People diagnosed with pelvic organ prolapse (POP) face preference-sensitive treatment decisions. We conducted a systematic review, meta-analysis, and narrative synthesis to determine the effect of decision-making interventions for prolapse on patient-reported outcomes. To gain a more complete understanding of all potentially accessed resources, we also conducted an environmental scan to determine the quantity and quality of online interventions for prolapse decision-making.
Methods:
We searched Ovid MEDLINE, Cochrane Trials, and Scopus from inception to August 2022, trial registries, and reference lists of included articles. For the systematic review, we included studies that compared a decision-making intervention to usual care among patients with prolapse. We calculated mean difference (MD), 95% confidence intervals (CIs), and statistical heterogeneity (I2). For the environmental scan, we also searched Google, app stores, and clinical society websites. We assessed intervention quality using DISCERN, the International Patient Decision Aid Standards checklist, and readability metrics.
Results:
We identified eight publications in the systematic review, including 512 patients across three countries. The average patient age was 60. In the meta-analysis and narrative synthesis, there were no differences in decisional conflict (MD 0.09, 95% CI: −2.91, 3.09; I2 = 0%), decision regret (MD 0.00, 95% CI: −0.22, 0.22; I2 = 0%), satisfaction (MD −0.10, 95% CI: −0.23, 0.03; I2 = 0%), knowledge, or shared decision-making. Study quality was low to moderate. We included 32 interventions in the environmental scan analysis. Most (22/32) were not interactive. Overall quality was low with a mean DISCERN of 48.2/80, and the mean reading grade level was 10.0.
Conclusions:
Existing decision-making interventions for prolapse did not improve patient-reported outcomes, and interventions were not tested in younger populations. The quality of online interventions is generally low with poor readability. Future research should address these gaps through the user-centered design of digital interventions with younger patients.
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