PAIRS(Psychiatric AI Risk Screen)

What is PAIRS?

PAIRS, the Psychiatric AI Risk Screen, is a structured clinical instrument for assessing harm from AI chatbot use in psychiatric patients. It gives clinicians a shared language and a systematic, documentable method for recognising and grading AI-related risk. But, more importantly, it is a supplement to clinical assessment and risk formulation, not a replacement for it.

Version 2.0 comprises a three-item Stage 1 Triage, three qualitative H-item gates, eight scored domains, three vulnerability tiers with graded thresholds and automatic escalation rules. It's intended for use by qualified mental health professionals.

We introduced a new domain (compulsion) to account for the ego-dystonic excessive use of AI, which doesn't necessarily pair with a lack of insight. We also merged what were previously two distinct domains, crisis substitution and self-harm, into a single category, on the basis that a longitudinal, spectrum-like approach captures that risk more reliably.

All other categories were maintained.

How to use PAIRS?

PAIRS is completed by a qualified clinician, on the basis of a clinical interview supported by collateral information where available. The assessment moves through three stages.

1
Stage 1, Triage
Three brief items establish whether AI use is clinically material for this patient. A documented low-risk exit is available after each item; if the patient screens negative throughout, the assessment may be discontinued.
2
Stage 2, H-items (H1 to H4)
Four qualitative gates targeting the highest-stakes presentations. A positive response on any H-item recommends scoring the associated domain at 3 and triggers a reconciliation check. This was introduced to ensure that high stakes domains are better represented on the scoring system.
3
Stage 3, Domain scoring
Eight domains, each rated 0 to 3 against written anchors. Apply the vulnerability modifier before scoring. The banding and escalation rules calculate the result.
Table 1 — Stage 1 Triage
Three items, administered in order. Clear-negative bands exit to Outcome A; borderline or clear-positive bands continue.
ITEMQUESTIONCLEAR NEGATIVEBORDERLINECLEAR POSITIVEDISPOSITION
ITEM 1
FREQUENCY
How often do you use AI?NeverSometimesMost days; every dayExit → A unless contradicted by history or collateral. Otherwise continue.
ITEM 2
FUNCTION
Do you ever chat to it about personal things, such as how you are feeling, or to discuss medical concerns?Instrumental use only: work, study, practical tasks.Occasional personal use. Minimisation; visible embarrassment or hesitation. Account discrepant with collateral.Personal or emotional use most days. Any statement of reliance: "I talk to it when I can't cope".Exit → A on clear negative. Borderline or clear positive → continue to Item 3.
ITEM 3
INSIGHT
What do you think is actually happening when it responds to you?Any account of a non-sentient mechanism, however technically imprecise: browses the internet, uses an algorithm, runs simulations, matches patterns in text. "I don't know" also scored here where no implicit belief in sentience or special understanding. Key marker: the AI is grasped as a technology — fallible, potentially biased, not a thinking entity.Partial model alongside clear anthropomorphisation: "I know it's a program, but it really does seem to understand me." Evasive account of how it works; guardedness or deflection when probed. Affect inconsistent with the stated understanding; the patient may say the right words but the emotional register suggests a more personal belief.Unmovable belief that the AI is genuinely thinking about or understanding them as a person: "It's different with me, I can tell". Persistent anthropomorphisation without qualification or self-correction. Delusional features: belief the AI has special access to personal information, is connected to other services, people or institutions, or is observing the patient outside the conversation.Exit → A on clear negative. Any clear positive, or borderline judged clinically significant → Flag.
What are we aiming for with PAIRS?

To give clinicians a structured, documentable way to identify, grade and respond to AI-related harm in psychiatric populations, and to build the evidence base needed for formal validation. A clinical records study screening 53,974 patients in Denmark identified 38 cases where AI chatbot use had potentially harmful consequences (Olsen, Reinecke-Tellefsen & Østergaard, 2026). Those 38 cases are almost certainly a substantial undercount. PAIRS exists because the clinical problem is real and currently has no shared method.

A validation programme comprising a Delphi panel for content validity, inter-rater reliability testing and criterion-validity assessment is underway.

Limitations
  • PAIRS hasn't been empirically validated. All scoring thresholds and escalation rules are provisional, derived from clinical reasoning rather than data. Sensitivity, specificity and predictive value are unknown.
  • The instrument and its domain selection are developer-led and subject to confirmation bias. Content validity hasn't been externally established.
  • PAIRS captures a single time point. Trajectory, meaning how harm escalates over time, may be the more clinically meaningful signal. This instrument doesn't track it.
  • Applied mechanically, it will generate false positives. A high score warrants further assessment; it doesn't demonstrate that AI use caused the presentation. Clinical judgement is always required.
  • The recommended actions are calibrated to the UK clinical and legal context and require local adaptation elsewhere.
For the full list of limitations and how we arrived at PAIRS, read our preprint (v2.0).
Dr Hellen von Winckler MBBS, MRCPsych · Dr Gabriel Hawthorne MBBS, MRCPsych · PAIRS v2.0 · Cite v2.0: DOI 10.5281/zenodo.21909430
PAIRS is free to use. It is not empirically validated and does not constitute clinical advice. Feedback: info@chatbotharm.org