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Revisions to the Young Schema Questionnaire using Rasch analysis: the YSQ-R

2023· dataset· en· W4394481732 on OpenAlexaff
Ozgur Yalcin, Ida Marais, Christopher Lee, Helen Correia

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRasch modelSchema (genetic algorithms)PsychologyDevelopmental psychologyComputer scienceInformation retrieval

Abstract

fetched live from OpenAlex

The aim of this study was to refine the YSQ-L3 by identifying the most statistically and clinically appropriate items for each Early Maladaptive Schema (EMS) using Rasch analysis. A Rasch analysis was undertaken on a large sample (<i>N</i> = 838) that included a heterogeneous clinical sample (<i>N</i> = 574) and a smaller non-clinical group (<i>N</i> = 264). Overall, 116 out of 232 items showed misfit across a number of statistical indicators. After the removal of these items, the fit improved for all subscales and showed good (.74) to excellent (.86) reliability with the exception of Enmeshment (.57). In line with previous research, items originally measuring Punitiveness were found to better fit two separate subscales, Punitiveness (Self) and Punitiveness (Other). Similarly, items assessing Emotional Inhibition fit better as two different constructs; Emotional Constriction, reflecting an over-control related to shame/embarrassment of showing emotions, and Fear of Losing Control, related to anxiety of the consequences if emotions are not contained. This is the first study to apply a rigorous methodological process to item selection from the YSQ-L3. The findings of this study are significant given the wide use of this scale cross-culturally in both clinical and research settings and offer a possible alternative to the current short form. <b>KEY POINTS</b> <b>What is already known about this topic</b>: Early Maladaptive Schemas (EMS) are transdiagnostic constructs that arise from unmet needs in childhood and become self-perpetuating through destructive patterns of interacting with the self, others, and the world.The Young Schema Questionnaire (YSQ) is the primary assessment tool used to assess 18 EMS, usually as part of Schema Therapy which is designed to treat complex and chronic psychological disorders.Psychometric evaluations of the YSQ have primarily focussed on factor structure and assessing the higher-order schema domains and have consistently yielded mixed findings across all versions. Early Maladaptive Schemas (EMS) are transdiagnostic constructs that arise from unmet needs in childhood and become self-perpetuating through destructive patterns of interacting with the self, others, and the world. The Young Schema Questionnaire (YSQ) is the primary assessment tool used to assess 18 EMS, usually as part of Schema Therapy which is designed to treat complex and chronic psychological disorders. Psychometric evaluations of the YSQ have primarily focussed on factor structure and assessing the higher-order schema domains and have consistently yielded mixed findings across all versions. <b>What this topic adds</b>: This is the first study to assess the psychometric properties at an individual item level in the YSQ using Rasch Analysis.Overall, only 116 out of 232 items in the YSQ-L3 showed appropriate fit across a number of statistical indicators.In line with previous research, the Emotional Inhibition schema is better conceptualised as two separate constructs which were a Fear of Losing Control and Emotional Constriction. Similarly, Punitiveness (Self) and Punitiveness (Other) are distinct constructs derived from the original Punitiveness schema. This is the first study to assess the psychometric properties at an individual item level in the YSQ using Rasch Analysis. Overall, only 116 out of 232 items in the YSQ-L3 showed appropriate fit across a number of statistical indicators. In line with previous research, the Emotional Inhibition schema is better conceptualised as two separate constructs which were a Fear of Losing Control and Emotional Constriction. Similarly, Punitiveness (Self) and Punitiveness (Other) are distinct constructs derived from the original Punitiveness schema.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.131
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2400.108

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 head0.215
GPT teacher head0.477
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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