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Licensed Unlicensed Requires Authentication Published online by De Gruyter April 29, 2024

Reducing decisional conflict in decisions about prenatal genetic testing: the impact of a dyadic intervention at the start of prenatal care

  • Christina Collart ORCID logo , Caitlin Craighead ORCID logo , Meng Yao ORCID logo , Susannah Rose ORCID logo , Edward K. Chien , Richard M. Frankel ORCID logo , Marissa Coleridge , Bo Hu , Brownsyne Tucker Edmonds , Angela C. Ranzini ORCID logo and Ruth M. Farrell EMAIL logo

Abstract

Objectives

Decisional conflict and regret about prenatal genetic screening and diagnostic tests may have important consequences in the current pregnancy and for future reproductive decisions. Identifying mechanisms that reduce conflict associated with the decision to use or decline these options is necessary for optimal patient counseling.

Methods

We conducted a cluster-randomized controlled trial of a shared decision-making tool (NEST) at the beginning of prenatal care. Enrolled patients completed follow-up surveys at the time of testing (QTT) and in the second–third trimester (QFF), including the Decision Conflict Scale (DCS). Total DCS scores were analyzed using a multivariate linear mixed-effect model.

Results

Of the total number of participants (n=502) enrolled, 449 completed the QTT and QFF surveys. The mean age of participants was 31.6±3.8, with most parous at the time of study participation (n=321; 71.7 %). Both the NEST (the intervention) and control groups had lower median total DCS scores at QFF (NEST 13.3 [1.7, 25.0] vs. control 16.7 [1.7, 25.0]; p=0.24) compared to QTT (NEST 20.8 [5.0, 25.0] vs. control 18.3 [3.3, 26.7]; p=0.89). Participants exposed to NEST had lower decisional conflict at QFF compared to control (β −3.889; [CI −7.341, −0.437]; p=0.027).

Conclusions

Using a shared decision-making tool at the start of prenatal care decreased decisional conflict regarding prenatal genetic testing. Such interventions have the potential to provide an important form of decision-making support for patients facing the unique type of complex and preference-based choices about the use of prenatal genetic tests.


Corresponding author: Ruth M. Farrell, Obstetrics and Gynecology Institute, Cleveland Clinic, Cleveland, OH, USA, Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA; and Center for Bioethics, Clinical Transformation, Cleveland Clinic, 9500 Euclid Ave, A81 44195, Cleveland, OH, USA, Phone: 2163125083, E-mail:

Award Identifier / Grant number: R01HG010092

Acknowledgements

We would like to thank Patricia Agatisa, PhD, and Uma Perni, MD, for their contributions to this project.

  1. Research ethics: This study has complied with all relevant national regulations and institutional policies of the Cleveland Clinic. It has been approved by the authors’ Institutional Review Board. The study has been conducted in accordance with the Declaration of Helsinki (as revised in 2013).

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. All authors met the following criteria: (1) substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; (2) drafting the work or revising it critically for important intellectual content; (3) final approval of the version to be published; (4) agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  4. Competing interests: Dr. Rose is a consulting ethicist for Blue Cross Blue Shield Association (national nonprofit). The remaining authors state no conflict of interest.

  5. Research funding: This study was funded by a grant from the National Human Genome Research Institute (R01HG010092).

  6. Data availability: The raw data can be obtained on request from the corresponding author.

  7. Trial registration: The trial was registered in clinicaltrials.gov.

References

1. Almli, LM, Ely, DM, Ailes, EC, Abouk, R, Grosse, SD, Isenburg, JL, et al.. Infant mortality attributable to birth defects — United States, 2003–2017. Morb Mortal Wkly Rep 2020;69. https://doi.org/10.15585/mmwr.mm6902a1.Search in Google Scholar PubMed PubMed Central

2. Xu, J, Murphy, SL, Kochanek, KD, Bastian, BA. Division of vital statistics. Deaths: final data for 2013. In:National vital statistics reports: from the centers for disease control and prevention, national center for health statistics. Natl Vital Stat Rep.; 2016, vol 62:1–119 pp.Search in Google Scholar

3. Berg, JW, Appelbaum, PS, Lidz, CW, Parker, LS. Informed consent: legal theory and clinical practice. Oxford University Press; 2001.Search in Google Scholar

4. Faden, RR, Beauchamp, TL. A history and theory of informed consent. Oxford University Press; 1986.Search in Google Scholar

5. Tymitz, K, Lidor, A, Lidor, A. The Institute of medicine: crossing the quality chasm. In: Tichansky, D, Morton, J, Jones, D, editors. The SAGES manual of quality, outcomes and patient safety. Boston, MA: Springer; 2011.10.1007/978-1-4419-7901-8_37Search in Google Scholar

6. Romano, PS, Hussey, P, Ritley, D. Selecting quality and resource use measures: a decision guide for community quality collaboratives. AHRQ. 2010;9:0073.Search in Google Scholar

7. Martin, JA, Hamilton, BE, Ventura, SJ, Osterman, MJ, Kirmeyer, S, Mathews, TJ, et al.. Births: final data for 2009. In:National vital statistics reports: from the centers for disease control and prevention, national center for health Statistics. Natl Vital Stat Rep; 2011, vol 60:1–72 pp.Search in Google Scholar

8. Osterman, MJ, Martin, JA. System timing and adequacy of prenatal care in the United States, 2016. In:National vital statistics reports: from the centers for disease control and prevention, national center for health statistics. Natl Vital Stat Rep.; 2018, vol 67:1–14 pp.Search in Google Scholar

9. Lewis, C, Hill, M, Chitty, LS. A qualitative study looking at informed choice in the context of non-invasive prenatal testing for aneuploidy. Prenat Diagn 2016;36:875–81. https://doi.org/10.1002/pd.4879.Search in Google Scholar PubMed PubMed Central

10. Aetna. Serum and urine marker screening for fetal aneuploidy; 2020.Search in Google Scholar

11. Fowles, JB, Terry, P, Xi, M, Hibbard, J, Bloom, CT, Harvey, L. Measuring self-management of patients’ and employees’ health: further validation of the Patient Activation Measure (PAM) based on its relation to employee characteristics. Patient Educ Counsel 2009;77:116–22. https://doi.org/10.1016/j.pec.2009.02.018.Search in Google Scholar PubMed

12. Kim, JY, Wineinger, NE, Steinhubl, SR. The influence of wireless self-monitoring program on the relationship between patient activation and health behaviors, medication adherence, and blood pressure levels in hypertensive patients: a substudy of a randomized controlled trial. J Med Internet Res 2016;18:e116. https://doi.org/10.2196/jmir.5429.Search in Google Scholar PubMed PubMed Central

13. Shively, MJ, Gardetto, NJ, Kodiath, MF, Kelly, A, Smith, TL, Stepnowsky, C, et al.. Effect of patient activation on self-management in patients with heart failure. J Cardiovasc Nurs 2013;28:20–34. https://doi.org/10.1097/jcn.0b013e318239f9f9.Search in Google Scholar PubMed

14. Stortz, SK, Mulligan, S, Snipes, M, Hippman, C, Shridhar, NN, Stoll, K, et al.. A randomized controlled trial on the effect of standardized video education on prenatal genetic testing choices: uptake of genetic testing. Am J Perinatol 2021;40:267–73. https://doi.org/10.1055/s-0041-1727229.Search in Google Scholar PubMed

15. Domecq, JP, Prutsky, G, Elraiyah, T, Wang, Z, Nabhan, M, Shippee, N, et al.. Patient engagement in research: a systematic review. BMC Health Serv Res 2014;14. https://doi.org/10.1186/1472-6963-14-89.Search in Google Scholar PubMed PubMed Central

16. James, J, Hibbard, J, Agres, T, Lott, R, Dentzer, S. Health policy brief: patient engagement. Health Aff 2013;33:1–6.Search in Google Scholar

17. Schnock, KO, Snyder, JE, Fuller, TE, Duckworth, M, Grant, M, Yoon, C, et al.. Acute care patient portal intervention: portal use and patient activation. J Med Internet Res 2019;21:e13336. https://doi.org/10.2196/13336.Search in Google Scholar PubMed PubMed Central

18. Harvey, L, Fowles, JB, Xi, M, Terry, P. When activation changes, what else changes? The relationship between change in patient activation measure (PAM) and employees’ health status and health behaviors. Patient Educ Counsel 2012;88:338–43. https://doi.org/10.1016/j.pec.2012.02.005.Search in Google Scholar PubMed

19. Harris, PA, Taylor, R, Thielke, R, Payne, J, Gonzalez, N, Conde, JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inf 2009;42:377–81. https://doi.org/10.1016/j.jbi.2008.08.010.Search in Google Scholar PubMed PubMed Central

20. Harris, PA, Taylor, R, Minor, BL, Elliott, V, Fernandez, M, O’Neal, L, et al.. The REDCap consortium: building an international community of software platform partners. J Biomed Inf 2019;95. https://doi.org/10.1016/j.jbi.2019.103208.Search in Google Scholar PubMed PubMed Central

21. Marteau, TM, Dormandy, E, Michie, S. A measure of informed choice. Health Expect 2001;4:99–108. https://doi.org/10.1046/j.1369-6513.2001.00140.x.Search in Google Scholar PubMed PubMed Central

22. Lewis, C, Hill, M, Skirton, H, Chitty, LS. Development and validation of a measure of informed choice for women undergoing non-invasive prenatal testing for aneuploidy. Eur J Hum Genet 2015;24:809–16. https://doi.org/10.1038/ejhg.2015.207.Search in Google Scholar PubMed PubMed Central

23. Degner, LF, Sloan, JA. Decision making during serious illness: what role do patients really want to play? J Clin Epidemiol 1992;45:941–50. https://doi.org/10.1016/0895-4356(92)90110-9.Search in Google Scholar PubMed

24. O’Connor, AM. User manual – decisional conflict scale. Ottawa: Ottawa Hospital Research Institute; 1993.Search in Google Scholar

25. Collart, C, Craighead, C, Yao, M, Chien, E, Rose, S, Frankel, RM, et al.. Identifying Strategies to improve shared decision-making for pregnant patients’ decisions about prenatal genetic screens and diagnostic tests. [Manuscript submitted for publication].Search in Google Scholar

26. Elwyn, G, Hutchings, H, Edwards, A, Rapport, F, Wensing, M, Cheung, W, et al.. The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks. Health Expect 2005;8:34–42. https://doi.org/10.1111/j.1369-7625.2004.00311.x.Search in Google Scholar PubMed PubMed Central

27. Werner-Lin, A, Barg, FK, Kellom, KS, Stumm, KJ, Pilchman, L, Tomlinson, AN, et al.. Couple’s narratives of communion and isolation following abnormal prenatal microarray testing results. Qual Health Res 2016;26:1975–87. https://doi.org/10.1177/1049732315603367.Search in Google Scholar PubMed

28. Bernhardt, BA, Soucier, D, Hanson, K, Savage, MS, Jackson, L, Wapner, RJ. Women’s experiences receiving abnormal prenatal chromosomal microarray testing results. Genet Med 2013;15:139–45. https://doi.org/10.1038/gim.2012.113.Search in Google Scholar PubMed PubMed Central

29. Harding, E, Hammond, J, Chitty, LS, Hill, M, Lewis, C. Couples experiences of receiving uncertain results following prenatal microarray or exome sequencing: a mixed-methods systematic review. Prenat Diagn 2020;40:1028–39. https://doi.org/10.1002/pd.5729.Search in Google Scholar PubMed PubMed Central

30. Agatisa, PK, Mercer, MB, Mitchum, A, Coleridge, MB, Farrell, RM. Patient-centered obstetric care in the age of cell-free fetal DNA prenatal screening. J Patient Exp 2017;5:26–33. https://doi.org/10.1177/2374373517720482.Search in Google Scholar PubMed PubMed Central

31. Becerra-Perez, MM, Menear, M, Turcotte, S, Labrecque, M, Légaré, F. More primary care patients regret health decisions if they experienced decisional conflict in the consultation: a secondary analysis of a multicenter descriptive study. BMC Fam Pract 2016;17. https://doi.org/10.1186/s12875-016-0558-0.Search in Google Scholar PubMed PubMed Central

32. Elwyn, G, Frosch, D, Volandes, AE, Edwards, A, Montori, VM. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions. Med Decis Making 2010;30:701–11. https://doi.org/10.1177/0272989x10386231.Search in Google Scholar

33. Hillman, SC, Skelton, J, Quinlan‐Jones, E, Wilson, A, Kilby, MD. “If it helps.” the use of microarray technology in prenatal testing: patient and partners reflections. Am J Med Genet. 2013;161:1619–27, https://doi.org/10.1002/ajmg.a.35981.Search in Google Scholar PubMed

34. Kuppermann, M, Pena, S, Bishop, JT, Nakagawa, S, Gregorich, SE, Sit, A, et al.. Effect of enhanced information, values clarification, and removal of financial barriers on use of prenatal genetic testing. JAMA 2014;312:1210. https://doi.org/10.1001/jama.2014.11479.Search in Google Scholar PubMed PubMed Central

35. Bryant, AS, Norton, ME, Nakagawa, S, Bishop, JT, Pena, S, Gregorich, SE, et al.. Variation in women’s understanding of prenatal testing. Obstet Gynecol 2015;125:1306–12. https://doi.org/10.1097/aog.0000000000000843.Search in Google Scholar PubMed PubMed Central

36. Beulen, L, van den Berg, M, Faas, BH, Feenstra, I, Hageman, M, van Vugt, JM, et al.. The effect of a decision aid on informed decision-making in the era of non-invasive prenatal testing: a randomised controlled trial. Eur J Hum Genet 2016;24:1409–16. https://doi.org/10.1038/ejhg.2016.39.Search in Google Scholar PubMed PubMed Central

37. McGlothlin, AE, Lewis, RJ. Minimal clinically important difference: defining what really matters to patients. JAMA 2014;312:1342–3. https://doi.org/10.1001/jama.2014.13128.Search in Google Scholar PubMed

38. Hartwig, TS, Borregaard Miltoft, C, Malmgren, CI, Tabor, A, Jørgensen, FS. High risk—what’s next? A survey study on decisional conflict, regret, and satisfaction among high-risk pregnant women making choices about further prenatal testing for fetal aneuploidy. Prenat Diagn 2019;39:635–42. https://doi.org/10.1002/pd.5476.Search in Google Scholar PubMed

39. Gammon, BL, Jaramillo, C, Riggan, KA, Allyse, M. Decisional regret in women receiving high risk or inconclusive prenatal cell-free DNA screening results. J Matern Neonatal Med 2018;33:1412–18. https://doi.org/10.1080/14767058.2018.1519541.Search in Google Scholar PubMed PubMed Central

Received: 2023-10-16
Accepted: 2024-03-19
Published Online: 2024-04-29

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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