Turkish Adaptation of the 4AT Delirium Screening Scale: A Validity and Reliability Study

Turkish Adaptation of the 4AT Delirium Screening Scale: A Validity and Reliability Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Turkish Adaptation of the 4AT Delirium Screening Scale: A Validity and Reliability Study İSLAM ELAGÖZ, Aynur KOYUNCU, Ayla YAVA, Musa ŞAHPOLAT This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6623222/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract Background This study aimed to evaluate the psychometric properties, specifically the validity and reliability, of the Turkish version of the 4AT Delirium Screening Tool. Methods This methodological study was conducted in the post-anaesthesia care unit of a public hospital between 1 April and 30 June 2023 with ethics committee approval (2023/025). Data were collected from 188 patients using a demographic form and delirium assessment tools, including the 4AT, CAM-ICU, and DSM-5 criteria. Analyses were performed using SPSS version 27.0. The internal consistency of the 4AT was assessed using KR-20, and its validity was examined using chi-square and ROC analyses. The significance level was set at p < 0.05. Results The 4AT demonstrated strong diagnostic agreement with the CAM-ICU (98.4%) and DSM-5 (98.4%) criteria. Its internal consistency was high (KR-20 = 0.899). In terms of diagnostic performance, the 4AT showed 97.8% sensitivity and 99.3% specificity, with an ROC analysis showing that the 4AT had a high discriminative ability to detect delirium, with an AUC of 0.981. Conclusion These findings indicate that the Turkish version of the 4AT is a valid, reliable, and practical tool for the rapid detection of post-operative delirium in clinical settings. Clinical Trial Registration: NCT06187389 Delirium Post-operative Care Reliability Screening Tool Validity Figures Figure 1 Figure 2 Figure 3 Inroduction Delirium is a serious cognitive disorder marked by sudden onset and a fluctuating course throughout the day. It significantly disrupts core cognitive abilities, particularly attention and awareness [ 1 ]. It is frequently encountered in the post-operative setting, particularly among vulnerable populations, such as the elderly and those with comorbidities [ 2 ]. Contributing factors include advanced age, pre-existing medical conditions, and the use of specific medications. Moreover, lengthy surgical procedures, hypothermia, and high doses of anaesthetic agents further increase the risk of developing delirium [ 1 ]. Delirium can present in hyperactive, hypoactive, or mixed subtypes, which differ in terms of symptom severity and clinical detectability. The reported incidence rates of delirium in post-anaesthesia care units range widely from 4.1–45% [ 2 , 3 ]. These findings highlight the need for more rigorous monitoring and critical reassessment of current post-operative care protocols. [ 4 ]. Post-operative delirium is associated with a broad spectrum of complications that may delay recovery, extend hospitalisation [ 5 ], and even elevate mortality rates [ 6 ]. These complications include infections, an increased likelihood of falls, urinary incontinence, and pressure injuries. Long-term consequences may involve persistent cognitive impairment, the onset of dementia, and a decline in functional capacity [ 5 , 6 ]. Such outcomes not only compromise patient well-being but also complicate caregiving efforts [ 6 ]. Therefore, early identification of delirium is essential for ensuring effective management during the post-operative period. The European Society of Anaesthesiology has emphasised the importance of prompt delirium detection in recovery units to minimise adverse outcomes and uphold patient safety [ 7 ]. A range of clinical tools and diagnostic techniques are available for delirium identification [ 8 , 9 ]. While a comprehensive psychiatric evaluation remains the diagnostic gold standard, its complexity and the need for specialised expertise make it impractical for routine use in fast-paced clinical settings, such as recovery rooms [ 10 ]. Many delirium screening tools require substantial training and are time intensive, limiting their practical utility [ 8 ]. Commonly used instruments include the Delirium Risk Assessment Scale, the Confusion Assessment Method (CAM) [ 9 ], CAM for the Intensive Care Unit (CAM-ICU) [ 11 ], 3D-CAM, Delirium Index (DI), and CAM severity (CAM-S). Despite their clinical value, the use of these tools remains limited in real-world practice. [ 8 , 12 ]. Timely recognition of delirium is vital, as delayed detection leads to increased healthcare costs, longer hospital stays, heavier workloads for clinical staff, and a higher risk of treatment complications [ 2 , 13 ]. These challenges underscore the urgent need for reliable and efficient screening protocols in recovery units [ 12 ]. The 4AT Delirium Screening Tool was developed to meet the need for a quick and practical delirium assessment in time-constrained clinical environments, such as recovery units [ 14 ]. Comprising four brief items, the 4AT can be administered in less than two minutes without requiring specialised training. Its diagnostic accuracy has been validated in numerous studies across diverse patient populations. [ 15 , 16 ]. Although it is widely adopted in global clinical practice, limited research exists on its specific use in post-anaesthesia recovery units. Although the 4AT has demonstrated strong diagnostic accuracy and ease of use, certain limitations have been noted in the literature. For instance, some studies suggest that the tool may have reduced sensitivity in detecting hypoactive delirium, a subtype that often presents with subtle symptoms and is frequently overlooked in clinical settings. This limitation may affect early intervention efforts, especially in post-operative patients who exhibit minimal agitation or overt confusion. Therefore, while the 4AT provides a practical solution, clinicians should remain vigilant for less apparent signs of cognitive dysfunction [ 17 ]. This study was initiated because of the absence of a fast and effective delirium screening tool tailored to the needs of post-anaesthesia care units in Turkey. The primary aim of this study was to evaluate the validity and reliability of the Turkish adaptation of the 4AT Delirium Screening Tool. By introducing a culturally and linguistically adapted version of the 4AT, this study seeks to facilitate faster and more reliable detection of post-operative delirium in Turkish clinical settings. The following research questions guided this investigation: What is the validity of the 4 AT Delirium Test for the Turkish patient population? What is the reliability of the 4 AT Delirium Test in the Turkish patient population? Methodology Study Design and Setting This methodological investigation was conducted between 1 April 2023 and 30 June 2023 at a state hospital in southeastern Turkey. The study population comprised adult patients who had undergone various elective surgical procedures, including general surgery (e.g. cholecystectomy, hernia repair), orthopaedic surgery (e.g. total knee or hip arthroplasty), and urological interventions (e.g. transurethral resection of the prostate), and were subsequently transferred to the post-anaesthesia care unit (PACU). The COSMIN guidelines were used to guide and standardise the methodological quality and reporting of the study. [ 18 ]. Ethical Considerations This study was approved by the Non-Interventional Ethics Committee of Kilis 7 Aralık University (2023/025). Both verbal and written informed consent were obtained from all participants in accordance with ethical practices supported by Emanuel EJ [ 19 ]. This study strictly adhered to the ethical principles outlined in the World Medical Association’s Declaration of Helsinki [ 20 ], which were meticulously followed throughout all stages of the research. Clinical trial registration : This study was registered on ClinicalTrials.gov with the number NCT06187389. Registration date: December 29, 2023. Participants The study population comprised patients with stable health conditions and without life-threatening conditions in the post-anaesthesia care unit of the hospital's operating theatre where the study was conducted. Participants who voluntarily agreed to participate were included in this study. G*Power 3.1.9.7 software (Düsseldorf, Germany) was used to determine sample size. Calculations were performed using Cohen's standard effect size (d) [ 21 ], with a correlation of 0.3, α error of 0.05, β error of 0.05, and a 95% statistical power. These parameters indicated that a minimum of 148 patients was sufficient for statistical reliability. To mitigate potential data loss, the researchers increased the number of participants by 25%, resulting in 188 individuals being included in the study. Sample Criteria The study sample consisted of adult patients who had undergone elective surgical procedures in the departments of neurosurgery, general surgery, gynaecology, orthopaedics, or urology, and were subsequently transferred to the post-anaesthesia care unit (PACU). Inclusion Criteria: Eligible participants met the following criteria: age > 18 years, ability to communicate, and no documented history of neurological or psychiatric disorders that could interfere with the accurate diagnosis of delirium. Exclusion criteria: Patients were excluded if they experienced severe complications following anaesthesia, had a diagnosis of advanced cognitive impairment or dementia, or demonstrated complete loss of communicative ability. Additional exclusion criteria included lack of cooperation during the study procedures, unwillingness or inability to provide the required information, and withdrawal of consent at any stage of participation. Data Collection Tools The data collection instruments employed in this study included the Patient Assessment Form, Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), and 4AT Delirium Test. Patient Assessment Form: This form was developed by the researchers to collect patient anamnesis during initial admission and systematically assess factors that may predispose patients to post-operative delirium. It comprised general demographic data and clinically relevant variables. The demographic and descriptive variables included age, sex, and body mass index (BMI, kg/m²). Surgery-related variables included the type of surgical department (neurosurgery, general surgery, gynaecology, orthopaedics, or urology), type of anaesthesia administered (general or regional), duration of the surgical procedure (in minutes), and mean arterial pressure (MAP) recorded during the perioperative period. Post-operative clinical parameters were also evaluated, including the patient's pain status (measured using a standardised pain assessment scale), presence of chronic diseases (e.g. hypertension and diabetes mellitus), substance use history (e.g. tobacco, alcohol, and sedative medications), and use of assistive devices such as glasses, hearing aids, or mobility aids. Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) Developed by Ely et al. in 2001, the CAM-ICU is a validated tool for delirium assessment in critically ill patients. The original English version demonstrated high sensitivity (93–100%), specificity (98–100%), and inter-rater reliability (κ = 0.96) [ 22 ]. The Turkish adaptation, completed in 2005, retained excellent specificity (97%) and reliability, with a slightly lower sensitivity (65–69%) [ 23 ]. 4AT Delirium Test: The 4AT is a brief (< 2 min), easy-to-administer screening tool designed to detect delirium and cognitive impairment. It is widely implemented in clinical practice globally and has been shown to improve delirium detection rates in hospitals [ 2 ]. A meta-synthesis of 17 studies reported a pooled sensitivity of 88% for the 4AT [ 24 ]. Language Adaptation of the Scale The Turkish adaptation of the 4AT delirium screening tool was conducted in accordance with the ISPOR guidelines for the cross-cultural adaptation of health-related measures [ 25 ]. A panel comprising two linguists whose native language was Turkish, three experienced academic nurses, and one psychiatrist was established for the translation. The initial translation was performed by two independent, native Turkish-speaking linguists, focusing on item validity, terminology consistency, and semantic accuracy. Subsequently, the research team reviewed and harmonised the translated version through panel discussions and reached a consensus. In the back-translation phase, two native Turkish-speaking linguists, who were unaware of the content of the original study, translated the Turkish 4AT version back to English. Semantic and conceptual differences were analysed by comparing them with the original 4AT. The researchers administered the preliminary Turkish version of the scale to 20 patients from the target population in a clinical setting. Each participant was asked to provide feedback regarding item clarity and comprehension. Based on the panel’s evaluation of the participant responses, no major issues were identified regarding item clarity, conceptual accuracy, or cultural relevance. Minor wording adjustments were made to improve readability. Overall, the tool was found to be comprehensible and feasible for use in routine clinical practice. Based on these outcomes, the final Turkish version of the 4AT Delirium Screening Scale was developed. Data Collection for the Research After hospital admission, informed consent was obtained from each participant during the preoperative phase of the study. Subsequently, the patients completed the demographic and clinical data forms. During hospitalisation, cognitive function was evaluated by a psychiatrist, and only individuals with normal cognitive function were included in the study. Following surgery, upon transfer to the post-anesthesia care unit (PACU), the presence of emergence delirium was evaluated using two standardized screening tools: the CAM-ICU and the 4AT Delirium Test. Additionally, an independent clinical evaluation was conducted by a psychiatrist blinded to the scores of both screening tools. The final diagnosis of delirium was made solely based on clinical criteria in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), through direct clinical observation without reference to any standardised screening tool scores (Fig. 2). Figure 2 here Statistical Analysis of the Data All statistical analyses were conducted using IBM SPSS Statistics version 27.0 (IBM Corp., Armonk, NY, USA) with a 99% confidence level (p < 0.05). Descriptive statistics (frequency, percentage, mean, and standard deviation) were used to summarise the demographic data. The normality of the continuous variables was assessed using the Shapiro-Wilk test. For normally distributed variables, independent-samples t-tests were used to examine group differences. The internal consistency of the adapted 4AT was assessed using the Kuder-Richardson Formula 20 (KR-20). Validity analyses included the calculation of item difficulty (via Heryson and Simple methods) and item discrimination indices. The diagnostic agreement between the adapted 4AT and reference tools (CAM-ICU and DSM-5) was evaluated using chi-square tests and agreement metrics. Additionally, ROC curve analysis was performed to determine the sensitivity, specificity, AUC, and optimal cut-off values for each diagnostic tool relative to the DSM-5 as the gold standard. Results Descriptive Characteristics of the Study Sample In total, 188 patients were included in this study. Among the participants, 43.62% (n = 82) were men and 56.38% (n = 106) were women. Regarding age distribution, 50.0% (n = 94) of the patients were between 18 and 40 years, 38.3% (n = 72) were between 41 and 65 years, and 11.7% (n = 22) were aged 65 years or older. The mean age was 43.62 ± 12.75 years (range, 18–82 years). In terms of body mass index (BMI), 29.8% (n = 56) of the patients had a BMI between 18.5–24.9 kg/m² (normal weight), 52.1% (n = 98) between 25.0–29.9 kg/m² (overweight), and 18.1% (n = 34) between 30.0–34.9 kg/m² (obese). The mean BMI was 27.07 ± 2.44 kg/m² (range: 21.46–33.12). The surgical duration ranged from 30 to 190 min, with a mean of 82.3 ± 31.44 min. Of the patients, 66.0% (n = 124) underwent surgery lasting between 30 and 90 min, while 34.0% (n = 64) had procedures lasting 90–190 min. The mean arterial pressure (MAP) ranged from 70 to 95 mmHg, with a mean value of 80.41 ± 6.97. MAP values of 62.8% (n = 118) of patients had MAP values between 70 and 85 mmHg, and those of 37.2% (n = 70) were between 85 and 95 mmHg. The distribution of patients according to surgical departments was as follows: 9.57% (n = 18) in neurosurgery, 31.91% (n = 60) in general surgery, 12.77% (n = 24) in gynaecology, 28.72% (n = 54) in orthopaedics, and 17.02% (n = 32) in urology. Regarding the type of anaesthesia, 68.09% (n = 128) received general anaesthesia and 31.91% (n = 60) underwent spinal anaesthesia. When assessing post-operative pain status, 70.21% (n = 132) of the patients reported the presence of pain, whereas 29.79% (n = 56) did not experience pain (Table 1). Table 1 HERE Item Difficulty Analysis The difficulty levels of the four items on the scale were evaluated using both the Heryson and Simple (Traditional) methods. According to the Heryson classification, Item 1 was classified as “Very Easy” (index: 0.936), while Items 2, 3, and 4 were all classified as “Easy”, with indices ranging from 0.729 to 0.771. When assessed with the Simple Method, Item 1 also remained in the “Very Easy” category (0.882), whereas Items 2–4 were rated as “Easy” to “Moderate” based on their respective indices between 0.520 and 0.578. These results suggest that all items fell within acceptable difficulty ranges, with Item 1 being the easiest across both classification methods (Table 2). Table 2 HERE Item Discrimination Analysis In this study, item discrimination indices were calculated to evaluate the ability of the scale items to distinguish between individuals with high and low scores on the scale. Item 1 had a discrimination index of 0.235 and was classified as a "marginal item" ( 0.20–0.29 range) according to accepted criteria. Therefore, the item was substantially revised in terms of content and clarity, based on expert opinions. The high internal consistency of the overall scale (KR-20 = 0.899) supported the inclusion of the revised item, and the retained item did not negatively affect the scale’s overall reliability. In contrast, items 2, 3, and 4 demonstrated excellent discrimination, with indices of 0.941, 0.961, and 0.843, respectively, and were retained in the scale without any modifications (Table 3). Table 3 HERE Criterion Validity In this study, the diagnostic agreement between the 4AT delirium screening tool and two widely validated reference tools, CAM-ICU and DSM-5, was evaluated in a sample of 188 patients. Diagnostic concordance was analysed using cross-tabulation and the chi-square test (χ²), and agreement metrics were calculated based on classification consistency. Compared with the CAM-ICU, the 4AT tool showed a strong diagnostic alignment. Among patients classified as delirium-positive by 4AT (n = 45, 23.4%), 43 (22.9%) were also positive according to CAM-ICU, resulting in an agreement rate of 98.4% and a statistically significant chi-square value (χ² = 171.8, p < 0.001). Similarly, among the 143 patients identified as negative by the 4AT, 143 were also negative by the CAM-ICU. Comparison with the DSM-5, regarded as the gold standard for delirium diagnosis, revealed a similarly high concordance. Among patients identified as delirious by 4AT, 41 (21.8%) were also positive on DSM-5, while 144 (76.6%) of those who were 4AT-negative were confirmed to be negative on DSM-5. This yielded an agreement rate of 98.4%, with a chi-square value of χ² = 171.6 (p < 0.001). These findings collectively support the criterion validity of the 4AT, demonstrating that it achieves diagnostic outcomes that are highly consistent with those of established clinical tools. The use of Fisher’s Exact Test confirmed the statistical significance of these associations (p < 0.05 in all comparisons).( (Table 4; Fig. 1). Table 4 HERE Figure 1 here Diagnostic Accuracy via ROC Analysis The diagnostic performance of the 4AT delirium screening tool was evaluated in comparison with two established reference tools: CAM-ICU and DSM-5. Sensitivity, specificity, likelihood ratios, predictive values, area under the curve (AUC), and Youden Index were calculated for each tool based on ROC analysis. The 4AT demonstrated excellent diagnostic accuracy, with a sensitivity of 97.8% (95% CI: 93.5–99.7) and specificity of 99.3% (95% CI: 97.1–99.9) at a cutoff score of ≥ 0.5. Its positive predictive value (PPV) was 97.6%, negative predictive value (NPV) was 99.4%, and AUC was 0.99. The Youden Index was 0.99, reflecting outstanding overall diagnostic capability. The CAM-ICU showed slightly lower sensitivity at 95.6% (90.1–98.9) but high specificity of 98.6% (95.9–99.8). At a cutoff score of ≥ 0.5, the positive and negative likelihood ratios were 68.3 and 0.045, respectively. The PPV and NPV were 92.1% and 99.2%, respectively, and the AUC was 0.98. The corresponding chi-square p-value for the comparison was 0.001, indicating statistical significance. The DSM-5, used as the clinical reference standard, exhibited a sensitivity of 93.2% (87.1–97.5) and a perfect specificity of 100% (98.9–100). Although the LR + was not calculated, the LR − was 0.068, with a PPV of 100% and an NPV of 98.3%. The AUC was 0.96 and the Youden Index was 0.93, again with a statistically significant difference from 4AT (p < 0.05). These findings reinforce the criterion validity of the 4AT scale by demonstrating near-perfect alignment with both a widely used clinical screening tool (CAM-ICU) and the diagnostic gold standard (DSM-5). (Table 5). Table 5 HERE Figure 3 here Discussion Delirium is a frequently encountered yet often overlooked post-operative complication [ 26 ]. Particularly among older adults, this condition can delay recovery, prolong hospitalisation, and increase the risk of additional health complications [ 2 ]. Prompt recognition of delirium in post-anaesthesia care units is critical, as it directly impacts patient safety and clinical outcomes [ 4 ]. Therefore, accurate and timely identification of delirium remains a clinical priority. The variability in reported delirium prevalence across studies is largely attributed to differences in diagnostic tools, highlighting the complexity of detecting this condition [ 15 , 16 , 24 ]. Within this context, the 4AT screening tool has emerged as a practical and reliable method for facilitating delirium detection [ 15 , 16 ]. This study was designed to evaluate the validity and reliability of the Turkish version of the 4AT, aiming to improve post-operative delirium detection in Turkish healthcare settings. The key finding of this study confirms that the Turkish version of the 4AT Delirium Screening Tool demonstrates strong psychometric properties. Comparative analyses revealed a high level of agreement between the 4AT and established instruments such as the CAM-ICU. In clinical diagnostics, sensitivity and specificity are essential parameters for evaluating a tool’s accuracy. A meta-analysis by Tieges et al. (2021) reported that the 4AT exhibits sensitivity and specificity rates of 88%. Similarly, Hendry et al. (2016) described the scale as a well-balanced tool with high sensitivity and adequate specificity. Other studies have also supported these findings, reinforcing the diagnostic reliability of the scale across diverse clinical populations. The ease of use and rapid administration of the 4AT make it particularly suitable for time-constrained clinical environments. In this study as well, sensitivity and specificity levels were found to be considerably high, reaffirming the tool’s appropriateness for rapid delirium assessment, especially among geriatric patients [ 27 ]. Furthermore, the study demonstrated strong alignment between the Turkish version of the 4AT and DSM-5-based clinical evaluations, further supporting the adapted scale’s clinical accuracy. Given that DSM-5 assessments require detailed clinical examination and expertise, the 4AT offers a significant advantage by providing rapid preliminary screening. The observed consistency between 4AT outcomes and DSM-5 diagnoses reinforces the tool’s utility in clinical practice. Particularly in fast-paced environments (e.g., recovery rooms, intensive care units, emergency departments), the 4AT’s rapid screening capability can support timely clinical decision-making and improve patient outcomes. The study also demonstrated that the Turkish version of the 4AT has a high reliability coefficient, indicating that it produces consistent results across applications. According to the literature, reliability coefficients above 0.7 are considered acceptable for psychological and clinical instruments [ 29 ]. The coefficient obtained in this study exceeded this threshold, further validating the tool’s robustness. Previous research conducted in various cultural and clinical contexts has also confirmed the scale’s reliability [ 14 , 29 , 30 ], supporting its broader applicability for delirium screening in different healthcare settings. No statistically significant association was found between gender and the incidence of delirium. However, a significant relationship was observed between the surgical department where the operation was performed and the likelihood of developing delirium. Additionally, patients who experienced delirium were generally older, and age was positively correlated with delirium risk. These findings are consistent with those of Hasegawa (2021), who identified advanced age as a major contributing factor to delirium development [ 14 ]. Thus, age is an important predictor of risk assessment. Neither the type of anaesthesia (general or spinal) nor the duration of surgery significantly influenced the incidence of postoperative delirium. Based on these findings, both patient age and surgical specialty appear to be critical variables in evaluating the risk of delirium during post-operative care. The ROC analysis results provide compelling evidence of the high diagnostic performance of the Turkish version of the 4AT in detecting post-operative delirium. The tool demonstrated excellent sensitivity and specificity, confirming its capacity to accurately differentiate between patients with and without delirium. The elevated AUC value further reinforces the scale’s discriminative strength. These findings are consistent with international validation studies, which have repeatedly affirmed the diagnostic utility of the 4AT across diverse clinical settings [ 15 , 26 ]. The strong diagnostic concordance between the 4AT and DSM-5 criteria is especially noteworthy. Although DSM-5 remains the diagnostic gold standard for delirium, its application requires comprehensive clinical judgment and time. In contrast, the 4AT offers a rapid, user-friendly alternative that does not compromise diagnostic reliability. The observed alignment between 4AT and DSM-5 outcomes enhances the tool’s value in high-acuity settings such as PACUs, ICUs, and emergency departments [ 31 ], where rapid screening is essential for timely clinical interventio. However, it is important to note that this study focused solely on short-term diagnostic outcomes. Although the Turkish version of the 4AT demonstrated strong immediate diagnostic accuracy, future longitudinal studies are warranted to explore its predictive validity and utility in monitoring long-term post-operative cognitive outcomes.. In conclusion, this study demonstrates that the Turkish version of the 4AT Delirium Screening Tool offers high diagnostic accuracy for the rapid and reliable identification of post-operative delirium. The tool's strong sensitivity and specificity values are consistent with findings reported in the international literature. Given its ease of administration and robust psychometric properties, the 4AT is recommended as an effective clinical instrument for early delirium screening, particularly among high-risk post-operative patients. Conclusion This study aimed to comprehensively evaluate the validity and reliability of the Turkish adaptation of the 4AT Delirium Screening Tool and to determine its place in clinical practice. The findings indicate that the Turkish version of the 4AT is a highly valid and reliable instrument for delirium screening. When evaluating the psychometric properties of the scale, a high level of agreement (ranging from 87–99%) was observed with established diagnostic criteria such as CAM-ICU, and DSM-5. These results demonstrate that the diagnostic accuracy of the 4AT is consistent with international literature. In particular, its short administration time (under two minutes) and simple structure provide practical advantages in busy clinical environments. Therefore, this study confirms that the Turkish version of the 4AT is a valid, reliable, and practical clinical tool for delirium screening. Especially suitable for use in post-anaesthesia care units and intensive care settings, this scale offers the potential for early diagnosis and intervention, thereby contributing to improved patient outcomes. However, further research involving larger samples across different patient populations and diverse clinical settings is necessary to evaluate the performance of the scale more comprehensively. Recommendations The adoption of the 4AT as a standard delirium screening tool is recommended for clinical settings where rapid assessment is essential, such as intensive care units, post-anaesthesia care units, and emergency departments. Although the Turkish version of the 4AT has demonstrated strong validity and reliability within the local patient population, further studies are warranted in broader surgical and medical cohorts. Expanding validation efforts would enhance the tool’s generalisability and support the timely detection of delirium across various clinical contexts. To improve accessibility and promote widespread utilisation, the development of digital health applications incorporating the 4AT is encouraged. A digital platform could provide healthcare professionals with immediate access to the tool, enabling more efficient screening and management of delirium. Additionally, large-scale implementation and testing of the 4AT across different geographic regions and healthcare institutions in Turkey are essential. Such efforts would allow for a more comprehensive evaluation of the tool’s psychometric performance in demographically and culturally diverse populations in the future. Limitations This study has several limitations. Chief among them is that the research was conducted exclusively in a post-anaesthesia care unit, which limits the generalisability of the findings to other clinical settings or different patient populations. Moreover, the study focused solely on short-term outcomes, and thus, potential long-term effects or persistent complications associated with delirium were not within the scope of this research. Declarations Competing interests: The authors declare that they have no competing interests. Funding: This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution İE: Contributed to the study design and methodology, coordinated the scale adaptation process, developed the data analysis strategy, conducted statistical analyses, organised and interpreted the results in tables, formatted the manuscript according to journal guidelines, and performed comparative evaluations with the literature. AK: Contributed to manuscript writing, English language editing, statistical analyses, presentation and interpretation of the results in tables and comparative evaluation with relevant literature. AY: Coordinated the scale adaptation process and supervised the study. MŞ was responsible for planning and conducting the data collection process. All authors actively contributed to all stages of the study and approved the final manuscript. Acknowledgement The authors would like to express their gratitude to the medical and nursing staff of the post-anesthesia care unit for their support and cooperation throughout the study. 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The DSM-5 criteria, level of arousal and delirium diagnosis: inclusiveness is safer. BMC medicine, 12, 141. https://doi.org/10.1186/s12916-014-0141-2 Ely, E. W., Gautam, S., Margolin, R., Francis, J., May, L., Speroff, T., Truman, B., Dittus, R., Bernard, R., & Inouye, S. K. (2001). The impact of delirium in the intensive care unit on hospital length of stay. Intensive care medicine , 27 (12), 1892–1900. https://doi.org/10.1007/s00134-001-1132-2 Inouye, S. K., Westendorp, R. G., & Saczynski, J. S. (2014). Delirium in elderly people. Lancet (London, England) , 383 (9920), 911–922. https://doi.org/10.1016/S0140-6736(13)60688-1 Hernandez, B. A., Lindroth, H., Rowley, P., Boncyk, C., Raz, A., Gaskell, A., García, P. S., Sleigh, J., & Sanders, R. D. (2017). Post-anaesthesia care unit delirium: incidence, risk factors and associated adverse outcomes. British journal of anaesthesia, 119(2), 288–290. https://doi.org/10.1093/bja/aex197 Hasegawa, T., Seo, T., Kubota, Y., Sudo, T., Yokota, K., Miyazaki, N., Muranaka, A., Hirano, S., Yamauchi, A., Nagashima, K., Iyo, M., & Sakai, I. (2022). Reliability and validity of the Japanese version of the 4A's Test for delirium screening in the elderly patient. Asian journal of psychiatry, 67, 102918. https://doi.org/10.1016/j.ajp.2021.102918 Hendry, K., Quinn, T. J., Evans, J., Scortichini, V., Miller, H., Burns, J., Cunnington, A., & Stott, D. J. (2016). Evaluation of delirium screening tools in geriatric medical inpatients: a diagnostic test accuracy study. Age and ageing, 45(6), 832–837. https://doi.org/10.1093/ageing/afw130 Infante, M. T., Pardini, M., Balestrino, M., Finocchi, C., Malfatto, L., Bellelli, G., Mancardi, G. L., Gandolfo, C., & Serrati, C. (2017). Delirium in the acute phase after stroke: comparison between methods of detection. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 38(6), 1101–1104. https://doi.org/10.1007/s10072-017-2832-x Evensen, S., Hylen Ranhoff, A., Lydersen, S. et al. The delirium screening tool 4AT in routine clinical practice: prediction of mortality, sensitivity and specificity. Eur Geriatr Med 12 , 793–800 (2021). https://doi.org/10.1007/s41999-021-00489-1 Mokkink, L. B., Prinsen, C. A., Bouter, L. M., Vet, H. C., & Terwee, C. B. (2016). The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and how to select an outcome measurement instrument. Brazilian journal of physical therapy , 20 (2), 105–113. https://doi.org/10.1590/bjpt-rbf.2014.0143 Emanuel EJ, Wendler D, Killen J, Grady C. What makes clinical research in developing countries ethical? The benchmarks of ethical research. J Infect Dis. 2004;189(5):930-937. doi: https://doi.org/10.4324/9780203771587. General Assembly of the World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. J Am Coll Dent. 2014 Summer;81(3):14-8. PMID: 25951678. http://www.wma.net/en/30publications/10policies/b3/index.html - PubMed Cohen J. Statistical power analysis for the behavioral sciences. Academic Press; 2013. doi: https://doi.org/10.4324/9780203771587. Ely, E. W., Inouye, S. K., Bernard, G. R., Gordon, S., Francis, J., May, L., Truman, B., Speroff, T., Gautam, S., Margolin, R., Hart, R. P., & Dittus, R. (2001). Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA, 286(21), 2703–2710. https://doi.org/10.1001/jama.286.21.2703 Aypar, Ü., Kanbak, M., Yorgancı, K., Özdemir, H., Akıncı, S. B., Çelikcan, A. ve Rezaki, M. (2005). Yoğun Bakım Ünitesinde Konfüzyon Değerlendirme Ölçeğinin geçerlik güvenilirlik çalışması. Türk Anesteziyoloji ve Reanimasyon Derneği Dergisi, 33(4), 333-341. Tieges, Z., Maclullich, A. M. J., Anand, A., Brookes, C., Cassarino, M., O'connor, M., Ryan, D., Saller, T., Arora, R. C., Chang, Y., Agarwal, K., Taffet, G., Quinn, T., Shenkin, S. D., & Galvin, R. (2021). Diagnostic accuracy of the 4AT for delirium detection in older adults: systematic review and meta-analysis. Age and ageing, 50(3), 733–743. https://doi.org/10.1093/ageing/afaa224 Wild, D., Grove, A., Martin, M., Eremenco, S., McElroy, S., Verjee-Lorenz, A., Erikson, P., & ISPOR Task Force for Translation and Cultural Adaptation (2005). Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures: report of the ISPOR Task Force for Translation and Cultural Adaptation. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 8(2), 94–104. https://doi.org/10.1111/j.1524-4733.2005.04054.x Wu, J., Zhang, T., He, J., & Zhang, Q. (2024). Association between nutritional status and post-operative delirium in elderly surgical patients. Current Topics in Nutraceutical Research, 22, 760-764. https://doi.org/10.37290/ctnr2641-452x.22:760-764 Hou, L., Zhang, Q., Cao, L., Chen, M., Wang, Q., Li, Y., Li, S., Ge, L., & Yang, K. (2023). Diagnostic accuracy of the 4AT for delirium: A systematic review and meta-analysis. Asian journal of psychiatry , 80 , 103374. https://doi.org/10.1016/j.ajp.2022.103374 ÖZDAMAR, Kazım (2016). Ölçek ve Test Geliştirme-Yapısal Eşitlik Modellemesi, Eskişehir: Nisan Kitabevi. Kuladee, S., & Prachason, T. (2016). Development and validation of the Thai version of the 4 'A's Test for delirium screening in hospitalized elderly patients with acute medical illnesses. Neuropsychiatric disease and treatment, 12, 437–443. https://doi.org/10.2147/NDT.S97228 Delgado-Parada, E., Morillo-Cuadrado, D., Saiz-Ruiz, J., Cebollada-Gracia, A., Ayuso-Mateos, J. L., & Cruz-Jentoft, A. J. (2022). Diagnostic accuracy of the Spanish version of the 4AT scale (4AT-ES) for delirium screening in older inpatients. The European Journal of Psychiatry, 36(3), 182-190. https://doi.org/10.1016/j.ejpsy.2022.01.003 Arnold, E., Lugton, J., Spiller, J., & Finucane, A. (2025). What are the experiences and support needs of district nurses caring for terminally ill people with delirium at home? A qualitative study. BMC palliative care, 24(1), 60. https://doi.org/10.1186/s12904-024-01627-9 Tables Table 1. Distribution of Patients' Demographic Characteristics (N=188) Variable n (%) Gender Male Female 82 (43.62) 106 (56.38) Age 18-40 41-65 65 and over 94 (%50.0) 72 (%38.3) 22 (%11.7) BMI (kg/m²) 18.5 - 24.9 25.0 - 29.9 30.0 - 34.9 56 (%29.8) 98 (%52.1) 34 (%18.1) Surgery Duration (mins) 30-90 90-190 124 (%66.0) 64 (%34.0) MAP Value 70-85 85-95 118 (%62.8) 70 (%37.2) Surgery Department Neurosurgery General Surgery Gynaecology Orthopaedics Urology 18 (9.57) 60 (31.91) 24 (12.77) 54 (28.72) 32 (17.02) Type of Anaesthesia General Spinal 128 (68.09) 60 (31.91) Pain Status Present Absent 132 (70.21) 56 (29.79) Variable Min.-Max. Mean±SD Age 18-82 43.62±12.75 BMI (kg/m²) 21.46-33.12 27.07±2.44 Surgery Duration (mins) 30-190 82.3±31.44 MAP Value (mmHg) 70-95 80.41±6.97 BMI: Body Mass Index; MAP: Mean Arterial Pressure; SD: Standard Deviation Table 2. Item Difficulty Index Results (N=188) Item Item Difficulty Index Evaluation Heryson Method Simple Method Item 1 0.936 0.882 Very Easy/Very Easy Item 2 0.739 0.529 Very Easy/Easy Item 3 0.729 0.520 Very Easy/Easy Item 4 0.771 0.578 Very Easy/Easy Classification Methods for Item Difficulty Index Heryson Method Classification :0.90: Very Easy. 0.70-0.89: Easy. 0.30-0.69: Moderate. 0.80: Very Easy. 0.60-0.79: Easy. 0.40-0.59: Moderate. <0.40: Difficult Table 3. Item Discrimination Index Results (N=188) Item Discrimination Index Evaluation & Action Item 1 0.235 Marginal Item / Requires Substantial Revision Item 2 0.941 Excellent Item / Retain Without Modification Item 3 0.961 Excellent Item / Retain Without Modification Item 4 0.843 Excellent Item / Retain Without Modification Interpretation Guidelines: ≥0.40: Excellent Item. 0.30–0.39: Good Item. 0.20–0.29: Marginal Item<0.20: Poor Item Table 4. Comparison of Diagnostic Concordance Between 4AT and CAM-ICU, NU-DESC, and DSM-5 (N=188) Delirium 4 AT n (%) CAM-ICU n (%) Agreement Metric (%) χ²/p Positive (23.4%) 43(22.9%) 98.4 171.8 0.001 Negative 143(76.6%) 2 (1.1%) 143 (76.1%) 4 AT n (%) DSM-V n (%) Agreement Metric (%) χ²/p Positive 44 (23.4%) 41 (21.8%) 98.40 171.6 0.001 Negative 144 (76.6%) 3 (1.6%) 144 (76.6%) 4AT: Delirium screening tool. CAM-ICU: Confusion Assessment Method for the Intensive Care Unit. NU-DESC: Nursing Delirium Screening Scale. DSM-5: Diagnostic and Statistical Manual of Mental Disorders. 5th Edition. χ²= Fisher’s Exact Test Chi-square test. Agreement Metric (Success Rate): This represents the percentage of consistent results between the 4AT scale and other tools. p<0.01 Table 5. Comparative Diagnostic Performance of 4at Delirium Screening Tools (N=188) Sensitivity (95% CI) Specificity (95% CI) Optimal Cut-Off LR+ LR- PPV NPV AUC Youden Index χ²p 4AT 97.8% (93.5-99.7) 99.3% (97.1-99.9) ≥ 0.5 139.7 0.022 97.6% 99.4% 0.99 0.99 0.001 CAM-ICU 95.6% (90.1-98.9) 98.6% (95.9-99.8) ≥ 0.5 68.3 0.045 92.1% 99.2% 0.98 0.96 0.001 DSM-5 93.2% (87.1-97.5) 100% (98.9-100) ≥ 4 - 0.068 100% 98.3% 0.96 0.93 0.001 CAM-ICU: Confusion Assessment Method for Intensive Care Unit. DSM-5 =Diagnostic and Statistical Manual of Mental Disorders-5. CI = Confidence Interval. LR+ =Positive Likelihood Ratio. LR- =Negative Likelihood Ratio. PPV =Positive Predictive Value. NPV= Negative Predictive Value. AUC= Area Under ROC Curve. Diagnostic Accuracy Categories: Sensitivity= Excellent: >90%. Acceptable: 80-90%. Poor: 95%. Acceptable: 90-95%. Poor: 10. Acceptable: 5-10. Poor: <5; LR-= Excellent: 0.2. p : Fisher’s Exact Test (for proportions). Δ sens (Difference ): 4AT's metric minus comparison tool's metric. Optimal Cut-Off: ≥ 0.5 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6623222","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483211571,"identity":"9f46db4f-ca67-4010-85c1-810a16ba5165","order_by":0,"name":"İSLAM ELAGÖZ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACNgbmBhAtA+Z9AImwE9TCCNbCAyIYZ4BEmAnag6SFGUIS0MDHf7Dx0w0GGx7+/sWHP9v82ibPx8zA+OFjDh6HSSQ2S+cwpPFI3HiWYJzbd9uwjZmBWXLmNnxaGBuAWg7zMNw4Y5Cc23ObEaiFjZkXnxb+g82/cxj+88gDtRy27LltT1gLQ2Ib0JYDPAbnewybGX7cTiSsRSKxzTrHIJnH8AZbMmNvw+3kNmbGZrx+ke8/fPh2ToWdnNz5w4c//Phz23Z+e/PBDx/xaIEAAyCWSADGURuIB4kpIgD/ASDxh0jFo2AUjIJRMKIAADnjS3MFTAjEAAAAAElFTkSuQmCC","orcid":"","institution":"Kilis 7 Aralık University","correspondingAuthor":true,"prefix":"","firstName":"İSLAM","middleName":"","lastName":"ELAGÖZ","suffix":""},{"id":483211572,"identity":"ffe5466c-9244-4a27-9ffe-2c0817ff1899","order_by":1,"name":"Aynur KOYUNCU","email":"","orcid":"","institution":"Hasan Kalyoncu University","correspondingAuthor":false,"prefix":"","firstName":"Aynur","middleName":"","lastName":"KOYUNCU","suffix":""},{"id":483211573,"identity":"b36756df-b3e9-46c2-928b-6942286b76b7","order_by":2,"name":"Ayla YAVA","email":"","orcid":"","institution":"Hasan Kalyoncu University","correspondingAuthor":false,"prefix":"","firstName":"Ayla","middleName":"","lastName":"YAVA","suffix":""},{"id":483211574,"identity":"e4652870-c4cc-4936-ac55-02c1e1884054","order_by":3,"name":"Musa ŞAHPOLAT","email":"","orcid":"","institution":"Yalova University","correspondingAuthor":false,"prefix":"","firstName":"Musa","middleName":"","lastName":"ŞAHPOLAT","suffix":""}],"badges":[],"createdAt":"2025-05-08 19:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6623222/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6623222/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86660342,"identity":"2c2f6fca-9e3b-4da0-a6c0-e8cabaad33f1","added_by":"auto","created_at":"2025-07-14 10:34:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePerformance Comparison of 4AT, CAM-ICU, NU-DESC, and DSM-5 in Detecting Delirium Based on ROC Metrics (n=188)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6623222/v1/b69ff6f36ba0d276679f8acd.png"},{"id":86662312,"identity":"658fc439-f9d2-413c-acdf-3a4722e9d5bf","added_by":"auto","created_at":"2025-07-14 10:42:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25373,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchema of Assessment Timeline Across Perioperative Phases\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6623222/v1/5595038cd8c74c7afdd8ce34.png"},{"id":86660345,"identity":"9cc1bec9-c298-436b-84b2-b1df1a71b1d5","added_by":"auto","created_at":"2025-07-14 10:34:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58877,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Curve for the 4AT Delirium Screening Tool Using DSM-5 as the Reference Standard\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6623222/v1/92defc853df9de7e78d50e43.png"},{"id":86665099,"identity":"46455c21-187d-491d-a101-3bac7b86e684","added_by":"auto","created_at":"2025-07-14 10:58:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1505489,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6623222/v1/e47a010f-4816-48c7-96f8-14694605c7a8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Turkish Adaptation of the 4AT Delirium Screening Scale: A Validity and Reliability Study","fulltext":[{"header":"Inroduction","content":"\u003cp\u003eDelirium is a serious cognitive disorder marked by sudden onset and a fluctuating course throughout the day. It significantly disrupts core cognitive abilities, particularly attention and awareness [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is frequently encountered in the post-operative setting, particularly among vulnerable populations, such as the elderly and those with comorbidities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Contributing factors include advanced age, pre-existing medical conditions, and the use of specific medications. Moreover, lengthy surgical procedures, hypothermia, and high doses of anaesthetic agents further increase the risk of developing delirium [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Delirium can present in hyperactive, hypoactive, or mixed subtypes, which differ in terms of symptom severity and clinical detectability. The reported incidence rates of delirium in post-anaesthesia care units range widely from 4.1\u0026ndash;45% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These findings highlight the need for more rigorous monitoring and critical reassessment of current post-operative care protocols. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePost-operative delirium is associated with a broad spectrum of complications that may delay recovery, extend hospitalisation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and even elevate mortality rates [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These complications include infections, an increased likelihood of falls, urinary incontinence, and pressure injuries. Long-term consequences may involve persistent cognitive impairment, the onset of dementia, and a decline in functional capacity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Such outcomes not only compromise patient well-being but also complicate caregiving efforts [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, early identification of delirium is essential for ensuring effective management during the post-operative period. The European Society of Anaesthesiology has emphasised the importance of prompt delirium detection in recovery units to minimise adverse outcomes and uphold patient safety [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA range of clinical tools and diagnostic techniques are available for delirium identification [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While a comprehensive psychiatric evaluation remains the diagnostic gold standard, its complexity and the need for specialised expertise make it impractical for routine use in fast-paced clinical settings, such as recovery rooms [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Many delirium screening tools require substantial training and are time intensive, limiting their practical utility [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Commonly used instruments include the Delirium Risk Assessment Scale, the Confusion Assessment Method (CAM) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], CAM for the Intensive Care Unit (CAM-ICU) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], 3D-CAM, Delirium Index (DI), and CAM severity (CAM-S). Despite their clinical value, the use of these tools remains limited in real-world practice. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTimely recognition of delirium is vital, as delayed detection leads to increased healthcare costs, longer hospital stays, heavier workloads for clinical staff, and a higher risk of treatment complications [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These challenges underscore the urgent need for reliable and efficient screening protocols in recovery units [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The 4AT Delirium Screening Tool was developed to meet the need for a quick and practical delirium assessment in time-constrained clinical environments, such as recovery units [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Comprising four brief items, the 4AT can be administered in less than two minutes without requiring specialised training. Its diagnostic accuracy has been validated in numerous studies across diverse patient populations. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Although it is widely adopted in global clinical practice, limited research exists on its specific use in post-anaesthesia recovery units. Although the 4AT has demonstrated strong diagnostic accuracy and ease of use, certain limitations have been noted in the literature. For instance, some studies suggest that the tool may have reduced sensitivity in detecting hypoactive delirium, a subtype that often presents with subtle symptoms and is frequently overlooked in clinical settings. This limitation may affect early intervention efforts, especially in post-operative patients who exhibit minimal agitation or overt confusion. Therefore, while the 4AT provides a practical solution, clinicians should remain vigilant for less apparent signs of cognitive dysfunction [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study was initiated because of the absence of a fast and effective delirium screening tool tailored to the needs of post-anaesthesia care units in Turkey. The primary aim of this study was to evaluate the validity and reliability of the Turkish adaptation of the 4AT Delirium Screening Tool. By introducing a culturally and linguistically adapted version of the 4AT, this study seeks to facilitate faster and more reliable detection of post-operative delirium in Turkish clinical settings. The following research questions guided this investigation:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the validity of the 4 AT Delirium Test for the Turkish patient population?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the reliability of the 4 AT Delirium Test in the Turkish patient population?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003eThis methodological investigation was conducted between 1 April 2023 and 30 June 2023 at a state hospital in southeastern Turkey. The study population comprised adult patients who had undergone various elective surgical procedures, including general surgery (e.g. cholecystectomy, hernia repair), orthopaedic surgery (e.g. total knee or hip arthroplasty), and urological interventions (e.g. transurethral resection of the prostate), and were subsequently transferred to the post-anaesthesia care unit (PACU). The COSMIN guidelines were used to guide and standardise the methodological quality and reporting of the study. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003e This study was approved by the Non-Interventional Ethics Committee of Kilis 7 Aralık University (2023/025). Both verbal and written informed consent were obtained from all participants in accordance with ethical practices supported by Emanuel EJ [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This study strictly adhered to the ethical principles outlined in the World Medical Association\u0026rsquo;s Declaration of Helsinki [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which were meticulously followed throughout all stages of the research.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical trial registration\u003c/b\u003e: This study was registered on ClinicalTrials.gov with the number NCT06187389. Registration date: December 29, 2023.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe study population comprised patients with stable health conditions and without life-threatening conditions in the post-anaesthesia care unit of the hospital's operating theatre where the study was conducted. Participants who voluntarily agreed to participate were included in this study. G*Power 3.1.9.7 software (D\u0026uuml;sseldorf, Germany) was used to determine sample size. Calculations were performed using Cohen's standard effect size (d) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], with a correlation of 0.3, α error of 0.05, β error of 0.05, and a 95% statistical power. These parameters indicated that a minimum of 148 patients was sufficient for statistical reliability. To mitigate potential data loss, the researchers increased the number of participants by 25%, resulting in 188 individuals being included in the study.\u003c/p\u003e\n\u003ch3\u003eSample Criteria\u003c/h3\u003e\n\u003cp\u003eThe study sample consisted of adult patients who had undergone elective surgical procedures in the departments of neurosurgery, general surgery, gynaecology, orthopaedics, or urology, and were subsequently transferred to the post-anaesthesia care unit (PACU).\u003c/p\u003e\n\u003ch3\u003eInclusion Criteria:\u003c/h3\u003e\n\u003cp\u003eEligible participants met the following criteria: age\u0026thinsp;\u0026gt;\u0026thinsp;18 years, ability to communicate, and no documented history of neurological or psychiatric disorders that could interfere with the accurate diagnosis of delirium.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eExclusion criteria:\u003c/h2\u003e\u003cp\u003ePatients were excluded if they experienced severe complications following anaesthesia, had a diagnosis of advanced cognitive impairment or dementia, or demonstrated complete loss of communicative ability. Additional exclusion criteria included lack of cooperation during the study procedures, unwillingness or inability to provide the required information, and withdrawal of consent at any stage of participation.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection Tools\u003c/h3\u003e\n\u003cp\u003eThe data collection instruments employed in this study included the Patient Assessment Form, Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), and 4AT Delirium Test.\u003c/p\u003e\n\u003ch3\u003ePatient Assessment Form:\u003c/h3\u003e\n\u003cp\u003eThis form was developed by the researchers to collect patient anamnesis during initial admission and systematically assess factors that may predispose patients to post-operative delirium. It comprised general demographic data and clinically relevant variables. The demographic and descriptive variables included age, sex, and body mass index (BMI, kg/m\u0026sup2;). Surgery-related variables included the type of surgical department (neurosurgery, general surgery, gynaecology, orthopaedics, or urology), type of anaesthesia administered (general or regional), duration of the surgical procedure (in minutes), and mean arterial pressure (MAP) recorded during the perioperative period. Post-operative clinical parameters were also evaluated, including the patient's pain status (measured using a standardised pain assessment scale), presence of chronic diseases (e.g. hypertension and diabetes mellitus), substance use history (e.g. tobacco, alcohol, and sedative medications), and use of assistive devices such as glasses, hearing aids, or mobility aids.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eConfusion Assessment Method for the Intensive Care Unit (CAM-ICU)\u003c/h2\u003e\u003cp\u003eDeveloped by Ely et al. in 2001, the CAM-ICU is a validated tool for delirium assessment in critically ill patients. The original English version demonstrated high sensitivity (93\u0026ndash;100%), specificity (98\u0026ndash;100%), and inter-rater reliability (κ\u0026thinsp;=\u0026thinsp;0.96) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The Turkish adaptation, completed in 2005, retained excellent specificity (97%) and reliability, with a slightly lower sensitivity (65\u0026ndash;69%) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4AT Delirium Test:\u003c/h2\u003e\u003cp\u003eThe 4AT is a brief (\u0026lt;\u0026thinsp;2 min), easy-to-administer screening tool designed to detect delirium and cognitive impairment. It is widely implemented in clinical practice globally and has been shown to improve delirium detection rates in hospitals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A meta-synthesis of 17 studies reported a pooled sensitivity of 88% for the 4AT [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eLanguage Adaptation of the Scale\u003c/h2\u003e\u003cp\u003eThe Turkish adaptation of the 4AT delirium screening tool was conducted in accordance with the ISPOR guidelines for the cross-cultural adaptation of health-related measures [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A panel comprising two linguists whose native language was Turkish, three experienced academic nurses, and one psychiatrist was established for the translation. The initial translation was performed by two independent, native Turkish-speaking linguists, focusing on item validity, terminology consistency, and semantic accuracy. Subsequently, the research team reviewed and harmonised the translated version through panel discussions and reached a consensus. In the back-translation phase, two native Turkish-speaking linguists, who were unaware of the content of the original study, translated the Turkish 4AT version back to English. Semantic and conceptual differences were analysed by comparing them with the original 4AT. The researchers administered the preliminary Turkish version of the scale to 20 patients from the target population in a clinical setting. Each participant was asked to provide feedback regarding item clarity and comprehension. Based on the panel\u0026rsquo;s evaluation of the participant responses, no major issues were identified regarding item clarity, conceptual accuracy, or cultural relevance. Minor wording adjustments were made to improve readability. Overall, the tool was found to be comprehensible and feasible for use in routine clinical practice. Based on these outcomes, the final Turkish version of the 4AT Delirium Screening Scale was developed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eData Collection for the Research\u003c/h2\u003e\u003cp\u003e After hospital admission, informed consent was obtained from each participant during the preoperative phase of the study. Subsequently, the patients completed the demographic and clinical data forms. During hospitalisation, cognitive function was evaluated by a psychiatrist, and only individuals with normal cognitive function were included in the study. Following surgery, upon transfer to the post-anesthesia care unit (PACU), the presence of emergence delirium was evaluated using two standardized screening tools: the CAM-ICU and the 4AT Delirium Test. Additionally, an independent clinical evaluation was conducted by a psychiatrist blinded to the scores of both screening tools. The final diagnosis of delirium was made solely based on clinical criteria in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), through direct clinical observation without reference to any standardised screening tool scores (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eFigure 2 here\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis of the Data\u003c/h2\u003e\u003cp\u003eAll statistical analyses were conducted using IBM SPSS Statistics version 27.0 (IBM Corp., Armonk, NY, USA) with a 99% confidence level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Descriptive statistics (frequency, percentage, mean, and standard deviation) were used to summarise the demographic data. The normality of the continuous variables was assessed using the Shapiro-Wilk test. For normally distributed variables, independent-samples t-tests were used to examine group differences. The internal consistency of the adapted 4AT was assessed using the Kuder-Richardson Formula 20 (KR-20). Validity analyses included the calculation of item difficulty (via Heryson and Simple methods) and item discrimination indices. The diagnostic agreement between the adapted 4AT and reference tools (CAM-ICU and DSM-5) was evaluated using chi-square tests and agreement metrics. Additionally, ROC curve analysis was performed to determine the sensitivity, specificity, AUC, and optimal cut-off values for each diagnostic tool relative to the DSM-5 as the gold standard.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDescriptive Characteristics of the Study Sample\u003c/h2\u003e\u003cp\u003eIn total, 188 patients were included in this study. Among the participants, 43.62% (n\u0026thinsp;=\u0026thinsp;82) were men and 56.38% (n\u0026thinsp;=\u0026thinsp;106) were women. Regarding age distribution, 50.0% (n\u0026thinsp;=\u0026thinsp;94) of the patients were between 18 and 40 years, 38.3% (n\u0026thinsp;=\u0026thinsp;72) were between 41 and 65 years, and 11.7% (n\u0026thinsp;=\u0026thinsp;22) were aged 65 years or older. The mean age was 43.62\u0026thinsp;\u0026plusmn;\u0026thinsp;12.75 years (range, 18\u0026ndash;82 years). In terms of body mass index (BMI), 29.8% (n\u0026thinsp;=\u0026thinsp;56) of the patients had a BMI between 18.5\u0026ndash;24.9 kg/m\u0026sup2; (normal weight), 52.1% (n\u0026thinsp;=\u0026thinsp;98) between 25.0\u0026ndash;29.9 kg/m\u0026sup2; (overweight), and 18.1% (n\u0026thinsp;=\u0026thinsp;34) between 30.0\u0026ndash;34.9 kg/m\u0026sup2; (obese). The mean BMI was 27.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44 kg/m\u0026sup2; (range: 21.46\u0026ndash;33.12). The surgical duration ranged from 30 to 190 min, with a mean of 82.3\u0026thinsp;\u0026plusmn;\u0026thinsp;31.44 min. Of the patients, 66.0% (n\u0026thinsp;=\u0026thinsp;124) underwent surgery lasting between 30 and 90 min, while 34.0% (n\u0026thinsp;=\u0026thinsp;64) had procedures lasting 90\u0026ndash;190 min. The mean arterial pressure (MAP) ranged from 70 to 95 mmHg, with a mean value of 80.41\u0026thinsp;\u0026plusmn;\u0026thinsp;6.97. MAP values of 62.8% (n\u0026thinsp;=\u0026thinsp;118) of patients had MAP values between 70 and 85 mmHg, and those of 37.2% (n\u0026thinsp;=\u0026thinsp;70) were between 85 and 95 mmHg. The distribution of patients according to surgical departments was as follows: 9.57% (n\u0026thinsp;=\u0026thinsp;18) in neurosurgery, 31.91% (n\u0026thinsp;=\u0026thinsp;60) in general surgery, 12.77% (n\u0026thinsp;=\u0026thinsp;24) in gynaecology, 28.72% (n\u0026thinsp;=\u0026thinsp;54) in orthopaedics, and 17.02% (n\u0026thinsp;=\u0026thinsp;32) in urology. Regarding the type of anaesthesia, 68.09% (n\u0026thinsp;=\u0026thinsp;128) received general anaesthesia and 31.91% (n\u0026thinsp;=\u0026thinsp;60) underwent spinal anaesthesia. When assessing post-operative pain status, 70.21% (n\u0026thinsp;=\u0026thinsp;132) of the patients reported the presence of pain, whereas 29.79% (n\u0026thinsp;=\u0026thinsp;56) did not experience pain (Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eTable\u0026nbsp;1 HERE\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eItem Difficulty Analysis\u003c/h2\u003e\u003cp\u003eThe difficulty levels of the four items on the scale were evaluated using both the Heryson and Simple (Traditional) methods. According to the Heryson classification, Item 1 was classified as \u0026ldquo;Very Easy\u0026rdquo; (index: 0.936), while Items 2, 3, and 4 were all classified as \u0026ldquo;Easy\u0026rdquo;, with indices ranging from 0.729 to 0.771. When assessed with the Simple Method, Item 1 also remained in the \u0026ldquo;Very Easy\u0026rdquo; category (0.882), whereas Items 2\u0026ndash;4 were rated as \u0026ldquo;Easy\u0026rdquo; to \u0026ldquo;Moderate\u0026rdquo; based on their respective indices between 0.520 and 0.578. These results suggest that all items fell within acceptable difficulty ranges, with Item 1 being the easiest across both classification methods (Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eTable\u0026nbsp;2 HERE\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eItem Discrimination Analysis\u003c/h2\u003e\u003cp\u003eIn this study, item discrimination indices were calculated to evaluate the ability of the scale items to distinguish between individuals with high and low scores on the scale. Item 1 had a discrimination index of 0.235 and was classified as a \"marginal item\" ( 0.20\u0026ndash;0.29 range) according to accepted criteria. Therefore, the item was substantially revised in terms of content and clarity, based on expert opinions. The high internal consistency of the overall scale (KR-20\u0026thinsp;=\u0026thinsp;0.899) supported the inclusion of the revised item, and the retained item did not negatively affect the scale\u0026rsquo;s overall reliability. In contrast, items 2, 3, and 4 demonstrated excellent discrimination, with indices of 0.941, 0.961, and 0.843, respectively, and were retained in the scale without any modifications (Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eTable\u0026nbsp;3 HERE\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eCriterion Validity\u003c/h2\u003e\u003cp\u003eIn this study, the diagnostic agreement between the 4AT delirium screening tool and two widely validated reference tools, CAM-ICU and DSM-5, was evaluated in a sample of 188 patients. Diagnostic concordance was analysed using cross-tabulation and the chi-square test (χ\u0026sup2;), and agreement metrics were calculated based on classification consistency. Compared with the CAM-ICU, the 4AT tool showed a strong diagnostic alignment. Among patients classified as delirium-positive by 4AT (n\u0026thinsp;=\u0026thinsp;45, 23.4%), 43 (22.9%) were also positive according to CAM-ICU, resulting in an agreement rate of 98.4% and a statistically significant chi-square value (χ\u0026sup2; = 171.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, among the 143 patients identified as negative by the 4AT, 143 were also negative by the CAM-ICU. Comparison with the DSM-5, regarded as the gold standard for delirium diagnosis, revealed a similarly high concordance. Among patients identified as delirious by 4AT, 41 (21.8%) were also positive on DSM-5, while 144 (76.6%) of those who were 4AT-negative were confirmed to be negative on DSM-5. This yielded an agreement rate of 98.4%, with a chi-square value of χ\u0026sup2; = 171.6 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings collectively support the criterion validity of the 4AT, demonstrating that it achieves diagnostic outcomes that are highly consistent with those of established clinical tools. The use of Fisher\u0026rsquo;s Exact Test confirmed the statistical significance of these associations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in all comparisons).( (Table\u0026nbsp;4; Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eTable\u0026nbsp;4 HERE\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eFigure 1 here\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic Accuracy via ROC Analysis\u003c/h2\u003e\u003cp\u003eThe diagnostic performance of the 4AT delirium screening tool was evaluated in comparison with two established reference tools: CAM-ICU and DSM-5. Sensitivity, specificity, likelihood ratios, predictive values, area under the curve (AUC), and Youden Index were calculated for each tool based on ROC analysis. The 4AT demonstrated excellent diagnostic accuracy, with a sensitivity of 97.8% (95% CI: 93.5\u0026ndash;99.7) and specificity of 99.3% (95% CI: 97.1\u0026ndash;99.9) at a cutoff score of \u0026ge;\u0026thinsp;0.5. Its positive predictive value (PPV) was 97.6%, negative predictive value (NPV) was 99.4%, and AUC was 0.99. The Youden Index was 0.99, reflecting outstanding overall diagnostic capability. The CAM-ICU showed slightly lower sensitivity at 95.6% (90.1\u0026ndash;98.9) but high specificity of 98.6% (95.9\u0026ndash;99.8). At a cutoff score of \u0026ge;\u0026thinsp;0.5, the positive and negative likelihood ratios were 68.3 and 0.045, respectively. The PPV and NPV were 92.1% and 99.2%, respectively, and the AUC was 0.98. The corresponding chi-square p-value for the comparison was 0.001, indicating statistical significance. The DSM-5, used as the clinical reference standard, exhibited a sensitivity of 93.2% (87.1\u0026ndash;97.5) and a perfect specificity of 100% (98.9\u0026ndash;100). Although the LR\u0026thinsp;+\u0026thinsp;was not calculated, the LR\u0026thinsp;\u0026minus;\u0026thinsp;was 0.068, with a PPV of 100% and an NPV of 98.3%. The AUC was 0.96 and the Youden Index was 0.93, again with a statistically significant difference from 4AT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings reinforce the criterion validity of the 4AT scale by demonstrating near-perfect alignment with both a widely used clinical screening tool (CAM-ICU) and the diagnostic gold standard (DSM-5). (Table\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eTable\u0026nbsp;5 HERE\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicUnderline\" class=\"BoldItalicUnderline\" name=\"Emphasis\"\u003eFigure 3 here\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDelirium is a frequently encountered yet often overlooked post-operative complication [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Particularly among older adults, this condition can delay recovery, prolong hospitalisation, and increase the risk of additional health complications [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Prompt recognition of delirium in post-anaesthesia care units is critical, as it directly impacts patient safety and clinical outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, accurate and timely identification of delirium remains a clinical priority. The variability in reported delirium prevalence across studies is largely attributed to differences in diagnostic tools, highlighting the complexity of detecting this condition [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Within this context, the 4AT screening tool has emerged as a practical and reliable method for facilitating delirium detection [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This study was designed to evaluate the validity and reliability of the Turkish version of the 4AT, aiming to improve post-operative delirium detection in Turkish healthcare settings.\u003c/p\u003e\u003cp\u003eThe key finding of this study confirms that the Turkish version of the 4AT Delirium Screening Tool demonstrates strong psychometric properties. Comparative analyses revealed a high level of agreement between the 4AT and established instruments such as the CAM-ICU. In clinical diagnostics, sensitivity and specificity are essential parameters for evaluating a tool\u0026rsquo;s accuracy. A meta-analysis by Tieges et al. (2021) reported that the 4AT exhibits sensitivity and specificity rates of 88%. Similarly, Hendry et al. (2016) described the scale as a well-balanced tool with high sensitivity and adequate specificity. Other studies have also supported these findings, reinforcing the diagnostic reliability of the scale across diverse clinical populations. The ease of use and rapid administration of the 4AT make it particularly suitable for time-constrained clinical environments. In this study as well, sensitivity and specificity levels were found to be considerably high, reaffirming the tool\u0026rsquo;s appropriateness for rapid delirium assessment, especially among geriatric patients [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, the study demonstrated strong alignment between the Turkish version of the 4AT and DSM-5-based clinical evaluations, further supporting the adapted scale\u0026rsquo;s clinical accuracy. Given that DSM-5 assessments require detailed clinical examination and expertise, the 4AT offers a significant advantage by providing rapid preliminary screening. The observed consistency between 4AT outcomes and DSM-5 diagnoses reinforces the tool\u0026rsquo;s utility in clinical practice. Particularly in fast-paced environments (e.g., recovery rooms, intensive care units, emergency departments), the 4AT\u0026rsquo;s rapid screening capability can support timely clinical decision-making and improve patient outcomes.\u003c/p\u003e\u003cp\u003eThe study also demonstrated that the Turkish version of the 4AT has a high reliability coefficient, indicating that it produces consistent results across applications. According to the literature, reliability coefficients above 0.7 are considered acceptable for psychological and clinical instruments [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The coefficient obtained in this study exceeded this threshold, further validating the tool\u0026rsquo;s robustness. Previous research conducted in various cultural and clinical contexts has also confirmed the scale\u0026rsquo;s reliability [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], supporting its broader applicability for delirium screening in different healthcare settings.\u003c/p\u003e\u003cp\u003eNo statistically significant association was found between gender and the incidence of delirium. However, a significant relationship was observed between the surgical department where the operation was performed and the likelihood of developing delirium. Additionally, patients who experienced delirium were generally older, and age was positively correlated with delirium risk. These findings are consistent with those of Hasegawa (2021), who identified advanced age as a major contributing factor to delirium development [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus, age is an important predictor of risk assessment. Neither the type of anaesthesia (general or spinal) nor the duration of surgery significantly influenced the incidence of postoperative delirium. Based on these findings, both patient age and surgical specialty appear to be critical variables in evaluating the risk of delirium during post-operative care.\u003c/p\u003e\u003cp\u003eThe ROC analysis results provide compelling evidence of the high diagnostic performance of the Turkish version of the 4AT in detecting post-operative delirium. The tool demonstrated excellent sensitivity and specificity, confirming its capacity to accurately differentiate between patients with and without delirium. The elevated AUC value further reinforces the scale\u0026rsquo;s discriminative strength. These findings are consistent with international validation studies, which have repeatedly affirmed the diagnostic utility of the 4AT across diverse clinical settings [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe strong diagnostic concordance between the 4AT and DSM-5 criteria is especially noteworthy. Although DSM-5 remains the diagnostic gold standard for delirium, its application requires comprehensive clinical judgment and time. In contrast, the 4AT offers a rapid, user-friendly alternative that does not compromise diagnostic reliability. The observed alignment between 4AT and DSM-5 outcomes enhances the tool\u0026rsquo;s value in high-acuity settings such as PACUs, ICUs, and emergency departments [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], where rapid screening is essential for timely clinical interventio. However, it is important to note that this study focused solely on short-term diagnostic outcomes. Although the Turkish version of the 4AT demonstrated strong immediate diagnostic accuracy, future longitudinal studies are warranted to explore its predictive validity and utility in monitoring long-term post-operative cognitive outcomes..\u003c/p\u003e\u003cp\u003eIn conclusion, this study demonstrates that the Turkish version of the 4AT Delirium Screening Tool offers high diagnostic accuracy for the rapid and reliable identification of post-operative delirium. The tool's strong sensitivity and specificity values are consistent with findings reported in the international literature. Given its ease of administration and robust psychometric properties, the 4AT is recommended as an effective clinical instrument for early delirium screening, particularly among high-risk post-operative patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study aimed to comprehensively evaluate the validity and reliability of the Turkish adaptation of the 4AT Delirium Screening Tool and to determine its place in clinical practice. The findings indicate that the Turkish version of the 4AT is a highly valid and reliable instrument for delirium screening. When evaluating the psychometric properties of the scale, a high level of agreement (ranging from 87\u0026ndash;99%) was observed with established diagnostic criteria such as CAM-ICU, and DSM-5. These results demonstrate that the diagnostic accuracy of the 4AT is consistent with international literature. In particular, its short administration time (under two minutes) and simple structure provide practical advantages in busy clinical environments. Therefore, this study confirms that the Turkish version of the 4AT is a valid, reliable, and practical clinical tool for delirium screening. Especially suitable for use in post-anaesthesia care units and intensive care settings, this scale offers the potential for early diagnosis and intervention, thereby contributing to improved patient outcomes. However, further research involving larger samples across different patient populations and diverse clinical settings is necessary to evaluate the performance of the scale more comprehensively.\u003c/p\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eRecommendations\u003c/h2\u003e\u003cp\u003eThe adoption of the 4AT as a standard delirium screening tool is recommended for clinical settings where rapid assessment is essential, such as intensive care units, post-anaesthesia care units, and emergency departments. Although the Turkish version of the 4AT has demonstrated strong validity and reliability within the local patient population, further studies are warranted in broader surgical and medical cohorts. Expanding validation efforts would enhance the tool\u0026rsquo;s generalisability and support the timely detection of delirium across various clinical contexts. To improve accessibility and promote widespread utilisation, the development of digital health applications incorporating the 4AT is encouraged. A digital platform could provide healthcare professionals with immediate access to the tool, enabling more efficient screening and management of delirium. Additionally, large-scale implementation and testing of the 4AT across different geographic regions and healthcare institutions in Turkey are essential. Such efforts would allow for a more comprehensive evaluation of the tool\u0026rsquo;s psychometric performance in demographically and culturally diverse populations in the future.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has several limitations. Chief among them is that the research was conducted exclusively in a post-anaesthesia care unit, which limits the generalisability of the findings to other clinical settings or different patient populations. Moreover, the study focused solely on short-term outcomes, and thus, potential long-term effects or persistent complications associated with delirium were not within the scope of this research.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests:\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eİE: Contributed to the study design and methodology, coordinated the scale adaptation process, developed the data analysis strategy, conducted statistical analyses, organised and interpreted the results in tables, formatted the manuscript according to journal guidelines, and performed comparative evaluations with the literature. AK: Contributed to manuscript writing, English language editing, statistical analyses, presentation and interpretation of the results in tables and comparative evaluation with relevant literature. AY: Coordinated the scale adaptation process and supervised the study. MŞ was responsible for planning and conducting the data collection process. All authors actively contributed to all stages of the study and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to express their gratitude to the medical and nursing staff of the post-anesthesia care unit for their support and cooperation throughout the study. We also thank all the patients who participated in the research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu, J., Gao, S., Zhang, S. \u003cem\u003eet al.\u003c/em\u003e Perioperative risk factors for recovery room delirium after elective non-cardiovascular surgery under general anaesthesia. \u003cem\u003ePerioper Med\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 3 (2021). https://doi.org/10.1186/s13741-020-00174-0\u003c/li\u003e\n\u003cli\u003eSaller, T., MacLullich, A. M. J., Sch\u0026auml;fer, S. T., Crispin, A., Neitzert, R., Sch\u0026uuml;le, C., von Dossow, V., \u0026amp; Hofmann-Kiefer, K. F. (2019). Screening for delirium after surgery: validation of the 4 A\u0026apos;s test (4AT) in the post-anaesthesia care unit. Anaesthesia, 74(10), 1260\u0026ndash;1266. https://doi.org/10.1111/anae.14682\u003c/li\u003e\n\u003cli\u003eNeufeld, K. J., Leoutsakos, J. S., Sieber, F. E., Joshi, D., Wanamaker, B. 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Journal of anesthesia, 34(5), 675\u0026ndash;687. https://doi.org/10.1007/s00540-020-02805-8,\u003c/li\u003e\n\u003cli\u003eHuang, J., Qi, H., Lv, K., Chen, X., Zhuang, Y., \u0026amp; Yang, L. (2020). Emergence Delirium in Elderly Patients as a Potential Predictor of Subsequent Post-operative Delirium: A Descriptive Correlational Study. \u003cem\u003eJournal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(5), 478\u0026ndash;483. https://doi.org/10.1016/j.jopan.2019.11.009\u003c/li\u003e\n\u003cli\u003eAldecoa, C., Bettelli, G., Bilotta, F., Sanders, R. D., Audisio, R., Borozdina, A., Cherubini, A., Jones, C., Kehlet, H., MacLullich, A., Radtke, F., Riese, F., Slooter, A. J., Veyckemans, F., Kramer, S., Neuner, B., Weiss, B., \u0026amp; Spies, C. D. (2017). 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S., Sleigh, J., \u0026amp; Sanders, R. D. (2017). Post-anaesthesia care unit delirium: incidence, risk factors and associated adverse outcomes. British journal of anaesthesia, 119(2), 288\u0026ndash;290. https://doi.org/10.1093/bja/aex197\u003c/li\u003e\n\u003cli\u003eHasegawa, T., Seo, T., Kubota, Y., Sudo, T., Yokota, K., Miyazaki, N., Muranaka, A., Hirano, S., Yamauchi, A., Nagashima, K., Iyo, M., \u0026amp; Sakai, I. (2022). Reliability and validity of the Japanese version of the 4A\u0026apos;s Test for delirium screening in the elderly patient. Asian journal of psychiatry, 67, 102918. https://doi.org/10.1016/j.ajp.2021.102918\u003c/li\u003e\n\u003cli\u003eHendry, K., Quinn, T. J., Evans, J., Scortichini, V., Miller, H., Burns, J., Cunnington, A., \u0026amp; Stott, D. J. (2016). Evaluation of delirium screening tools in geriatric medical inpatients: a diagnostic test accuracy study. 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Statistical power analysis for the behavioral sciences. Academic Press; 2013. doi: https://doi.org/10.4324/9780203771587.\u003c/li\u003e\n\u003cli\u003eEly, E. W., Inouye, S. K., Bernard, G. R., Gordon, S., Francis, J., May, L., Truman, B., Speroff, T., Gautam, S., Margolin, R., Hart, R. P., \u0026amp; Dittus, R. (2001). Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA, 286(21), 2703\u0026ndash;2710. https://doi.org/10.1001/jama.286.21.2703\u003c/li\u003e\n\u003cli\u003eAypar, \u0026Uuml;., Kanbak, M., Yorgancı, K., \u0026Ouml;zdemir, H., Akıncı, S. B., \u0026Ccedil;elikcan, A. ve Rezaki, M. (2005). Yoğun Bakım \u0026Uuml;nitesinde Konf\u0026uuml;zyon Değerlendirme \u0026Ouml;l\u0026ccedil;eğinin ge\u0026ccedil;erlik g\u0026uuml;venilirlik \u0026ccedil;alışması. T\u0026uuml;rk Anesteziyoloji ve Reanimasyon Derneği Dergisi, 33(4), 333-341.\u003c/li\u003e\n\u003cli\u003eTieges, Z., Maclullich, A. M. J., Anand, A., Brookes, C., Cassarino, M., O\u0026apos;connor, M., Ryan, D., Saller, T., Arora, R. C., Chang, Y., Agarwal, K., Taffet, G., Quinn, T., Shenkin, S. D., \u0026amp; Galvin, R. (2021). Diagnostic accuracy of the 4AT for delirium detection in older adults: systematic review and meta-analysis. Age and ageing, 50(3), 733\u0026ndash;743. https://doi.org/10.1093/ageing/afaa224\u003c/li\u003e\n\u003cli\u003eWild, D., Grove, A., Martin, M., Eremenco, S., McElroy, S., Verjee-Lorenz, A., Erikson, P., \u0026amp; ISPOR Task Force for Translation and Cultural Adaptation (2005). Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures: report of the ISPOR Task Force for Translation and Cultural Adaptation. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 8(2), 94\u0026ndash;104. https://doi.org/10.1111/j.1524-4733.2005.04054.x\u003c/li\u003e\n\u003cli\u003eWu, J., Zhang, T., He, J., \u0026amp; Zhang, Q. (2024). Association between nutritional status and post-operative delirium in elderly surgical patients. Current Topics in Nutraceutical Research, 22, 760-764. https://doi.org/10.37290/ctnr2641-452x.22:760-764\u003c/li\u003e\n\u003cli\u003eHou, L., Zhang, Q., Cao, L., Chen, M., Wang, Q., Li, Y., Li, S., Ge, L., \u0026amp; Yang, K. (2023). Diagnostic accuracy of the 4AT for delirium: A systematic review and meta-analysis. \u003cem\u003eAsian journal of psychiatry\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e, 103374. https://doi.org/10.1016/j.ajp.2022.103374\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;ZDAMAR, Kazım (2016). \u0026Ouml;l\u0026ccedil;ek ve Test Geliştirme-Yapısal Eşitlik Modellemesi, Eskişehir: Nisan Kitabevi.\u003c/li\u003e\n\u003cli\u003eKuladee, S., \u0026amp; Prachason, T. (2016). Development and validation of the Thai version of the 4 \u0026apos;A\u0026apos;s Test for delirium screening in hospitalized elderly patients with acute medical illnesses. Neuropsychiatric disease and treatment, 12, 437\u0026ndash;443. https://doi.org/10.2147/NDT.S97228\u003c/li\u003e\n\u003cli\u003eDelgado-Parada, E., Morillo-Cuadrado, D., Saiz-Ruiz, J., Cebollada-Gracia, A., Ayuso-Mateos, J. L., \u0026amp; Cruz-Jentoft, A. J. (2022). Diagnostic accuracy of the Spanish version of the 4AT scale (4AT-ES) for delirium screening in older inpatients. The European Journal of Psychiatry, 36(3), 182-190. https://doi.org/10.1016/j.ejpsy.2022.01.003\u003c/li\u003e\n\u003cli\u003eArnold, E., Lugton, J., Spiller, J., \u0026amp; Finucane, A. (2025). What are the experiences and support needs of district nurses caring for terminally ill people with delirium at home? A qualitative study. BMC palliative care, 24(1), 60. https://doi.org/10.1186/s12904-024-01627-9\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Distribution of Patients\u0026apos; Demographic Characteristics (N=188)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"563\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82 (43.62)\u003c/p\u003e\n \u003cp\u003e106 (56.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e18-40\u003c/p\u003e\n \u003cp\u003e41-65\u003c/p\u003e\n \u003cp\u003e65 and over\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e94 (%50.0)\u003c/p\u003e\n \u003cp\u003e72 (%38.3)\u003c/p\u003e\n \u003cp\u003e22 (%11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e18.5 - 24.9\u003c/p\u003e\n \u003cp\u003e25.0 - 29.9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30.0 - 34.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56 (%29.8)\u003c/p\u003e\n \u003cp\u003e98 (%52.1)\u003c/p\u003e\n \u003cp\u003e34 (%18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery Duration (mins)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e30-90\u003c/p\u003e\n \u003cp\u003e90-190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e124 (%66.0)\u003c/p\u003e\n \u003cp\u003e64 (%34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAP Value\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e70-85\u003c/p\u003e\n \u003cp\u003e85-95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e118 (%62.8)\u003c/p\u003e\n \u003cp\u003e70 (%37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery Department\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNeurosurgery\u003c/p\u003e\n \u003cp\u003eGeneral Surgery\u003c/p\u003e\n \u003cp\u003eGynaecology\u003c/p\u003e\n \u003cp\u003eOrthopaedics\u003c/p\u003e\n \u003cp\u003eUrology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (9.57)\u003c/p\u003e\n \u003cp\u003e60 (31.91)\u003c/p\u003e\n \u003cp\u003e24 (12.77)\u003c/p\u003e\n \u003cp\u003e54 (28.72)\u003c/p\u003e\n \u003cp\u003e32 (17.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of Anaesthesia\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003cp\u003eSpinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e128 (68.09)\u003c/p\u003e\n \u003cp\u003e60 (31.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePain Status\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e132 (70.21)\u003c/p\u003e\n \u003cp\u003e56 (29.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin.-Max.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e18-82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e43.62\u0026plusmn;12.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e21.46-33.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e27.07\u0026plusmn;2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery Duration (mins)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e30-190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e82.3\u0026plusmn;31.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAP Value (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e70-95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e80.41\u0026plusmn;6.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 563px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI:\u003c/strong\u003e Body Mass Index; MAP: Mean Arterial Pressure; \u003cstrong\u003eSD:\u003c/strong\u003e\u0026nbsp; Standard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Item Difficulty Index Results (N=188)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem Difficulty Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeryson Method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple Method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eVery Easy/Very Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eVery Easy/Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eVery Easy/Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eVery Easy/Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 629px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClassification Methods for Item Difficulty Index\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHeryson Method Classification\u003c/strong\u003e:0.90: Very Easy. 0.70-0.89: Easy. 0.30-0.69: Moderate. \u0026lt;0.30: Difficult\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSimple Method (Traditional) Classification:\u003c/strong\u003e \u0026gt;0.80: Very Easy. 0.60-0.79: Easy. 0.40-0.59: Moderate. \u0026lt;0.40: Difficult\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Item Discrimination Index Results (N=188)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiscrimination Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 363px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation \u0026amp; Action\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 363px;\"\u003e\n \u003cp\u003eMarginal Item / Requires Substantial Revision\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 363px;\"\u003e\n \u003cp\u003eExcellent Item / Retain Without Modification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 363px;\"\u003e\n \u003cp\u003eExcellent Item / Retain Without Modification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 363px;\"\u003e\n \u003cp\u003eExcellent Item / Retain Without Modification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 629px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation Guidelines:\u003c/strong\u003e \u0026ge;0.40: Excellent Item. 0.30\u0026ndash;0.39: Good Item. 0.20\u0026ndash;0.29: Marginal Item\u0026lt;0.20: Poor Item\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Comparison of Diagnostic Concordance Between 4AT and CAM-ICU, NU-DESC, and DSM-5 (N=188)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelirium\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 AT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAM-ICU\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgreement Metric (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;/p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e(23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e43(22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 139px;\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 111px;\"\u003e\n \u003cp\u003e171.8\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003eNegative\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e143(76.6%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e2 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e143 (76.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 AT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDSM-V\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgreement Metric (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;/p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePositive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e44 (23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e41\u0026nbsp;(21.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 139px;\"\u003e\n \u003cp\u003e98.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 111px;\"\u003e\n \u003cp\u003e171.6\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003eNegative\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e144 (76.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e3 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e144 (76.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 632px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4AT:\u0026nbsp;\u003c/strong\u003eDelirium screening tool. \u003cstrong\u003eCAM-ICU:\u0026nbsp;\u003c/strong\u003eConfusion Assessment Method for the Intensive Care Unit. \u003cstrong\u003eNU-DESC:\u0026nbsp;\u003c/strong\u003eNursing Delirium Screening Scale. \u003cstrong\u003eDSM-5:\u0026nbsp;\u003c/strong\u003eDiagnostic and Statistical Manual of Mental Disorders. 5th Edition. \u003cstrong\u003e\u0026chi;\u0026sup2;=\u003c/strong\u003e Fisher\u0026rsquo;s Exact Test Chi-square test. \u003cstrong\u003eAgreement Metric (Success Rate):\u0026nbsp;\u003c/strong\u003eThis represents the percentage of consistent results between the 4AT scale and other tools.\u0026nbsp;p\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Comparative Diagnostic Performance of 4at Delirium Screening Tools (N=188)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"746\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOptimal Cut-Off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLR+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLR-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4AT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e97.8% (93.5-99.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e99.3% (97.1-99.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026ge; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e139.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e97.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e99.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAM-ICU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e95.6% (90.1-98.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e98.6% (95.9-99.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026ge; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e68.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e92.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e99.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDSM-5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e93.2% (87.1-97.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e100% (98.9-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026ge; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e98.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 746px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAM-ICU:\u003c/strong\u003e Confusion Assessment Method for Intensive Care Unit. \u003cstrong\u003eDSM-5\u003c/strong\u003e=Diagnostic and Statistical Manual of Mental Disorders-5. \u003cstrong\u003eCI\u003c/strong\u003e= Confidence Interval. \u003cstrong\u003eLR+\u003c/strong\u003e=Positive Likelihood Ratio. \u003cstrong\u003eLR-\u003c/strong\u003e=Negative Likelihood Ratio. \u0026nbsp;\u003cstrong\u003ePPV\u003c/strong\u003e=Positive Predictive Value. \u003cstrong\u003eNPV=\u003c/strong\u003eNegative Predictive Value. \u003cstrong\u003eAUC=\u003c/strong\u003eArea Under ROC Curve.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic Accuracy Categories:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity=\u003c/strong\u003e Excellent: \u0026gt;90%. Acceptable: 80-90%. Poor: \u0026lt;80%; \u003cstrong\u003eSpecificity=\u003c/strong\u003eExcellent: \u0026gt;95%. Acceptable: 90-95%. Poor: \u0026lt;90%; \u003cstrong\u003eLR+=\u003c/strong\u003e Excellent: \u0026gt;10. Acceptable: 5-10. Poor: \u0026lt;5; \u003cstrong\u003eLR-=\u003c/strong\u003e Excellent: \u0026lt;0.1. Acceptable: 0.1-0.2. Poor: \u0026gt;0.2. p\u003cstrong\u003e:\u003c/strong\u003e Fisher\u0026rsquo;s Exact Test (for proportions). \u003cstrong\u003e\u0026Delta; sens (Difference\u003c/strong\u003e): 4AT\u0026apos;s metric minus comparison tool\u0026apos;s metric.\u0026nbsp;Optimal Cut-Off:\u0026nbsp;\u0026ge; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Delirium, Post-operative Care, Reliability, Screening Tool, Validity","lastPublishedDoi":"10.21203/rs.3.rs-6623222/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6623222/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the psychometric properties, specifically the validity and reliability, of the Turkish version of the 4AT Delirium Screening Tool.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis methodological study was conducted in the post-anaesthesia care unit of a public hospital between 1 April and 30 June 2023 with ethics committee approval (2023/025). Data were collected from 188 patients using a demographic form and delirium assessment tools, including the 4AT, CAM-ICU, and DSM-5 criteria. Analyses were performed using SPSS version 27.0. The internal consistency of the 4AT was assessed using KR-20, and its validity was examined using chi-square and ROC analyses. The significance level was set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 4AT demonstrated strong diagnostic agreement with the CAM-ICU (98.4%) and DSM-5 (98.4%) criteria. Its internal consistency was high (KR-20 = 0.899). In terms of diagnostic performance, the 4AT showed 97.8% sensitivity and 99.3% specificity, with an ROC analysis showing that the 4AT had a high discriminative ability to detect delirium, with an AUC of 0.981.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings indicate that the Turkish version of the 4AT is a valid, reliable, and practical tool for the rapid detection of post-operative delirium in clinical settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Registration:\u003c/strong\u003e NCT06187389\u003c/p\u003e","manuscriptTitle":"Turkish Adaptation of the 4AT Delirium Screening Scale: A Validity and Reliability Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 10:34:45","doi":"10.21203/rs.3.rs-6623222/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-07-31T21:36:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-28T20:54:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-25T09:52:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-23T12:01:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41724100327338232887202969489469633092","date":"2025-07-22T21:04:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90106115739280195371833015657637926653","date":"2025-07-21T14:02:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T09:21:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-18T15:50:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-18T07:46:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73597281242995936647504043843046971148","date":"2025-07-16T08:24:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172636537143077190660456246832225605580","date":"2025-07-16T05:24:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167327759541336575305007936501658311224","date":"2025-07-15T10:28:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265512697312178273548076435895973012532","date":"2025-07-13T07:21:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99419826376674330566458157856776969122","date":"2025-07-09T06:42:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-09T06:20:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-14T15:07:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-14T05:13:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-14T05:11:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2025-05-08T19:35:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33eedbd1-0879-490f-baad-efd1a60bdef5","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-01T18:33:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 10:34:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6623222","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6623222","identity":"rs-6623222","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}