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Record W4413731748 · doi:10.2196/75736

Preoperative Anxiety and Information Desire Among Patients Undergoing Elective Surgery in Northern Sudan: Multicenter Cross-Sectional Study

2025· article· en· W4413731748 on OpenAlexvenueno aff
Abeer Ahmed, Mohamed Nasur, Eman Mohamed, Mustafa Ahmed, Murouj Mohammed, Mohamed A. Issak

Bibliographic record

VenueJMIR Perioperative Medicine · 2025
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsCross-sectional studyPreprintAnxietyMedicineMulticenter studyElective surgeryGeneral surgerySurgeryPsychiatryRandomized controlled trialPathology

Abstract

fetched live from OpenAlex

Background: Preoperative anxiety is a common psychological condition, and many patients express a desire for more information before surgery. Understanding the prevalence and associated factors of both preoperative anxiety and the desire for information can improve patient care. Objective: This study aimed to assess the prevalence of preoperative anxiety and desire for information, as well as their associated sociodemographic, medical, and surgical factors, among patients undergoing elective surgery in Northern State, Sudan. Methods: A hospital-based, multicenter, cross-sectional study was conducted from November 2024 to February 2025 in Northern State, Sudan, involving patients undergoing elective surgery. Data were collected through face-to-face interviews using a structured questionnaire and the validated Arabic version of the Amsterdam Preoperative Anxiety and Information Scale (APAIS). Chi-square tests and univariate and multivariate logistic regression were performed to identify the associated factors and the magnitude, with statistical significance set at P<.05. Results: Of the 380 patients approached, 305 participated in the study (response rate=80.3%): 173 of the 305 participants (56.7%) were male, and the median age was 43 (IQR 30-64) years. Most participants were married (n=207, 67.9%), educated (n=248, 81.3%), and had family support (n=253, 83.0%). Regarding surgical characteristics, the majority underwent either intermediate (n=136, 44.6%) or major (n=142, 46.6%) procedures. General anesthesia was the most common type used (n=159, 52.2%), and most participants (n=169, 55.4%) underwent surgery in public hospitals. Most participants reported that their surgeries were not covered by insurance (n=264, 86.6%) and described good sleep quality the night before surgery (n=221, 72.5%). Of the 305 participants, 75 (24.6%) experienced preoperative anxiety, whereas 92 (30.1%) expressed a moderate to high desire for information. Preoperative anxiety was significantly associated with family support (adjusted odds ratio [aOR] 7.12, 95% CI 2.64-19.23; P<.001), surgery in public hospitals (aOR 4.31, 95% CI 2.30-8.07; P<.001), poor sleep quality the night before surgery (aOR 2.85, 95% CI 1.51-5.38; P=.001), and American Society of Anesthesiologists (ASA) classification III/IV (aOR 2.36, 95% CI 1.00-5.54; P=.049). Similarly, a higher desire for information was significantly associated with being educated (aOR 2.48, 95% CI 1.00-6.11; P=.049), having family support (aOR 4.10, 95% CI 1.81-9.30; P=.001), undergoing surgery in a public hospital (aOR 3.57, 95% CI 1.93-6.61; P<.001), and being classified as ASA III/IV (aOR 3.26, 95% CI 1.39-7.64; P=.001). Conclusions: Preoperative anxiety and desire for information are common among Sudanese patients. Family involvement may paradoxically increase anxiety and the desire for more information due to shared concerns and cultural factors. Other significant predictors of anxiety include poor sleep quality and higher ASA classification. Additionally, education, family support, and chronic diseases were associated with a higher desire for information. Addressing these factors may alleviate preoperative anxiety, satisfy communication needs, and improve preoperative care.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.356
Teacher spread0.332 · 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 designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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