Death anxiety and older adults' vulnerability to fraud: the mediating role of materialism.

Death anxiety arousal, provoked by anticipating self-nonexistence, may be used as a fraud tactic by scammers on older adults; however, little is known about how it affects older adults' decision making when confronted with a scam and the mechanisms underlying these effects. This study used a questionnaire survey and experimental design to examine them. In Study 1, 307 older adults in China completed questionnaires. The results showed a positive link between death anxiety and vulnerability to fraud, partially mediated by materialism. In Study 2, 82 older adults in China were randomly assigned to the mortality salience group and control group to examine whether death anxiety arousal can increase older adults' vulnerability to fraud and the mediating role of materialism. The results indicated that death anxiety and materialism increase the risk of consumer products and services fraud; therefore, targeting these risk factors might protect older adults from fraud.

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.

Healthcare insurance fraud detection using data mining.

BACKGROUND: Healthcare programs and insurance initiatives play a crucial role in ensuring that people have access to medical care. There are many benefits of healthcare insurance programs but fraud in healthcare continues to be a significant challenge in the insurance industry. Healthcare insurance fraud detection faces challenges from evolving and sophisticated fraud schemes that adapt to detection methods. Analyzing extensive healthcare data is hindered by complexity, data quality issues, and the need for real-time detection, while privacy concerns and false positives pose additional hurdles. The lack of standardization in coding and limited resources further complicate efforts to address fraudulent activities effectively. METHODOLGY: In this study, a fraud detection methodology is presented that utilizes association rule mining augmented with unsupervised learning techniques to detect healthcare insurance fraud. Dataset from the Centres for Medicare and Medicaid Services (CMS) 2008-2010 DE-SynPUF is used for analysis. The proposed methodology works in two stages. First, association rule mining is used to extract frequent rules from the transactions based on patient, service and service provider features. Second, the extracted rules are passed to unsupervised classifiers, such as IF, CBLOF, ECOD, and OCSVM, to identify fraudulent activity. RESULTS: Descriptive analysis shows patterns and trends in the data revealing interesting relationship among diagnosis codes, procedure codes and the physicians. The baseline anomaly detection algorithms generated results in 902.24 seconds. Another experiment retrieved frequent rules using association rule mining with apriori algorithm combined with unsupervised techniques in 868.18 seconds. The silhouette scoring method calculated the efficacy of four different anomaly detection techniques showing CBLOF with highest score of 0.114 followed by isolation forest with the score of 0.103. The ECOD and OCSVM techniques have lower scores of 0.063 and 0.060, respectively. CONCLUSION: The proposed methodology enhances healthcare insurance fraud detection by using association rule mining for pattern discovery and unsupervised classifiers for effective anomaly detection.

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.

False Health Claims Abound, but Physicians Are Still the Most Trusted Source for Health Information.

This Medical News article discusses a KFF poll about the public's exposure to and beliefs about inaccurate health information, as well as media use and trust in sources.

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.

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents.

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

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.

The court's judgment on the true identity of the author responsible for identity fraud and the consequent batch retraction of Iranian's papers in the journal of diagnostic pathology.

This letter concerns retracted papers published in the Journal of Diagnostic Pathology, where my name was misused as the author or corresponding author without my permission or knowledge. Considering that all misconducts were directed by an author during initial manuscripts' submissions, I opened a case in Iran's Cyber Police (FATA) to unravel the true identity of the submitting author. After Cyber Police's report revealed the true identity of the submitting author, the court started a thorough investigation and finally convicted the submitting author for identity fraud and data forgery through creating and using fake email addresses.

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.

Research on the risk governance of fraudulent reimbursement of patient consultation fees.

Background: The fundamental medical insurance fund, often referred to as the public's "life-saving fund," plays a crucial role in both individual well-being and the pursuit of social justice. Medicare fraudulent claims reduce "life-saving money" to "Tang's monk meat", undermining social justice and affecting social stability. Methods: We utilized crawler technology to gather textual data from 215 cases involving fraudulent health insurance claims. Simultaneously, statistical data spanning 2018 to 2021 was collected from the official websites of the China Medical Insurance Bureau and Anhui Medical Insurance Bureau. The collected data underwent comprehensive analysis through Excel, SPSS 26.0 and R4.2.1. Differential Auto-Regressive Moving Average Model (ARIMA (p, d, q)) was used to fit the fund safety forecast model, and test the predictive validity of the forecast model on the fund security data from July 2021 to October 2023 (the fund security data of Anhui Province from September 2021 to October 2023). Results: The outcomes revealed that fraudulent claims by health insurance stakeholders adversely impact the equity of health insurance funds. Furthermore, the risk management practices of Medicare fund administrators influence the publication of fraudulent claims cases. Notably, differences among Medicare stakeholders were observed in the prevalence of fraudulent claims. Additionally, effective governance of fraudulent claims risks was found to have a positive impact on the overall health of healthcare funds. Moreover, the predictive validity of the forecast model on the national and Anhui province's fund security data was 92.86% and 100% respectively. Conclusion: We propose four recommendations for the governance of health insurance fraudulent claims risk behaviors. These recommendations include strategies such as "combatting health insurance fraudulent claims to preserve the fairness of health insurance funds", "introducing initiatives for fraud risk governance and strengthening awareness of the rule of law", "focusing on designated medical institutions and establishing a robust long-term regulatory system", and "adapting to contemporary needs while maintaining a focus on long-term regulation".

Fraud victimization across the lifespan: evidence on repeat victimization using perpetrator data.

Older adults are thought to be more susceptible to scams, yet understanding the relationship between chronological age and victimization is limited by underreporting. This study avoids underreporting bias by merging four longitudinal databases of Americans (N = 1.33 million) who paid money in response to mail scams over 20 years. We investigate the risk of repeat victimization and victimization by multiple scam types over the life course. Victims in their 70s and 80s are 9% more likely to experience another victimization incident than those in their 50s. Those age 18 to 29 are 24% less likely to experience another victimization incident. Relative to adults in their 50s, the odds of victimization by multiple scams are greater for those in their 60s and 70s, but lower for those 80 + . This study demonstrates the research potential in using scammers' data to understand patterns of victimization. Fraud prevention efforts should target older individuals who are at higher risk of repeat victimization and suffer greater losses as a result.

What influences the public's willingness to report health insurance fraud in familiar or unfamiliar healthcare settings? a cross-sectional study of the young and middle-aged people in China.

INTRODUCTION: Young and middle-aged people are important participants in the fight against health insurance fraud. The study aims to investigate the differences in their willingness to report health insurance fraud and the factors influencing it when it occurs in familiar or unfamiliar healthcare settings. METHODS: Data were obtained from a validated questionnaire from 828 young and middle-aged people. McNemar's test was used to compare the public's willingness to report under the two scenarios. Chi-square tests and multiple logistic regression analysis were used to analyze the determinants of individuals' willingness to report health insurance fraud in different scenarios. RESULTS: Young and middle-aged people were more likely to report health insurance fraud in a familiar healthcare setting than in an unfamiliar one (McNemar's χ²=26.51, P < 0.05). Their sense of responsibility for maintaining the security of the health insurance fund, the government's openness about fraud cases, and the perception of their ability to report had significant positive effects on the public's willingness to report in both settings (P < 0.05). In a familiar healthcare setting, the more satisfied the public is with government measures to protect whistleblowers, the more likely they are to report (OR = 1.44, P = 0.025). Those who perceive the consequences of health insurance fraud to be serious are more likely to report than those who perceive the consequences to be less serious (OR = 1.61, P = 0.042). CONCLUSION: Individuals are more likely to report health insurance fraud in familiar healthcare settings than in unfamiliar ones, in which their awareness of the severity of the consequences of health insurance fraud and their perceived risk after reporting it play an important role. The government's publicizing of fraud cases and enhancing the public's sense of responsibility and ability to maintain the safety of the health insurance fund may be a way to increase their willingness to report, regardless of whether they are familiar with the healthcare setting or not.

The Assessment of Situational Judgement Questionnaire: A Novel Instrument to Detect Susceptibility to Financial Scamming.

BACKGROUND: Existing measures of scam susceptibility lack ecological validity and situational variability. Evidence suggests that all adults may be susceptible to scams, though a comprehensive fraud victimization theory remains to be explored. OBJECTIVE: To identify cognitive and sociodemographic variables that differentiate individuals with high scam susceptibility from those less susceptible. This article describes the development and feasibility of the Assessment of Situational Judgment questionnaire (ASJ), a brief tool designed to detect scam susceptibility. METHODS: The 17-item ASJ was developed using a combination of existing scams reported by the Florida Division of Consumer Services and legitimate scenarios. Participants were presented with scam and legitimate scenarios and queried regarding their willingness to engage. Response options were offered with instructions on a 7-point Likert scale (extremely unlikely to extremely likely). Pilot data from a development sample provided the foundation for the final version of the ASJ. RESULTS: The final version of the ASJ was administered to 183 online participants. The Scam factor (8 items) explained 50.6% of the variance. The Legit factor (9 items) reported on a 7-point Likert scale explaining 10.6% of the variance. A Scam to Legit ratio provides a proxy for overall scam susceptibility. Cut-off scores of 24 on the Scam factor, 47 on the Legit factor, and 0.62 on the ratio optimize measures of scam susceptibility. CONCLUSIONS: The ASJ is a brief, ecologically valid measure of scam susceptibility. There is a need for a sensitive and specific tool to detect scam susceptibility in clinical, community, and financial settings.

Radiology residency oversight: A Qui Tam wake-up call.

Like every physician practice, academic radiology practices must pay heed to all governmental regulations. The federal False Claims Act serves to protect US taxpayers and requires strict adherence. Violations, often brought forth by whistleblowers, can carry steep financial repercussions.

What are people's attitudes toward medical insurance fraud whistleblowers? a study from China.

PURPOSE: Medical insurance fraud has caused huge losses to countries around the world, and public reporting has become an important means to combat medical insurance fraud. The attitude of medical insurance fraud whistleblowers affects people's reporting behavior, and understanding people's attitude toward medical insurance fraud whistleblowers provides a basis for further improving the system and policy of public participation in medical insurance fund supervision. METHODS: We adopted the questionnaire method to conduct a national cross-sectional survey of the Chinese public and analyzed the data using Chi-square tests, Fisher's exact tests, and binary logistic regression models. RESULTS: A total of 837 respondents were included, and 81.8% of the population had a supportive attitude toward medical insurance fraud whistleblowers, with gender, whether they had used medical insurance reimbursement, and present life satisfaction being statistically significant (P < 0.05). CONCLUSION: The public is generally supportive of medical insurance fraud whistleblowers, and women, those who have used medical insurance for reimbursement, and those who are satisfied with their lives are more likely to be supportive of medical insurance fraud whistleblowers.

Database of Food Fraud Records: Summary of Data from 1980 to 2022.

Food fraud prevention and detection remains a challenging problem, despite recent developments in regulatory and auditing requirements. In 2012, the United States Pharmacopeial Convention created a database of food ingredient fraud. The objective of this research was to report on updates made to the database structure and to provide an updated analysis of food fraud records. The restructured database was relational and included four tables: ingredients, adulterants, adulteration records, and references. Four adulteration record types were created to capture the variety of information that can be found in public food fraud reports. Information was searched and extracted from the peer-reviewed scientific literature, media publications, regulatory reports, judicial records, trade association reports, and other public sources covering 1980-present. Over an almost seven-year data entry period, a total of 15,575 records were entered, sourced primarily from the peer-reviewed literature and media reports. The percentage of records that included at least one potentially hazardous adulterant ranged from 34% to 60%, depending on the record type. The ingredients with the highest number of incident and inference records included fluid cow's milk, extra virgin olive oil, honey, beef, and chili powder. The ingredient groups with the highest number of incident and inference records included Dairy Ingredients, Seafood Products, Meat and Poultry Products, Herbs, Spices, and Seasonings, Milk and Cream, and Alcoholic Beverages. This database was created to serve as a standardized source of information about publicly documented occurrences of food fraud and other information relevant to fraud risk to support food fraud vulnerability assessments, mitigation plans, and food safety plans. These data support the contention that food fraud presents a public health risk that should continue to be addressed by food safety systems worldwide.