Effects of 3D ultrasonography and 3D printed images on maternal-fetal attachment and its correlation with overall smoking within pregnancy: A pilot study

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Coté, Remington D. Coté, Dannie Dilsaver, Suena Massey, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4663887/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2024 Read the published version in 3D Printing in Medicine → Version 1 posted 9 You are reading this latest preprint version Abstract Background Smoking in pregnancy continues to cause significant morbidity to mothers and babies and contributes to tremendous costs to society. Maternal-fetal attachment (MFA) may differentiate smokers who quit or pregnant smokers from non-smokers. Researchers have recommended utilizing interventions that improve MFA to help decrease smoking within pregnancy. Methods We performed a randomized clinical trial of pregnant smokers ( n = 33) using an MFA-informed, intention-to-treat protocol. We recruited pregnant smokers and provided timeline follow back (TLFB) interviews from 27 weeks of pregnancy until 6 weeks post-partum. Salivary cotinine was also collected at five different time points. 3D ultrasonography was performed, and patients were randomly assigned a 3D picture or a 3D model of their fetus. Results Overall, the average percent reduction in cigarette use was 37.03% (SD = 31.18). The main effect of 3D type was not significant (3D Model vs. 3D Print Estimate = -0.09, 95% CI: − 0.19 to 0.01, p = 0.066). A total of 4 patients (12%) quit smoking within one week of delivery. A 10% reduction in cigarette use was associated with a 30.57 g increase in birth weight (Estimate = 30.57, 95% CI: -14.15 to 75.29); a 10% reduction in cigarette use was associated with a 0.14 week increase in estimate gestational age at delivery (Estimate = 0.14, 95% CI: -0.01 to 0.28). Conclusions Patients who smoke in pregnancy decrease the number of cigarettes smoked after receiving either a 3D picture or 3D model of their fetus. Trial registration: clinicaltrials.gov (NCT04541121) 3D-printing Maternal-fetal attachment Smoking Pregnancy Figures Figure 1 Figure 2 Figure 3 BACKGROUND Smoking during pregnancy continues to be a leading preventable risk factor for pre-term delivery (PTD), low birth weight (LBW), neonatal intensive care unit (NICU) admission, and intrauterine fetal demises (IUFD) ( 1 ). The current American College of Obstetricians and Gynecologists (ACOG) recommendations for smoking cessation emphasize the 5A’s (‘Ask’, ‘Advise’, ‘Assess’, ‘Assist’, and ‘Arrange’) ( 2 ). Despite these well-established guidelines, healthcare providers have low rates of ‘Assisting’ and ‘Arranging’ and smoking cessation interventions are underutilized( 3 ). Ultrasonography in pregnancy is routine and established and has been shown to increase MFA in multiple studies( 4 , 5 ). There is mounting evidence that 3D ultrasonography improves MFA scores more than 2D ultrasonography( 5 ). Additionally, 3D printed physical models will improve MFA scores statistically more than 3D ultrasonography alone( 4 ). Ironically, patients receiving 3D pictures and 3D models increase MFA scores equally( 5 ). MFA is also linked to smoking behavior with researchers recommending the next steps to included examining if MFA informed interventions could assist in smoking cessation efforts( 6 – 8 ). To our knowledge there are no studies that have examined MFA interventions and smoking in pregnancy. The aims of the current study were to compare the effectiveness of two easily implemented MFA-informed smoking interventions on smoking habits during pregnancy. MATERIALS AND METHODS All procedures described were approved by the Institutional Review Board of Creighton University. Participants were thirty English-speaking actively smoking pregnant adults with single gestations recruited from clinics in a medium-sized city in the Midwestern U.S. between 26 and 31 weeks of gestation (Fig. 1 ). Following informed consent procedures, we collected data described below from participants at the following timepoints: Time 1-enrollment (M = 28.8 weeks, SD = 1.4); Time 2-intervention (M = 29.9 weeks, SD = 1.4); Time 3-one week after intervention (M = 30.9 weeks, SD = 1.5); Time 4-two weeks post-partum; Time 5-six weeks post-partum. 3D Images After completing the MAAS questionnaires along with the demographics, patients were block randomized with equal allocation and block sizes of four, to a 3D model or 3D picture and then underwent a 15–20-minute ultrasonography examination at M = 28.8 weeks (SD = 1.4) using a General Electric (GE) Voluson™ E10 ultrasonography machine to capture a 3D image of the fetal face. After the patient left the clinic, the ultrasonographer either printed one of the 3D images on thermal paper or they exported a stereolighography (STL) file to a thumb drive to be modified. The STL file had artifacts removed and a 3D model was printed with a TAZ 6 Workhorse™ 3D printer using skin tone appropriate polylactic acid (PLA). Either the 3D picture or 3D model were presented to the corresponding patients one week after their ultrasonography (Time-2). Smoking Smoking was assessed from 27 weeks of pregnancy until 6 weeks post-partum using the TLFB method, the gold standard quantitative measure of patterns of substance use over time( 9 ). At each of the 5 timepoints participants reported how much they smoked on each day during the 2-week period immediately preceding the visit. Additionally, patients provided saliva samples also at each of the five timepoint (Salimetrics Salivary Cotinine Assay Kit Cat. No. 1-2002). Saliva samples were stored at -80 degrees Celsius before shipment to Salimetrics (State College, PA). Samples were assayed using the, without modifications to the manufacturers’ protocol. Samples were thawed to room temperature, vortexed, and then centrifuged for 15 minutes at approximately 3,000 RPM immediately before performing the assay. Samples were tested using a high sensitivity enzyme immunoassay (Cat. No. 1-2002). Sample volume was 20 µL of saliva per determination. The assay has a lower limit of sensitivity of 0.15 ng/mL, a standard curve ranges from 0.8–200 ng/mL. Analytic Strategy To assess change in cigarettes smoked during pregnancy, we estimated a piecewise mixed-effects Poisson regression model. The first segment estimated cigarette use from study enrollment until receiving a 3D ultrasound, this 7-day period was identical for both the 3D print and the 3D model group. The second segment estimated cigarette use from the day of 3D ultrasound until delivery, which varied across patients. Then, we evaluated the change in cigarettes smoked during pregnancy by time and 3D type. This final piecewise model included four fixed effects: time pre-3D ultrasound, time post-3D ultrasound, 3D types, and the time post-3D ultrasound-by-3D type interaction effect. The interaction effect evaluated whether 3D type moderated the effect of time. Residual pseudo-likelihood estimation was used. Time was modeled as a continuous variable (days). We accounted for the correlation of observations from the same patient by estimating random subject effects. Secondary Objectives We evaluated the relationship between cigarette reduction and birth weight. Cigarette reduction was quantified as the percent reduction in cigarettes smoked between the 7-day period prior to receiving the 3D ultrasound and the 7-day period prior to delivery. Lastly, we estimated two linear regression models with birth weight and estimated gestational age at delivery as the outcomes and percent cigarette reduction as the predictors. All analyses used SAS v. 9.4 with two-tailed p < 0.05 indicating statistical significance. RESULTS Descriptive-Demographics A total of 33 patients were randomized: 3D picture (N = 16) vs 3D model (N = 17). Demographic and obstetric patient data are presented in Table 1 . Descriptive characteristics were similar between the 3D picture and the 3D model group. Table 1 Patient descriptives stratified by 3D product Overall 3D Product Print Model Age, years 28 (23–31) 27 (22–31) 28 (24–32) Baseline Body Mass Index, kg/m2 32 (27–37) 31 (25–37) 32 (27–35) Baseline cotinine level, ng/mL 170 (104–257) 170 (93–259) 170 (142–257) Baseline MAAS score 84 (80–87) 84 (82–87) 85 (77–87) Race, N (%) White 22 (66.67) 11 (68.75) 11 (64.71) Black 10 (30.30) 4 (25.00) 6 (35.29) Hispanic 1 (3.03) 1 (6.25) 0 (0) Married, N (%) 29 (87.88) 15 (93.75) 14 (82.35) Medicaid insurance, N (%) 31 (93.94) 15 (93.75) 16 (94.12) Income $ , N (%) 0–20 19 (65.52) 11 (73.33) 8 (57.14) 20–40 5 (17.24) 3 (20.00) 2 (14.29) 40–65 4 (13.79) 1 (6.67) 3 (21.43) 65–100 1 (3.45) 0 (0) 1 (7.14) Education, N (%) Some high school 7 (21.21) 4 (25.00) 3 (17.65) Highschool graduate 19 (57.58) 9 (56.25) 10 (58.82) Some college/college graduate 7 (21.21) 3 (18.75) 4 (23.53) Gravida, N (%) 1 pregnancy 9 (27.27) 4 (25.00) 5 (29.41) 2 pregnancies 7 (21.21) 2 (12.50) 5 (29.41) 3 + pregnancies 17 (15.52) 10 (62.50) 7 (21.18) Para, N (%) 0 previous deliveries 14 (42.42) 6 (37.50) 8 (47.06) 1 previous delivery 5 (15.15) 1 (6.25) 4 (23.53) 2 + previous deliveries 14 (42.42) 9 (56.25) 5 (29.41) History of secondhand smoke exposure, N (%) 22 (66.67) 10 (62.50) 12 (70.59) History of e-cigarette use, N (%) 7 (21.21) 2 (12.50) 5 (29.41) Continuous variables are presented as median (interquartile range). Categorical variables were presented as frequency (percent). Primary Objective In the 7-days prior to receiving the 3D ultrasound, the main effect of time was not significant (Estimate = -0.03, 95% CI: -0.09 to 0.02, p = 0.200; Fig. 2 ). The main effect of 3D type was not significant (3D Model vs. 3D Picture Estimate = -0.09, 95% CI: − 0.19 to 0.01, p = 0.066; Fig. 2 ). The time-by-3D type interaction was significant indicating that 3D type moderated the effect of time (interaction p < 0.001; Fig. 2 ). After receiving a 3D picture, the number of cigarettes smoked decreased by 0.4 cigarettes each 7-day period (Estimate = -0.04, 95% CI: = − 0.05 to -0.03, p < 0.001; Fig. 2 ). After receiving a 3D model, the number of cigarettes smoked decreased by 0.01 cigarettes each 7-day period (Estimate = -0.01, 95% CI: = − 0.02 to 0.00, p = 0.243; Fig. 2 ). The average percent reduction in cigarette use was 37.03% (SD = 31.18). For the 3D picture and 3D model groups, the average reduction in cigarette use was 43.33% (SD: 32.12%) and 31.52% (SD = 30.26%), respectively. There was no statistical difference in percent cigarette reduction between the 3D picture and the 3D model group (3D Model vs. 3D Picture Difference = -11.81%, 95% CI: -35.16–11.53%, p = 0.309). Based on TLFB interviews for all the patients, 12% (N = 4) quit smoking within a week of delivery. Salivary cotinine levels had an average intra-assay coefficient of variation of 6.38%, and an average inter-assay coefficient of variation 6.63%. Currently, a cotinine cut point of 3ng/mL has been recommended for distinguishing smokers from non-smokers( 10 ). Of the patients with salivary cotinine data at Time-4 (2-weeks after delivery; N = 19), 11% (N = 2) had smoking cessation chemically confirmed. Secondary Objectives Post-birth outcomes are presented in Table 2 . Notably, 36.26% (N = 12) of patients experienced preeclampsia. A 10% reduction in cigarette use was associated with a 30.57 gram increase in birth weight (Estimate = 30.57, 95% CI: -14.15 to 75.29, p = 0.173; Fig. 3 a). A 10% reduction in cigarette use was associated with a 0.14 week increase in estimate gestational age at delivery (Estimate = 0.14, 95% CI: -0.01 to 0.28, p = 0.063; Fig. 3 b). Table 2 Birth outcomes stratified by 3D product Overall 3D Product p Print Model Estimated gestational age at delivery, weeks 39 (38–39) 39 (39–40) 39 (37–39) 0.090 Birth weight, g 3,130 (2,985-3,350) 3,135 (2,990-3,365) 3,100 (2,820-3,350) 0.614 Low birth weight, % 3 (9.09) 0 (0) 3 (17.65) 0.227 Neonatal intensive care unit admission, N (%) 2 (6.06) 0 (0) 2 (11.76) 0.485 Pre-eclampsia, N (%) 12 (36.36) 6 (37.50) 6 (37.50) 0.895 a. Continuous variables are presented as median (interquartile range). b. LBW was defined as a birth weight less than 2,020 g for females and less than 2,730 g for males. DISCUSSION Previous research has focused on interventions to improve MFA scores in pregnancy, yet this is the first study to examine the effects of 3D fetal models or 3D pictures on smoking in pregnancy. Our findings showed no difference between 3D interventions; yet our within-subject design showed improvement in smoking reduction for both MFA interventions and is particularly impactful when considering the effects of smoking on birth outcomes in the general population. Multiple studies suggested the rate of LBW and PTD in smokers can be 2–3 times greater than in non-smokers, yet our findings suggest an improved LBW and PTD rate for pregnancy smokers after the interventions with only a 6% rate of LBW and PTD compared to the national 8.6% and 10.38% respectively( 11 , 12 ). Consistant with other studies, we found that decreasing smoking may increase the risk of pre-eclampsia( 13 ). Notably, our findings support the need to evaluate these interventions on a larger scale. Current recommendations contend that the use of ultrasound without a medical indication to view the fetus is inappropriate and contrary to responsible medical practice( 14 ). This recommendation has its roots in the “as low as reasonably achievable” (ALARA) principle. Interestingly, these organizations emphasize that ultrasound is a safe and risk-free method for prenatal diagnosis as “the literature does not include a single study reporting a risk to the fetus as a result of ultrasound”( 15 ). While the responsible use of fetal ultrasound is important the chilling effect these recommendations have on the use of ultrasonography is a slippery slope. In fact, a German ordinance has made any non-medical ultrasound exposure of a fetus a violation of the law that can be punished as a misdemeanor( 16 ). Certain ultrasound techniques and advancements in the technological aspects of ultrasonography increase MFA scores, some more than others. Specifically, both 2D and 3D ultrasonography have been shown to increase MFA scores, yet 3D ultrasound images increase scores more than 2D ultrasound images on average( 5 ). This may be because the visual recognizability and perception of the fetus is higher with a 3D image compared to a 2D image and is consistant with neural correlates seen with facial processing( 17 , 18 ). Unfortunately, the ultrasound experience and effects on MFA may be short lived. Westerneng et al., 2022 evaluated the effect of offering a routine ultrasound on MFA and found that an ultrasound may be associated with higher MFA score after a third trimester ultrasound only at lower baseline MFA scores( 19 ). Unfortunately, their ultrasound was done between Time 1 (mean 24.1 +/- 1.96) and Time 2 (32.1 +/- 0.72) but with no comparison of when the ultrasonography was performed. Our recent comparison of 3D ultrasonography to a 3D facial model supports the ability of the 3D images to increase MFA and reinforces the potential of the physical representation of the fetal face to increase MFA scores and continue to do so over time( 4 ). Our study had a few limitations. First, because this was a pilot study, the sample size limits any conclusion we can make about the interventions and smoking. The unforeseen pandemic along with lower-than-expected smoking rates will necessitate a multi-center trial going forward. Second, there was not a no intervention control group; however, ethical implications, and the fact that the standard of care encourages providers to intervene with the 5As argues against the appropriateness of not offering a portion of the patients an intervention that may be useful. The greatest weakness of not having a control group is that smoking might be expected to decline without intervention from 27 to 36 weeks or so following rising progesterone which is known to reduce cravings across sexes and substances. There are no statistics on the percentage of patients who receive an image of their fetus at the time of their ultrasound. It is the assumption that the “keepsake” ultrasound has no medical indication which may inhibit the universal production and distribution of these images to patients. Our findings bring to light the possibility that advocacy for 3D ultrasonography and by extension 3D printed images may play a larger role than just “entertainment”. Larger, multi-center trials are still needed. CONCLUSIONS This is the first study to evaluate MFA associated interventions in smoking cessation. The results are encouraging and build an impressive argument for utilizing ultrasonography and 3D printing to improve smoking rates in pregnant patients. Comparing outcomes (overall birth weight, birth weight percentile, low birth weight (LBW) percentile, neonatal intensive care unit (NICU) admissions, preterm delivery (PTD) rates and hypertensive diseases of pregnancy rates) to current baseline rates of pregnant smokers and non-smokers support a recommendation of utilizing 3D printed technologies to help decrease smoking in pregnancy. Abbreviations ACOG American College of Obstetricians and Gynecologists ALARA as low as reasonably achievable CI confidence interval GE General Electric IUFD intrauterine fetal demise LBW low birth weight MFA maternal-fetal attachment µL microliter mL milliliter ng nanogram NICU neonatal intensive care unit PLA polylactic acid PTD preterm delivery RPM revolutions per minute SAS statistical analysis system SD standard deviation STL stereolithography TLFB timeline follow back U.S. United States Declarations Ethics declarations This research was approved by the Creighton’s Institutional Review Board (protocol number 2001287), registered at clinicaltrials.gov (NCT04541121), carried out in accordance with The Code of Ethics of the World Medical Association for experiments involving humans, and all participants were provided informed consent. Competing Interests JC, RC and BC are related to the owner of the company that produced the 3D models for the study at cost. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Consent for publication While no identifying information was utilized, consent for 3D images utilized in Figure 1 was obtained. Corresponding author Correspondence to John Coté at [email protected] Data Availability Data utilized for this manuscript can be found at 10.5281/zenodo.10901063 Role of Funding Sources Funding for this study was provided by the State of Nebraska Cancer and Smoking Disease Research Program (LB595). Creighton University School of Medicine, CHI/CommonSpirit Health, and the State of Nebraska had no role in the study design, collection, analysis, or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. Author’s contributions JC and ABB contributed to the study conception or data acquisition, analysis, interpretation, drafting or critical revision, final approval and accountability of this article. All other authors contributed to analysis, interpretation, drafting or critical revision, final approval and accountability of this article. The author(s) read and approved the final manuscript. Acknowledgements The authors wish to thank Ryan Walters PhD for overseeing this project. Author’s information John J. Coté MD, FACOG ab* , Remington D. Coté c , Dannie Dilsaver MS d , Suena Massey, MD ef , Pooja Doehrman MD, MPH, FACOG ghi , Brayden P. Coté BS j , Riley Kilzer BS k , Amy S. Badura-Brack PhD l a CHI Health/CommonSpirit Health, Omaha, NE USA b Creighton University School of Medicine, Department of Obstetrics and Gynecology, Omaha, NE USA c Creighton University, Department of Biology, Omaha, NE USA d Creighton University School of Medicine, Department of Clinical Research and Public Health, Omaha, NE USA e Brigham and Women’s Hospital, Department of Psychiatry, Boston, MA, USA f Harvard Medical School, Boston, MA, USA g Creighton University School of Medicine, Phoenix Campus, Department of Obstetrics and Gynecology, Phoenix, AZ USA h University of Arizona College of Medicine, Department of Obstetrics and Gynecology, Phoenix, AZ USA i Dignity Health/CommonSpirit Health, Phoenix, AZ USA j Chestnut Hill College, Department of Phycology, Philadelphia, PA USA k University of Nebraska Medical Center, College of Medicine, Omaha, NE USA l Creighton University, Department of Psychological Science, Omaha, NE USA References Sequí-Canet JM, Sequí-Sabater JM, Marco-Sabater A, Corpas-Burgos F, Del Castillo JIC, Orta-Sibú N. 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Two- versus three-dimensional ultrasound in the second and third trimester of pregnancy: impact on recognition and maternal-fetal bonding. A prospective pilot study. Arch Gynecol Obstet. 2007;276(5):475–9. Westerneng M, De Jonge A, Van Baar AL, Witteveen AB, Jellema P, Paarlberg KM, et al. The effect of offering a third-trimester routine ultrasound on pregnancy‐specific anxiety and mother‐to‐infant bonding in low‐risk women: A pragmatic cluster‐randomized controlled trial. Birth. 2022;49(1):61–70. Additional Declarations Competing interest reported. JC, RC and BC are related to the owner of the company that produced the 3D models for the study at cost. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2024 Read the published version in 3D Printing in Medicine → Version 1 posted Editorial decision: Revision requested 22 Aug, 2024 Reviews received at journal 31 Jul, 2024 Reviews received at journal 31 Jul, 2024 Reviewers agreed at journal 12 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers invited by journal 10 Jul, 2024 Editor assigned by journal 30 Jun, 2024 Submission checks completed at journal 30 Jun, 2024 First submitted to journal 30 Jun, 2024 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-4663887","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":330446830,"identity":"9e046378-dd62-43b0-b7fd-89882d143029","order_by":0,"name":"John J. 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Coté","email":"","orcid":"","institution":"Creighton University","correspondingAuthor":false,"prefix":"","firstName":"Remington","middleName":"D.","lastName":"Coté","suffix":""},{"id":330446832,"identity":"b754d424-380f-4fd0-9502-490f2edbe3a4","order_by":2,"name":"Dannie Dilsaver","email":"","orcid":"","institution":"Creighton University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Dannie","middleName":"","lastName":"Dilsaver","suffix":""},{"id":330446833,"identity":"a9766bdb-8944-4c56-8482-6fac590128fb","order_by":3,"name":"Suena Massey","email":"","orcid":"","institution":"Brigham and Women's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Suena","middleName":"","lastName":"Massey","suffix":""},{"id":330446834,"identity":"f1eabcba-acbe-4e22-a480-1fa502f0f940","order_by":4,"name":"Pooja Doehrman","email":"","orcid":"","institution":"Creighton University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Pooja","middleName":"","lastName":"Doehrman","suffix":""},{"id":330446835,"identity":"8efc3fcf-1410-4982-b955-c32a0654601d","order_by":5,"name":"Brayden P. Coté","email":"","orcid":"","institution":"Chestnut Hill College","correspondingAuthor":false,"prefix":"","firstName":"Brayden","middleName":"P.","lastName":"Coté","suffix":""},{"id":330446836,"identity":"dcc2b2aa-c22f-4943-bdde-2c89b6f1f110","order_by":6,"name":"Riley Kilzer","email":"","orcid":"","institution":"University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Riley","middleName":"","lastName":"Kilzer","suffix":""},{"id":330446837,"identity":"7a84f616-ad11-457d-b32c-6aba181fc1de","order_by":7,"name":"Amy S. Badura-Brack","email":"","orcid":"","institution":"Creighton University","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"S.","lastName":"Badura-Brack","suffix":""}],"badges":[],"createdAt":"2024-06-30 18:00:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4663887/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4663887/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s41205-024-00238-7","type":"published","date":"2024-10-30T16:20:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60912705,"identity":"d3b761e5-48e3-4a96-9b3a-e1de196c8469","added_by":"auto","created_at":"2024-07-23 13:05:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85045,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCONSORT flow diagram\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure13DPM1.png","url":"https://assets-eu.researchsquare.com/files/rs-4663887/v1/4e354ce587d65b4007f37852.png"},{"id":60912706,"identity":"9854d03f-ac45-44e6-a780-9b4cdc0a401d","added_by":"auto","created_at":"2024-07-23 13:05:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54846,"visible":true,"origin":"","legend":"\u003cp\u003eCigarette use throughout pregnancy stratified by 3D print and 3D model.\u003c/p\u003e","description":"","filename":"Figure13DPM2.png","url":"https://assets-eu.researchsquare.com/files/rs-4663887/v1/217646813f5bff90463735b6.png"},{"id":60912707,"identity":"e8b826c8-b869-4957-867e-adbc13accd33","added_by":"auto","created_at":"2024-07-23 13:05:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":126115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e3a\u003c/strong\u003e. Association between cigarette reduction and birth weight stratified by 3D print and 3D model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3b\u003c/strong\u003e. Association between cigarette reduction and estimated gestational age at delivery stratified by 3D print and 3D model.\u003c/p\u003e","description":"","filename":"Figure13DPM3.png","url":"https://assets-eu.researchsquare.com/files/rs-4663887/v1/7ccea8d514f96aa530ef79d3.png"},{"id":68207160,"identity":"241b309f-5337-4e6d-a5ce-fd89ae884d82","added_by":"auto","created_at":"2024-11-04 16:35:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":788245,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4663887/v1/00dbc868-2048-4b31-bb10-298b63740c4b.pdf"}],"financialInterests":"Competing interest reported. JC, RC and BC are related to the owner of the company that produced the 3D models for the study at cost. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","formattedTitle":"Effects of 3D ultrasonography and 3D printed images on maternal-fetal attachment and its correlation with overall smoking within pregnancy: A pilot study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eSmoking during pregnancy continues to be a leading preventable risk factor for pre-term delivery (PTD), low birth weight (LBW), neonatal intensive care unit (NICU) admission, and intrauterine fetal demises (IUFD) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The current American College of Obstetricians and Gynecologists (ACOG) recommendations for smoking cessation emphasize the 5A\u0026rsquo;s (\u0026lsquo;Ask\u0026rsquo;, \u0026lsquo;Advise\u0026rsquo;, \u0026lsquo;Assess\u0026rsquo;, \u0026lsquo;Assist\u0026rsquo;, and \u0026lsquo;Arrange\u0026rsquo;) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Despite these well-established guidelines, healthcare providers have low rates of \u0026lsquo;Assisting\u0026rsquo; and \u0026lsquo;Arranging\u0026rsquo; and smoking cessation interventions are underutilized(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Ultrasonography in pregnancy is routine and established and has been shown to increase MFA in multiple studies(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). There is mounting evidence that 3D ultrasonography improves MFA scores more than 2D ultrasonography(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Additionally, 3D printed physical models will improve MFA scores statistically more than 3D ultrasonography alone(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Ironically, patients receiving 3D pictures and 3D models increase MFA scores equally(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). MFA is also linked to smoking behavior with researchers recommending the next steps to included examining if MFA informed interventions could assist in smoking cessation efforts(\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). To our knowledge there are no studies that have examined MFA interventions and smoking in pregnancy. The aims of the current study were to compare the effectiveness of two easily implemented MFA-informed smoking interventions on smoking habits during pregnancy.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eAll procedures described were approved by the Institutional Review Board of Creighton University. Participants were thirty English-speaking actively smoking pregnant adults with single gestations recruited from clinics in a medium-sized city in the Midwestern U.S. between 26 and 31 weeks of gestation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Following informed consent procedures, we collected data described below from participants at the following timepoints: Time 1-enrollment (M\u0026thinsp;=\u0026thinsp;28.8 weeks, SD\u0026thinsp;=\u0026thinsp;1.4); Time 2-intervention (M\u0026thinsp;=\u0026thinsp;29.9 weeks, SD\u0026thinsp;=\u0026thinsp;1.4); Time 3-one week after intervention (M\u0026thinsp;=\u0026thinsp;30.9 weeks, SD\u0026thinsp;=\u0026thinsp;1.5); Time 4-two weeks post-partum; Time 5-six weeks post-partum.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e3D Images\u003c/h2\u003e \u003cp\u003eAfter completing the MAAS questionnaires along with the demographics, patients were block randomized with equal allocation and block sizes of four, to a 3D model or 3D picture and then underwent a 15\u0026ndash;20-minute ultrasonography examination at M\u0026thinsp;=\u0026thinsp;28.8 weeks (SD\u0026thinsp;=\u0026thinsp;1.4) using a General Electric (GE) Voluson\u0026trade; E10 ultrasonography machine to capture a 3D image of the fetal face. After the patient left the clinic, the ultrasonographer either printed one of the 3D images on thermal paper or they exported a stereolighography (STL) file to a thumb drive to be modified. The STL file had artifacts removed and a 3D model was printed with a TAZ 6 Workhorse\u0026trade; 3D printer using skin tone appropriate polylactic acid (PLA). Either the 3D picture or 3D model were presented to the corresponding patients one week after their ultrasonography (Time-2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSmoking\u003c/h2\u003e \u003cp\u003eSmoking was assessed from 27 weeks of pregnancy until 6 weeks post-partum using the TLFB method, the gold standard quantitative measure of patterns of substance use over time(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). At each of the 5 timepoints participants reported how much they smoked on each day during the 2-week period immediately preceding the visit. Additionally, patients provided saliva samples also at each of the five timepoint (Salimetrics Salivary Cotinine Assay Kit Cat. No. 1-2002). Saliva samples were stored at -80 degrees Celsius before shipment to Salimetrics (State College, PA). Samples were assayed using the, without modifications to the manufacturers\u0026rsquo; protocol. Samples were thawed to room temperature, vortexed, and then centrifuged for 15 minutes at approximately 3,000 RPM immediately before performing the assay. Samples were tested using a high sensitivity enzyme immunoassay (Cat. No. 1-2002). Sample volume was 20 \u0026micro;L of saliva per determination. The assay has a lower limit of sensitivity of 0.15 ng/mL, a standard curve ranges from 0.8\u0026ndash;200 ng/mL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAnalytic Strategy\u003c/h2\u003e \u003cp\u003eTo assess change in cigarettes smoked during pregnancy, we estimated a piecewise mixed-effects Poisson regression model. The first segment estimated cigarette use from study enrollment until receiving a 3D ultrasound, this 7-day period was identical for both the 3D print and the 3D model group. The second segment estimated cigarette use from the day of 3D ultrasound until delivery, which varied across patients. Then, we evaluated the change in cigarettes smoked during pregnancy by time and 3D type. This final piecewise model included four fixed effects: time pre-3D ultrasound, time post-3D ultrasound, 3D types, and the time post-3D ultrasound-by-3D type interaction effect. The interaction effect evaluated whether 3D type moderated the effect of time. Residual pseudo-likelihood estimation was used. Time was modeled as a continuous variable (days). We accounted for the correlation of observations from the same patient by estimating random subject effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSecondary Objectives\u003c/h2\u003e \u003cp\u003eWe evaluated the relationship between cigarette reduction and birth weight. Cigarette reduction was quantified as the percent reduction in cigarettes smoked between the 7-day period prior to receiving the 3D ultrasound and the 7-day period prior to delivery. Lastly, we estimated two linear regression models with birth weight and estimated gestational age at delivery as the outcomes and percent cigarette reduction as the predictors. All analyses used SAS v. 9.4 with two-tailed p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive-Demographics\u003c/h2\u003e \u003cp\u003eA total of 33 patients were randomized: 3D picture (N\u0026thinsp;=\u0026thinsp;16) vs 3D model (N\u0026thinsp;=\u0026thinsp;17). Demographic and obstetric patient data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Descriptive characteristics were similar between the 3D picture and the 3D model group.\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 \u003cp\u003ePatient descriptives stratified by 3D product\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3D Product\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (23\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (22\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (24\u0026ndash;32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline Body Mass Index, kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (27\u0026ndash;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (25\u0026ndash;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (27\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline cotinine level, ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170 (104\u0026ndash;257)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170 (93\u0026ndash;259)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e170 (142\u0026ndash;257)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline MAAS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (80\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (82\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (77\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, N (%)\u003c/p\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (68.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (64.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (30.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (35.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (87.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (93.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (82.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid insurance, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (93.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (93.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (94.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome \u003cspan\u003e$\u003c/span\u003e, N (%)\u003c/p\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (65.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (73.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (57.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (17.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (20.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (14.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (13.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (21.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (7.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation, N (%)\u003c/p\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (21.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (17.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighschool graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (57.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (56.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (58.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college/college graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (21.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (18.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (23.53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravida, N (%)\u003c/p\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (27.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (29.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 pregnancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (21.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (29.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;pregnancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (15.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (62.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (21.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePara, N (%)\u003c/p\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 previous deliveries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (42.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (37.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (47.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 previous delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (15.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (23.53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026thinsp;+\u0026thinsp;previous deliveries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (42.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (56.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (29.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of secondhand smoke exposure, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (62.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (70.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of e-cigarette use, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (21.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (29.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eContinuous variables are presented as median (interquartile range). Categorical variables were presented as frequency (percent).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Objective\u003c/h2\u003e \u003cp\u003eIn the 7-days prior to receiving the 3D ultrasound, the main effect of time was not significant (Estimate = -0.03, 95% CI: -0.09 to 0.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.200; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The main effect of 3D type was not significant (3D Model vs. 3D Picture Estimate = -0.09, 95% CI: \u0026minus;\u0026thinsp;0.19 to 0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.066; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The time-by-3D type interaction was significant indicating that 3D type moderated the effect of time (interaction p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After receiving a 3D picture, the number of cigarettes smoked decreased by 0.4 cigarettes each 7-day period (Estimate = -0.04, 95% CI:\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.05 to -0.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After receiving a 3D model, the number of cigarettes smoked decreased by 0.01 cigarettes each 7-day period (Estimate = -0.01, 95% CI:\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.02 to 0.00, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.243; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe average percent reduction in cigarette use was 37.03% (SD\u0026thinsp;=\u0026thinsp;31.18). For the 3D picture and 3D model groups, the average reduction in cigarette use was 43.33% (SD: 32.12%) and 31.52% (SD\u0026thinsp;=\u0026thinsp;30.26%), respectively. There was no statistical difference in percent cigarette reduction between the 3D picture and the 3D model group (3D Model vs. 3D Picture Difference = -11.81%, 95% CI: -35.16\u0026ndash;11.53%, p\u0026thinsp;=\u0026thinsp;0.309). Based on TLFB interviews for all the patients, 12% (N\u0026thinsp;=\u0026thinsp;4) quit smoking within a week of delivery.\u003c/p\u003e \u003cp\u003eSalivary cotinine levels had an average intra-assay coefficient of variation of 6.38%, and an average inter-assay coefficient of variation 6.63%. Currently, a cotinine cut point of 3ng/mL has been recommended for distinguishing smokers from non-smokers(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Of the patients with salivary cotinine data at Time-4 (2-weeks after delivery; N\u0026thinsp;=\u0026thinsp;19), 11% (N\u0026thinsp;=\u0026thinsp;2) had smoking cessation chemically confirmed.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eSecondary Objectives\u003c/h2\u003e \u003cp\u003ePost-birth outcomes are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Notably, 36.26% (N\u0026thinsp;=\u0026thinsp;12) of patients experienced preeclampsia. A 10% reduction in cigarette use was associated with a 30.57 gram increase in birth weight (Estimate\u0026thinsp;=\u0026thinsp;30.57, 95% CI: -14.15 to 75.29, p\u0026thinsp;=\u0026thinsp;0.173; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). A 10% reduction in cigarette use was associated with a 0.14 week increase in estimate gestational age at delivery (Estimate\u0026thinsp;=\u0026thinsp;0.14, 95% CI: -0.01 to 0.28, p\u0026thinsp;=\u0026thinsp;0.063; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBirth outcomes stratified by 3D product\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3D Product\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstimated gestational age at delivery, weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (38\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (39\u0026ndash;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (37\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,130 (2,985-3,350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,135 (2,990-3,365)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,100 (2,820-3,350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow birth weight, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (9.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (17.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal intensive care unit admission, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (11.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-eclampsia, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (36.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (37.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (37.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ea. Continuous variables are presented as median (interquartile range).\u003c/p\u003e \u003cp\u003eb. LBW was defined as a birth weight less than 2,020 g for females and less than 2,730 g for males.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePrevious research has focused on interventions to improve MFA scores in pregnancy, yet this is the first study to examine the effects of 3D fetal models or 3D pictures on smoking in pregnancy. Our findings showed no difference between 3D interventions; yet our within-subject design showed improvement in smoking reduction for both MFA interventions and is particularly impactful when considering the effects of smoking on birth outcomes in the general population.\u003c/p\u003e \u003cp\u003eMultiple studies suggested the rate of LBW and PTD in smokers can be 2\u0026ndash;3 times greater than in non-smokers, yet our findings suggest an improved LBW and PTD rate for pregnancy smokers after the interventions with only a 6% rate of LBW and PTD compared to the national 8.6% and 10.38% respectively(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Consistant with other studies, we found that decreasing smoking may increase the risk of pre-eclampsia(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Notably, our findings support the need to evaluate these interventions on a larger scale.\u003c/p\u003e \u003cp\u003eCurrent recommendations contend that the use of ultrasound without a medical indication to view the fetus is inappropriate and contrary to responsible medical practice(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This recommendation has its roots in the \u0026ldquo;as low as reasonably achievable\u0026rdquo; (ALARA) principle. Interestingly, these organizations emphasize that ultrasound is a safe and risk-free method for prenatal diagnosis as \u0026ldquo;the literature does not include a single study reporting a risk to the fetus as a result of ultrasound\u0026rdquo;(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). While the responsible use of fetal ultrasound is important the chilling effect these recommendations have on the use of ultrasonography is a slippery slope. In fact, a German ordinance has made any non-medical ultrasound exposure of a fetus a violation of the law that can be punished as a misdemeanor(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCertain ultrasound techniques and advancements in the technological aspects of ultrasonography increase MFA scores, some more than others. Specifically, both 2D and 3D ultrasonography have been shown to increase MFA scores, yet 3D ultrasound images increase scores more than 2D ultrasound images on average(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). This may be because the visual recognizability and perception of the fetus is higher with a 3D image compared to a 2D image and is consistant with neural correlates seen with facial processing(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Unfortunately, the ultrasound experience and effects on MFA may be short lived. Westerneng et al., 2022 evaluated the effect of offering a routine ultrasound on MFA and found that an ultrasound may be associated with higher MFA score after a third trimester ultrasound only at lower baseline MFA scores(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Unfortunately, their ultrasound was done between Time 1 (mean 24.1 +/- 1.96) and Time 2 (32.1 +/- 0.72) but with no comparison of when the ultrasonography was performed. Our recent comparison of 3D ultrasonography to a 3D facial model supports the ability of the 3D images to increase MFA and reinforces the potential of the physical representation of the fetal face to increase MFA scores and continue to do so over time(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study had a few limitations. First, because this was a pilot study, the sample size limits any conclusion we can make about the interventions and smoking. The unforeseen pandemic along with lower-than-expected smoking rates will necessitate a multi-center trial going forward. Second, there was not a no intervention control group; however, ethical implications, and the fact that the standard of care encourages providers to intervene with the 5As argues against the appropriateness of not offering a portion of the patients an intervention that may be useful. The greatest weakness of not having a control group is that smoking might be expected to decline without intervention from 27 to 36 weeks or so following rising progesterone which is known to reduce cravings across sexes and substances.\u003c/p\u003e \u003cp\u003eThere are no statistics on the percentage of patients who receive an image of their fetus at the time of their ultrasound. It is the assumption that the \u0026ldquo;keepsake\u0026rdquo; ultrasound has no medical indication which may inhibit the universal production and distribution of these images to patients. Our findings bring to light the possibility that advocacy for 3D ultrasonography and by extension 3D printed images may play a larger role than just \u0026ldquo;entertainment\u0026rdquo;. Larger, multi-center trials are still needed.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis is the first study to evaluate MFA associated interventions in smoking cessation. The results are encouraging and build an impressive argument for utilizing ultrasonography and 3D printing to improve smoking rates in pregnant patients. Comparing outcomes (overall birth weight, birth weight percentile, low birth weight (LBW) percentile, neonatal intensive care unit (NICU) admissions, preterm delivery (PTD) rates and hypertensive diseases of pregnancy rates) to current baseline rates of pregnant smokers and non-smokers support a recommendation of utilizing 3D printed technologies to help decrease smoking in pregnancy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eACOG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican College of Obstetricians and Gynecologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eALARA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eas low as reasonably achievable\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneral Electric\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIUFD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintrauterine fetal demise\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLBW\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow birth weight\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMFA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ematernal-fetal attachment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003e\u0026micro;L\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emicroliter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003emL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emilliliter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eng\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enanogram\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNICU\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneonatal intensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePLA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolylactic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePTD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epreterm delivery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRPM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erevolutions per minute\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSAS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estatistical analysis system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSTL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estereolithography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTLFB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etimeline follow back\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eU.S.\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was approved by the Creighton\u0026rsquo;s Institutional Review Board (protocol number 2001287), registered at clinicaltrials.gov (NCT04541121), carried out in accordance with The Code of Ethics of the World Medical Association for experiments involving humans, and all participants were provided informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eJC, RC and BC are related to the owner of the company that produced the 3D models for the study at cost. \u0026nbsp;All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile no identifying information was utilized, consent for 3D images utilized in Figure 1 was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to John Cot\u0026eacute; at [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData utilized for this manuscript can be found at 10.5281/zenodo.10901063\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of Funding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this study was provided by\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe State of Nebraska Cancer and Smoking Disease Research Program (LB595). \u0026nbsp; Creighton University School of Medicine, CHI/CommonSpirit Health, and the State of Nebraska had no role in the study design, collection, analysis, or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJC and ABB contributed to the study conception or data acquisition, analysis, interpretation, drafting or critical revision, final approval and accountability of this article. All other authors contributed to analysis, interpretation, drafting or critical revision, final approval and accountability of this article. \u0026nbsp;The author(s) read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank Ryan Walters PhD for overseeing this project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJohn J. Cot\u0026eacute; MD, FACOG\u003csup\u003eab*\u003c/sup\u003e, Remington D. Cot\u0026eacute;\u003csup\u003ec\u003c/sup\u003e, Dannie Dilsaver MS\u003csup\u003ed\u003c/sup\u003e, Suena Massey, MD\u003csup\u003eef\u003c/sup\u003e, Pooja Doehrman MD, MPH, FACOG\u003csup\u003eghi\u003c/sup\u003e, Brayden P. Cot\u0026eacute; BS\u003csup\u003ej\u003c/sup\u003e, Riley Kilzer BS\u003csup\u003ek\u003c/sup\u003e, Amy S. Badura-Brack PhD\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eCHI Health/CommonSpirit Health, Omaha, NE USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eCreighton University School of Medicine, Department of Obstetrics and Gynecology, Omaha, NE USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eCreighton University, Department of Biology, Omaha, NE \u0026nbsp; USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u003c/sup\u003eCreighton University School of Medicine, Department of Clinical Research and Public Health, Omaha, NE USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ee\u003c/sup\u003eBrigham and\u0026nbsp;Women\u0026rsquo;s Hospital, Department of\u0026nbsp;Psychiatry, Boston, MA, USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ef\u0026nbsp;\u003c/sup\u003eHarvard Medical School, Boston, MA, USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eg\u003c/sup\u003eCreighton University School of Medicine, Phoenix Campus, Department of Obstetrics and Gynecology,\u0026nbsp;Phoenix,\u0026nbsp;AZ USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eh\u003c/sup\u003eUniversity of Arizona College of Medicine, Department of Obstetrics and Gynecology, Phoenix,\u0026nbsp;AZ USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ei\u003c/sup\u003eDignity Health/CommonSpirit Health,\u0026nbsp;Phoenix,\u0026nbsp;AZ USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ej\u003c/sup\u003eChestnut Hill College, Department of Phycology, Philadelphia, PA USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ek\u003c/sup\u003eUniversity of Nebraska Medical Center, College of Medicine, Omaha, NE USA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003el\u003c/sup\u003eCreighton University, Department of Psychological Science, Omaha, NE USA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSequ\u0026iacute;-Canet JM, Sequ\u0026iacute;-Sabater JM, Marco-Sabater A, Corpas-Burgos F, Del Castillo JIC, Orta-Sib\u0026uacute; N. Maternal factors associated with smoking during gestation and consequences in newborns: Results of an 18-year study. J Clin Translational Res. 2022;8(1):6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGynecologists ACoOa. Tobacco and Nicotine Cessation During Pregnancy: ACOG Committee Opinion, Number 807. Obstet Gynecol. 2020;135(5):e221\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar R, Stevenson L, Jobling J, Bar-Zeev Y, Eftekhari P, Gould GS. Health providers\u0026rsquo; and pregnant women\u0026rsquo;s perspectives about smoking cessation support: a COM-B analysis of a global systematic review of qualitative studies. BMC Pregnancy Childbirth. 2021;21:1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCote JJ, Badura-Brack AS, Walters RW, Dubay NG, Bredehoeft MR. Randomized Controlled Trial of the Effects of 3D-Printed Models and 3D Ultrasonography on Maternal-Fetal Attachment. J Obstet Gynecol Neonatal Nurs. 2020;49(2):190\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCot\u0026eacute; JJ, C\u0026ocirc;t\u0026eacute;-Arsenault D, Handelzalts JE, Badura-Brack AS, Kalata M, Walters RW, et al. Effects of 3D-Printed Models and 3D Printed Pictures on Maternal\u0026ndash;and Paternal\u0026ndash;Fetal Attachment, Anxiety, and Depression. J Obstetric Gynecologic Neonatal Nurs. 2023;52(3):223\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMassey SH, Bublitz MH, Magee SR, Salisbury A, Niaura RS, Wakschlag LS, et al. Maternal-fetal attachment differentiates patterns of prenatal smoking and exposure. Addict Behav. 2015;45:51\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJussila H, Pelto J, Korja R, Ekholm E, Pajulo M, Karlsson L, et al. The association of maternal-fetal attachment with smoking and smoking cessation during pregnancy in The FinnBrain Birth Cohort Study. BMC Pregnancy Childbirth. 2020;20(1):1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKartal Z. Comparison of Prenatal Attachment Levels in Smoking and Non-Smoking Pregnant Women. Bağımlılık Dergisi. 2023;24(4):514\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCui Y, Robinson JD, Kypriotakis G, Minnix JA, Green CE, Kim S et al. Comparable cigarette consumption data collected using timeline follow-back and digital diary among treatment-seeking smokers. Psychol Addict Behav. 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenowitz NL, Schultz KE, Haller CA, Wu AH, Dains KM, Jacob P III. Prevalence of smoking assessed biochemically in an urban public hospital: a rationale for routine cotinine screening. Am J Epidemiol. 2009;170(7):885\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi H-K, Gan Y, Lu K, Wang C, Zhu Y, Meng X, et al. Maternal smoking status during pregnancy and low birth weight in offspring: systematic review and meta-analysis of 55 cohort studies published from 1986 to 2020. World J Pediatr. 2022;18(3):176\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDriscoll A, Osterman M, Hamilton B, Valenzuela C, Martin J. Quarterly Provisional Estimates for Selected Birth Indicators, Quarter 1, 2020\u0026ndash;Quarter 1, 2022. National Center for Health Statistics National Vital Statistics System, Vital Statistics Rapid Release Program.; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarrison-Desany HM, Ladd-Acosta C, Hong X, Wang G, Burd I, van der Meer Sanchez Z, et al. Addressing the smoking-hypertension paradox in pregnancy: insight from a multiethnic US birth cohort. Precision Nutr. 2023;2(2):e00035.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalvesen K, Abramowicz J, Ter Haar G, Miloro P, Sinkovskaya E, Dall'Asta A, et al. ISUOG statement on the non-diagnostic use of ultrasound in pregnancy. Ultrasound Obstet gynecology: official J Int Soc Ultrasound Obstet Gynecol. 2021;58(1):147.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeling K-S, Kozlowski P. Safety aspects of ultrasound in prenatal diagnosis. Ultraschall der Medizin-European J Ultrasound. 2020;41(02):116\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDudwiesus H, Merz E. How safe is it to use ultrasound in prenatal medicine? Facts and contradictions\u0026ndash;Part 2\u0026ndash;Laboratory experiments regarding non-thermal effects and epidemiological studies. Ultraschall der Medizin-European J Ultrasound. 2021;42(05):460\u0026ndash;502.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePascalis O, de Martin de Vivi\u0026eacute;s X, Anzures G, Quinn PC, Slater AM, Tanaka JW, et al. Development of face processing. Wiley Interdisciplinary Reviews: Cogn Sci. 2011;2(6):666\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLapaire O, Alder J, Peukert R, Holzgreve W, Tercanli S. Two- versus three-dimensional ultrasound in the second and third trimester of pregnancy: impact on recognition and maternal-fetal bonding. A prospective pilot study. Arch Gynecol Obstet. 2007;276(5):475\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWesterneng M, De Jonge A, Van Baar AL, Witteveen AB, Jellema P, Paarlberg KM, et al. The effect of offering a third-trimester routine ultrasound on pregnancy‐specific anxiety and mother‐to‐infant bonding in low‐risk women: A pragmatic cluster‐randomized controlled trial. Birth. 2022;49(1):61\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"3d-printing-in-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tdpm","sideBox":"Learn more about [3D Printing in Medicine](https://threedmedprint.biomedcentral.com/)","snPcode":"41205","submissionUrl":"https://submission.nature.com/new-submission/41205/3","title":"3D Printing in Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"3D-printing, Maternal-fetal attachment, Smoking, Pregnancy","lastPublishedDoi":"10.21203/rs.3.rs-4663887/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4663887/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSmoking in pregnancy continues to cause significant morbidity to mothers and babies and contributes to tremendous costs to society. Maternal-fetal attachment (MFA) may differentiate smokers who quit or pregnant smokers from non-smokers. Researchers have recommended utilizing interventions that improve MFA to help decrease smoking within pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a randomized clinical trial of pregnant smokers (\u003cem\u003en =\u003c/em\u003e 33) using an MFA-informed, intention-to-treat protocol. We recruited pregnant smokers and provided timeline follow back (TLFB) interviews from 27 weeks of pregnancy until 6 weeks post-partum. Salivary cotinine was also collected at five different time points. 3D ultrasonography was performed, and patients were randomly assigned a 3D picture or a 3D model of their fetus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, the average percent reduction in cigarette use was 37.03% (SD = 31.18). The main effect of 3D type was not significant (3D Model vs. 3D Print Estimate = -0.09, 95% CI: − 0.19 to 0.01, \u003cem\u003ep\u003c/em\u003e = 0.066). A total of 4 patients (12%) quit smoking within one week of delivery. A 10% reduction in cigarette use was associated with a 30.57 g increase in birth weight (Estimate = 30.57, 95% CI: -14.15 to 75.29); a 10% reduction in cigarette use was associated with a 0.14 week increase in estimate gestational age at delivery (Estimate = 0.14, 95% CI: -0.01 to 0.28).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients who smoke in pregnancy decrease the number of cigarettes smoked after receiving either a 3D picture or 3D model of their fetus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration: \u003c/strong\u003eclinicaltrials.gov (NCT04541121)\u003c/p\u003e","manuscriptTitle":"Effects of 3D ultrasonography and 3D printed images on maternal-fetal attachment and its correlation with overall smoking within pregnancy: A pilot study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-23 13:04:58","doi":"10.21203/rs.3.rs-4663887/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-22T20:54:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-31T15:11:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-31T14:46:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260849245846212345258393337156696824366","date":"2024-07-12T13:55:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274982378166688384038319340698408516318","date":"2024-07-10T12:07:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-10T04:22:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-30T23:34:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-30T23:34:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"3D Printing in Medicine","date":"2024-06-30T17:59:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"3d-printing-in-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tdpm","sideBox":"Learn more about [3D Printing in Medicine](https://threedmedprint.biomedcentral.com/)","snPcode":"41205","submissionUrl":"https://submission.nature.com/new-submission/41205/3","title":"3D Printing in Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af6866da-2b6f-4465-8652-4f84a88638bd","owner":[],"postedDate":"July 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:25:13+00:00","versionOfRecord":{"articleIdentity":"rs-4663887","link":"https://doi.org/10.1186/s41205-024-00238-7","journal":{"identity":"3d-printing-in-medicine","isVorOnly":false,"title":"3D Printing in Medicine"},"publishedOn":"2024-10-30 16:20:04","publishedOnDateReadable":"October 30th, 2024"},"versionCreatedAt":"2024-07-23 13:04:58","video":"","vorDoi":"10.1186/s41205-024-00238-7","vorDoiUrl":"https://doi.org/10.1186/s41205-024-00238-7","workflowStages":[]},"version":"v1","identity":"rs-4663887","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4663887","identity":"rs-4663887","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}