FAQs

Contextualizing Participatory methods at the data collection level

1. Broadly, there are three methods in participatory research at the data collection level;
   1. Multi-leaning ( several tools can be used as well: Multi-learning means using a combination of tools to learn from the source actively. In line with qualitative methods, this could be FGD, Community mapping, and Client-centered Learning (a non-directive way of collecting information from clients).
   2. Dialogue: In Qualitative-Health Focus Research: This is done usually through; Community forums, Narrative sessions- stories of events told in groups, Interactive workshops, etc. This may not be feasible and appropriate for the current pre-set study design.
   3. Domain Exercises: Usually done where participants reflect on community issues, and group them into domains. Within the identified, domains, participants are grouped into common groups to discuss specific domains, rank the issues, and prioritize them in order of importance. The research agenda is then focused on addressing the most pressing issues/needs. This will not be feasible in the current design.

1. The overriding principle in Participatory Research is the RIGHT to participation and active involvement. This takes on several forms. In this particular design, clients will participate, through the provision of information ( open-ended, in-depth discussions)
2. Below is an example of how multi-centered learning can be operationalized

For details: contact rbatamwita@src.ug

Contextualizing Rapid Ethnography Qualitative Research Methods

1. Broadly, Rapid Ethnography combines both observations and interviews of a case/unit of analysis
2. The uniqueness of the method is to observe how a particular event/process or actions happen and functions in the normal setting of a reference unit. In promoted behaviors, like the use of Insect Side-Treated nets. The researcher might be interested in the entire process in natural/traditional settings of how homesteads adopt the use of nets and if they use them.
3. In a program setting Rapid can be operationalized to a maximum of 3 days per case/unit pre-sampled: See the summary below

Table one is an example of How we can apply Rapid Ethnography to the KAP study at an MCH clinic that gives out Nets to Pregnant adolescents and in a home where the adolescent goes or resides after receiving the net

For details: contact rbatamwita@src.ug

Background: It is common practice to measure social and public health situations in pursuit of social determination of health outcomes. However, errors in calculation are common and evidence is sometimes reported inaccurately leading to erroneous decisions and priority setting.  For instance, a researcher would be interested in generating evidence on how people living with chronic diseases such as HIV are perceived and treated by others in the same community.  The perception could be either positive or negative. Usually, the negative perceptions, are of interest to the research and generally entice more focus.   The notion of various perceptions and experiences denote that several of these experiences must be explored, combined (added) but also averaged. For instance, 300 out of 1000 persons living with HIV who participated in the survey in Angola reported that during the last 12 months, they experienced at least one of the eleven listed items that exhibit Stigma and Discrimination (S&D):

• Exclusion from social gatherings
• Exclusion from religious gathers/activities
• Exclusion from family activities
• Discriminatory remarks/gossip from family members
• Discriminatory remarks from people outside the family
• Discriminatory remarks to sex partners/ and or children
• Verbal harassment/
• Blackmail
• Physical harassment
• Employment refusal
• The nature of job ever changed

In calculating this evidence, the researcher would directly indicate that   30% (300) experienced S&D. But this is erroneous because, of the 300, not all experienced the S&D from the 11 items, nor did all experience only 1 component. Therefore, the aspect of average which we shall call mean score becomes handy.  Assuming the average score is 2.71 generated from the primary data of the 300 cases, then this average must be subdivided by 11 items ( 2.71/11)  to get the mean score and then multiplied by 100%. To get the percentage score.  This means the right index of discrimination in Angola will be 25% instead of 30% which was erroneously calculated before.

Contact Richard Batamwita: at rbatamwita@src.ug  and Charles Namisi charlespcn@gmail.com for more technical briefs.