What is qualitative observation?

qualitative observation

 

Essentially, observation is a type of, or more likely, a part of ethnography. In ethnography, anthropologists (people who study people) turn their observations of people, cultures and organisations into written field notes (a bit like a research diary). While some of this may be reflexive (the participants own thoughts and feelings) most focuses on the activities and interactions of the people being studied.

 

There are broadly two types of observation. The first is participant observation in which the researcher becomes part of and gets involved in the context, area or group they are studying. The second is direct observation, where the researcher does not take part in the activity or setting, but is more of a fly on the wall – passively watching and recording what is happening.

 

There are advantages to both approaches: for example it’s easier to observe and take notes with direct observation, while during participant observation you may be actively taking part in the meeting / surfboarding session (Kawulich 2005). However, participant observation can allow for a deeper level of understanding, embedding and acceptance from the study group, allowing for more significant insights. Taking part in the culture/activity can also provide a ‘Walk two moons in their moccasins’ revelation, allowing the researcher to fully understand and empathise with the decisions and actions of participants.

 

Typically, a participant observer would offer to get involved by volunteering, doing some useful task like taking minutes or driving people around – essentially doing favours that let them help out while being able to see what is going on. It does not need to involve the actual task or skill being researched – for example in an ethnography of two tattoo parlours the author “helped maintain files of tattoo designs, working behind the front desk” although eventually got tattoos herself (Velliquette 1998).

 

One specific field of observational research is ‘Organisational Ethnography’, where researchers look at organisations, management or work places. (Ybema et al. 2009). Here ethnographers may look at a wide range of organisations from parliament (Crewe 2018) to a steel mill in Sheffield (Ahrens and Mollona 2007).

 

However there are also methodological limitations to observation. Even with direct observation, there can be an effect from having the researcher in the room – people’s behaviour may not be normal, and maybe modified if participants have a sense of being watched or judged (see the Hawthorne Effect). With time and acceptance of the research, the effect may become less, but it is still difficult to claim pure objectivity in observational research, especially when the researcher is talking part directly in the culture of the researched.

 


This is why reflexivity is so important in ethnography and participant observation, because the prejudices and interpretations of the researcher need to be untangled (or at least made explicit) from the data.

 

Observational data


Any method of observation has a myriad of practical and theoretical challenges. The first is to consider what kinds of data will be produced during the observation. Usually these will be field notes, but may also include documents (minutes from meetings, policy), audio, video, music and direct comments from people in the field of study. Many ethnographers use a dictaphone to record either the whole session live, or more likely their own thoughts and reflections afterwards. This creates audio data which probably will need to be at least partially transcribed.


Researchers need to have a loose plan before they start their fieldwork of what kinds of data will be collected and how, so that they can make sure the data can be effectively analysed. However, there will often be unexpected sources and type of data in a long and embedded fieldwork project like this, so prepare for some flexibility. Also, consider the volume of data that participant observation will generate (like most qualitative methods). For one study 40 hours of observation generated 28,000 words when transcribed (Conway 2017).


It’s also worth thinking about triangulation, and paring with other qualitative methods. For example, semi-structured interviews can be a good compliment to observation, as interviews allow you to ask questions one-on-one with people who have been part of the ethnography. These can be used to check assumptions, and ask for questions and clarifications on aspects of culture that are not obvious (e.g. Why do you all wear these hats?). Just remember that these direct questions are generating a different type of data to the observation: the participant during an interview is conscious of being questioned about their culture, and is giving an expressed opinion (These hats are stylish) which may not match the researchers interpretations based solely on observation (People wear hats to emulate the cool kids).


In fact, there is usually a little informal observation going on in most qualitative research projects. It’s hard just to meet a series of people for interviews without watching the culture around them and how they act with others (as Katz (2002) says – social researchers are always in ‘the field’). And often finding the right people to interview (if this is your designated research method) involves some participant observation to identify the most interesting respondents.

 

 

Gaining access, consent and trust


Yet for any type of observation, there will be significant issues around access and consent. The first hurdle is to persuade a group of people that it is a good idea to have a nosey researcher hanging out with them for months at a time. It can sometimes be tempting to claim that the research will be useful to them; in getting their situation better understood, or identifying issues and problems in their culture. However, this is a difficult thing to promise. While all good researchers should provide feedback and share findings with participants, the things that an academic researcher is investigating may not match with the immediate problems of participants. Qualitative observation of this type is usually based around fairly speculative exploration, with a sort of grounded theory approach, so there is little guarantee from the start exactly what the area of focus will be.


Usually, gaining access will be done through ‘gatekeepers’ (see more on gatekeepers in this article on recruitment  – https://www.quirkos.com/blog/post/designing-a-qualitative-recruitment-strategy). This may be a senior leader (mayor, tribal leader) in a cultural setting, or manager in an organisation. However, it is worth considering wider issues of consent with the many people a researcher will encounter. Although a senior manager may have given permission for the research, this does not automatically mean that their subordinates also give consent. There may be situations where this is explicit ‘Everyone must take part’ but individuals may not be freely giving consent if they are scared of going against the wishes of their boss.


Getting access for this type of in-depth observation can be a lengthy and fractional process, where researchers are only given access to certain areas at first, and as trust grows they are invited to more closed-off activities (such as weddings or management meetings). Building trust and rapport is an important skill that ethnographers must develop, and to which there are rarely shortcuts – long periods of time are usually required to negotiate access. Indeed, some researchers have come to see the difficulty of negotiating access as an important part of the ethnography itself (Frandsen 2015).

 

 

We are going to look more at ethnography in a future blog post, but what ever type of observation you are making, you might consider qualitative analysis software like Quirkos to help analyse and find themes in your qualitative text data. Download a free trial today, and see why people describe Quirkos as ‘intuitive’, ‘colourful’, and even ‘fun’!

 

 

Why qualitative research?

There are lies, damn lies, and statistics

It’s easy to knock statistics for being misleading, or even misused to support spurious findings. In fact, there seems to be a growing backlash at the automatic way that significance tests in scientific papers are assumed to be the basis for proving findings (an article neatly rebutted here in the aptly named post “Give p a chance!”). However, I think most of the time statistics are actually undervalued. They are extremely good at conveying succinct summaries about large numbers of things. Not that there isn’t room for more public literacy about statistics, a charge that can be levied at many academic researchers too.

But there is a clear limit to how far statistics can take us, especially when dealing with complex and messy social issues. These are often the result of intricately entangled factors, decided by fickle and seemingly irrational human beings. Statistics can give you an overview of what is happening, but they can’t tell you why. To really understand the behaviour and decisions of an individual, or a group of actors, we need to get an in-depth knowledge: one data point in a distribution isn’t going to be enough power.

Sometimes, to understand a public health issue like obesity, we need to know about everything from supermarket psychology that promotes unhealthy food, to how childhood depression can be linked with obesity. When done well, qualitative research allows us to look across societal and personal factors, integrating individuals stories into a social narrative that can explain important issues.

To do this, we can observe the behaviour of people in a supermarket, or interview people about their lives. But one of the key factors in some qualitative research, is that we don’t always know what we are looking for. If we explicitly go into a supermarket with the idea that watching shoppers will prove that supermarket two-for-one offers are causing obesity, we might miss other issues: the shelf placement of junk food, or the high cost of fresh vegetables. In the same way, if we interview someone with set questions about childhood depression, we might miss factors like time needed for food preparation, or cuts to welfare benefits.

This open ended, sometimes called ‘semi-structured’, or inductive analytical approach is one of the most difficult, but most powerful methods of qualitative research. Collecting data first, and then using grounded theory in the analytic phase to discover underlying themes from which can build hypotheses, sometimes seems like backward thinking. But when you don’t know what the right questions are, it’s difficult to find the right answers.

More on all this soon…