Preliminary outcomes of a new pelvic training app among incontinent pregnant women attending clinics in the Hulu Langat District, Selangor, Malaysia
Pregnant women do experience difficulty controlling urine or urinary incontinence (UI). Kegel exercise or pelvic floor muscle training (PFMT) is recommended for its treatment. PFMT is when someone performs pelvic floor muscle exercise (PFME), according to the prescription by healthcare professionals...
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Format: | Thesis |
Language: | English |
Published: |
2022
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Online Access: | http://psasir.upm.edu.my/id/eprint/103822/1/7648%20AIDA%20JAFFAR%2013122022%20-%20IR.pdf http://psasir.upm.edu.my/id/eprint/103822/ |
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Summary: | Pregnant women do experience difficulty controlling urine or urinary incontinence (UI). Kegel exercise or pelvic floor muscle training (PFMT) is recommended for its treatment. PFMT is when someone performs pelvic floor muscle exercise (PFME), according to the prescription by healthcare professionals. Despite advances in digital and mobile health apps, limited PFMT apps were evidence-based. Thus, this study proposed a PFMT mHealth app using the Capability, Opportunity, Motivational and Behaviour Model to assist in its adherence. This study aimed to develop and evaluate the preliminary outcomes of a PFMT app on knowledge, attitude, practice, self-efficacy, and adherence to PFMT among incontinent pregnant women attending a clinic in Hulu Langat district, Selangor.
The multiphase mixed methods design approach comprises three main phases were involved. In phase 1, two studies were conducted; (1) a cross-sectional study to determine the knowledge, attitude, and practices (KAP) of pelvic floor muscle exercise (PFME), the prevalence of UI and its quality of life (QOL) among pregnant women (N=440), through validated questionnaires (Knowledge, Attitude and Practice on PFME, Incontinence Questionnaire-Urinary Incontinence Short Form, and ICIQ-Lower Urinary Tract Symptoms Quality of Life, and (2) five focus group discussions (FGDs) to evaluate pregnant women’s (N=24) preferred design for the app. In phase 2, two concurrent studies were performed to finalize the Kegel Exercise Pregnancy Training (KEPT) app prototype design. It consisted of usability studies from both incontinent pregnant women (N=5) and experts (N=4) using the Malay-mHealth App Usability Questionnaire (Malay-MAUQ), and mHealth App Usability Questionnaire (MAUQ). Finally, phase 3 involved a pilot randomized control trial (RCT) among incontinent pregnant women (N=26) to assess the preliminary outcomes of the KEPT app, utilizing a few questionnaires, such as the Exercise Adherence Rating Scale, the Self-Efficacy Scale For Practicing Pelvic Floor Exercise Questionnaire, and the Malay-MAUQ, in addition to similar questionnaires as phase 1. The generalized estimating equation (GEE) was used to compare both groups' improvement scores.
Phase 1 indicated that the mean age of respondents was 29.8 years old (SD 4.69), with the prevalence of UI moderately high at 40.1% (95%CI: 2.04-2.70), and only 12.7% performed regular PFME. Stress UI, (OR 6.94, 95%CI 4.00–12.04) and urge UI (OR3.87, 95%CI 0.48–31.28) were significantly associated with negative QOL. Phase 2 demonstrated that the incontinent pregnant women evaluated the app’s ease-of-use, interface and satisfaction, and usefulness with 5.52/7.0, 6.4/7.0, and 6.17/7.0, respectively, whereas the experts evaluated the app’s ease-of-use, interface and satisfaction, and usefulness with 5.80/7.0, 5.57/7.0, and 5.83/7.0. Phase 3 reported a retention rate of 61.5%, and only attitude toward PFMT was significantly improved post-intervention (β = 5.884, P = 0.034), whilst the adherence towards PFMT scored with (β = -2.910, P = 0.312). They rated the KEPT app (interactive version) as being usable with system information arrangement (4.98/7.0), usefulness (4.89/7.0), and ease-of-use and satisfaction (5.03/7.0).
Therefore, the KEPT app has the potential to help pregnant women adhere to PFMT. Future research should identify the effectiveness of the KEPT app in achieving adherence to PFMT and improving its UI. |
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