Literature DB >> 33688842

Mobile App-Based Intervention for Pregnant Women With Stress Urinary Incontinence: Protocol for a Hybrid Effectiveness-Implementation Trial.

Tiantian Li1,2, Xiaomin Chen1, Jia Wang1,2, Ling Chen1, Wenzhi Cai1,2.   

Abstract

BACKGROUND: Stress urinary incontinence (SUI) is a common source of distress among women during and after pregnancy. It has a negative effect on quality of life but with poor care-seeking. Mobile health (mHealth) may be a promising solution with potential advantages. However, there is uncertainty whether a mobile app is effective for SUI symptom improvement during and after pregnancy. The implementation is also unclear. We developed an app named UIW (Urinary Incontinence for Women) aimed at improving perinatal incontinence.
OBJECTIVE: The objective of this study is to evaluate the effectiveness of the UIW app-based intervention in improving SUI symptoms among pregnant women and explore the facilitators and barriers to using the UIW app to help refine and optimize the intervention.
METHODS: This study is a hybrid effectiveness-implementation trial with a randomized controlled trial alongside a mixed-methods process evaluation according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Pregnant women with SUI (n=336) will be recruited from a university-affiliated hospital in China. They will be randomly allocated (1:1) to either the intervention group that receive usual care plus UIW app or control group that receive usual care alone. The intervention period will last 2 months. The 5 dimensions of the RE-AIM framework will be evaluated at recruitment (-T1), baseline (T0), immediately after intervention (T1), 42 days after delivery (T2), 3 months after delivery (T3), and 6 months after delivery (T4) through project documents, online questionnaires and a pelvic floor muscle training diary, surface electromyography, log data in the background management system, and qualitative interviews. Data analysis will follow the intention-to-treat principle. Descriptive statistics, t tests, chi-square tests, and a linear mixed model will be used to analyze the quantitative data. Deductive and inductive content analysis will be used to analyze the qualitative data.
RESULTS: The effectiveness-implementation trial started in June 2020, trial recruitment was completed in October 2020, and the intervention will last for a 2-month period. Completion of the 6-month follow-up will be in July 2021, and we anticipate that the results of this study will be published in December 2021.
CONCLUSIONS: This study will evaluate both effectiveness and implementation of the UIW app-based intervention among pregnant women. The hybrid effectiveness-implementation trial design according to the RE-AIM framework with a mixed-methods approach will give valuable insights into the effects as well as facilitators and barriers to the implementation that will influence the effects of the UIW app-based intervention. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1800016171; http://www.chictr.org.cn/showproj.aspx?proj=27455. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/22771. ©Tiantian Li, Xiaomin Chen, Jia Wang, Ling Chen, Wenzhi Cai. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 10.03.2021.

Entities:  

Keywords:  mHealth; mixed methods; pregnancy; process evaluation; randomized controlled trial; stress urinary incontinence; study protocol

Year:  2021        PMID: 33688842      PMCID: PMC7991980          DOI: 10.2196/22771

Source DB:  PubMed          Journal:  JMIR Res Protoc        ISSN: 1929-0748


  55 in total

1.  Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.

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2.  Achieving integration in mixed methods designs-principles and practices.

Authors:  Michael D Fetters; Leslie A Curry; John W Creswell
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Review 3.  Preventing urinary incontinence during pregnancy and postpartum: a review.

Authors:  Stian Langeland Wesnes; Gunnar Lose
Journal:  Int Urogynecol J       Date:  2013-02-23       Impact factor: 2.894

4.  "Are you doing your pelvic floor?" An ethnographic exploration of the interaction between women and midwives about pelvic floor muscle exercises (PFME) during pregnancy.

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Review 5.  An International Urogynecological Association (IUGA)/International Continence Society (ICS) joint report on the terminology for female pelvic floor dysfunction.

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6.  The Chinese version of ICIQ: a useful tool in clinical practice and research on urinary incontinence.

Authors:  Liang Huang; Song-wen Zhang; Shi-liang Wu; Le Ma; Xiao-hong Deng
Journal:  Neurourol Urodyn       Date:  2008       Impact factor: 2.696

7.  Scientific rigour in qualitative research--examples from a study of women's health in family practice.

Authors:  K Hamberg; E Johansson; G Lindgren; G Westman
Journal:  Fam Pract       Date:  1994-06       Impact factor: 2.267

Review 8.  Stress urinary incontinence in pregnant women: a review of prevalence, pathophysiology, and treatment.

Authors:  Bussara Sangsawang; Nucharee Sangsawang
Journal:  Int Urogynecol J       Date:  2013-02-23       Impact factor: 2.894

9.  Community-based exercise for health promotion and secondary cancer prevention in Canada: protocol for a hybrid effectiveness-implementation study.

Authors:  Margaret L McNeely; Christopher Sellar; Tanya Williamson; Melissa Shea-Budgell; Anil Abraham Joy; Harold Y Lau; Jacob C Easaw; Albert D Murtha; Jeffrey Vallance; Kerry Courneya; John R Mackey; Matthew Parliament; Nicole Culos-Reed
Journal:  BMJ Open       Date:  2019-09-13       Impact factor: 2.692

10.  Pelvic floor muscle training versus no treatment, or inactive control treatments, for urinary incontinence in women.

Authors:  Chantale Dumoulin; Licia P Cacciari; E Jean C Hay-Smith
Journal:  Cochrane Database Syst Rev       Date:  2018-10-04
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  2 in total

Review 1.  Persuasive Technology in an mHealth App Designed for Pelvic Floor Muscle Training Among Women: Systematic Review.

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2.  Mitigating urinary incontinence condition using machine learning.

Authors:  Haneen Ali; Abdulaziz Ahmed; Carlos Olivos; Khaled Khamis; Jia Liu
Journal:  BMC Med Inform Decis Mak       Date:  2022-09-17       Impact factor: 3.298

  2 in total

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