The Effect of Mobile Application Support for Postpartum Women on Postpartum Quality of Life

Year 2021, Volume: 11 Issue: 2, 242 - 250, 30.06.2021

Pınar Mallı Ayla Berkiten Ergin

https://doi.org/10.33808/clinexphealthsci.731557

Cited By: 1

Abstract

Objective: This study aims to determine the effect of a mobile application prepared by midwives on postpartum quality of life, and to present a mobile training method for use by health care professionals.

Methods: The sample for this randomized controlled study consisted of 64 (experimental group = 32, control group = 32) postpartum women for whom inclusion criteria for participation in the study were that they presented to a private counseling center had the ability to use the internet and mobile applications. The study was conducted between March 1, 2018 and July 15, 2019. Data were collected using the Maternal
Postpartum Quality of Life Questionnaire (MAPPQOL) and the Web-based Education Software Scale (WBESS) to gather descriptive characteristics of the participants and obstetric data. Applicable statistical methods, which included Mann-Whitney U test, and Spearman correlation test.

Results: The mean scores on the MAPPQOL for the control and experimental group were 21.99 ± 2.97 and 20.30 ± 4.33. There was nostatistically significant difference between the mean scores obtained by the two groups on the MAPPQOL (p = 0.073; p> 0.05). Furthermore, there was no statistically significant relationship between the mean scores on the total MAPPQOL and the mean MAPPQOL subscale scores of the experimental group and the mean scores on the WBESS and the subscale scores of this scale (p> 0.05). It was found that the experimental group’s competence level of the mobile application (62.5 %, n = 32) was very good according to their WBESS mean score.

Conclusion: Postpartum quality of life score swere found to be higher in the postpartum patients who used the mobile application and it was observed that mobile application support increased postpartum quality of life. The scope was found to be valid this comprehensive mobile training model can be in recommended for use midwifery applications.

Keywords

Midwifery, mobile application, mobile health, postpartum, postpartum quality of life, innovation in midwifery

Project Number

2018/059 nolu Bilimsel Araştırma

References

• REFERENCES 1. Aslan E. Normal Puerperium Process and Care, (Chapter 14). Nezihe Kızılkaya Beji (Ed) Women's Health and Diseases for Nurses and Midwives, Extended Edition II. Copyright Nobel Publication, Ankara, 2017, 413-472.
• 2. Murray S, Mckinney E. Foundations of Maternal –Newborn and Women’s Health Nursing (5th Edition). Missouri, 2010, Chapter 17, 391-420.
• 3. Şimşek Ç, Esencan T. Nursing Care During the Postpartum Period. Medical Bulletin of Zeynep Kâmil. 2017; 48(4):183-189.
• 4. Optimizing postpartum care. ACOG Committee Opinion No. 736. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2018; 131: e140–50.
• 5. WHO, Managing Complications In Pregnancy And Childbirth: A Guide For Midwives and Doctors? 2017 (To access: 30.05.2019) https:/ /apps. who. int/iris/bitstream/ handle/ 10665/ 255760/9789241565493-eng. pdf; jsessionid= 81926615 AD706AD36BF9A2F8B4787FB1? sequence=1
• 6. Waegemann CP. Mhealth: The Next Generation of Telemedicine? Telemedicine and e-Health. 2010;16(1) :23-25, doi: 10.1089/tmj.2010.9990.
• 7. Shorey S, Yang YY, Dennis CL. A Mobile Health App-Based Postnatal Educational Program (Home-but not Alone): Descriptive Qualitative Study. J Med Internet Res. 2018;20(4):e119. Published 2018 Apr 19. doi:10.2196/jmir.9188.
• 8. United Nations Foundations. Mhealth For Development: Mobile For Communication. (Toaccess:10.04.2019) http://www.globalproblems-globalsolutions-files.org/unf_website/assets/publications/technology/mhealth/mHealth_for_Development_full.pdf
• 9. Entsieh AA, Emmelin M, Odberg Pettersson K. Learning the ABCs of pregnancy and newborn care through mobile technology, Global Health Action. 2015; 8:1, doi: 10.3402/ gha.v8.29340.
• 10. Velez O, Okyere BP, Kanter SA, Bakken S, A Usubility Study of A Mobile Helath Aplication For Rural Ghanaihan Midwives, J Midwifery Women’s Health. 2014; 59(2): 184–191. doi:10.1111/jmwh.12071.
• 11. Zadoroznyj M, Brodribb WE, Young K. ‘I really needed help’: What mothers say about their post-birth care in Queensland, Australia. Women and Birth. 2015; 28(3): 246-51, (doi: 10.1016/j.wombi.2015.03.004).
• 12. Colaceci S, Glusti A, Chapin EM. E-Learning to Improve Healthcare Professionals’ Attitudes and Practices on Breastfeeding. Breastfeeding Medicine, 2017; 12(10). 629-636.
• 13. Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement, Updated Guidelines for Reporting Parallel Group Randomized Trials, American Collage of Obstetricans and Gynecologists. 2010; 115(3). 1063-70.
• 14. Fiş Erümit S. Designing and Implementing Course Material in Web Based Distance Education and Determining Criteria for Material Designing, Master Thesis. Karadeniz Technical University, Institute of Science and Technology, Trabzon, 2011.
• 15. Top ED, Karaçam Z. Effectiveness of Education on Reducing of Depression Symptom Level in Women During Postpartum Period, Master Thesis, Adnan Menderes University, Institute of Health Science. Aydın, 2012
• 16. Hill PD, Aldağ J, Hekel B, Riner G. Maternal Postpartum Quality of Life Questionnaire. Journal of Nursing Measurement. 2006, Winter;14(3):205-20.
• 17. Altuntuğ K, Ege E. Validity and Reliability of Turkish Version of Maternal Postpartum Quality of Life Questionnaire. Journal of Anatolia Nursing and Health Sciences. 2012; 15(3), 214-222.
• 18. Osma J, Barrera AZ, Ramphos E. Are Pregnant and Postpartum Women Interested In Health-Related Apps? Implications for The Prevention Of Perinatal Depression. Cyberpsychol Behav Soc Netw. 2016;19 (6): 412-5. doi: 10.1089/cyber.2015.0549.
• 19. Peragallo Urrutia R, Berger AA, Ivins AA, Urrutia EG, Beckham AJ, Thorp JM Jr, Nicholson WK. Internet Use and Access Among Pregnant Women via Computer and Mobile Phone: Implications for Delivery of Perinatal Care, JMIR Mhealth Uhealth. 2015;3(1):e25, doi: 10.2196/mhealth.3347.
• 20. PEW research, Internet/Broadband Fact Sheet (To access: 22.08.2019) https://www.pewinternet.org/fact-sheet/internet-broadband/
• 21. TUİK, Household Information Technology (IT) Use Survey 2018 Report (To access: 22.08.2019) http://www.tuik.gov.tr/PreHaberBultenleri.do?id=27819
• 22. Hadımlı A, Demirelöz Akyüz M and Tuna Oran N. Pregnant Women' Frequencies and Causes of Using the Internet, Life Sciences (NWSALS). 2018; 13(3):32-43, doi: 10.12739/NWSA.2018.13.3.4B0018.
• 23. Baker B, Yang I. Social Media as Social Support in Pregnancy and the Postpartum, Sexual& Reproductive Healthcare. 2018; 17; 31-34, doi: https:// doi. org/10.1016/j.srhc. 2018.05.003.
• 24. Bağcı S, Altuntuğ K. Problems Experienced by Mothers in Postpartum Period and Their Associations with Quality of Life. Journal of Human Sciences. 2016;13(2): 3266-3279, (doi:10.14687/Jhs.V13i2.3884).
• 25. Özkan Şat S, Yaman Sözbir Ş. Use f Mobile Applications and Blogs by Pregnant Women in Turkey and The Impact On Adaptation To Pregnancy. Midwifery. 2018; 62:273-277. doi.org/10.1016/j.midw.2018.04.001.
• 26. Guerra Reyes L, Christie MV, Prabhakar A et al. Postpartum Health information seeking using mobile phones: Experiences of low- income mothers. Maternal Child Health J. 2016; 20:13–21.
• 27. Kuo MC, Lu YC, Chang P. A Newborn Baby Care Support App and System for Mhealth. 11th International Congress on Nursing Informatics, Canada. 2012: P. 228-228
• 28. Himes KP, Donovan H, Wang S et al. Healthy Beyond Pregnancy, a Web-Based Intervention to Improve Adherence to Postpartum Care: Randomized Controlled Feasibility. Trial JMIR Hum Factors. 2017;4(4): e26, doi: 10.2196/humanfactors.7964.
• 29. Feroz, A., Perveen, S. & Aftab, W. Role of Mhealth Applications for Improving Antenatal and Postnatal Care In Low And Middle Income Countries: A Systematic Review. BMC Health Serv Re. 2017, Nov 7. doi: 10.1186/s12913-017-2664-7.
• 30. Jiménez-Serrano S, Tortajada S, García-Gómez Jm. A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning. Telemed J E Health. 2015 Jul;21(7):567-74. doi: 10.1089/tmj.2014.0113. Epub 2015 Mar 3.