According to Forbes, the American Psychiatric Association (APA) has a formal, five-level evaluation framework for mental health apps, last detailed in a 2021 research paper published before ChatGPT’s 2022 debut. The model, designed to guide clinicians and patients, assesses apps on accessibility, privacy, clinical foundation, engagement, and therapeutic goals. The article’s contributor, who has written over 100 columns on AI and mental health, argues this existing framework does not robustly account for AI capabilities, a critical gap given that consulting generative AI on mental health is now a top use case. This is especially pressing as millions, including ChatGPT’s 800 million weekly active users, turn to AI for mental health advice, despite significant risks like the potential for AI to foster delusions or give harmful guidance, as highlighted in a recent lawsuit against OpenAI.
The AI Mental Health Wild West
Here’s the thing: we’re in a totally unregulated boom. People are already using these tools en masse because they’re cheap, available 24/7, and don’t carry the stigma or scheduling hassles of traditional therapy. But that’s the problem. It’s the ultimate case of the cart being miles ahead of the horse. The APA’s framework was built for a world of dedicated, purpose-built apps—some good, some bad—but not for a world where a general-purpose chatbot that can also write your resume might suddenly become your de facto therapist.
And the app landscape itself has become a confusing mess. The article breaks it down into six categories, from legacy non-AI apps to shoddy AI bolt-ons and new apps built from the ground up with AI. How do you even begin to compare them? A traditional evaluation might give high marks to an app’s privacy policy and clinical foundations, but completely miss that its new AI chatbot add-on is a poorly integrated, unvetted API that could go off the rails. The framework isn’t equipped to ask the right questions.
What’s Missing From The Framework
So what should an “AI-augmented” evaluation model include? The Forbes piece doesn’t spell out a precise new level, but the implications are clear. It needs to probe the AI’s specific training data and safeguards. What guardrails are in place to prevent dangerous advice? How does the AI handle crisis situations—does it even recognize them? There’s a huge difference between an AI trained on curated, peer-reviewed therapeutic techniques and one that’s essentially a web-scraper with a friendly interface.
It also needs to assess transparency. Is the AI a “black box,” or can clinicians understand why it suggests certain responses? And critically, it must evaluate integration. Is the AI a seamless part of a therapeutic journey, or just a gimmicky feature tacked on for marketing? A bad AI integration isn’t just useless; it could actively undermine the other good qualities of an app. The current model’s steps on “Clinical Foundation” and “Usability” just don’t cut it for this new layer of complexity.
A Critical Need For Clinicians And Patients
Look, updating this framework isn’t an academic exercise. It’s a practical necessity for clinicians being asked by patients about these tools. They need a trusted, structured way to separate the wheat from the chaff in an overwhelming market. And patients need protection. The lawsuit against OpenAI mentioned in the article is probably just the first of many. When the stakes are mental health, “move fast and break things” is a terrifying ethos.
Basically, the APA has a respected model that’s already adaptable. But the AI wave has hit, and it’s time for a revision. Without it, everyone—doctors, patients, even the legit app developers—is navigating in the dark. The goal shouldn’t be to stifle innovation, but to ensure that when AI is in the therapist’s chair, even virtually, we have some way of knowing if it’s qualified.
