Title |
Improving the implementation of tailored expectant management in subfertile couples: protocol for a cluster randomized trial
|
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Published in |
Implementation Science, May 2013
|
DOI | 10.1186/1748-5908-8-53 |
Pubmed ID | |
Authors |
Noortje M van den Boogaard, Fleur AM Kersten, Mariëtte Goddijn, Patrick MM Bossuyt, Fulco van der Veen, Peter GA Hompes, Rosella PMG Hermens, Didi DM Braat, Ben Willem J Mol, Willianne LDM Nelen, for the Improvement Study Group |
Abstract |
Prognostic models in reproductive medicine can help to identify subfertile couples who would benefit from fertility treatment. Expectant management in couples with a good chance of natural conception, i.e., tailored expectant management (TEM), prevents unnecessary treatment and is therefore recommended in international fertility guidelines. However, current implementation is not optimal, leaving room for improvement. Based on barriers and facilitators for TEM that were recently identified among professionals and subfertile couples, we have developed a multifaceted implementation strategy. The goal of this study is to assess the effects of this implementation strategy on the guideline adherence on TEM. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Unknown | 85 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 15 | 17% |
Student > Ph. D. Student | 14 | 16% |
Researcher | 10 | 12% |
Librarian | 6 | 7% |
Student > Bachelor | 5 | 6% |
Other | 19 | 22% |
Unknown | 17 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 31 | 36% |
Business, Management and Accounting | 9 | 10% |
Psychology | 7 | 8% |
Social Sciences | 6 | 7% |
Nursing and Health Professions | 3 | 3% |
Other | 8 | 9% |
Unknown | 22 | 26% |