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Assessing Chatbot Use in Psychosis

Navigating the intersection of generative AI and mental health. A synthesis of current frameworks and empirical data for clinical assessment.

No single validated instrument exists; these are proposed structural models.
1

The Conversational Approach

Proposed by Saba & Weeks (JAMA Psychiatry)

A motivational-interviewing-style sequence over a simple checklist. Judgmental framing suppresses disclosure.

Normalize Before Asking

Set a non-judgmental baseline.

Explore Benefits First

Patients disengage if criticized initially.

Direct Examination

Invite patients to bring actual prompts & outputs.

Ongoing Dialogue

Not a one-time screening

2

AI-Informed Care Framework

Morrin et al. (Lancet Psychiatry)

Management-oriented. Reframes the AI as an “epistemic ally” rather than a therapist or friend.

Instruction Protocols
Reflective Check-ins
Advance Statements
Escalation Safeguards
System Prompt Safeguards

role: “epistemic ally”,

behavior: [

“do not claim sentience”,

“clarify limitations”,

“refer to clinical care”

],

// Requires co-design with service users

3

Domains Supported by Empirical Data

Highest-yield screening questions based on the Buck & Maheux survey.

Ever-use alone does NOT differentiate risk groups.

Intensity

Several times daily, >30 min/day, ≥6 conv/day

OR 1.70–2.56
Most Distinctive Marker

Role Ascription

Viewing AI as a companion, friend, therapist, or romantic partner.

OR 1.76–3.08

Clinical Content

Delusion-related interactions (13.3%-30.7% in elevated risk).

Med/Diagnosis adviceHidden meanings/Personal ref
4

Functional Typology

Flathers et al. (Lancet Digital Health)

Classifying system role to guide clinical/tech responses, moving away from a unitary label.

Catalyst
Amplifier
Coauthor
Object
5

Adaptable Existing Frameworks

  • Psychiatric Inquiry into Digital Media

    Moreno et al. (Psychiatric Services)

    Emphasizes quality over quantity. The closest general-purpose model.

  • Problematic Internet Use Scales

    ISAAQ, PIUQ-6, Young's IAT

    Captures compulsivity, but misses AI specific risks (anthropomorphism/delusion). Partial proxy only.

  • Technology Use Survey

    Dwyer et al.

    Assesses digital literacy, not risk. Good for checking if patient understands what an LLM is.

The Defensible Current Standard

Currently, none of these tools are validated against psychosis outcomes. Only 16% of LLM chatbot studies undergo clinical efficacy testing (Hua et al.). The practical standard is to incorporate a brief structured inquiry into routine assessment and document it as a maintenance factor where positive:

Normalized OpeningIntensityRole AscriptionMed ContentPersonal-Reference

Infographic based on synthesis of current literature regarding LLMs and Psychosis Assessment.

Citations derived from JAMA Psychiatry, Lancet Psychiatry, JMIR, and others (2024-2026).

This page was medically reviewed by Eric Wexler M.D., Ph.D. on August 14, 2026.