ERP for OCD

Practise exposure and response prevention for OCD across a whole treatment: the rationale, the hierarchy, the first exposures with ritual prevention, the middle sessions and the ending.

What you practise

• Map obsessions, feared consequences, visible and covert rituals, avoidance and reassurance sources.
• Build the ERP rationale from the patient's own examples and check that it landed.
• Anchor the distress scale and build a specific, graded hierarchy.
• State ritual-prevention rules completely and hold them through negotiation.
• Conduct in vivo exposure: encourage approach, stay in it, track distress, no reassurance or distraction.
• Conduct imaginal exposure with a present-tense script that includes the feared outcome.

Who you can meet

• Tobias, 36 — Checks the stove, the door and the chargers before leaving, and drives home at lunch to check again. Tobias is 36, an IT support technician, and since his daughter was born he has doubted every time he leaves that he left the house safe. He photographs the knobs and the lock to look at later, turns the car round after a bump in the road, and asks his partner the same questions several times a day. Useful focus: build the rationale from his own routine, find the rituals he does not count as rituals, and plan exposure with ritual prevention he can actually keep.

What the feedback looks at

• Functional assessment
• Treatment rationale
• Hierarchy and distress scale
• Ritual-prevention rules
• In vivo exposure conduct
• Imaginal exposure conduct
• Reassurance and accommodation
• Processing after exposure

Rated against: Dimensions are PsychBase's own, authored from the ERP-for-OCD competence list in the UCL (Roth and Pilling) CBT competence framework and the session components of the Foa, Yadin and Lichner therapist guide (2012); the exposure-conduct anchors adapt the behaviour classes of the Exposure Process Coding System and the Exposure Guide (Benito and colleagues). No published, anchored competence scale exists for ERP. Every anchor is written in our own words; nothing is transcribed. Scores are generated by an AI reviewer for practice feedback and are not equivalent to rating by a trained human; nothing here is endorsed by any of these authors or bodies.

This lab is for clinical training. The patient is generated by an AI language model from a written case; no real patient and no patient data are involved. Browsing is open; starting a session needs a free account.