In each country the research project will be different but consistent with the ethos of the People Living with HIV Stigma Index. The number of people interviewed will be different, as will be the outreach and composition of responses from different groups (such as men who have sex with men, sex workers, injecting drug users and other vulnerable groups). The methodology and research design in each country will build on a core commitment to the ethical process and rigor and sensitivity of each individual interview. 

Sampling and research design

In each of the country projects, the research team will include partners from local academic institutions and other experts who can advise on the research design and sampling strategy that is appropriate to the specific context.


Developing a sampling strategy for a research study can be a complex task. When the team is ready to consider this, it is recommended that they contact the Stigma Index Partnership (GNP+, UNAIDS or ICW) and seek their advice. In addition, advice could also be sought from a statistician within a local university or research institute.


There has been much debate about sampling for this index. Research studies such as these take a representative sample of the population of interest, with the aim of producing results that can be generalized for that population. This means that information collected from a sub-section of a population (the representative sample) can be used to reach conclusions that apply to the population as a whole. This process is called inference.

The problem in our case is that it is not possible to take a representative sample of the whole population of people living with HIV. That would require us to use an objective method of selection where all members of the study population have a definable chance of being part of the sample (what is termed a probability-based method of selection). However, it is very difficult to take a representative sample of people living with HIV given that we don't have a complete list of everyone living with the virus (i.e. the whole population of interest). We are therefore left with two options...


Finally, it is important to bear in mind the question of sample size. You need to take a sample that is large enough to capture the main features of the population as well as the divergence from the main features - or what is termed variability. But what is large enough? Or to put this more formally, What sample size is required to ensure that the study results can be relied upon to make generalizations?

This is a difficult question to answer because it depends on a number of factors, including how precise you want your findings to be and the variability of the study population with respect to the characteristics of interest. The sample size has nothing to do with the underlying size of the population of interest (a common myth). However, it does depend on whether you want to present results at the international (global) level only or use it to compare different countries, or areas within a particular country. It also depends on whether you want to show national-level results or breakdowns for specific areas or groups of people.

For example, one study in Tanzania sampled three key groups of interest to measure stigma related to HIV: general community members, health care providers, and people living with HIV. The study intended to gather 100 responses from people living with HIV "to fall within the minimum required size on which statistical tests could be meaningfully conducted and within the maximum that the study resources could support". In the end, to ensure gender balance in the sample size, they extended the survey to include 218 respondents since the majority of the first 100 respondents were women. In the Asia Pacific Network of People Living with HIV/AIDS study, there was a sample size of 764 (302 from India, 338 from Thailand, 82 from Philippines and 42 from Indonesia).  These examples highlight that sample size will vary depending on the context and focus of each country study.

Some important things to remember for each individual study using the People Living with HIV Stigma Index include:

  • What is the minimum size required to meaningfully run statistical tests?
  • What is the maximum size that the study resources can support?
  • If balance is important for the study (e.g. gender), do you have an equal number of responses (e.g. from men and women)?
  • Even if the study cannot be representative, do you have a sample that contains a mix of positive people of different ages, sexuality and economic, social and educational backgrounds?

Ultimately, you need to settle on the best and most feasible sampling strategy for your research. The People Living with HIV Stigma Index partnership will be able to inform you about what other countries' teams have done and provide you with the necessary advice for your country.

Quality control


Rigor, consistency and reliability are important concerns for the implementation of the people living with HIV stigma index as they are for any research process.


Each interview and in-country research process contains a referrals and follow-up section and a quality control procedures panel. These should be filled in by the interviewer after finishing the interview and, later, by other members of the survey team back in the office.


As soon as questionnaires come back to the office, they should be checked by the team leader. Each questionnaire includes a quality check section on the last page so that the country team leader can check that the interviewer is doing a good job, and to query any work that does not seem to be satisfactory.

Analyzing the data


There are many ways to analyze the data collected from the index. Through this final analytical process, the research team will be able to produce a report that documents the key results and findings from the People Living with HIV Stigma Index and make some recommendations for the future.


Before all this can happen, data capturers (two or more people) need to enter the raw data or original responses and narratives from each of the questionnaires into a computer-based programme, so that it can be analysed e.g EPI Info or SPSS.

When planning the actual data entry process, it is important to bear in mind the following steps in order to get the raw data collated:

  • Install the statistical programme on a computer

EPI-Info is a free software package that contains statistical facilities for developing a questionnaire; customizing the data entry process; entering the data and; analyzing the data. EPI-Info can be downloaded from the Centre for Disease Control and Prevention (CDC) website .

There are a number of versions available, but the latest version is EPI-Info™ Version 3.4.3. EPI-Info is designed for users who only have basic computer skills and gives step-by-step instructions to complete the basic tasks.If you are using EPI-Info for the first time, it is strongly advised that you download the user manual .

  • Download the database for the questionnaire in EPI-Info

A centralized database has been created in EPI-Info. Each country team will be using a similar database and the information once shared with the International Partnership will be stored centrally.

  • Enter the data

When planning the data entry process, consideration should be given to the amount of time needed to complete this task. From our experience, it takes approximately 20 minutes to enter the data from each questionnaire.

  • Analyze the data

This component allows you to access the data from your data tables to perform the analysis. In terms of analysis, EPI-Info will be able to produce lists, frequencies, cross tabulations and many other statistical tasks that will assist you to extract useful findings.

The analysis process can help you:

  • describe the experiences of the whole data set;
  • make comparisons between groups;  
  • verify data.

For example, Section 1 of the questionnaire describes the interviewees in terms of their age, gender, education, employment status and household income. When this information is compared to the responses in Sections 2 and 3 (which focus more on interviewees’ experiences of stigma and discrimination, and their experiences of HIV testing, disclosure and access to services), interesting associations or connections might emerge. These could be, for example, between the educational level and income of interviewees, the nature of a relationship they are in and their access to services. A programme like EPI-Info can assist in exploring associations like these and helps manage a big data set.

 It can also help the research team compare answers between different questions to help verify (or confirm) that the data provided by interviewees are consistent or reliable across themes in the questionnaire. As an example, in Section 1:

  • Question 9 (the interviewee’s employment status)
  • Question 12 (whether they live in an urban or rural area)
  • Question 13 (what the average income of the household is per month) and
  • Question 14 (whether the household ever runs out of money to buy food or not)

These can be looked at as a group of questions. When one puts all the responses of one interviewee together, we would expect to be able to build a picture of the life or lifestyle of that person. For example, someone who is in fulltime employment will (most likely) live in an urban area (as there is improved access to employment) and have a relatively comfortable household income. This person is likely to never run out of money for food. Another interviewee may be doing part-time or casual work and really struggle to consistently provide an income for their household and as such be more vulnerable to not having enough money to pay for basic resources like food.

It is important to share the information with the international partnership at this stage.