The stakes are enormous. The second Lancet Commission on Adolescent Health and Wellbeing has estimated that by 2030 more than one billion adolescents aged 10 to 24 — roughly half of all adolescents globally — will live in countries where preventable health problems threaten their wellbeing. During early and middle adolescence, six intertwined risk behaviours tend to emerge: poor nutrition, inadequate physical activity, poor sleep, excessive recreational screen time, alcohol use, and smoking or vaping. Researchers call these the “Big 6,” and they rarely appear in isolation. They cluster together, reinforce one another, and track stubbornly into adulthood, laying the foundations for chronic disease decades later. Families experiencing socio-economic disadvantage are hit hardest, facing structural and systemic barriers that make every one of these behaviours more likely. In Australia, adolescents in the most disadvantaged areas are more likely to drink at risky levels and to smoke, and less likely to meet fruit consumption guidelines, than their more advantaged peers.

Parents, the research team argues, are the most underused lever in prevention. Caregivers shape adolescent health through role modelling, rule-setting, monitoring and communication, and prior trials of parent-based programs have shown real promise, particularly when paired with youth-focused components. Yet engaging parents is notoriously difficult. Time scarcity and competing demands consistently emerge as barriers, and these are magnified for parents juggling financial stress, household pressure and limited social support. Digital interventions promise a way around these obstacles — flexible, remote, and free of travel and childcare costs — but a nagging question has remained: how much human support do parents actually need? Guided programs tend to boost engagement and adherence, while unguided ones are cheaper and scale effortlessly. Nobody knew where the sweet spot lay, especially for disadvantaged families, and a systematic review by the same group found only one parent intervention in the entire literature designed specifically for them.

Enter the Multiphase Optimisation Strategy, or MOST, a framework borrowed from engineering that treats an intervention not as a monolithic package but as an assembly of independently testable parts. Rather than running a traditional randomised controlled trial that asks “does the whole program work?”, MOST asks “which parts work, which parts are dead weight, and which combinations deliver the most benefit for the least burden?” The framework unfolds in three phases — preparation, optimisation and evaluation — and the new study represents the optimisation phase, the first time MOST has ever been applied to a digital intervention helping parents improve multiple adolescent health behaviours. In the preparation phase, the team built a conceptual model grounded in Social Cognitive Theory and Family Systems Theory, then co-designed every component with parents and adolescents from disadvantaged communities through workshops, school focus groups and a standing parent–adolescent advisory group.

The trial itself was a feat of experimental design. Between April and October 2025, the researchers recruited 303 parents of 11-to-15-year-olds living in the 40 per cent most disadvantaged areas of New South Wales, Australia, identified using the Australian Bureau of Statistics’ Index of Relative Socio-economic Disadvantage. Every parent received a core package of six online learning modules — one each for screen time, smoking and vaping, alcohol, sleep, healthy eating and physical activity — each roughly 20 minutes long, built around podcast-style videos with health professionals, interactive strategy summaries and goal-setting activities. Parents were then randomised across 16 experimental conditions in a 2×2×2×2 factorial design, with four additional components switched on or off: automated text messages, tailored feedback on their parenting, a stress management module, and weekly telehealth coaching calls from trained non-specialist health coaches. After data quality checks removed fraudulent responses, 292 parents formed the final baseline sample, with 79 per cent retained at the three-month follow-up.

The primary outcome was change in parental encouragement of adolescent health habits, measured with the validated Health Habits sub-scale of the Parenting to Reduce Adolescent Depression Anxiety Scale, a 12-item measure scored from 0 to 12 with very high reliability in this sample. The statistical machinery was correspondingly sophisticated: pre-specified linear mixed models with effect coding estimated each component’s main effect over time, while every possible two-, three- and four-way interaction was tested for synergy or antagonism. Missing data were handled by maximum likelihood, and analyses ran on an intention-to-treat basis. Notably, the team used a more liberal significance threshold of p < 0.10, consistent with MOST guidance, to avoid prematurely discarding potentially useful components during this exploratory screening stage.

The results delivered surprises in both directions. Telehealth coaching significantly improved parental encouragement (Cohen’s d = 0.38), as did tailored feedback (d = 0.26), and there was no statistical difference between the two. Crucially, combining them produced no significant synergistic effect — a direct challenge to the assumption that more support is always better. Text messages, meanwhile, backfired spectacularly: the component significantly reduced parental encouragement over time (d = −0.41), despite being co-designed with parents and intended as gentle encouragement. The authors speculate that the semi-automated messages may have added pressure for time-poor parents, felt too generic, or simply drowned in the noise of daily notifications. Stress management training showed no effect at all, possibly because a single module delivered late in the sequence could not shift entrenched household stress within the trial’s timeframe.

The optimisation decision then hinged on burden, not just efficacy. Parents who received both effective components rated telehealth coaching as significantly more effortful than tailored feedback (mean 2.4 versus 2.1 on a five-point effort scale). Coaching also demands real-world resources — trained staff, scheduling, fidelity monitoring — that cap scalability, whereas automated feedback costs almost nothing once built. Weighing effectiveness against effort, the team selected the package combining the online modules with automated tailored feedback alone as the optimised intervention. Feedback surveys suggested parents embraced it: 97.7 per cent of respondents reported a good or very good experience, 90.6 per cent found the length about right, and 80 per cent found it easy to fit into their lives. Coaching fidelity, for the record, averaged 91.9 per cent, so the component’s screening-out reflected burden, not poor delivery.

The study is not without limitations. The sample was 87 per cent mothers and drawn from a single Australian state, and because eligibility was based on area-level rather than individual-level disadvantage, many participants held post-secondary qualifications and moderate incomes, meaning the findings may not extend to families facing the most severe deprivation. The primary outcome relied on parent self-report, leaving room for social desirability bias, and internet access was required to participate. Yet the strengths are considerable: strong retention, rigorous fraud screening, prospectively registered methods, and a design that finally puts disadvantaged families at the centre of prevention science rather than its margins.

The bigger story is methodological. By dismantling a multicomponent intervention and rebuilding it from empirically validated parts, the researchers demonstrated that intervention science can work like engineering — identifying what earns its place and what does not. The optimised Health4Life Parents & Teens program now moves into the evaluation phase, a cluster randomised controlled trial with economic analysis that will test whether pairing it with the existing school-based Health4Life program improves the Big 6 behaviours in parent–adolescent dyads. If it succeeds, the payoff extends far beyond Australia: the same optimisation logic could stretch scarce prevention dollars further in low- and middle-income settings, and future work may explore whether artificial intelligence can deliver coaching-like support without the human cost. For a field long guilty of bolting components together and hoping for the best, this trial offers a sharper, more honest blueprint — and a reminder that sometimes the most powerful thing a program can do is know what to leave out.

Subject of Research: Optimisation of a digital parent-based intervention for adolescent health risk behaviours using the MOST framework

Article Title: Optimising a digital parent-based intervention to improve adolescent health risk behaviours in families living in socio-economically disadvantaged communities: findings from the Health4Life Parents & Teens factorial randomised trial

Article References: Champion, K. E., Davidson, L., Sunderland, M., Hunter, E., Spring, B., Thornton, L., Haidinger, A., Finn, T., Osman, B., Chapman, C., Burrows, T., Slade, T., Partridge, S. R., Gardner, L. A., Parmenter, B. J., Baur, L. A., Teesson, M., Mihalopoulos, C., Johnson, G., … Newton, N. C. (2026). Optimising a digital parent-based intervention to improve adolescent health risk behaviours in families living in socio-economically disadvantaged communities: findings from the Health4Life Parents &amp; Teens factorial randomised trial. The Lancet Regional Health – Western Pacific, Article 101987. https://doi.org/10.1016/j.lanwpc.2026.101987

Image Credits: AI Generated

DOI: Not provided

Keywords: adolescent health, digital intervention, parenting, MOST framework, factorial randomised trial, health risk behaviours, socio-economic disadvantage, telehealth coaching, tailored feedback, prevention, Australia, behaviour change