Background: Web-based surveys increase access to study participation and improve opportunities to reach diverse populations. However, web-based surveys are vulnerable to data quality threats, including fraudulent entries from automated bots and duplicative submissions. Widely used proprietary tools to identify fraud offer little transparency about the methods used, effectiveness, or representativeness of resulting data sets. Robust, reproducible, and context-specific methods of accurately detecting fraudulent responses are needed to ensure integrity and maximize the value of web-based survey research. Objective: This study aims to describe a multilayered fraud detection system implemented in a large web-based survey about COVID-19 attitudes, beliefs, and behaviors; examine the agreement between this fraud detection system and a proprietary fraud detection system; and compare the resulting study samples from each of the 2 fraud detection methods. Methods: The PhillyCEAL Common Survey is a cross-sectional web-based survey that remotely enrolled residents ages 13 years and older to assess how the COVID-19 pandemic impacted individuals, neighborhoods, and communities in Philadelphia, Pennsylvania. Two fraud detection methods are described and compared: (1) a multilayer fraud detection strategy developed by the research team that combined automated validation of response data and real-time verification of study entries by study personnel and (2) the proprietary fraud detection system used by the Qualtrics (Qualtrics) survey platform. Descriptive statistics were computed for the full sample and for responses classified as valid by 2 different fraud detection methods, and classification tables were created to assess agreement between the methods. The impact of fraud detection methods on the distribution of vaccine confidence by racial or ethnic group was assessed. Results: Of 7950 completed surveys, our multilayer fraud detection system identified 3228 (40.60%) cases as valid, while the Qualtrics fraud detection system identified 4389 (55.21%) cases as valid. The 2 methods showed only “fair” or “minimal” agreement in their classifications (κ=0.25; 95% CI 0.23-0.27). The choice of fraud detection method impacted the distribution of vaccine confidence by racial or ethnic group. Conclusions: The selection of a fraud detection method can affect the study’s sample composition. The findings of this study, while not conclusive, suggest that a multilayered approach to fraud detection that includes conservative use of automated fraud detection and integration of human review of entries tailored to the study’s specific context and its participants may be warranted for future survey research.

Increasingly popular in qualitative and mixed-methods research design, visual timelines help organize participants’ life histories with an emphasis on temporality and the context in which important life events and experiences take place. Often, research using timelines focuses on individual participants. Yet, we know that life events, experiences, and decisions that individuals highlight in life history and narrative forms of research are relational in nature. Dyadic interviews allow for participant interaction, exploration of relationality, and the potential for increased breadth and depth in data collection. Recently, LGBTQ+ researchers have begun to evaluate dyadic approaches to timeline research. This paper describes a dyadic approach to timeline development designed to be combined with dyadic narrative interviews. We explain the data elicitation process, utility and value derived from the approach, and detail the development of post hoc linear, graphic timelines. This complementary approach leverages the strengths of dyadic narrative interviews and visual qualitative data synthesis and analysis to explore shared lives in context, highlighting their value as applied in research focused on a sample of sexual minority female couples (a community in which particular types of health disparities have been documented) from across the United States engaged in a series of clinically intensive shared decisions.

Background: While the significance of care navigation in facilitating access to health care within the lesbian, gay, bisexual, transgender, queer, and other (LGBTQ+) communities has been acknowledged, there is limited research examining how care navigation influences an individual’s ability to understand and access the care they need in real-world settings. By analyzing private sector data, we can bridge the gap between theoretical research findings and practical applications, ultimately informing both business strategies and public policy with evidence grounded in real-world efficacy. Objective: The objective of this study was to evaluate the impact of specialized virtual care navigation services on LGBTQ+ individuals’ ability to comprehend and access necessary care within a national cohort of commercially insured members. Methods: This case study is based on the experience of commercially insured members, aged 18 or older, who used the LGBTQ+ Health Care Navigation (LGBTQ+ Navigation) service by Included Health between January 26 and July 31, 2023. Care coordinators assisted members by connecting them with vetted identity-affirming in-network providers, helping them navigate and understand their LGBTQ+ health benefits, and providing education and advocacy for clinical and nonclinical needs. We examined the impact of navigation on 5 member-reported outcomes. In addition to reporting the proportion who agreed or strongly agreed, we calculated an impact score that averaged assigned numerical values to all 5 question responses (1=strongly disagree to 5=strongly agree) for each respondent. We used ANOVA with Tukey post hoc tests and t tests to explore the relationships between the impact score and member characteristics, including optional self-reported demographics. Results: Out of 4703 LGBTQ+ Navigation cases, 7.53% (n=354) had member-reported outcomes. A large majority of LGBTQ+ members agreed or strongly agreed that care navigation resulted in less stress (315/354, 89%), less care avoidance (305/354, 86.2%), higher confidence in finding an identity-affirming provider (327/354, 92.4%), improved ability to comprehend health care information (312/354, 88.1%), and improved ability to engage with providers (308/354, 87%). The average impact score was 4.44 (SD 0.69), with statistically significant differences by gender identity (P=.003), race (P=.01), ethnicity (P=.008), and pronouns (P=.02). The scores were highest for members with multiple gender identities (mean 4.56, SD 0.37), and members who did not provide their race, ethnicity, or their pronouns (mean 4.55, SD 0.64). Impact scores were lowest for transgender members (mean 4.11, SD 0.95). Conclusions: The LGBTQ+ Navigation service, by enhancing members’ comprehension and use of necessary care, demonstrates potential public health utility and value. Continuous evaluation of navigation services can serve as a supplementary tool for employers seeking to promote health equity and improve belonging among employees. This is particularly important as discrimination and stigma against LGBTQ+ communities persist in the United States. Therefore, scalable and system-level changes that use navigation services are essential to reach a larger proportion of the LGBTQ+ population.