Arabic translation and validation of the Clinician Administered Staden Schizophrenia Anxiety Rating Scale (S-SARS)
Bibliographic record
Abstract
Abstract Background: Literature on anxiety in patients with schizophrenia of Arab origin is surprisingly scarce, particularly given that expressions of both psychotic disorders and anxiety disorders can be largely shaped by cultural factors. The present study proposes to complement the literature by examining the psychometric properties of an Arabic translation of the Staden Schizophrenia Anxiety Rating Scale (S-SARS) in a sample of chronic, remitted patients with schizophrenia from Lebanon. As the Arabic version of the Generalized Anxiety Disorder 7‑Item Scale (GAD‑7) has not been previously validated in an Arabic-speaking clinical population of patients with schizophrenia, this study had as a secondary objective to examine the psychometric properties of this scale before its use. Method: his cross-sectional study has been conducted during August and October 2023. A total of 117 chronic inpatients diagnosed with schizophrenia who were remitted and clinically stable filled the survey, with a mean age of 57.86 ± 10.88 years and 63.3% males. Results: Confirmatory factor analyses showed that all 10 items were condensed into a single factor and had high factor loading values between 0.53 and 0.81. The reliability of the Arabic version of the S-SARS was excellent as attested by a Cronbach’s alpha and a McDonald’s omega coefficients of 0.89 and .90, respectively. The score of Arabic S-SARS correlated positively with the GAD-7 scores (r = .55; p < .001), thus supporting good convergent validity. As for discriminant validity, findings showed positive correlations between S-SARS and depression scores as assessed using the Calgary Depressive Symptoms Scale. In addition, the Arabic S-SARS correlated negatively with general functioning, further supporting the good validity and clinical relevance of the scale. Finally, measurement invariance was established in the gender subsamples (males vs. females) at the configural, metric and scalar levels, with females showing more anxiety than males. Conclusion: Findings suggest that the Arabic S-SARS holds good psychometric properties, and is suitable for use among Arabic-speaking patients with schizophrenia in clinical practice and research. The Arabic version of S-SARS will hopefully be widely applied to provide useful and timely clinical information for monitoring and adequately treating patients with schizophrenia, in order to improve the course and prognosis of the disease.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".