Participant Fraud in Virtual Qualitative Substance Use Research: Recommendations and Considerations for Detection and Prevention Based on a Case Study.

Background: The COVID-19 pandemic has accelerated and amplified the use of virtual research methods. While online research has several advantages, it also provides greater opportunity for individuals to misrepresent their identities to fraudulently participate in research for financial gain. Participant deception and fraud have become a growing concern for virtual research. Reports of deception and preventative strategies have been discussed within online quantitative research, particularly survey studies. Though, there is a dearth of literature surrounding these issues pertaining to qualitative studies, particularly within substance use research. Results: In this commentary, we detail an unforeseen case study of several individuals who appeared to deliberately misrepresent their identities and information during participation in a virtual synchronous qualitative substance use study. Through our experiences, we offer strategies to detect and prevent participant deception and fraud, as well as challenges to consider when implementing these approaches. Conclusions: Without general awareness and protective measures, the integrity of virtual research methods remains vulnerable to inaccuracy. As online research continues to expand, it is essential to proactively design innovative solutions to safeguard future studies against increasingly sophisticated deception and fraud.

A novel method for detecting credit card fraud problems.

Credit card fraud is a significant problem that costs billions of dollars annually. Detecting fraudulent transactions is challenging due to the imbalance in class distribution, where the majority of transactions are legitimate. While pre-processing techniques such as oversampling of minority classes are commonly used to address this issue, they often generate unrealistic or overgeneralized samples. This paper proposes a method called autoencoder with probabilistic xgboost based on SMOTE and CGAN(AE-XGB-SMOTE-CGAN) for detecting credit card frauds.AE-XGB-SMOTE-CGAN is a novel method proposed for credit card fraud detection problems. The credit card fraud dataset comes from a real dataset anonymized by a bank and is highly imbalanced, with normal data far greater than fraud data. Autoencoder (AE) is used to extract relevant features from the dataset, enhancing the ability of feature representation learning, and are then fed into xgboost for classification according to the threshold. Additionally, in this study, we propose a novel approach that hybridizes Generative Adversarial Network (GAN) and Synthetic Minority Over-Sampling Technique (SMOTE) to tackle class imbalance problems. Our two-phase oversampling approach involves knowledge transfer and leverages the synergies of SMOTE and GAN. Specifically, GAN transforms the unrealistic or overgeneralized samples generated by SMOTE into realistic data distributions where there is not enough minority class data available for GAN to process effectively on its own. SMOTE is used to address class imbalance issues and CGAN is used to generate new, realistic data to supplement the original dataset. The AE-XGB-SMOTE-CGAN algorithm is also compared to other commonly used machine learning algorithms, such as KNN and Light GBM, and shows an overall improvement of 2% in terms of the ACC index compared to these algorithms. The AE-XGB-SMOTE-CGAN algorithm also outperforms KNN in terms of the MCC index by 30% when the threshold is set to 0.35. This indicates that the AE-XGB-SMOTE-CGAN algorithm has higher accuracy, true positive rate, true negative rate, and Matthew's correlation coefficient, making it a promising method for detecting credit card fraud.

Anticounterfeiting and Fraud Mitigation Solutions for High-value Food Products.

Globalization and the increasing complexity of supply chains have allowed food fraud to expand to a great extent. Some of the most serious effects of these deceitful activities are damage to a brand's reputation and trust, economic losses, and public health risks. The usual victims of food fraud are dairy, meat, fish, and seafood products, as well as fats/oils and alcoholic drinks. The purpose of this review paper is to present an updated analysis of the currently available anticounterfeit technologies and their application to the four most fraud-affected food supply chains. An assessment that was conducted to determine when the adoption of a combination of technologies could enhance food safety and brand protection is also provided. The obtained results indicate that electronic and data-driven technologies (RFID devices and digital traceability systems) are still in their infancy in the food sectors that are subjected the most to fraudulent activities. Research is necessary to develop innovative digital and physical technologies to "outsmart" such fraudsters and to prevent their illicit actions in the food sector.

Case Studies of Fraud Associated with the Use of Radiation Sources: Practical Avoidance Strategies Based on Lessons Learned.

ABSTRACT: Periodically the radiation protection profession has experienced purposeful deception practices that remained undetected for some time. Upon discovery, the cases of fraud revealed gaps in confirmation or validation practices that the radiation protection community should note. Summarized here is a convenience sample of actual cases of fraud involving radiation sources along with the exploited process vulnerabilities. Recommended process improvements that the radiation safety community may consider are presented to improve the collective fidelity of radiation protection processes.

Federal Enforcement of Pharmaceutical Fraud under the False Claims Act, 2006-2022.

CONTEXT: The False Claims Act is the US federal government's primary tool for identifying and penalizing pharmaceutical fraud. The Department of Justice uses the False Claims Act to bring civil cases against drug manufacturers that allegedly obtain improper payment from federal programs. METHODS: The authors searched the Department of Justice website for press releases published between 2006 and 2022 that announced fraud actions brought against drug companies. They then used the World Health Organization's Anatomical Therapeutic Classification index to identify the classes of prescription drugs implicated in fraud actions. FINDINGS: During fiscal years 2006-2022, payments by six manufacturers amounted to more than 28% of total payments made as a result of federal False Claims Act actions. Nervous system and cardiovascular drugs were the classes of medications most commonly implicated in alleged fraud. Federal officials most frequently alleged that companies improperly promoted nervous system drugs and paid kickbacks to increase revenues from cardiovascular, antineoplastic and immunomodulating, and alimentary tract and metabolism drugs. CONCLUSIONS: Despite frequent pharmaceutical fraud settlements and penalties, incidence of alleged fraud among drug companies remains high. Alternative methods for preventing and deterring fraud could help safeguard our health systems and promote public health, and policy makers should ensure that effective fraud enforcement complements preventive public health regulation.

Corruption risks in health procurement during the COVID-19 pandemic and anti-corruption, transparency and accountability (ACTA) mechanisms to reduce these risks: a rapid review.

BACKGROUND: Health systems are often susceptible to corruption risks. Corruption within health systems has been found to negatively affect the efficacy, safety, and, significantly, equitable distribution of health products. Enforcing effective anti-corruption mechanisms is important to reduce the risks of corruption but requires first an understanding of the ways in which corruption manifests. When there are public health crises, such as the COVID-19 pandemic, corruption risks can increase due to the need for accelerated rates of resource deployment that may result in the bypassing of standard operating procedures. MAIN BODY: A rapid review was conducted to examine factors that increased corruption risks during the COVID-19 pandemic as well as potential anti-corruption, transparency and accountability (ACTA) mechanisms to reduce these risks. A search was conducted including terms related to corruption, COVID-19, and health systems from January 2020 until January 2022. In addition, relevant grey literature websites were hand searched for items. A single reviewer screened the search results removing those that did not meet the inclusion criteria. This reviewer then extracted data relevant to the research objectives from the included articles. 20 academic articles and 17 grey literature pieces were included in this review. Majority of the included articles described cases of substandard and falsified products. Several papers attributed shortages of these products as a major factor for the emergence of falsified versions. Majority of described corruption instances occurred in low- and middle-income countries. The main affected products identified were chloroquine tablets, personal protective equipment, COVID-19 vaccine, and diagnostic tests. Half of the articles were able to offer potential anti-corruption strategies. CONCLUSION: Shortages of health products during the COVID-19 pandemic seemed to be associated with increased corruption risks. We found that low- and middle-income countries are particularly vulnerable to corruption during global emergencies. Lastly, there is a need for additional research on effective anti-corruption mechanisms.

Fraud within the Nigerian health system, a double threat for resilience of a health system and the response to the COVID-19 pandemic: a review.

As Nigeria battles the COVID-19 pandemic, systemic fraud within the health system may undermine the efforts to halt the devastating effect of the disease and the fight against COVID-19. Fraud is a major concern worldwide, especially in developing countries such as Nigeria, where it is widespread within the health system. The vulnerability of the Nigerian health system despite several efforts from relevant stakeholders, has consistently been underscored before the pandemic arose, raising serious concerns. These concerns include fraud, embezzlement, and mismanagement of funds, exploitation, lack of transparency in policymaking, cutting corners in procurement processes, and taking advantage of the healthcare workforce for personal benefits. Also, other involvements in the vulnerability of the Nigerian health system that are worrisome include stakeholders using the pandemic to their advantage to increase their private benefits, a short supply of vital health resources, fraudulent recruitment of the health workforce, and ineffective crisis management. This study explores fraud within the Nigerian health system, its impact and implications for health-system resilience as well as its response to the COVID-19 pandemic. Guided by agency theory, causes and impacts of fraud in the health system and its implications on the response to COVID-19 were explained. Systematic review method was employed; out of 1462 articles identified and screened dated from 1991 to 2021, sixty articles were included in the analysis and interpretation. Specific fraud interventions should focus on a weak and vulnerable health system, service delivery, high-risk institutionalized health workforce, and addressing issues of fraud within and outside the health system in order to curb the dreaded COVID-19 and its variants in Nigeria.

Laser Sensing and Chemometric Analysis for Rapid Detection of Oregano Fraud.

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes.

False Claims Act and Anti-Kickback Statute: Avoiding Legal Landmines.

Health care entities doing business with the federal government may run afoul of the False Claims Act and Anti-Kickback Statute not only when they directly submit fraudulent claims for government reimbursement but also when they create schemes that manipulate others into submitting (whether knowingly or unknowingly) illegal claims. In recent years, the Department of Justice is deploying these statutes to ensure that electronic health records are built and maintained with appropriate cybersecurity protections.

Reducing older people's risk of fraud victimization through an anti-scam board game.

This study adopted an experimental design to evaluate the effectiveness of an anti-scam education program for older adults. Participants in the experimental group (n = 55) first participated in an anti-scam board game and then joined another board game featuring local tea restaurants two weeks later, whereas such order was reversed for the control group (n = 54). Compared with the control group, participants in the experimental group reported significant increases in their self-efficacy in fraud prevention and awareness of scam situations, and a significant decrease in perceived susceptibility to scams immediately and two weeks after the intervention, demonstrating the immediate and the short-term effects of the anti-scam education program in reducing fraud victimization risk of older adults.

Mitigating the Risk of Digital Financial Exploitation.

The article by Zhang and colleagues in this issue of The Journal calls attention to an important but underrecognized problem facing today's seniors and their loved ones. The risk of digital financial exploitation, particularly in the wake of the COVID-19 pandemic, has risen considerably in recent years and continues to rise today. Zhang et al. provide a helpful analysis of assessment tools currently available to forensic psychiatrists for the evaluation of financial capacity. Although many of these tools were not originally intended to encompass technologically based transactions, the risks of fraud and scams associated with payment apps, social media, and electronic fund transfers are considerable and growing. Fraudsters frequently target vulnerable older adults, and victims have lost large sums through some of the more prevalent schemes. Several strategies can help to mitigate the risk of severe losses and to increase the likelihood that lost assets can be recovered. Proactive education through increased awareness will prove helpful, but given the growing sophistication of modern digital cons, such as romance scams, increased technological safeguards are warranted in the setting of reduced financial capacity. When losses do occur, there are some resources for recovery and for filing complaints against perpetrators.

Understanding medical corruption in China: a mixed-methods study.

Medical corruption is a significant obstacle to achieving health-related Sustainable Development Goals. However, the understanding of medical corruption is limited, especially in developing countries. As the largest developing country, China is also plagued by medical corruption. By employing a mixed-methods design and combining data from three resources, this study attempts to examine patterns of medical corruption in China, explore its key drivers and investigate the perceived effectiveness of recent anti-corruption interventions. Using extracted data from 3546 cases on the China Judgments Online website between 2013 and 2019, we found that bribery, embezzlement and insurance fraud accounted for 68.1%, 22.8% and 9.1% of all medical corruption cases, respectively. Bribery was the major form of medical corruption. Approximately 80% of bribe-takers were healthcare providers, and most bribe-givers were suppliers of pharmaceuticals, medical equipment and consumables. Using a nationally representative household survey, we further found that the prevalence of informal payments from patients remained at a low level between 2011 and 2018. In 2018, only 0.4% of outpatients and 1.4% of inpatients reported that they had ever given 'red envelopes' to physicians in the past. Finally, we conducted interviews with 17 key informants to explore drivers of medical corruption and investigated the perceived effectiveness of recent anti-corruption interventions in China. Interview results showed that financial pressure and weak oversight were two main reasons for corrupt behaviours. Interview results also suggested that the anti-corruption campaign since 2012, the national volume-based procurement, and the special campaign against medical insurance fraud had reduced opportunities for medical corruption, implying China's positive progress in combating medical corruption. These findings hold lessons for anti-corruption interventions in China as well as other developing countries.

An Affordable NIR Spectroscopic System for Fraud Detection in Olive Oil.

Adulterations of olive oil are performed by adding seed oils to this high-quality product, which are cheaper than olive oils. Food safety controls have been established by the European Union to avoid these episodes. Most of these methodologies require expensive equipment, time-consuming procedures, and expert personnel to execute. Near-infrared spectroscopy (NIRS) technology has many applications in the food processing industry. It analyzes food safety and quality parameters along the food chain. Using principal component analysis (PCA), the differences and similarities between olive oil and seed oils (sesame, sunflower, and flax oil) have been evaluated. To quantify the percentage of adulterated seed oil in olive oils, partial least squares (PLS) have been employed. A total of 96 samples of olive oil adulterated with seed oils were prepared. These samples were used to build a spectra library covering various mixtures containing seed oils and olive oil contents. Eighteen chemometric models were developed by combining the first and second derivatives with Standard Normal Variable (SNV) for scatter correction to classify and quantify seed oil adulteration and percentage. The results obtained for all seed oils show excellent coefficients of determination for calibration higher than 0.80. Because the instrumental aspects are not generally sufficiently addressed in the articles, we include a specific section on some key aspects of developing a high-performance and cost-effective NIR spectroscopy solution for fraud detection in olive oil. First, spectroscopy architectures are introduced, especially the Texas Instruments Digital Light Processing (DLP) technology for spectroscopy that has been used in this work. These results demonstrate that the portable prototype can be used as an effective tool to detect food fraud in liquid samples.

Relationship Between Socioeconomic Conditions and Financial Fraud Victimization Among Older Adults in China: Do Financial Literacy and Financial Attitudes Matter?

Using data from the 2015 wave of the China Household Finance Survey (N ≈ 12,100), this study used structural equation modeling to examine the relationship between socioeconomic conditions (i.e., educational attainments, hukou status, and household financial assets per capita) and financial fraud victimization among Chinese older adults and the mediating roles of financial literacy and financial attitudes (i.e., interest in financial matters and risk tolerance). We found that although neither educational attainment nor hukou status was directly related to financial fraud victimization, household financial assets per capita was postively associated with the risk of financial fraud victimization. In addition, higher educational attainment, urban hukou, and more financial assets per capita were associated with more risk of financial fraud victimization through higher levels of financial literacy and higher interest in financial matters. Implications for preventing and protecting Chinese older adults from financial fraud victimization are discussed.

Anti-corruption in global health systems: using key informant interviews to explore anti-corruption, accountability and transparency in international health organisations.

OBJECTIVES: Corruption undermines the quality of healthcare and leads to inequitable access to essential health products. WHO, Global Fund, United Nations Development Programme (UNDP) and World Bank are engaged in anti-corruption in health sectors globally. Throughout the COVID-19 pandemic, weakened health systems and overlooked regulatory processes have increased corruption risks. The objective of this study is thus to explore the strengths and weaknesses of these organisations' anti-corruption mechanisms and their trajectories since the pandemic began. DESIGN, SETTING AND PARTICIPANTS: 25 semistructured key informant interviews with a total of 27 participants were conducted via Zoom between April and July 2021 with informants from WHO, World Bank, Global Fund and UNDP, other non-governmental organisations involved in anti-corruption and academic institutions. Key informant selection was guided by purposive and snowball sampling. Detailed interview notes were qualitatively coded by three researchers. Data analysis followed an inductive-deductive hybrid thematic analysis framework. RESULTS: The findings demonstrate that WHO, World Bank, Global Fund and UNDP have shifted from criminalisation/punitive approaches to anti-corruption to preventative ones and that anti-corruption initiatives are strong when they are well funded, explicitly address corruption and are complemented by strong monitoring and evaluation mechanisms. Weaknesses in the organisations' approaches to anti-corruption include one-size-fits-all approaches, lack of political will to address corruption and zero-tolerance policies for corruption. The COVID-19 pandemic has highlighted the necessity of improving anti-corruption by promoting strong accountability and transparency in health systems. CONCLUSIONS: Results from this study highlight the strengths, weaknesses and recent trajectories of anti-corruption in the Global Fund, World Bank, UNDP and WHO. This study underscores the importance of implementing strong and robust anti-corruption mechanisms specifically geared towards corruption prevention that remain resilient even in times of emergency.

New Software Interface for Registering Rapid Antigen Test Results to Prevent Fraud.

Donald O. Besong has already documented that the online registration of unsupervised lateral flow test results poses concerns in the case of a serious pandemic where there are not enough medics to read scans or watch videos of candidates' results (Besong Int J Biomed Healthc Sci. 2022;12(1):1-12). Scanning or videorecording requires a high number of available medics (Besong Int J Biomed Healthc Sci. 2022;12(1):1-12) in an adverse pandemic scenario. In the above study (Besong Int J Biomed Healthc Sci. 2022;12(1):1-12), an artificial intelligence (AI) interface with image recognition was suggested as a method to prevent cheating during the online registration of unsupervised test results. The second solution suggested was a method that obscures the meaning of the result the candidate reads from their test device so that a software interface can resolve that from a database (Besong Int J Biomed Healthc Sci. 2022;12(1):1-12). This is an entirely new method. In this study, the latter (entirely new) method is proposed and described in detail. Precisely, this simple but new method is all about blinding the test strips so that the candidate does not know what the face values signify. The software then connects to a database of unique strip identification numbers to determine the test result when the candidate or patient registers their results. Both strip number and the value of their test must be entered to register results. This method has never been proposed or implemented. The technique will be described in detail.