Positive Predictive Power Research Articles

Social Support and Expectancy as Predictors of Licensure Examination Success Among Professional Teachers

This study aimed to determine the Licensure Examination for Teachers (LET) profile, the Level of Social Support and Expectancy and their relationships and identify the dimensions that predict LET Success Rating. This quantitative study utilized descriptive-correlational design among LET Passers and Licensed Professional Teachers produced by the University of Mindanao from 2019–2023. 303 LPTs composed of 109 Elementary and 194 Secondary teachers selected via convenience and snowball sampling responded to the virtual survey. The collected data were analyzed using mean, standard deviation, spearman correlations, and multiple regressions. Results revealed that 87% of the LPTs were top-performing and had high social support and expectancy levels during their LET preparation. The correlation between social support and the LET Success Rating is positive but very weak. Likewise, the correlation between expectancy and LET Success Rating is positive but very weak. Moreover, social support predicts the LET Success Rating by 1.9%; expectancy predicts it by 0.4%. Furthermore, support from Friends and/or classmates has moderate and positive correlations and has a strong positive predictive power with LET Success Rating.

Economic policy uncertainty in OFDI host countries and the cross-section of stock returns

This study examines the association between foreign economic policy uncertainty (FEPU) originating from the host countries (regions) of outward foreign direct investment (OFDI) and expected stock returns. We construct a novel variable, FEPU, based on the year-end OFDI amounts of Chinese listed multinational enterprises (MNEs) and the EPU indices of 23 host countries (regions). Our findings reveal that stocks with higher FEPU outperform those with lower FEPU by 4.96 % annually. Beyond predicting short-term expected returns, FEPU also exhibits strong positive predictive power for firms’ long-term cumulative returns. Additionally, through mechanism tests, we demonstrate that this excess return is attributable to compensation for risk premium. Unlike the majority of studies that focus solely on the impact of EPU within a single country or region, we examine the cross-border implications of EPU. This approach offers an innovative perspective on the pricing of MNEs’ stocks by characterizing the exposure to external EPU.

An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.

Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise to improve BC diagnosis and subtype differentiation. In this case, novel quantitative computational methods, such as radiomics, have been developed to enhance the sensitivity and specificity of early BC diagnosis and classification. The potential of radiomics in improving the diagnostic efficacy of imaging studies has been shown in several studies. In this review article, we discuss the radiomics workflow and current handcrafted radiomics methods in the diagnosis and classification of BC based on the most recent studies on different imaging modalities, e.g., MRI, mammography, contrast-enhanced spectral mammography (CESM), ultrasound imaging, and digital breast tumosynthesis (DBT). We also discuss current challenges and potential strategies to improve the specificity and sensitivity of radiomics in breast cancer to help achieve a higher level of BC classification and diagnosis in the clinical setting. The growing field of AI incorporation with imaging information has opened a great opportunity to provide a higher level of care for BC patients.

B - 90 Establishing Cutoffs for Impaired Cognition in Virtual Reality Assessment: the Virtual Kitchen Protocol for Learning and Memory

Abstract Objective The Virtual Kitchen Protocol for Learning and Memory (VKP-LM) is a virtual-reality-based measure of everyday functioning through procedural memory tasks. Previous literature has introduced the VKP-LM and begun validation processes. This study explores cutoff scores to determine cognitive impairment across the Immediate (VKP-IR) and Delayed-Recall (VKP-DR) portions of the VKP-LM. Method Adults (N = 126; Mage = 70.29; 56.3% Female) completed the VKP-LM as a part of a neuropsychological evaluation in a community-based assessment center. Participants were categorized binarily as to whether they received a neurocognitive disorder (NCD) diagnosis. Discriminatory abilities and cutoffs were determined by the Receiver Operator Curve’s (ROC) Area Under the Curve (AUC) and sensitivity-specificity charts. Classification tables determined the Positive Predictive Power (PPP) and Negative Predictive Power (NPP) given the established cutoffs. Results ROC analysis showed the VKP-IR (Max = 70; Cutoff = 28) to have good discriminatory abilities (AUC = 0.788) and the VKP-DR (Max = 70; Cutoff = 26;) to have excellent discriminatory abilities (AUC = 0.855). The classification tables showed that the VKP-IR had a PPP = 63.0% and NPP = 87.9%, while the VKP-DR had a PPP = 86.4% and NPP = 90.4%. Conclusion Due to the multifaceted nature of diagnosing NCDs, single-domain measures (i.e., procedural memory) will always struggle to obtain excellent PPP, as not all NCDs have amnestic cognitive profiles (e.g., cerebral vascular, Lewy body disease, etc.). Further research should explore comparing discriminatory abilities against other measures, increasing the sample size (both groups), and comparing discriminatory abilities among only NCDs with amnestic cognitive profiles, such as Alzheimer’s disease.

Comparison of the Validity of the PRE-DELIRIC model and the E-PRE-DELIRIC model for Predicting Delirium in patients after Cardiac Surgery

Purpose: The purpose of this study was to analyze the validity of the PRE-DELIRIC model and E-PRE-DELIRIC model.Methods: Patients who underwent cardiac surgery at a tertiary hospital between January 2019 and December 2022 were included. The presence or absence of delirium was determined based on risk groups, and the sensitivity, specificity, positive predictive power, and negative predictive power were verified using the Youden index. Receiver operating characteristic curves were derived for the PRE-DELIRIC model and E-PRE-DELIRIC model, the area under the curve was calculated, and the 95% confidence interval (CI) was presented.Results: The incidence of delirium was 28.8%. The average scores of the PRE-DELIRIC model and E-PRE-DELIRIC model were 49.72±29.91 and 18.14±0.41, respectively. In the PRE-DELIRIC model, for which a cut-off point of 14.05 was established using the Youden index, the sensitivity, specificity, positive predictive power, and negative predictive power were 64.8%, 83.2%, 61.0%, and 85.4%, respectively. In the E-PRE-DELIRIC model, with a cut-off point of 64.01, the corresponding indicators were 73.1%, 51.5%, 37.8%, and 82.6%, respectively. The areas under the curve for the PRE-DELIRIC model and the E-PRE-DELIRIC model were 0.77 (95% CI, 0.74~0.82) and 0.65 (95% CI, 0.61~0.69), respectively.Conclusion: It may be helpful to use both the E-PRE-DELIRIC and PRE-DELIRIC models. The two prediction models are expected to help improve the quality of nursing for the early detection and prevention of delirium, enabling intensive observations and interventions for patients at high risk of delirium.

Screening adolescent transgender-related distress: Gender preoccupation and stability questionnaire demonstrates excellent criterion validity with multi-disciplinary, pediatric gender specialist assessment

Objective To assess the psychometric properties of a gender-related distress questionnaire in adolescents questioning or experiencing gender incongruence and/or gender dysphoria, aged under 18 years, with multi-disciplinary, specialist pediatric gender assessment. Design & Setting : Prospective cohort study at state-wide tertiary children’s hospital gender clinic (2017–2021). Participants N = 299, aged 11–17 years referred for support with gender identity. Main outcome measure: The Gender Preoccupation and Stability Questionnaire (GPSQ) was designed for adults to assess gender dysphoria and intervention suitability. This study examined the psychometric properties of the GPSQ in an adolescent population and screening utility against the criterion of specialist assessment of gender dysphoria in a pediatric gender service. Results GPSQ demonstrated a univariate construct ‘gender dysphoria’ (α = 0.77) via factor analysis. It moderately correlated with outdated gender measure GIDYQ-AA (r = −0.31, p < .001) and strongly predicted specialist assessment outcomes (99% positive predictive power). However, negative predictive power or false negatives were high at 27%. Conclusions GPSQ is a reliable, valid tool for Australian adolescents under 18 years of age with excellent positive predictive power with a specialist pediatric gender dysphoria assessment. Caution is needed due to a high false-negative rate. General practitioners, pediatricians, psychiatrists, mental health professionals, school nurses and youth workers may benefit from the use of a reliable screening tool for gender-related distress to inform primary care planning, referrals, mental health formulation, psycho-education and conversations with young people and their parents. This is the first study to establish a reliable and valid screening tool for gender related distress in Australian minors with utility across all genders and criterion validity against multi-disciplinary, pediatric gender clinic assessment.

Perceived formative assessment practices in homework and creativity competence: The mediating effects of self-confidence in learning and intrinsic motivation

The aim of this study was to explore the impact mechanism of teachers' formative assessment on students' creativity competence. Herein, structural equation modeling (SEM) was utilized to investigate the potential mediating role of self-confidence in learning and intrinsic motivation based on large-scale longitudinal tracking data. The results indicate that, after controlling for pretests of creativity competence, socioeconomic status (SES), and gender, it was found that formative assessment practices have a direct and positive predictive power for creativity competence (the direct effect accounts for 39.4 %). Furthermore, formative assessment practices indirectly and positively predict creativity competence through the mediation of self-confidence in learning (the indirect effect accounts for 10.0 %) and intrinsic motivation (the indirect effect accounts for 50.6 %). We conclude that the main contribution from formative assessment to creativity may be in building an environment that fosters self-confidence in learning and intrinsic motivation.

Natural antibodies targeting LPS in pleural effusions of various etiologies.

Respiratory infection, cancer, and heart failure can cause abnormal accumulation of fluid in the pleural cavity. The immune responses within the cavity are orchestrated by leucocytes that reside in the serosal-associated lymphoid tissue. Natural antibodies (NAbs) are abundant in the serum (S) having a major role in systemic and mucosal immunity; however, their occurrence in pleural fluid (PF) remains an open question. Our aim herein was to detect and measure the levels of NAbs (IgM, IgG, IgA) targeting lipopolysaccharides (LPS) in both the pleural fluid and the serum of 78 patients with pleural effusions (PEs) of various etiologies. The values of anti-LPS NAb activity were extracted through a normalization step regarding the total IgM, IgG, and IgA levels, all determined by in-house ELISA. In addition, the ratios of PF/S values were analyzed further with other critical biochemical parameters from pleural fluids. Anti-LPS NAbs of all Ig classes were detected in most of the samples, while a significant increase of anti-LPS activity was observed in infectious and noninfectious compared with malignant PEs. Multivariate linear regression confirmed a negative correlation of IgM and IgA anti-LPS PF/S ratio with malignancy. Moreover, anti-LPS NAbs PF/S measurements led to increased positive and negative predictive power in ROC curves generated for the discrimination between benign and malignant PEs. Our results highlight the role of anti-LPS NAbs in the pleural cavity and demonstrate the potential translational impact that should be further explored.NEW & NOTEWORTHY Here we describe the detection and quantification of natural antibodies (NAbs) in the human pleural cavity. We show for the first time that IgM, IgG, and IgA anti-LPS natural antibodies are detected and measured in pleural effusions of infectious, noninfectious, and malignant etiologies and provide clinical correlates to demonstrate the translational impact of our findings.

The Predictive Power of Bosniak 3 and 4 Cystic Renal Lesion Categorization Using Contrast-Enhanced Ultrasound.

Contrast-enhanced ultrasound (CEUS) is increasingly utilized for the noninvasive assessment of renal cystic lesions, using the Bosniak grading system. Bosniak 3-4 lesions require surgical referral, which allows correlation with the histopathological outcome. In this single-center, retrospective study we evaluated renal CEUS exams conducted with SonoVue® with a diagnosis of a Bosniak 3 or 4 lesion between 2019 and 2022. A total of 49 patients and 50 lesions met the inclusion criteria, 31 lesions had available histopathological results. Patient demographics, cyst morphology, and dominant imaging features were registered. The histopathological diagnosis was considered a reference standard. Positive predictive power (PPV) for neoplastic lesions was comparable in the Bosniak 3 and 4 categories (75 vs 93.3%, P = .33), while PPV for histopathologically malignant lesion was considerably higher in the latter group (25 vs 93.33%, P = .0002). None of the lesions which had vividly enhancing thin septa as their dominant CEUS feature were malignant. Oncocytoma, multilocular cystic renal neoplasm of low malignant potential, and cystic nephroma were the major benign entities among Bosniak 3 lesions. Localized cystic kidney disease and hemorrhagic cysts were found to be the primary mimickers leading to false positive imaging findings. CEUS has a high predictive power for malignancy in the Bosniak 4 category, which is not maintained in the Bosniak 3 group due to the large proportion of benign lesions. Adherence to rigorous rule-in criteria and active surveillance strategies need to be considered for equivocal CEUS Bosniak 3 lesions.

Relationships among Willingness to Communicate, Self-Perceived Communication Competence and Communication Anxiety

This study investigated the relationships among L2 communicative willingness (WTC), self-perceived communicative competence (SPCC), and communication anxiety (CA) of English as a foreign language (EFL) learners in northwestern China. 71 English majors participated in the study and 10 of them also took part in the structured interview. The results indicated that: (1) SPCC had a positive correlation with WTC and negative correlation with CA while CA showed a negative relationship with WTC and SPCC; (2) SPCC held a positive predictive power on WTC. Both qualitative and quantitative results of the study showed that students with high SPCC also had strong WTC and low CA. Students with high CA had relatively low WTC and SPCC. Based on the current findings, some practical implications about enhancing EFL learners’ willingness to communicate were discussed.

Manager sentiment, deal characteristics, and takeover performance

Various studies analyze the driving forces behind takeover activities, including investor sentiment, liquidity, and fundamental shocks. In this study, we examine how manager sentiment influences takeover characteristics and long-term performance using textual analysis of data in 10-K and 10-Q filings. Our findings identify that manager sentiment has strong positive predictive power for takeover activities, and high (positive) manager sentiment decreases the long-term performance of takeover deals. Moreover, we show that high-sentiment managers tend to undertake large deals, decrease all-stock transactions, acquire hard-to-value targets, and provide high target valuations, suggesting over-investment for underperforming high-sentiment deals.

Serum concentrations of proinflammatory biomarker interleukin-6 (IL-6) as a predictor of postoperative complications after elective colorectal surgery

BackgroundThe aim of this prospective study was to evaluate the role of serum IL-6 as a potential predictive biomarker of postoperative complications (POC) in elective colorectal surgery.MethodA total of 115 patients underwent colorectal surgery for malignancy. IL-6 was measured on the first and third postoperative days (POD1, POD3), and C-reactive protein (CRP) was measured on the POD3. POC was analysed in subgroups according to Clavien‒Dindo (CD), antibiotic (ATB) treatment, intensive care unit (ICU) and hospital length of stay. The predictive power of variables for evaluated endpoints was analysed using receiver-operating characteristic (ROC) analysis and described by area under the curve (AUC). ROC analysis was adopted for the identification of optimal cut-offs. Histological analysis was performed to verify IL-6 production by the tumour.ResultsOut of 115 patients who were analysed, 42% had POC. Patients with POC had significantly higher serum levels of IL-6 on POD1 (p < 0.001) and POD3 (p < 0.001). IL-6 early on POD1 as a predictor of antibiotic treatment, ICU stay and hospital stay (AUC 0.818; 0.811; 0.771) did not significantly differ from the AUC of CRP late on POD3 (0.879; 0.838, 0.752). A cut-off IL-6 value of 113 pg/ml on POD1 and 180.5 pg/ml on POD3 in severe complications (CD > 3a) resulted in 75% and 72% sensitivity, 78.6% and 99% specificity, negative predictive value 96.4% and 97% and positive predictive value 29% and 88.9%.ConclusionThe serum level of interleukin-6 can predict severe (CD > 3a) POC early on POD1. On POD3, IL-6 is superior to CRP in terms of high positive predictive power of severe POC. Interestingly, the advantage of IL-6 on POD1 is early prediction of the need for antibiotic treatment, ICU stay and hospital stay, which is comparable to the CRP serum level late on the third POD.

Efficient classification of kidney disease detection using Heterogeneous Modified Artificial Neural Network and Fruit Fly Optimization Algorithm

Chronic kidney disease (CKD), a significant issue for public health, affects millions of individuals globally. The course of end-stage renal disease must be stopped or reversed, hence it is crucial to find chronic kidney disease early in order to receive therapy. Prediction of CKD is a second source of treatment, as machine learning techniques, with their high classification accuracy, are becoming increasingly significant in medical diagnosis. To learn about CKD and associated issues in this situation, deep learning is used. The sole inputs used to construct the three distinct types of models were the retinal fundus image alone (test model), the covariate only (the reference model), and the retinal fundus image plus covariate (hybrid model). To maintain the accuracy of contemporary classification systems, feature selection techniques must be applied correctly in order to reduce data size. Here, recommend the Fruit fly optimisation algorithm (FFOA) and the heterogeneous artificial neural network (HMANN) in this paper for efficient disease categorization. An Internet of Medical Things (IoMT) platform is presented for the early detection, segmentation, and diagnosis of chronic renal failure using a heterogeneous modified artificial neural network (HMANN). The Multilayer Perceptron (MLP) and Support Vector Machine (SVM) algorithms are used to classify the suggested HMANN. The ideal feature is chosen using an FFOA from a large pool of candidate features. The proposed method uses ultrasound pictures as its foundation and, as a first step in processing, slices a region of interest in the kidney in the ultrasound image. The accuracy, sensitivity, specificity, positive predictive power, negative predictive power, false positive rate, and false negative rate of the suggested CKD classification system were all taken into consideration when evaluating its performance.

The impact of emotional intelligence on operational effectiveness: The mediating role of organizational citizenship behavior and leadership.

This article examines the influence of emotional intelligence on organizational citizenship behavior and transformational and transactional leadership, and the impact of these dimensions on operational effectiveness. The analysis was based on 180 valid questionnaires from organizations in Colombia's manufacturing sector of the Valle del Cauca region. The variables were analyzed using structural equation modeling to identify the relationships among the studied constructs. The results suggest that emotional intelligence positively affects organizational citizenship behavior. Nevertheless, emotional intelligence does not impact transformational leadership and only partially affects transactional leadership and operational effectiveness. Emotional intelligence has a strong and positive impact on operational effectiveness when mediated by organizational citizenship behavior, which does have a strong and positive predictive power on operational effectiveness. Hence, in the search for competitive advantage, leaders should seek to improve operational effectiveness by focusing on developing emotional intelligence and organizational citizenship behaviour skills. Interestingly, of the two leadership styles examined in this study, only transactional leadership impacts operational effectiveness, which is inconsistent with the current literature and indicates a need for further leadership training. The value of this paper lies in discerning the current capabilities and strategies that individuals in an organization must address for proper transactional and transformational leadership. However, before operational effectiveness and a sustainable competitive advantage can be achieved, the role of leaders should be managed through the appropriate application of the concepts of emotional intelligence and organizational leadership behavior.

Multiple large shareholders, blockholder trading and stock price crash risk

AbstractWe show that in a setting with a strong concern for controlling shareholder entrenchment, firms with multiple large shareholders (MLS) are more likely to experience stock price crashes. As a result, when anticipating future revelations of bad news concerning corporate misconduct on information disclosure, large shareholders can exploit their information advantage and initiate their sales ex ante as far as eight quarters ahead. The positive association between MLS and crashes is more pronounced in the presence of noncontrolling shareholders' sales. Also, the positive predictive power of MLS on crash risk is more potent in firms with weak internal or external governance.

OLD-TAVR score to predict 2-year mortality in patients aged 75years and more undergoing transcatheter aortic valve replacement.

Decision-making on transcatheter aortic valve replacement (TAVR) in patients aged 75years and older is complex. It could be facilitated by the identification of predictors of long-term mortality. This study aimed to identify predictors of 2-year mortality to develop a 2-year mortality risk score. Cohort study of consecutive patients aged ≥ 75years who underwent TAVR after a comprehensive geriatric assessment (CGA) at our university hospital between 2012 and 2019. Predictors of 2-year mortality were determined using multivariable Cox regression. A point-based predictive model was developed based on risk factors and subsequently internally validated by fivefold cross-validation. The 345 patients (median age 87years, 54% women) were fit/vulnerable (32%), mildly frail (37%), or moderately/severely frail (31%). The overall 2-year mortality rate was 26%, predicted by atrial fibrillation, hemoglobin ≤ 10g/dL, age ≥ 87years, BMI ≤ 24, eGFR ≤ 50ml/min, and moderate/severe frailty. The risk score (range 0-12), named OLD-TAVR score, for 2-year mortality showed good discriminative power (AUC 0.70) and remained consistent after fivefold cross-validation (cvAUC 0.69). A risk score ≥ 8 (prevalence 20%) predicted a 45% (95%CI: 34-58%) two-year mortality, with high specificity (86%) and good positive predictive power (+ LR2.43). A 2-year mortality risk score (OLD-TAVR score) for very old patients undergoing TAVR was developed based on six bio-clinical items. A score ≥ 8 identified patients in whom 2-year mortality was very high and thereby the TAVR futile. Study protocol B403, 26/09/2022, retrospectively registered.

Building-Level Detection Threshold of SARS-CoV-2 in Wastewater.

We established wastewater surveillance of SARS-CoV-2 in a small, residential, urban college as part of an integrated public health response during the COVID-19 pandemic. Students returned to campus in spring 2021. During the semester, students were required to perform nasal PCR tests twice weekly. At the same time, wastewater monitoring was established in 3 campus dormitory buildings. Two were dedicated dormitories with populations of 188 and 138 students; 1 was an isolation building where students were moved within 2 h of receiving positive test results. Analysis of wastewater from isolation indicated that the amount of viral shedding was highly variable and that viral concentration could not be used to estimate the number of cases at the building level. However, rapid movement of students to isolation enabled determination of predictive power, specificity, and sensitivity from instances in which generally one positive case at a time occurred in a building. Our assay yields effective results with an ~60% positive predictive power, ~90% negative predictive power, and ~90% specificity. Sensitivity, however, is low at ~40%. Detection is improved in the few instances of 2 simultaneous positive cases, with sensitivity of 1 case versus 2 cases increasing from ~20% to 100%. We also measured the appearance of a variant of concern on campus and noted a similarity in timeline with increased prevalence in surrounding New York City. Monitoring SARS-CoV-2 in the sewage outflow of individual buildings can be used with a realistic goal of containing outbreak clusters but not necessarily single cases. IMPORTANCE Diagnostic testing of sewage can detect levels of circulating viruses to help inform public health. Wastewater-based epidemiology has been particularly active during the COVID-19 pandemic to measure the prevalence of SARS-CoV-2. Understanding the technical limitations of diagnostic testing for individual buildings would help inform future surveillance programs. We report our diagnostic and clinical data monitoring of buildings on a college campus in New York City during the spring 2021 semester. Frequent nasal testing, mitigation measures, and public health protocols provided a context in which to study the effectiveness of wastewater-based epidemiology. Our efforts could not consistently detect individual positive COVID-19 cases, but sensitivity is significantly improved in detecting two simultaneous cases. We therefore contend that wastewater surveillance may be more practically suited for the mitigation of outbreak clusters.

Machine-Learning Approach for Risk Estimation and Risk Prediction of the Effect of Climate on Bovine Respiratory Disease

Bovine respiratory disease (BRD) is a major cause of illness and death in cattle; however, its global extent and distribution remain unclear. As climate change continues to impact the environment, it is important to understand the environmental factors contributing to BRD’s emergence and re-emergence. In this study, we used machine-learning models and remotely sensed climate data at 2.5 min (21 km2) resolution environmental layers to estimate the risk of BRD and predict its potential future distribution. We analysed 13,431 BRD cases from 1727 cities worldwide between 2005 and 2021 using two machine-learning models, maximum entropy (MaxEnt) and Boosted Regression Trees (BRT), to predict the risk and geographical distribution of the risk of BRD globally with varying model parameters. Different re-sampling regimes were used to visualise and measure various sources of uncertainty and prediction performance. The best-fitting model was assessed based on the area under the receiver operator curve (AUC-ROC), positive predictive power and Cohen’s Kappa. We found that BRT had better predictive power compared with MaxEnt. Our findings showed that favourable habitats for BRD occurrence were associated with the mean annual temperature, precipitation of the coldest quarter, mean diurnal range and minimum temperature of the coldest month. Similarly, we showed that the risk of BRD is not limited to the currently known suitable regions of Europe and west and central Africa but extends to other areas, such as Russia, China and Australia. This study highlights the need for global surveillance and early detection systems to prevent the spread of disease across borders. The findings also underscore the importance of bio-security surveillance and livestock sector interventions, such as policy-making and farmer education, to address the impact of climate change on animal diseases and prevent emergencies and the spread of BRD to new areas.

Examining the Impact of Marketing Motives and Concerns on User Satisfaction and Re-Purchase Intentions in a Sharing Economy

In a fast-growing global economy, there is much debate in the socio-economic models about the sharing economy, which is a digital platform that benefits society and improves people’s quality of life. A significant benchmark of the sharing economy is that it enables individuals to monetize their assets that need to be used fully. This highlights an individual’s ability and perhaps their preference to either rent or borrow goods rather than own them. This study investigated Saudi Arabian students’ User Satisfaction (US) and their Re-Purchase Intentions (RPI) in the context of the sharing economy. We employed a deductive approach that utilized cross-sectional data collected through online sampling. The results were derived from 324 acceptable completed questionnaires. We used a Structural Equation Model (SEM) to confirm the positive and significant predictive power of Trust, Economic Benefits (EBs), Sharing Economy Philosophy (SEP), Service Quality and Net Benefits (NBs) on US and RPI. The results also demonstrated a positive and significant effect of concerns such as Lack of Trust (LoT) and Expected Effort (EE) on US. Finally, among Saudi Arabian students, US is a positive and significant predictor of RPI. In the context of a developing country such as Saudi Arabia, this study’s insights to the practical and theoretical spheres contribute to operational management and the literature about online digital learning.

The study on designed gamified mobile learning model to assess students’ learning outcome of accounting education

This study constructs an innovative course for accounting teaching based on a student-centered strategy. The curriculum is designed through the effective teaching module (BOPPPS) to assist students to understand accounting knowledge. A game-based mobile learning environment is created by developing an accounting mobile game and combining it with a mobile learning system (TronClass). The private technology university students had been selected by purposive sampling. A total of 81 accounting majored students, among them, 41 students are in the experimental group, and the rest were in the control group. The quasi-experimental design was to be applied in curriculum development. Meanwhile, quantitative data were collected by questionnaires and the qualitative data were collected through interviews. The result shows that game-based mobile learning can be beneficial to teaching effectiveness. And the regression model supports that information quality and service quality have positive predictive power on use intention. In addition, use intention and user satisfaction impacted learning engagement positively. Further, user satisfaction has a mediating effect. Finally, some suggestions are put forward to provide references for accounting educators and researchers.