Unlock the Power of Feedback Mechanisms in Mobile Data Collection
Many features of mobile data collection are well known, from automatic form submissions for faster data collection to validation conditions for more accurate data. However, there is one feature whose benefits often go overlooked: feedback mechanisms. Not only can they improve both worker performance and program outcomes, but feedback mechanisms also improve relationships between frontline workers and their beneficiaries.
However, understanding how to take advantage of these benefits can be tricky, especially when you are just starting out with your mobile data collection tool.
The ‘Mobile Acquired Data’ (MAD) Research Series
Between 2016 and 2017, Oikoi, the Australian-based development research organization, studied the value of adopting CommCare in international agricultural research. Their effort, supported by the Australian Centre for International Agricultural Research (ACIAR), assisted nine agricultural research projects in five countries in adopting CommCare as their field data collection solution. One of the most exciting things they found was that the most successful adopters were those who used CommCare to rapidly share valuable knowledge with their respondent communities.
Mangau Navian, a frontline worker in Vanuatu, provides personalized feedback to Brother Leonard, a local cattle farmer. Photo: Oikoi
Doesn’t research already do that?
Knowledge sharing might sound obvious, but in the rush, complexity, and unpredictability of completing fieldwork, most programs fail to allocate the necessary time and resources for proper knowledge sharing with their respondents.
This additional time is needed to:
- Assess the information gathered from communities during fieldwork
- Identify and prepare valuable information to be presented as feedback
- Provide this information during formal feedback sessions (e.g. via workshops)
Indeed, even when these steps are taken by program managers, most provide respondents with feedback during group workshops, rather than one-on-one. This means the information being shared is still generalized at the community level instead of being targeted to an individual or household where decisions are usually made.
How does mobile data collection change knowledge sharing?
To take advantage of knowledge sharing and feedback, see if your mobile data collection platform offers a combination of features that allow prompts or notifications for frontline workers and beneficiaries. In CommCare, for instance, you can use lookup tables, display conditions, and hidden value calculations to share knowledge in tandem with data collection. Essentially, the application will review collected data against an existing dataset (hidden calculations using lookup tables), and decide whether it needs to display a notification or message to the user (display conditions). This creates the opportunity for personalized knowledge sharing and feedback during the survey itself.
Feedback in Action: A Case Study From Vanuatu
During the MAD Research Series, Oikoi supported a team at the University of Queensland, surveying smallholder beef producers in Vanuatu.
The survey collected live cattle weights on beef farms as part of its study. During the app building process, project lead Dr. Simon Quigley realized they could use CommCare to turn these cattle weights (by assessing information gathered in the form) and the prices paid by local buyers for cattle (via a lookup table) to calculate the current market value of each animal (a hidden value calculation).
Workers surveyed each farm and every cow weighed received an estimated market value. The project purchased a mobile printer that was used to print out a Case Details list from CommCare, displaying the farmer’s cattle and their live weight and price.
Farmers reported that they were immediately using this real-time market value information to make farm decisions.
Both researchers and field staff commented that this activity improved the relationship with the study participants and the perceptions of the project in the community.
Field staff were particularly enthusiastic on this point, with 100% of them saying their relationships had changed for the better thanks to the use of CommCare. The success of the Vanuatu Beef project was that it was able to relate general market information to each farmer’s circumstances, providing them both relevant and actionable feedback. This overcame a barrier to the implementation of knowledge that had existed in traditional extension services using paper forms.
A Universal Experience
While the example from Vanuatu is specific, the effect of this type of knowledge sharing on relationships was widely reported throughout the MAD Research Series.
In an International Rice Research Institute project in Myanmar, similar rapid feedback systems using CommCare provided rice farmers with estimates of their seasonal profits while they were being surveyed. By the end of this research, seventy-five percent of enumerators working on this project agreed that CommCare changed their relationship with farmers.
In Pakistan, a University of Melbourne project studying dairy production went further, specifically testing the effect of using CommCare apps to deliver extension advice (either as digital factsheets or as interactive apps). They found interactive CommCare apps were the most highly rated method of information sharing among extension workers. All participating workers agreed that CommCare made the job of interacting with farmers and sharing information easier and that it helped farmers retain the information they shared. One participating extension worker pointed out that “in this tool, we use three senses [to] deliver the message: audio, visual, and touch.”
Frontline workers interviewing farmers in Jaguwala village during a survey for a smallholder dairy research project in Pakistan found interactive CommCare applications to be the most successful form of knowledge sharing. Photo: Oikoi
Let knowledge sharing inspire you
While it is true that these feedback mechanisms require additional app design and development time, mobile acquired data can significantly reduce the effort traditionally required to translate general knowledge into meaningful advice for individual circumstances. And crucially, it can allow us to share this knowledge at the individual level while we collect our data.
It is possible to add a feedback mechanism to an existing application, but we recommend building in these features from the start. Rapid feedback can help spark enthusiasm in your entire team, including supervisors, managers, colleagues and especially frontline workers. Ask yourself how your project might use the technology in a way that creates the greatest impact for communities. By doing so, you will not only change the impact of your project but the relationship it has with its respondents and their community.
The Vermont Care Network/Vermont Care Partners 'Wheels and Waves' Program - Treating Opioid Use Disorder with Video Directly Observed Therapy (VDOT)
Vermont Care Network/Vermont Care Partners collaborates with SureAdhere by Dimagi to expand the Waves and Wheels Program, a telemedicine intervention approach to treat opioid use disorders in the State of Vermont.
Dimagi Partner Blog
December 14, 2022
Researcher Spotlight: Nick Tarantino, PhD
Nick Tarantino, PhD, a psychologist and Assistant Professor at Brown University, discusses his research on HIV treatment-adherence in Ghana as well as his use of gamification through mobile phones, and the challenge of making mHealth interventions locally appropriate.
Dimagi Partner Blog
December 14, 2022
Digital Health Must Invest in Local Digital Ecosystems
Donors and aid programs deploying innovative solutions tend to displace local digital ecosystems. That needs to change as the rise of technology talent in Africa necessitates the importance of fostering local tech markets and the disruptive influence that international funding can have.
Dimagi Partner Blog
September 23, 2022