However, where data to be collected by fieldworkers are primarily quantitative in nature, here are my top 10 reasons (in no particular order) to use a good mobile data collection service (I’d like to include Mobile Researcher in that category but will let others decide that):

1. Capture once: With Mobile Researcher, you only capture the data once – in the field during survey conduction – it is then available for export as an Excel file (for example) once it has uploaded from the handset.
2. Validate in the field: Mobile Researcher allows you to design logic and validation rules which prevent many common erroneous entries (the clichéd “pregnant male”, accidentally skipped questions, etc) in the field. As there’s no separate data capture involved, there are also fewer points of failure.
3. Reduce latency: Data collected via Mobile Researcher is available for analysis as soon as it is uploaded – typically within a few minutes. This allows for faster analysis, near real-time data cleaning (automated or manual) and the opportunity to pick up anomalies while the study is in progress rather than weeks or months afterwards.
4. Conserve the environment: Obviously not using paper saves money and trees. We’ve had thousands of survey responses, each equivalent to 50 printed pages or more, captured using Mobile Researcher.
5. Reduce cost: In many cases, using Mobile Researcher is actually cheaper than paper (apart from the other benefits).  This is due to the removal of the exhausting print, distribute, collect and capture processes.
6. Increase flexibility: Surveys can be modified very easily – even with fieldworkers in the field. Survey design errors can be corrected, missed questions added, confusing questions rephrased, etc.  That’s very expensive and logistically taxing with paper.
7. Monitor activity: Using Mobile Researcher you can see what time surveys were started and completed. If the handset is GPS-enabled, we will also stamp the location of where the survey took place.
8. Improve data integrity: Once data has been captured using Mobile Researcher a full audit trail is maintained recording who modified data (if they even have permission to do so), when it was modified and what it was modified from and to.  Ensuring data is able to be cleaned without being incorrectly altered is more challenging on paper.
9. Preserve confidentiality: Once data has been captured on Mobile Researcher, it is securely transmitted to our servers.  Only authorised personnel you grant access to can view the data (there are other very granular permissions as well).  Our systems utilise the same level of encryption used by online banks.
10. Simplify survey conduction: Fieldworkers don’t need to understand branching or skip logic – this is built into the design of the survey.  Based on their response to each question, they are automatically directed to the next appropriate question.  This simplifies training substantially – particularly where prerequisites are complex.

I’ve covered some of the challenges involved in paper-based data collection in several previous posts but here I wanted to summarise the key factors I feel are important.

Perhaps there are other factors which are more important to you? Or are their areas where you disagree? Feel free to post your thoughts.

The article is available for download here but I’d like to highlight some key findings and comments:

Overall, our findings demonstrate that mobile phone based data collection is feasible at scale.

The software application and web-based interface enhanced real-time supervision of data collectors.

Real-time supervision of CHW performance was a significant advance over previous implementation work.

The automated graphs and real-time information allowed supervisors to focus their time on other aspects of quality control and solving logistical difficulties in the field.

Our experience with a large scale baseline survey suggests that the real-time quality control and data collector supervision enabled by the use of a mobile phone based survey system make this an attractive management option and preferable to a paper based approach.

One clarification I’d like to make on a point mentioned in the publication is that although the source code for the custom management system as described in the article may be released under an open source license agreement (at the election of the software sponsor), there is no intention (at present) for the core Mobile Researcher source code to be released under such an agreement.

On several occasions, I’ve had the experience where, after a survey has been sent for translation (and we were assured no further changes would be made), the inevitable “last” few modifications have followed soon thereafter.  Such changes could be as a result of mistakes made in the design of the original survey or based on feedback received from survey pilots.  In other cases, stakeholders who hadn’t been involved early on in the process suddenly want to add their feedback.

Short of sending surveys for complete re-translation every time a change is made, maintaining synchronisation between translations is difficult and frustrating – not to mention costly. This complexity increases exponentially with the number of additional languages.

Our approach

To overcome the logistical nightmares which often accompany multi-lingual surveys, we focused on three key areas.

Firstly, we built the survey designer to give users the freedom to design in any language and easily switch from one to another. The key point is that the structure remains intact, regardless of the language you’re working with. Logic, question order and constraints remain unaffected by the language. Only the text shown to the fieldworker changes.

Secondly, we decided to take a very practical view on the actual translation process. While it’s true that at some point in the future (watch this space) we may provide “fancier” and more collaborative mechanisms for translation, for now we settled on the concept of translation tables.

A translation table is simply an Excel export of the text used in the survey. There is a source language (e.g. English) and a destination language (e.g. isiZulu). The spreadsheet produced by the system, contains the source language for the translator as well as a cell for the translated equivalent. This file is sent to a translator who opens it and simply fills in the blanks. Upon returning the file to you, all that remains is to upload the file and the translated text will be imported and stored for the specified language.

Should a question change, the translation table is simply regenerated and sent to the translator. All their previous translations will be provided with highlighted cells indicating where their input is needed. Once their changes have been made, uploading the file overwrites the previous translation text.

The final step we took was to allow the generation of translations for any source and destination combination. Assume you have a survey which, for example, needs to be available in 3 languages: English, Afrikaans and German. You may have a translator who can speak English and Afrikaans and another who can speak Afrikaans and German. The translation functionality in Mobile Researcher allows you to export a translation table for English-to-Afrikaans and, once the Afrikaans translation has been performed, a table for Afrikaans-to-English.

Translation is an area we are planning to give a lot more attention to in the future. I think we have some really neat ideas which I’ll share with you in future posts. Hopefully as things stand currently, you’ll find the existing functionality a huge help.

In the first stage of the field research process, the metrics are usually determined – the question “What data must be collected?” is answered.  Once this has been decided on, the surveys (aka questionnaires or forms – depending on function) are designed.  The goals which survey designers should be cognisant of during this process are:

• Surveys are structured in an unambiguous manner which does not make their responses subject to fieldworker bias or (mis)interpretation.  Factors such as localised terminology, advanced logic and respondent fatigue come into play.
• The collected data is easy (or at the very least possible) to analyse.  Tables are a common favourite amongst designers who are used to deploying surveys on paper because they use very little space – but they can create tremendous challenges when trying to unravel them at a later stage.

In the majority of cases, the design process involves multiple stakeholders (such as principal investigators, consultants, ethics committees, etc) and the design tools used are often run-of-the-mill word processors (such as Microsoft Word or OpenOffice).  Countless versions (and I use the term version rather loosely here) are emailed from one stakeholder to the next with limited regard for change control. 

Without a dedicated survey design tool, asking questions in a consistent fashion and the way in which the logic is described to the fieldworker can vary significantly – even within the same survey.  That’s bad news for data integrity.

If a change has to be made to a survey (and that occurs rather frequently) such as the addition of a new question, or removal of an unwanted one, it often necessitates a thorough check of the entire survey to ensure that skip logic references and numbering still make sense.

Our approach

When developing the survey designer component of Mobile Researcher, we decided to keep the existing conceptual model of a designing a survey on paper.  Designers lay out their surveys section by section and can select from a variety of question types.  We felt that it was a better idea to pass the complexity of survey logic on to the designer rather than leave it to fieldworkers to follow instructions.

Instead of writing out instructions which fieldworkers need to interpret or follow, the survey workflow (logic) is built into the design of the survey itself. This logic is not actually shown to the fieldworker but is evaluated and executed by the mobile application on their phone.  The fieldworker is only ever presented with one question at a time.

Using a consistent approach to survey design improves efficiency and reduces the likelihood of errors being introduced by confused fieldworkers.  A caveat to the approach is that survey designers need to think clearly about how they’d like the survey to flow.  Although the designer is intended to be intuitive to use, there is no substitute for logical thought.

Somewhat obviously, the challenges differ somewhat depending on the nature of the data collection exercise but, in general, there is a great deal of commonality.  In a series of discussions on the challenges of paper-based field research, I’ll use the scenario whereby a fieldworker interviews a respondent to collect the necessary information (interviewer administered survey).

In a typical field research exercise, there are several key processes which occur in a reasonably sequential fashion.  An obvious observation is that each process has outputs or deliverables which feed into and impact on subsequent processes and thus the final outcome.

Some of the processes and activities which I will cover in separate posts include:

• Survey design
• Translation
• Deployment
• Conduction
• Collection
• Capture
• Cleaning and processing
• Analysis
• Archive
• Quality control
• Privacy and confidentiality
• Management of distributed resources

Each process can pose significant obstacles and expense when making use of paper-based techniques.  By replacing paper with a suitable technology alternative, we can go a long way to improving the efficiency and quality of field research and data collection.

Providing a platform for real-time data collection in rural clinics using standard mobile phones. Download the case study.

Organisation Profile

The Human Sciences Research Council (HSRC) of South Africa, a statutory body, supports development nationally, in the Southern African Development Community (SADC) and in Africa. It primarily conducts large-scale, policy-relevant, social-scientific projects for public-sector users, non-governmental organisations and international development agencies, in partnership with researchers globally, but specifically in Africa.

Project Scope

Project Masihambisane, a clinic-based effectiveness trial, attempts to address an important aspect of the evidence gap which exists on how best to improve the standard Prevention-of-mother-to-child-transmission (PMTCT) programme. A mentor mother support intervention, which supplements the standard PMTCT programme has been implemented in eight primary health care clinics in rural KwaZulu-Natal, South Africa, and will be assessed over 12 – 18 months. A sample of approximately 1,600 participants will be evaluated during this period as well as a number of indicators relating to uptake, attendance and participation.

The project entails the collection of data from participants by means of face-to-face interviews at several points during the assessment period with over a thousand data elements captured per participant in total. In addition to interviews, information from other clinic sources is captured as well as clinic and session attendance indicators.

Mobile Researcher Implementation

A team of eighteen female fieldworkers was assembled to collect data daily across the eight clinics using standard Nokia handsets loaded with the Mobile Researcher application. The team received basic training and between August and November 2008, captured over 110,000 data elements.

The intuitive method in which Mobile Researcher guides fieldworkers, question by question, through the conduction of a survey – using a device they are intimately familiar with – allowed complex questionnaires equivalent to 20 condensed printed pages to be captured.

Within hours of surveys being conducted, supervisors, project administrators and researchers had access to the captured data as well as reports on fieldworker activity via the web-based console which forms part of the standard Mobile Researcher service offering.

Using Mobile Researcher’s integrated support for multi-language scenarios, surveys could be designed and conducted in English or isiZulu with data seamlessly merged for reporting and export purposes. 

Lasting Impact

Mobile Researcher has become a self-service tool empowering Project Masihambisane staff to alter, deploy and even design entirely new surveys unassisted. The on-demand availability of collected information, coupled with tighter controls over data quality, provides a solid base from which the HSRC’s dedicated team can pursue the project’s objectives.

“Birth to Twenty” is the largest and longest running study of child and adolescent health and development in Africa. In 2009, it embraces the mobile era by connecting several thousand participants to the Mobile Researcher platform, facilitating real-time mobile data collection.

For seven weeks between March and June 1990, following Nelson Mandela’s release from prison, 3273 children were born in the metropolitan area of Johannesburg-Soweto and enrolled into a long-term birth cohort study that would follow them and their families for the next 20 years.

18 years into the study, colloquially nicknamed “Mandela’s Children”, the unprecedented adoption of mobile technologies by almost every segment of society, particularly the youth, presents the research team with an opportunity to connect with and collect data from the participants using entry level mobile phones and the Mobile Researcher platform.

A tiny mobile application installed on each participant’s phone will synchronise and download any surveys designed by the research team and guide participants, question by question, through submitting their responses. The ability for researchers to obtain information quickly, without the need to print, distribute, collect and capture responses manually is set to significantly enhance existing research capabilities and provide new opportunities for groundbreaking research.

By leveraging mobile phones, participants will be able to answer questions on a range of topics using an interface intimately familiar to them. Surveys containing complex logic can be designed from the system’s web-based console and deployed to specific individuals within minutes.

As the Birth to Twenty cohort moves from adolescence to adulthood, a new study called the “3G Study” has been launched in which female participants who are expecting babies and those who may already have children may enroll. This will provide further insight in a study which to date has had its findings presented at over 250 conferences and workshops worldwide, produced over 100 scientific papers and had a direct impact on government policy.

About Populi.net Mobile Researcher
Powered by the Populi.net platform, Mobile Researcher transforms the ubiquitous mobile phone into a cutting-edge research tool.

Leverage web and mobile technologies to design and deploy surveys to fieldworkers in minutes, monitor, manage and communicate with your team and analyse responses in real-time.

Developed by Digital Solutions company Clyral, Mobile Researcher presents a breakthrough in research technology. Learn more at mobileresearcher.com.

The MRC selected Mobile Researcher, a locally developed research platform, for a large-scale baseline study conducted in Umlazi, KZN. Equipped with standard cellphones, fieldworkers were able to capture and upload responses from within the mobile application, eliminating the need for paper and subsequent data capture.

The Medical Research Council of South Africa is one of the largest research organisations in the country. It has as its mandate to promote and conduct research for the improvement of health and quality of life of the public.

The intention of the study was to collect baseline data on a large number of households within the Umlazi area, located near Durban, South Africa. The study included questions pertaining to the structure of dwellings and access to basic services. Statistics on female inhabitants and infant mortality were also captured as part of the baseline study to provide reference points for future intervention projects. The surveys conducted were relatively brief with 60 data fields captured per household on average.

A team of approximately 25 fieldworkers was assembled to conduct interviews with Umlazi residents on an ongoing basis. Each fieldworker was issued with a low cost Nokia 2626 handset. The Mobile Researcher application was installed on each phone to allow surveys to be conducted and uploaded using low cost GPRS. SMS was not a viable technology for the study due to survey length, data complexity and intermittent reception. SMS was however used to assist in logistics with all fieldworker communication managed and logged via the Mobile Researcher system.

Key Successes

• Low cost Nokia 2626 handsets were successfully used by fieldworkers to conduct surveys.
• On average, over 400 households were surveyed daily with data available for analysis and reporting before the fieldworkers returned to the field the following day.
• Research staff and management were able to isolate and rectify issues whilst the study was in progress.
• Fieldworker activity could be monitored routinely via the web-based console for training, quality assurance and remuneration purposes.
• More than 25,000 households were surveyed in the first 3 months.
• In total over 85,000 surveys were conducted.

The resounding success of the project illustrates the potential of leveraging web and mobile technologies for the conduction of large-scale field research ? particularly in rural areas. Combining even entry-level mobile phones and the Mobile Researcher system enables high quality, affordable research to be conducted even where no cell phone reception is available.

About Populi.net Mobile Researcher
Powered by the Populi.net platform, Mobile Researcher transforms the ubiquitous mobile phone into a cutting-edge research tool.

Leverage web and mobile technologies to design and deploy surveys to fieldworkers in minutes, monitor, manage and communicate with your team and analyse responses in real-time.

Developed by Digital Solutions company Clyral, Mobile Researcher presents a breakthrough in research technology. Learn more at mobileresearcher.com.