Quality of Life in OCD: Differential Impact of Obsessions, Compulsions, and Depression Comorbidity
Bibliographic record
Abstract
OBJECTIVE: An anxiety disorder severely affects the sufferer's quality of life (QOL), and this may be particularly true of those with obsessive-compulsive disorder (OCD). This study examines the differential impact of obsessions, compulsions, and depression comorbidity on the QOL of individuals with OCD. METHOD: Forty-three individuals diagnosed with OCD according to DSM-IV criteria and experiencing clinically significant obsessions and compulsions completed measures of QOL, obsessive-compulsive symptom severity, and depression severity. RESULTS: Obsession severity was found to significantly predict patient QOL, whereas the severity of compulsive rituals did not impact on QOL ratings. Comorbid depression severity was the single greatest predictor of poor QOL, accounting for 54% of the variance. CONCLUSIONS: Given the importance of these symptoms, treatments that directly target obsessions and secondary depression symptoms in OCD are warranted. However, replication of these findings in a prospective cohort study is required, because although the the current study's cross-sectional design allows for the examination of the associations among obsessions, depression, and QOL, it cannot establish their temporal framework (that is, causal relations).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".