Revisions to the Young Schema Questionnaire using Rasch analysis: the YSQ-R
Bibliographic record
Abstract
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 (N = 838) that included a heterogeneous clinical sample (N = 574) and a smaller non-clinical group (N = 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. KEY POINTS What is already known about this topic: 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. What this topic adds: 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".