Clover Caldwell

As digital and remote research methods become more prevalent, the risk of fraudulent participants—individuals who deliberately misrepresent themselves to gain access to studies and associated incentives—has emerged as a significant challenge. These inauthentic participants threaten data validity, obscure treatment effects, and may lead to interventions being developed based on inaccurate representations of target populations. Despite the growing recognition of this issue, researchers have limited guidance on how to detect and respond to fraud when it occurs, particularly when committed by real people rather than automated systems. We present 3 case studies from our own research where participants engaged in deception to gain study incentives. We identify recurring patterns of behavior as “red” (clear signs of inauthenticity) and “yellow” (ambiguous behavior common among fraudulent participants) flags, describe how our team responded, and share lessons learned for future studies. This work aims to support researchers in identifying fraudulent participants more effectively, helping to ensure the validity and credibility of data collected in online research.

UNSTRUCTURED As digital and remote research methods become more prevalent, the risk of fraudulent participants—individuals who deliberately misrepresent themselves to gain access to studies and associated incentives—has emerged as a significant challenge. These inauthentic participants threaten data validity, obscure treatment effects, and may lead to interventions being developed based on inaccurate representations of target populations. Despite the growing recognition of this issue, researchers have limited guidance on how to detect and respond to fraud when it occurs, particularly when committed by real people rather than automated systems. We present 3 case studies from our own research where participants engaged in deception to gain study incentives. We identify recurring patterns of behavior as “red” (clear signs of inauthenticity) and “yellow” (ambiguous behavior common among fraudulent participants) flags, describe how our team responded, and share lessons learned for future studies. This work aims to support researchers in identifying fraudulent participants more effectively, helping to ensure the validity and credibility of data collected in online research.

Background: As Alzheimer disease (AD) and AD-related dementias (ADRD) progress, individuals increasingly require assistance from unpaid, informal caregivers to support them in activities of daily living. These caregivers may experience high levels of financial, mental, and physical strain associated with providing care. CareVirtue is a web-based tool created to connect and support multiple individuals across a care network to coordinate care activities and share important information, thereby reducing care burden. Objective: This study aims to use a computational informatics approach to thematically analyze open text written by AD/ADRD caregivers in the CareVirtue platform. We then explore relationships between identified themes and use patterns. Methods: We analyzed journal posts (n=1555 posts; 170,212 words) generated by 51 unique users of the CareVirtue platform. Latent themes were identified using a neural network approach to topic modeling. We calculated a sentiment score for each post using the Valence Aware Dictionary and Sentiment Reasoner. We then examined relationships between identified topics; semantic sentiment; and use-related data, including post word count and self-reported mood. Results: We identified 5 primary topics in users’ journal posts, including descriptions of specific events, professional and medical care, routine daily activities, nighttime symptoms, and bathroom/toileting issues. This 5-topic model demonstrated adequate fit to the data, having the highest coherence score (0.41) among those tested. We observed group differences across these topics in both word count and semantic sentiment. Further, posts made in the evening were both longer and more semantically positive than other times of the day. Conclusions: Users of the CareVirtue platform journaled about a variety of different topics, including generalized experiences and specific behavioral symptomology of AD/ADRD, suggesting a desire to record and share broadly across the care network. Posts were the most positive in the early evening when the tool was used habitually, rather than when writing about acute events or symptomology. We discuss the value of embedding informatics-based tools into digital interventions to facilitate real-time content delivery.

BACKGROUND As Alzheimer disease (AD) and AD-related dementias (ADRD) progress, individuals increasingly require assistance from unpaid, informal caregivers to support them in activities of daily living. These caregivers may experience high levels of financial, mental, and physical strain associated with providing care. CareVirtue is a web-based tool created to connect and support multiple individuals across a care network to coordinate care activities and share important information, thereby reducing care burden. OBJECTIVE This study aims to use a computational informatics approach to thematically analyze open text written by AD/ADRD caregivers in the CareVirtue platform. We then explore relationships between identified themes and use patterns. METHODS We analyzed journal posts (n=1555 posts; 170,212 words) generated by 51 unique users of the CareVirtue platform. Latent themes were identified using a neural network approach to topic modeling. We calculated a sentiment score for each post using the Valence Aware Dictionary and Sentiment Reasoner. We then examined relationships between identified topics; semantic sentiment; and use-related data, including post word count and self-reported mood. RESULTS We identified 5 primary topics in users’ journal posts, including descriptions of specific events, professional and medical care, routine daily activities, nighttime symptoms, and bathroom/toileting issues. This 5-topic model demonstrated adequate fit to the data, having the highest coherence score (0.41) among those tested. We observed group differences across these topics in both word count and semantic sentiment. Further, posts made in the evening were both longer and more semantically positive than other times of the day. CONCLUSIONS Users of the CareVirtue platform journaled about a variety of different topics, including generalized experiences and specific behavioral symptomology of AD/ADRD, suggesting a desire to record and share broadly across the care network. Posts were the most positive in the early evening when the tool was used habitually, rather than when writing about acute events or symptomology. We discuss the value of embedding informatics-based tools into digital interventions to facilitate real-time content delivery.