Our field workers are the backbone of what we do.
Outline India believes in ensuring data quality at every step of the research cycle, right from study design, through data collection, to dissemination.
Our focus is on data quality improvement, not just assurance. Standard data quality assurance protocols focus on the obvious gaps, incomplete information, the inconsistencies and the missing data points. However, our emphasis is on ensuring the reliability, accuracy, and relevance of data.
We ensure data quality by the following:
We qualitatively pre-test survey tools in a location with a similar socio-demographic profile to the study site. This checks for consistency, appropriateness of translation, relevance and context, as well as uncovering inconsistencies.
Through our learnings from the pre-test we prepare detailed training manuals for each study in consultation with the client, to ensure clarity and standardization in data collection.
Field workers are trained on background of the evaluation, question-by-question overview of the survey tool, cultural sensitivity and ethical research considerations, technical training, obtaining informed consent, data security and data transfer. Trainings include field mocks and debriefing sessions so that we can resolve any outstanding issues before data collection starts.
After training, our researchers stay on the field for the initial days to monitor each field worker, clarify doubts, address linguistic and comprehension inconsistencies and implement the sampling strategy. The Field Manager continues in the field for additional days to provide ongoing support.
We ensure the privacy of our respondents, taking extra precautions to keep their responses confidential. We regularly obtain ethical approvals for our projects.
We use digital data collection devices like Computer-Assisted Personal Interviewing (CAPI) platforms to conduct face-to-face interviews. Through CAPI we incorporate hints and instructions for field workers, record and visualise location of interviews, take pictures, switch between languages and monitor data in real-time.
Before each project, we put together project specific field teams who not only have cultural and linguistic familiarity but also have relevant domain experience. The finalization of the teams is based on their performance post-training by our researchers, based on standardized performance assessment protocols.
There is a ceiling limit to the number of interviews that a surveyor can conduct in a day, to ensure quality. The duration of each interview is recorded and included in the final data set.
Each survey form and data point goes through three levels of approvals and quality checks – Field Supervisor, Field Manager and Data Manager. We can troubleshoot inconsistencies and errors, and re-train/debrief individual field workers in real time. Additionally, we conduct telephonic and in-person back-checks.
For qualitative data collection, we re-visit recordings and field notes to ensure that transcriptions are accurate and context is provided to make sense of them.
After each study we put together a field report, detailing data collection context and progress, documenting field definitions and assumptions and providing recommendations.
We work at the confluence of theoretical research and the field with all its messy realities. Things often don’t go as planned.
This is our attempt to document the strange, sometimes funny and sometimes disturbing experiences we have had in the field and the hard-won lessons we have learned from them.
“How do you clean your hands?”
“With mud”, he answered.
“Could you show us?”
He walked over to the tap, diligently scrubbed his hands with water, applied soap and washed it off. No mud ever entered the process.
It was a study to understand hand hygiene practices, and we were using a survey tool, enumerators observations and spot checks to understand how people washed their hands. The rationale for using multiple methods was to check how people washed their hands, without trying to impress the enumerator or changing their behavior because they were being watched.
As this example shows, the different tools found different answers. Yet it was difficult to reconcile the findings during analysis as there was no accompanying qualitative data to explain why the respondent would say one thing and do another. Luckily, during the pre-test, our researchers had noticed this. We found that respondents, who had interacted with peer educators telling them to wash their hands with soap and water, thought they were being asked to show the ideal way to wash hands. Not how they normally do it.
“What's your age didi?”
“17”, she giggles, her grey hair glinting in the sunlight.
“Didi are you sure you are 17?” “Yes, Yes”
Concepts of time and space in some rural areas aren’t the same as Western ones. Yet almost every survey you come across asks the question - ‘what’s your age?’ Over the years, we have developed strategies to answer this question.
For young children, we check their government-issued MCP card. If they don’t have one we ask if they were born before or after the most recent local natural disasters and then make an educated guess. For adolescent girls, we ask how long ago they started menstruating, and use the average age of menstruation to calculate. For men, we ask family members and neighbours.
And for the didi we met in Bihar, we asked if she was alive when India became independent? Turns out she was.
Respondents don’t just stay at the field site – they move around over time. In rural areas, especially, members of the household often migrate to nearby cities or urban areas in search of work. But what happens when we are required to conduct a baseline, midline as well as an endline study in the same location with the same respondents? You may not find your respondents in their home all year round. And this is exactly what happened with us!
We were conducting an endline study in Rajasthan in November, but just couldn’t find the baseline respondents we had surveyed earlier. We knocked on their homes only to find from the family members that the original respondent had migrated either to Gujarat to harvest cotton or to Punjab to sow wheat.
The lesson we learnt: Look at migration patterns and cropping cycles before deciding on study phases!
A loo isn’t supposed to be pretty but this one was. A bright yellow building, newly painted, it gleamed in the sun. The teacher who was guiding us pointed it out proudly – “that’s the girls’ toilets” she said.
“Can we go in?” we asked. “It’s locked” she stammered. “Don’t you have the key?” we asked, wondering why would anyone lock a toilet. By this time the School Principal had joined us. We told him it was a beautiful building and could we look inside? Again he, didn’t seem keen, but he unlocked the building.
And inside was a bare floor, no latrine, no tap, not even a hole.
It was during an interview of a school principal, a well-respected man in the community. The respondent was all too happy to cooperate, answering our researcher’s questions in length. But in the middle of the interview, he paused and grabbed her hand, explaining that he holds the hands of disobedient children. But he didn’t let go.
She finished the interview, extracted her hand and left with her colleagues. But it shook us all up, an unnerving and unwelcome incident. For the remaining interviews, we asked a male field worker to accompany our female staff, and there were no more incidents. But as an organization we do vehemently defend and uphold our independence and work towards making the development sector gender neutral. This was a sad setback.
She had been following us for hours. Survey after survey after, a steady shadow that dogged our steps despite the midday heat at the height of the Delhi summer. “Didi, why are you here?” we finally asked. “Survey me as well” she answered.
She wasn’t one of our randomly selected respondents. The survey was long, almost two hours, and we normally had to beg respondents to take it, not fend them off. “Didi, why do you want to be surveyed?” we asked. Her answer was garbled with her passion but with some help from her neighbours we finally got the story.
A couple of years ago another set of researchers had visited and administered surveys. Like us they were randomly choosing respondents. But unlike us, it was for the baseline of Randomized Control Trial where the selected respondents were given monetary and technical help to construct houses. She hadn’t been selected, but her neighbours had. And she had watched over the years, as they built their fancy homes while she was forced to live in her shack. Determined not to be omitted from a survey again, she now makes sure that surveyors include her.
“Aapke ghar mein kitne purush rehte hain?”
“Kitne aadmi rehte hain?”
Did we make a mistake? Yes, we did - in Rajasthan, the word aadmi denotes “husbands” not men. For our respondent, the question translated to “How many husbands do you have?” No wonder she was offended.
We wanted to know the number of male members living in the households. Finally, after apologies, some subtle probing we got the number.
Lesson learnt: There are more linguistic variations than what we might be aware of. So be wary while translating!
The village was, as is often the case, remote – 3 to 5 kilometres from the nearest road. Coming in we were immediately met with stares, our guide, a local ASHA, told us that outsiders were rare. This too, was not unique – what was odd, however, was our reception. The villagers followed us around, tense, listening carefully to what we were saying in our unfamiliar accents. Our study – on the topic of sexual and reproductive health – was a sensitive one and we were to talk to young adolescents in groups by themselves. The village members were clearly not happy with this, and although the village’s ASHA and Mukhiya supported us, we were not welcome. We ended up having a small group discussion with the few adolescents whose parents were comfortable. We left quickly, the villagers following us to make sure that we were gone.
“Why were we met with so much hostility?” We asked the ASHA, the Mukhiya and the few friendly respondents. Soon the story came out – there were rumoured cases of outsiders luring children away from a neighbouring village, and harvesting their organs. Us strangers coming in, wanting to speak privately with children had unknowingly triggered the villagers’ fears.
For institutional review boards, the ethics are clear – you go to a village, you get informed consent, tell the respondent the risks and benefits, talk to the respondent privately so that they are not ostracised for their views and then you leave. We had followed these best practices and more, going ahead and talking to the ASHA and Mukhiya, explaining our study and gaining their support. But the backlash still happened. How do you get data from a place that doesn’t trust you?