Videra Health Launches “Check on Mom,” the First Free AI-Powered Postpartum Depression Screener

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New initiative empowers moms with a confidential, stigma-free video screener for postpartum depression, powered by conversational AI

Orem, UT, September 23, 2025 – Videra Health, a leading AI platform for behavioral health providers, today announced the launch of Check on Mom, the first free, confidential AI-powered postpartum depression screener. The self-assessment tool empowers mothers to complete a private, video-based check-in using conversational AI that captures both verbal and non-verbal signs of postpartum depression (PPD) and generates results they can share with a provider.

Unlike traditional written screeners, Check on Mom uses video and AI language models trained specifically for healthcare to analyze both spoken words and non-verbal cues. This dual-layer approach provides deeper insights into maternal mental health, making it easier to distinguish between common “baby blues” and postpartum depression.

“Check on Mom is not just a digital tool, it is a public health resource,” said Loren Larsen, co-founder and CEO of Videra Health. “By showing what is possible with AI-powered video screeners, we are opening new opportunities for earlier detection and better outcomes, not just in maternal health but across conditions where timely screening can make a real difference for patients and providers.”

How Check on Mom Works:

  • Free and confidential: No insurance, no cost.
  • Fast and convenient: Completed on almost any device, at any time, in less than three minutes.
  • Video-based and shame-free: Instead of static surveys, moms can speak openly and naturally about how they feel, and results are theirs to share
  • Clinically validated insights: Downloadable results can be shared with OBs, midwives, or primary care providers to guide next steps.

One in eight mothers experience postpartum depression, yet most go undiagnosed or untreated because screenings are inconsistent, stigma persists, and support often arrives too late. With Check on Mom, any mother can complete a short, video-based screener in just a few minutes and access secure results immediately without waiting for a six-week appointment or navigating health system barriers.

Check on Mom is more than a consumer resource. It is a proof point for how AI can transform condition-specific screening at scale. By applying conversational AI and video analysis, Videra Health is creating earlier pathways to care for conditions that are too often overlooked.

In addition to proprietary AI models already used to screen for depression, anxiety, trauma, and other conditions, the company most recently released TDScreen, the first AI-powered screener for tardive dyskinesia. These tools show how AI screeners can:

  • Expand access to early detection in underserved populations.
  • Deliver patient-centered insights that improve diagnosis and treatment.
  • Provide adaptable, condition-specific screening models that can be applied across therapeutic areas.

Across healthcare from patients and providers to pharma leaders, Check on Mom demonstrates how technology can expand access to postpartum depression screening, improve early detection, and support better patient outcomes. Videra is working to normalize maternal mental health conversations and demonstrate a new model for patient-first innovation.

Check on Mom is available free of charge for any mom wanting to screen for postpartum depression. Visit www.checkonmom.ai to learn more.

About Videra Health™

Videra Health is a leading AI platform for behavioral health providers and proactively identifies, triages and monitors at-risk patients using linguistic, audio and video analysis. The FDA-registered digital platform transforms how doctors and healthcare systems interact and track a patient’s journey, illuminating the hidden depths of patient behavior and outcomes. Videra Health connects providers and patients anytime, anywhere, between visits and post-discharge via written and video assessments that translate into actionable quantitative and qualitative patient data. The platform streamlines diagnoses, enhances care accessibility, optimizes workflows and drives down costs for providers and healthcare systems.

Addressing the Invisible Wounds of PTSD: Technology-Enabled Strategies for Healing

PTSD Awareness Month

The invisible wounds of post-traumatic stress disorder (PTSD) affect approximately 8 million Americans annually. Behind this statistic lies a complex clinical challenge that technology-enabled PTSD treatment approaches are beginning to address: how do we effectively treat a condition that manifests uniquely in each person, remains largely hidden from external observation, and often prevents the very help-seeking behaviors necessary for recovery?

Traditional PTSD treatment approaches, while valuable, have struggled with persistent challenges of access, engagement, and personalization. Many patients face geographical barriers to specialized care, while others confront the paradox that their symptoms—particularly avoidance—directly interfere with consistent treatment participation.

In my fifteen years working with trauma survivors, I’ve witnessed both the limitations of conventional approaches and the emerging promise of technology-enabled solutions. This isn’t simply about digitizing existing treatments; it’s about fundamentally reimagining how we conceptualize, measure, and address the complex manifestations of psychological trauma.

The Challenge: Why Traditional PTSD Treatment Falls Short

The journey toward effective PTSD treatment has been marked by both significant progress and persistent obstacles. Despite decades of research and clinical refinement, several challenges continue to limit the reach and efficacy of traditional approaches:

  • Access barriers: Studies show only about 50% of those with PTSD seek treatment1, with rural populations, ethnic minorities, and military veterans particularly underserved due to provider shortages and geographic limitations
  • Engagement difficulties: The longitudinal nature of trauma recovery requires consistent participation, yet PTSD symptoms themselves—particularly avoidance—often directly interfere with treatment adherence
  • Measurement limitations: Clinical assessments conducted at periodic intervals frequently miss the day-to-day symptom fluctuations that characterize PTSD, limiting timely intervention and treatment adjustment
  • One-size-fits-all approaches: Standard protocols, while evidence-based, often fail to address the unique manifestation and neurobiological underpinnings of trauma responses in different individuals

These challenges aren’t simply administrative hurdles; they represent fundamental limitations in our ability to meet patients where they are—both literally and figuratively. They call for innovation that extends beyond incremental improvements to existing models.

Technology-Enabled PTSD Treatment: A Bridge to Healing

The convergence of digital health innovation, neuroscience, and trauma research has created a watershed moment in PTSD treatment. Emerging technologies offer novel approaches to longstanding barriers, creating possibilities that were unimaginable even a decade ago:

1. Digital Tools and Measurement-Based Care

The fundamental principle that “you can’t manage what you don’t measure” takes on particular significance in PTSD treatment. Traditional assessment relies heavily on retrospective self-reporting, which is vulnerable to recall bias and symptom fluctuations. The moment-by-moment quantification of individual-level human behavior using data from personal digital devices offers an unprecedented window into the lived experience of PTSD.

Research on passive sensing for PTSD detection shows promising results, with a recent study demonstrating that smartphone-collected GPS data alone can differentiate individuals with PTSD from those without with 77% accuracy, suggesting the potential for continuous, unobtrusive mental health monitoring.2 These approaches capture objective behavioral markers that patients may not recognize or report, including:

  • Sleep disturbances through movement and device usage patterns
  • Social isolation through communication metadata and app usage
  • Avoidance behaviors through location data and activity levels
  • Emotional dysregulation through voice analysis and text communication patterns

2. Virtual Reality Exposure Therapy (VRET)

Exposure therapy represents one of the most empirically supported treatments for PTSD, yet its implementation faces significant practical and psychological barriers. Creating realistic trauma-relevant contexts while maintaining patient safety and therapeutic control presents an inherent challenge. As a technology-enabled PTSD treatment modality, virtual reality technology offers a compelling solution by enabling immersive, controllable experiences that facilitate emotional processing without the logistical challenges of in vivo exposure.

A 2019 meta-analysis of 30 randomized controlled trials involving 1,057 participants, published in the Journal of Anxiety Disorders, found that VRET produced outcomes comparable to in-person exposure therapy3. The analysis revealed several key findings:

  • VRET demonstrated a large effect size (g = 0.90) compared to waitlist controls and a medium to large effect size compared to psychological placebo conditions
  • When compared directly to in vivo exposure therapy, no significant difference in effectiveness was found (g = −0.07), indicating VRET is equally effective
  • The analysis included studies across multiple anxiety disorders: 14 for specific phobias, 8 for social anxiety disorder or performance anxiety, 5 for PTSD, and 3 for panic disorder

Results were relatively consistent across different anxiety disorders, suggesting broad applicability. The technology offers advantages including controlled, gradual exposure that is easy for therapists to implement and often more acceptable to patients than traditional exposure methods.

3. AI-Enhanced Therapy Support

The integration of artificial intelligence into PTSD treatment represents not a replacement for human therapists but an amplification of their capabilities and reach. Natural language processing can analyze therapy session content to identify emotional patterns, treatment engagement markers, and early warning signs of deterioration. Machine learning algorithms, trained on longitudinal datasets, can identify subtle precursors to symptom exacerbation, enabling proactive rather than reactive intervention.

A Stanford University study published in the Journal of Medical Internet Research evaluated an AI therapy app (Youper) for anxiety and depression and found significant improvements over a 4-week period4:

  • Anxiety symptoms reduced by 24% (Cohen’s d = 0.60) from baseline to 28-day follow-up
  • Depression symptoms reduced by 17% (Cohen’s d = 0.42) over the same period
  • High user acceptability with an average rating of 4.84 out of 5 stars
  • Strong retention rates with 89% of users remaining active after week 1 and 67% completing the full 4-week subscription period

These results suggest that AI-enhanced, technology-enabled PTSD treatment protocols may help address accessibility challenges in mental health care by providing scalable, effective interventions that users find engaging and helpful.

4. Precision Treatment Matching 

Perhaps the most transformative application of technology in PTSD treatment lies in the emerging field of precision psychiatry. The considerable heterogeneity in trauma responses—shaped by genetic factors, prior trauma history, developmental timing, and numerous other variables—suggests that treatment effectiveness could be substantially improved through personalized intervention selection.

By integrating multiple data streams—genetic information, digital biomarkers, neuroimaging findings, and detailed clinical phenotyping—we can begin to develop predictive models that match patients to optimal interventions. This approach moves beyond the traditional trial-and-error method of treatment selection toward an evidence-based, personalized strategy.

Recent advances in precision medicine as a technology-enabled PTSD treatment selection demonstrate the potential of personalized treatment approaches. According to the National Center for PTSD, when evidence-based psychotherapies (CPT, PE, or EMDR) are properly matched to patients, 53 out of 100 patients will no longer meet criteria for PTSD, while medication alone achieves remission in 42 out of 100 patients.5 VA’s large-scale Cooperative Studies Program trial (CSP #591) comparing prolonged exposure and CPT across 916 veterans at 18 medical centers represents one of the most ambitious efforts to identify optimal treatment matching strategies.6

Emerging research on treatment personalization includes work on MDMA-assisted therapy, which has shown large effect sizes in recent Phase 3 trials7, and studies demonstrating that CPT delivered via telehealth achieves outcomes equivalent to in-person delivery. Additionally, research has shown that combining treatments—such as dialectical behavior therapy with prolonged exposure—can benefit specific populations, with one study showing 91% of participants experiencing significant PTSD symptom reduction.

These findings suggest we are approaching an era where technology and precision medicine enable us to move beyond asking “what works for PTSD?” to the more nuanced question: “what works best for each individual patient?

Implementation Challenges and Ethical Considerations

The promise of technology-enabled PTSD treatment comes with significant responsibilities. As we navigate this rapidly evolving landscape, several important challenges require thoughtful consideration:

Privacy and security: For trauma survivors, issues of safety, control, and trust take on heightened significance. Any technological intervention must prioritize rigorous data protection and transparent communication about information usage. The principle of “do no harm” extends to ensuring that digital tools themselves do not become sources of vulnerability or retraumatization.

Digital equity: Technology-enabled interventions risk exacerbating existing healthcare disparities if not implemented with attention to access barriers. Research from the Pew Research Center indicates that digital divides persist along socioeconomic, age, and geographical lines—precisely overlapping with populations already underserved in mental healthcare.

Maintaining therapeutic alliance: Technology should enhance rather than diminish the fundamental human connection at the core of trauma recovery. Research shows technology works best complementing, not replacing, therapeutic relationships. A review in the American Journal of Psychiatry found technology-based applications most effective when augmenting treatment through session monitoring and adherence tracking while maintaining the patient-therapist connection.8

Algorithmic transparency and bias: Machine learning models trained on historical clinical data risk perpetuating existing biases in diagnosis and treatment. Ensuring diverse training datasets and ongoing monitoring for disparate impact remains essential for equitable implementation.

These challenges are substantial but not insurmountable. They require interdisciplinary collaboration among clinicians, technologists, ethicists, and—most importantly—individuals with lived experience of PTSD.

The Way Forward: Integrated Technology-Enabled PTSD Treatment

The narrative of technology in PTSD treatment should not be one of replacement but of integration. The implemented “connected care” framework—a model that weaves together evidence-based clinical practices with technological innovation in service of more accessible, personalized, and effective trauma treatment.

This framework consists of four integrated components:

  • Evidence-based therapies delivered by trained clinicians through both in-person and telehealth modalities, including Cognitive Processing Therapy (CPT), Prolonged Exposure (PE), and EMDR
  • Digital measurement systems that capture both subjective experience through ecological momentary assessment and objective functioning through passive monitoring
  • Asynchronous therapeutic support provided through secure messaging, AI-enhanced monitoring, and just-in-time interventions for moments of acute distress
  • Community connection facilitated through moderated peer support networks that address the social isolation often accompanying PTSD

This integrated “connected care” approach is particularly well-suited for PTSD treatment based on several key research findings:

  • Addressing PTSD’s Complex Nature: PTSD is characterized by heterogeneous symptoms including intrusive memories, avoidance behaviors, negative cognitions, and hyperarousal. Research shows that no single intervention addresses all aspects effectively. The multi-modal framework mirrors the disorder’s complexity by targeting different symptom clusters through complementary approaches—evidence-based therapy for core trauma processing, digital monitoring for between-session symptoms, and peer support for social reintegration.
  • Overcoming Treatment Barriers: Studies consistently show that 50% of those with PTSD don’t seek treatment, with rural populations, minorities, and veterans particularly underserved.9 The connected care model directly addresses documented barriers: telehealth eliminates geographic obstacles,10 asynchronous support provides help outside business hours, and peer networks reduce stigma-related reluctance. Research demonstrates that when these barriers are removed, treatment engagement significantly improves.
  • Leveraging Therapeutic Alliance: Evidence indicates that the therapeutic relationship is crucial for PTSD recovery, with treatment outcomes strongly correlated to alliance quality. Rather than diminishing this relationship, the framework enhances it by providing continuous connection between sessions. Clinicians gain richer data about patients’ daily experiences, enabling more personalized interventions while maintaining the human connection essential for trauma healing.11
  • Supporting Neurobiological Healing: PTSD involves dysregulation of fear networks and stress response systems that operate continuously, not just during therapy hours. The 24/7 monitoring and just-in-time interventions align with neuroscience findings showing that repeated, distributed practice of coping skills is more effective for rewiring trauma responses than weekly sessions alone. This matches research on memory reconsolidation and extinction learning.

Evidence-Based Integration: Each component has independent empirical support—CPT/PE/EMDR show 53% remission rates,12 digital phenotyping can detect PTSD with 77% accuracy,13 and peer support improves treatment retention. By combining validated approaches rather than creating entirely new interventions, the framework builds on established efficacy while addressing individual limitations of each component.

Conclusion: Technology as an Assistant in Human Healing

The story of PTSD treatment is ultimately a human story—one of suffering, resilience, and the search for effective pathways to recovery. Technology enters this narrative not as a protagonist but as an enabling force that can help overcome barriers that have limited our ability to address the invisible wounds of trauma.

The integration of digital phenotyping, virtual reality, artificial intelligence, and precision treatment approaches represents more than incremental improvement; it offers the possibility of fundamental transformation in how we conceptualize and deliver trauma care. These technologies allow us to measure what was previously unmeasurable, to reach those who were previously unreachable, and to personalize treatment in ways that were previously unimaginable.

Yet as we embrace these technological possibilities, we must remain grounded in the core principles of trauma-informed care: safety, trustworthiness, choice, collaboration, and empowerment. Technology that fails to embody these principles will ultimately fail to serve those who need it most.

The road ahead requires continued innovation, rigorous evaluation, and a commitment to ethical implementation. It demands collaboration across disciplines and centering the voices of those with lived experience of trauma. Most importantly, it requires us to remember that technology is not an end in itself but a means to advance our fundamental mission: supporting healing and recovery for all who live with the invisible wounds of PTSD.

1. Sidran Institute. (n.d.). Post-traumatic stress disorder statistics. Retrieved from [URL]. As cited in: The Treetop Recovery. (2023). 50+ PTSD statistics & facts: How common is PTSD? Retrieved from https://www.thetreetop.com/statistics/ptsd-statistics-facts-prevelanece

2. Ranjan, G., Nguyen, T. N. B., Meng, H., Kashyap, R., Jain, R., Bhandari, S., Duffecy, J., Langenecker, S. A., Zulueta, J., McInnis, M. G., Merikangas, K. R., De Choudhury, M., & Jacobson, N. C. (2021). Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma. Scientific Reports, 11, Article 10303. https://doi.org/10.1038/s41598-021-89768-2

3. Carl, E., Stein, A. T., Levihn-Coon, A., Pogue, J. R., Rothbaum, B., Emmelkamp, P., Asmundson, G. J. G., Carlbring, P., & Powers, M. B. (2019). Virtual reality exposure therapy for anxiety and related disorders: A meta-analysis of randomized controlled trials. Journal of Anxiety Disorders, 61, 27-36. https://doi.org/10.1016/j.janxdis.2018.08.003

4. Mehta, A., Niles, A. N., Vargas, J. H., Marafon, T., Couto, D. D., & Gross, J. J. (2021). Acceptability and effectiveness of artificial intelligence therapy for anxiety and depression (Youper): Longitudinal observational study. Journal of Medical Internet Research, 23(6), e26771. https://doi.org/10.2196/26771

5. National Center for PTSD. (2023). Overview of psychotherapy for PTSD. U.S. Department of Veterans Affairs. Retrieved from https://ptsd.va.gov/professional/treat/txessentials/overview_therapy.asp

6. VA Cooperative Studies Program. (2023). Head-to-head comparison of prolonged exposure and CPT (CSP #591). U.S. Department of Veterans Affairs. Retrieved from https://www.research.va.gov/topics/ptsd.cfm

7. Mitchell, J. M., et al. (2021). MDMA-assisted therapy for severe PTSD: A randomized, double-blind, placebo-controlled phase 3 study. Nature Medicine, 27(6), 1025-1033.

8. Harvey, P. D., Goldberg, T. E., Bowie, C. R., Moeller, D., Horan, W. P., Hellemann, G., Wilder, C., Kotwicki, R. J., & Velligan, D. I. (2023). Technology and mental health: State of the art for assessment and treatment. American Journal of Psychiatry, 180(9), 638-648. https://doi.org/10.1176/appi.ajp.21121254

9. Sidran Institute. (n.d.). Post-traumatic stress disorder statistics. As cited in: The Treetop Recovery. (2023). 50+ PTSD statistics & facts: How common is PTSD? Retrieved from https://www.thetreetop.com/statistics/ptsd-statistics-facts-prevelanece

10. National Center for PTSD. (2023). PTSD and telemental health. U.S. Department of Veterans Affairs. Retrieved from https://www.ptsd.va.gov/professional/treat/txessentials/telemental_health.asp

11. Harvey, P. D., et al. (2023). Technology and mental health: State of the art for assessment and treatment. American Journal of Psychiatry, 180(9), 638-648. https://doi.org/10.1176/appi.ajp.21121254

12. National Center for PTSD. (2023). Overview of psychotherapy for PTSD. U.S. Department of Veterans Affairs. Retrieved from https://ptsd.va.gov/professional/treat/txessentials/overview_therapy.asp

13. Ranjan, G., et al. (2021). Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma. Scientific Reports, 11, Article 10303. https://doi.org/10.1038/s41598-021-89768-2

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Why We Made TDScreen Free: A CEO’s Perspective on Democratizing Mental Health Screening

TDScreen AI-powered TD screening tool interface showing patient assessment dashboard

Last week we announced the launch of TDScreen – our AI-powered Tardive Dyskinesia (TD) screening tool. The response has been immediate and overwhelming, validating everything we believed about the urgent need for accessible TD screening.

This is exactly why we built TDScreen.

The Hidden Crisis in Plain Sight

Let me share some numbers that keep me up at night:

  • At least 500,000 Americans suffer with Tardive Dyskinesia
  • Only 20% of those  have been diagnosed
  • That’s a 80% diagnosis gap

But here’s what those statistics don’t capture: Each untreated case represents someone whose involuntary movements might be dismissed as nervousness, aging, or “just a quirk.” Someone who might stop taking life-changing medications because they’re embarrassed by movements that could be managed. Someone whose quality of life is quietly deteriorating while effective treatments exist.

Why Traditional Screening Fails

The standard AIMS assessment takes 15-20 minutes of specialized clinical time. For a psychiatrist seeing 20-30 patients daily, screening everyone quarterly (as guidelines recommend) is mathematically impossible. It’s not about clinician dedication – it’s about the brutal reality of time constraints in modern healthcare.

This is where AI changes everything. TDScreen compresses expert-level assessment into a 5-minute patient self-assessment, with accuracy that actually exceeds human raters (0.89 AUC, validated in our Journal of Clinical Psychiatry study).

The Business Decision to Make TDScreen Free

We’re not in the business of gatekeeping essential healthcare tools. We’re in the business of transforming behavioral health outcomes.

Making TDScreen free isn’t charity – it’s strategy. Every provider who adopts TDScreen becomes part of our mission to modernize behavioral healthcare. Every patient who gets screened is a potential life improved. And every success story builds the foundation for our broader platform vision.

What Our TD Screening Tool Actually Does

For providers wondering about the specifics – here’s exactly what you get:

Immediate Clinical Value

  • Patient completes video assessment (smartphone, tablet, or computer)
  • AI analyzes movement patterns based on AIMS criteria
  • You receive an objective risk score with visual highlights
  • Track changes over time with quantitative data

Zero Hidden Costs

  • No subscription fees
  • No per-patient charges
  • No training requirements
  • No IT integration needed
  • Start screening in under 15 minutes

The Evidence Behind TDScreen

Our research, published yesterday in the Journal of Clinical Psychiatry, demonstrates that TDScreen achieves:

  • Superior consistency compared to human raters (Cohen’s Kappa of 0.61)
  • Validated across 350+ patients in multi-site clinical trials

This isn’t theoretical – it’s proven technology ready for clinical use today. Our partners in the study – Dr. Anthony A. Sterns, Ph.D., lead researcher on the project and CEO at iRxReminder, Dr. Owen Muir, CMO of iRxReminder, CMO and co-founder of Radial Health, and co-author of the publication, and the National Institutes of Health – provided the data and analysis that helped to create TDScreen.

The Bigger Vision

Why This TD Screening Tool Changes Everything

TDScreen is just the beginning. At Videra Health, we’re building a comprehensive AI platform that transforms how behavioral health providers deliver care. But we started with TD screening for a reason: it’s a massive, solvable problem where AI demonstrably outperforms traditional methods.

By making TDScreen free, we’re proving that AI in healthcare doesn’t have to be expensive, complex, or intimidating. It can be as simple as sending your patient a link.

Your Patients Are Waiting

If you prescribe antipsychotics, you have patients at risk for TD. Statistically, several already have symptoms. The question isn’t whether to screen – it’s whether you’ll do it the old way or the better way.

TDScreen is live, validated, and free at tdscreen.ai.

No sales calls. No demos required. No contracts to sign.

Just better care, starting today.

Join the Movement

In healthcare innovation, the best time to adopt new technology is when it’s proven but not yet universal. TDScreen has the validation (peer-reviewed research), the accessibility (completely free), and the simplicity (5-minute assessments) to transform TD screening.

The providers who adopt TDScreen today aren’t just using a tool – they’re setting a new standard of care for their patients.

Will you join us?

Start screening at tdscreen.ai

Register for TDScreen now

Videra Health Launches TDScreen, a First-of-Its-Kind Video-based, AI-powered Tool to Assess Tardive Dyskinesia Symptoms

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New study published in the Journal of Clinical Psychiatry reveals AI enables efficient, accurate and scalable detection of TD, representing a significant advancement in meeting the standard of care for TD screening

Orem, UT, June 3, 2025 – Videra Health, a leading AI platform for behavioral health providers, has announced the launch of TDScreen, the first-ever automated, video-based AI solution on the market to screen for Tardive Dyskinesia (TD) symptoms. TD is a chronic, involuntary movement disorder that can develop as a side effect of long-term use of certain medications, particularly antipsychotic drugs. While TDScreen isn’t intended as a standalone diagnostic tool, it represents a significant advancement in meeting the standard of care for TD screening.

TD presents unique screening challenges even for experienced clinicians and remains underdiagnosed. TD affects up to 2.6 million Americans, and up to 7 million Americans taking antipsychotic medications could develop TD symptoms. With its involuntary movements often mistaken for nervousness, aging, or other conditions, the gap in recognition represents not just a clinical challenge, but a deeply human one that affects quality of life and treatment outcomes. A paper published Wednesday in The Journal of Clinical Psychiatry, led by Principal Investigator Dr. Anthony Sterns and members of the iRxReminder and Videra Health teams, reveals that video-based AI enables efficient, accurate, and scalable detection of TD. This application has the potential to significantly improve early diagnosis and patient outcomes, especially in remote care settings where resources are scarcest. Videra Health’s TDScreen algorithm was built using the data from multiple studies, which was supported in part by the National Institute of Mental Health, and represents a significant leap forward in integrating artificial intelligence into psychiatric care, particularly in the era of telemedicine.

“Videra Health is thrilled to be able to launch a first-of-its-kind innovative solution to screen for TD symptoms, effectively,” said Loren Larsen, CEO of Videra Health. “TDScreen and our broader AI platform aren’t about replacing clinician judgment—they’re about enhancing it. By automating routine screenings, we free healthcare providers to focus on what matters most: the human connections and complex decision-making that drive quality care.” Larsen added, “We are grateful for the multiple academic and research partners who have contributed their time and expertise to these studies.”

“Early detection of TD is critical to mitigating its debilitating effects,” said Dr. Anthony A. Sterns, Ph.D., lead researcher on the project and CEO at iRxReminder. “Our AI-driven approach not only matches but exceeds human expert performance, offering a scalable solution to a major unmet clinical need,” added Dr. Joel W. Hughes, Ph.D., collaborator from Kent State University.

“As a physician who both treats –and lives with– tardive dyskinesia, this research marks a turning point for millions of patients who have been forced to wonder if the movement disorder they suffer from could be treatable,” says Owen S, Muir, M.D., CMO of iRxReminder, CMO and co-founder of Radial Health, and co-author of the publication.  “Now, physicians have a simple, evidence-based AI-guided tool to support their clinical decision making.”

TDScreen was validated across three clinical studies involving more than 350 participants on antipsychotic medications. The innovative AI tool developed by Videra Health utilizes advanced video analysis and a vision transformer machine learning architecture to detect TD with unprecedented accuracy. TDScreen demonstrates a Cohen’s Kappa of 0.61—a number indicating the algorithm is outperforming even calibrated human raters. The algorithm achieved an area under the receiver-operating-characteristic curve (AUC) of 0.89, surpassing the sensitivity and specificity of trained human raters using the standard Abnormal Involuntary Movement Scale (AIMS).

These numbers represent more than just statistical achievements—they translate to real-world benefits:

  • Consistency: Unlike human raters whose assessments may vary, AI provides the same evaluation standards every time
  • Accessibility: Patients can complete assessments from home on their own devices
  • Efficiency: Providers save valuable clinical time while increasing screening frequency
  • Earlier detection: Subtle symptoms can be identified before they become pronounced

Continuous monitoring: Regular assessments track symptom progression or improvement

With TDScreen, patients on antipsychotics can easily complete video-based screenings in-office or remotely, and enable providers to monitor or modify their treatment plans. The TDScreen tool is based on the Abnormal Involuntary Movement Scale (AIMS), a comprehensive clinician-rated scale designed to specifically evaluate involuntary movements. Employing advanced AI video technology, TDScreen efficiently assesses and quantifies the risk of TD in less than 5 minutes. The resulting score generated by this assessment can aid in clinical decision-making and management strategies.

TDscreen is available free of charge for any provider or patient wanting to screen for TD. Visit tdscreen.ai to learn more.

About Videra Health™

Videra Health is a leading AI platform for behavioral health providers and proactively identifies, triages and monitors at-risk patients using linguistic, audio and video analysis. The FDA-registered digital platform transforms how doctors and healthcare systems interact and track a patient’s journey, illuminating the hidden depths of patient behavior and outcomes. Videra Health connects providers and patients anytime, anywhere, between visits and post-discharge via written and video assessments that translate into actionable quantitative and qualitative patient data. The platform streamlines diagnoses, enhances care accessibility, optimizes workflows and drives down costs for providers and healthcare systems. 

For more information, visit www.viderahealth.com.

About iRxReminder
iRxReminder specializes in digital health solutions aimed at enhancing medication adherence and mental health management through cutting-edge technology applications and innovative behavioral science solutions.

For more information, visit www.irxreminder.com.

How AI Expands Care When Care Demands Continues to Rise

Healthcare provider using AI mental health platform on tablet while speaking with patient, illustrating how AI in mental healthcare amplifies human care

As we recognize Mental Health Awareness Month this May, we find ourselves at a critical juncture where AI in mental healthcare offers promising solutions. The need for mental health services continues to grow at an unprecedented rate, while provider shortages and burnout intensify. According to data from across the healthcare landscape, 47% of the U.S. population now lives in an area with a mental health workforce shortage, and wait times for appointments often stretch beyond three months.

At Videra Health, we’ve been tackling this challenge head-on, working with providers who face the daily reality of trying to deliver quality care despite limited resources. Our experiences have revealed a fundamental truth: we cannot simply produce more clinicians fast enough to meet the growing demand. Instead, we must find innovative ways to expand the reach and impact of our existing clinical workforce.

The Human Understanding Gap: Where AI in Mental Healthcare Makes a Difference

The core of effective mental healthcare has always been human connection and understanding. Providers need to know not just what their patients are saying, but how they’re feeling, their emotional state, and whether they’re at risk. Traditionally, this understanding has been limited to in-office interactions, creating significant blind spots in patient care journeys.

What happens when a patient struggling with depression has a difficult week between appointments? How can a substance use disorder treatment center identify which discharged patients are at risk of relapse? How do we ensure that individuals experiencing suicidal ideation are identified and supported before reaching crisis?

These questions highlight what I call the “human understanding gap” – the critical information about patient wellbeing that falls through the cracks between formal care touchpoints.

AI in Mental Healthcare: Building Bridges, Not Replacements

This is where thoughtfully designed AI systems can make a transformative difference. At Videra, we’ve seen firsthand how clinical AI can serve as a bridge that extends human care, rather than replacing it.

Our platform uses video, audio, and text assessments powered by artificial intelligence to understand patients in their own words and on their own time. By analyzing facial expressions, voice patterns, language, and behavioral indicators, we can identify signs of emotional distress, suicidal language, medication adherence challenges, and other critical indicators that might otherwise go unnoticed between appointments.

The results have been profound. In one behavioral health system implementation, we’ve seen that patients with higher engagement in post-discharge monitoring demonstrate significantly stronger recovery outcomes. Another community mental health center utilizing our technology reduced crisis alerts by 64% after just two weeks of proactive monitoring.

Amplifying Human Care, Not Replacing It

The most important lesson we’ve learned is that effective clinical AI doesn’t aim to replace human providers – it amplifies their capabilities and extends their reach. By handling routine clinical assessments and identifying at-risk patients, AI creates a force multiplier for clinical expertise, allowing providers to direct their specialized skills where they’re needed most.

For example, our automated assessment system can engage thousands of patients consistently and frequently to identify those with acute needs, before, during or after care. Our note-taking technology reduces documentation time, giving clinicians more face-to-face time with patients. And our monitoring tools provide continuous support between appointments, creating a safety net that would be impossible to maintain manually.

This clinical enhancement works alongside our workflow solutions, which address a separate but complementary need. While clinical AI focuses on assessment and insights, our workflow tools tackle the administrative burdens that consume valuable provider time.

The result is a multiplier effect on care capacity. Providers using these integrated AI-powered clinical and workflow tools can effectively support more patients without sacrificing quality of care – in fact, they can often deliver better outcomes by focusing their expertise where it’s most needed.

Looking Forward: The Future of AI in Mental Healthcare

As we look ahead, I believe we’re only beginning to tap into AI’s potential to address the growing mental health crisis. Future developments will likely include:

  • More sophisticated risk prediction models that can identify potential issues before they become crises
  • Deeper integration with treatment pathways to provide personalized care recommendations
  • Enhanced accessibility tools that break down barriers to care for underserved populations
  • Advanced training systems that help new clinicians develop expertise more quickly

At Videra Health, we’re committed to advancing these innovations responsibly, always keeping the human connection at the center of our work. Because ultimately, the goal isn’t to build AI that replaces humans – it’s to build AI that helps humans help more humans.

A Call to Action

As we observe Mental Health Awareness Month, I encourage healthcare leaders to consider how AI can extend your organization’s capacity to deliver care. The mental health crisis isn’t waiting, and neither should we.

We need to embrace tools that allow us to do more with our existing resources, reaching patients when and where they need support. By implementing AI in mental healthcare thoughtfully, we can ensure that more people receive the care they need, when they need it most.

Together, we can build a future where technology and human connection work in harmony to meet the growing demand for mental healthcare – not by replacing the invaluable work of clinicians, but by amplifying their impact and extending their reach.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Discovery Behavioral Health boosts care and revenue with patient engagement efforts

Healthcare IT News highlights how Discovery Behavioral Health is advancing patient care and operational efficiency through post-discharge engagement powered by AI. By implementing a white-labeled version of Videra Health’s video-based assessment platform, Discovery extended support beyond the walls of its facilities—gaining real-time insights into patient recovery and unlocking new opportunities for early intervention and re-engagement. This proactive, tech-enabled approach exemplifies the shift toward continuous, personalized care across the behavioral health spectrum. With measurable improvements in patient outcomes and provider efficiency, the article shows how innovation can meaningfully transform the recovery journey.
Read the full article here.

Managing Stress in the Digital Age: Practical Tools for Behavioral Health Clinics

digital solutions for behavioral health clinicians

In today’s fast-paced healthcare environment, behavioral health clinicians face unprecedented challenges. Rising patient demand, administrative burdens, and the constant pressure to deliver high-quality care can create a perfect storm of stress for even the most dedicated professionals. As Videra Health’s Chief Clinical Officer, I’ve witnessed firsthand how digital solutions can either add to this burden or, when thoughtfully implemented, help alleviate it.

The Growing Challenge

The statistics paint a clear picture: nearly half of the U.S. population lives in a mental health workforce shortage area, average wait times for mental health services exceed three months, and no-show rates hover around 30%. These challenges create immense pressure on clinicians, leading to burnout and decreased quality of care.

However, I’ve observed a positive shift in how behavioral health organizations are leveraging technology to address these challenges. The right digital tools can transform workflows, enhance patient engagement, and provide valuable insights that improve both clinical outcomes and staff wellbeing.

Digital Solutions That Actually Help

At Videra Health, we’ve worked with hundreds of behavioral health organizations to identify which digital approaches actually reduce clinician stress rather than adding to it. Here are key strategies we’ve found most effective:

1. Automate Administrative Tasks, Not Clinical Judgment

The most successful digital implementations focus on eliminating repetitive administrative tasks while preserving and enhancing clinicians’ unique expertise and judgment. For example, automating intake assessments and post-discharge follow-ups can save hours of staff time while still providing rich clinical data.

When our client’s large behavioral health practice implemented automated post-discharge monitoring, they didn’t just save staff time—they identified patients needing intervention who might otherwise have fallen through the cracks. As one clinician shared, “We had four alerts over the weekend, and we were able to reach out to support clients and one came back for services… we would have never been able to find these patients in time without Videra.”

2. Implement Proactive Risk Identification

One of the most stressful aspects of behavioral health practice is worrying about patients between sessions. Digital tools that allow for ongoing monitoring and proactive risk identification can alleviate this burden.

Our experience with behavioral health support services shows that timely alerts for emotional distress, suicidal ideation, and other concerning patterns can enable early intervention. This not only improves patient outcomes and scales across the entire patient population, but also reduces the psychological burden on clinicians who otherwise might worry about patients between appointments.

3. Leverage Multimodal Assessments

Traditional questionnaire-based assessments only tell part of the story. Modern behavioral health platforms that incorporate video, audio, and text assessments can capture much richer data. This approach allows patients to express themselves in their own words, providing clinicians with deeper insights while reducing the time needed to gather comprehensive information.

One clinician noted, “Because Videra is video-based, it gives the clinician or staff the very information that you would be looking for if the patient were sitting across from you in your office.” This deeper understanding helps clinicians make more informed decisions more efficiently.

4. Focus on Meaningful Measurement

Not all data is created equal. The most effective digital solutions focus on collecting and analyzing information that directly informs clinical decisions and improves care.

By tracking key metrics like changes in PHQ-9 scores, medication adherence, and social determinants of health over time, clinicians can identify trends and adjust treatment plans accordingly. This data-driven approach not only improves patient outcomes but also gives clinicians confidence that their interventions are having the desired effect.

5. Engage Patients Between Visits

Patient engagement doesn’t have to stop when the session ends. Digital platforms that facilitate ongoing communication and support between visits can extend the impact of therapy while reducing the pressure on in-person appointments.

Research shows that patients with higher engagement in digital follow-up programs demonstrate stronger recovery, with better protective factors and lower relapse rates. This continuous engagement creates a more sustainable care model for both patients and providers.

The Human Element Remains Essential

As we embrace these digital solutions, it’s crucial to remember that technology should enhance rather than replace the human connection at the heart of behavioral healthcare. The most effective implementations leverage technology to handle routine tasks, gather information, and identify risks—freeing clinicians to focus on what they do best: providing compassionate, personalized care.

One CCBHC director summarized it perfectly: “Technology doesn’t replace our clinicians—it amplifies their impact by ensuring they can focus their time and expertise where it’s needed most.”

Moving Forward Together

The future of behavioral healthcare isn’t about choosing between human expertise and digital efficiency—it’s about thoughtfully integrating both to create more sustainable, effective, and scalable care models. By implementing the right digital tools in the right way, behavioral health organizations can reduce clinician stress, improve patient outcomes, and build more resilient healthcare systems.

At Videra Health, we’re committed to supporting this integration with solutions designed specifically for the unique challenges of behavioral healthcare. Together, we can create a future where technology doesn’t add to clinician burden but instead helps create more manageable, rewarding work environments where both providers and patients can thrive.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Improving Intake Processes Without Overloading Staff: Technology’s Role in Patient Flow

As healthcare providers, we all share a common challenge: efficiently managing the automated healthcare intake process while maintaining quality care and not overwhelming our already stretched staff. Whether you’re running a behavioral health clinic or coordinating clinical trials, intake processes often create bottlenecks that impact everything downstream.

The Automated Healthcare Intake Revolution

The statistics tell a sobering story. Traditional intake assessments typically require 30-60 minutes of clinical time per patient, with staff spending additional hours on documentation and coordination. For many behavioral health organizations, this translates to:

  • Extended wait times averaging 3+ months for new patient appointments
  • High no-show rates (often exceeding 30%) due to delayed access
  • Significant administrative burden leading to clinician burnout
  • Lost revenue from unfilled appointments and incomplete assessments

Clinical trial administrators face similar challenges, with participant screening and enrollment often consuming 30% of total study costs and extending timelines by months.

How Our Automated Healthcare Intake Process Works

At Videra Health, we’ve focused on developing solutions that specifically address these intake challenges while preserving what matters most – the human connection between providers and patients.

Our Videra Intake Manager transforms the traditional intake process by combining AI-driven automation with thoughtful human design. This system allows patients to complete comprehensive assessments on their own time while automatically generating the documentation your team needs.

Key capabilities include:

  • Automated pre-screening that identifies appropriate level of care before the first appointment
  • Self-directed video assessments that capture rich clinical information without provider time
  • AI-assisted documentation that generates structured intake reports
  • Seamless EHR integration that eliminates duplicate data entry
  • Multi-language support that expands access to diverse populations

Real Results from Real Implementations

Behavioral health organizations implementing our intake solutions have reported impressive outcomes:

  • 50% reduction in administrative time spent on new patient processing
  • 35% increase in completed intake appointments
  • 28% decrease in time-to-treatment for new patients
  • 42% improvement in staff satisfaction with intake processes

For clinical trial administrators, our system has demonstrated:

  • 40% faster participant screening and enrollment
  • 65% reduction in administrative processing time
  • 30% improvement in protocol adherence during screening
  • Significant enhancement in participant diversity through expanded access

A Practical Implementation Approach

The most successful implementations we’ve seen take a phased approach. Rather than completely overhauling existing processes, many organizations begin by implementing Videra Assess for pre-appointment screening, then gradually integrate more automation as staff and patients become comfortable with the technology.

This measured approach ensures that technology enhances rather than disrupts your care delivery model, with each phase building on previous successes.

Looking Forward: The Integrated Intake Ecosystem

The future of intake management lies in seamless integration between automated assessment tools, documentation systems, and advanced operational tools.

Together, these create an ecosystem that not only improves efficiency but actually enhances the quality of clinical information gathered during the intake process.

To learn more about how Videra Health can transform your intake processes, schedule a personalized demonstration with our team.

Your patients deserve prompt access to care, and your staff deserves technology that makes their jobs easier rather than more complicated. Let’s work together to make that a reality.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

5 Ways AI Can Help Mental Health Clinicians Manage a Growing Caseload

As mental health providers face mounting caseloads and rising demand, AI offers a path forward by enhancing efficiency without sacrificing personalized care. This article highlights how AI-powered screening platforms, rooted in measurement-based care, are helping clinicians prioritize high-risk patients, automate routine tasks, and extend their reach beyond the office. The result is more time for meaningful client interactions and stronger therapeutic relationships—hallmarks of quality care. With the right implementation, AI serves not as a replacement, but as a trusted partner in the delivery of smarter, more responsive mental health services.
Read the full article here.

How AI is Empowering Providers with Early Detection of Mental Illness

AI is transforming mental health care by enabling earlier, more precise detection of symptoms that might otherwise go unnoticed until crisis points. This thoughtful piece explores how technology can continuously monitor subtle behavioral shifts—augmenting clinical expertise and allowing providers to intervene sooner. By analyzing data across multiple modalities and comparing patients to their own baselines, AI supports a shift from reactive treatment to proactive care. The result is better outcomes, lower costs, and a future where clinicians are empowered—not replaced—by intelligent tools.
Read the full article here.

Breaking Down Barriers: How CCBHCs Can Lead Healthcare Access Innovation

As we gather for the NACBHDD Legislative and Policy Conference in Washington DC, I’m struck by the critical conversations around innovation and access to behavioral healthcare. The conference agenda highlights what many CCBHC leaders already know – we’re facing multiple, interrelated challenges: medical debt, administrative burdens, workforce shortages, and coordination with justice systems.

At Videra Health, we’re seeing CCBHCs tackle these challenges through innovative approaches to care delivery. Key trends emerging from our partnerships include:

The upcoming Medicaid discussions at the conference are particularly relevant. As the largest payer of behavioral health services, changes to Medicaid structure will significantly impact CCBHCs’ ability to serve their communities. We must ensure that technological innovation aligns with policy evolution to support, not hinder, access to care.

Looking ahead, CCBHCs are uniquely positioned to lead healthcare transformation. By combining policy advocacy with practical innovation, we can create more accessible, efficient, and effective behavioral health systems.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Transforming Clinical Trials: The Power of Multi-Modal AI Assessment

Multimodal AI clinical trials dashboard showing video, voice and text analysis

As pharmaceutical companies seek to develop new treatments for behavioral health and movement disorders, traditional trial designs often struggle to capture the full spectrum of patient experiences and treatment effects. The challenge isn’t just gathering more data – it’s gathering the right data at the right time.

Through our work supporting clinical trials, we’ve found that combining multiple modes of AI analysis – video, voice, and text – provides a more comprehensive understanding of treatment response. This integrated approach allows research teams to:

  • Track subtle changes in movement patterns that may indicate treatment effects
  • Analyze speech patterns for cognitive and emotional indicators
  • Monitor facial expressions for signs of distress or improvement
  • Capture patient-reported experiences in their own words
  • Document symptoms consistently between site visits

This comprehensive approach benefits multiple stakeholders:

For Research Teams:

  • More frequent assessment points without increasing site burden
  • Earlier detection of safety signals
  • Objective measurement of subjective experiences
  • Improved protocol compliance monitoring

For Patients:

  • More natural assessment experience
  • Fewer in-person visits required
  • Ability to report symptoms in real-time
  • Multiple channels for sharing their experience

For Sponsors:

  • Richer data for efficacy analysis
  • Better engagement and retention
  • More complete safety monitoring
  • Potential for novel endpoints

As we look to the future of CNS drug development, moving beyond traditional endpoints isn’t just about technology – it’s about better understanding the patient journey. Multi-modal AI assessment helps bridge the gap between periodic site visits, providing a more complete picture of treatment impact.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

2025 Trends in Behavioral Health Technology – Part 2

Two hands - one human, one robotic - pointing to 2025

As discussed in part one of this series, the behavioral health technology landscape is undergoing a profound metamorphosis, with artificial intelligence (AI) and digital technologies reshaping how behavioral health professionals train, deliver care, and interact with patients. Here’s the last four trends I think will impact the behavioral healthcare space in 2025.

Intelligent Training and Skill Development

Continuous improvement has always been the hallmark of exceptional clinical practice. Now, AI is revolutionizing how behavioral health professionals refine their craft. Imagine a world where every therapy session becomes a learning opportunity—not through traditional supervision alone, but through intelligent, nuanced feedback systems that can analyze communication patterns, emotional resonance, and therapeutic techniques with unprecedented depth.

Advanced AI tools can now listen to therapy sessions, providing granular insights into communication effectiveness. These systems don’t just provide mechanical feedback; they offer sophisticated analysis of therapeutic alliance, helping clinicians understand subtle interpersonal dynamics that might otherwise go unnoticed. Simulated training environments allow practitioners to practice with AI patients, creating safe spaces to experiment with diverse therapeutic approaches and develop skills for treating populations they might find challenging.

This isn’t about replacing human supervision but augmenting it. By reducing time and cost barriers associated with traditional training methods, these technologies democratize professional development, allowing more practitioners to access high-quality skill enhancement.

The Emerging Landscape of Digital Therapeutics

The regulatory landscape for digital behavioral health tools is rapidly evolving. The FDA’s increasing approval of digital therapeutics and CMS’s recent Medicare billing codes represent a watershed moment. What was once considered experimental is now becoming mainstream healthcare.

Digital therapeutics are no longer peripheral technologies but integrated healthcare solutions. Much like traditional prescriptions, clinicians can now “prescribe” FDA-approved digital applications. This represents a fundamental shift in how we conceptualize behavioral health treatment—expanding therapeutic interventions beyond traditional in-person or telehealth models.

However, this emerging ecosystem is not without risks. The proliferation of behavioral health apps has created a complex marketplace where marketing claims often outpace clinical evidence. Consumers and practitioners must develop sophisticated digital literacy, distinguishing between rigorously tested interventions and unsubstantiated digital offerings.

Navigating the Ethics of AI in Therapy

The potential for AI to automate risk assessment and even conduct preliminary therapeutic interactions is tantalizing. Yet, this technological frontier demands careful navigation. While AI tools can provide initial screenings and support, they cannot—and should not—replace the profound human elements of therapeutic relationships.

We are witnessing the early stages of what might become a regulatory “Wild West” in digital behavioral health. Expect increased scrutiny, with regulatory bodies working to establish clear guidelines that protect patient safety while allowing technological innovation.

A Holistic View of Technological Integration

These trends are not isolated developments but interconnected elements of a broader transformation. They represent a holistic reimagining of behavioral healthcare—where technology serves as an empowering tool, not a replacement for human connection.

The most successful organizations will be those that view these technologies not as standalone solutions but as integrated components of a comprehensive care strategy. Success will depend on maintaining a delicate balance: leveraging technological capabilities while preserving the irreplaceable human elements of empathy, nuance, and genuine therapeutic connection.

Embracing Responsible Innovation

As we move deeper into 2025, the behavioral health landscape stands at a critical juncture. The technologies emerging today have the potential to democratize behavioral healthcare, reduce systemic barriers, and create more personalized, effective treatment modalities.

Yet, with this potential comes profound responsibility. Our challenge is not merely to adopt new technologies but to do so thoughtfully, ethically, and with an unwavering commitment to patient well-being.

The future of behavioral health is not about technology replacing human care—it’s about technology expanding and enhancing our capacity for compassion, understanding, and healing.

Deep Dive Into the Trends

Curious about how these technologies impact care, how the regulatory landscape is changing to meet the new paradigm, or how AI can help super-charge efforts to bring new medications to market? Join our webinar on January 31, 2025 at 3PM ET / 12PM PT to discuss 2025 trends and what it means for healthcare.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

2025 Trends in Behavioral Health Technology, Part 1

Two hands - one human, one robotic - pointing to 2025

The First Three Trends

As we enter 2025, the behavioral health technology landscape is on the cusp of a revolution, with artificial intelligence (AI), digital tools, and innovative approaches poised to dramatically reshape how mental health services are delivered, accessed, and personalized. I expect these first three key emerging trends will fundamentally alter the healthcare ecosystem.

Expanding Access and Democratizing Behavioral Health Care with Technology

Digital health technologies are emerging as powerful democratizing forces in healthcare delivery. For populations historically marginalized—rural communities, economically constrained individuals, and underserved demographic groups—AI and digital platforms represent more than technological solutions. They are bridges to care, pathways to understanding, and tools of empowerment.

These technologies are not about replacing human connection but extending its reach. By breaking down geographical, economic, and systemic barriers, they create opportunities for more inclusive, accessible behavioral health support. Intelligent systems can now provide initial screenings, offer preliminary support, and guide individuals towards appropriate resources with unprecedented sensitivity and efficiency.

The Precision Medicine of Behavioral Health

 The era of one-size-fits-all treatment is rapidly dissolving. Artificial intelligence is ushering in a new paradigm of precision behavioral healthcare, where treatment plans are as unique as the individuals receiving them. By analyzing complex, multi-dimensional datasets, AI can now recommend care pathways with a level of personalization that was once the domain of highly specialized, resource-intensive approaches.

This isn’t about algorithmic replacement of clinical judgment but about providing clinicians with powerful, nuanced tools for understanding and supporting patient well-being. Each recommendation is a collaborative insight, bridging technological sophistication with human empathy.

Navigating the Ethical Considerations in the Human-Technology Interface

As we embrace these transformative technologies, we must remain vigilant about maintaining the core ethical principles of healthcare. Artificial intelligence and digital tools are powerful assistants, not autonomous decision-makers. They augment human capability, illuminate hidden insights, and create opportunities for more profound, more personalized care.

The most successful approaches will be those that view behavioral health technology not as a replacement for human interaction but as a sophisticated tool for enhancing our collective capacity for understanding, compassion, and healing.

Read part two of my Top Trends for 2025 here.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Patient Safety & Quality Healthcare (PSQH): Revolutionizing Mental Healthcare Through AI-Enhanced Provider-Patient Relationships

In a recent feature for Patient Safety and Quality Healthcare (PSQH), our CEO Loren Larsen emphasized the transformative role of AI in improving mental health provider-patient relationships.

The mental health sector is overwhelmed by increasing demand, paired with significant shortages in clinical staff. Traditional care models are not equipped to handle the need for more frequent monitoring between in-person sessions.

This article delves into how AI and video technology can revolutionize mental healthcare:

  • AI-assisted screenings: Automate and enhance the accuracy of assessments.
  • Video-based evaluations: Offer real-time insights into patient mental health.
  • Continuous patient monitoring: Leverage AI to analyze emotional and behavioral changes over time.

This AI-driven approach enables providers to:

  • Deliver more personalized care.
  • Identify high-risk patients earlier.
  • Enhance patient outcomes with timely interventions.

Read the full article here. 

HIT CONSULTANT: 3 Ways AI Can Reduce Relapse Rates in Behavioral Health

The article “3 Ways AI Can Reduce Relapse Rates in Behavioral Health” by Fred Pennic discusses the persistent hurdle of high relapse rates in behavioral health treatment and how AI is emerging as a powerful tool to combat this problem. With up to 80% of individuals with substance use disorders experiencing relapse, both patients and providers are often discouraged. However, the use of AI technology, such as the platform provided by Videra Health, offers hope for better outcomes.

One of the key benefits of AI in reducing relapse rates is its ability to detect warning signs earlier than traditional methods. By analyzing a combination of video, audio, and text data, AI can identify subtle changes in a patient’s behavior or emotional state, allowing for earlier intervention and prevention of full relapse episodes.

Moreover, AI-driven platforms offer other valuable tools for reducing relapse rates, such as data-driven decision-making, smarter interventions tailored to individual needs, and continued monitoring through remote assessments. These capabilities help identify potential triggers, personalize treatment strategies, and provide ongoing support for sustained recovery.

One significant advantage of using AI in behavioral health treatment is its ability to provide objective data for measurement-based care. This approach empowers providers to deliver more effective and personalized care plans, leading to improved patient outcomes and significant reductions in relapse rates.

Overall, AI-powered screening and remote patient monitoring platforms are changing the game in behavioral health treatment. They provide early detection, personalized care, and objective data to support long-term recovery and reduce overall healthcare costs associated with addiction treatment. With AI as a game-changer in this field, there is hope for a future with improved outcomes and reduced relapse rates for those seeking behavioral health treatment. Read the full article here.