The economic impacts of social activism and corporate social responsibility on food fraud.

The study examines the relationship between the corporate social responsibility (CSR) investments of a food firm, an activist's incentive to target the firm to uncover and deter fraudulent behavior, and the firm's incentive to commit food fraud. Specifically, we develop a game theoretic model to analyze the strategic interaction between a food firm that decides whether to provide a credence food attribute and whether to misrepresent the quality of its product, and an activist who decides whether to monitor the firm and launch a campaign to uncover and remove false/misleading quality claims. We further examine the effect of CSR and the activist's presence on the level of quality the firm provides. We derive the conditions under which an activist will find it optimal to monitor the firm to uncover fraudulent quality claims and the firm will find it optimal to misrepresent its product quality. Analytical results show that the greater the firm's CSR investments, the less likely it is that the activist will find it optimal to monitor the firm, and the more likely it is that the firm will find it optimal to misrepresent its product quality. Results also show that the firm is more likely to misrepresent its product quality when its effectiveness in contesting the activist's campaign is relatively high, and more likely to actually provide a high-quality product when the cost of the credence attribute is relatively low.

The challenges associated with the prevention of smuggling and counterfeiting health goods in Iran.

BACKGROUND: Smuggling health goods given the importance and critical nature of health services should be undeniably addressed and controlled by all countries. This issue is especially more widespread in developing countries with more damaging consequences. This paper therefore aims to identify and analyze the challenges of preventing smuggling of health goods in Iran. METHOD: Within this qualitative study, we conducted face-to-face, semi-structured interviews with 30 purposefully recruited key informants and stakeholders in the detection, prevention, and combating of health goods smuggling. Each interview was analyzed thematically, using an inductive approach to generate codes, then categorized and presented in the form of main themes and sub-themes. Maxqda 11 assisted in coding, analysis, and data management. RESULTS: Three main themes emerged representing the challenges of prevention of smuggling in Iran in the areas of anti-smuggling policy development, including categories of inefficient policy and plan, and failure to reach agenda; policy implementation; categorized into actors, resources and instruments, and implementation guarantee; and finally monitoring and evaluation; including, procedures and practices, and the role of surveyors. CONCLUSION: Prevention of smuggling health goods proves to be a highly complex, challenging, and multi-faceted practice. Therefore, strengthening policy-making, regulatory frameworks, and facilitation functions about smuggling, counterfeiting, and corruption should be promoted in parallel.

Combating Fraudulent Participation in Urban American Indian and Alaska Native Virtual Health Research: Protocol for Increasing Data Integrity in Online Research (PRIOR).

BACKGROUND: While the advantages of using the internet and social media for research recruitment are well documented, the evolving online environment also enhances motivations for misrepresentation to receive incentives or to "troll" research studies. Such fraudulent assaults can compromise data integrity, with substantial losses in project time; money; and especially for vulnerable populations, research trust. With the rapid advent of new technology and ever-evolving social media platforms, it has become easier for misrepresentation to occur within online data collection. This perpetuation can occur by bots or individuals with malintent, but careful planning can help aid in filtering out fraudulent data. OBJECTIVE: Using an example with urban American Indian and Alaska Native young women, this paper aims to describe PRIOR (Protocol for Increasing Data Integrity in Online Research), which is a 2-step integration protocol for combating fraudulent participation in online survey research. METHODS: From February 2019 to August 2020, we recruited participants for formative research preparatory to an online randomized control trial of a preconceptual health program. First, we described our initial protocol for preventing fraudulent participation, which proved to be unsuccessful. Then, we described modifications we made in May 2020 to improve the protocol performance and the creation of PRIOR. Changes included transferring data collection platforms, collecting embedded geospatial variables, enabling timing features within the screening survey, creating URL links for each method or platform of data collection, and manually confirming potentially eligible participants' identifying information. RESULTS: Before the implementation of PRIOR, the project experienced substantial fraudulent attempts at study enrollment, with less than 1% (n=6) of 1300 screened participants being identified as truly eligible. With the modified protocol, of the 461 individuals who completed a screening survey, 381 did not meet the eligibility criteria assessed on the survey. Of the 80 that did, 25 (31%) were identified as ineligible via PRIOR. A total of 55 (69%) were identified as eligible and verified in the protocol and were enrolled in the formative study. CONCLUSIONS: Fraudulent surveys compromise study integrity, validity of the data, and trust among participant populations. They also deplete scarce research resources including respondent compensation and personnel time. Our approach of PRIOR to prevent online misrepresentation in data was successful. This paper reviews key elements regarding fraudulent data participation in online research and demonstrates why enhanced protocols to prevent fraudulent data collection are crucial for building trust with vulnerable populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT04376346; https://www.clinicaltrials.gov/study/NCT04376346. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52281.

The role of corruption in global food systems: a systematic scoping review.

BACKGROUND: Corruption exists at all levels of our global society and is a potential threat to food security, food safety, equity, and social justice. However, there is a knowledge gap in the role and impact of corruption within the context of the global food system. We aimed to systematically review empirical literature focused on corruption in the global food system to examine how it is characterized, the actors involved, its potential impacts, and the solutions that have been proposed to address corruption in the food system. METHODS: We used a systematic scoping review methodology. Terms combining corruption and the food system were searched in Scopus, PubMed, Web of Science, PsycInfo and Econlit, in October 2021. Two screeners applied a priori selection criteria to screen the articles at the title and abstract and full-text levels. Data was extracted into a charting form and thematically synthesized to describe the types of corruption in the food system, the actors involved, how corruption impacts the food system, and potential solutions. Sankey diagrams and narrative summaries were developed to summarize the included studies and findings. RESULTS: From the 238 included records, five main types of corruption were identified in the global food system: bureaucratic corruption, fraud, bribery, organized crime, and corporate political activity. These different types of corruption spanned across various food system areas, from policy and governance structures to food environments, and involved a wide range of actors. More powerful actors like those in public and private sectors tended to instigate corruption in the food system, while community members and primary producers tended to be impacted by it. The impacts of corruption were mostly negative and corruption was found to undermine food system governance and regulatory structures; threaten health, safety, and food security; and lead or contribute to environmental degradation, economic loss, erosion of trust, social inequities, and decreased agricultural productivity. While solution-oriented literature was limited, the essential role of strong governance,  use of technology and predictive modelling methods to improve detection of corruption, and organizational approaches to problem solving were identified. CONCLUSION: Our review findings provide researchers and policymakers with a comprehensive overview of corruption in the global food system, providing insights to inform a more holistic approach to addressing the issue. Addressing corruption in the food system is an essential element of supporting the transition to a more healthy, equitable and sustainable global food system.

Rapid and sensitive approaches for detecting food fraud: A review on prospects and challenges.

Precise and reliable analytical techniques are required to guarantee food quality in light of the expanding concerns regarding food safety and quality. Because traditional procedures are expensive and time-consuming, quick food control techniques are required to ensure product quality. Various analytical techniques are used to identify and detect food fraud, including spectroscopy, chromatography, DNA barcoding, and inotrope ratio mass spectrometry (IRMS). Due to its quick findings, simplicity of use, high throughput, affordability, and non-destructive evaluations of numerous food matrices, NI spectroscopy and hyperspectral imaging are financially preferred in the food business. The applicability of this technology has increased with the development of chemometric techniques and near-infrared spectroscopy-based instruments. The current research also discusses the use of several multivariate analytical techniques in identifying food fraud, such as principal component analysis, partial least squares, cluster analysis, multivariate curve resolutions, and artificial intelligence.

Legislating for Good Governance in the Pharmaceutical Sector through UN Convention Against Corruption (UNCAC) Compliance.

Pharmaceutical sector corruption undermines patient access to medicines by diverting public funds for private gain and exacerbating health inequities. This paper presents an analysis of UN Convention Against Corruption (UNCAC) compliance in seven countries and examines how full UNCAC adoption may reduce corruption risks within four key pharmaceutical decision-making points: product approval, formulary selection, procurement, and dispensing. Countries were selected based on their participation in the Medicines Transparency Alliance and the WHO Good Governance for Medicines Programme. Each country's domestic anti-corruption laws and policies were catalogued and analysed to evaluate their implementation of select UNCAC Articles relevant to the pharmaceutical sector. Countries displayed high compliance with UNCAC provisions on procurement and the recognition of most public sector corruption offences. However, several countries do not penalise private sector bribery or provide statutory protection to whistleblowers or witnesses in corruption proceedings, suggesting that private sector pharmaceutical dispensing may be a decision-making point particularly vulnerable to corruption. Fully implementing the UNCAC is a meaningful first step that countries can take reduce pharmaceutical sector corruption. However, without broader commitment to cultures of transparency and institutional integrity, corruption legislation alone is likely insufficient to ensure long-term, sustainable pharmaceutical sector good governance.

A water-soluble label for food products prevents packaging waste and counterfeiting.

Sustainability, humidity sensing and product origin are important features of food packaging. While waste generated from labelling and packaging causes environmental destruction, humidity can result in food spoilage during delivery and counterfeit-prone labelling undermines consumer trust. Here we introduce a food label based on a water-soluble nanocomposite ink with a high refractive index that addresses these issues. By patterning the nanocomposite ink using nanoimprint lithography, the resultant metasurface shows bright and vivid structural colours. This method makes it possible to quickly and inexpensively create patterns on large surfaces. A QR code is also developed that can provide up-to-date information on food products. Microprinting hidden in the QR code protects against counterfeiting, cannot be physically detached or replicated and may be used as a humidity indicator. Our proposed food label can reduce waste while ensuring customers receive accurate product information.

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.

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.

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.

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.

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.

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.