Radically different
Background: As digital communication becomes central to daily life, psychotherapy increasingly has access to patients’ electronic media data. Although digital phenotyping has been widely studied, less is known about whether incorporating personal communication data, such as text messages, improves clinical outcomes in psychotherapy. Objective: This study aimed to determine whether integrating personalized text message data into psychotherapy improves depression, anxiety, health-related quality of life, and therapeutic alliance and to examine whether increased access to collateral information influences clinical decision-making. Methods: The Electronic Media and its Impact on Psychotherapy (EMAP) study was a randomized controlled trial conducted in adult and geriatric outpatient and partial hospitalization settings at an academic psychiatric hospital. Participants receiving psychotherapy for primary depression or anxiety (n=101) were randomized to electronic media–enhanced therapy (EME; n=52) or treatment as usual (TAU; n=49). In EME, research staff reviewed participants’ text messages prior to sessions using personalized mood-related key terms and presented aggregated findings on a Health Insurance Portability and Accountability Act (HIPAA)–compliant clinician dashboard. TAU participants received standard care without message review. Outcomes included change scores for the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the 36-item Short Form Health Survey (SF-36), and the Working Alliance Inventory–Short Revised (WAI-SR). Linear regression and nonparametric tests compared groups. Moderation analyses assessed whether the frequency of information access influenced treatment changes. Results: No statistically significant between-group differences were observed in anxiety or working alliance. Among participants with SF-36 follow-up data (n=65), EME participants demonstrated greater improvement in the pain subscale. Greater frequency of information access was associated with increased treatment-related changes in the EME group. Access to additional collateral information was associated with more clinical actions but not with improved distal outcomes. Conclusions: Integrating personalized text message data into short-term psychotherapy did not significantly improve depression or anxiety, and it neither improved nor worsened therapeutic alliance. However, access to greater amounts of collateral information, including electronic media, influenced clinical decision-making, suggesting nuanced and context-dependent effects. Trial Registration: ClinicalTrials.gov NCT03712267; https://clinicaltrials.gov/study/NCT03712267
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Background: Digital mental health interventions (DMHIs) are increasingly popular for their ability to disseminate evidence-based treatments in a scalable, accessible way. Engagement with digital treatments is critical for effectiveness but remains poorly defined and measured. Most studies rely on subjective self-reports or 1 or 2 objective metrics, overlooking the multidimensional nature of how users interact with DMHIs. Objective: This exploratory secondary analysis applied a road map for comprehensive behavioral engagement measurement, developed for a prior smartphone cognitive behavioral therapy program for body dysmorphic disorder, to a 12-week randomized controlled trial of smartphone cognitive behavioral therapy for obsessive compulsive disorder (OCD; N=60). Aims were to (1) comprehensively characterize behavioral engagement using 21 objective app analytics-based variables, (2) identify distinct behavioral engagement profiles via cluster analysis, (3) assess whether profiles were differentially associated with OCD symptom change, and (4) evaluate associations between profiles and pretreatment credibility, expectancy, posttreatment satisfaction, and perceived app quality. Methods: Behavioral engagement was measured via 21 objective variables derived from app analytics, spanning use volume, frequency, feature usage, session duration, and temporal patterns. Hierarchical agglomerative cluster analysis identified engagement profiles. Associations between cluster membership and OCD severity change (Yale-Brown Obsessive Compulsive Scale) were examined using hierarchical generalized linear mixed models. Objective measures were complemented with subjective self-reports: namely, cluster differences in treatment credibility, expectancy, satisfaction, and perceived app quality were examined using ANOVAs and Wilcoxon rank-sum tests. Results: Cluster analysis indicated a 3-cluster solution representing high (cluster 1: 21/60, 35%), moderate (cluster 2: 31/60, 52%), and low (cluster 3: 8/60, 13%) app users. All 3 clusters experienced significant reductions in OCD severity, with no significant differences in pre- to posttreatment Yale-Brown Obsessive Compulsive Scale change across clusters. Descriptively, cluster 1 had a higher rate of treatment responders than cluster 3. While clusters 1 and 2 had similar perceptions of treatment credibility and expectancy at baseline and satisfaction at posttreatment, cluster 3 perceived the intervention as significantly less credible, had lower expectations, and reported significantly lower satisfaction than cluster 2. All clusters rated app quality as similarly high. Conclusions: Comprehensive behavioral engagement measurement is feasible and informative across different DMHIs and clinical populations. The finding that all engagement profiles showed comparable symptom improvement challenges simple dose-response assumptions and may suggest that multiple paths of engagement can be therapeutically beneficial; nonsignificant differences in improvement across clusters may also reflect limited power to detect differences. Pretreatment credibility and expectancy are associated with engagement patterns, identifying a potential modifiable intervention target. Trial Registration: ClinicalTrials.gov NCT04136626; https://clinicaltrials.gov/study/NCT04136626
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Background: Health care professionals in safety-net settings often rely on lengthy and inconsistently maintained community health resource lists when connecting patients with services. Bridgedd is a health care staff–facing web application designed to generate geographically and categorically filtered community resources in a unique format that makes information about each resource more accessible. Objective: This formative pilot study aimed to characterize the perceptions of behavioral health professionals toward Bridgedd’s usability, comparative value relative to existing community resource filtering and communication tools, and their intent to use it with patients if made available. Methods: We conducted a single-site, cross-sectional formative pilot of the web-based tool we developed, Bridgedd, within Grady Health System’s Integrated Behavioral Health Program between April 23 and May 14, 2026. All 21 program team members attending an all-staff meeting received a presentation about Bridgedd and were given the opportunity to try the tool and ask questions. Then, they independently evaluated it using a self-generated hypothetical patient scenario. Eleven completed an investigator-developed anonymous feedback survey assessing perceived ease of use, comparative value relative to existing tools, intent to use the tool with patients, and open-ended feedback. Quantitative responses were summarized using raw counts, and open-ended responses were summarized as descriptive observations. A post hoc descriptive analysis excluded 2 potentially direction-confused response patterns. The post hoc descriptive analysis did not materially change the overall interpretation. Results: Eleven behavioral health professionals (therapists, n=4; licensed professional counselors, n=3; social workers, n=2; mental health counselor, n=1; certified peer specialist–mental health, n=1) completed the survey. Of the 11 respondents, 9 rated the tool as very easy to use, none reported technical problems, 8 agreed or strongly agreed that Bridgedd was better than the tools they currently use to help patients navigate community health resources, and 8 reported an intent to use the tool with patients if it were made available. In the open-ended responses, 7 of the 11 respondents suggested that nothing was missing or offered no additional suggestions for improvement, while the remaining 4 open-ended responses centered on expanding mental or behavioral health resources, providing additional county coverage, including more resources within each category, and building a mechanism for updating resource information. Conclusions: In this small, single-setting formative pilot study using hypothetical patient scenarios, participating behavioral health professionals generally reported favorable perceptions of Bridgedd’s usability and potential utility. Further evaluation during routine clinical care is needed to assess actual use, workflow effects, patient experience, referral completion, and patient-level outcomes.
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Background: Design research on AI technologies for mental health has expanded rapidly, yet existing work has largely focused on practitioners’ perspectives within isolated therapeutic stages or specific services. As a result, there is limited understanding of how practitioners view the role of AI across the full therapeutic journey, including assessment, diagnosis, and treatment, or how these perspectives can be translated into actionable and ethically grounded design guidance. This lack of stage-specific guidance introduces several risks: (1) the development of AI tools that practitioners may not trust or adopt, (2) heightened ethical concerns, particularly in diagnosis where bias and erosion of human judgment are most likely, and (3) missed opportunities to leverage AI to support ongoing assessment and treatment adaptation. Objective: This study aimed to explore mental health practitioners’ perspectives on how AI may support or hinder therapeutic practice across all 3 therapeutic stages, with particular attention to their ethical considerations. Methods: We conducted semistructured interviews with 18 mental health practitioners to explore how AI may support or hinder therapeutic practice across assessment, diagnosis, and treatment. Data were analyzed thematically, and ethical challenges were organized using 4 biomedical principles. This study received approval from the Lancaster University Institutional Ethics Committee (ID 3530). Results: Findings suggest a stage-specific pattern: practitioners identified valuable roles for AI in supporting clinical assessment and treatment, while expressing strong resistance to autonomous AI diagnosis, which was regarded as the most ethically sensitive stage. Across contexts, AI was seen as supporting and validating, rather than replacing, clinical judgment. Ethical concerns were organized using these principles, with key issues including data validity, inclusivity, privacy, transparency, and explainability. Grounded in these findings, four design directions are proposed: (1) AI-enabled clinical assessment hubs for analyzing multimodal patient data to support transparent decision-making; (2) natural language processing-based tools to enable richer understanding of patients’ lived experiences; (3) new models of trust to support ethically sensitive AI-assisted diagnostic decision-making; and (4) large language model–powered personalized and adaptive mental health support systems that maintain human-AI partnership and preserve practitioners’ central role in care. Conclusions: This study provides a stage-specific understanding of practitioners’ perspectives on AI use across assessment, diagnosis, and treatment and systematically frames ethical challenges using biomedical principles. The findings translate practitioner insights into actionable design guidance for ethically informed AI-supported mental health practice.
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Guanfacine is a non-stimulant medication that is FDA-approved to treat ADHD in children and teens. It can also be used off label to treat tic disorders and symptoms of autism.
Guanfacine is not as powerful in reducing ADHD symptoms as stimulant medications, but it’s especially helpful for children who are hyperactive and impulsive — who can’t sit still in class, blurt out answers, interrupt, melt down easily, or have trouble shifting gears.
“I always describe guanfacine as a behavioral medication,” says Paul Mitrani, MD, PhD, a child and adolescent psychiatrist at the Child Mind Institute. It can help kids who struggle to regulate their impulses and emotions take time to pause before acting.
Guanfacine is a kind of medication called an alpha-2A adrenergic receptor agonist. Alpha-2 agonists — including guanfacine and clonidine, among others — were originally developed to treat adults with hypertension, or high blood pressure. But guanfacine may be best known as a treatment for ADHD.
Guanfacine (under the brand name Intuniv) was officially approved to treat ADHD in children in 2009 but has been used for this purpose since the 1990s.
The alpha-2A receptors that guanfacine targets are found in various regions of the brain and nervous system, but heavily concentrated in the prefrontal cortex, the part of the brain that helps regulate attention, emotion, impulsivity, and behavior.
Researchers don’t fully understand how guanfacine works, but it is thought to act by enhancing the functioning capabilities of those alpha-2A- receptors in the prefrontal cortex, improving a person’s ability to focus “above the noise” of the environment.
Guanfacine also has a calming effect by acting on alpha-2A receptors in the sympathetic nervous system, reducing sympathetic nerve impulses. This calming effect is especially helpful for hyperactivity and impulsivity. (The sympathetic nervous system also regulates blood pressure, thus the drug’s original use.)
Guanfacine can be used to treat ADHD on its own, but it is commonly used in addition to a stimulant.
The first-line medication treatment for ADHD, for both children and adults, is a stimulant medication like methylphenidate (Ritalin) or amphetamine (Adderall). Guanfacine, however, is a non-stimulant drug — it can target the same symptoms, it just goes about it in a different way.
Still, Dr. Mitrani adds: “We don’t typically start with guanfacine as a medication for ADHD unless the behaviors are more of the problem or there’s concern about starting a stimulant.”
For example, guanfacine may be beneficial for a child who does well academically but has trouble settling down and following rules in class. “I see kids who are really bright, so they don’t have to pay full attention to do well in school but can still struggle with behaviors that are causing a problem,” says Dr. Mitrani. For other kids, “they may benefit from a stimulant for their attention and behaviors, but parents are concerned that a stimulant may result in them not eating, which can impact growth. That’s where I may start with guanfacine.”
For some children, adding guanfacine can also address issues associated with stimulant medications, including sleep problems and the “crash” in mood and behavior that some kids experience at the end of the day, when they’re coming off a stimulant. Guanfacine may make kids drowsy, so it’s usually taken at night, says Dr. Mitrani. That means it can offset side effects of a stimulant by helping kids get tired when it’s time for bed. But some kids take guanfacine in the morning without feeling sleepy during the day, he adds.
Sleepiness: A common side effect of guanfacine is sleepiness or fatigue. But if a child is really tired after taking guanfacine, says Dr. Mitrani, it’s probably not a great fit. “Tiredness is the one side effect we are most concerned with because if it makes you tired, it’s not a good medicine for you.”
If a child is taking guanfacine in addition to a stimulant, consider their whole medication schedule when discussing any concerns with their pediatrician. “For example,” says Dr. Mitrani, “if they don’t take their stimulant on the weekend, but they stay on the guanfacine, they may feel more tired on the weekends than they do during the week because the stimulant is helping balance things out.”
Low blood pressure: Guanfacine can also lower blood pressure, which can cause dizziness. “Most kids tolerate any small drop in blood pressure fine because their hearts are young and healthy and they compensate with an increased heart rate,” Dr. Mitrani says. But other possible side effects related to lower blood pressure (hypotension) include constipation, dry mouth, or headaches.
There are two kinds of guanfacine: immediate-release (IR), which lasts for several hours, and extended-release (ER), which lasts all day.
Immediate-release (IR) guanfacine: Guanfacine IR (previously known by the brand name Tenex) is used off label to treat ADHD and other disorders. Guanfacine IR is absorbed faster, peaks earlier, and lasts for less time than the extended-release version. Children typically take more than one dose per day.
Guanfacine ER (Intuniv): Guanfacine ER is FDA-approved to treat ADHD in children ages 6 through 17, either alone or in addition to stimulants. Guanfacine ER is available in a range of doses, typically starting at 1mg, and is taken once per day.
Notes on dosing: The recommended pediatric dose of guanfacine ER is 1–4mg daily for children 6 to 12. Children 13 to 17 are FDA-approved to receive a dose up to 7mg. But some young children tolerate and benefit from doses above 4mg, says Dr. Mitrani. Still, any amount of the drug should be handled with caution. If a decision is made for a child to stop taking guanfacine, the dose should be tapered off over a period of time, usually several weeks. Stopping the medication abruptly, particularly at a higher dose, can cause a spike in blood pressure, Dr. Mitrani explains.
Short- and long-acting forms of guanfacine are not interchangeable in terms of dosing. For example, if your child is taking guanfacine ER 2mg, that doesn’t mean it would be appropriate for them to make a direct switch to guanfacine IR 2mg — these medicines are not equivalent because of the way they are absorbed. If a child switches medications, their dose must be adjusted.
Guanfacine isn’t the only drug of its class that can be used to help with ADHD symptoms like hyperactivity or impulsivity. Another commonly used alpha-2 agonist is called clonidine (Catapres, Kapvay). Clonidine, FDA-approved to treat ADHD in children 6 to 17, essentially works the same way as guanfacine but tends to be a little more potent. As a result, side effects like sleepiness can be more pronounced, so it’s usually not the first choice, says Dr. Mitrani.
On the positive side, newer versions of clonidine (Onyda XR) are available in liquid form, which makes it possible to control the dose to a finer degree. “With guanfacine, in its long-acting form, you’re working with 1 milligram, 2 milligrams, 3 milligrams, etcetera,” Dr. Mitrani explains. “With the liquid clonidine, you could do 0.15 milligrams or 0.25 milligrams. So, you can optimize the dose, and hopefully, reduce any negative side effects.”
Liquid clonidine, which, like guanfacine ER, lasts 24 hours, is also a good option for kids with sensory issues or an aversion to swallowing pills. Guanfacine ER tablets cannot be crushed or broken because then the medication may be released too quickly. Children must swallow time-release tablets whole.
Guanfacine has been shown to be effective in treating some children with tic disorders. Researchers aren’t entirely sure why guanfacine can reduce tic severity, and their thinking has shifted in recent years. They theorize that the drug’s effects on the prefrontal cortex may help regulate attention and suppress tics.
Some studies show that the short-acting version of guanfacine, which kids typically take two to three times a day, can help manage tics better, says Dr. Mitrani. “Tics wax and wane; they come and go,” he explains. “They can be triggered by being excited, being tired, or being stressed.” Immediate-release guanfacine may be better-suited to address these fluctuations.
Kids with tic disorders often have other disorders, including ADHD. Studies show that guanfacine is more effective for kids with tics and ADHD than kids with tic disorders alone.
Guanfacine can also be prescribed off label to help treat autism. It may be effective in these cases because it helps regulate symptoms that are similar to or associated with ADHD, such as hyperactivity, impulsivity, and distractibility. (Researchers estimate that about one-third of children with autism also have ADHD.) Guanfacine is also sometimes used to address irritability, oppositional behavior, or problematic repetitive behaviors.
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