Incentives are a cornerstone of attracting and retaining participants in clinical research studies. 1 They serve as compensation for the time and effort individuals dedicate to the research process. 1 However, previous randomized clinical trials found incentivizing was not associated with increased rates of clinical trial recruitment. 2 , 3 Furthermore, the rate participants redeem these incentives can vary considerably. 1 , 4
Although numerous methods have been used to increase trial recruitment, no studies have been conducted to explore factors associated with incentive redemption, regardless of clinical area. Understanding the factors that influence redemption is crucial for researchers to optimize research recruitment and follow‐up strategies. 5 First, it allows for a more strategic allocation of research funds toward participant compensation. 1 By identifying what influences redemption rates, researchers can optimize incentive structures to maximize participation while staying within budgetary constraints. Second, knowledge of these factors can help identify potential barriers associated with the redemption process itself. 5 For example, a cumbersome or inconvenient redemption method might discourage participants from claiming their reward, which may discourage future participation. Finally, this knowledge can inform the development of more effective incentive strategies. Researchers can enhance their motivational impact and improve overall study enrollment by tailoring incentives to specific participant demographics or preferences.
Our objective was to identify key variables influencing whether participants successfully claimed their rewards in a multicenter, prospective syncope study. This information can then be used to refine incentive programs and ultimately lead to more efficient and effective research processes.
We conducted a secondary analysis using a federally funded, multicenter prospective cohort study, Practical Approaches to Care in Emergency Syncope (PACES, NCT04533425). The PACES study was conducted at six urban academic medical centers across three states: New York, Tennessee, and California. The objective was to externally validate two syncope risk‐stratification tools, the Canadian Syncope Risk Score and the FAINT score. 6 , 7 Adults aged 40 or older who presented to the emergency department (ED) following an episode of syncope or presyncope between August 2021 and September 2023 were included. We prepared and reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Ethical approvals were obtained from the institutional review boards (IRB) at enrolling sites. Patient confidentiality was preserved by using anonymous health information.
Data from the PACES database included patient demographics, participating sites, and incentive status information. For the PACES study, TruCentive, a platform specializing in incentive programs, was used. Participants who consented to enroll and completed telephone follow‐up 30 days after their ED visits received two digital gift cards of $25 each. The gift card was electronically sent via cell phone or email. Participants could choose from six different retail vendors for each gift card code: Amazon, Walmart, Target, CVS, Bed Bath & Beyond, and Whole Foods Market. The redemption codes automatically expired after 6 months, and up to three reminders were sent out during this time. Research coordinators were available by phone to assist participants with the gift card redemption. Participants enrolling in Rochester, New York, were given a single $50 gift card code upon consenting to participate in this study, in contrast to participants at other sites who received two $25 gift cards, once after giving their consents and another after the 30‐day follow‐up, due to local IRB requirements. We collected data on demographic factors and redemption of gift cards from the PACES and TruCentive databases. We also assessed the participants' Area Deprivation Index (ADI), a composite measurement of neighborhood socioeconomic disadvantage, using the patient's home address. The primary outcome was any redemption of the electronic gift cards. We explored factors associated with incentive redemption status.
All analyses were conducted using STATA MP, Version 16 (StataCorp). Categorical variables were reported using frequencies and percentages, while continuous variables were reported using mean with standard deviation or median with interquartile range (IQR). ADI was reported by the participant's national and state rank and was categorized as quintile. Multiple logistic regression was used to estimate the association between participants’ factors and redeemed incentive status adjusted for demographic factors (including age, gender, race, and ethnicity), enrolling state, ADI national rank, and payment type. Crude and adjusted odds ratios (ORs) with their corresponding 95% confidence intervals (CIs) were presented. All tests were two‐sided, and a p‐value of less than 0.05 was considered statistically significant.
A total of 586 participants were sent electronic gift cards and included in this study. Of these, 390 (67%, 95% CI 63%–70%) redeemed monetary incentives at least once (out of two cards offered). The median (IQR) age was 65 (57–74) years, and the majority were female (55%), White (39%), and non‐Hispanic/Latino (60%). Among ADI groups, most participants (47%) had the top ADI national quintile rank (least disadvantaged). Age was the only factor found to be associated with incentive redemption. Participants aged 60–69 years (adjusted odds ratio [aOR] 0.5, 95% CI 0.3 to 0.9), 70–79 years (aOR 0.3, 95% CI 0.1 to 0.5), and ≥80 years (aOR 0.3, 95% CI 0.1 to 0.5) were significantly less likely to redeem incentives compared to participants aged 40–49. Table 1 summarizes the characteristics of included participants and aORs of incentive redemption.
TABLE 1.
Characteristics of included participants aORs of incentive redemption.
| Characteristics | Overall (n = 586) | Incentive redemption (n = 390) | No incentive redemption (n = 196) | Chance of incentive redemption | ||
|---|---|---|---|---|---|---|
| Unadjusted OR (95% CI) | aOR (95% CI) | p‐value | ||||
| Age (years), median (IQR) | 65 (54–74) | 63 (52–72) | 69 (60–76) | — | — | — |
| Age category (years) | ||||||
| 40–49 | 95 (16) | 78 (20) | 17 (9) | Reference | Reference | — |
| 50–59 | 116 (20) | 84 (22) | 32 (16) | 0.6 (0.3–1.1) | 0.6 (0.3–1.2) | 0.13 |
| 60–69 | 155 (26) | 105 (27) | 50 (26) | 0.5 (0.2–0.9) | 0.5 (0.3–0.9) | 0.03 |
| 70–79 | 154 (26) | 87 (22) | 67 (34) | 0.3 (0.2–0.5) | 0.3 (0.1–0.5) | <0.001 |
| ≥80 | 66 (11) | 36 (9) | 30 (15) | 0.3 (0.1–0.5) | 0.3 (0.1–0.5) | <0.001 |
| Gender – male | 262 (45) | 170 (44) | 92 (47) | 0.9 (0.6–1.2) | 0.8 (0.6–1.2) | 0.38 |
| Race | ||||||
| White | 227 (39) | 165 (42) | 62 (32) | Reference | Reference | — |
| Black/African American | 141 (24) | 87 (22) | 54 (28) | 0.6 (0.4–0.9) | 0.6 (0.4–1.1) | 0.09 |
| Others | 41 (7) | 27 (7) | 14 (7) | 0.7 (0.4–1.5) | 0.8 (0.3–1.8) | 0.56 |
| Preferred not to state | 177 (30) | 111 (28) | 66 (34) | 0.6 (0.4–1.0) | 1.1 (0.6–2.2) | 0.67 |
| Ethnicity | ||||||
| Non‐Hispanic/Latino | 353 (60) | 252 (65) | 101 (52) | Reference | Reference | — |
| Hispanic/Latino | 233 (40) | 138 (35) | 95 (48) | 0.6 (0.4–0.8) | 0.6 (0.3–1.0) | 0.07 |
| Participating site (by state) | ||||||
| New York | 469 (80) | 310 (79) | 159 (81) | Reference | Reference | — |
| Tennessee | 59 (10) | 39 (10) | 20 (10) | 1.0 (0.6–1.8) | 0.9 (0.4–1.9) | 0.81 |
| California | 58 (10) | 41 (11) | 17 (9) | 1.2 (0.7–2.2) | 1.2 (0.6–2.3) | 0.68 |
| Area deprivation index national rank: quintile | ||||||
| 1st (1–20): least disadvantaged | 269 (47) | 172 (45) | 97 (50) | Reference | Reference | — |
| 2nd (21–40) | 169 (29) | 102 (27) | 67 (35) | 0.9 (0.6–1.3) | 0.8 (0.5–1.2) | 0.30 |
| 3rd (41–60) | 51 (9) | 39 (10) | 12 (6) | 1.8 (0.9–3.7) | 1.3 (0.6–2.8) | 0.57 |
| 4th (61–80) | 48 (8) | 39 (10) | 9 (5) | 2.4 (1.1–5.3) | 1.2 (0.5–3.1) | 0.69 |
| 5th (81–100) | 40 (7) | 31 (8) | 9 (5) | 1.9 (0.9–4.2) | 1.1 (0.4–2.9) | 0.81 |
| ADI state rank: quintile a | ||||||
| 1st (1, 2): least disadvantaged | 152 (26) | 101 (26) | 51 (26) | Reference | — | — |
| 2nd (3, 4) | 107 (19) | 68 (18) | 39 (20) | 0.9 (0.5–1.5) | — | — |
| 3rd (5, 6) | 145 (25) | 81 (21) | 64 (33) | 0.6 (0.4–1.0) | — | — |
| 4th (7, 8) | 86 (15) | 61 (16) | 25 (13) | 1.2 (0.7–2.2) | — | — |
| 5th (9, 10) | 87 (15) | 72 (19) | 15 (8) | 2.4 (1.3–4.6) | — | — |
| Payment category type | ||||||
| Two codes ($25 each) | 482 (82) | 304 (78) | 178 (91) | Reference | Reference | — |
| Single code (a total of $50) | 104 (18) | 86 (22) | 18 (9) | 2.8 (1.6–4.8) | 2.1 (0.9–4.8) | 0.08 |
Note: Values are numbers with (percentages) in parentheses unless stated otherwise (percentages have been rounded and may not equal 100).
Abbreviations: ADI, Area Deprivation Index; aOR, adjusted odds ratio.
Not included in the multivariable model.
Although incentives such as gift cards are crucial for attracting and retaining participants in clinical research, 3 up to one‐third of participants in our study who received gift cards did not redeem them. This underscores the importance of understanding and addressing barriers to incentive redemption to ensure that these rewards effectively contribute to participant engagement.
To our knowledge, this is the first study to explore the factors associated with incentive redemption. Several factors may contribute to the nonredemption of electronic gift cards. 8 These could include logistic challenges, such as technical difficulties accessing or navigating the redemption process or personal circumstances that hinder participants from utilizing the incentives within the allotted time frame. Addressing the issue of nonredemption requires a multidimensional approach and would be valued for future studies.
Interestingly, age was found to be a strong predictor of incentive redemption. Older individuals tended not to redeem incentives despite participating in the study and receiving digital gift cards. Unfortunately, remarkably little data exist on what influences older adults to redeem incentives. 9 Previous literature suggested that the following have been shown to affect their decision making about incentives: emotional regulations, changes in executive function, and age‐related cognitive declines. 9 Future studies should investigate the underlying factors contributing to the lower redemption rates among older adults. Furthermore, exploring alternative financial incentives tailored to the preferences and needs of older adults, such as physical gift cards, may be warranted. Electronic gift cards may not resonate with older adults due to factors such as technological barriers, limited familiarity with digital platforms, or preferences for nonmonetary rewards. 10 Offering alternative options, such as services, transportation assistance, or contributions to charitable organizations, may be more appealing and motivating for them.
Several limitations should be acknowledged. First, the study's design precludes causal inference regarding the relationship between demographic factors and incentive redemption. Second, the PACES study focuses on syncope patients, skewing the population toward older adults, therefore limiting the generalizability of the findings. Furthermore, we did not explore participants’ reasons for nonredemption, which could provide valuable insights into barriers and challenges affecting incentive redemption. Qualitative research methods, such as interviews or focus groups, could be employed to explore the attitudes, perceptions, and experiences of older participants regarding incentive redemption. Addressing these limitations in future research is crucial for advancing our understanding of incentive redemption behavior and developing more effective strategies to optimize participant engagement and resource allocation.
Our findings underscore the critical importance of understanding and addressing barriers to incentive redemption. Up to one‐third of all participants did not redeem the offered incentives. Age was found to be a strong predictor of incentive redemption. Older individuals tended not to redeem incentives despite participating in the study and receiving digital gift cards. Future studies are needed to describe and explore reasons to address this issue, and alternative financial incentives may be warranted for older adults.
AUTHOR CONTRIBUTIONS
Wachira Wongtanasarasin, Daniel K. Nishijima, Nancy Wood, John DeAngelis, Alan Storrow, Jonathan Schimmel, Nataly Beltre, Dana Sacco, and Marc A. Probst conceptualized the study design and concept. Wachira Wongtanasarasin, Daniel K. Nishijima, Nataly Beltre, and Marc A. Probst contributed to the data acquisition. Wachira Wongtanasarasin, Daniel K. Nishijima, and Marc A. Probst contributed to the analysis and interpretation of the data. Wachira Wongtanasarasin drafted the manuscript. Daniel K. Nishijima and Marc A. Probst supervised, critically revised, and edited the manuscript. All authors contributed to its revision and approved the final manuscript.
FUNDING INFORMATION
The PACES study was supported by the National Heart, Lung, and Blood Institute (R01HL149680).
CONFLICT OF INTEREST STATEMENT
MP is currently supported by an R01 grant from the NIH/NHLBI (R01HL149680) and received a one‐time research donation from Roche Diagnostics in 2023.
ACKNOWLEDGMENTS
The authors acknowledge all PACES study staff who supported implementing, monitoring, and evaluating the 30‐day telephone follow‐up. The PACES study is supported by a grant from the NIH/NHLBI (R01 HL149680). The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number UL1 TR001860. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Wongtanasarasin W, Nishijima DK, Wood N, et al. Factors associated with incentive redemption among participants in a multicenter prospective syncope clinical study. Acad Emerg Med. 2024;31:1276‐1279. doi: 10.1111/acem.14979
Presented at the Society for Academic Emergency Medicine (SAEM) Annual Meeting, Phoenix, AZ, May 2024.
Supervising Editor: Shellie Asher
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