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Published on: January 12, 2018
Quantity over quality-Findings from a systematic review and environmental scan of patient decision aids on early
Kyla Z Donnelly1, Glyn Elwyn1, Rachel Thompson1
1The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, USA.
Background:
The availability and effectiveness of decision aids (DAs) on early abortion methods remain unknown, despite their potential for supporting women's decision making.
Objective:
To describe the availability, impact and quality of DAs on surgical and medical early abortion methods for women seeking induced abortion.
Search Strategy:
For the systematic review, we searched MEDLINE, Cochrane Library, CINAHL, EMBASE and PsycINFO. For the environmental scan, we searched Google and App Stores and consulted key informants.
Inclusion Criteria:
For the systematic review, we included studies evaluating an early abortion method DA (any format and language) vs a comparison group on women's decision making. DAs must have met the Stacey et al (2014). Cochrane review definition of DAs. For the environmental scan, we included English DAs developed for the US context.
Data Extraction And Synthesis:
We extracted study and DA characteristics, assessed study quality using the Effective Practice and Organization of Care risk of bias tool and assessed DA quality using International Patient Decision Aid Standards (IPDAS).
Results:
The systematic review identified one study, which found that the DA group had higher knowledge and felt more informed. The evaluated DA met few IPDAS criteria. In contrast, the environmental scan identified 49 DAs created by non-specialists. On average, these met 28% of IPDAS criteria for Content, 22% for Development and 0% for Effectiveness.
Conclusions:
Research evaluating DAs on early abortion methods is lacking, and although many tools are accessible, they demonstrate suboptimal quality. Efforts to revise existing or develop new DAs, support patients to identify high-quality DAs and facilitate non-specialist developers' adoption of best practices for DA development are needed.
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