1 / 11

Measuring HIV-related stigma: Why, How and What’s next Susan Timberlake Senior Human Rights and Law Adviser, UNAIDS

Measuring HIV-related stigma: Why, How and What’s next Susan Timberlake Senior Human Rights and Law Adviser, UNAIDS. HIV-related stigma and discrimination. Stigma Negative beliefs, feelings and attitudes Discrimination Unfair and unjust treatment (act or omission) Human rights violation.

rocio
Download Presentation

Measuring HIV-related stigma: Why, How and What’s next Susan Timberlake Senior Human Rights and Law Adviser, UNAIDS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Measuring HIV-related stigma: Why, How and What’s next Susan Timberlake Senior Human Rights and Law Adviser, UNAIDS

  2. HIV-related stigma and discrimination Stigma • Negative beliefs, feelings and attitudes Discrimination • Unfair and unjust treatment (act or omission) • Human rights violation

  3. Why do we care about HIV-related stigma and discrimination? • Harsh negative impact on quality of life of person • Seriously impedes the response to AIDS (uptake of HIV prevention, testing, adherence to treatment, disclosure of HIV-status, etc.) • Highly prevalent in communities, work places, education and health care settings • Those most at risk of HIV, such as men who have sex with men, sex workers, people who use drugs, experience the most severe forms

  4. Measure what is measurable, and make measurable what is not so Galileo Galilei

  5. Why measure stigma and discrimination • Government commitments to reduce stigma and human rights obligation not to discriminate • Cannot manage it unless you measure it • To track progress in programmatic efforts to reduce stigma and discrimination • Follow the money! – pressure to show results  funding directed to areas that can be measured

  6. For every complex problem, there is a simple solution that is wrong George Bernard Shaw

  7. How to measure stigma and discrimination • Complex reality: S&D indicators at outcome and impact level complicated – cannot be reduced to one measure • To understand S&D and design effective S&D reduction programmes: • Need to measure different aspects/forms of stigma and discrimination • Need to measure S&D among different populations

  8. Reality check! • Many scientific studies on S&D using different measures (i.e. cannot compare results) • Very few commonly used indicators in national M&E frameworks • Current outcome level indicators: • Accepting attitudes towards PLHIV (DHS) • PLHIV Stigma Index • Current output level indicators (collected through the National Composite Policy Index, Global AIDS Response Progress Reporting) • Non-discrimination laws • Laws that present obstacles • Mechanism to address discrimination • Programmes to reduce stigma and discrimination • Legal services • Training for judges

  9. Towards standardised measures on S&D • PLHIV: The PLHIV Stigma Index • General public: New draft indicators developed by expert group in 2010-11 in several domains: anticipated stigma, perceived stigma, fear of infection, prejudice and stereotypes, discrimination • Field tested in 2011 (results available soon!) • Health care settings: standardised questionnaire currently being field tested

  10. Knowledge is of no value unless you put it into practice Anton Chekhov

  11. Data for action! • Avoid data silos sitting on a shelf: combine data collected among different populations; by government and by affected communities • Build the capacity of community groups to collect and use good quality data • Package data for different audiences and use in evidence based advocacy to influence: • policy decisions • programming priorities • funding allocations

More Related