Can structured prompting improve cognitive distortion detection?
This explores whether breaking distortion diagnosis into discrete stages—mirroring clinical CBT workflow—helps language models identify and classify thinking patterns more accurately than standard approaches.
Diagnosis of Thought (DoT) prompting structures cognitive distortion detection into three stages that mirror how clinical psychologists actually diagnose thinking patterns:
Stage 1 — Subjectivity Assessment. Patient speech mixes reality (objective facts) with interpretations (subjective thoughts). The first step separates these, summarizing objective facts into "situations" that serve as the evidence base for diagnosing the subjective thoughts. This prevents the model from treating interpretations as facts.
Stage 2 — Contrastive Reasoning. Based on the situation, the model generates reasoning processes both supporting and contradicting the patient's thoughts. By contrasting two different interpretations grounded in the same facts, distorted thought patterns become visible. This mirrors the CBT technique of examining evidence for and against a belief.
Stage 3 — Schema Analysis. The model identifies the underlying cognitive structures (schemas) that produced the specific reasoning process, mapping them to recognized cognitive distortion types (emotional reasoning, overgeneralization, mental filter, should statements, all-or-nothing, mind reading, fortune telling, magnification, personalization, labeling).
DoT achieves >10% relative improvement on distortion assessment and >15% on classification over ChatGPT zero-shot. Expert evaluation rated the generated rationales as "comprehensive" or "partially good" at high rates. The three-stage structure generates explanations that are clinically useful — therapists could use them as starting points for case formulation.
Since Can cognitive scaffolding improve how models reason about social scenes?, structured multi-stage prompting that maps to established cognitive frameworks consistently outperforms unstructured approaches. DoT is the CBT-specific instance of this general principle: domain-expert reasoning workflows decompose into inspectable stages that LLMs can follow.
Source: Psychology Therapy Practice
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Can cognitive scaffolding improve how models reason about social scenes?
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same structural insight applied to visual reasoning
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Why do discourse patterns predict anxiety better than single words?
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Can critical questions improve how language models reason?
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parallel: domain-specific structured prompting improves performance
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How do readers track segments, purposes, and salience together?
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Original note title
cognitive distortion detection benefits from structured three-stage prompting that separates subjectivity assessment from contrastive reasoning from schema analysis