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Promoting contraceptive use among unmarried female migrants in one factory in Shanghai: a pilot workplace intervention

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Qian, X., H. Smith, et al. (2007). "Promoting contraceptive use among unmarried female migrants in one factory in Shanghai: a pilot workplace intervention." BMC Health Services Research 7(77): (31 May 2007)-(2031 May 2007).

Background: In urban China, more single women are becoming pregnant and resorting to induced abortion, despite the wide availability of temporary methods of contraception. We developed and piloted a workplace-based intervention to promote contraceptive use in unmarried female migrants working in privately owned factories.

Methods: Quasi-experimental design. In consultation with clients, we developed a workplace based intervention to promote contraception use in unmarried female migrants in a privately owned factory. We then implemented this in one factory, using a controlled before-and-after design. The intervention included lectures, bespoke information leaflets, and support to the factory doctors in providing a contraceptive service.

Results: 598 women participated: most were under 25, migrants to the city, with high school education. Twenty percent were lost when staff were made redundant, and implementation was logistically complicated. All women attended the initial lecture, and just over half the second lecture. Most reported reading the educational material provided (73%), but very few women reported using the free family planning services offered at the factory clinic (5%) or the Family Planning Institute (3%). At baseline, 90% (N=539) stated that contraceptives were required if having sex before marriage; of those reporting sex in the last three months, the majority reporting using contraceptives (78%, 62/79) but condom use was low (44%, 35/79). Qualitative data showed that the reading material seemed to be popular and young women expressed a need for more specific reproductive health information, particularly on HIV/AIDS. Women wanted services with some privacy and anonymity, and views on the factory service were mixed.

Conclusion: Implementing a complex intervention with a hard to reach population through a factory in China, using a quasi-experimental design, is not easy. Further research should focus on the specific needs and service preferences of this population and these should be considered in any policy reform so that contraceptive use may be encouraged among young urban migrant workers.

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A common challenge from policy makers, funders, community members, people directly experiencing development issues, and governments is: Demonstrate your Impact. Prove that what you are doing works. The high quality, highly credible data presented on the cards below is designed to help you answer that question for your social change, behaviour change, community engagement, communication and media for development, strategy formulation, policy engagement and funding initiatives. At this link filter the research data to your specific interests and priorities

Why a playing cards design?

There is a physical pack of cards with this data (to get a copy please request through the comment form for any card). The card approach allows for easy identification and selection of relevant direct impact data in any context. For example if talking with a donor and you need to identify proof of impact say "take a look at the 7 of Hearts". Quick access can be provided to high-quality data for many areas of your work – funding, planning, policy, advocacy, community dialogue, training, partner engagement, and more. A card deck is also engaging, easy to use and share, a conversation starter, and a resource - and they are fun and different. So we kept that design for the online images as it can serve similar purposes. 

What are the criteria for inclusion?

The impact data presented meets the following high standard for inclusion criteria:

  • Positive change or trend in a priority development issue;
  • Social change or behaviour change strategy or process;
  • Randomized Control Trial or Systematic Review methodology;
  • High quality peer review journal published;
  • Numeric impact data point
  • Published since 2010.