Korean J Women Health Nurs.  2023 Mar;29(1):20-31. 10.4069/kjwhn.2023.02.21.

Analysis of online parenting community posts on expanded newborn screening for metabolic disorders using topic modeling: a quantitative content analysis

Affiliations
  • 1Department of Nursing, Nambu University, Gwangju, Korea
  • 2Department of Computer Engineering, Chosun University, Gwangju, Korea
  • 3Department of Nursing, Chosun University, Gwangju, Korea

Abstract

Purpose
As more newborns have received expanded newborn screening (NBS) for metabolic disorders, the overall number of false-positive results has increased. The purpose of this study was to explore the psychological impacts experienced by mothers related to the NBS process. Methods: An online parenting community in Korea was selected, and questions regarding NBS were collected using web crawling for the period from October 2018 to August 2021. In total, 634 posts were analyzed. The collected unstructured text data were preprocessed, and keyword analysis, topic modeling, and visualization were performed. Results: Of 1,057 words extracted from posts, the top keyword based on ‘term frequency-inverse document frequency’ values was “hypothyroidism,” followed by “discharge,” “close examination,” “thyroid-stimulating hormone levels,” and “jaundice.” The top keyword based on the simple frequency of appearance was “XXX hospital,” followed by “close examination,” “discharge,” “breastfeeding,” “hypothyroidism,” and “professor.” As a result of LDA topic modeling, posts related to inborn errors of metabolism (IEMs) were classified into four main themes: “confirmatory tests of IEMs,” “mother and newborn with thyroid function problems,” “retests of IEMs,” and “feeding related to IEMs.” Mothers experienced substantial frustration, stress, and anxiety when they received positive NBS results. Conclusion: The online parenting community played an important role in acquiring and sharing information, as well as psychological support related to NBS in newborn mothers. Nurses can use this study’s findings to develop timely and evidence-based information for parents whose children receive positive NBS results to reduce the negative psychological impact.

Keyword

Information; Inborn metabolism errors; Mothers; Neonatal screening; 정보; 선천성 대사이상; 어머니; 신생아선별검사

Figure

  • Figure 1. Visualization of the top 500 keywords by term frequency (A) and term frequency-inverse document frequency (B).

  • Figure 2. Silhouette coefficient to the number of topics.

  • Figure 3. Topic network of the main keywords.

  • Figure 4. Word cloud of topic keywords. (A) Topic 1: feeding related to IEMs. (B) Topic 2: mother and newborn with thyroid function problems. (C) Topic 3: retests of IEMs. (D) Topic 4: confirmatory tests of IEMs.IEM: Inborn error of metabolism.


Reference

References

1. Kim TK, Lee SH, Yu ST, Oh YK. Analysis of major factors affecting false positive results in neonatal screening test within 3 days after birth. Perinatol. 2019; 30(3):154–159. https://doi.org/10.14734/PN.2019.30.3.154.
Article
2. Lee DH. The past, present, future of newborn screening in Korea. J Korean Soc Inherit Metab Dis. 2014; 14(1):1–9.
3. O'Connor K, Jukes T, Goobie S, DiRaimo J, Moran G, Potter BK, et al. Psychosocial impact on mothers receiving expanded newborn screening results. Eur J Hum Genet. 2018; 26(4):477–484. https://doi.org/10.1038/s41431-017-0069-z.
4. Kim H, Shin SM, Ko SY, Lee YK, Park SW. Investigation of false positive rates newborn screening using Tandem Mass Spectrometry (TMS) technology in single center. J Korean Soc Inherit Metab Dis. 2016; 16(1):18–23.
5. Song WJ, Lee S, Jeon YM, Kim SZ, Jang MY. 18-year follow-up of expanded newborn screening for metabolic and endocrine disorders. J Korean Soc Inherit Metab Dis. 2018; 18(2):35–42.
6. Cho SE, Park EJ, Seo DH, Lee IB, Lee HJ, Cho DY, et al. Neonatal screening tests for inherited metabolic disorders using tandem mass spectrometry: experience of a clinical laboratory in Korea. Lab Med Online. 2015; 5(4):196–203. https://doi.org/10.3343/lmo.2015.5.4.196.
Article
7. Schmidt JL, Castellanos-Brown K, Childress S, Bonhomme N, Oktay JS, Terry SF, et al. The impact of false-positive newborn screening results on families: a qualitative study. Genet Med. 2012; 14(1):76–80. https://doi.org/10.1038/gim.2011.5.
Article
8. Dinchong R. Reducing the pyschosocial impact of a false positive newborn screen for inborn errors of metabolism [master thesis]. Winnipeg, MB: University of Manitoba; 2019. 121 p.
9. DeLuca J, Zanni KL, Bonhomme N, Kemper AR. Implications of newborn screening for nurses. J Nurs Scholarsh. 2013; 45(1):25–33. https://doi.org/10.1111/jnu.12005.
Article
10. Joseph RA. Expanded newborn screening: challenges to NICU nurses. Adv Neonatal Care. 2017; 17(3):151–161. https://doi.org/10.1097/ANC.0000000000000381.
Article
11. Malvagia S, Forni G, Ombrone D, la Marca G. Development of strategies to decrease false positive results in newborn screening. Int J Neonatal Screen. 2020; 6(4):84. https://doi.org/10.3390/ijns6040084.
Article
12. DeLuca JM, Kearney MH, Norton SA, Arnold GL. Parents’ experiences of expanded newborn screening evaluations. Pediatrics. 2011; 128(1):53–61. https://doi.org/10.1542/peds.2010-3413.
Article
13. Gehtland LM, Paquin RS, Andrews SM, Lee AM, Gwaltney A, Duparc M, et al. Using a patient portal to increase enrollment in a newborn screening research study: observational study. JMIR Pediatr Parent. 2022; 5(1):e30941. https://doi.org/10.2196/30941.
Article
14. Abad PJ, Sibulo MS, Sur AL. Role of the nurse in newborn screening: Integrating genetics in nursing education and practice. Philipp J Nurs. 2019; 89(1):16–21.
15. Mak CM, Law EC, Lee HH, Siu WK, Chow KM, Au Yeung SK, et al. The first pilot study of expanded newborn screening for inborn errors of metabolism and survey of related knowledge and opinions of health care professionals in Hong Kong. Hong Kong Med J. 2018; 24(3):226–237. https://doi.org/10.12809/hkmj176939.
Article
16. Moody L, Atkinson L, Kehal I, Bonham JR. Healthcare professionals’ and parents’ experiences of the confirmatory testing period: a qualitative study of the UK expanded newborn screening pilot. BMC Pediatr. 2017; 17(1):121. https://doi.org/10.1186/s12887-017-0873-1.
Article
17. Newcomb P, True B, Wells JN, Walsh J, Pehl S. Informing new mothers about newborn screening bloodspot repositories during postpartum hospitalization. MCN Am J Matern Child Nurs. 2019; 44(6):332–337. https://doi.org/10.1097/NMC.0000000000000562.
Article
18. Park SH, Woo MS, June KJ, Yu JO. Analysis of women’s concern about pregnancy and child birth in the internet community. Perspect Nurs Sci. 2020; 17(1):49–60. https://doi.org/10.16952/pns.2020.17.1.49.
Article
19. You MA, Baek EB, Kang NG. The influences of mother’s eHealth literacy, health information orientation, and social support on the use of internet on health promotion behaviors for their children. J Health Info Stat. 2021; 46(2):221–229. https://doi.org/10.21032/jhis.2021.46.2.221.
Article
20. Moon RY, Mathews A, Oden R, Carlin R. Mothers’ perceptions of the internet and social media as sources of parenting and health information: qualitative study. J Med Internet Res. 2019; 21(7):e14289. https://doi.org/10.2196/14289.
Article
21. Yu JO, June KJ, Park SH, Woo MS. Content analysis of mothers’ questions related to parenting young children in internet parenting community. J Korean Soc Matern Child Health. 2020; 24(4):234–243. https://doi.org/10.21896/jksmch.2020.24.4.234.
Article
22. Blei DM. Probabilistic topic models. Communications ACM. 2012; 55(4):77–84. https://doi.org/10.1145/2133806.2133826.
Article
23. Lee J, Kim Y, Kwak E, Park S. A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling. J Korean Acad Soc Nurs Educ. 2021; 27(2):175–185. https://doi.org/10.5977/jkasne.2021.27.2.175.
Article
24. Cyram Inc. CYRAM NetMiner 4.4 program. Seongnam: Cyram Inc.; 2021.
25. Statistics Korea. The 8th Korean Standard Classification of Diseases and Causes. Seoul: Statistics Korea; 2020.
26. Jeong SJ. A topic modeling approach to the analysis of domestic environmental education research trend: focusing on Journal of Korean Society for Environmental Education. Korean J Environ Educ. 2020; 33(2):231–246. https://doi.org/10.17965/kjee.2020.33.2.231.
Article
27. Lee SS. A study on the application of topic modeling for the book report text. J Korean Libr Info Sci Soc. 2016; 47(4):1–18. https://doi.org/10.16981/kliss.47.4.201612.1.
Article
28. Naili M, Chaibi AH, Ghézala HB. Arabic topic identification based on empirical studies of topic models. ARIMA Journal. 2017; 27:45–59. https://doi.org/10.46298/arima.3102.
Article
29. Mehta V, Caceres RS, Carter KM. Evaluating topic quality using model clustering. Paper presented at: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM); 2014 Dec 9-12; Orlando, FL. IEEE; 2014. p. 178-185. https://doi.org/10.1109/cidm.2014.7008665.
30. Hong KB, Park JY, Chang YP, Yu J. Thyroid dysfunction in premature infants. Korean J Pediatr. 2009; 52(9):991–998. https://doi.org/10.3345/kjp.2009.52.9.991.
Article
31. Conway M, Vuong TT, Hart K, Rohrwasser A, Eilbeck K. Pain points in parents' interactions with newborn screening systems: a qualitative study. BMC Pediatr. 2022; 22(1):167. https://doi.org/10.1186/s12887-022-03160-1.
Article
32. Park JH, Moon CJ, Jung MH, Sung IK, Kim SY. Perinatal factors associated with the preterm thyroid screening test. Korean J Perinatol. 2016; 27(1):45–52. https://doi.org/10.14734/kjp.2016.27.1.45.
Article
33. Yoon HR, Ahn S, Lee H. Evaluation of the congenital hypothyroidism for newborn Screening program in Korea: a 14-year retrospective cohort study. J Korean Soc Inherit Metab Dis. 2019; 19(1):1–11.
34. de Miranda KS, dos Santos IC, de Almeida Neto OP, Calegari T. Barriers experienced by nurses in newborn screening: a integrative review. Revista de Atenção à Saúde,. 2020; 8(66):247–256. https//doi.org/10.13037/ras.vol18n66.7212.
35. Timmermans S, Buchbinder M. Patients-in-waiting: living between sickness and health in the genomics era. J Health Soc Behav. 2010; 51(4):408–423. https://doi.org/10.1177/0022146510386794.
Article
36. Kamleh M, Williamson JM, Casas K, Mohamed M. Reduction in newborn screening false positive results following a new collection protocol: a quality improvement project. J Pediatr Pharmacol Ther. 2021; 26(7):723–727. https://doi.org/10.5863/1551-6776-26.7.723.
Article
37. Rosettenstein KR, Lain SJ, Wormleaton N, Jack MM. A systematic review of the outcomes of false-positive results on newborn screening for congenital hypothyroidism. Clin Endocrinol (Oxf). 2021; 95(5):766–781. https://doi.org/10.1111/cen.14562.
Article
38. IJzebrink A, van Dijk T, Franková V, Loeber G, Kožich V, Henneman L, et al. Informing parents about newborn screening: a European comparison study. Int J Neonatal Screen. 2021; 7(1):13. https://doi.org/10.3390/ijns7010013.
Article
39. Whittemore B. A newborn screening disorders online portal for the primary care providers and parents [doctoral dissertation]. Fort Lauderdale, FL: Nova Southeastern University; 2019. 133 p.
40. Barr JA, Tsai LP, Welch A, Faradz SM, Lane-Krebs K, Howie V, et al. Current practice for genetic counselling by nurses: an integrative review. Int J Nurs Pract. 2018; 24(2):e12629. https://doi.org/10.1111/ijn.12629.
Article
41. Choi KS, Kim HJ, Jang ES, Park JA. A study of the curriculum of genetics nursing education. J Korean Oncol Nurs. 2010; 10(1):103–111.
42. Choi H. Undergraduate nursing students’ perceived knowledge and attitudes toward genetics and nursing competencies for genetics. J Korean Biol Nurs Sci. 2014; 16(2):69–79. https://doi.org/10.7586/jkbns.2014.16.2.69.
Article
43. Sohn YB. A diagnostic algorithm of newborn screening for galactosemia. J Korean Soc Inherit Metab Dis. 2015; 15(3):101–109.
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