Factors Influencing Adoption of Online Payment via E-Commerce Platforms

In this study, the research group applied the Technology Acceptance Model (TAM) by Davis (1989) to analyze factors influencing customers’ intention to use the online payment via e-commerce platforms as well as to encourage Vietnamese consumers to adapt this means of payment. Besides Perceived Ease of Use and Perceived Usefulness in the original model of Davis (1989), three additional dependent factors (Subjective Norm, Trust, Risk) were added to the model. The new model proposed by the research group aims to give a more well-rounded explanation on Vietnamese consumers’ attitude and intention towards the online payment. Using sample data including 448 consumers in the Northern region of Vietnam, the research group has been able to validate the hypothesis model and prove that independent and dependent variables (Attitude towards Use and Intention to Use) are positively correlated. Among the 5 dependent variables, Subjective Norm is found to be the most significant factor contributing to promote online payment attitude and intention through e-commerce websites of Vietnamese consumers. Keywords: TAM, online payment, online shopping, e-commerce DOI: 10.7176/EJBM/13-8-19 Publication date: April 30th 202

How to check a simulation study

Simulation studies are powerful tools in epidemiology and biostatistics, but they can be hard to conduct successfully. Sometimes unexpected results are obtained. We offer advice on how to check a simulation study when this occurs, and how to design and conduct the study to give results that are easier to check. Simulation studies should be designed to include some settings in which answers are already known. They should be coded in stages, with data-generating mechanisms checked before simulated data are analysed. Results should be explored carefully, with scatterplots of standard error estimates against point estimates surprisingly powerful tools. Failed estimation and outlying estimates should be identified and dealt with by changing data-generating mechanisms or coding realistic hybrid analysis procedures. Finally, we give a series of ideas that have been useful to us in the past for checking unexpected results. Following our advice may help to prevent errors and to improve the quality of published simulation studies

Ethnic Differences in the Prevalence of Type 2 Diabetes Diagnoses in the UK: Cross-Sectional Analysis of the Health Improvement Network Primary Care Database.

AIMS/HYPOTHESIS: Type 2 diabetes mellitus is associated with high levels of disease burden, including increased mortality risk and significant long-term morbidity. The prevalence of diabetes differs substantially among ethnic groups. We examined the prevalence of type 2 diabetes diagnoses in the UK primary care setting. METHODS: We analysed data from 404,318 individuals in The Health Improvement Network database, aged 0-99 years and permanently registered with general practices in London. The association between ethnicity and the prevalence of type 2 diabetes diagnoses in 2013 was estimated using a logistic regression model, adjusting for effect of age group, sex, and social deprivation. A multiple imputation approach utilising population-level information about ethnicity from the UK census was used for imputing missing data. RESULTS: Compared with those of White ethnicity (5.04%, 95% CI 4.95 to 5.13), the crude percentage prevalence of type 2 diabetes was higher in the Asian (7.69%, 95% CI 7.46 to 7.92) and Black (5.58%, 95% CI 5.35 to 5.81) ethnic groups, while lower in the Mixed/Other group (3.42%, 95% CI 3.19 to 3.66). After adjusting for differences in age group, sex, and social deprivation, all minority ethnic groups were more likely to have a diagnosis of type 2 diabetes compared with the White group (OR Asian versus White 2.36, 95% CI 2.26 to 2.47; OR Black versus White 1.65, 95% CI 1.56 to 1.73; OR Mixed/Other versus White 1.17, 95% CI 1.08 to 1.27). CONCLUSION: The prevalence of type 2 diabetes was higher in the Asian and Black ethnic groups, compared with the White group. Accurate estimates of ethnic prevalence of type 2 diabetes based on large datasets are important for facilitating appropriate allocation of public health resources, and for allowing population-level research to be undertaken examining disease trajectories among minority ethnic groups, that might help reduce inequalities

Does exporting spur firm productivity and promote inclusive growth? : evidence from Vietnam

Are exporting firms superior because only superior firms choose to become exporters or do they become superior by virtue of being exporters and having to face greater competition and to specialize in core activities? Findings show that the decision to export induces a gain in capital productivity for the new exporters, but no significant effect is observed for labour productivity and Total Factor Productivity (TFP). This result offers some support for the learning-by-exporting effect that occurs within a sector. Entry of Vietnamese firms into the world market can spur inclusive economic growth of the country

Reliability of hospital scores for the Cancer Patient Experience Survey: analysis of publicly reported patient survey data.

OBJECTIVES: To assess the degree to which variations in publicly reported hospital scores arising from the English Cancer Patient Experience Survey (CPES) are subject to chance. DESIGN: Secondary analysis of publically reported data. SETTING: English National Health Service hospitals. PARTICIPANTS: 72 756 patients who were recently treated for cancer in one of 146 hospitals and responded to the 2016 English CPES. MAIN OUTCOME MEASURES: Spearman-Brown reliability of hospital scores on 51 evaluative questions regarding cancer care. RESULTS: Hospitals varied in respondent sample size with a median hospital sample size of 419 responses (range 31-1972). There were some hospitals with generally highly reliable scores across most questions, whereas other hospitals had generally unreliable scores (the median reliability of question scores within individual hospitals varied between 0.11 and 0.86). Similarly, there were some questions with generally high reliability across most hospitals, whereas other questions had generally low reliability. Of the 7377 individual hospital scores publically reported (146 hospitals by 51 questions, minus 69 suppressed scores), only 34% reached a reliability of 0.7, the minimum generally considered to be useful. In order for 80% of the individual hospital scores to reach a reliability of 0.7, some hospitals would require a fourfold increase in number of respondents; although in a few other hospitals sample sizes could be reduced. CONCLUSIONS: The English Patient Experience Survey represents a globally unique source for understanding experience of a patient with cancer; but in its present form, it is not reliable for high stakes comparisons of the performance of different hospitals. Revised sampling strategies and survey questions could help increase the reliability of hospital scores, and thus make the survey fit for use in performance comparisons.This research was funded by Macmillan Cancer Support (grant number 5995414). GL is funded by a Cancer Research UK Advanced Clinician Scientist Fellowship award (grant number C18081/A18180)

Synthesis of cuprous oxide nanocubes combined with chitosan nanoparticles and its application to p-nitrophenol degradation

For the first time, cuprous oxide nanocubes (Cu2O NCBs) were successfully combined with chitosan nanoparticles (CS NPs) to generate Cu2O NCBs/CS NPs composites material with highly optical property and photocatalytic activity using a simple and eco-friendly synthetic approach at room temperature for 30 min. The synthesized Cu2O NCBs NPs/CS NPs were determined characterizations by Ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), X – ray Diffraction (XRD),  Transmission Electron Microscope (TEM) and Energy-dispersive X-ray spectroscopy (EDX). Results show that the Cu2O NCBs/CS NPs composites have an average particle size of ~3-5 nm; in which, Cu2O has the form of nanocubes (Cu2O NCBs) with size ~3-4 nm and chitosan nanoparticles with spherical shape (CS NPs) with size ~4-5 nm. In addition, the percent (%) composition of elements present in Cu2O NCBs/CS NPs composites material have been obtained respective: Cu (23.99%), O (38.18%), and C (33.61%). Moreover, Cu2O NCBs/CS NPs composites material was also investigated for photocatalytic activity applied in p-nitrophenol degradation. The obtained results showed that the catalytic capability of Cu2O NCBs/CS NPs for p-nitrophenol reduction reached the highest efficiency >55% in the treatment time of 25 min, and this efficiency was higher than that result of using ZnO@chitosan nanoparticles (ZnO@CS NPs) catalyst under the same conditions for comparison

Population-calibrated multiple imputation for a binary/categorical covariate in categorical regression models.

Multiple imputation (MI) has become popular for analyses with missing data in medical research. The standard implementation of MI is based on the assumption of data being missing at random (MAR). However, for missing data generated by missing not at random mechanisms, MI performed assuming MAR might not be satisfactory. For an incomplete variable in a given data set, its corresponding population marginal distribution might also be available in an external data source. We show how this information can be readily utilised in the imputation model to calibrate inference to the population by incorporating an appropriately calculated offset termed the "calibrated-δ adjustment." We describe the derivation of this offset from the population distribution of the incomplete variable and show how, in applications, it can be used to closely (and often exactly) match the post-imputation distribution to the population level. Through analytic and simulation studies, we show that our proposed calibrated-δ adjustment MI method can give the same inference as standard MI when data are MAR, and can produce more accurate inference under two general missing not at random missingness mechanisms. The method is used to impute missing ethnicity data in a type 2 diabetes prevalence case study using UK primary care electronic health records, where it results in scientifically relevant changes in inference for non-White ethnic groups compared with standard MI. Calibrated-δ adjustment MI represents a pragmatic approach for utilising available population-level information in a sensitivity analysis to explore potential departures from the MAR assumption.Tra My Pham was supported by the National Institute for Health Research (NIHR) School for Primary Care Research (project number 379) and awards to establish the Farr Institute of Health Informatics Research, London, from the Medical Research Council, Arthritis Research UK, British Heart Foundation, Cancer Research UK, Chief Scientist Office, Economic and Social Research Council, Engineering and Physical Sciences Research Council, NIHR, National Institute for Social Care and Health Research, and Wellcome Trust (grant MR/K006584/1). James Carpenter and Tim Morris were supported by the Medical Research Council (grant numbers MC_UU_12023/21 and MC_UU_12023/29)

Diagnostic route is associated with care satisfaction independently of tumour stage: Evidence from linked English Cancer Patient Experience Survey and cancer registration data.

BACKGROUND: Whether diagnostic route (e.g. emergency presentation) is associated with cancer care experience independently of tumour stage is unknown. METHODS: We analysed data on 18 590 patients with breast, prostate, colon, lung, and rectal cancers who responded to the 2014 English Cancer Patient Experience Survey, linked to cancer registration data on diagnostic route and tumour stage at diagnosis. We estimated odds ratios (OR) of reporting a negative experience of overall cancer care by tumour stage and diagnostic route (crude and adjusted for patient characteristic and cancer site variables) and examined their interactions with cancer site. RESULTS: After adjustment, the likelihood of reporting a negative experience was highest for emergency presenters and lowest for screening-detected patients with breast, colon, and rectal cancers (OR versus two-week-wait 1.51, 95% confidence interval [CI] 1.24-1.83; 0.88, 95% CI 0.75-1.03, respectively). Patients with the most advanced stage were more likely to report a negative experience (OR stage IV versus I 1.37, 95% CI 1.15-1.62) with little confounding between stage and route, and no evidence for cancer-stage or cancer-route interactions. CONCLUSIONS: Though the extent of disease is strongly associated with ratings of overall cancer care, diagnostic route (particularly emergency presentation or screening detection) exerts important independent effects.This work is supported by Macmillan Cancer Support grant 5995414 for which GAA and GL are joint principal investigators. GL is supported by a Cancer Research UK Advanced Clinician Scientist Fellowship Award (C18081/A18180)

Statistical Analysis Plan for the Motor Neuron Disease Systematic Multi-Arm Adaptive Randomised Trial (MND-SMART)

Abstract Background MND-SMART is a platform, multi-arm, multi-stage, multi-centre, randomised controlled trial recruiting people with motor neuron disease. Initially, the treatments memantine and trazodone will each be compared against placebo, but other investigational treatments will be introduced into the trial later. The co-primary outcomes are the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALS-FRS-R) functional outcome, which is assessed longitudinally, and overall survival. Methods Initially in MND-SMART, participants are randomised 1:1:1 via a minimisation algorithm to receive placebo or one of the two investigational treatments with up to 531 to be randomised in total. The comparisons between each research arm and placebo will be conducted in four stages, with the opportunity to cease further randomisations to poorly performing research arms at the end of stages 1 or 2. The final ALS-FRS-R analysis will be at the end of stage 3 and final survival analysis at the end of stage 4. The estimands for the co-primary outcomes are described in detail. The primary analysis of ALS-FRS-R at the end of stages 1 to 3 will involve fitting a normal linear mixed model to the data to calculate a mean difference in rate of ALS-FRS-R change between each research treatment and placebo. The pairwise type 1 error rate will be controlled, because each treatment comparison will generate its own distinct and separate interpretation. This publication is based on a formal statistical analysis plan document that was finalised and signed on 18 May 2022. Discussion In developing the statistical analysis plan, we had to carefully consider several issues such as multiple testing, estimand specification, interim analyses, and statistical analysis of the repeated measurements of ALS-FRS-R. This analysis plan attempts to balance multiple factors, including minimisation of bias, maximising power and precision, and deriving clinically interpretable summaries of treatment effects. Trial registration EudraCT Number, 2019–000099-41. Registered 2 October 2019, https://www.clinicaltrialsregister.eu/ctr-search/search?query=mnd-smart ClinicalTrials.gov, NCT04302870 . Registered 10 March 2020

The burden and characteristics of enteric fever at a healthcare facility in a densely populated area of Kathmandu

Enteric fever, caused by Salmonella enterica serovars Typhi and Paratyphi A (S. Typhi and S. Paratyphi A) remains a major public health problem in many settings. The disease is limited to locations with poor sanitation which facilitates the transmission of the infecting organisms. Efficacious and inexpensive vaccines are available for S. Typhi, yet are not commonly deployed to control the disease. Lack of vaccination is due partly to uncertainty of the disease burden arising from a paucity of epidemiological information in key locations. We have collected and analyzed data from 3,898 cases of blood culture-confirmed enteric fever from Patan Hospital in Lalitpur Sub-Metropolitan City (LSMC), between June 2005 and May 2009. Demographic data was available for a subset of these patients (n = 527) that were resident in LSMC and who were enrolled in trials. We show a considerable burden of enteric fever caused by S. Typhi (2,672; 68.5%) and S. Paratyphi A (1,226; 31.5%) at this Hospital over a four year period, which correlate with seasonal fluctuations in rainfall. We found that local population density was not related to incidence and we identified a focus of infections in the east of LSMC. With data from patients resident in LSMC we found that the median age of those with S. Typhi (16 years) was significantly less than S. Paratyphi A (20 years) and that males aged 15 to 25 were disproportionately infected. Our findings provide a snapshot into the epidemiological patterns of enteric fever in Kathmandu. The uneven distribution of enteric fever patients within the population suggests local variation in risk factors, such as contaminated drinking water. These findings are important for initiating a vaccination scheme and improvements in sanitation. We suggest any such intervention should be implemented throughout the LSMC area.This work was supported by The Wellcome Trust, Euston Road, London, United Kingdom. MFB is supported by the Medical Research Council (grant G0600718). SB is supported by an OAK foundation fellowship through Oxford University