Evidence map›Paper›PMID 41230365›Full record

ArticleClinical neuropsychiatry2025

From Attachment Trauma to Traumatic Attachment: Invisible Injuries of Early Childhood and Subtle Relational Codes of Self-Regulation.

Vedat Şar

Abstract read
In one paragraph

Article in Clinical neuropsychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Vedat ŞarDepartment of Psychiatry, Koç University School of Medicine, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Building on recent contributions by Farina and Schimmenti (2025a), this paper advances a more nuanced framework for their concept of attachment trauma focusing on the underlying mechanisms. The injury of attachment trauma, often concealed within ostensibly ordinary family systems, may leave no explicit memory trace yet manifest as enduring patterns of dysregulation. Instead, it becomes apparent through its clinical consequences such as Complex PTSD, borderline phenomena, dissociative disorders and their various complications. Central to the framework presented in this paper are the concept of relational encryption, in which interpersonal signals are coded to establish a balanced interpersonal dependency, and internal moderation, defined as the capacity for flexible regulation between affective and relational extremes, which is needed to overcome trauma-related paradoxes. Encryption vulnerability due to deficient or excessive relational coding, on the other hand, leads to "traumatic attachment" which is one of the consequences of attachment trauma. In accordance with these concepts, Implicit Psychotherapy, as a technique of communication, provides a clinical framework for safely engaging with these pre-reflective, unspoken wounds through pacing, symbolic containment, and embodied relational experience. Dialectical Dynamic Therapy (DDT), as a conceptual framework, facilitates the re-establishment of internal moderation. The paper points toward transformative therapeutic pathways grounded in embodied relational repair, epistemic trust, and dynamic therapeutic engagement. Ultimately, the paper advocates for a post-linear model of trauma, one that embraces complexity, dialectical thinking, and the reparative potential of therapeutic relationships, while insisting on the need to "unpack" the overloaded construct of attachment trauma.

Indexed as

attachment traumadialectic dynamic therapyencryption vulnerabilityimplicit psychotherapyinternal moderation

Identifiers

PMID41230365
PMCPMC12603937

What OpenQuestion holds

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Registered trials

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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.