Nidal Moukaddam, MD, PhD

Tales From the Clinic: The Art of Psychiatry,

 we cover an intriguing case of dual substance use super-imposed on mood, anxiety, and trauma clinical picture. A significant challenge for this group of patients is the need for patient, methodical, consistent care to unravel the complex multifaceted triggers and perpetuating factors for continued maladaptive behaviors. The case description spans years of treatment and, while the details may seem sensational, they reflect the reality of what the addiction treatment clinic team encounters. In addition, there is much difficulty in hearing and processing patient accounts of trauma, which could lead to physician burnout.

“Ms Martin” is a 45-year-old female with bipolar disorder, generalized anxiety disorder, and suspected borderline personality disorder. She was transferred to the substance use disorders clinic by another psychiatrist after a diagnosis of opioid use disorder was obvious. At the time of her transfer, she was involved in prostitution to finance her roughly 25 tablets of acetaminophen and hydrocodone daily. Her opioid use disorder history had a protracted course, with her first exposure to prescription opioids at the age of 16 following a significant injury requiring surgical intervention. Her longest lifetime period of sobriety was 2 years.

A Love Letter to the Patient-Physician Relationship

Her immediate environment was not conducive to recovery, as she lived in a trailer with a male roommate who had mutual acquaintances that provided pain pills. In addition, Ms Martin engaged in sexual activity with the roommate in exchange for opioids. As time progressed, the relationship became physically abusive; she left after her roommate tried to hit her with a vacuum cleaner when she “didn’t do a good job cleaning the trailer.” At the time, she had been in treatment for 1 year, was started in medication-assisted therapy (MAT), and had been prescribed buprenorphine. She moved into an apartment with her mother, which greatly reduced access to opioids. She responded very well to MAT, with an absence of significant relapses as evidenced by the drug screenings during her monthly visits.

Three years into treatment, Ms Martin met a new boyfriend. Her urine drug screen (UDS) resulted positive for amphetamine. He provided her with substances that boosted her energy and aided in weight loss. She was not fully aware of what she was taking, but she thought it might have been amphetamine since it came in a “large jar with many capsules.” Testing verified the presence of methamphetamine.

These results were shared with Ms Martin, to her genuine surprise, and she expressed earnest motivation to stop methamphetamine use. Unfortunately, over the next year, she eventually met criteria for stimulant (methamphetamine) use disorder. This paralleled toxic developments in her relationship. She described a continued strong sexual attachment to her partner, and she remained intimate with him despite knowledge that he was simultaneously sexually active with her mother. She later bashfully admitted engaging in group intercourse with her partner and mother. During intercourse she described her partner’s derogatory and sadistic tendencies, which she felt she “deserved.”

Eventually, she developed disgust toward him. This resulted in an internal conflict because while she described feeling revolted by him, she simultaneously experienced severe loneliness and feelings of abandonment when he did not give her attention. This fueled further methamphetamine use as she wanted to be “skinny and pretty.”

The ongoing sexual relationship between her partner and mother resulted in significant tension within the apartment they all shared. On multiple occasions, Ms Martin described anxiety that her partner and mother were colluding against her. Methamphetamine use may have intensified these feelings. Although at times she expressed a desire to leave, she felt she had nowhere to go. Her partner contributed to paying bills, which further complicated her situation.

For the next year, Ms Martin continued to express significant ambivalence about her relationship. She recognized how the situation placed a strain on her relationship with her mother, yet she simultaneously feared the rejection, abandonment, and loneliness that would result from a breakup. She described symptoms of anxiety and sadness when away from her partner, and he was using methamphetamine pills as a tool to control her. She compared her “love-hate” relationship with her significant other with that of her relationship with the methamphetamine pills.

In addition to work in building Ms Martin’s feelings of self-worth and autonomy, a motivational interviewing style was utilized to help her resolve some of her ambivalence toward the relationship. Although she voiced much more change talk to end the relationship, compared to sustain talk, she had difficulty committing to ending the relationship.

Due to the alarming rate of opioid overdoses secondary to fentanyl, clinicians and those struggling with substance use are becoming aware that the product purchased is not always as marketed. Anecdotal reports of increasing concomitant opioid and amphetamine use abound, but the condition is not well understood, nor systematically studied. In the case of this patient, confirmatory test showed methamphetamine, whereas she believed she was getting amphetamine or methylphenidate; she may have inadvertently gained access to a supply of methamphetamine.

Currently, there are no US Food and Drug Administration-approved treatments for methamphetamine use disorder. Some studies suggest the use of bupropion, naltrexone, and mirtazapine may have some limited efficacy in 

 In addition to treating Ms Martin’s SUD, the team addressed co-occurring mood and anxiety symptoms (she had witnessed her brother injured in a car accident). Her initial regimen included duloxetine and aripiprazole for depression, anxiety, and mood stabilization. Bupropion was not tried due to her concern of its risk of exacerbating her anxiety, and she declined mirtazapine due to its risk of weight gain because she already struggled with her body image. After Ms Martin expressed concerns that aripiprazole may be contributing to her weight gain, she was switched to cariprazine with the perceived potential benefit of weight-neutrality, since a desire for weight loss was a contributing factor to continued methamphetamine use. Another potential benefit of cariprazine includes preliminary interest in the D3 receptor affecting addictive behaviors.

Methylphenidate and lisdexamfetamine were other pharmacological therapies considered for treatment, given that Ms Martin has shown good response to replacement therapy such as buprenorphine. However, agonist substitution, while an excellent harm reduction approach, still faces stigma and resistance in clinical practice, especially for stimulant use.

According to the Centers for Disease Control, 40.4% of adults using methamphetamine within the last year also misused prescription opioids, and 16.9% used heroin between 2015 and 2018. In the United States there has been an increase in overdose deaths and hospital admissions involving 

 After limited availability of ephedrine and pseudoephedrine due to regulations, synthesis returned partially back to using phenyl-2-propanone (P2P).

 Due to increased purity and potency, there is concern that the P2P formulation may be contributing to addiction.

 This is something to keep in mind when treating a patient diagnosed with both opioid and stimulant use disorders. Unfortunately, there is no guideline as to whether MAT should be discontinued if a co-occurring substance use is still ongoing.

Ms Martin maintained abstinence from opioids while on MAT, but continued to use methamphetamine pills. The treatment team wondered if she was truly benefiting from the current level of care, and considered tapering off buprenorphine and referring her to a residential treatment program or a methadone clinic. However, Ms Martin did not have the financial resources for the latter and, in regards to the former, expressed anxiety and fear about being separated from her dog as well as the feeling of “being locked up.” Thus, her treatment team sought to maximize psychosocial support and psychotherapy interventions, but she had stopped going to group therapy and declined virtual therapy sessions.

With continued work, despite ongoing significant trauma, interpersonal conflict, financial instability, and continued methamphetamine use, Ms Martin increased engagement in treatment and is adherent with all medication management visits. The treatment team ultimately decided not to taper off the buprenorphine, given her gradual progress toward treatment goals was a product of a harm-reduction approach. She could have benefited from inpatient rehabilitation. However, reluctance to go into rehabilitation is common in patients with SUD. Additionally, most states do not allow involuntary inpatient SUD treatment as they do for involuntary psychiatric care, so patients have to suffer legal repercussion to be forced to attend court-ordered rehabilitation. Finally, many residential treatment programs may not be able to accommodate patients on MAT, as some are not yet comfortable with a harm-reduction approach or medical model of addictions treatment.

This case highlights several clinical and psychotherapeutic challenges that may arise in the treatment of substance use disorders. First, it is important to look for the presence of significant trauma in a patient with several barriers to care preventing access to psychotherapy, as there is a known link between a history of trauma and the development of 

 In this case, Ms Martin was a victim of physical, emotional, and sexual abuse. Unfortunately, there are limited standardized or manualized approaches to addressing trauma in patients with substance use disorders. When trauma informed therapy is available, access is often limited.

Similarly, another significant factor contributing to Ms Martin’s ambivalence about leaving the relationship was the codependency that existed with her partner.

Medication management visits typical to community psychiatry practice are likely not of sufficient length to address complex issues involving psychopharmacology and psychotherapy. Although the COVID-19 pandemic has accelerated the development of telepsychiatry, many patients do not have the technological means to make these visits and may not have private and safe living spaces where they can share sensitive information.

Additionally, drug use is perpetuated by perceived benefits, and cessation of use does not happen unless the patient appreciates the negative impact of substance use on their lives. When Ms Martin finally understood she was taking methamphetamine, it created an opportunity to see its use as a problem instead of an agent for cognitive enhancement/weight loss.

Methamphetamine is commonly used to improve sexual function. In fact, 

 has described methamphetamine as increasing sexual desire, pleasure, reducing the refractory period between intercourse, exacerbating impulsiveness, and impacting behavioral inhibition.

 In this case, it would be worth further exploring that idea, as the patient’s partner was supplying methamphetamine and requesting particular sexual demands.

A major challenge in the field continues to be the lack of available effective pharmacologic treatments for stimulant use disorders. Contingency management in combination with community reinforcement is a proven effective behavioral treatment for stimulant use disorders, as confirmed by 

 However, there are considerable barriers to implementing contingency management at this time, including public stigma and limited Medicaid support.

Lastly, in the context of treatment, it is often easy to feel patients are to blame for maladaptive, promiscuous, or risky behaviors. Countertransference feelings or bias may hinder patients getting expanded treatment options, especially if they display anger and hostility upon exploration of sensitive topics in session.

However, despite significant barriers to care, the presence of trauma, and ongoing struggles with stimulant use, patients demonstrate resilience and often continue to express desire for full recovery. Cognitive-behavioral therapy, relapse prevention, mindfulness, and psychodynamic therapies are all useful in treatment, but the level of complexity of patients with SUD often means a prolonged course of treatment with multiple modalities needed.

is a PGY-4 general psychiatry resident in the Menninger Department of Psychiatry & Behavioral Sciences at Baylor College of Medicine. He plans to pursue a fellowship in Addiction Psychiatry after graduation.

is an associate professor and addiction-boarded faculty at Harris Health System in the Menninger Department of Psychiatry and Behavioral Sciences at Baylor College of Medicine. 

 is associate professor, Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, and Ben Taub Adult Outpatient Services director, medical director, Stabilization, Treatment & Rehabilitation (STAR) Program for Psychosis. She also serves on

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6. Dolatshahi B, Farhoudian A, Falahatdoost M, et al. A qualitative study of the relationship between methamphetamine abuse and sexual dysfunction in male substance abusers. 

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10. McMahan VM, Kingston S, Newman A, et al. Interest in reducing methamphetamine and opioid use among syringe services program participants in Washington State. 

Articles

A patient presents with multiple substance use disorders super-imposed on mood and anxiety disorders. Where does a clinician even begin?

I Had to Use

This is a love letter. It is an ode to clinical psychiatry from one psychiatrist to another, to all those who are seeing patients in hospitals, whether they are on consult teams, in emergency departments, in solo offices, or on little screens scattered around the country. All of us psychiatrists, mental health clinicians, and therapists are listening to stories, absorbing emotions, and offering patients and families reassurance and positive action. Together, we are promoting healing and recovery.

Why would someone write a love letter to their specialty? Because after 2 decades of practicing medicine, I still find the intricacies of the human mind fascinating; I have the utmost respect for my field, which beautifully combines art and science. The scientific advances in psychiatry are fast-paced and intricate, and revolutions in conceptualizing mental illnesses are afoot. Yet, none of these advances or treatments can be meaningfully implemented without a thorough history-taking, an understanding of the patient’s environment and family dynamics, and an assessment of their insight into symptoms and their willingness to engage in treatment. Most importantly, none can be implemented without the trust and connectedness that occur in a healthy patient-physician relationship.

Roberto D. Sanchez, DO; Benjamin Li, MD; Nidal Moukaddam, MD, PhD

The art of psychiatry goes back to the patient-physician relationship, the basic building block of medicine, as it has been for millennia. That relationship has evolved, of course, reflecting changes in our understanding of disease, wellness, and the roles of patients and physicians. Over the centuries, the physician has been transformed from a healer with quasi-magical powers to a partner in wellness and recovery. This evolution has been obvious through history, but only recently has scientific attention turned to what, exactly, physicians are doing that is so impactful.

 coined the concept of the doctor as drug. He highlighted the importance of therapeutic interaction, calling it vital to treatment while acknowledging that the dose of this treatment—the required number of visits and the duration of visits—was not clear. Later literature developed new terminology. Mainstream medicine labeled it the “patient-physician relationship,” whereas the psychiatric field would call it nonspecific factors. Regardless of terminology, it is the 

 that takes place in the intimacy of a real conversation between human beings.

 (such as healthy eating, substance use, and physical activity).

 Whether or not patients modify these behaviors depends to a great extent on the level of trust they give to their 

 Qualities such as availability, benevolence, compassion, competence, honesty, integrity, knowledge, reliability, respectfulness, sincerity, and understanding are cited as essential in fostering and maintaining a healthy patient-physician relationship.

The realities of modern health care, however, are not matched to this paradigm of relationship growth, nor do they protect it. In recent decades, the foundations of clinical medicine/psychiatry have been under attack from the health care system itself. Visit lengths have 

 as has the number of psychiatrists providing therapy.

 So the question must be raised: In a visit of 10 to 15 minutes, how much of a therapeutic alliance can actually be built? I fear our self-conception is changing, too. Words like provider, prescriber, and mental health specialist do not capture the centrality of the patient-physician relationship. We are at risk of losing the sense that, in the words of Hugh Crichton-Miller, MD, “The patient [is] not simply an object but a person, needing enlightenment and reassurance.”

The health care system has been attempting to standardize aspects of the patient-physician relationship that could promote success. Bias and countertransference are 2 aspects that have been 

 and it is recognized that concordance in the patient-physician relationship is a desirable asset for successful treatment alliances.

 Achieving that concordance in short, sparse clinical visits may not be achievable, but the operationalization of these concepts nevertheless leads to a better understanding of nonspecific factors in the patient-physician relationship.

When physicians and patients are unable to build strong relationships, patients fare worse. In the treatment of depression, the number of meetings with the therapist or physician, regardless of the therapeutic modality, affects outcomes, even when patients are being treated with 

 The working alliance becomes even more important when addressing difficult issues of trauma and addiction.

 Recent advances inform us that nonspecific factors in treatment can be conceptualized in 2 areas: expectancy and alliance. These can be further subdivided into trait-like and state-like dimensions, each with their own neurobiological underpinnings.

 Trait-like components refer to attachment and personality styles, and they influence the relationship between the patient and the individual treating them in a nonspecific manner.

 When used optimally and at the right time, state-like dimensions can be used as active ingredients for change in therapy. Technological advances allow us to study the therapeutic alliance as it evolves session by session, taking into account within-person fluctuations and stable between-person differences.

The therapeutic alliance is also crucial to overcoming mental health stigma. Individuals sometimes resent psychiatric labels, and some patients may be harassed for using mental health care. To bridge that gap, we resort to the art of psychiatry, the alliance in the patient-physician relationship that helps patients see their treatment as a means to achieve life goals and recovery.

The patient-physician relationship is what the upcoming 

 series, "Tales From The Clinic: The Art of Psychiatry," is all about. The cases discussed are fictional, but they represent common presentations. Moving from the case, the human story, we transition to the evidence-based application of psychiatric research, highlighting the complex interplay of art and science. As readers will note, some of the cases span years of treatment. Many patients will say that they never thought their improvements were possible, and that treatment has given them a new life. But progress is not possible without both art and science—the art of human rapport, and the science that brings us effective, precise treatments.

So, to all my fellow psychiatrists and therapists, this is a love letter to our wonderful field, where the magic of medicine is still alive. Your comments on these cases are welcome. Please send them to 

is associate professor, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, and Ben Taub Adult Outpatient Services director, medical director, Stabilization, Treatment & Rehabilitation (STAR) Program for Psychosis. She also serves on the 

1. Balint M. The doctor, his patient, and the illness. 

2. Danaei G, Ding EL, Mozaffarian D, et al. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors. 

3. Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. 

4. Berry LL, Parish JT, Janakiraman R, et al. Patients’ commitment to their primary physician and why it matters. 

5. Grant SB. Are there blueprints for building a strong patient-physician relationship? 

6. Gottschalk A, Flocke SA. Time spent in face-to-face patient care and work outside the examination room. 

7. Olfson M, Marcus SC, Druss B, et al. National trends in the outpatient treatment of depression. 

The Doctor’s Personality: The Doctor’s Role in Society

9. Dehon E, Weiss N, Jones J, et al. A systematic review of the impact of physician implicit racial bias on clinical decision making. 

10. Dovidio JF, Penner LA, Albrecht TL, . Disparities and distrust: the implications of psychological processes for understanding racial disparities in health and health care. 

11. Hirsh AT, Hollingshead NA, Ashburn-Nardo L, Kroenke K. The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions. 

12. Johnson TJ, Winger DG, Hickey RW, et al. Comparison of physician implicit racial bias toward adults versus children. 

13. Schinkel S, Schouten BC, Street RL Jr, et al. Enhancing health communication outcomes among ethnic minority patients: the effects of the match between participation preferences and perceptions and doctor-patient concordance. 

14. Street RL Jr, Gordon H, Haidet P. Physicians’ communication and perceptions of patients: is it how they look, how they talk, or is it just the doctor?

15. Falkenström F, Josefsson A, Berggren T, Holmqvist R. How much therapy is enough? comparing dose-effect and good-enough models in two different settings. 

16. Wang LP, Maxwell SE. On disaggregating between-person and within-person effects with longitudinal data using multilevel models. 

17. Zilcha-Mano S, Roose SP, Brown PJ, Rutherford BR. Not just nonspecific factors: the roles of alliance and expectancy in treatment, and their neurobiological underpinnings. 

18. Falkenström F, Solomonov N, Rubel J. Using time-lagged panel data analysis to study mechanisms of change in psychotherapy research: methodological recommendations. 

What can be done to strengthen the therapeutic alliance?

Digital therapeutics (DTx) is a new category of medicine that refers to treatments delivered directly to patients via software or apps. The scope of DTx encompasses treatment, management, and prevention of a broad spectrum of diseases and disorders. As such, DTx are part of a larger ecosystem of digital health technologies that provides support for patients, clinicians, and medical institutions. These technologies include patient- and clinician-platforms, as well as the unseen operational components.

DTx differs from the multitude of mental health apps on the market because they are meant to be prescribed or recommended by a health care professional; part of a comprehensive treatment plan; evidence-based; and subject to the same regulatory requirements as traditional medical treatments. The development of DTx is an area that affects patients, clinicians, payors, and policymakers. The 

 has put forth a 10-point list of core principles for DTx products as a first step in operationalizing the industry; these principles also help to distinguish DTx products from unregulated apps.

In order to use DTx effectively, we must understand its relationship to the following categories: patients, clinicians, health care systems, and innovation/discovery, especially as it relates to comorbid disorders.

80% of adults in the US have a smartphone

, and many of them spend hours per day interacting with their devices.

 Although most of that time is likely for entertainment purposes, there are also opportunities to improve their health.

Recent advances in technology have led to the unobtrusive, seamless collection of patient-generated health data from smartphones, which can be used to improve patient care and outcomes. For example, smartphones can collect data on sleep, activity, physiology, and device use, as well as provide an environmental context. Digital phenotyping refers to the “moment-by-moment quantification of the individual-level human phenotype in situ, using data from smartphones and other personal devices,” and DTx takes it to the next level by 

recommending actions based on that phenotyping

The near ubiquity of these devices means that the clinical applications of digital phenotyping and DTx are highly scalable; their use also allows the individuals’ data to be used as their own unique baseline. Research has demonstrated the 

feasibility and acceptability of physiological data

 The hope is that digital markers of behavioral change (ie, observable changes in sleep, physical activity, and social interaction) might become 

sensitive measures of meaningful variation

 in functional status, symptoms, and risk for adverse outcomes in patients, thereby better guiding and personalizing care.

Acceptability of app use, and DTx in general, is an encouraging sign. Scalability will likely depend on age and generational influences (younger individuals may potentially be more amenable to DTx use), comfort with technology in general, and socioeconomic disparities (ie, more affluent individuals with better phones/wearables will be able to access more nuanced DTx options).

A yet unexplored problem is adherence to DTx use once prescribed; as large-scale implementation becomes a reality, this issue will need to be appropriately addressed. “App burnout,” a phenomenon referring to the short-term use of apps, may be relevant to DTx as the prescribed length of time (ie, weeks, months, years) increases. Current studies in mental health, for instance, have looked at DTx with contingency management and cognitive behavioral therapy for 12 to 16 weeks; medication active sensing systems meant to improve adherence, such as Abilify MyCite (aripiprazole tablets with sensor), have been helpful in short-term studies and have been evaluated for a maximum of 26 weeks per the United States Food and Drug Administration (FDA) approval. Thus, although the short-term implementation of DTx has been an attractive option for the management of chronic disorders, much is still unknown about the interaction of DTx with the naturalistic course of a chronic illness, and much remains unknown about the best times to implement DTX measures (

 Extracting Biobehavioral Markers From Sensors for the Development of DTX

DTx have been developed over the past 15 to 20 years to target chronic medical and mental issues, with the assumption that many of these conditions can be improved by shaping behaviors. However, physicians adopting DTx in chronic management face ethical, legal, and practical challenges. In the case of psychotic disorders, ingestible sensors (despite positive data in 

) are seen as potentially decompensating factors in a patient’s delusion, thus limiting adoptability.

 have faced adoptability challenges for depressive and psychotic disorders because of clinician concerns that they may worsen the primary disease.

, a maturity technology timeline that relates technology visibility to time. This concept explains the issues involved in DTx adoptability, including novelty of the new modality, expected value, expectation inflation of opinion related to innovation, and time needed for the technology itself to reach maturity.

Clinicians theoretically support the idea of closing treatment gaps and would likely be open to leveraging concrete treatment planning and adherence tools to reinforce what was discussed in-session. However, despite FDA approval of DTx apps (such as Welldoc’s BlueStar for Type II diabetes management and Pear Therapeutics’ reSET for the treatment of substance use disorder), DTx is still globally an underprescribed and underused modality. In addition, the 

From a clinician perspective, there are a number of hurdles to overcome, including lack of familiarity with DTx, lack of time to introduce and administer DTx, and the lack of DTx integration with electronic health records. Similarly, there are obstacles in billing for DTx. Although they exist, very few physicians are employed in systems that offer digital formularies. Thus, adoption by physicians is an unsolved challenge for DTx implementation. In order to achieve DTx scalability, it is necessary to change the clinical visit microenvironment and make DTx a viable treatment decision.

Reimbursement and oversight are the 2 big areas of concern in health care systems, yet the 

 The first question that must be answered is who is responsible for regulating DTx. The second is, what is the relation of DTx to machine learning and whether changes in software or updated machine learning algorithms would require reapproval or new approvals. The 

 approach currently under consideration by the FDA could address some of these concerns.

Currently, approved or cleared products have received their acceptance from the FDA Center for Devices and Radiological Health, some using the Breakthrough Therapy designation. The aim, ideally, would be a path for software-as-a-medical-device (SaMD) products, with predetermined steps through the lifecycle of the software. This will require modernization of the FDA paths for medical devices, which were written in 1976.

System-level challenges of DTx also include cybersecurity. DTx interfaces with, and is reliant on, multiple nonmedical entities, including internet, phone, and cloud storage service providers. There are currently no global answers to these issues, but patients and clinicians alike will be reluctant to transmit sensitive health data over unsecured channels. Moreover, reimbursement for DTx is moving slowly but surely. Some private insurers pay for DTx as prescribed, but nationwide reimbursement codes remain uncommon.

Thus far, the main DTx developments have been the delivery of already proven treatments via electronic/software means. However, the future of DTx will likely include higher-order constructs and products that address comorbid disorders. Digital innovation in mental health already exists, and is accelerating rapidly, which is a good thing. Digital innovation serves 3 broad purposes.

First, digital innovation can increase access to mental health care. With the currently available technologies, there has been a continual improvement in the delivery of mental health services via telemedicine/telepsychiatry. Telepsychiatry has been important in facilitating patient follow-up by reducing travel, thereby helping longitudinal engagement. This, in turn, has improved adherence and reduces loneliness and misinformation.

 may not always be optimal for patient engagement and patient-physician rapport, studies have shown it is not inferior to face-to-face care.

 Feasibility and success in delivering therapeutic interventions, such as cognitive behavioral or supportive therapy, and sleep hygiene education via the internet/phone/apps have been demonstrated.

Second, digital innovations provide a new arsenal of tools to measure aspects of patient biology and behavior in ways that were not previously possible. This objective data collection, in turn, will likely allow better diagnosis and will allow clinicians to adjust care, as necessary.

Third, the fast-expanding repertoire of artificial intelligence tools enables the discovery of complex relationships between new forms of data and mental health conditions. As a result, novel ideas are emerging to quantify complex concepts like loneliness, mood swings, and cravings/binge eating that may underlie worsening mental health symptoms. Future DTx developments are expected to go beyond already proven treatments.

Mobile and Wearable Technologies in Mental Health

 reviewed mobile phone/wearable sensor–based mobile studies (N = 33) for mental health conditions between 2009 and 2018. The majority of the studies targeted unipolar depression or anxiety in healthy participants, with fewer studies focusing on bipolar and psychotic disorders. The Global Positioning System (GPS) was the most common sensor used. Features such as reduced mobility patterns and time spent at home during specific time intervals of the day were associated with scores indicative of depression or anxiety, as measured by questionnaires such as the Patient Health Questionnaire (PHQ)-9, Generalized Anxiety Disorder (GAD)-7, or by Ecological Momentary Assessment (EMA) self-reported mood.

, measured with an accelerometer/gyroscope; this was followed by phone call logs.

Higher-level clinically relevant constructs, such as behavioral regularity, may be useful to better understand behavior patterns. Data from 

 showed that 2 behavioral regularity indices

 were correlated with perceived stress scale scores, the mental component scale of the 12-Item Short Form Health Survey (SF-12), and daily self-reported mood.

 The indices included a sleep regularity index that quantified the regularity of sleep time, wake time, and sleep duration, and a daily mobility index that detailed routines based on GPS data. Using behavioral rhythm markers (eg, ultradian, circadian, and infradian rhythms) estimated from mobile phone sensors, these data predicted self-reported symptoms from individuals with schizophrenia (the machine learning algorithm is able to predict when patients will be reporting certain symptoms based on behavioral patterns collected as above).

 based on mobile phone sensors were used to predict symptom resurgence in patients with schizophrenia.

higher-level construct of social ambiance

 can likewise be obtained by unconstrained day-long recordings from wrist-worn audio-bands that estimate the number of simultaneous speakers.

 The number of simultaneous speakers was used as a proxy for an individual’s sociability, as social isolation is often a symptom of mental illness. By classifying audio into 4 levels (ie, quiet, low, mid, and high social ambiance), researchers found that individuals with depression or psychosis spent less time in diverse environments with higher social ambiance levels. Moreover, social ambiance patterns are associated with the severity of self-reported depression and anxiety symptoms, and personality traits such as neuroticism and agreeableness.

Despite strong preliminary evidence associating sensor data with mental health conditions, many challenges lie ahead in data-driven modeling and inference. This issue is a major challenge associated with the scalability of DTx development, as it requires industry and academic collaborations. For instance, computational models need to learn associations between individual patients’ biomarkers and mental health constructs (eg, symptoms, critical events). Every patient has different behavioral patterns and physiological responses, so the challenge becomes, how to determine regular/irregular patterns for each patient, or each group of patients.

A single computational model might not be able to fit the heterogeneity of different patients. Similarly, patients’ symptoms are based on their self-reports, which are subject to variabilities and biased perceptions. Current technology has a limited ability to detect biased self-reports, thereby limiting the usability of deep learning. Deep learning is a popular and powerful approach to developing complex neural network models; however, it is hard to interpret why certain models work well, and model-building requires a significant amount of data per patient.

Although the overlap between depressive disorders and diabetes is not well understood, it has been hypothesized to be potentially linked to immune system overactivity/systemic inflammation, psychoneuroendocrine dysregulation, cognitive functioning, and 

 This type of comorbidity could be effectively targeted with DTx if models are built to understand this disease overlap,

 especially as the field undergoes a paradigm shift.

One of the biggest conceptual ongoing shifts in psychiatry is characterizing mental illnesses dimensionally, in contrast to the current practice of categorical classification. Taking major depressive disorder (MDD) as an example, a shift in both diagnosis and management can be achieved by leveraging technology and by adopting a more modern, innovative approach to diagnosis. In the current diagnostic paradigm, MDD is defined in the DSM-5 as having 5 of 9 symptoms (with necessary inclusion of depressed mood and/or anhedonia). Thus, it is possible that 2 patients with the same MDD diagnosis have no overlapping symptoms: one has depressed mood, the other anhedonia; one eats too much, one eats too little; one sleeps too much, the other too little; one is suicidal, the other is not, etc.

The National Institute of Mental Health has established the Research Domain Criteria (RDoC) program, which recommends that mental health research be focused on symptoms instead of diagnoses, and studies should be done not categorically, but dimensionally, in a manner that allows overlap with tech-based objective information gathering. The RDoC highlights the following neurobiological transdiagnostic research dimensions: negative valence, positive valence, cognitive processes, systems for social processes, and arousal/regulatory systems. The current state of DTx is patient-centered/patient-driven information collection, but most DTx structures, thus far, do not fit categorical or dimensional psychiatric diagnostic frameworks; instead, they focus on individual symptoms and may be the simplest level of dimensional classification.

In the dimensional paradigm, a symptom like low energy can be translated into low physical activity/low mobility/low socialization by sensor detection. Those, in turn, can be addressed with a focused intervention, such as behavioral activation. This approach has measurable outcomes, is easy to explain to patients, and is more amenable to process improvement based on real-time feedback. The current approach to MDD treatment, which usually starts with the addition of a selective serotonin reuptake inhibitor (SSRI), aims to improve feelings of depression/anhedonia generating the low activity/low energy.

 provides some improvement in survival in the 

, but not the expected protective effect that is hoped for in diabetes and depression.

 Intuitively, this makes sense as a lifting mood may not fully translate into the desired energy increase, unless the patient specifically learns the needed skills to effect this change.

The field has turned to dimensions that may impact behavioral change, and those in turn will need to be measured and relayed back to the patient in a feedback loop. A good illustration of this is self-efficacy, or the belief that one has control over health behaviors. Self-efficacy tends to be diminished in patients with chronic illnesses, who may accept many symptoms as an inevitable part of the disease process, and lack the understanding/ability to take control of their biological processes. Poor self-efficacy may overlap with the social determinants of health and health care disparities but, in general, studies on self-efficacy and specific diabetes-related mitigating behaviors are promising.

 Taking care of oneself would help to improve mobility/energy and, by extension, mood. At this point, this stepped process lacks clarity and established protocols, but it could be an excellent DTx goal for further development.

Leveraging DTx to improve mental and physical health is likely to be the biggest, paradigm-shifting change that medicine has known since the invention of antibiotics. However, how to apply these tools remains an area that needs operationalization. DTx is at the nexus of digital innovation and scalability/wide-scale use of digital interventions, with more exciting developments on the horizon.

is associate professor, Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, and Ben Taub Adult Outpatient Services Director, Medical Director, Stabilization, Treatment & Rehabilitation (STAR) Program for Psychosis.

is an Assistant Professor at Rice University, Department of Electrical and Computer Engineering, Computer Science,

and Bioengineering. She also directs the Computational Wellbeing Group.

is an associate professor of Psychiatry Research at Baylor College of Medicine.

is chair of the Department of Electrical and Computer Engineering and the Earnest Dell Butcher professor of engineering at Rice University.

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Digital therapeutics may be the biggest paradigm-shifting change medicine has seen yet... 

Nidal Moukaddam, MD, PhD

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