Читать книгу Turning Ideas into Research - Barbara Fawcett - Страница 20

It is uncommon for researchers to work alone. In fact, the more usual situation is for research teams to be formed that draw together a range of expertise to support the achievement of project outcomes. Research teams share common features with other workplace teams and can be understood in similar ways. Teams are groups of individuals who come together to work with each other for a common purpose. Small-group theory and theories about reflective practice and interprofessional working have informed the extensive literature on teamwork – for example, Brookfield (1995), Fook and Gardner (2007), O’Hara (2011), Reid (1997), Schön (1987) and Weber and Pockett (2011b). Feminist perspectives have also informed understandings of gender differences and the ways in which women work in small-group situations, and this has particular resonance for teams in the workplace including research teams (Schiller, 1997).

In a qualitative study exploring shared perceptions of effective teams, Mickan and Rodger (2005) identified six conceptual categories that were consistently present. These were mutual respect, goals, leadership, communication, cohesion and purpose, all of which were supported by ‘active design and maintenance’ (p. 367) underpinned by critical reflection and appraisal of performance, planning and evaluation. These elements interacted across four domains: environment, structure, process and individual contribution. Team functioning has also been represented through modelling team structures. For example, Pritchard (1995), cited in Weber and Pockett (2011b), described teams as being ‘parallel’, ‘hierarchical’ or ‘collaborative’, depending on team behaviour and characteristics around key tasks and activities. In parallel teams, disciplines work in parallel with each other and decisions are made independently with only occasional interaction, although they may be part of the same workplace. Hierarchical teams have a top-down approach to decision-making, and co-operation may sometimes be affected by power imbalances and inequalities between team members. In collaborative teams work is undertaken by team members with equal status and power, and close communication and shared responsibilities for decision-making are evident. Within all of these team models, difficulties will arise if there is a mismatch of purpose and team style or differing perceptions of them amongst team members.

Research team members usually have different and complementary skills and expertise. These may incude theoretical expertise in the field of study; technical expertise in the development of research tools such as survey instruments and questionnaires; abilities to complete comprehensive literature reviews; interviewing skills; skills in data management, data analysis and data presentation; and administrative skills in negotiating and maintaining the infrastructure support required to keep projects moving forward to completion. As such they come together as a team of individuals who are no different from other teams in terms of how they need to function to successfully support their team purpose.

Processes need to be in place that enable team members to critically appraise and make decisions about roles and responsibilities. In the initial setting-up of a research team this may include agreements about intellectual property, recognition and acknowledgement of achievements, and publication and authorship conventions to be followed. Who will be first author, for example? What criteria will be used to determine first authorship: will it be alphabetical; by contribution to the content of the written work; or will all work be attributed to and led by the principal investigator? Roles for all team members need to be clearly articulated and agreed, including understandings of contributions and participation; regular and consistent communication processes need to be in place with clear documentation and reporting lines. Problem-solving processes need to be established, ideally based on a continuous open review and evaluation of all aspects of team functioning.

Teams can be interdisciplinary where members come together bringing different discipline perspectives, or unidisciplinary where members are from a single discipline. In interdisciplinary teams, some disciplines may be viewed as more powerful either by perception or assumed authority, and this is particularly the case when there is an already established hierarchy between those disciplines in the workplace. The health field is a good example of this where science-based professions are dominant. This may be further exacerbated on projects for which external grant funding has been obtained. Although this chapter does not address research funding specifically, it is true to say that competition for sources of research funding is universally fierce and the auspice of the funding body itself can also influence the way in which projects are developed. Funding bodies are ‘key players’ in the way projects are formulated (Alston and Bowles, 2012; D’Cruz and Jones, 2014). They are also a significant part of the research ‘environment’ referred to as a thematic domain by Mickan and Rodger (2005). The acquisition of research grant funding bestows significant status and prestige on research teams and, in particular, on the principal investigator. This can have a powerful influence on internal team dynamics, including authority and decision-making.

A further challenge in research teams is the dominance or privileging of research paradigms. In the health field, for example, the dominance of the physical sciences and scientifically orientated positivist world-views may pose difficulties for social scientists seeking to participate in blended or mixed method studies. The process of blending different research orientations together within fields where one has been traditionally more dominant presents a number of challenges. Appeasing dominant paradigms can sometimes lead to compromised methodology, as when quantitative approaches are applied to qualitative research design to meet more entrenched understandings of what ‘good quality’ research is. An example here may be the use of thematic coding software to analyse free text data that counts clusters of terms used by participants. Conclusions are then drawn from the statistical incidence of terms rather than the context in which they are used in an attempt to address a ‘perceived bias’ in qualitative thematic coding methods. Conversely, studies which are developed by teams drawing from qualitative research paradigms may make attempts to introduce quantitative elements to their study, particularly with regard to the findings where claims may be made that the findings have wider generalizability, when this in fact cannot be the case.