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Online surveys have become a key tool of modern health research, offering a fast, cost-effective, and convenient means of data collection. It enables researchers to access diverse populations, such as those underrepresented in traditional studies, and facilitates the collection of stigmatized or sensitive behaviors through greater anonymity. However, the ease of participation also introduces significant challenges, particularly around data integrity and rigor. As fraudulent responses—whether from bots, repeat responders, or individuals misrepresenting themselves—become more sophisticated and pervasive, ensuring the rigor of online surveys has never been more crucial. This article provides a comprehensive synthesis of practical strategies that help to increase the rigor of online surveys through the detection and removal of fraudulent data. Drawing on recent literature and case studies, we outline several options that address the full research cycle from predata collection strategies to validation post data collection. We emphasize the integration of automated screening techniques (eg, CAPTCHAs and honeypot questions) and attention checks (eg, trap questions) for purposeful survey design. Robust recruitment procedures (eg, concealed eligibility criteria and 2-stage screening) and a proper incentive or compensation structure can also help to deter fraudulent participation. We examine the merits and limitations of different sampling methodologies, including river sampling, online panels, and crowdsourcing platforms, offering guidance on how to select samples based on specific research objectives. Post data collection, we discuss metadata-based techniques to detect fraudulent data (eg, duplicate email or IP addresses, response time analysis), alongside methods to better screen for low-quality responses (eg, inconsistent response patterns and improbable qualitative responses). The escalating sophistication of fraud tactics, particularly with the growth of artificial intelligence (AI), demands that researchers continuously adapt and stay vigilant. We propose the use of dynamic protocols, combining multiple strategies into a multipronged approach that can better filter for fraudulent data and evolve depending on the type of responses received across the data collection process. However, there is still significant room for strategies to develop, and it should be a key focus for upcoming research. As online surveys become increasingly integral to health research, investing in robust strategies to screen for fraudulent data and increasing the rigor of studies is key to upholding scientific integrity.

Digital recruitment methods offer opportunities to address challenges in clinical research participation, particularly in neurology. However, the impact of digital approaches across socioeconomic and demographic groups remains inadequately understood. This study investigates the influence of sociodemographic factors on recruitment and attrition in a remote neurological research cohort, mapping participation pathways and identifying disparities to inform inclusive digital strategies. We conducted a nonexperimental, observational longitudinal cohort study at Mayo Clinic using patient-portal invitations between March and July 2024 as part of a remote speech capture study. Eligibility criteria included age 18 years and older, US residence, and English proficiency. Of 5846 invited patients, progression was tracked across checkpoints (invitation, eligibility screening, electronic consent, and task completion) using Epic (Epic Systems Corporation) to obtain demographic information, Qualtrics (Qualtrics, LLC) for screening, PTrax (a Mayo Clinic-developed Participant Tracking System) for consent tracking, and the recording platform. Socioeconomic context was assessed using the Housing-based Socioeconomic Status (HOUSES) index, where higher values indicate higher socioeconomic status, and the Area Deprivation Index (ADI), where higher values reflect greater neighborhood disadvantage. Data diagnostics included Anderson-Darling tests for non-normality and Little missing completely at random (MCAR) test to characterize missingness. Associations between participation outcomes and age, sex, urbanicity, and socioeconomic indices were examined using nonparametric tests. Exact P values and 95% CIs are reported. Analyses were conducted using BlueSky Statistics (BlueSky Statistics, LLC) and the Python SciPy package. Overall, 415 out of 5846 participants (7.1%) completed all study requirements. Completers were older (median age 66.4, IQR 56.0-72.5; 95% CI 65.1-67.6 years) than noncompleters (median age 62.8, IQR 47.5-72.7; 95% CI 62.2-63.2 years; P<.001). Participants from more socioeconomically disadvantaged neighborhoods were less likely to respond (invitation nonresponder median ADI 45.0, IQR 29.0-63.0 vs interested median ADI 42.0, IQR 27.0-59.0; P<.001), and completers had slightly lower ADI ranks than noncompleters (median 41.0, IQR 27.0-56.0 vs median 44.5, IQR 28.0-62.0; P=.04). Urban participants enrolled faster (median 32.0, IQR 9.0-58.0; 95% CI 31.0-37.0 days) than rural (median 41.0, IQR 22.0-65.0; 95% CI 37.0-49.0 days; P=.01). Female participants responded slower (median 38.5, IQR 14.8-66.3; 95% CI 35.0-41.0 days) than males (median 32.0, IQR 8.0-57.5; 95% CI 29.0-38.0 days; P=.01). No significant differences were observed for the HOUSES index, and device type was unrelated to completion or timelines. Missingness for key variables was completely at random (MCAR χ²3=3.45; P=.24). Digital recruitment does not overcome traditional barriers to participation and may introduce new disparities related to age, urbanicity, and neighborhood disadvantage. These findings inform inclusive digital research strategies, including multichannel outreach, age-specific engagement, and rural technical support. This study applies longitudinal pathway analysis to digital neurology recruitment, offering actionable insights for improving inclusivity in remote research.

Annual lung cancer screening (LCS) can decrease lung cancer-related mortality by finding cancer at earlier, more treatable stages, yet uptake remains abysmally low in the United States, especially among adults who seldom interact with the health system. Many eligible individuals are unaware that LCS exists, underscoring the critical need for scalable, population-level communication strategies that increase awareness and engagement. The aim of this study was to evaluate reach, as defined by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, as the extent to which the target population comes in contact with a social media-based strategy, Facebook-targeted advertisement (FBTA), designed to connect LCS-eligible individuals in the United States with a digital health communication message. The advertisement served as a digital outreach strategy for promoting engagement with LungTalk, an evidence-based intervention aimed at increasing awareness and informed decision-making about LCS. As part of the INSPIRE-Lung Study (INnovating Social Media for Prevention: LUNG Cancer Screening Awareness, Knowledge, and Uptake), 5 FBTA campaigns were launched over a 79-day period throughout the United States. Advertisements targeted adults aged 50-80 years with interests related to smoking or smoking cessation and linked to a study website where participants could complete an eligibility screener and learn more about the trial. Facebook analytics were used to assess reach, defined by the number, proportion, and demographic characteristics of individuals exposed to and interacting with FBTA content. Key metrics included total reach, impressions, link clicks, and cost-efficiency. The FBTA campaigns reached 1,048,191 unique users and generated 3,109,482 impressions (total advertisement displays, including repeat exposures to the same user). A total of 24,816 individuals clicked on the advertisements (2.37% click-through rate), and 7117 completed the eligibility screener. Of those eligible, 1272 (17.9%) met lung screening criteria, and of these, 483 (38% participation rate) enrolled in the trial. The cost per click was US $0.40, and the cost per enrolled participant was US $19.46. Individuals reached via FBTA were demographically diverse and included many who may be disconnected from traditional health care systems. FBTA is a scalable, cost-effective strategy to achieve population-level reach of LCS-eligible adults. By conceptualizing reach as exposure to an upstream digital message rather than enrollment alone, this study illustrates how social media can broaden population access to evidence-based cancer prevention tools such as LungTalk. Future research should explore embedding intervention content directly into social media platforms and tracking downstream clinical outcomes.

The All of Us Research Program (AoURP) is a prominent precision medicine research initiative committed to diverse participation. The program harnesses digital outreach as a key strategy for recruiting and retaining underrepresented populations, using language that sometimes invokes notions of solidarity. This targeted recruitment of underrepresented groups and potential use of solidaristic language raise concerns about how participation will manifest tangible benefits for these populations and whether institutions assume responsibility for addressing past and present research harms. This study examines how the AoURP conceptualizes \"diversity\" in its social media outreach and how this implementation aligns with the program's stated goals. Specifically, we perform a mixed methods analysis to descriptively capture (1) which underrepresented populations are targeted by the AoURP's social media and (2) how solidaristic messaging is used, if at all, in these calls for participation. AoURP social media posts (n=380) from a 6-month period in 2020-2021 were coded to identify visual depictions and explicit mentions of any \"underrepresented in biomedical research\" (UBR) categories officially targeted by the program. To then characterize UBR-specific appeals, we performed a thematic analysis of UBR-targeted posts, using a coding scheme that identified unsolidaristic language (ie, appeals to individual benefits) and solidaristic language (ie, appeals to benefitting others, attaining shared goals, and addressing injustices). Among the 10 UBR categories officially recognized by the AoURP, \"Race and Ethnicity\" (187/380, 49% of posts) and \"Age\" (71/380, 19%) were the most frequently emphasized, while each of the other remaining categories was rarely invoked (<4/380, 1%). The thematic analysis further identified calls to participate that spanned receiving genetic results (ie, individual benefits), uncovering family and community disease predispositions (ie, benefitting others), improving the future of health (ie, achieving shared goals), and addressing data and health disparities (ie, resolving injustices). In addition to highlighting UBR categories that are more and less emphasized in the AoURP's social media outreach, we also find that the program's messaging indeed resembles a solidaristic appeal to participate. Drawing upon the existing literature on solidarity, we leverage conceptualizations of solidarity as a shared practice grounded in mutuality and bidirectionality to question the AoURP's appeals when institutions fail to fully reciprocate this solidarity. Specifically, we raise concerns about (1) unclear links between participation and addressing health disparities, (2) incomplete acknowledgment of institutions' role in data disparities, and (3) the use of empowerment rhetoric that diverts the onus for correcting these disparities onto participants. Finally, we consider the implications of these issues for future outreach efforts.

The integration of social media into human subjects research offers significant opportunities for data collection, disease surveillance, and participant recruitment. However, it also poses a number of ethical challenges. This article evaluates the dual nature of social media as a research tool, highlighting its potential benefits while also addressing concerns about exacerbating health disparities, compromising participant privacy and confidentiality, challenging expectations around participant disclosure, and perpetuating discriminatory practices. By exploring issues related to equity and privacy, this article discusses the implications of digital recruitment and online behavioral advertising, underscoring the vital role of institutional review boards in ensuring ethical standards are upheld. Furthermore, this work proposes key strategies for researchers and regulatory authorities, emphasizing community engagement, transparency, and inclusive recruitment practices. The analysis aims to guide stakeholders in navigating the ethical complexities of digital research, fostering transparency, trust, and accountability in the realm of human subjects research.

Randomized controlled trials (RCTs) face challenges such as limited generalizability, insufficient recruitment diversity, and high failure rates, often due to restrictive eligibility criteria and inefficient patient selection. Large language models (LLMs) have shown promise in various clinical tasks, but their potential role in RCT design remains underexplored. This study investigates the ability of LLMs, specifically GPT-4-Turbo-Preview, to assist in designing RCTs that enhance generalizability, recruitment diversity, and reduce failure rates, while maintaining clinical safety and ethical standards. We conducted a noninterventional, observational study analyzing 20 parallel-arm RCTs, comprising 10 completed and 10 registered studies published after January 2024 to mitigate pretraining biases. The LLM was tasked with generating RCT designs based on input criteria, including eligibility, recruitment strategies, interventions, and outcomes. The accuracy of LLM-generated designs was quantitatively assessed by 2 independent clinical experts by comparing them to clinically validated ground truth data from ClinicalTrials.gov. We have conducted statistical analysis using natural language processing-based methods, including Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation (ROUGE)-L, and Metric for Evaluation of Translation with Explicit ORdering (METEOR), for objective scoring on corresponding LLM outputs. Qualitative assessments were performed using Likert scale ratings (1-3) for domains such as safety, clinical accuracy, objectivity or bias, pragmatism, inclusivity, and diversity. The LLM achieved an overall accuracy of 72% in replicating RCT designs. Recruitment and intervention designs demonstrated high agreement with the ground truth, achieving 88% and 93% accuracy, respectively. However, LLMs showed lower accuracy in designing eligibility criteria (55%) and outcomes measurement (53%). Natural language processing statistical analysis reported BLEU=0.04, ROUGE-L=0.20, and METEOR=0.18 on average objective scoring of LLM outputs. Qualitative evaluations showed that LLM-generated designs scored above 2 points and closely matched the original designs in scores across all domains, indicating strong clinical alignment. Specifically, both original and LLM-based designs ranked similarly high in safety, clinical accuracy, and objectivity or bias in published RCTs. Moreover, LLM-based design ranked noninferior to original designs in registered RCTs in multiple domains. In particular, LLMs enhanced diversity and pragmatism, which are key factors in improving RCT generalizability and addressing failure rates. LLMs, such as GPT-4-Turbo-Preview, have demonstrated potential in improving RCT design, particularly in recruitment and intervention planning, while enhancing generalizability and addressing diversity. However, expert oversight and regulatory measures are essential to ensure patient safety and ethical standards. The findings support further integration of LLMs into clinical trial design, although continued refinement is necessary to address limitations in eligibility and outcomes measurement.

Recruitment to population-based health studies remains challenging, with difficulties meeting target participant numbers, biosample returns, and achieving a representative sample. Few studies provide evaluations of traditional and web-based recruitment methods particularly for studies with broad inclusion criteria and extended recruitment periods. Generation Scotland (GS) is a family-based cohort study that initiated a new wave of recruitment in 2022 using web-based data collection and remote saliva sampling (for genotyping). Here, we provide an overview of recruitment strategies used by GS over the first 18 months of new recruitment, highlighting which proved most effective and cost-efficient in order to inform future research. This study evaluated recruitment strategies using four main outcomes: (1) absolute recruitment numbers, (2) sociodemographic representativeness, (3) biosample return rate, and (4) cost per participant. Between May 2022 and December 2023, recruitment was undertaken via snowball recruitment (through friends and family of existing volunteers), invitations to those who participated in a previous survey (CovidLife: the GS COVID-19 impact survey), and Scotland-wide recruitment through social media (including sponsored Meta-advertisements), news media, and TV advertisement. The method of recruitment was self-reported in the baseline questionnaire. We present absolute recruitment numbers and sociodemographic characteristics by recruitment method and evaluate the saliva sample return rate by recruitment strategy using chi-square tests. The overall cost and cost per participant were calculated for each method. In total, 7889 new participants joined the cohort over this period. Recruitment sources by contribution were social media (n=2436, 30.9%), survey responder invitations (n=2049, 26.0%), TV advertising (n=367, 17.3%), snowball (n=891, 11.3%), news media (n=747, 9.5%), and other methods or unknown (n=399, 5.0%). More females signed up than males (5570/7889, 70.5% female). To date, 83.5% (6543/7836) of participants returned their postal saliva sample, which also varied by demographic factors (3485/3851, 90.5% older than 60 years vs 471/662, 71.1% aged 16-34 years). Average cost per participant across all recruitment strategies was £13.52 (US $16.82). Previous survey recontacting was the most cost-effective (£0.37 [US $0.46]), followed by social media (£14.78 [US $18.39]), while TV advertisement recruitment was the most expensive per recruit (£33.67 [US $41.89]). This study highlights both the challenges and the opportunities in large web-based cohort recruitment. Overall, social media advertising has been the most cost-effective and easily sustained strategy for recruitment over the reported recruitment period. We note that different strategies resulted in successful recruitment over varying timescales (eg, consistent sustained recruitment for social media and large spikes for news media and TV advertising), which may be informative for future studies with different requirements of recruitment periods. Limitations include self-reported methods of recruitment and difficulties in evaluating multilayered recruitment. Overall, these data demonstrate the potential cost requirements and effectiveness of different strategies that could be applied to future research studies.

Menstrual complaints are widespread but often stigmatized. The most common is dysmenorrhea, or menstrual cramps, which manifests as mild to severe pain during menstruation and affects >40% of women throughout their reproductive lifespan. Dysmenorrhea is often endured silently or managed through self-medication. Consequently, a vast majority of patients with dysmenorrhea may not be found in medical practices, highlighting the need for direct-to-patient communication to reach a broad and diverse patient population. Primarily, this study aims to reveal the diagnosis status, pain levels, comorbidities, eligibility, and willingness to participate in clinical trials of women affected by dysmenorrhea and menstrual discomfort, based on a broad patient population not necessarily reached in medical practices. Second, this study attempts to test the effectiveness of direct-to-patient communication via online campaigns in engaging patients affected by dysmenorrhea or conditions that may benefit from direct-to-patient communication. Women experiencing menstrual pain were reached through a targeted online campaign using Google Ads (Google LLC) and Facebook (Meta Platforms, Inc) in Germany, Austria, and Poland and were surveyed from April to June 2023. This study is observational. We surveyed 3546 women, 94.6% (3230/3413) of whom reported symptoms consistent with dysmenorrhea, highlighting the high specificity of the Google and Facebook campaigns. Of the affected women in Germany and Austria, 88.5% (874/988) reported pain levels of 6 or higher on a scale of 0 to 10, with even higher pain levels observed in Poland. Elevated pain levels were correlated with dysmenorrhea symptoms but not with premenstrual syndrome (PMS) symptoms. Notably, of the 3230 women reporting symptoms consistent with dysmenorrhea, only 4.6% (n=149) reported being diagnosed with the condition, regardless of elevated pain levels. This can be attributed to two factors: (1) 90.3% (3065/3395) of surveyed women did not seek medical advice, were uncertain about their diagnosis, or their menstrual-related symptoms were not recognized as pathological and (2) among the 9.7% (330/3395) diagnosed, only half of DYS-affected women (149/318, 46.9%) were diagnosed with dysmenorrhea. The other 53.1% (169/318) were diagnosed with PMS but not dysmenorrhea despite regularly experiencing dysmenorrhea symptoms. The situation was better for PMS. Among the 330 diagnosed women, 77.3% (n=255) were diagnosed with PMS, in line with the 80.1% (2729/3409) PMS prevalence in the survey population. Overall, about 8.6% (235/2729) of women with PMS symptoms reported having been diagnosed with PMS, nearly double the diagnosis rate reported for dysmenorrhea. The data reveal a significant diagnostic gap for dysmenorrhea, but not necessarily for PMS, even in high-income countries, as observed in Germany, Austria, and Poland. In these 3 countries, most dysmenorrhea-affected women do not seek medical advice, and up to half of dysmenorrhea diagnoses might be missed. Thus, most affected women might not be found in medical settings (doctors' offices and clinics) despite experiencing significant pain. Online campaigns are shown to effectively reach individuals with menstrual complaints, including those who are undiagnosed or not seeking medical care.

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are genetically mediated, life-threatening reactions usually caused by a medication in adults. These genetic associations promise an opportunity for pre-prescription screening, prevention, and understanding influences at a population level. Importantly, older adults disproportionally face more severe SJS/TEN reactions and higher mortality rates. However, the study of genetic risk and long-term sequelae of SJS/TEN across racially diverse populations and age groups is hampered by many factors, including rarity, social disparities, and trust in health care and providers, impacting access to hospital- and clinic-based research studies. This paper aims to explore the utility of multiple social media and web-based search tools to increase study enrollment numbers, diversity, and inclusivity of all populations and ages in the SJS Survivor Study. The community-based SJS/TEN Survivor Study remotely recruited drug-induced SJS/TEN survivors in the United States. The aims were to help determine genetic risk and long-term outcomes of SJS/TEN. Baseline recruitment included advertisements through the SJS Foundation website and American Burn Association newsletter. Two years into the study, in hopes of improving accessibility and enrollment diversity, social media ads were introduced on the Vanderbilt University Medical Center (VUMC) Facebook and Instagram accounts. Posts were created using flyers and 60-second SJS/TEN survivor video vignettes. Finally, we launched a nationwide Google Ad campaign. To understand the impact of the additional online advertising, we measured the change in registration in both the study interest and the effectiveness of implementation of specific social media and web-based search tools before and after implementation. With the introduction of social media and Google Ads, we report a 48.6% increase in enrollment overall and a 289.5% increase in participation interest. We noticed the ads were accessible to all age groups and notably reported a more even age distribution of enrolled participants from 18 through 74 years, with an average of 15% enrolled in each age category. The largest increase in any age category was seen in the 65- to 74-year-old patients (n=19), with 16.5% of the age distribution. The most significant increase in enrollment and diversity of responses came from Google Ads, with a total of 201 expressions of interest, from 56 enrolled participants, 33% of which self-identified as non-White. VUMC Facebook ads had an enrollment rate of 15.3%, and VUMC Instagram ads saw an enrollment rate of 14.3%. Social media and web-based search tools differ in their enrollment effectiveness. Google Ads were found to be the most effective advertisement for recruitment in this community-based study. Each of the social media and web-based strategies used increased enrollment numbers, accessibility to more age ranges, and diversity of enrollment. They show promise as tools to improve inclusion and enrollment in rare disease research such as SJS/TEN.

Digital health interventions (DHIs) can broaden the reach of HIV prevention interventions and overcome barriers for young cisgender men who have sex with men (YMSM). Community-based organizations (CBOs) have delivered HIV prevention interventions for decades, but few studies have examined how CBOs implement DHIs, including recruitment and retention. Keep It Up! (KIU!) is a Centers for Disease Control and Prevention-designated best-evidence DHI that can promote risk reduction behaviors and reduce sexually transmitted infection incidence. We sought to descriptively assess CBOs' approaches to recruitment and retention, elucidate lessons learned, and provide examples of recruitment and retention for future implementers. Twenty-two CBOs in counties with high HIV rates and large proportions of YMSM were selected through a request for proposal process to implement KIU!. Data were extracted from request for proposal applications and notes from monthly calls with CBO staff. Twenty-five staff members across CBOs were interviewed in the middle of implementation. A descriptive thematic analysis of the lessons learned in recruiting and retaining participants was performed. The research team developed an application dashboard for CBO staff to register participants, track participant progress through the intervention, record and track participant contact, and export usage data. CBO logins to the KIU! dashboard were tracked across the implementation. To descriptively compare approaches to recruitment and retention, the study team divided CBOs according to annual HIV testing volume in the 3 years prior to implementation and years of HIV service provision to YMSM. The most frequent modes of recruitment were outreach and community partnerships (21/22, 95%), and the least frequent modes were via hook-up apps (6/22, 27%) and participant referrals (5/22, 23%). CBOs with a low HIV testing volume used online recruitment slightly more frequently, while medium-volume CBOs most frequently used hook-up apps for recruitment. Low-volume CBOs more frequently used phone calls and emails to remind participants to complete intervention modules, while high- and medium-volume CBOs more frequently used text messages. CBOs with more years of HIV service provision to YMSM more frequently had a set reminder schedule for contact with participants. CBO staff identified a need to change how KIU! is pitched to clients by using personalized, recipient-centered language rather than technical jargon. CBOs changed intake forms to ensure that staff remembered to offer KIU! to participants. CBOs had a difficult time retaining participants despite holding in-person events for enrolled participants (eg, raffles and trivia nights) and altering the frequency with which they reminded participants to complete modules. Although CBOs had experience in implementing other evidence-based interventions with YMSM, there was no consensus on successful recruitment and retention strategies for this population. We have presented approaches that future CBOs may use in their own implementation of KIU!.