the study, and made aware of their right to withdraw at any time without reason and without them being at any disadvantage. If it is not possible to inform participants of the full purpose of the study at the outset (e.g., because this might bias their behaviour and defeat the object of the study), then they should be debriefed fully at the end of the study.
It is common practice to provide a written information sheet outlining the purpose of the study, what is expected of participants, how their data will be stored, used and, if applicable, shared and how findings will be reported. Depending on the circumstances, it may be appropriate to gather either written or verbal consent; if written then the record should be kept securely, and separately from data. Preece et al. (2015) suggest that requiring participants to sign an informed consent form helps to keep the relationship between researcher and participants “clear and professional.” This is true in some situations, but not in others, where verbal consent may be less disruptive for participants. For example, verbal consent may work better if observing someone briefly while they go about their work, if getting written consent would disrupt the work disproportionately.
With the growing use of social media, and of research methods making use of such data (e.g., from Twitter or online forums), there are situations where gathering informed consent is impractical or maybe even impossible. In such situations, it is important to weigh up the value of the research and how to ensure that confidentiality and respect are maintained. Bear in mind that although such data has been made publicly available, the authors may not have considered all possible uses of the data and may feel a strong sense of ownership of it. If in doubt, discuss possible ethical concerns with experts in research ethics.
Privacy and confidentiality should be respected in data gathering, management and reporting. Some of this is covered in data protection laws and information governance procedures. It is good practice to anonymise data as soon as is practical, i.e., when taking notes or transcribing audio. This means replacing people’s names with a participant number (e.g., “P3”) or pseudonym, and removing other proper nouns that have the potential to personally identify participants (e.g., company names, specific places, such as the name of a small town, etc.). It may be necessary to retain contact details securely so that it is possible to inform participants of the outcome of the study later, but this would normally only be done with informed consent, for participants who want to know more.
Ethics goes beyond the principle of no harm: it should also be about doing good. There must be some value in the research, otherwise it is not worth doing. This might require a long-term perspective: understanding current design and user experiences to guide the design of future technologies. That long-term view may not give research participants immediate pay-back, but where possible there should be benefits to participating in a study. In our experience, participants have responded positively to us explaining that findings from their study will not be used to inform the design of the technology they actually use, but with the aim of making this sort of technology easier to use for people in the future.
It is important to review the safety of the researcher as well as that of participants. This commonly involves doing a risk analysis. For example, researchers should meet participants who are not already known to them in public spaces wherever possible. For home studies, it is generally good practice to work in pairs, or to consider other ways of mitigating any risks.
2.5 ACCOMMODATING RESEARCHER BIASES AND PREEXISTING THEORY WHEN PLANNING A STUDY
In addition to resources, constraints and ethical considerations, there are various less tangible factors that shape any study. Probably the most important are the ways that pre-existing theory can be used to inform data gathering, analysis and reporting of a study, and also the biases, understanding, and experience of the researcher(s) involved in the project (Denzin and Lincoln, 2011).
No researcher is a tabula rasa: each comes to a study with pre-existing understanding, experience, interests, etc. Hertzum and Jacobsen (2001) studied how several analysts independently identified usability difficulties from the same video data in which other participants had been thinking aloud while interacting with a user interface. There was significant variability in what issues their participating analysts identified. They considered this to be “chilling”: that there is no objective, shared understanding, even with an activity as superficially simple as identifying usability difficulties from think-aloud data. If this is true for analysing pre-determined data with a pre-defined question, it clearly has an even greater effect when the researcher is shaping the entire study.
For the individual, it may be difficult to identify or articulate many of the factors that shape the research they conduct, but one obvious factor is the role of theory in a study. Theory may shape the research from the outset, come into play during the analysis, or be most prominent towards the end of a research project. In Chapter 6, we discuss how theory may be introduced in an analysis, and how it can contribute to the generalisability of findings. Here, we focus on how it may be used to shape a study at the planning stage.
Theory may be introduced early into a study: either to test an existing theory in a new context or to better understand the study context while having a focus that helps to manage its complexity. A theory can act as a “lens,” providing sensitising concepts that help to shape and focus data gathering and impose a partial structure on the data that is gathered. Similarly, a theory can help in shaping analysis.
Where this is done, it is important not to trust an existing theoretical framework unquestioningly, but to test and extend that framework: are there counter-examples that challenge the accuracy of the existing framework? Are there examples that go beyond the framework and introduce important extensions to it? Many studies that introduce theory early end up extending or refining the theory and also making the study more manageable. For example, when studying the interactive behaviour of lawyers when looking for information on the Web (Makri et al., 2008a), we shaped our approach to data gathering and analysis around the work of Ellis et al. (1993) and Ellis and Haugan (1997). While this was not our intention at the beginning of the study, as our study evolved we noticed that many of the interactive behaviours the lawyers displayed were highly similar to those identified by Ellis and colleagues in other disciplines (and when using electronic library catalogues rather than the Web). Later data gathering and analysis focused on Ellis’s model. However, rather than assume that all of Ellis and colleagues’ findings applied in this new context, we questioned their total fit. This resulted in the existing theory being enriched by both extending and refining previous findings. A different example of contributing to theory arose from our attempts to apply DCog to analyse a control room. DCog is a theoretical perspective that views cognition as being distributed in the world, rather than residing solely in the mind, recognising the role of artefacts and information flow in supporting cognition. We found the theory lacked a suitable method to apply it, so we developed a method called DiCoT (Distributed Cognition for Teamwork) to fill this gap (Furniss and Blandford, 2006). Sometimes contributions to theory and method can be greater than the insights for the context under study.
Figure 2.5: A view of a control room with shared information artefacts that shaped the development of DiCoT (Furniss and Blandford, 2006).
2.6 SUMMARY AND CHECKLIST: PLANNING A STUDY
Just as the director of a documentary film is driven by their vision and has to plan what and where to film within their constraints before starting, you have to think about your study’s purpose and plan before you start to gather data. You might review relevant literature and do a pilot study early on to check your study design or to shape your approach. You might consult with a specialist user group to check your plans are feasible. You might need to review the focus of your study or approach as a result. But without a plan, a study is unlikely to be robust or deliver useful outcomes. There comes a point when you simply have to head off and
