Challenges of insight assessment in pediatric obsessive-compulsive disorder: Initial results and clinical considerations from a measure development study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Assessing insight among OCD-affected youth has been limited by the absence of a multi-item measure for this population. The present study outlines the development of the Measure of Insight for Obsessive-Compulsive Disorder (MI-OCD), presents initial findings, and explores conceptual challenges. Methods: Along with the Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS), the 7-item MI-OCD was administered to 178 OCD-affected youth aged 7–19 (mean age = 13.5, SD = 2.8; 55% female) presenting for assessment across three OCD-specialty clinics. Items 4–7 were only completed by those with an identified feared outcome (61%). Results: MI-OCD items were positively correlated with the CY-BOCS’ insight question, but were not related to age or avoidance. Correlations and factor analysis indicated items coalesced around concepts of symptoms as unwanted (1–3) and symptoms as useful/valid (4–7), although factor fit and internal consistency was sub-optimal. Most youth perceived their symptoms as unwanted (positively correlated with severity), while the extent to which youth perceived symptoms as useful was more varied (not associated with severity). Discussion: Insight remains a challenging construct to assess in youth given various developmental, psychological, and environmental confounds. The MI-OCD may be useful in the context of evaluating and addressing individual barriers to treatment engagement over time.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it