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Managing Qualitative Data Across Four Southern African Countries: A brief look into the daily research data management of The Family Caregiving Programme

How do you manage in-depth qualitative data across 25 researchers, sixteen research sites and four different countries in Southern Africa? When issues of data confidentiality, anonymity and security are coupled with everyday realities of access to mobile data, internet connections and unstable electricity supply? How do you ensure accessible, effective, and reliable methods of data management? That was the task we were given at the beginning of the year as we prepared for the research study, which is part of the family caregiving programme, a programme that is dedicated to understanding family care of older persons in Southern Africa.

The study explores caregivers and care receivers experiences of family care of older persons in South Africa, Botswana, Namibia and Malawi. Key to a project of this size and scope is research data management, which is happening in vastly different geographical locations, in different languages, and with different researchers who all have different research experiences. Keeping consistency across the research sites whilst allowing for local and contextual specificities was what guided us through this process.

Our data officer, Zeenat Samodien, briefly describes our data management practices in this blog, specifically highlighting the data collection process and the path it follows from the participant to the data officer. The diagram below illustrates several of the key steps involved in our daily data management which will be outlined in this blog.


Family Caregiving Programme Daily Data Management Illustration

As summarised in our Fieldwork Training Pack, our data collection methods are multiple and include a short assessment on activities of daily living, individual in-depth qualitative interviews, a family map (akin to a genogram), and a household budget. The researchers are working with 80 households in each country over two points in time. This means we are gathering a mix of images, text, and short survey responses from 1280 participants across four different countries and multiple research sites within each country. Have a look at our Fieldwork Training Pack to learn more about our data collection tools and the Interview Protocol.

So how does it work?


Collecting data:

Our data is collected by our researchers when visiting a household. Our researchers collect data via a mobile device that is dedicated to fieldwork. To ensure good practice, all researchers have the same device provided by the programme, and all devices are preloaded with the required tools to conduct fieldwork and are pre-loaded with mobile data. To simplify the process and avoid being in the field with multiple electronic devices, the mobile device has an audio recorder to record all interviews. The device has a camera which is used to capture images of the hardcopy consent forms, household monthly budgets and family maps. The required tools are easily accessed on the home screen of the mobile devices as shown below.













Uploading Data:

Once the data is collected the researchers then share all the data that they have collected with the data officer using the same device used to capture the data. The researcher uploads the audio recording of the interview, along with images of the consent form, family map and household budget via online forms, shown in the image below.

The forms used to upload the data contain a few questions aimed at summarising key information about the household visited. This allows us to keep track of the sample and prevents us from over-sampling specific households, something that is difficult to control when interviews are happening simultaneously across different sites within different countries. Once shared in the above way, the uploaded forms and their attachments are accessed by the data officer.

Data Review:

The data officer by accessing the cloud space reviews the data collected during the interviews. Thanks to the accessible format of the audio and images, no additional conversion is necessary, meaning she can provide instant feedback. Upon receiving the files, the data officer records the participant pseudonym along with metadata, such as when the interview took place, where it took place and who the interviewer was.

The data officer, upon initial review, will flag any issues regarding the quality of the data, such as blurry images or incomplete data, directly with the researcher to ensure appropriate action is taken in a timely manner. At this stage, she reviews the attachments to ensure that the correct files were uploaded. It is imperative to ensure that the files received are indeed the files belonging to the intended participant before saving the files to the relevant folders. This stage of data management helps avoid any potential errors, inaccuracies or other issues that could arise at a later stage. This review stage is essential for data quality and requires diligence and meticulous detail to ensure that data is reliable.

Storing Data:

Once confident that the correct files have been received and have undergone the necessary quality checks, the data officer then organizes the files according to country, site, household, and household member, following a naming convention for storing data files. This is a step that is crucial when working with large amounts of data. Following a standardized naming convention that is consistent across the team is important as it ensures that the data files are well organised which allows for easy retrieval when needed.

Reporting on the Sample:

Once the data has been safely stored, she then shares feedback on the participant sample and the data received thus far. The feedback is shared during weekly team meetings and serves to provide an overview of the households visited, where they are located and who the caregivers and care receivers are. This further prevents oversampling from occurring as the researchers, even though dedicated to certain sites, are provided with an overview of all participants in the programme and are therefore able to make decisions in the field on which households to include. This sample overview is made available on our website under the South African Country Profile, where weekly sample updates are shared, allowing you to keep up with our research as we progress!

Why is data management crucial for any research programme?

Following a data management plan, such as the one shared above ensures that the data collected is effectively managed, stored and preserved. This was especially important given the nature of The Family Caregiving of Older Persons in Southern Africa Research Programme. We were tasked with managing large data sets comprising of in-depth qualitative data across four different countries in Southern Africa.  By prioritising issues of data confidentiality, anonymity, and security in a context whereby we take seriously the everyday realities of varied access to mobile data and internet connections as well as unstable electricity – we carved out our own unique data management plan which allows us to ensure accessible, effective, and reliable methods of data management. Research data management is therefore integral to any research project and is embedded within the research protocol as well as the daily realities of the context in which research is being conducted.  This is a step that should not be overlooked when conducting research on any scale and has the potential to bring intriguing insights into the nature of your research programme as a whole!

This blog is in conversation with our Fieldwork Training Pack and written by Zeenat Samodien, the Family Caregiving Programme’s data officer. 



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