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Record W3206678525 · doi:10.3389/fpsyg.2021.718440

The Hierarchy of Defense Mechanisms: Assessing Defensive Functioning With the Defense Mechanisms Rating Scales Q-Sort

2021· article· en· W3206678525 on OpenAlexaff
Mariagrazia Di Giuseppe, J. Christopher Perry

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsPsychologyCognitive psychologyClinical psychology

Abstract

fetched live from OpenAlex

The psychodynamic concept of defense mechanisms is nowadays considered by professionals with various theoretical orientations of great importance in the understanding of human development and psychological functioning. More than half century of empirical research has demonstrated the impact of defensive functioning in psychological well-being, personality organization and treatment process-outcome. Despite the availability of a large number of measures for their evaluation, only a few instruments assess the whole hierarchy of defenses, based on the Defense Mechanisms Rating Scales (DMRS), which arguably offers an observer-rated gold standard of assessment. The present article illustrates the theoretical and methodological background of the DMRS-Q, the Q-sort version of the DMRS for clinical use. Starting from the definition and function of the 30 defense mechanisms included in the hierarchy, we extracted 150 items that captured a full range of defensive manifestations according to the DMRS theory. The DMRS-Q set is described in this paper with reference to the DMRS manual. Directions are also provided for using the DMRS-Q online software for the free and unlimited coding of defense mechanisms. After each coding, the DMRS-Q software provides a report including qualitative and quantitative scores reflecting the individual’s defensive functioning. Qualitative scores are displayed as the Defensive Profile Narratives (DPN), while quantitative scores are reported as Overall Defensive Functioning (ODF), defensive categories, defense levels, and individual defense mechanisms. Syntax for the scoring is displayed in the results and a clinical vignette of a psychotherapy session coded with the DMRS-Q is provided. The DMRS-Q is an easy-to-use, free, computerized measure that can help clinicians in monitoring changes in defense mechanisms, addressing therapeutic intervention, fostering symptoms decreasing and therapeutic alliance. Moreover, the DMRS-Q might be a valid tool for teaching the hierarchy of defense mechanisms and increase the observer-rated assessment of this construct in several research fields.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.321
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations112
Published2021
Admission routes1
Has abstractyes

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