Evidence map›Paper›PMID 41908131›Full record

ArticleFrontiers in psychiatry2026

Perceive-Assess-Dose-Safeguard: a safety-gated state-action grammar for psychotherapy micro-decisions in computational psychiatry.

Eik Niederlohmann

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Eik NiederlohmannDepartment of Psychosomatic Medicine and Psychotherapy, Kliniken Erlabrunn, Breitenbrunn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psychotherapy unfolds as a sequence of rapid micro-decisions under uncertainty. Within seconds, clinicians integrate verbal, paraverbal, embodied, and relational cues, estimate the patient's momentary capacity for affective work, choose an intervention dose, and apply stop rules to prevent overwhelm and rupture. Computational psychiatry offers principled frameworks for sequential decision-making, but progress in computational psychotherapy remains constrained by the lack of clinically grounded, machine-readable grammars that capture therapist micro-decisions in context. I introduce the Perceive-Assess-Dose-Safeguard (PAD-S) decision matrix as a safety-gated state-action grammar for psychotherapy micro-decisions. PAD-S formalizes four "front-of-system" signals-defensive/avoidant organization (DEF), anxiety/arousal and tolerance (ANX), patient progression toward direct experience and action (PRO), and self-attack/shame processes (SUP)-together with three safety thresholds (A-C) that gate intervention dose. Each decision point can be logged as an "episode line" (trigger, state, threshold, action, and expected functional impact), enabling transcript annotation and structured datasets. PAD-S is grounded in experiential dynamic psychotherapy (EDT/ISTDP) yet expressed as an orientation-translatable representation layer: DEF can be read as avoidance/safety behavior, ANX as arousal/tolerance, PRO as approach and value-consistent action, and SUP as self-criticism/shame. I show how PAD-S trajectories can interface with hybrid neural-cognitive models such as SPICE to discover sparse, interpretable equations of process change, and I outline testable hypotheses and feasible pilot studies (reliability, outcome linkage, and modeling) to evaluate the framework. computational psychiatry; computational psychotherapy; psychotherapy process coding; interpretable AI; human-in-the-loop; active inference; SPICE; Mini-ICF-APP.

Indexed as

active inferencecomputational psychiatrycomputational psychotherapyhuman-in-the-loopinterpretable AIMini-ICF-APPpsychotherapy process codingSPICE

Identifiers

PMID41908131
PMCPMC13023058

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.