Multilevel Hierarchical Model Research Articles

Extending the Transformational Leadership-Innovative Work Behavior Relationship: Integrating Climate for Innovation and Dissimilarities in Dyad Relational Demography

This study assessed a multilevel mediation of transformational leadership, climate for innovation, and innovative work behavior (IWB). It employed relational demography variables, which included employee-supervisor sex, age, and tenure dissimilarities, as moderators. Employees and their direct supervisors from 37 organizations (service and manufacturing) were involved in the study. The analysis used 458 dyad samples. The SPSS Macro for assessing multilevel mediation (MLMed) and Hierarchical Linear Modeling (HLM) statistical tools were employed to examine the proposed hypotheses. A positive influence of transformational leadership on IWB was found. Climate for innovation mediated the relationship between transformational leadership and IWB. Age and tenure dissimilarities, along with climate for innovation, had positive joint effects on IWB. Sex dissimilarity and climate for innovation also had a positive, albeit weaker, joint effect on IWB. The study enriches the literature by (1) describing the mediating role of climate for innovation between transformational leadership and IWB and (2) disclosing the moderating roles of demographic dissimilarities between employees and supervisors in the relationship between climate for innovation and IWB. Research limitations and suggestions for future research are also addressed.

Disentangling the effects of intermittent faecal shedding and imperfect test sensitivity on the microscopy-based detection of gut parasites in stool samples.

Gut-parasite transmission often involves faecal shedding, and detecting parasites in stool samples remains the cornerstone of diagnosis. However, not all samples drawn from infected hosts contain parasites (because of intermittent shedding), and no test can detect the target parasites in 100% of parasite-bearing samples (because of imperfect sensitivity). Disentangling the effects of intermittent shedding and imperfect sensitivity on pathogen detection would help us better understand transmission dynamics, disease epidemiology, and diagnostic-test performance. Using paediatric Giardia infections as a case-study, here we illustrate a hierarchical-modelling approach to separately estimating the probabilities of host-level infection (Ψ); stool-sample-level shedding, given infection (θ); and test-level detection, given infection and shedding (p). We collected 1-3 stool samples, in consecutive weeks, from 276 children. Samples (413 overall) were independently examined, via standard sedimentation/optical microscopy, by a senior parasitologist and a junior, trained student (826 tests overall). Using replicate test results and multilevel hierarchical models, we estimated per-sample Giardia shedding probability at [Formula: see text] and observer-specific test sensitivities at [Formula: see text] and [Formula: see text]. Gender-specific infection-frequency estimates were [Formula: see text] and [Formula: see text]. Had we used a (hypothetical) Perfect Test with 100% narrow-sense sensitivity (pPT = 1.0), the average probability of detecting Giardia in a sample drawn from an infected child (Ψ = 1.0) would have been Pr(d|i,PT) = Ψ×θ×pPT≈1.0×0.44×1.0≈0.44. Because no test can be >100% sensitive, Pr(d|i) (which measures clinical sensitivity) can only be brought above ~ 0.44 by tinkering with the availability of Giardia in stool samples (i.e., θ); for example, drawing-and-pooling 3 replicate samples would yield [Formula: see text]. By allowing separate estimation (and modelling) of pathogen-shedding probabilities, the approach we illustrate provides a means to study pathogen transmission cycles and dynamics in unprecedented detail. Separate estimation (and modelling) of true test sensitivity, moreover, may cast new light on the performance of diagnostic tests and procedures, whether novel or routine-practice.

The impact of institutional autonomy on higher education institutions in Europe

Abstract This paper aims to evaluate the effect of institutional autonomy on higher education institutions (HEIs). The research question is whether increasing institutional autonomy leads to HEIs fulfilling three major missions with greater success. This study utilizes multiple sets of regression models, including multilevel hierarchical models, combining data from four sources for European HEIs, which includes variables on a state and institutional level. The three sets of regression models each estimate the effect of HEIs’ autonomy on their success in one of their missions. Although results indicate a good model fit, the effects of increasing HEI autonomy on the mission objectives appear mostly minor and even, in some cases, negative and therefore contradictory to the autonomy literature. A possible theoretical explanation question whether recent developments actually create additional autonomy or only shift autonomy among HEI actors without quantitative impact. A methodological explanation aims to stimulate further improvements and standardization of measurements.

Temporal trends in the utilization, costs, and outcomes of concomitant left atrial appendage closure across a statewide collaborative

ObjectiveWith the rising incidence of atrial fibrillation, left atrial appendage closure (LAAC) at the time of cardiac surgery remains an important adjunct. The present study characterized trends, associated resource utilization, and potential disparities in the use of left atrial appendage exclusion. MethodsUsing a Society of Thoracic Surgeons regional academic collaborative database, we queried all adult patients undergoing coronary and valve procedures with concomitant LAAC between 2015 and 2021. Trends in LAAC, as well as the technique for closure, were evaluated. Multilevel hierarchical logistic modeling was applied to delineate factors associated with LAAC, accounting for patient and operative characteristics. Generalized linear models were developed to perform risk-adjusted incremental cost analysis. ResultsOf the 8699 patients who met the study criteria, 1377 underwent left atrial appendage closure. Over the study period, the annual rate of LAAC increased from 16.7% to 30.8% (P < .001). LAAC patients were older, but less commonly insulin-dependent diabetics or on dialysis. Female sex, redo, and urgent operative status had lower risk-adjusted odds of LAAC. Although LAAC was associated with longer bypass time, there was no significant association with 30-day mortality or 30-day readmission. LAAC was associated with an incremental increase in adjusted costs by $10,602 (95% confidence interval, $4078-$17,126). ConclusionsRates of LAAC are increasing but less common among female patients, as well as those requiring urgent/emergent interventions. LAAC did not significantly impact short-term mortality. Our results suggest that LAAC may be a high-value intervention among patient populations that have the greatest potential to derive its benefits.

Risk Evaluation for Human Factors of Flight Dispatcher Based on the Hesitant Fuzzy TOPSIS-DEMATEL-ISM Approach: A Case Study in Sichuan Airlines

To effectively mitigate unsafe events and accident symptoms stemming from flight dispatchers’ human factors, this paper proposes a novel risk evaluation model to accurately identify and evaluate potential human risks associated with flight dispatchers. First, the HFACS (Human Factors Analysis and Classification System, HFACS) model is employed to construct a human risk assessment indicator system for flight dispatchers. Second, the hesitant fuzzy set is introduced to represent the uncertainty during experts’ evaluation, and the improved TOPSIS (Technique for Order Preference by Similarity to Ideal Solution, TOPSIS) method is applied within a hesitant fuzzy environment to obtain rankings of human factors. Third, the hesitant fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory, DEMATEL)-ISM (Interpretive Structural Modeling, ISM) approach is constructed to analyze the correlation among human factors, leading to the establishment of a multi-level hierarchical structure model. Finally, a case study of risk assessment for human factors of flight dispatchers in Sichuan Airlines is conducted to demonstrate the effectiveness of the proposed method. The results revealed the flight dispatchers’ human factors associated with higher risks and identified the key factors with a larger impact on other factors in Sichuan Airlines. Subsequently, a multi-level hierarchical structure model comprising five layers is developed to investigate the internal correlations among human factors, facilitating the formulation of targeted improvement suggestions for the higher risk indicators and key influencing factors.

Cross-National Trends in Adolescents Psychological and Somatic Complaints Before and After the Onset of COVID-19 Pandemic

PurposeBuilding on research suggesting that the COVID-19 pandemic may have led to an exacerbation of deteriorating trends in mental health among adolescents, this paper examined trends in adolescents' psychological and somatic complaints across 35 countries from 2010 to 2022, and tested trends in sociodemographic inequalities in these outcomes between 2018 and 2022. MethodsUsing data from 792,606 adolescents from 35 countries (51% girls; mean age = 13.5; standard deviation 1.6) across four Health Behaviour in School-aged Children surveys (2010, 2014, 2018, 2022), hierarchical multilevel models estimated cross-national trends in adolescent psychological and somatic complaints. We tested whether observed values in 2022 were in line with predicted values based on 2010–2018 linear trends. Finally, moderation effects of age, family affluence, and family structures on the outcomes were tested (2018–2022). ResultsBoth girls and boys showed substantially higher levels of psychological complaints in 2022 compared with the predicted values. For somatic complaints, higher levels than predicted in 2022 were observed only in girls. Moderation analyses revealed an increase from 2018 to 2022 in age gaps and a narrowing in the socioeconomic gap for both outcomes. Also, there was a widening gap between adolescents living with 2 parents and those living in a single parent household in 2022 compared to 2018. DiscussionCross-national increases in adolescent psychological and somatic complaints were higher than expected in 2022, based on previous trends. Magnitudes of change varied across different sociodemographics groups, with implications for pre-existing mental health inequalities.

Investigating the determinants of user adoption behavior in the context of conflicting health information: a DEMATEL-ISM model approach

PurposeThe purpose of this paper is to investigate the factors influencing user adoption behavior in the context of conflicting health information, thereby contributing to the understanding of users' information decision-making and adoption processes within intricate information environments. Furthermore, this research endeavors to offer guidance for mitigating the adverse effects of contradictory health information on users' cognitive perceptions.Design/methodology/approachFirst, this study used literature coding to identify factors that influence user adoption behavior in the context of conflicting health information. Secondly, we utilized the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to unveil the key influencing factors based on centrality and causality. Lastly, utilizing the Interpretive Structural Model (ISM), we constructed the multilevel hierarchical structure model of influencing factors to delineate the relationships among factors across different levels.FindingsThe key causal factors influencing user adoption behavior in the context of conflicting health information include user basic characteristics, experience accumulation, and information type. The key result factors consist of psychological emotion, perceived trade-offs, and the source credibility. The significant elements include users' psychological emotions, perceived trade-offs, emotional support, source credibility, and informational support. Furthermore, user adoption behavior in the context of conflicting health information is a manifestation of the interplay among surface-level, mid-level, and deep-level factors.Research limitations/implicationsTheoretically, this paper enriches the existing relevant theoretical framework and offers a novel perspective for further investigation into user adoption behavior concerning conflicting health information. Practically, this study extracts factors that can influence user adoption behavior in the context of conflicting health information which is an essential reference value for guiding and optimizing user adoption behavior.Originality/valueThis paper expands the system of factors influencing user adoption behavior in the context of conflicting health information from individual, information and social perspectives. Utilizing DEMATEL quantitative analysis and ISM multilevel hierarchical models, this research examines and illustrates the significance of the influencing factors and their interrelationships.

Absenteeism and Achievement in Early Elementary Grades: A Multilevel Organizational Analysis

This paper presents empirical analyses illustrating the organizational relationship between chronic absenteeism and student achievement as estimated via a contextual model of school-level and student-level relationships. We conduct a series of descriptive analyses and multilevel hierarchical models (HLM) in which absenteeism is used to predict variation in student achievement for nearly 50,000 individual students in grades K-3 in 109 elementary schools in Delaware during the 2014–2015 through 2017–2019 school years. Results demonstrate that chronic absenteeism tends to be clustered in a subset of schools, and that the adverse contextual effects of absenteeism at the school level are many times larger than the negative effects at the individual level. Implications for education policy and interventions are discussed.

The model for optimizing cutting parameters for processing products on metal-cutting machines

The paper discusses the issues of multi-criteria optimization of the process of manufacturing products on metal-cutting machines. The efficiency of the optimization process directly depends on its level of detail and the optimal set of targets and control parameters. The change in the structure and properties of a product during its manufacture can be represent-ed in the form of a hierarchical model based on the decomposition of the original goal, which must be achieved through the comprehensive optimization of individual elements of the process. Described herein is a multi-level hierarchical model for optimizing a machining process comprising five levels of control. The following control levels are identified: Technological Process, Processing Stage, Technological Operation, Process Transition, Work Stroke. For each structural element of the model, control parameters, specific optimization criteria are defined, and vector optimiza-tion criteria are formed. The practical implementation of the control model is presented on the example of optimization of the target indicators of the technologi-cal process of the ”Roller” product. Graph of change of object states in process of its manufacturing is pre-sented, optimal values of target indicators and cutting parameters are determined.

Escalation of Human Resource Quality in National Health Resilience Through Estimating Multilevel Model Parameters with the Restricted Maximum Likelihood Approach to The 2019 UTBK Average

Multilevel modeling or Hierarchical Linear Modeling (HLM) is a statistical approach specifically used to analyze data with a two-level structure. This approach allows an understanding of the contribution of factors at both the individual and group levels to the response variable. One method commonly used in HLM is Restricted Maximum Likelihood (REML). REML is a parameter estimation method that is often applied in statistical models, especially linear models that incorporate random components. This allows more efficient parameter assessment compared to conventional estimation methods. In this research, multilevel model parameter estimation analysis was carried out using the limited maximum likelihood approach. The aim is to determine the multilevel linear regression model on the average UTBK score for health cluster study programs in 2019. This involves selecting the optimal node point based on the minimum Generalized Cross Validation (GCV) and identifying the factors that influence it. Predictor variables considered include interest and capacity of study programs at university level (Level-1), as well as the average UNBK and HDI scores at provincial level (Level-2). The findings of this research indicate that the most appropriate multilevel regression model is formed with three nodes with a minimum GCV value at Level-1 of 864.6593 and at Level-2 of 3.1816. At Level-1, the influencing factor is the interest variable and at Level-2 is the average provincial UNBK score in 2019 and the Human Development Index (HDI).

Research on the design of growable solid wood children’s beds

To meet children’s needs for beds at different stages of growth, a product design model integrating the KANO Model, the Hierarchical Analysis Method, and Axiomatic Design (KANO-AHP-AD) was adopted to conduct a design study on the growability of solid wood children’s beds. In accordance with the KANO model, the demands for children’s beds coming from questionnaires among families with children were classified and sorted, and the demand indicators were then summarized. Secondly, AHP was introduced to establish a multilevel hierarchical model, construct a judgment matrix of design elements, and calculate the weights of these elements to improve the accuracy of users’ demand weights. Then, AD was used to complete the mapping of the demand domain, function domain, and design domain of children’s beds and to judge their reasonableness through the matrix. Such a design allows users to evaluate and verify the rationality of the program. Through modular design techniques, the growability requirements were fulfilled. A low number of product modules were freely combined to form product types with multiple functions to meet customers’ needs for personalization and functional diversification. The work has value for the design of growable children’s beds, thus contributing to sustainable development and environmental protection causes.

Aerodynamic shape optimization at low Reynolds number using multi-level hierarchical Kriging models

Aerodynamic shape optimization at low Reynolds number using multi-level hierarchical Kriging models

Assessing the effect of concerns about contraceptive-induced fertility impairment on hormonal contraceptive use by parity and residence: evidence from PMA Ethiopia 2020 cross-sectional survey

ObjectivesThis study aims to describe patterns of beliefs about contraceptive-induced infertility and assess their relationship with current contraceptive use, including whether these relationships vary by parity and residence.DesignWe use data...

Multilevel Hierarchical Bayesian Modeling of Cross-National Factors in Vehicle Sales

SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers. Recognising the complex interplay between geographical and economic conditions across countries, we delve into cross-national factors that significantly influence SUV sales. This article presents an analysis of the global sales of SUVs (sport utility vehicles) using multilevel hierarchical Bayesian modelling. We identify key predictors of SUV sales, including the effects of fuel prices, income levels and geographical aspects. We prepared four statistical models that differ in their probability distribution or hierarchical internal structure. The last presented model, with Student’s t-distribution and separate distribution for unique alpha parameter values, turned out to be the best one. Our analysis contributes to a deeper understanding of the automotive market dynamics, and it can also assist manufacturers and policymakers in designing effective sales strategies.

Short-term outcomes of asphyxiated neonates depending on requirement for transfer in the first 24 h of life

ImportanceIn neonates with birth asphyxia (BA) and hypoxic-ischemic encephalopathy, therapeutic hypothermia (TH), initiated within six hours, is the only safe and established neuroprotective measure to prevent secondary brain injury. Infants born outside of TH centers have delayed access to cooling. ObjectiveTo compare in-hospital mortality, occurrence of seizures, and functional status at discharge in newborns with BA depending on postnatal transfer for treatment to another hospital within 24 h of admission (transferred (TN) versus non-transferred neonates (NTN)). DesignNationwide retrospective cohort study from a comprehensive hospital dataset using codes of the International Classification of Diseases, 10th modification (ICD-10). Clinical and outcome information was retrieved from diagnostic and procedural codes. Hierarchical multilevel logistic regression modeling was performed to quantify the effect of being postnatally transferred on target outcomes. SettingAll discharges from German hospitals from 2016 to 2021. ParticipantsFull term neonates with birth asphyxia (ICD-10 code: P21) admitted to a pediatric department on their first day of life. ExposuresPostnatal transfer to a pediatric department within 24 h of admission to an external hospital. Main outcomesIn-hospital death; secondary outcomes: seizures and pediatric complex chronic conditions category (PCCC) ≥ 2. ResultsOf 11,703,800 pediatric cases, 25,914 fulfilled the inclusion criteria. TNs had higher proportions of organ dysfunction, TH, organ replacement therapies, and neurological sequelae in spite of slightly lower proportions of maternal risk factors. In TNs, the adjusted odds ratios (OR) for death, seizures, and PCCC ≥ 2 were 4.08 ((95% confidence interval 3.41–4.89), 2.99 (2.65–3.38), and 1.76 (1.52–2.05), respectively. A subgroup analysis among infants receiving TH (n = 3,283) found less pronounced adjusted ORs for death (1.67 (1.29–2.17)) and seizures (1.26 (1.07–1.48)) and inverse effects for PCCC ≥ 2 (0.81 (0.64–1.02)) in TNs. Conclusion and relevanceThis comprehensive nationwide study found increased odds for adverse outcomes in neonates with BA who were transferred to another facility within 24 h of hospital admission. Closely linking obstetrical units to a pediatric department and balancing geographical coverage of different levels of care facilities might help to minimize risks for postnatal emergency transfer and optimize perinatal care.

Corruption spills over on citizens: The case of self‐reported motivation to cheat on tax

AbstractCorruption poses a significant threat to societies’ social and economic fabric, eroding trust and contractual relationships between governments and citizens. This study investigates the repercussions of corruption spillover on individuals and explores how they adjust their motivation to engage in tax cheating by exploiting two distinct types of corruption heterogeneities at both individual and national levels. Leveraging newly collected individual corruption experiences locally from the World Value Survey alongside national‐level corruption data from Transparency International, we employ multilevel hierarchical modeling to estimate the effects of corruption on individual tax behavior. Our findings reveal that corruption negatively impacts people's willingness to comply with tax laws, with individuals who have personally experienced corruption exhibiting a more pronounced erosion of tax morale compared to those who have not. By shedding light on the intricate dynamics of corruption's influence on tax compliance, this paper contributes to our understanding of the broader implications of corruption for people and society. This paper can also inform policymakers and stakeholders in designing targeted interventions to mitigate the adverse consequences of corruption and restore citizens’ trust in their government.

Impact of Local Tailoring on Acute Stroke Care in 21 Disparate Emergency Departments: A Prospective Stepped Wedge Type III Hybrid Effectiveness-Implementation Study.

Faster delivery of tPA (tissue-type plasminogen activator) results in better health outcomes for eligible patients with stroke. Standardization of stroke protocols in emergency departments (EDs) has been difficult, especially in nonstroke centers. We measured the effectiveness of a centrally led implementation strategy with local site tailoring to sustain adherence to an acute stroke protocol to improve door-to-needle (DTN) times across disparate EDs in a multihospital health system. Prospective, type III hybrid effectiveness-implementation cohort study measuring performance at 21 EDs in Utah and Idaho (stroke centers [4]/nonstroke centers [17]) from January 2018 to February 2020 using a nonrandomized stepped-wedge design, monthly repeated site measures and multilevel hierarchical modeling. Each site received the implementation strategies in 1 of 6 steps providing control and intervention data. Co-primary outcomes were percentage of DTN times ≤60 minutes and median DTN time. Secondary outcomes included percentage of door-to-activation of neurological consult times ≤10 minutes and clinical effectiveness outcomes. Results were stratified between stroke and nonstroke centers. A total of 855 474 ED patient encounters occurred with 5325 code stroke activations (median age, 69 [IQR, 56-79] years; 51.8% female patients]. Percentage of door-to-activation times ≤10 minutes increased from 47.5% to 59.9% (adjusted odds ratio, 1.93 [95% CI, 1.40-2.67]). A total of 615 patients received tPA of ≤3 hours from symptom onset (median age, 71 [IQR, 58-80] years; 49.6% female patients). The percentage of DTN times ≤60 minutes increased from 72.5% to 86.1% (adjusted odds ratio, 3.38, [95% CI, 1.47-7.78]; stroke centers (77.4%-90.0%); nonstroke centers [59.3%-72.1%]). Median DTN time declined from 46 to 38 minutes (adjusted median difference, -9.68 [95% CI, -17.17 to -2.20]; stroke centers [41-35 minutes]; nonstroke centers [55-52 minutes]). No differences were observed in clinical effectiveness outcomes. A centrally led implementation strategy with local site tailoring led to faster delivery of tPA across disparate EDs in a multihospital system with no change in clinical effectiveness outcomes including rates of complication. Disparities in performance persisted between stroke and nonstroke centers.

Factors associated with health professionals’ stress reactions, job satisfaction, intention to leave and health-related outcomes in acute care, rehabilitation and psychiatric hospitals, nursing homes and home care organisations

The aim of this study is to identify (1) the extent of work-related stress and (2) stressors associated with cognitive and behavioral stress reactions, burnout symptoms, health status, quality of sleep, job satisfaction, and intention to leave the organization and the profession among health professionals working in acute care /rehabilitation hospitals, psychiatric hospitals, nursing homes, and home care organizations.BackgroundHealth professionals are faced with various stressors at work and as a consequence are leaving their profession prematurely. This study aimed to identify the extent of work-related stress and stressors associated with stress reactions, job satisfaction, and intention to leave and health-related outcomes among health professionals working in different healthcare sectors (acute care, rehabilitation and psychiatric hospitals, nursing homes and home care organizations).MethodsThis study is based on a repeated cross-sectional design, which includes three data measures between 2017 and 2020 and 19,340 participating health professionals from 26 acute care / rehabilitation hospitals, 12 psychiatric hospitals, 86 nursing homes and 41 home care organizations in Switzerland. For data analysis, hierarchical multilevel models (using AIC) were calculated separately for hospitals, nursing homes, and home care organizations, regarding health professionals’ stress symptoms, job satisfaction, intention to leave the organization / profession, general health status, burnout symptoms, and quality of sleep.ResultsThe main findings reveal that the incompatibility of health professionals’ work and private life was significantly associated (p < 0.05) with their stress reactions, job satisfaction, intention to leave, and health-related outcomes in all the included work areas. The direct supervisor’s good leadership qualities were also associated with health professionals’ job satisfaction regarding all work areas (B ≥ 0.22, p = 0.000). In addition, a positive perceived bond with the organization (B ≥ 0.13, p < 0.01) and better development opportunities (B ≥ 0.05, p < 0.05) were associated with higher job satisfaction and a lower intention to leave the organization and profession among health professionals. Also, a younger age of health professionals was associated with a higher intention to leave the organization and the profession prematurely in all the included work areas. High physical (B ≥ 0.04, p < 0.05) and quantitative demands (B ≥ 0.05, p = 0.000) at work were also associated with negative health-related outcomes.

Multi-fidelity expected improvement based on multi-level hierarchical kriging model for efficient aerodynamic design optimization

To reduce the computational burden of aerodynamic design optimization, a multi-fidelity expected improvement (MFEI) method is developed, based on the error analysis of a multi-level hierarchical kriging (MHK) model for accelerating optimization convergence. By maximizing the MFEI function, a new sample of arbitrary fidelity level is determined to ameliorate the accuracy of the MHK model, and convergence to the high-fidelity optimum is ensured. The proposed optimization method based on MFEI and MHK is demonstrated by two analytical function cases and verified by two aerodynamic design optimizations: drag minimizations of an RAE2822 aerofoil and an ONERA M6 wing in transonic flows. It is shown that the MFEI method tends to infill more gainful samples of lower fidelities during optimization, so fewer highest-fidelity samples are required. This confirms that the proposed method can obtain optimal results within a limited computational budget and is more efficient than the existing single-fidelity or two-fidelity methods.

Postoperative Outcomes Associated with the Timing of Surgery After SARS-CoV-2 Infection.

Examine the association between prior SARS-CoV-2 infection, interval from infection to surgery, and adverse surgical outcomes. Earlier series have reported worse outcomes for surgery after COVID-19 illness, and these findings have led to routinely deferring surgery seven weeks after infection. We created a retrospective cohort of patients from the US Veterans Health Administration facilities nationwide, April 2020 to September 2022, undergoing surgical procedures. Primary outcomes were 90-day all-cause mortality and 30-day complications. Within surgical procedure groupings, SARS-CoV-2 infected and uninfected patients were matched in a 1:4 ratio. We categorized patients by 2-week intervals from SARS-CoV-2 positive test to surgery. Hierarchical multilevel multivariable logistic regression models were used to estimate the association between infection to surgery interval versus no infection and primary end points. We identified 82,815 veterans undergoing eligible operations (33% general, 27% orthopedic, 13% urologic, 9% vascular), of whom 16,563 (20%) had laboratory-confirmed SARS-CoV-2 infection before surgery. The multivariable models demonstrated an association between prior SARS-CoV-2 infection and increased 90-day mortality (odds ratio (OR) 1.42, 95% CI: 1.08, 1.86) and complications (OR 1.32, 95% CI: 1.11, 1.57) only for patients having surgery within 14 days of infection. ASA-stratified multivariable models showed that the associations between increased 90-day mortality (OR 1.40, 95% CI: 1.12, 1.75) and complications (OR 1.73, 95% CI: 1.34, 2.24) for patients having surgery within 14 days of infection were confined to those with ASA 4-5. In a contemporary surgical cohort, patients with prior SARS-CoV-2 infection only had increased postoperative mortality or complications when they had surgery within 14 days after the positive test. These findings support revising timing recommendations between surgery and prior SARS-CoV-2 infection.