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The overall purpose of this study was to determine whether an app-based treatment was as effective as “usual care” for treating urinary incontinence (UI) [1]. Usual care consisted of pelvic floor muscle training or bladder training, pessary placement, drugs, absorbent products, or referral to a pelvic physical therapist. The researchers examined all types of UI including stress, urgency, and mixed-type. As the primary outcome, they used the International Consultation on Incontinence Modular Questionnaire Urinary Incontinence Short Form (ICIQ-UI-SF) to assess the change of UI severity from baseline to 4 months following treatment. They compared the results of this questionnaire between groups. As secondary outcomes, they looked at the change in UI-specific lower urinary tract symptoms quality of life, the number of UI episodes per day, and the overall feeling of improvement of urinary incontinence.
This study used a parallel-arm, randomized, non-inferiority study design in the North of the Netherlands. Due to the nature of the treatment, participants and their clinicians were not blinded to the treatment. A total of 262 women were randomized into either the usual care group or the app-based treatment group. The study used a linear regression analysis to determine if the app-based treatment was non-inferior to usual care in reducing UI severity in a time frame of 4 months. Because there was no significant difference in severity of UI symptoms between groups, the results suggest that the app-based treatment was indeed non-inferior, but also non superior, to usual care in the treatment of UI symptoms.
Global impression of UI symptom improvement was a secondary outcome and statistical significance was not calculated for each category of improvement. Our group discussed how there was a greater proportion of patients in the usual care group who rated their improvement as “very much better” as compared to the app-based group. This suggests that analyzing the data stratified by levels of improvement may show differences at various levels. A standardized approach to the “care as usual” treatment would have eliminated the variety of care approaches to UI. The study was performed at 31 practices in the Netherlands which leads to the potential for inconsistent care, weakening the study results. Although the 31 practices were following guidelines, different amounts of time may have been spent counseling each patient. This may impact the effectiveness of treatments such as pelvic floor exercises if less time was given to teaching proper technique. In addition, severity of UI was not stratified and was defined as women with two episodes of UI per week, meaning that women with varying levels of incontinence severity were compared. Efficacy of treatment methods could differ by incontinence severity and this was not captured in the analysis. Finally, risk factors for UI including number of births, family history of UI and patient weight were not considered.
Selection bias may be present with the study group more adherent to treatment than the general population. The participants selected for the study had already brought up urinary incontinence to their physician and were seeking treatment. Therefore, they may be more motivated to adhere to treatment. Inclusion criterion for the study may have favored those who had increased access to health care due to the requirement of a smartphone or tablet and recruitment through social media. This may affect the generalizability of the study to the general population where access to healthcare varies widely. The inability to blind the participants in the study was another issue because women who were randomized to the treatment they desired, may be more adherent than those who did not receive their desired treatment. Also, although study participants were randomized, there may have been a selection bias of participants more receptive to app-based treatments. Those that were not technologically advanced or those who were weary of app-based treatments may not have signed up for the study. Some women may prefer a “hands-on” approach from their physicians and be less willing to adhere to an app-based treatment. These women would have poor outcomes with an app-based treatment. In this study, women were all inclined to try an app-based treatment so the positive outcomes may be artificially inflated.
The applicability of this study to populations outside of the Netherlands is questionable due to the demographic and healthcare system differences. The Netherlands is a European country with a population of 17.5 million people [2] with individuals of Dutch descent making up 75.8% of the population and other Europeans making up an additional 10.3% [2]. This is drastically different from the 331-million-person population of the United States of America (USA) that is much more ethnically diverse [3]. Variation in receptiveness to app-based care makes it difficult to translate this study to a patient population in the USA. Additionally, the Netherlands and the USA have substantially different healthcare systems which may impact physicians' willingness to incorporate app-based treatment into their care plans. Insurance coverage is an additional variable that is present in the USA, but less so in the study population. Differences in internet access presents another barrier to applying app-based UI treatment to patients in the USA, as a higher percentage of the Netherland population reports using the internet [4].
The difference in applicability of this study to rural and urban areas was also discussed. The development of app-based treatment options could greatly benefit both populations, however, it could also lead to unique challenges. In rural areas, patients may face barriers to healthcare such as physician shortages, limited access to specialists, and lack of transportation [5]. App-based treatment could be a valuable resource to this population. It would give them a treatment option that could be accessed from home, eliminating the need to travel long distances and would allow them to bypass long wait times to schedule an appointment with a provider. A common misconception is that people in rural areas may not be as technologically advanced, however, a 2021 survey found that 80% of people who live in rural areas use a smartphone, compared to 84% in suburbs and 89% in urban areas [6]. App-based treatment options could also benefit underserved urban areas, as they also face physician shortages. However, we felt that the most impact could be made in rural areas where some of these issues are more prevalent.
Overall, this study presents a comparison between physician-led usual care treatment and app-based treatment for urinary incontinence. As the world continues to become more technologically advanced, it is important that healthcare follows this trend. In more sensitive subject areas such as urinary incontinence, women may feel shame or embarrassment to seek treatment which could hinder their ability to receive care. An app-based approach would allow for a more discrete method to treat urinary incontinence in the privacy of her own home without needing to visit a physician. This study demonstrated that app-based treatment is a non-inferior option to usual care and is a viable option in treating urinary incontinence.
References
1. Loohuis AMM, Wessels NJ, Dekker JH, van Merode NAM, Slieker-Ten Hove MCP, Kollen BJ, Berger MY, van der Worp H, Blanker MH. App-Based Treatment in Primary Care for Urinary Incontinence: A Pragmatic, Randomized Controlled Trial. Ann Fam Med. 2021 Mar-Apr;19(2):102-109. doi: 10.1370/afm.2585. PMID: 33685871; PMCID: PMC7939722.
2. Statistic Netherlands. (n.d.). CBS Statline. https://opendata.cbs.nl/statline/#/CBS/en/dataset/37325eng/table?ts=1624...
3. U.S. Census Bureau. (2020). U.S. Department of Commerce. US Census 2020. https://www.census.gov/quickfacts/fact/table/US/POP010220.
4. International Telecommunication Union (ITU ) World Telecommunication/ICT Indicators Database. Individuals using the Internet (% of population). The World Bank. https://data.worldbank.org/indicator/IT.NET.USER.ZS?end=2019&most_recent... esc=tru e&start=1960&view=chart
5. Green-Hernandez, C. (2006). Transportation Challenges in Rural Healthcare. The Nurse Practitioner, 31(12), 10. https://doi.org/10.1097/01.npr.0000393077.02176.6b
6. Pew Research Center. (2021, April 7). Demographics of Mobile Device Ownership and Adoption in the United States. Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/fact-sheet/mobile/.