Digital Health Intervention for and Long-Term Health Outcomes of a Divorce Cohort With Linked Danish Data: 5-Year Posttrial Follow-Up of a Randomized Controlled Trial.

Background: Digital health interventions are increasingly promoted as scalable and cost-effective approaches to support mental health and resilience. Short-term benefits are well documented, but evidence on long-term outcomes (beyond 12 mo) remains scarce, particularly when assessed with objective measures in large cohorts. Most studies to date have focused on small samples, relied on self-reported outcomes, and used follow-up periods of less than a year. This leaves uncertainty about whether early changes are sustained over time and whether they can be observed in objective indicators of health. This gap is particularly relevant for stressful life transitions, where the risk of long-term adverse health outcomes is high. Divorce, a common and stressful transition linked to poorer mental and physical health, thus provides an ideal case for investigating the long-term potential of digital health interventions. Objective: This study examined the association between SES One, a digital health intervention for Danish divorcees, and mental health medication use, primary care usage, and hospitalizations over a 5-year follow-up period using Danish national health registers. Methods: Participants (n=1856) from a randomized controlled trial of SES One in Denmark were followed for 5 years after divorce. Outcomes included mental health medication prescriptions (eg, antipsychotics, anxiolytics, hypnotics, sedatives, and antidepressants), primary care usage (eg, billable interactions with general practitioners, specialist practitioners, and psychologists), and hospitalizations. Odds ratios and incidence rate ratios were calculated to compare outcomes between SES One participants and the control group. Results: Over 5 years, SES One participants did not have significantly lower odds of filling a prescription (odds ratio [OR] 0.836; P=.09) but filled 28% fewer prescriptions overall (incidence rate ratio 0.720; P=.045), indicating a reduce-not-remove effect. No overall differences were observed in primary care usage or hospitalizations. However, participants had 38% (OR 0.624, P=.003) and 27% (OR 0.730, P=.001) lower odds of visiting primary care in years 2 and 3, respectively, and 32% (OR 0.677, P=.046) lower odds of hospitalization in year 4, suggesting possible late-onset effects. Conclusions: The findings advance the field by showing that a targeted digital health intervention can generate measurable long-term health benefits in a large cohort when evaluated with objective registry data. The results suggest that such interventions may reduce reliance on medication and health care services over time, not by eliminating needs entirely but by reducing them. These patterns can be interpreted as reflecting both legacy and late-onset pathways. Long-term evaluations with objective data are essential to fully capture the durability and timing of digital health intervention effects.