The effect of remuneration schedule on data completion and retention in the Pregnancy Eating Attributes Study (PEAS)

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Lipsky, Anna Maria Siega-Riz, Aiyi Liu, Tonja R. Nansel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.17853/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Maximizing data completion and study retention is essential in population research. There is scant research to inform how remuneration schedules and data collection modality influence participant data completion and retention. Purpose: We examined the effect of remuneration schedule and data collection modality on data completion and retention in the Pregnancy Eating Attributes Study (PEAS) cohort. Methods: Participants (n=458) completed self-administered surveys and diet recalls online and attended six study visits. Initially, remuneration was a prespecified amount per visit (lump sum). The remuneration schedule was changed mid-study to be based on the number of forms completed (pro-rated). Survey data collection modality was changed to in-person at the 1-year postpartum visit. Remuneration schedule as a predictor of withdrawal by visit was modeled using Poisson regression; differences in retention at 1-year postpartum were examined by t-test. Differences in survey and diet record completion were determined by t-test, analysis of covariance, and logistic regression. Results: There was no significant difference in the time to withdrawal and no interaction of visit with remuneration schedule on withdrawal. Survey and diet recall completion were significantly lower under prorated remuneration at the first visit but did not significantly differ at subsequent visits. Survey completion at 1-year postpartum was significantly higher for in-person versus online completion. Conclusions: Findings suggest that remuneration schedule and data collection modality can impact completion of self-reported assessments. Further research is needed to understand how remuneration and data collection practices intersect with diverse populations to influence data completion and retention. Health Economics & Outcomes Research pregnancy remuneration data completion retention BACKGROUND Participants in research studies are typically provided with monetary remuneration as compensation for their time and effort. Remuneration may influence participation, data completion, or study retention [ 1 – 4 ], thereby impacting internal and external validity. Furthermore, recent advances in technology have facilitated the expansion of off-site, participant-initiated data collection, but whether this data collection modality impacts data completion or participant retention is unknown. Understanding how remuneration and data collection modality influence recruitment, retention, and data completion is critical for informing the most efficient and cost-effective design of human subjects’ research. Participant remuneration is typically distributed via a predetermined schedule based on the time and effort associated with participation (e.g. assessment time, cost of transportation, childcare, etc.), and evidence suggests that adequate remuneration may be critical to incentivize study participation [ 5 – 8 ] and retention [ 9 ]. Remuneration schedule, which refers to the system of dispersal of funds to participants throughout a study, varies across studies [ 10 ]. Remuneration may be provided conditionally (i.e. only after the completion of certain study tasks) in either a lump sum at a single time point or piecemeal, or as a prespecified amount paid unconditionally (i.e. not study task dependent) throughout the study according to milestones (i.e. number of visits completed) as specified by an institution’s human subjects’ review board (IRB). Another approach is to enter participants into a lottery for a gift card or monetary reward, if allowed by the IRB. To our knowledge, no studies have investigated how different payment schedules affect data completion and retention. Additionally, studies use different strategies to collect data that may impact participant retention and data completion. Self-report measures may be collected, for example, at a central study location, at in-home assessments conducted by research staff, by telephone, or via participant self-administered online assessments. In-person survey completion at a central location may improve efficiency from the investigator’s perspective but necessitates physical space and on-site staffing and requires participant effort in terms of scheduling, and transportation and parking. Alternatively, off-site participant-initiated survey completion via secure website or applications may be more flexible and reduce participant burden associated with attending study visits at a central location but may also increase susceptibility to distraction and competing priorities and increase the cognitive burden associated with initiating and completing assessments. Differences in these data collection modalities may impact participant retention and data completion. However, this has not been empirically investigated. The purpose of this secondary analysis was to investigate the effect of remuneration schedule and data collection modality on participant data completion and retention in the Pregnancy Eating Attributes Study (PEAS). PEAS enrolled a cohort of women ≤ 12 weeks gestation to study eating behaviors and weight change from pregnancy through one-year postpartum. All participants were drawn from the same source population; however, two changes to study procedures were made based on findings from ongoing data collection monitoring. Because initial data completion rates during pregnancy assessments were lower than anticipated, the remuneration schedule was changed mid-study. Those recruited early in the study received a prespecified remuneration amount at each study visit regardless of how many self-initiated online forms they completed. Participants recruited later in the study were paid conditionally for each online form they completed. Additionally, in response to poorer completion of self-initiated, off-site online surveys during postpartum, data collection procedures were changed, and the number of required surveys were reduced for the final study visit such that participants completed surveys at the in-person assessment. These changes in study procedures facilitate an investigation into whether differences in remuneration schedule impacted data completion or withdrawal, and whether in-person versus off-site participant-initiated data collection modality influenced data completion. SUBJECTS AND METHODS Study design and participants PEAS was a prospective observational study of 458 healthy pregnant women recruited at ≤ 12 weeks gestation and followed through 1-year postpartum. Details of study recruitment and methods have been published elsewhere [ 11 ]. Participants were recruited from women receiving prenatal care at two obstetrics clinics in the University of North Carolina at Chapel Hill Healthcare System. Inclusion criteria were: confirmed pregnant ≤ 12 weeks gestation at enrollment; uncomplicated singleton pregnancy anticipated; age 18–45 years at screening; willingness to undergo study procedures and provide informed consent for her participation and assent for the baby’s participation; BMI ≥ 18.5 kg/m 2 ; able to complete self-report assessments in English; access to internet with email; plan to deliver at the UNC Women’s Hospital; and plan to remain in the geographical vicinity of the clinical site for 1 year following delivery. Exclusion criteria included pre-existing diabetes; multiple pregnancy; participant-reported eating disorder; any chronic illnesses or use of medication that could affect diet or weight; psychosocial condition hindering participation in the study. Recruitment occurred from November 2014 to December 2016. Data collection was completed in August 2018. Protocols including modifications to the mode and remuneration were approved by the UNC IRB. Anthropometrics and biospecimens were collected at in-person study visits once per pregnancy trimester and 3 times between delivery up to 1 year postpartum. Participants were also asked to complete self-administered online surveys on eating- and health-related behaviors and a 24-hour dietary recall outside of study visits via a secure study website. Participants logged on to the website with their username and password within specified time windows around each visit (at 6–12 weeks, 16–27 weeks, and 28–36 weeks gestation; and at 4–14 weeks, 23–31 weeks, and 50–58 weeks postpartum). The website listed all required surveys for that window, with a link to the online survey form, and participants could complete them all at once or across multiple logins. When the visit window closed, the surveys were no longer accessible. Completion of the surveys and 24-hour dietary recalls were monitored by research assistants, who provided email reminders three weeks prior and phone reminders one week prior to window closure. Remuneration Initially, participants received a prespecified renumeration at each study visit - $ 50 each for the first and third prenatal visits; $ 75 for the second prenatal and second postpartum visit, and $ 100 for the final postpartum visit, for a total of $ 400 for completion of all visits. Due to lower than expected completion of online forms in the first several months of data collection, the remuneration schedule was changed in February 2016 for all subsequently recruited participants to be pro-rated based on the number of completed self-administered forms. Under the prorated remuneration schedule, participants received $ 15 for each clinic visit plus $ 3- $ 10 per online form (based on the estimated time to complete) and $ 14 for the dietary recall, for a maximum total of $ 400 (Supplementary Table 1). The first 284 participants received lump sum remuneration; the remaining 174 received prorated remuneration. Participants remained under the same remuneration schedule for the entire study. Data collection procedures at final study visit When ongoing study monitoring indicated particularly low rates of data completion at the one-year postpartum visit, a second change in study procedures occurred. To ensure that the most critical self-report measures were obtained at the final postpartum study visit, several surveys were eliminated from the assessment schedule and participants were asked to complete all surveys during the clinic visit if they had not already completed them at home. This change occurred in March 2017, after 180 participants had already completed the final visit; 185 participants completed the final visit under the revised data collection modality. Statistical Analysis Differences between the two remuneration groups in socio-demographic characteristics were examined using t-tests for continuous variables and chi-square for categorical variables; education and income were included as covariates in all subsequent analyses by remuneration schedule. Remuneration schedule as a predictor of withdrawal by visit was modeled using Poisson regression. Group differences in study retention at 1 year postpartum were examined by t-test. Test for differences between remuneration groups in the percent of measures completed at each assessment period was determined by analysis of covariance. Differences in percent of participants who completed the 24-hour dietary recall at each visit by remuneration group were examined by logistic regression with prorated remuneration as the referent group. Data completion rates before and after the changes to the last postpartum visit were examined by t test. All analyses were completed using SAS version 9.4. RESULTS Participants were mostly white, highly educated, and working at least part time (Table 1 ). Table 1 Baseline Sociodemographics of women in PEAS under lump sum and prorated remuneration b Lump Sum (N = 2 84 ) b Prorated (N = 1 74 ) * p a Demographics Mean ± SD or N% Mean ± SD or N% Age 30.7 ± 4.7 30.1 ± 4.8 0.27 Marital Status 0.15 Married 217 (90.4) 116 (91.3) Not Married 23 (9.6) 11 (8.7) Employment status 0.32 Full Time 158 (65.8) 75 (59.0) Part Time 34 (14.2) 18 (14.2) Not Working or Student 48 (20.0) 34 (26.8) Education 0.07 Less Than College 23 (9.6) 11 (8.7) College 126 (52.5) 52 (40.9) Graduate School 91 (37.9) 64 (50.4) Race 0.33 White 168 (73.4) 98 (67.1) Black 42 (16.4) 25 (17.1) Other or Mixed Race 26 (10.2) 23 (15.8) Ethnicity 0.18 Hispanic or Latino 22 (9.1) 11 (7.8) Not Hispanic or Latino 219 (90.1) 130 (92.2) c Income-poverty ratio 3.71 ± 1.2 4.08 ± 0.17 0.08 d Household Size 3.0 ± 1.2 2.9 ± 1.2 0.67 e Any Aid Program 0.1 No Aid 204 (78.2) 124 (84.9) Receives Aid 57 (21.8) 22 (15.1) a Demographic data missing for 91 participants for household size, income, marital status, and education, 63 participants for race, 51 for program aid, and 76 participants for ethnicity b Investigators changed the remuneration schedule mid-study. Participants enrolled earlier in the study received a “lump sum” remuneration (n = 284) at each of the clinic visits where paid a set amount in full regardless of the amount of survey measures completed. Participants enrolled later in the study received pro-rated remuneration (n = 174) according to the number of measures completed. c Income-Poverty Ratio is an index the represents family income compared to the poverty threshold. d Household size is the number of people in the household. e Programs included SNAP (Supplemental Nutrition Assistance Program), WIC (Women, Infants, and Children), free school lunch program, social security benefits, supplemental security income disability benefits * t-tests for continuous variables and chi-square for categorical variables. Statistical significance at p = 0.05. There were no significant differences between remuneration groups in age, marital status, employment, education, race, and receipt of government aid. Differences in education and household income approached statistical significance and were therefore used as covariates in subsequent analyses. [Table 1 Here] Of 458 participants enrolled, 365 remained in the study through delivery and 339 through one-year postpartum for an overall study retention rate of 74%. Among the participants that withdrew, 91 (20%) withdrew prior to delivery and 41 (9%) withdrew during postpartum. Reasons for withdrawal included 54 no longer willing to participate; 29 experienced miscarriage, stillbirth, or death of baby; 24 moved away or changed medical provider; 19 were noncompliant with study visits; and 6 developed conditions resulting in ineligibility. There was no significant difference in the time to withdrawal between the two remuneration schedules, and no interaction of visit with remuneration schedule on number of withdrawals (95% confidence interval [CI] = 0.21,0.43; p = 0.49). There were no significant differences in the number of withdrawals between the two remuneration groups (24% in the lump sum remuneration, 30% in the prorated remuneration, χ 2 = 1.16, p = 0.20). Survey completion was significantly lower under prorated remuneration than lump sum remuneration at the first trimester visit, and the difference between groups approached the threshold for statistical significance at the second visit (Table 2). Completion rates did not significantly differ between remuneration schedules at the subsequent study visits. Similarly, at the first two visits, participants were more likely to complete the 24-hour dietary recalls under the lump sum remuneration schedule, but no differences were observed at subsequent visits (Table 3). Table 2 . a Survey completion by remuneration schedule Study Visit 1 Lump Sum n 1 Prorated % Complete (mean ± sd) p n % Complete (mean ± sd) Pregnancy 1st Trimester 267 78.8 ± 1.94 160 67.44 ± 3.14 0.001 2nd Trimester 253 71.99 ± 2.7 146 60.19 ± 3.93 0.06 3rd Trimester 238 73.42 ± 2.86 132 70.34 ± 3.99 0.66 Postpartum 4–6 Weeks 221 61.56 ± 3.04 115 64.89 ± 4.12 0.34 6 Months 216 56.08 ± 3.01 112 63.99 ± 3.88 0.13 a Analysis of Covariance of percent measures complete by remuneration group controlling for education and income. Values are mean ± SD. Statistical significance at p = 0.05. Table 3 . a Diet record completion (n, %) and OR (95% CI) of diet record completion associated with remuneration schedule Study Visit b Lump Sum b Prorated Odds Ratio 95% CI n (%) Complete n (%) Complete Pregnancy 1st Trimester 267 80.90% 160 65.63% 3.39 1.77–6.84 2nd Trimester 253 71.94% 146 56.16% 2.01 1.18–3.43 3rd Trimester 238 68.91% 132 62.79% 1.38 0.82–2.33 Postpartum 4–6 Weeks 221 57.58% 115 57.36% 1.11 0.68–1.83 6 Months 216 48.20% 112 59.52% 0.61 0.37–1.01 a Logistic regression on percent of participants completing diet records controlling for education and income with prorated remuneration as referent group. b Investigators changed the remuneration schedule mid-study. Participants enrolled earlier in the study received a “lump sum” remuneration at each of the clinic visits where paid a set amount in full regardless of the amount of survey measures completed. Participants enrolled later in the study received pro-rated remuneration according to the number of measures completed. Data completion at the one-year postpartum visit was significantly higher when participants completed surveys at the study visit, with 49.4% survey completion prior to procedural change, versus 97.5% afterward, (p < .0001). DISCUSSION To increase data completion in this study of women assessed during pregnancy and postpartum, investigators changed the remuneration schedule approximately midway through data collection by linking remuneration amount to completion of each self-report measure rather than using a lump-sum remuneration schedule. Study findings indicate that the prorated remuneration schedule resulted in lower data completion at initial study visits. No differences were observed in data collection at later study visits, and retention and time to withdrawal were unchanged. As such, the findings are contrary to the research team’s hypothesis and intention for changing the remuneration schedule mid-study. In contrast, changing data collection modality from off-site, participant-initiated to in-person assessment at the one-year postpartum visit had the most significant effect on data completion, with substantially higher data completion after the modality change. The absence of an effect of remuneration schedule on retention suggests that other factors likely influenced withdrawals. Motivations for research participation previously reported include scientific interest or curiosity, the desire to further scientific knowledge, and humanitarian reasons [ 12 ]. Intrinsic motivators such as willingness to help medical research, improving the knowledge of science, and altruism are the most frequent reasons pregnant women report entering clinical studies [ 13 ]. Although payment is typically expected for study participation, participants in one study in a lower-income South African population reported they were willing to participate even if no compensation were provided [ 14 ]. Monetary compensation may be among the top motivating factors in populations of low income or disproportional unemployment [ 15 ]. The PEAS sample was different in that on average women were highly educated and of relatively high income. While intrinsic and monetary compensation may motivate research participation, retention may be impacted by unrelated issues such as changing family circumstances, health events, or job responsibilities [ 16 , 17 ]. Multiple retention strategies that have been shown to increase retention rates [ 18 – 20 ] were used in PEAS including periodic newsletters, holiday cards, and provision of convenient times and locations for study visits. Therefore, retention in the PEAS sample may be more attributable to the various strategies used, rather than remuneration schedule. While lower data completion under prorated remuneration was unexpected, results may be consistent with previous findings suggesting that monetary incentives may undermine intrinsic motivation [ 21 , 22 ]. While task-noncontingent monetary rewards like lump sum remuneration have shown no impact on intrinsic motivation [ 23 ], task-contingent rewards like prorated remuneration have been found to decrease intrinsic motivation and reduce performance. As such, the prorated remuneration schedule used in PEAS could have decreased participants’ intrinsic motivation (i.e. a motivation shift from intrinsic to extrinsic), thus resulting in lower data completion rates. However, this explanation would not account for the lack of differences observed by remuneration schedule at later study visits. Additionally, the amount offered per survey under prorated remuneration may not have been adequate to motivate participants to complete surveys given the income levels of our participants. One study assessing performance quizzes and volunteer tasks at different payment levels suggests that effect of monetary incentives in small amounts can be detrimental to performance [ 24 ]. Thus, these finding taken together with previous work suggest that larger lump sum payments may lead to more favorable data completion and retention and partitioning remuneration into a smaller series of payments may be a deterrent to data completion and retention. Analysis of the one-year postpartum visit indicated that survey completion was dramatically improved by administering the surveys in-person during the study visit and reducing the number of surveys rather than relying on patient-initiated survey completion offsite. While logistical issues at the clinical site did not allow for in-person survey administration during pregnancy, and there is no literature directly comparing in-person survey administration versus off-site participant-initiated survey administration, these findings suggest that in-person administration of measures should be used whenever feasible and underscore the need to determine methods to improve self-administered survey completion. Study findings should be interpreted in light of several limitations. Participants were not randomized into the remuneration groups; however, there were no significant differences in the socio-demographic characteristics between groups and no known historical changes across the study period (e.g. changes in study procedures, eligibility criteria, recruitment rates, or the population served by the clinics) that would impact comparability of the two groups. The study sample was largely well-educated with limited socioeconomic or racial diversity, and from a single geographic region; thus, findings may not be generalizable to participants with different demographic characteristics. CONCLUSIONS Findings from this study indicate that remuneration schedule and data collection modality can impact completion of self-reported assessments. Changing the remuneration from a lump sum, task-noncontingent approach to a task-contingent prorated system resulted in lower data completion rates at initial visits but did not result in differential data completion at later visits. In contrast, changing the data collection modality from off-site, self-initiated to in-person resulted in substantial improvement in data completion. Further research is needed to understand how remuneration practices and data collection modality intersect with the economic status and demographics of diverse populations to influence data completion and retention. DECLARATIONS Ethics Approval and Consent to Participate Informed consent was obtained from all individual participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Ethics committee: University of North Carolina at Chapel Hill Institutional Review Board #13-3848 Consent for Publication Not Applicable Availability of Data and Materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Declarations Disclosure: The authors declared no conflict of interest. Competing Interests The authors declare that they have no competing interests. Funding This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program (contract #HHSN275201300015C and #HHSN275201300026I/HHSN27500002). Funding: This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program (contract #HHSN275201300015C and #HHSN275201300026I/HHSN27500002). Authors' Contributions TRN, LL, and AMSR designed and conducted the study. NT, TRN, LL, and AL developed the research question and analytic approach. NT conducted data analyses and drafted the manuscript. All authors contributed to manuscript critical revisions and approved the final manuscript. Acknowledgements Not Applicable References 1. Brealey SD, Atwell C, Bryan S, et al. Improving response rates using a monetary incentive for patient completion of questionnaires: an observational study. 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Quarterly Journal of Economics. 2000;115(3):791-810. doi:10.1162/003355300554917. Abbreviations PEAS, UNC Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8484","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":229176,"identity":"60bd9e26-8f12-4a5e-918b-58782d99981e","order_by":1,"name":"Ndeah Terry","email":"","orcid":"https://orcid.org/0000-0001-7951-7093","institution":"National Institute of Child Health and Human Development","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ndeah","middleName":"","lastName":"Terry","suffix":""},{"id":229177,"identity":"b6b57d51-def3-410a-a81b-13b60a30d2a9","order_by":2,"name":"Leah M. Lipsky","email":"","orcid":"","institution":"National Institute of Child Health and Human Development","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Leah","middleName":"M.","lastName":"Lipsky","suffix":""},{"id":229178,"identity":"5ebe53b6-85da-4df5-a191-23be72c2ed47","order_by":3,"name":"Anna Maria Siega-Riz","email":"","orcid":"","institution":"University of Virginia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anna","middleName":"Maria","lastName":"Siega-Riz","suffix":""},{"id":229179,"identity":"20085093-2f1f-40d2-b062-32418e3816f9","order_by":4,"name":"Aiyi Liu","email":"","orcid":"","institution":"National Institute of Child Health and Human Development","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aiyi","middleName":"","lastName":"Liu","suffix":""},{"id":229180,"identity":"8c820a06-bf18-42b8-a785-20e55ea682b8","order_by":5,"name":"Tonja R. Nansel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYNCCAgY5BgbGxgMMDBIJRGoxMDAGamkgTUtiA5ACamEgrMWc/ezhDx8M/qSvbT/ccIBxh0UeA//iYxL4tFj25KVJzjAwyN12JhGo5YxEMYPEszS8WgwO5Jgx84C0HABpaZNIbJA4Y2yAV8v5N8af/xgYpJudf0islhs5BtJA7yeY3YDZwt9j+AC/ljdmkj0GxobbbgBtSQRqaZNgS8Sv5XyO8YcfFXLyZufTHz742FaX2M9/+MABfFpQQQIQsxEdmwjAT4Ido2AUjIJRMCIAAPZiT3WxT80UAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-8298-7595","institution":"","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Tonja","middleName":"R.","lastName":"Nansel","suffix":""}],"badges":[],"createdAt":"2019-11-25 12:18:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.17853/v1","doiUrl":"https://doi.org/10.21203/rs.2.17853/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13480238,"identity":"1ca4ee73-bcc7-4b5a-8a2a-905c396ff791","added_by":"auto","created_at":"2021-09-16 21:42:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":331176,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8484/v1/3c00d86e-8407-4c7f-97c7-c1a7df9a002d.pdf"}],"financialInterests":"","formattedTitle":"The effect of remuneration schedule on data completion and retention in the Pregnancy Eating Attributes Study (PEAS)","fulltext":[{"header":"BACKGROUND","content":" \u003cp\u003eParticipants in research studies are typically provided with monetary remuneration as compensation for their time and effort. Remuneration may influence participation, data completion, or study retention [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], thereby impacting internal and external validity. Furthermore, recent advances in technology have facilitated the expansion of off-site, participant-initiated data collection, but whether this data collection modality impacts data completion or participant retention is unknown. Understanding how remuneration and data collection modality influence recruitment, retention, and data completion is critical for informing the most efficient and cost-effective design of human subjects\u0026rsquo; research.\u003c/p\u003e \u003cp\u003eParticipant remuneration is typically distributed via a predetermined schedule based on the time and effort associated with participation (e.g. assessment time, cost of transportation, childcare, etc.), and evidence suggests that adequate remuneration may be critical to incentivize study participation [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and retention [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Remuneration schedule, which refers to the system of dispersal of funds to participants throughout a study, varies across studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Remuneration may be provided conditionally (i.e. only after the completion of certain study tasks) in either a lump sum at a single time point or piecemeal, or as a prespecified amount paid unconditionally (i.e. not study task dependent) throughout the study according to milestones (i.e. number of visits completed) as specified by an institution\u0026rsquo;s human subjects\u0026rsquo; review board (IRB). Another approach is to enter participants into a lottery for a gift card or monetary reward, if allowed by the IRB. To our knowledge, no studies have investigated how different payment schedules affect data completion and retention.\u003c/p\u003e \u003cp\u003eAdditionally, studies use different strategies to collect data that may impact participant retention and data completion. Self-report measures may be collected, for example, at a central study location, at in-home assessments conducted by research staff, by telephone, or via participant self-administered online assessments. In-person survey completion at a central location may improve efficiency from the investigator\u0026rsquo;s perspective but necessitates physical space and on-site staffing and requires participant effort in terms of scheduling, and transportation and parking. Alternatively, off-site participant-initiated survey completion via secure website or applications may be more flexible and reduce participant burden associated with attending study visits at a central location but may also increase susceptibility to distraction and competing priorities and increase the cognitive burden associated with initiating and completing assessments. Differences in these data collection modalities may impact participant retention and data completion. However, this has not been empirically investigated.\u003c/p\u003e \u003cp\u003eThe purpose of this secondary analysis was to investigate the effect of remuneration schedule and data collection modality on participant data completion and retention in the Pregnancy Eating Attributes Study (PEAS). PEAS enrolled a cohort of women\u0026thinsp;\u0026le;\u0026thinsp;12 weeks gestation to study eating behaviors and weight change from pregnancy through one-year postpartum. All participants were drawn from the same source population; however, two changes to study procedures were made based on findings from ongoing data collection monitoring. Because initial data completion rates during pregnancy assessments were lower than anticipated, the remuneration schedule was changed mid-study. Those recruited early in the study received a prespecified remuneration amount at each study visit regardless of how many self-initiated online forms they completed. Participants recruited later in the study were paid conditionally for each online form they completed. Additionally, in response to poorer completion of self-initiated, off-site online surveys during postpartum, data collection procedures were changed, and the number of required surveys were reduced for the final study visit such that participants completed surveys at the in-person assessment. These changes in study procedures facilitate an investigation into whether differences in remuneration schedule impacted data completion or withdrawal, and whether in-person versus off-site participant-initiated data collection modality influenced data completion.\u003c/p\u003e "},{"header":"SUBJECTS AND METHODS","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003ePEAS was a prospective observational study of 458 healthy pregnant women recruited at \u0026le;\u0026thinsp;12 weeks gestation and followed through 1-year postpartum. Details of study recruitment and methods have been published elsewhere [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Participants were recruited from women receiving prenatal care at two obstetrics clinics in the University of North Carolina at Chapel Hill Healthcare System. Inclusion criteria were: confirmed pregnant\u0026thinsp;\u0026le;\u0026thinsp;12 weeks gestation at enrollment; uncomplicated singleton pregnancy anticipated; age 18\u0026ndash;45\u0026nbsp;years at screening; willingness to undergo study procedures and provide informed consent for her participation and assent for the baby\u0026rsquo;s participation; BMI\u0026thinsp;\u0026ge;\u0026thinsp;18.5\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e; able to complete self-report assessments in English; access to internet with email; plan to deliver at the UNC Women\u0026rsquo;s Hospital; and plan to remain in the geographical vicinity of the clinical site for 1\u0026nbsp;year following delivery. Exclusion criteria included pre-existing diabetes; multiple pregnancy; participant-reported eating disorder; any chronic illnesses or use of medication that could affect diet or weight; psychosocial condition hindering participation in the study. Recruitment occurred from November 2014 to December 2016. Data collection was completed in August 2018. Protocols including modifications to the mode and remuneration were approved by the UNC IRB.\u003c/p\u003e \u003cp\u003eAnthropometrics and biospecimens were collected at in-person study visits once per pregnancy trimester and 3 times between delivery up to 1\u0026nbsp;year postpartum. Participants were also asked to complete self-administered online surveys on eating- and health-related behaviors and a 24-hour dietary recall outside of study visits via a secure study website. Participants logged on to the website with their username and password within specified time windows around each visit (at 6\u0026ndash;12 weeks, 16\u0026ndash;27 weeks, and 28\u0026ndash;36 weeks gestation; and at 4\u0026ndash;14 weeks, 23\u0026ndash;31 weeks, and 50\u0026ndash;58 weeks postpartum). The website listed all required surveys for that window, with a link to the online survey form, and participants could complete them all at once or across multiple logins. When the visit window closed, the surveys were no longer accessible. Completion of the surveys and 24-hour dietary recalls were monitored by research assistants, who provided email reminders three weeks prior and phone reminders one week prior to window closure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRemuneration\u003c/h2\u003e \u003cp\u003eInitially, participants received a prespecified renumeration at each study visit - \u003cspan\u003e$\u003c/span\u003e50 each for the first and third prenatal visits; \u003cspan\u003e$\u003c/span\u003e75 for the second prenatal and second postpartum visit, and \u003cspan\u003e$\u003c/span\u003e100 for the final postpartum visit, for a total of \u003cspan\u003e$\u003c/span\u003e400 for completion of all visits. Due to lower than expected completion of online forms in the first several months of data collection, the remuneration schedule was changed in February 2016 for all subsequently recruited participants to be pro-rated based on the number of completed self-administered forms. Under the prorated remuneration schedule, participants received \u003cspan\u003e$\u003c/span\u003e15 for each clinic visit plus \u003cspan\u003e$\u003c/span\u003e3-\u003cspan\u003e$\u003c/span\u003e10 per online form (based on the estimated time to complete) and \u003cspan\u003e$\u003c/span\u003e14 for the dietary recall, for a maximum total of \u003cspan\u003e$\u003c/span\u003e400 (Supplementary Table\u0026nbsp;1). The first 284 participants received lump sum remuneration; the remaining 174 received prorated remuneration. Participants remained under the same remuneration schedule for the entire study.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection procedures at final study visit\u003c/h2\u003e \u003cp\u003eWhen ongoing study monitoring indicated particularly low rates of data completion at the one-year postpartum visit, a second change in study procedures occurred. To ensure that the most critical self-report measures were obtained at the final postpartum study visit, several surveys were eliminated from the assessment schedule and participants were asked to complete all surveys during the clinic visit if they had not already completed them at home. This change occurred in March 2017, after 180 participants had already completed the final visit; 185 participants completed the final visit under the revised data collection modality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDifferences between the two remuneration groups in socio-demographic characteristics were examined using t-tests for continuous variables and chi-square for categorical variables; education and income were included as covariates in all subsequent analyses by remuneration schedule. Remuneration schedule as a predictor of withdrawal by visit was modeled using Poisson regression. Group differences in study retention at 1\u0026nbsp;year postpartum were examined by t-test. Test for differences between remuneration groups in the percent of measures completed at each assessment period was determined by analysis of covariance. Differences in percent of participants who completed the 24-hour dietary recall at each visit by remuneration group were examined by logistic regression with prorated remuneration as the referent group. Data completion rates before and after the changes to the last postpartum visit were examined by t test. All analyses were completed using SAS version 9.4.\u003c/p\u003e \u003c/div\u003e "},{"header":"RESULTS","content":" \u003cp\u003eParticipants were mostly white, highly educated, and working at least part time (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eBaseline Sociodemographics of women in PEAS under lump sum and prorated remuneration\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003eb\u003c/sup\u003e Lump Sum (N\u0026thinsp;=\u0026thinsp;2\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e84\u003c/span\u003e)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003eb\u003c/sup\u003e Prorated (N\u0026thinsp;=\u0026thinsp;1\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e74\u003c/span\u003e)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e*\u003c/span\u003e p\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ea\u003c/span\u003e\u003c/sup\u003e Demographics\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or N%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or N%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAge\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e30.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.27\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eMarital Status\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.15\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eMarried\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e217 (90.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e116 (91.3)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNot Married\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e23 (9.6)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e11 (8.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eEmployment status\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.32\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eFull Time\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e158 (65.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e75 (59.0)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePart Time\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e34 (14.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e18 (14.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNot Working or Student\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e48 (20.0)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e34 (26.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eEducation\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.07\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLess Than College\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e23 (9.6)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e11 (8.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCollege\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e126 (52.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e52 (40.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eGraduate School\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e91 (37.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e64 (50.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eRace\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.33\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eWhite\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e168 (73.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e98 (67.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBlack\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e42 (16.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e25 (17.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eOther or Mixed Race\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e26 (10.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e23 (15.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eEthnicity\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e0.18\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHispanic or Latino\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e22 (9.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e11 (7.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNot Hispanic or Latino\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e219 (90.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e130 (92.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003ec\u003c/sup\u003e Income-poverty ratio\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.08\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003ed\u003c/sup\u003e Household Size\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.67\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003ee\u003c/sup\u003e Any Aid Program\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.1\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo Aid\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e204 (78.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e124 (84.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eReceives Aid\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e57 (21.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e22 (15.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003e Demographic data missing for 91 participants for household size, income, marital status, and education,\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e63 participants for race, 51 for program aid, and 76 participants for ethnicity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eb Investigators changed the remuneration schedule mid-study. Participants enrolled earlier in the study received a \u0026ldquo;lump sum\u0026rdquo; remuneration (n\u0026thinsp;=\u0026thinsp;284) at each of the clinic visits where paid a set amount in full regardless of the amount of survey measures completed. Participants enrolled later in the study received pro-rated remuneration (n\u0026thinsp;=\u0026thinsp;174) according to the number of measures completed.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ec Income-Poverty Ratio is an index the represents family income compared to the poverty threshold. \u003csup\u003ed\u003c/sup\u003e Household size is the number of people in the household.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ee\u003c/sup\u003e Programs included SNAP (Supplemental Nutrition Assistance Program), WIC (Women, Infants, and Children), free school lunch program, social security benefits, supplemental security income disability benefits\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e*\u003c/sup\u003e t-tests for continuous variables and chi-square for categorical variables. Statistical significance at p\u0026thinsp;=\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere were no significant differences between remuneration groups in age, marital status, employment, education, race, and receipt of government aid. Differences in education and household income approached statistical significance and were therefore used as covariates in subsequent analyses.\u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003eOf 458 participants enrolled, 365 remained in the study through delivery and 339 through one-year postpartum for an overall study retention rate of 74%. Among the participants that withdrew, 91 (20%) withdrew prior to delivery and 41 (9%) withdrew during postpartum. Reasons for withdrawal included 54 no longer willing to participate; 29 experienced miscarriage, stillbirth, or death of baby; 24 moved away or changed medical provider; 19 were noncompliant with study visits; and 6 developed conditions resulting in ineligibility. There was no significant difference in the time to withdrawal between the two remuneration schedules, and no interaction of visit with remuneration schedule on number of withdrawals (95% confidence interval [CI]\u0026thinsp;=\u0026thinsp;0.21,0.43; p\u0026thinsp;=\u0026thinsp;0.49). There were no significant differences in the number of withdrawals between the two remuneration groups (24% in the lump sum remuneration, 30% in the prorated remuneration, χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.16, p\u0026thinsp;=\u0026thinsp;0.20).\u003c/p\u003e \u003cp\u003eSurvey completion was significantly lower under prorated remuneration than lump sum remuneration at the first trimester visit, and the difference between groups approached the threshold for statistical significance at the second visit (Table\u0026nbsp;2). Completion rates did not significantly differ between remuneration schedules at the subsequent study visits. Similarly, at the first two visits, participants were more likely to complete the 24-hour dietary recalls under the lump sum remuneration schedule, but no differences were observed at subsequent visits (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTable\u0026nbsp;2\u003c/span\u003e. \u003csup\u003ea\u003c/sup\u003e Survey completion by remuneration schedule\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eStudy Visit\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e1\u003c/sup\u003eLump Sum\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003en\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e1\u003c/sup\u003eProrated\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e% Complete\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003ep\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003en\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e% Complete (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePregnancy\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e1st Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e267\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e160\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e67.44\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e2nd Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e253\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e71.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e146\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e60.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.06\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e3rd Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e238\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e73.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e132\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e70.34\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.66\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePostpartum\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e4\u0026ndash;6 Weeks\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e221\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e61.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e115\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e64.89\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.34\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e6 Months\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e216\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e56.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e112\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e63.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.13\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Analysis of Covariance of percent measures complete by remuneration group controlling for education and income. Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Statistical significance at p\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTable\u0026nbsp;3\u003c/span\u003e. \u003csup\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ea\u003c/span\u003e\u003c/sup\u003e Diet record completion (n, %) and OR (95% CI) of diet record completion associated with remuneration schedule\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eStudy Visit\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003eb\u003c/sup\u003e Lump Sum\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003eb\u003c/sup\u003e Prorated\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eOdds\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eRatio\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e95% CI\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003en\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e(%) Complete\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003en\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e(%) Complete\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePregnancy\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e1st Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e267\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e80.90%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e160\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e65.63%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.39\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.77\u0026ndash;6.84\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e2nd Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e253\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e71.94%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e146\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e56.16%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e2.01\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.18\u0026ndash;3.43\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e3rd Trimester\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e238\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e68.91%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e132\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e62.79%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.38\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.82\u0026ndash;2.33\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePostpartum 4\u0026ndash;6 Weeks\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e221\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.58%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e115\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.36%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.11\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.68\u0026ndash;1.83\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e6 Months\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e216\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e48.20%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e112\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e59.52%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.61\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.37\u0026ndash;1.01\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"OrderedList\"\u003e \u003cdiv class=\"ListItem\"\u003e \u003cspan class=\"EditNotAllowed OListNum\" name=\"ItemNumber\"\u003ea\u003c/span\u003e \u003cdiv class=\"ItemContent\"\u003e \u003cdiv id=\"Par37\" class=\"OListPara\" name=\"Para\"\u003eLogistic regression on percent of participants completing diet records controlling for education and income with prorated remuneration as referent group.\u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"ListItem\"\u003e \u003cspan class=\"EditNotAllowed OListNum\" name=\"ItemNumber\"\u003eb\u003c/span\u003e \u003cdiv class=\"ItemContent\"\u003e \u003cdiv id=\"Par38\" class=\"OListPara\" name=\"Para\"\u003eInvestigators changed the remuneration schedule mid-study. Participants enrolled earlier in the study received a \u0026ldquo;lump sum\u0026rdquo; remuneration at each of the clinic visits where paid a set amount in full regardless of the amount of survey measures completed. Participants enrolled later in the study received pro-rated remuneration according to the number of measures completed.\u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eData completion at the one-year postpartum visit was significantly higher when participants completed surveys at the study visit, with 49.4% survey completion prior to procedural change, versus 97.5% afterward, (p\u0026thinsp;\u0026lt;\u0026thinsp;.0001).\u003c/p\u003e "},{"header":"DISCUSSION","content":" \u003cp\u003eTo increase data completion in this study of women assessed during pregnancy and postpartum, investigators changed the remuneration schedule approximately midway through data collection by linking remuneration amount to completion of each self-report measure rather than using a lump-sum remuneration schedule. Study findings indicate that the prorated remuneration schedule resulted in lower data completion at initial study visits. No differences were observed in data collection at later study visits, and retention and time to withdrawal were unchanged. As such, the findings are contrary to the research team\u0026rsquo;s hypothesis and intention for changing the remuneration schedule mid-study. In contrast, changing data collection modality from off-site, participant-initiated to in-person assessment at the one-year postpartum visit had the most significant effect on data completion, with substantially higher data completion after the modality change.\u003c/p\u003e \u003cp\u003eThe absence of an effect of remuneration schedule on retention suggests that other factors likely influenced withdrawals. Motivations for research participation previously reported include scientific interest or curiosity, the desire to further scientific knowledge, and humanitarian reasons [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Intrinsic motivators such as willingness to help medical research, improving the knowledge of science, and altruism are the most frequent reasons pregnant women report entering clinical studies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although payment is typically expected for study participation, participants in one study in a lower-income South African population reported they were willing to participate even if no compensation were provided [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Monetary compensation may be among the top motivating factors in populations of low income or disproportional unemployment [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The PEAS sample was different in that on average women were highly educated and of relatively high income. While intrinsic and monetary compensation may motivate research participation, retention may be impacted by unrelated issues such as changing family circumstances, health events, or job responsibilities [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Multiple retention strategies that have been shown to increase retention rates [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] were used in PEAS including periodic newsletters, holiday cards, and provision of convenient times and locations for study visits. Therefore, retention in the PEAS sample may be more attributable to the various strategies used, rather than remuneration schedule.\u003c/p\u003e \u003cp\u003eWhile lower data completion under prorated remuneration was unexpected, results may be consistent with previous findings suggesting that monetary incentives may undermine intrinsic motivation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While task-noncontingent monetary rewards like lump sum remuneration have shown no impact on intrinsic motivation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], task-contingent rewards like prorated remuneration have been found to decrease intrinsic motivation and reduce performance. As such, the prorated remuneration schedule used in PEAS could have decreased participants\u0026rsquo; intrinsic motivation (i.e. a motivation shift from intrinsic to extrinsic), thus resulting in lower data completion rates. However, this explanation would not account for the lack of differences observed by remuneration schedule at later study visits. Additionally, the amount offered per survey under prorated remuneration may not have been adequate to motivate participants to complete surveys given the income levels of our participants. One study assessing performance quizzes and volunteer tasks at different payment levels suggests that effect of monetary incentives in small amounts can be detrimental to performance [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Thus, these finding taken together with previous work suggest that larger lump sum payments may lead to more favorable data completion and retention and partitioning remuneration into a smaller series of payments may be a deterrent to data completion and retention.\u003c/p\u003e \u003cp\u003eAnalysis of the one-year postpartum visit indicated that survey completion was dramatically improved by administering the surveys in-person during the study visit and reducing the number of surveys rather than relying on patient-initiated survey completion offsite. While logistical issues at the clinical site did not allow for in-person survey administration during pregnancy, and there is no literature directly comparing in-person survey administration versus off-site participant-initiated survey administration, these findings suggest that in-person administration of measures should be used whenever feasible and underscore the need to determine methods to improve self-administered survey completion.\u003c/p\u003e \u003cp\u003eStudy findings should be interpreted in light of several limitations. Participants were not randomized into the remuneration groups; however, there were no significant differences in the socio-demographic characteristics between groups and no known historical changes across the study period (e.g. changes in study procedures, eligibility criteria, recruitment rates, or the population served by the clinics) that would impact comparability of the two groups. The study sample was largely well-educated with limited socioeconomic or racial diversity, and from a single geographic region; thus, findings may not be generalizable to participants with different demographic characteristics.\u003c/p\u003e "},{"header":"CONCLUSIONS","content":" \u003cp\u003eFindings from this study indicate that remuneration schedule and data collection modality can impact completion of self-reported assessments. Changing the remuneration from a lump sum, task-noncontingent approach to a task-contingent prorated system resulted in lower data completion rates at initial visits but did not result in differential data completion at later visits. In contrast, changing the data collection modality from off-site, self-initiated to in-person resulted\u003c/p\u003e \u003cp\u003ein substantial improvement in data completion. Further research is needed to understand how remuneration practices and data collection modality intersect with the economic status and demographics of diverse populations to influence data completion and retention.\u003c/p\u003e "},{"header":"DECLARATIONS","content":" \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e \u003cp\u003eInformed consent was obtained from all individual participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.\u003c/p\u003e \u003cp\u003eEthics committee: University of North Carolina at Chapel Hill Institutional Review Board\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e#13-3848\u003c/h2\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eConsent for Publication\u003c/h2\u003e \u003cp\u003eNot Applicable\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAvailability of Data and Materials\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":" \u003cdiv id=\"FPar4\" renderingstyle=\"Style1\" class=\"FormalPara\"\u003e \u003cdiv class=\"Heading\"\u003eDisclosure:\u003c/div\u003e \u003cp\u003eThe authors declared no conflict of interest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"FPar8\" renderingstyle=\"Style1\" class=\"FormalPara\"\u003e \u003cdiv class=\"Heading\"\u003eCompeting Interests\u003c/div\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"FPar9\" renderingstyle=\"Style1\" class=\"FormalPara\"\u003e \u003cdiv class=\"Heading\"\u003eFunding\u003c/div\u003e \u003cp\u003eThis research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program (contract #HHSN275201300015C and #HHSN275201300026I/HHSN27500002).\u003c/p\u003e \u003c/div\u003e \u003cdiv class=\"Heading\"\u003eFunding:\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eThis research was supported by the \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eEunice Kennedy Shriver\u003c/span\u003e National Institute of Child Health and Human Development Intramural Research Program (contract #HHSN275201300015C and #HHSN275201300026I/HHSN27500002).\u003c/div\u003e \u003cdiv class=\"Heading\"\u003eAuthors' Contributions\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eTRN, LL, and AMSR designed and conducted the study. NT, TRN, LL, and AL developed the research question and analytic approach. NT conducted data analyses and drafted the manuscript. All authors contributed to manuscript critical revisions and approved the final manuscript.\u003c/div\u003e \u003cdiv class=\"Heading\"\u003eAcknowledgements\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eNot Applicable\u003c/div\u003e "},{"header":"References","content":"\u003cp\u003e1. Brealey SD, Atwell C, Bryan S, et al. Improving response rates using a monetary incentive for patient completion of questionnaires: an observational study. BMC Medical Research Methodology. 2007;7(1). doi:10.1186/1471-2288-7-12 \u003c/p\u003e\n\n\u003cp\u003e2. Simmons E, Wilmot A. Incentive payments on social surveys: A literature review. Social survey methodology bulletin. 2004:1-1. \u003c/p\u003e\n\n\u003cp\u003e3. Singer E, Groves RM, Corning A. Differential Incentives: Beliefs about Practices, Perceptions of Equity, and Effects on Survey Participation. 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Quarterly Journal of \u003c/p\u003e\n\n\u003cp\u003eEconomics. 2000;115(3):791-810. doi:10.1162/003355300554917. \u003c/p\u003e\n"},{"header":"Abbreviations","content":"\u003cp\u003ePEAS, UNC\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"pregnancy, remuneration, data completion, retention \t","lastPublishedDoi":"10.21203/rs.2.17853/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.17853/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background: Maximizing data completion and study retention is essential in population research. There is scant research to inform how remuneration schedules and data collection modality influence participant data completion and retention.\n\nPurpose: We examined the effect of remuneration schedule and data collection modality on data completion and retention in the Pregnancy Eating Attributes Study (PEAS) cohort.\n\nMethods: Participants (n=458) completed self-administered surveys and diet recalls online and attended six study visits. Initially, remuneration was a prespecified amount per visit (lump sum). The remuneration schedule was changed mid-study to be based on the number of forms completed (pro-rated). Survey data collection modality was changed to in-person at the 1-year postpartum visit. Remuneration schedule as a predictor of withdrawal by visit was modeled using\n\nPoisson regression; differences in retention at 1-year postpartum were examined by t-test. Differences in survey and diet record completion were determined by t-test, analysis of covariance, and logistic regression.\n\nResults: There was no significant difference in the time to withdrawal and no interaction of visit with remuneration schedule on withdrawal. Survey and diet recall completion were significantly lower under prorated remuneration at the first visit but did not significantly differ at subsequent visits. Survey completion at 1-year postpartum was significantly higher for in-person versus online completion.\n\nConclusions: Findings suggest that remuneration schedule and data collection modality can impact completion of self-reported assessments. Further research is needed to understand how remuneration and data collection practices intersect with diverse populations to influence data completion and retention.","manuscriptTitle":"The effect of remuneration schedule on data completion and retention in the Pregnancy Eating Attributes Study (PEAS)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2019-11-27 21:51:56","doi":"10.21203/rs.2.17853/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0548d939-df49-433e-ab83-168f79d799cc","owner":[],"postedDate":"November 27th, 2019","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38694,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2020-05-29T03:02:24+00:00","versionOfRecord":[],"versionCreatedAt":"2019-11-27 21:51:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8484","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-8484","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}