Measuring Mental Health in Motion: How Wearable Measures Can Transform Youth Care Worldwide

By Michelle Freund, PhD
Director, Strategic Data Initiatives, Child Mind Institute
&
Michael P. Milham, MD, PhD
Chief Science Officer, Child Mind Institute

We’re entering an era where everyday technology — from smartphones to fitness trackers — can provide unprecedented insights into youth mental health. But realizing this potential requires careful planning, ethical safeguards, and a commitment to ensuring these tools work for all young people, not just those in wealthy countries.

A new white paper from the Stavros Niarchos Foundation (SNF) Global Center for Child and Adolescent Mental Health at the Child Mind Institute charts a strategic course forward, outlining how wearable and physiological measures can bridge the gap between research and real-world clinical care.

Traditional mental health assessments rely heavily on what happens in a clinician’s office. While valuable, questionnaires, observations, and conversations provide limited snapshots. Mental health is complex and doesn’t happen in scheduled increments. It unfolds across days and weeks, shaped by sleep patterns, daily stressors, social interactions, and countless other factors that never make it into a clinical note.

Wearable devices offer something different: continuous, objective data about the rhythms of daily life. Heart rate variability during a stressful exam, sleep disruptions following an argument with a friend, activity levels that gradually decline — these digital breadcrumbs can reveal patterns invisible to traditional assessment methods. The potential is enormous. But so are the challenges — particularly when it comes to making these tools accessible and appropriate across diverse cultural and economic contexts. The goal is not to replace laboratory science but to connect it to real-world behavior.

Here’s an uncomfortable truth: Most wearable research happens in high-income countries, using devices designed for more affluent consumers. A $400 smartwatch may be commonplace in Manhattan, but it’s out of reach for most families in low- and middle-income areas such as Nairobi or New Delhi, for example. This matters because mental health challenges don’t respect borders or income levels. In fact, roughly 90 percent of young people live in low- and middle-income countries (LMICs), where mental health needs are often greatest and resources most scarce.

The paper’s road map addresses this head-on, calling for investment in affordable, research-grade devices tailored to LMIC contexts. This includes:

• Local language interfaces
• Discreet designs (clip-ons rather than conspicuous smartwatches)
• Designs with cultural sensitivity, recognizing that gender norms and social contexts shape what devices are acceptable and practical in different settings
• Strategies to reduce import costs

One of the most promising recommendations involves leveraging technology many young people already have: smartphones. Most phones contain sophisticated sensors capable of tracking movement, screen time, voice patterns, and location — all potentially relevant to mental health monitoring. The key is doing this responsibly. With an emphasis on safeguarding policies, the road map establishes transparent consent, strict data minimization, and robust oversight to prevent misuse. Standardized methods for extracting and analyzing smartphone data would also ensure findings from different studies can be compared — accelerating the pace of discovery. Of course, smartphone availability and connectivity is not universal and other alternatives must be considered for our work to be truly inclusive.

Physiological data becomes far more meaningful when paired with context. That’s where Ecological Momentary Assessments (EMA) come in — brief surveys delivered via smartphone that capture how someone is feeling and what they’re experiencing in real time. Imagine combining heart rate data showing elevated stress with an EMA response revealing the teen just had a conflict with a friend. Or correlating disrupted sleep patterns with reports of anxiety about an upcoming test. This multi-modal integration creates a richer, more nuanced picture of mental health dynamics while maintaining protection protocols.

The challenge is doing this without overwhelming participants. Nobody wants their phone constantly buzzing with survey questions. The road map calls for adaptive approaches where EMA prompts are triggered intelligently — perhaps by physiological signals suggesting elevated distress — rather than on arbitrary schedules.

It also suggests possible alternatives to monetary incentives, which may not be sustainable. Lessons learned from game design: achievement badges, progress indicators, social recognition might offer more scalable ways to encourage participation.

Laboratory research offers controlled conditions and mechanistic insights. Real-world research captures the messy complexity of actual experience. We need both.

Emerging technologies are making this integration possible. Mobile Brain/Body Imaging (MoBI) labs, for example, integrate cutting-edge sensors and analytic tools to study how the brain and body respond during cognitive and emotional tasks. Data collected from a MoBI lab includes the synchronization of EEG with motion capture, eye-tracking, and other measures, enabling the study of cognition and emotion during naturalistic activities. The Child Mind Institute has been a leader in developing open source MoBI tools and training programs, positioning this approach as a critical bridge between traditional lab methods and ecological measurement. Virtual reality offers another promising avenue — simulating real-world scenarios in controlled settings, then measuring responses that might predict behavior outside the lab. Even traditional tools like EEG are evolving. Wearable EEG devices, though still emerging, could eventually bring neurophysiological measurement out of the lab and into daily life — if issues of comfort, stigma, and data quality can be resolved.

Research findings truly matter when they improve care. That means integrating wearable data into clinical workflows in ways that are practical, sustainable, and actually helpful.

In high-resource settings, this might involve dashboards that present clinicians with objective data alongside traditional assessments — similar to how cardiologists now routinely review data from continuous heart monitors. In LMICs where electronic health record infrastructure may be limited, integration could happen through school-based programs, community clinics, or mobile health platforms.

The vision extends beyond assessment to intervention. Just-in-time adaptive interventions could deliver targeted support automatically when wearable data indicates heightened risk — a mindfulness prompt triggered by elevated physiological stress, for instance, or a check-in message following disrupted sleep.

These technologies should extend human judgment, not replace it. The goal is to give clinicians better information, not to reduce mental health care to algorithms.

With great data comes great responsibility. The road map emphasizes that any partnerships with commercial technology companies must guarantee access to raw research-grade data, fair intellectual property arrangements, and strict protections against youth data monetization or exploitation.

This is especially critical in LMIC contexts, where extractive research practices have a troubling history. Local researchers bring essential expertise and must be positioned as partners and leaders rather than solely as sources for data. Agreements should ensure that benefits — whether new diagnostic tools, intervention approaches, or fundamental knowledge — flow back to the communities that contributed.

Policymakers have a role too: establishing national guidelines for wearable data collection that balance innovation with privacy, promoting digital infrastructure investments that enable continuous data collection, and requiring transparency in how youth data is used.

Technology alone won’t solve the challenges without people trained to use it effectively. The road map, therefore, also calls for significant investment in training programs covering device setup, data integration, AI-assisted analysis, and governance frameworks — with particular emphasis on building capacity in LMICs.

This includes:

• Supporting regional manufacturing and validation of devices
• Creating networks that connect researchers across institutions and countries
• Developing open source tools and protocols that reduce barriers to entry

The goal is a truly global research ecosystem where every region can contribute to and benefit from advances in youth mental health measurement.

Perhaps most importantly, the road map calls for coordination. Too often, research teams work in isolation, using different devices, protocols, and analysis methods — making it nearly impossible to compare findings or build cumulative knowledge.

Establishing a core dataset, with minimum standards for what gets measured and how, would enable more robust comparison across studies while still allowing for regional adaptation. Open data repositories could accelerate discovery by allowing researchers to pool findings. Preregistration and transparent reporting of methods would strengthen reproducibility.

These may sound like technical details, but they’re essential infrastructure for translating scattered insights into systematic knowledge.

The road map is ambitious, and success is far from guaranteed. It will require sustained commitment from funders who recognize the vision, measurable impact, and strategic advantage of investing in locally led initiatives and open tools. From researchers willing to prioritize collaboration over competition and open science over proprietary advantage, policymakers willing to update regulations for a digital age, and technology companies willing to prioritize youth well-being over profit maximization.

Every young person — regardless of where they live or household income — deserves access to mental health care informed by the best available evidence and most appropriate tools.

Wearables and physiological measures aren’t a panacea. Mental health is complex, shaped by biology, psychology, relationships, trauma, inequality, and countless other factors. No device can capture that full complexity. What these tools can provide, however, is a window into daily experiences that traditional methods may miss. They can help identify young people who need support earlier. They can track whether interventions are working. They can generate insights that improve how we understand and address mental health challenges.

The Child Mind Institute is proud to help lead this work through the SNF Global Center for Child and Adolescent Mental Health, because measurement matters. And because every young person deserves care grounded in evidence that reflects their reality.