Evidence map›Paper›PMID 42145542›Full record

ReviewFrontiers in psychology2026

Clinical Organizational Science: an integrative framework for structural intervention in complex organizations.

Makoto Yamanaka, Masaya Nakamori

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Makoto YamanakaDroR Corporation, Tokyo, Japan.
Masaya NakamoriDroR Corporation, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organizations frequently fail to sustain transformation despite substantial investment in leadership development, cultural change programs, and structural redesign. Existing frameworks tend to treat organizational stability as passive inertia rather than as an actively and recursively reproduced dynamic state. This paper introduces Clinical Organizational Science (COS), an integrative framework that addresses this gap by specifying the structural mechanisms through which organizational stability is generated and through which durable transformation can be induced. Drawing on complexity science, neuroscience, organizational psychology, and behavioral science, COS proposes a multilevel mechanistic account-the emergence bridge-connecting individual behavioral habituation to organizational-level attractor transition. Three structured intervention techniques are presented-Field Gradient Theory, Loop Conversion Design, and Neural Base Design-each operationalizing a distinct structural mechanism with specified theoretical foundations and failure conditions. Illustrative patterns consistent with the framework's theoretical predictions are discussed across behavioral, relational, and organizational levels, with explicit acknowledgment of their conceptual rather than evidentiary status. An ethics framework governing neuroscience-informed organizational intervention is also proposed. COS offers a theoretically grounded conceptual framework that repositions organizational transformation from a behavioral change project to a structural intervention problem, accompanied by testable propositions and directions for independent empirical investigation.

Indexed as

Clinical Organizational Sciencecomplex adaptive systemsorganizational changeorganizational developmentorganizational interventionorganizational transformationpsychological safetystructural intervention

Identifiers

PMID42145542
PMCPMC13171585

What OpenQuestion holds

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Registered trials

None linked

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.