Things to consider Concept communication What message do you want to bring along Why would your target group be willing to achieve the desired outcome How would they benefit from applying the positively deviant practices Think of a narrative that will encourage communities to engage Incentive model When conducting a quantitative investigation you might face the problem of getting enough responses Think of ways to encourage respondents to fill out your survey without having a negative impact on the data quality For example consider getting approbation through community leaders Convincing people who are influential in the community to participate in the study can incentivize other community members to participate Gatekeeper Somewhat related to the previous point are there individuals or entities who could act as shortcuts to interviewees and respondents Ethical considerations The PD inquiry is based on a deep respect for the community its members and its culture and focuses on interactive engagement and the capacity to let the community lead Make sure you take that into account when you reach out to communities Who will collect the data and how Will the data expose stakeholders to potential harm How might you mitigate the risks For further guidance check Tool 3 2 in the tools section Resources What resources do you have financial time and personnel for reaching out to communities And for collecting and analyzing the data you will gather Reflect on how this might affect your choice of study design and research methods Data Collection In the second step of Stage 3 you will collect the data needed to identify factors that favor PD While the conventional PD approach focuses mainly on individual level factors the Data Powered Positive Deviance DPPD method enables you to take a more systemic lens that also considers structural level factors like infrastructure public policies or social dynamics This should help you gain a more comprehensive understanding of the complex forces at play behind positively deviant practices or solutions It is important to design your data collection instruments in such a way as to capture this mix of both individual and structural factors There are several methods you can use and the choice of participants to include in each method depends on your study design If you follow a mixed methods approach as recommended in the previous step you should include positive deviants in the initial qualitative data collection In the following quantitative data collection you should include the larger target group having both positive and non positive deviants If you follow either an entirely qualitative or an entirely quantitative approach you should include both positive and non positive deviants simultaneously Some of the qualitative and quantitative methods that can be used for the data collection are outlined below The main benefit of qualitative methods is that the information you gather is richer and therefore it generally provides deeper insights into the phenomenon you are investigating It might also help you understand the interaction between relevant factors Examples of common qualitative methods include Qualitative methods Individual interviews Interview your positive deviants to identify any uncommon attributes attitudes and or practices that might distinguish them from non positive deviants Focus group discussions Have a collective discussion with a group of positive and non positive deviants Observations Observe positive deviants practices closely to understand what they do and how they do it In the Ecuador pilot a convenience sampling was carried out that achieved diversity in the farms animal load pasture forest and ha poverty level index access to roads and proximity to the main city The team used a qualitative study design in which the key informants were farm owners or those in charge of the farm 83 84

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