One of the main problems in using digital mental health tools in the United States is the lack of digital health literacy. Digital health literacy means how well both providers and patients can find, understand, and use basic health information with digital tools to make good health decisions. Tools like the eHealth Literacy Scale (eHEALS) measure this ability and show how important it is for managing mental health and using digital platforms correctly.
Many allied health professionals, such as nurses, therapists, social workers, and counselors, have different levels of comfort and skill with new digital technologies. Even though many know the benefits, some lack the technical skills needed to make these tools part of their daily work. Some have little experience with new health computer systems or AI digital tools, which lowers their confidence and ability to use them well.
Patients, especially those in outpatient or community clinics, often have bigger problems with digital literacy. People with long-term mental health issues may also face challenges because of their age, income, education, or language skills. This makes it harder for them to use telehealth or app-based cognitive behavioral therapy. Without proper training or help, both clinicians and patients may not use digital mental health services enough, which can lead to worse treatment results.
Using digital mental health programs is more than just giving patients technology. A key problem is keeping patients involved for a long time. Internet-based cognitive behavioral therapies (iCBTs) have shown good results in treating anxiety and depression, especially when a therapist helps. Studies in the Journal of Medical Internet Research (JMIR) show that therapist-guided iCBTs have fewer patients quitting than self-guided ones.
Allied health professionals with many patients find it hard to balance time between helping each person and managing technology. If therapist support goes down, patients are more likely to stop using the program. This shows that digital tools save money and give more access but still need some human support to work well.
It is also hard to keep patients interested because mental health problems often need ongoing support and motivation. Short, targeted digital activities called microinterventions have been suggested to keep patients involved. These give easy steps for behavior change. Still, it is tough to add these activities regularly and make smooth programs in real practice.
Practice administrators and IT managers must train health workers on ways to boost patient involvement. They should also make patient interfaces easy to use. Technical ease, reminder systems, and feedback are all important for patients to follow their care plans. Without these, clinics may not get good results from investing in digital mental health tools.
The United States has many rules about health technologies, and digital mental health tools bring added legal and ethical questions for allied health workers and clinic managers. Following laws like the Health Insurance Portability and Accountability Act (HIPAA) is required to protect patient privacy and keep data safe. Still, digital tools can cause new risks like data theft and unauthorized access. Clinics must check if technology vendors meet security rules.
Besides privacy, AI mental health tools raise ethical questions. The Journal of Medical Internet Research talks about the “right to explanation” for AI health decisions. Patients and providers want to know how AI makes choices or suggests treatments. Allied health professionals must explain and justify care decisions supported by AI, even if the AI works quietly behind the scenes.
Another legal issue is accountability when AI plays a role in decisions. If an AI gives advice that causes harm, it is unclear who is responsible—the software maker, the clinician, or the clinic. These doubts make some hesitate to fully use AI in patient care.
Other problems include billing and payment systems. Telehealth grew a lot during the COVID-19 pandemic, but payment rules for digital mental health services are still not steady across states and insurers. Allied health workers often spend a lot of time checking if their digital services will be paid for, which slows down use.
Allied health professionals need ongoing education about the ethical use of new technologies to meet state rules and professional standards. Clinic leaders and IT managers should support this with training programs to handle these complex rules.
Using artificial intelligence (AI) and workflow automation in mental health care can help with some problems, but they also bring new ones for allied health professionals and managers. AI tools that handle phone calls and patient communication, like those made by companies such as Simbo AI, are changing how clinics work in the United States.
These AI systems help schedule appointments, answer patient questions, send reminders, and manage calls without needing human workers all the time. This helps reduce the work for allied health professionals so they can focus more on clinical care. Automated systems adjust to patient needs, handle many calls, and are available 24/7, which helps mental health patients who might need help outside normal hours.
AI can also help screen patients by spotting risk signs or symptoms from phone conversations using natural language processing. When combined with clinical exams, this can help clinics find patients who need urgent care faster. Automation also speeds up referrals, paperwork, and follow-ups, making busy outpatient clinics more efficient.
However, using AI and automation means providers have to learn to trust and work well with these technologies, which links back to the need for digital skills. Being clear about how AI works is important to keep patient trust, especially since some systems handle sensitive mental health details.
Many clinics still use old software that does not work well with new AI tools. This makes it harder to add AI to electronic health records or clinic management systems. IT managers are important for choosing tools that fit clinic technology, keep data safe, follow laws, and cause little trouble for workflows.
When done right, AI and automation can help reduce the pressure on staff, letting allied health professionals spend more time caring for patients and improve access to mental health services across the country.
JMIR is a leading, peer-reviewed open access journal focusing on digital medicine and health care technologies. It ranks highly in Medical Informatics and Health Care Sciences, making it a significant source for research on emerging digital health innovations, including public mental health interventions.
JMIR provides open access to research that includes applied science on digital health tools, which allied health professionals can use for patient education, prevention, and clinical care, thus enhancing access to current evidence-based mental health interventions.
The journal covers Internet-based cognitive behavioral therapies (iCBTs), including therapist-assisted and self-guided formats, highlighting their cost-effectiveness and use in treating various mental health disorders with attention to engagement and adherence.
Therapist-assisted iCBTs have lower dropout rates compared to self-guided ones, indicating that therapist involvement supports engagement and adherence, which is crucial for effective public mental health intervention delivery.
Long-term engagement remains challenging, with research suggesting microinterventions as a way to provide flexible, short, and meaningful behavior changes. However, integrating multiple microinterventions into coherent narratives over time needs further exploration.
Digital health literacy is essential for patients and providers to effectively utilize online resources. Tools like the eHealth Literacy Scale (eHEALS) help assess these skills to tailor interventions and ensure access and understanding.
Biofeedback systems show promise in improving psychological well-being and mental health among workers, although current evidence often comes from controlled settings, limiting generalizability for workplace public mental health initiatives.
AI integration offers potential improvements in decision-making and patient care but raises concerns about transparency, accountability, and the right to explanation, affecting ethical delivery of digital mental health services.
Barriers include maintaining patient engagement, ensuring adequate therapist involvement, digital literacy limitations, and navigating complex legal and ethical frameworks around new technologies like AI.
JMIR encourages open science, patient participation as peer reviewers, and publication of protocols before data collection, supporting collaborative and transparent research that can inform more accessible mental health interventions for allied health professionals.
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