Developing theory based behaviour change interventions using a systematic approach

The MRC framework and NICE guidance on the development of interventions draws upon evidence which suggests that interventions grounded in theory should be considered above others (Craig et al., 2013, National Institute for Health and Care Excellence, 2014b). There are a multitude of behaviour change theories and frameworks which currently exist which can prove daunting, particularly to those tasked with developing interventions that have very little or no psychological experience (Michie et al., 2011). French et al. (2012) developed a four step method which aims to facilitate intervention development and draws upon previous guidance (French et al., 2012). This process is represented in Figure 7.

35 Figure 7: Model development approach

Adapted from French et al (2012)

Utilising a systematic approach, such as that outlined by French et al (2012) allows for the identification of the target behaviour(s) that needs to change and helps expose both barriers and facilitators which may potentially initiate a change.

This process adds to the existing evidence base, allows us to select and tailor an intervention whilst strengthening the likelihood of its success (Craig et al., 2013).

Using a theoretical framework aids understanding of both barriers and facilitators surrounding a particular behaviour and directs how the particular mechanisms of an intervention might work.

The research in this thesis aimed to draw upon evidence surrounding the determinants of fruit and vegetable consumption in young children by exploring both barriers and facilitators to consumption (focusing on step one and two of this approach). The discussion chapter focuses on steps three and four, assessing intervention components and their likelihood of success in addressing the barriers and facilitators identified. Finally, consideration will be given to how intervention components might be best implemented, measured and operationalised in practice.

4. How will behaviour change be initiated and measured?

3. Which intervention components could overcome the barriers and enhance the faciliators?

2. Using a theoretical framework, which barriers and facilitators need to be addressed?

1. Who needs to do what differently?

36 1.10 Aim and objectives of this research

The stated aim and objectives for this thesis are outlined below:

Aim: To develop the evidence base to inform a theory based behavioural intervention to increase fruit and vegetable consumption in young children.

Objectives:

1. To systematically review evidence on the determinants of fruit and vegetable intake in young children.

2. To explore the barriers and facilitators to fruit and vegetable consumption in young children.

3. To consider caregiver views and perceptions of barriers and facilitators of fruit and vegetable provision.

4. To develop a conceptual model of evidence-based determinants of fruit and vegetable consumption in young children to inform theory-based intervention development.

Throughout the thesis participants will be referred to as either professional caregivers (i.e. teachers) or parents (including parents and any other carers).

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2. Chapter 2: Research design and methodological approach

A mixed methods approach was utilised for the purpose of this PhD thesis. This chapter will describe common philosophical approaches that are taken by researchers and provide examples of appropriateness of use, depending upon the type of research being conducted. My own philosophical stance will be stated, followed by a description of mixed methods research, possible designs, and advantages and disadvantages of use. Justification for using mixed methods for this research will be discussed, however the specific methods used for each phase will be described in detail within corresponding chapters. Particular problems such as data integration will be deliberated and a discussion of how such issues were overcome using model development will ensue. Finally, a visual representation of the design procedures employed throughout this PhD will be presented.

2.1 Philosophical considerations

Understanding the development of knowledge and the particular nature of such knowledge, provides grounding, and helps determine the direction that research may take. The way a researcher views the world and how they “see” the data will differ depending upon background and training. Such views, often referred to as paradigms help shape and explain why particular decisions are made with regard to research and these will help determine the subsequent approach, whether that be quantitative, qualitative or a mixture of both (mixed methods).

Cresswell and Poth (2017) describe such worldviews as the “general philosophical orientation about the world and the nature of research that a researcher brings to a study” (Creswell and Poth, 2017). There are a number of research philosophies that can be adopted, however three of the most common are; positivism, interpretivism and post-positivism. Each of these involves different assumptions about the world (ontology) and how we understand it. A researcher’s position of understanding (epistemological stance) is a key driver in informing research decisions.

38 2.1.1 Positivism

A pure positivist researcher holds a belief that complete understanding can only be reached through traditional scientific experimentation and observation.

Deductive reasoning, empirical evidence and hypothesis testing are key characteristics of this philosophical view. Such researchers see the world objectively and believe that our subjective experiences should be considered independently of the scientific evidence and that the researcher should remain emotionally detached and uninvolved (Johnson and Onwuegbuzie, 2004).

Quantitative researchers who predominantly deal with large numeric data sets and surveys are likely to take this view.

2.1.2 Interpretivism

Interpretivists believe that in order to understand human action in a variety of settings individuals need to be observed in their natural setting. They believe that people’s experiences and views are a reflection of their internal beliefs and are independent of any worldly, extraneous influences. They do not believe in objectivity due to the diversity of human experience and generate theory inductively through the identification of meaning (Denzin and Lincoln, 2017).

Qualitative researchers such as those undertaking ethnographic and detailed observational studies often hold these views.

2.1.3 Post-positivism

Forming a post-positivistic view, a researcher shares the main assumptions as associated with that of a positivist, one that is grounded in objectivity. However they also believe that the subjective experiences which an individual’s experience’s help shape knowledge and our understanding of a particular phenomenon and that comprehension cannot be fully achieved without both.

Post-positivism holds elements of cause and effect and embraces both logic and empiricism. Reductionism is key to this approach determined by a priori theories (Creswell and Poth, 2017). Researchers who utilise both quantitative and qualitative methods (mixed methods researchers) are generally of this view.

39 2.1.4 Philosophical stance

As a researcher, I hold a pragmatic post positivistic view of the world and believe that to successfully understand the complexities surrounding fruit and vegetable consumption in young children, both quantitative and qualitative strategies need to be employed to ensure that a ‘complete’ picture of evidence is captured. I believe that both quantitative and qualitative data is of value in different ways and both need to be addressed in order to achieve both the aims and objectives outlined in this thesis.

Identifying quantifiable associations between determinants and fruit and vegetable consumption is important to ascertain statistical trends and establish the current evidence base in order to verify which interventions are most beneficial. However, this does not provide an in-depth understanding of such determinants which qualitative inquiry can potentially achieve. For example, if we seek to further understand these determinants through first hand experiences (e.g. interviews), both barriers and/or facilitators to consumption can be explored.

Gaining a more meaningful and comprehensive understanding of these determinants, allows for a more directive and specific approach when designing and implementing interventions aimed at increasing fruit and vegetable consumption in young children, and increases their likelihood of success.

Therefore this thesis will follow a mixed methods design.

2.2 Mixed methods research

There are a plethora of research designs available to draw upon, depending upon appropriateness for answering the research question posed. However, mixed methods research has the advantage of utilising a number of techniques to investigate a complex research problem (Shorten and Smith, 2017). If carried out effectively mixed methods research has the potential to enhance the evidence base. The primary aim of using a mixed methods study design is to gain a comprehensive understanding of a research issue and involves the collecting, analysing and integration of both quantitative and qualitative research data (Creswell, 2005). In combining both methods it is hoped to achieve a thorough and robust depiction of a particular phenomenon of interest that cannot be fully achieved, should only one stand-alone method be used. In order to combine both quantitative and qualitative evidence within one study, the advantages and

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disadvantages of using both quantitative and qualitative research methods need to be understood. Table 2 outlines these and allows for comparisons to be made between quantitative and qualitative research enquiry. Provided both methods are combined effectively, taking the positive aspects of each into account it is more likely to give rise to a successful analysis (Tashakkori, 1998).

Table 2: Quantitative versus qualitative research Quantitative

Advantages Disadvantages

 Draws conclusions for large numbers of people

 Analyses data efficiently

 Investigates relationships within data

 Examines probable causes and effects

 Controls bias

 Appeals to peoples preference for numbers

 Is impersonal

 Does not record the words of participants

 Provides limited understanding of the context of participants

 Is largely researcher driven

Qualitative

Advantages Disadvantages

 Provides detailed perspectives of a few people

 Captures the voices of participants

 Allows participants’ experiences to be understood in context

 Is based on the views of participants, not the researcher

 Appeals to people’s enjoyment of stories

Source: (Creswell and Poth, 2017)

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2.2.1 Challenges in mixed methods research 2.2.1.1 Philosophical differences

Given that both quantitative and qualitative methods differ in many ways, difficulties arise when combining the results of both. It has been argued that the diverse philosophical grounding of each design does not allow for them to be merged (Sale et al., 2002). However there are others who argue that both approaches can be combined as they share the same common goal, which is to understand the world in which we live and that this can be best understood by the ‘union’ of a series of phenomena (Feilzer, 2009). Many researchers believe multiple paradigms form the basis of mixed methods research and that utilising a combination of these creates a fuller, more comprehensive understanding of the research problem (Greene and Caracelli, 2003).

2.2.1.2 Data presentation and integration

The integrative strategy taken when combining both qualitative and quantitative data is an important consideration for mixed methods researchers. Presentation and analysis of findings can be dealt with separately and combined in a final comparison stage, whereby the quantitative and qualitative elements remain entirely distinct in analysis yet are compared and discussed together to draw conclusions and make inferences regarding the data. Quantitizing and qualititizing are other common methods employed whereby one type of data is transformed to another to create variables that may relate to themes or constructs which can then be combined. For example quantitative transformation may involve the numeric coding of interview data and be expressed in terms of how many respondents agreed or disagreed with a statement (Tariq and Woodman, 2013).

2.2.1.3 Sequence and design of mixed methods research

The sequence in which the data are collected and presented can vary from study to study; however, this is also determined by the research question. There are a number of ways in which this can be achieved and Creswell outlines the three main basic designs which are said to form the basis of all mixed methods studies (Creswell and Poth, 2017):

1. The convergent design, which involves the simultaneous collection of both quantitative and qualitative data followed by the analysis and

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merging of results. Most commonly integration occurs during the interpretation phase when results are merged.

2. The explanatory sequential design, in which quantitative methods are used followed by qualitative to help explain and provide additional explanation of the results.

3. The exploratory sequential design in which qualitative data is explored first followed quantitative. The qualitative strand can sometimes be used to build upon theory or to identify variables that are tested in the quantitative follow-up.

The approach used in this thesis will be that of a sequential explanatory mixed methods design and will now be discussed further.

2.3 Sequential explanatory mixed methods

Creswell and colleagues have advocated the use of a post positivistic approach complementing a sequential mixed methods design (Creswell and Poth, 2017).

Sequential explanatory mixed methods are commonly used by researchers and typically involve an initial quantitative phase followed by a qualitative data collection and analysis phase. Data is generally mixed using a connecting method whereby analysis of one type of data leads to another (Creswell, 2011). Graphical representation of the study design process is advocated to better understand the methods used and steps taken in the data collection, analysis and interpretation stages of mixed methods research. The study design process example shown in Figure 8 illustrates how the data collected and analysed in the quantitative phase provides an initial body of evidence that can be explored further and elaborated on in the qualitative phase.

43 Figure 8: Study design process

Source:

Adapted from (Creswell and Poth, 2017)

Although seemingly basic there are a number of methodological considerations that need to be taken in to account when utilising this type of design. Such considerations include; deciding on weighting given to both quantitative and qualitative phases, sequencing of data collection and analysis and process and timing of the integration of phases. Clarification of these points leads to design transparency and ultimately a more robust study (Ivankova et al., 2006).

2.4 Data integration using a model development approach

Model development and framework analysis will be employed throughout, providing an interconnecting tool with which to integrate and explain the relationship between data from all phases.

As the aim of this thesis is to understand the determinants of fruit and vegetable consumption a model development approach will combine both the quantitative and qualitative data. It will be used as an interconnecting tool with which to integrate, illustrate and understand both the quantitative and qualitative data generated in this thesis. Initially an a-priori conceptual model (in this case a model of determinants of fruit and vegetable consumption) will be presented at the end of this chapter. This model will be built upon throughout the progression of the thesis, drawing upon evidence generated in each chapter with the presentation of new determinants being progressively added. On summarising each chapter the determinants (including any barriers and facilitators to fruit and vegetable provision) identified will be added to the model and presented until a final model of determinants is achieved. This model will be developed using a “best fit”

44 2.5 Framework synthesis approach

Framework analysis is a frequently used data interpretive analysis tool applied to primary qualitative research (Gale et al., 2013). Developed in 1980’s by social policy researchers, it is referred to a matrix-based approach which allows for the categorisation and coding of data into pre-specified themes. Advantages are that the data can be explored in greater depth, a level of rigour and transparency is maintained and interconnecting and development stages are explicitly described throughout the analysis process. In addition, this method is believed to be the most appropriate in providing an holistic, descriptive overview of a phenomena taking a variety of subject related data into account (Smith and Firth, 2011).

However there are limitations which must be considered such as the issue of subjectivity in the early stages and the inability to capture and synthesise highly heterogeneous data (Gale et al., 2013).

However by building on an initial framework approach a “best fit” framework provides a more systematic method resulting in the generation of a context specific conceptual model which aims to define and rationalise the decision making and health behaviours of patients and other groups (Carroll et al., 2013).

This is a frequently used data analysis tool applied to primary qualitative research and adopted by non-qualitative researchers who wish to further understand a problem from a variety of perspectives (Booth and Carroll, 2015).

2.5.1 The Theoretical Domains Framework (TDF)

As previously outlined in the introduction (Chapter 1) the TDF is an integrative theoretical framework that has been applied across a wide range of populations to help further understand the determinants of behaviour change (Francis et al., 2009, Heslehurst et al., 2014, McDonald et al., 2015, Nicholson et al., 2014a).

The framework was originally developed using a consensus approach by a group of health psychology theorists, health service researchers and health psychologists (Michie et al., 2005). The team of experts reviewed 33 existing psychological theories, comprising of 128 theoretical constructs which they then combined into one framework of 12 domains. These domains capture a collection of theoretical concepts that characterise barriers and facilitators of healthcare professional’s behaviours (Michie et al., 2005). The domains include: 1.

Knowledge, 2. Skills, 3. Social/professional role and identity, 4. Beliefs about

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capabilities, 5. Beliefs about consequences, 6. Motivation and goals, 7. Memory, attention and decision processes, 8. Environmental context and resources, 9.

Social influences, 10. Emotion, 11. Behavioural regulation, 12. Nature of the behaviours.

Further validation work in implementation science research and application of the TDF resulted in the development of a 14 domain version (Cane et al., 2012). Eight of the domains were similar to the original framework: ‘Knowledge’, ‘Skills’,

‘Social/Professional Role and Identity’, ‘Memory, Attention and Decision Processes’, ‘Environmental Context and Resources’, ‘Social Influences’,

‘Emotion’, and ‘Behavioural Regulation’. However the domains ‘Beliefs about Capabilities’, ‘Beliefs about Consequences’, and ‘Motivation and Goals’ were preserved but were divided into six new clusters. The domain of ‘Nature of the Behaviours’ was removed because it was not believed to be fully represented.

The aim of using the TDF to synthesise this evidence-base is to utilise a theoretically informed framework to systematically identify determinants (namely barriers and facilitators) to behaviours in order to inform future behaviour change interventions. However, use of the TDF has evolved over time and it is now used in a number of ways such as; to identify important influences of behaviour, identify relevant theories, to map theory to behaviour change techniques and to guide intervention development. Recently, a guide was developed to facilitate implementation of the TDF, providing a number examples which demonstrate a variety of ways in which the TDF can be used whilst considering practical applications (Atkins et al., 2017). I used the TDF throughout my PhD as an a-priori framework as an interconnecting tool with which to integrate and explain the relationship between data from all phases of this mixed methods PhD, to inform the model development.

2.6 Sequential approach for this research

This PhD will follow a sequential explanatory mixed methods approach (as described earlier in this chapter), whereby the results from one phase will inform the next. An a-priori conceptual model will be presented, and each phase contributed to refining the model during the model development process. The

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phases shown in Figure 9 are adapted from a study which adopted a similar process (Heslehurst et al., 2015). Phases will be carried out as follows:

Phase 1. A quantitative systematic review to assess the determinants of change in fruit and vegetable consumption in young children.

This review will assess both prospective cohort and intervention studies to quantitatively identify determinants of fruit and vegetable consumption in children.

Phase 2. A mixed methods systematic review to explore the barriers and facilitators of parents and professional caregiver’s fruit and vegetable provision to young children.

This review will include both qualitative and quantitative survey studies to further explore determinants identified in Phase 1, and identify additional barriers and facilitators to fruit and vegetable provision among parents and professional caregivers.

Phase 3. Qualitative semi-structured interviews to explore parental views and perceptions of barriers and facilitators to fruit and vegetable provision in young children.

Semi-structured interviews will be carried out with caregivers of young children to corroborate evidence identified in phases 1 and 2 and help further understand barriers and facilitators to fruit and vegetable consumption in young children.

In document Characterising the determinants of fruit and vegetable consumption in pre-school children (Page 55-200)