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Record W4403458788 · doi:10.1186/s12888-024-06142-y

The translation and validation of the surgical anxiety questionnaire into the modern standard Arabic language: results from classical test theory and item response theory analyses

2024· article· en· W4403458788 on OpenAlexaff
Abdulmajeed Abdullah Alghamdi, Khalid Alghuthayr, Ziyad Mohammed Alshahrani, Abdullah Mohammed Asiri, Hadeel Ghazzawi, Mai Helmy, Khaled Trabelsi, Mariwan Husni, Haitham Jahrami

Bibliographic record

VenueBMC Psychiatry · 2024
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsNOSM University
Fundersnot available
KeywordsArabicTest (biology)Item response theoryPsychologyAnxietyClinical psychologyPsychometricsTranslation (biology)Natural language processingLinguisticsCognitive psychologyPsychiatryComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

BACKGROUND: Preoperative anxiety is commonly found in patients who are waiting for surgery and can lead to negative surgical outcomes. Understanding the sources of surgical anxiety allows healthcare providers to identify at-risk patients and implement psychosocial interventions such as counseling, relaxation techniques, and cognitive‒behavioral therapy to minimize anxiety. Few comprehensive psychiatric measures are available to assess preoperative anxiety in Arabic. OBJECTIVE: Our study aimed to translate, adapt, and validate the Surgical Anxiety Questionnaire (SAQ) into the modern standard Arabic language, also known as Fusha al-Asr Arabic. METHODS: To translate the questionnaire, the research team used the gold standard process of forward translation by two independent translators along with back translation evaluation by four trained medical doctors. A cross-sectional study was conducted using an online survey completed by 208 Arabic speakers (mean age 38 years, 44% women) from four countries. Psychometric analyses, which included internal consistency, test-retest reliability, convergent validity, confirmatory factor analysis, and item response analysis, were performed. Convergent validity tests were performed against the Generalized Anxiety Disorder 2-item Scale (GAD-2), Patient Health Questionnaire-4 (PHQ-2), Perceived Stress Scale 4 (PSS-4), and Arabic version of the Visual Analog Scale for anxiety (VAS-A). RESULTS: The mean SAQ of our sample was 19.38 ± 12.63 (possible range 0-68). The Arabic SAQ translation demonstrated excellent internal consistency, with McDonald's omega and a Cronbach's alpha of approximately 0.90. The test-retest reliability was also high, with an intraclass coefficient of 0.94. The SAQ showed strong convergent validity against the GAD-2 (r = 0.94, p < 0.01). The SAQ also showed weak-moderate correlations with the PHQ-2 (r = 0.26, p < 0.01), PSS-4 (r = 43, p < 0.01), and VAS-A (r = 0.36, p < 0.01) scores. The original three-factor structure was supported by confirmatory factor analysis, confirming the original structure reported in the original English language version. The results for fitness indices showed acceptable preliminary results (CFI/TLI approximately 0.90), and deleting some items improved the model fit (CFI/TLI > 0.90, RMSEA < 0.08). We suggest retaining the original factorial solution until further validation studies can be conducted. The item response theory (IRT) results identified no items that were excessively difficult or subject to guessing. The multidimensional IRT provided evidence that the SAQ items form a multidimensional scale assessing surgical anxiety that fits the classical model reasonably well. CONCLUSION: The SAQ has demonstrated acceptable reliability and validity; thus, it is a trustworthy and valid tool for evaluating preoperative anxiety in Arabic speakers. Future research could benefit from using the SAQ in both surgical and psychiatric research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.368
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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