Transdiagnostic relevance of subjective cognitive complaints: a validation and population-based study using two Canadian scales (SSTICS and MoCA) in the UAE
Bibliographic record
Abstract
Background: Cognitive disorders span several diagnostic categories in psychiatry, but subjective cognitive complaints (SCC) remain underutilized in transdiagnostic assessments, particularly in Arab contexts. These difficulties can also be present in Affective disorder illnesses are assessed using neuropsychological tests. Self-assessments are useful for understanding difficulties from the user's perspective. The Subjective Scale to Investigate Cognition in Schizophrenia (SSTICS) is a rating scale designed to measure subjective cognitive complaints in persons with schizophrenia. This study explores the SSTIC-E, a culturally adapted tool, highlighting its cross-diagnostic relevance over simple psychometric validation. Methods: This cross-sectional study was conducted among 210 participants (126 patients, 84 controls) in the United Arab Emirates. Patients met ICD-10/DSM-5 criteria for schizophrenia spectrum disorders and affective disorders, in addition to other psychiatric disorders. The instruments included the SSTIC-E and the MoCA. Analysis focused on internal consistency, confirmatory factor analysis (CFA), and transdiagnostic comparisons. Results: = 0.89). No significant differences were observed in SCCs between the schizophrenia and affective disorder groups. CFA analysis confirmed a one-factor model with residual item correlations (CFI = 0.91, RMSEA = 0.058). Women reported higher SCC; age had no effect. Discussion: The SSTIC-E demonstrates utility beyond diagnostic silos, providing a valuable and culturally relevant instrument for transdiagnostic psychiatric assessment in Arabic-speaking populations. Schizophrenia exhibited slightly higher SCC compared to patients with affective disorders, with a lack of clear association between subjective and objective cognition. SCC is common across psychiatric diagnoses in the United Arab Emirates, supporting a dimensional model of cognitive dysfunction. SSTIC-E reveals insights into the lived experiences of patients not captured by objective tests. Cultural and gender influences underscore the necessity of context-specific approaches.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".