disadvantage, such as poverty, poor mental health, and low educational attainment. Families in this more vulnerable group may need additional or more intensive forms of support that go beyond what a digital navigation program can provide.
The practical implication is that health systems should not assume a 'one-size-fits-all' digital approach will reach all populations equitably. The authors call for tiered service models — where the level and type of support is matched to the complexity of a family's needs — to ensure that the most vulnerable families are not left behind as digital health tools become more widely used.
John J, Winata T, Wang S, Smead M, Wu W, Kohlhoff J, et al.. (2026). Identifying subgroups with differential levels of service response to a digital screening and service navigation program for unmet social care needs.. PloS one. https://doi.org/10.1371/journal.pone.0332790