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Conducting thematic analysis on brief texts: The structured tabular approach

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Abstract

In this article I present a structured approach to thematic analysis that is designed for working with brief texts. It is grounded in both the ecumenical thematic analysis of Boyatzis and the reflexive thematic analysis of Braun and Clarke. The process of structured tabular thematic analysis (ST-TA) is best conducted in spreadsheet software such as Microsoft Excel. As with other forms of thematic analysis, it permits inductive, deductive or hybrid approaches to theme development and analysis. Its logistical processes are well suited to working with the large samples that can be achieved when gathering brief text data. It can be used to conduct purely qualitative analyses, and can also elicit frequency data that can, in principle, be analysed quantitatively too. The process of checking agreement between analysts is an integral feature of the method. I discuss the practical implications of the approach and its applicability to various qualitative and mixed-methods research designs.
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Conducting thematic analysis on brief texts: The structured tabular approach
Dr Oliver C. Robinson
University of Greenwich
Dreadnought Building, London, SE10 9LS
Email: o.c.robinson@gre.ac.uk
Tel: +44 208 331 9630
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Abstract
In this article I present a structured approach to thematic analysis that is designed for working
with brief texts. It is grounded in both the ecumenical thematic analysis of Boyatzis and the
reflexive thematic analysis of Braun and Clarke. The process of structured tabular TA (ST-
TA) is best conducted in spreadsheet software such as Microsoft Excel. As with other forms
of thematic analysis, it permits inductive, deductive or hybrid approaches to theme
development and analysis. Its logistical processes are well suited to working with the large
samples that can be achieved when gathering brief text data. It can be used to conduct purely
qualitative analyses, and can also elicit frequency data that can, in principle, be analysed
quantitatively too. The process of checking agreement between analysts is an integral feature
of the method. I discuss the practical implications of the approach and its applicability to
various qualitative and mixed-methods research designs.
Keywords: thematic analysis; brief texts, short stories, flexibility, qualitative psychology,
mixed methods
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Conducting thematic analysis on brief texts: The structured tabular approach
The development of qualitative research methodologies in psychology and the social sciences
has from the outset been bound up with an emphasis on gathering in-depth data. This
emphasis has presented an important counteractive to the reductionist tendencies of
quantitative psychology. Qualitative research initially emerged in psychology in conjunction
with analysing individual cases or critical incidents in depth. Examples of early work include
Erik Erikson’s biographical case studies of Ghandhi and Luther (1958; 1969); Festinger’s
quasi-ethnographic case study of a UFO cult (Festinger, Rieken, & Schacter, 1956); and
Flanagan’s work developing the Critical Incident Technique and his applications of it on
learning to fly (Flanagan, 1954). From the 1980s, as qualitative methodology became
explicitly recognized within psychology and the social sciences, early sourcebooks on
qualitative methods all focused on in-depth data collection from each case (Glaser & Strauss,
1967; Lincoln and Guba, 1985; Miles & Huberman, 1984; Reason & Rowan, 1981).
Interviews and focus groups subsequently became the most widely used data collection
methods in qualitative psychology (Howitt, 2016).
This focus on long texts (i.e. thousands of words per person or per conversational
interaction) has remained integral to qualitative methods in the intervening decades.
Analytical approaches such as Grounded Theory, the Comparative Method, Conversation
Analysis and Interpretative Phenomenological Analysis were all developed with the aim of
analysing these in-depth texts. Until recently, little has been provided by way of
methodological injunctions for how to work analytically with brief texts, and what the
theoretical and practical arguments are for doing so. To meet this need within a flexible
epistemological framework, in this article I set out a variant of thematic analysis entitled
structured tabular thematic analysis (ST-TA), which offers an adaptable technique for
working with brief qualitative data in a relatively structured way.
My own epistemological is informed by the middle-ground approach of critical
realism, which allows for multiple interpretations of a phenomenon but clearly distinguishes
between better and worse interpretations by the relationship of those ideas to a reality beyond
words and texts (Robinson & Smith, 2010). It is also is founded on the importance of
dialectical reasoning. This means that when I investigate any topic that has debate and
disagreement within it, I actively explore whether a hidden consensus, synthesis or unity can
be found behind the plurality of viewpoints (e.g. Robinson, 2020a). This dialectical reasoning
process involves critically examining and deconstructing apparently opposing presentations
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of complex matters to seek hidden but often unarticulated common assumptions. Finding a
synthesis or unity in this way does not over-ride plurality and difference; these often happily
co-exist, like multiple notes in a single piano chord. In the context of methodology, I contend
that taking a dialectical approach to word-based and number-based methods shows that both
emerge from a complex range of overlapping epistemologies, all of which are founded on the
central importance of resorting to evidence when asserting facts or generalities. This means
that the incompatibility thesis, which argues that (a) positivism undergirds quantitative
research, (b) interpretivism is the foundation of qualitative research, and (c) these are
incompatible (e.g. Wiggins, 2011), is wrong. I elaborate on this point below, but before that I
consider why brief texts matter to psychology and the social sciences.
The forms and functions of brief texts in qualitative psychology
There are various theoretical and practical arguments for acknowledging the
important role that brief texts (i.e. typically one paragraph or less) currently serve in the
social sciences and why they are likely to become even more important to research in the
future. The first argument is the sheer growth in their prevalence since the rise of social
media. Qualitative studies have already been conducted on social media texts in the form of
YouTube comments (Carpentier, 2014; Mejova & Srinivasan, 2012; Schultes, Dorner &
Lehner, 2013); Facebook posts (Vraga et al. 2015); Twitter feeds (Giles, 2017; Lyles et al.,
2013); and forum-based online discussions (Giles, 2016; Giles, 2014). The accounts of life
events and experiences that are conveyed in social media are referred to by some theorists as
small stories (Georgakopoulou, 2014). They have some advantages over depth data that is
elicited in autobiographical interviews. For example, compared with the generally
retrospective nature of interviews, social media postings typically represent events and
experiences that have happened that very day or may be ongoing, hence they are less heavily
filtered by memory. Furthermore, the socially interactive nature of social media postings,
being composed as initial texts with subsequent comments and replies, can convey how
experiences can be framed and interpreted within an intersubjective frame (Georgakopoulou,
2017).
As well as social media, another important phenomenon that has boosted the
availability of short forms of qualitative data is the online survey platform, such as Qualtrics,
Typeform or QuestionPro. Through these, participants can write brief stories, reflections or
respond to open-ended questions. Such data is important for qualitative psychology for at
least the following reasons. Firstly, it allows access to hard-to-reach sample groups or
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geographically dispersed populations that standard depth methods struggle to reach (Terry &
Braun, 2017). Secondly, such data collection allows for total anonymity, which can be an
ethical strength when asking individuals to disclose information about highly personal or
sensitive topics (Slepian & Moulton-Tetlock, 2018). Thirdly, using online platforms allows
for gathering a larger, and hence potentially more representative, sample than in-depth
methods. This can be an advantage if the aim of a qualitative study is to make inductive
claims about a broader population group from which the sample is drawn. Such an aim is, for
example, often the case in qualitative evaluation studies that make claims about intervention
efficacy (Thomas, 2006).
For an extensive exposition of the functions and potentials of qualitative surveys, the
reader is directed to Terry and Braun (2017). These authors present a theoretical and practical
guide to this form of data collection, exemplifying their approach with a qualitative survey
study on views about body hair removal, which was conducted via this method with a sample
of over 600 participants from New Zealand. Another technique for eliciting data that can be
captured via online survey platforms is the story completion method. In this method, the first
sentence of a story is provided about a specific topic. This must then be completed by
participants, typically of a few hundred words in length (Clarke et al., 2018). This method has
recently been used with data collected online to explore parents’ perceptions of the future for
a child with a chronic pain syndrome termed Complex Regional Pain Syndrome (Coningsby
& Jordan, 2019).
Along with the pragmatic opportunities and benefits of working with brief data, there
is a pluralist epistemological argument for working with brief data alongside depth data.
According to this argument, the more varied forms of qualitative data that can be
meaningfully analysed, the more effectively we can grasp the complexities of human
behavior, inner life and interpersonal interaction that can be conveyed through words and text
(Frost et al., 2010). Put another way, much qualitative data is available in small texts, so to
include them fully within the auspices of qualitative methods is to ensure that psychology and
the social sciences reach out to all possible forms of textual data and the potential insights
they contain.
Structured tabular thematic analysis: A conceptual analytic comparison with existing
methods
ST-TA locates itself in a currently unoccupied niche between (a) existing approaches
to thematic analysis, most specifically those of Boyatzis (1998) and Braun & Clarke (2006),
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and (b) existing approaches to analysing brief texts, such as the narrative analysis of small
stories (Bamberg and Georgakopoulou, 2017). In order to justify that such a niche exists and
is worth occupying, I here present a conceptual comparison with these other methods,
focusing on key differences and similarities with these established approaches. Central to this
discussion is my contention that doing qualitative research does not entail negating the
language of number as a key tool for science. Numbers are symbols and signs that assume
meaning via complex cultural and cognitive networks of sense-making, just as words do
(Osbeck, 2014). The language of number that we use today has evolved over millennia from
a combination of Arab, Hindu and Roman systems, and, as such, has a cultural linguistic
heritage just as written language does (Seife, 2000). Numbers in the context of scientific data
never interpret or explain themselves. Turning numerical data into scientific understanding
entails complex abductive conceptual leaps and inferences that are typically located in the
discussion section of a journal article. I argue that to support qualitative research with the
judicious use of numbers, particularly in calculations of researcher agreement and theme
frequencies, gives additional clarity, precision and meaning to an analysis. On the flipside,
using words to illuminate quantitative data is equally essential.
The development of ST-TA has been influenced by two established approaches to
thematic analysis: the ecumenical approach set out by Boyatzis (1998) and also the reflexive
approach devised by Braun and Clarke (Braun & Clarke, 2006; Braun, Clarke, Hayfield &
Terry, 2018). Both approaches embrace a pragmatic ethos in which the research problem is
paramount. They both also concur that the objective of thematic analysis is seeking recurrent
patterns across multiple cases that point to some kind of meaningful invariance that can help
understand a class of phenomena or events. In both methods, inductive and deductive
research can be legitimately conducted. The approaches both allow for themes to be extracted
at a descriptive/manifest level or latent/inferential level, via a defined yet flexible series of
analytical phases. ST-TA stands on these foundations, which together can be summarised as a
problem-focused commitment to the flexible seeking of patterns and meaning in data that
serve clearly defined research problems, according to clear and explicit parameters of
transparent and rigorous research.
As well as these similarities, ST-TA also has points of difference with both
approaches. Braun and Clarke (2019) have recently argued that formal processes for
establishing agreement across analysts dilute or pollute qualitative research by drawing in the
positivist agenda of quantitative research that ultimately denies the contextualised
subjectivity of the researcher conducting thematic analysis. In contrast ST-TA adopts the
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importance of using processes for establishing agreement, including using a simple
quantitative benchmark for determining adequate agreement.
This process of agreement checking has often been referred to previously as checking
inter-rater reliability (Boyatzis, 1998), but this term is problematic for several reasons: firstly,
thematic analysts do not rate data, and secondly reliability is a term that comes laden with
meanings from psychometrics and classical test theory. To call the process of seeking
agreement in a qualitative analysis as a reliability process conflates it with the very different
process of ensuring that psychometric questionnaires and tests give the same response over
time and across item sets. The term that I use instead for ST-TA is inter-analyst agreement.
Boyatzis’ method does incorporate a similar process. He is of the view, as am I, that
undertaking a process of reaching a high level of coding agreement between two or more
researchers means that the eventual description and labelling of themes is more likely to be
based on a consensual and transparent understanding of the subject matter (Hill et al., 1997).
Braun and Clarke (2019) have incorrectly labelled Boyatzis’ injunction to calculate an
agreement metric as quasi-positivist, but this is based on the assumption that quantification is
itself positivist. I discuss below why that assumption is faulty. Boyatzis does not actually
construe the process of reaching agreement as a means of determining objective fact, but
rather as one of bringing about a working consensus that is essential when (a) conducting
research as a team, and/or (b) when research is to be replicated or extended in new directions
by different researchers in the future. Using a constructionist or interpretivist framework,
which is common in thematic analysis, does not mean giving up on reaching agreement with
others, but instead involves interpreting agreement across analysts as the reaching of inter-
subjective consensus within an agreed interpretive or discursive framework, rather than
discovery of an objective ‘fact’. Analysis does not end when agreement is reached, for new
questions may arise in the process of reaching a consensus that lead to new avenues of
enquiry (Ballesteros & Mata-Benito, 2018).
Another area where ST-TA entails an overlap between qualitative and quantitative
processes is in the calculation of theme frequencies. Theme frequencies refer to the number
or proportion of participants who have text allocated to a particular theme. Brief texts allow
for larger samples than depth approaches, and larger samples provide for more meaningful
statements of a theme’s potential prevalence within a target population than smaller samples
do. Neither Boyatzis nor Braun and Clarke provide protocols for calculating such
frequencies, hence the process within ST-TA is a clear point of difference with existing TA
methods. Frequencies in qualitative reports convey some information on the salience and
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importance of a theme to the study’s message, but do not by themselves convey the centrality
or salience of themes. The relationship between aims, research questions and themes is also
key in discerning theme salience during an analysis (Braun & Clarke, 2016). With that caveat
in mind, theme frequencies do provide important information. If they are misrepresented or
not included, it can lead to major issues of interpretation for the reader. For example, in
qualitative research that evaluates the experience of an intervention across multiple
participants, the proportion of participants who refer to the intervention as leading to positive
rather than negative experiences is essential information for the reader. Another example is in
the growing domain of qualitative research into the experience of psychedelic drugs. It is
important for the transparency of such studies to convey what proportion of participants
reported enlightening or distressing subjective experiences (Davis et al., 2020). Frequencies
provide that information to the reader, and it is up to the reader or future researcher how to
use that information in conjunction with other information provided.
ST-TA is well suited to mixed-methods research. For example, it can be used to
analyse open-ended questions within a survey that can, in turn, be linked to quantitative data
gained within the same survey. A common criticism of mixed-methods research is that
qualitative and quantitative methods are philosophically incompatible, given that the former
is interpretivist and the latter is positivist, and that these paradigms have discrepant
epistemological assumptions (Wiggins, 2011). I present an argument against this contention,
based principally on the point that quantitative research is based on a plural combination of
epistemologies, of which positivism is at best a minority player, in Appendix A.
As well as overlapping with existing forms of thematic analysis, ST-TA finds itself in
methodological proximity to other methods devised to work with certain kinds of brief texts.
As another established method for working with brief data, Bamberg and
Georgakopoulou (2008) have devised a form of narrative analysis for working with short
stories. Short stories are brief written accounts of events or happenings in a person’s life.
These have become the standard currency of many social media platforms that are based on
brief autobiographical reflections and comments from others (Georgakopoulou, 2017). The
form of analysis that Bamberg and Georgakopoulou have devised to analyse short stories
focuses specifically on identity construction in short stories and takes the form of five steps:
1. Who are the characters and how are they relationally positioned?
2. The interactive accomplishment of ‘narrating’
3. How is the speaker positioned within the interactive flow of turns that constitute
the situation as ‘research’
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4. How are relationships between all characters managed?
5. How is the self portrayed in this brief story telling?
Bamberg and Georgakopoulou’s approach to short story narrative analysis is an
exemplar of taking an existing broad approach to analysis and then making it bespoke to the
challenges of working with brief texts. Its approach is anchored specifically in the tradition of
narrative analysis developed by Labov (1997), and also a model of identity positioning that
involves the analysis of the self as presented in relation to other characters (Bamberg, 1997).
It differs from ST-TA insofar as the former requires brief autobiographical reflections as its
data, while the latter can be used with any kind of brief text, including, for example, answers
to open-ended questions in surveys (that may not have any self-reference, characters or
story).
Although not specifically devised for brief data, content analysis has been used
extensively for analysing brief qualitative data. To give one recent example, Davis et al.
(2020) conducted a qualitative content analysis of 2,561 brief written descriptions of
memorable experiences of taking the psychedelic DMT. The methodological processes of
such content analysis studies show notable similarities with ST-TA, however the outcome of
this kind of content analysis is a list of codes and frequencies with little by way of theme
description, example quotes and discussion of patterns found. In contrast, ST-TA places a
strong emphasis on conveying the meaning and context of qualitative themes, with verbatim
examples taken from the data to support and illustrate any general concepts conveyed. It’s
embracing of some quantification is done in addition to this fundamental qualitative process,
rather than instead of it.
The process of conducting ST-TA on brief texts
Structured tabular thematic analysis (ST-TA) is conducted in spreadsheet software
such as Excel and is designed to meet the challenges and opportunities of working with brief
texts. It requires no specialist qualitative analysis programmes so is accessible to all
researchers, no matter their budget or technical knowledge.
At a procedural level, structured tabular TA follows a hybridized process approach
that incorporates elements of Braun and Clarke’s TA process (2006) and Boyatzis’s TA
phases (1998). Below I describe each phase in turn and whether it applies to inductive
research, deductive research or hybrid inductive-deductive designs. Table 1 summarizes the
phases for inductive, deductive and hybrid options. To illustrate some points, I use data,
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tables and a figure based on a study on how perceptions of parenting relate to authenticity in
young adults (Ayoola & Robinson, 2017).
INSERT TABLE 1 HERE
Phase A: A-priori theme development (Deductive and Hybrid only)
Thematic analysis that is purely deductive in approach does not require the generation of new
codes and themes. It commences with a set of themes prior to data collection and analysis,
taken directly from a previous study in the topic area and then seeks to apply those to a new
sample. Research objectives suitable for a deductive approach include: (a) replicating an
existing thematic analysis study or (b) developing, extending or testing an existing thematic
framework or theory. In order to develop a set of themes for a deductive study, one can take
either a broadly theory-based approach, in which themes are inferred from a theory, or a
prior-research-based approach, in which themes are taken from the findings of an existing
thematic analysis study (Boyatzis, 1998).
Deductive and inductive approaches can be combined in hybrid designs (Robinson &
Smith, 2010). A hybrid approach is appropriate where there is (a) substantial qualitative
literature on the topic of study to draw on, meaning a purely inductive approach would
potentially omit existing insights and knowledge, but also (b) a clear sense that existing
knowledge is partial, and hence there is a need for continued development of thematic
frameworks and theory.
In such a hybrid approach, the analyst will firstly deploy an initial set of themes or
concepts from existing work to orientate the analysis process. These provide a starting point
as orientating constructs. The process of generating codes and themes is then worked through
with this opening set of constructs or themes in mind, and these are modified or added to
depending on whether the data fits the scheme or not. For example, in a study on admiration
in young adults, myself and colleagues used this hybrid approach to organize our analysis of
brief written descriptions of an admired individual provided by young adults from three
cultures (Robinson et al., 2015). We employed a thematic framework from an existing
qualitative study (Schlenker et al. 2008), and then refined this set of themes as we analysed
the data. So, the final set of themes only partially drew on the initial themes.
In summary, if you are intending to conduct a deductive or hybrid analysis, you will
need to select a set of constructs or themes from existing literature and provide a robust
rationale for why you have done so.
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Phase B: Deep immersion in the data (Deductive, Inductive and Hybrid)
For this phase, you will need to transcribe or import your data into Excel in such a way that
each brief text occupies one cell in a column, as illustrated in Table 2. You will also need to
include a column with an anonymized participant identifier or number, and columns with
demographic details. Two key injunctions that Braun and Clarke emphasize in their
methodology, which are also essential to this first phase of the tabular approach, are (a)
repeated reading of the data, and (b) taking initial notes for codes. To facilitate repeated
reading of the data in Excel, make sure to select the ‘Wrap Text’ option (right click > Format
Cells > Alignment > Wrap Text). This ensures that all text is shown in each cell. To facilitate
taking notes, next to the column of data, create a column labelled initial notes. See Table 2
for an illustration of the layout of the spreadsheet. Carefully and slowly read each data
segment, adding notes for possible codes, or other initial analytical ideas, as you go. If you
have started with an a-priori theme set, you might make notes on any cases that you think do
not fit the scheme. For this task, you can either do this on screen or print the spreadsheet out,
depending on your preference. Follow this process of immersive reading of the entire dataset
at least twice, until you feel a strong familiarity with all the data and start to get an early
sense of any patterns therein.
INSERT TABLE 2 HERE
Phase C Generating initial codes and themes (Inductive and Hybrid Only)
After the initial process of familiarising yourself with the data, you can move onto the
development of codes, if you are using an inductive or hybrid design. In a hybrid design, a
priori themes will tentatively inform theme generation.
For the process of generating initial codes, add an additional column to your
spreadsheet and add the title in the top row of ‘Initial Codes’, as shown in Table 2. Based on
your immersive reading and initial notes, add in names of codes into this new column. Enter
terms or words that you think, based on your repeated reading, subsume or describe content
in multiple data segments or texts. By so doing, you are taking the first step towards finding
common patterns, words or ideas, which is always your ultimate goal in a thematic analysis.
Once the process of code development is complete, you will have at least one code
entered in every row. For the next step, copy and paste the full column of code words into
another worksheet in the same Excel file (NB. click the button at the bottom to do this).
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On this new sheet, use the copy and paste function to move codes around and group them into
clusters. You can use different columns for different clusters to aid visualising the process.
Each cluster of codes is a prospective theme. Then, you need to name your clustered codes
using phrases or terms that are clearly anchored in the data and are as idiosyncratic to your
study as possible (that can sometimes mean using a longer, rather than shorter, theme name).
A common error is to name themes with terms that are so short or generic that they have no
clear relationship to your specific study or research question. For initial codes and subthemes,
using the words and phrases that participants use is key to ensuring that the process of
thematic abstraction is grounded in the language of participants. For higher order themes, it is
avoidance of the ambiguity that comes with excessive concision that is key to idiosyncrasy.
An example is shown in Table 3; the theme name “Perceived negative effect of parenting on
authenticity”, at seven words long, is longer than most themes that one sees in most thematic
analysis studies. However, by using a phrase like this for the theme name, the meaning is far
less ambiguous than if one were to attempt to reduce it to one or two words.
You can continue to move codes between clusters, combine clusters, and re-name
themes until you have a framework that you are satisfied will allow all, or nearly all, of your
brief texts to be linked to at least one theme. A popular way of creating an additional layer of
order in your themes is to have two levels of theme: main theme and sub-theme. Main themes
are more abstract and therefore include more semantic content than sub-themes, hence
provide an additional quality of analytical parsimony, should that be desired. Whether or not
two levels of theme are appropriate to your study depends on the research questions you pose,
and whether a more abstract level of thematising helps to convey clear and coherent answers
to your questions.
The structured tabular approach to thematic analysis is open to searching for semantic
or latent themes (Braun & Clarke, 2006). Semantic themes are manifest in the surface
meanings of the data; they are descriptive and minimize inference from the textual content.
Latent themes require further interpretation, as they are not manifest in the data, but are
implicit beyond or below the surface content.
Phase D Tabulating themes against data segments (deductive, inductive and hybrid)
Phase D involves attaching data segments to themes in a tabulated form, an example of which
is shown in Table 3. This provides a foundation for the agreement-checking and frequency
calculation processes outlined in Phases E and F. The practical process of Phase D is as
follows:
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1. If you are working inductively, open a new worksheet in your Excel file and copy a
duplicated version of your Phase B spreadsheet, including participant number,
demographic data and qualitative text data in the left-hand columns. Delete the notes
and themes columns (make sure to keep the original worksheet with those notes and
themes on file).
2. Insert a row at the top of the new spreadsheet. Write your theme names across the top
row, starting with the column to the right of your qualitative text column. If you have
just one level of theme, then one row at the top will suffice. If your themes are
differentiated into main themes and sub-themes, insert two rows at the top and put the
main themes across row 1, and the sub-themes across row 2. For main themes, merge
the cells across the columns that main themes refer to, as shown in the example in
Table 3. Keep theme columns narrow, so that you can fit many on the screen at once
this helps the process of analytically allocating texts to themes.
3. Select the top row or top two rows (depending on whether you have one or two levels
of theme), then go to View > Freeze Panes > Freeze Panes (based on current
selection). This will mean that your theme names remain visible as you scroll
downwards.
4. Once you are sure that you have your final set of themes, go down through each brief
text and wherever a sub-theme is represented in the data, add a 1 in the relevant
column. Do this until all have been allocated to sub-themes. You can attach each text
to multiple themes if appropriate. Table 3 shows an example in which texts from 5
participants have been allocated to three themes, extracted from the authenticity and
parenting study by Ayoola and Robinson (2017).
INSERT TABLE 3 HERE
This process of tabulation allows the relationship between data and themes to be visually
related in new ways, so may lead to continued theme development. If themes are further
developed at this point, make sure to keep a dated log of all changes. This helps your
analytical process to be fully transparent to others. One option for keeping a log of thematic
developments is by creating an additional worksheet in your Excel file and using it a log. In
this way, it will also be found in the same place as your analysis.
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Phase E: Checking inter-analyst agreement
Phase E involves the process of checking the level of thematising agreement between
yourself and another analyst. One way of reaching agreement is through an informal
discussion-based approach where the two researchers discuss the themes they have attached
to the brief texts and resolve differences and debates in order to end up with a more
consistent, coherent and clear set of themes. A more structured set of processes for checking
agreement across analysts is as follows:
1. Two individuals are provided with a blank version of the data tabulation spreadsheet with
no. 1s entered. Both individuals should ideally be familiar with the theme names and
codes developed or employed for the study.
2. The two analysts should allocate texts to themes independently of each other.
a. If the dataset is large, an option is to select a subset of participants for this
agreement check (20-30 is an appropriate number).
3. Having both done that, one of the analysts combines the two spreadsheets into one for
checking, by inserting the theme columns from one into the other.
4. For each row, the analysts must then calculate the number of agreements (where both
analysts have a 1 in the same cell), and the number of disagreements (one analyst has a
1 in the cell, but the other does not).
5. The total number of disagreements and agreements should be calculated across all cases.
A percentage level of agreement is calculated as follows:
Total no. of agreements
________________________________
Total no. of agreements + disagreements
The aim of this process is to end up with a level of agreement that supports the
proposition that the analytical scheme and process is transparent, rigorous, coherent and
trustworthy (Nowell, Norris, White & Moules, 2017; Yardley, 2000). If a thematic scheme is
clear and coherent, and themes are described with rigour and transparency, analysts should
have little problem agreeing on which texts are allocated to which theme. Conversely, a weak
analysis, in the words of Braun and Clarke, is where “the themes do not appear to work,
where there is too much overlap between themes, or where the themes are not internally
coherent and consistent” (2006, p.94). If themes are vague, poorly defined, or poorly labelled,
two analysts will find it difficult to tabulate themes against brief texts, and this will be shown
up in this process.
x 100
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An appropriate rule-of-thumb to aim for, originally put forward by Miles and
Huberman (1994) based on extensive trialling of inter-analyst checking, is 80% agreement. If
this level is not achieved, the two analysts can convene and discuss their disagreements and
consider ways of adapting theme names or theme descriptions to come to a higher level of
agreement. This second stage of reaching consensus need not be done blind, but rather should
be done as a discursive process of continued theme development between the two researchers
until a consensus position is achieved. This may of course lead to theme re-development, in
which case the process cycles back to Phase C.
Phase F Exploring Theme Frequencies
The use of structured tabular thematic analysis provides for a higher degree of
precision with which statements of a theme’s prevalence across the sample can be made.
Having such prevalence data increases the trustworthiness and transparency of the findings,
in line with other injunctions for trustworthiness in thematic analysis (Nowell et al., 2017). It
is, however, important to emphasize again that frequency of a theme does not equate on its
own to how relevant or salient a theme is within a study (Braun & Clarke, 2016).
To calculate the frequency of participants allocated to each theme, add a frequency
calculation cell at the bottom of each column, as illustrated in Table 3. To calculate this
automatically using an Excel formula, write =SUM( ) in the cell, with the brackets containing
the top and bottom cell code, separated by a colon. So, for example, if a theme is shown in
column D and there are 40 participants, the first of which is in row 2 (because themes occupy
row 1), the formula would be = SUM(D2:D41). The resulting frequency data is primarily to
provide accurate statements about the prevalence of themes when writing up the report in
Phase 6. You can also choose to explore frequencies by comparing them across key
demographic groups, for example, comparing males and females, if that is considered
appropriate to the research question.
Frequency data present the opportunity of further quantitative analysis beyond total-
sample frequencies. For example, if a researcher had data from males and females and was
interested in gender differences in terms of theme prevalence, they could transfer the
spreadsheet into a statistics package, insert 0 for all the instances where a theme has not been
coded, enter gender in a column as a nominal variable, and run a frequency-based test such as
Chi Square to test the difference. This process fits within a form of mixed-methods research
design referred to as the data transformation model (Creswell & Plan Clark, 2010).
16
Phase G: Developing thematic maps and diagrams
Braun and Clarke (2006) emphasize the benefits of thematic maps and diagrams to thematic
analysis. These can aid analysis by presenting a visual representation of relations among
themes that stimulate an integration of themes into a model or a conceptual framework
(Robinson, 2011). Maps and diagrams are also integral to the structured tabular approach to
TA, both as a way of helping to develop and relate themes, and as a way of presenting
analytical patterns concisely and coherently. See Figure 1 for an example of a diagram
developed from the Ayoola and Robinson (2017) study on authenticity and parenting in
childhood.
INSERT FIGURE 1 HERE
Creating diagrams and maps involves examining relationships between themes and then
using the arrows or lines in the diagram to represent those relationships. Through this
process, a list of themes moves towards becoming a model, framework or integrated scheme.
It is recommended that once a list of themes has been provisionally developed, they can be
written on post-it notes or small pieces of paper and combined in patterns with potential
relationships also written onto post-it notes and placed between themes. This process may
lead to further insights in theme development, as when a ‘whole’ is achieved by way of
creating a theoretical frame, it can inform the nature and labelling of the themes to some
degree. Thus, there may be a recursive process between Phase G back to Phase C.
To support this process of relating themes to achieve integration, a ‘bolt on’ method
called Relational Analysis (Robinson, 2011) can be used. Relational analysis presents ten
kinds of ways that themes can relate: descriptive, comparative, semiotic, evocative,
contingency, causal, reciprocal, dialectical, conceptual part-whole and contextual part-
whole. These relational forms can be explored as candidates for making sense of how themes
relate. Researchers can undertake this process of exploring relationships in dialogue or
individually. The outcome of exploring inter-theme relationships feeds directly into the
process of creating a map or a diagram, as lines or arrows in maps visually indicate such
relationships.
Phase H - Producing the report
In any thematic analysis study, writing the report is an active part of the analytical
process, and this holds true of the structured tabular approach. The nature and structure of the
17
report depends on whether a tabular thematic analysis is used as (1) a stand-alone analysis,
(2) alongside in-depth qualitative methods, or (3) with quantitative methods. If brief texts are
the sole form of data, the report will contain a singular results section that presents the themes
using the typical structure of a qualitative results section. If forms of in-depth qualitative data
have been collected concurrently as part of the study, it is recommended that the two are
presented in two subsequent results sections, with an integrative discussion to systematically
compare the brevity-and-breadth findings of the tabular approach with the length-and-depth
findings of the other method.
Another option for a report including a structured tabular thematic analysis is a
mixed-methods paper that combines qualitative and quantitative findings. As mentioned
earlier, a popular option in mixed-methods research is to concurrently gather numerical and
brief textual data about a specific phenomenon by way of an online data collection tool, then
integrating these forms of data to inform findings. For example, the Ayoola and Robinson
(2017) study from which the data extracts in Table 2 and Table 3 are taken, included (a) brief
texts on how parenting during childhood is perceived to influence adult authenticity, as well
as (b) psychometric data on trait authenticity and retrospective ratings of parental care and/or
neglect during childhood. The qualitative and quantitative analyses were discussed in the
report and interpreted in combination.
Sampling concerns
A pertinent issue that relates to ST-TA is the matter of sampling. Qualitative methods
that have traditionally been associated with depth data have been associated with purposive
sampling (e.g. Lincoln & Guba, 1985). Purposive sampling involves the intentional selection
of specific kinds of participant from the target sample to ensure variability of the sample
along key parameters that may differ in their responses (e.g. ensuring a balance of males and
females or young and old). It is thus designed to elicit a sample that represents a broader
population when the N is low (Robinson, 2014b).
Brief text research gains its richness through the diversity of responses, rather than the
depth of responses. Therefore, when ST-TA is used, the sample N will often be larger than
in-depth qualitative studies. Thus, it can and should employ a different sampling approach to
the purposive strategies of small-N interview studies. Random sampling is premised on the
logic that the larger the number of participants in a sample, the more likely they are to be
representative of a target population. Thus, samples of hundreds or thousands may well show
representative parameters in ways that samples of 10 or 20 will not. However, a range of
18
factors mitigate against random sampling even with large samples. The voluntary nature of
psychological research studies means that people who are interested take part. These
psychologically curious individuals may well not be representative of the population. Another
issues is that if recruitment processes are locally situated, for example via a university or via
recruitment posters, they may end up with a convenience sample, limited by geography;
social connections to the researcher; socio-economic background, or a whole range of other
factors, which may mean the sample is not truly random. Online recruitment agencies may
have a greater geographical access, but their participants are those who have signed up for
getting micro-payments through research participation. Such individuals are unlikely to be a
random sample.
One solution to this is to combine random sampling with purposive sampling
(Robinson, 2014b). For example, if it is considered important to have an equal distribution of
males and females in a sample, and also to have an equal distribution of younger adults and
older adults, a researcher can purposively select to have 30-40 young adult males, 30-40
young adult females, 30-40 older adult males and 30-40 older adult females in a sample, but
then randomly sample within each of these cells to reach that target. In sum, a problem-
focused and flexible approach to sampling, which can incorporate purposive and random
sampling or combinations of the two, is appropriate to accompany ST-TA.
Conclusion
I have presented the structured tabular approach to thematic analysis as a way of
flexibly and rigorously analysing brief texts. Such an approach is of growing importance
given both the increasing availability of such data via social media along with the rising
popularity of open-ended survey response or short story elicitation methods (Clarke et al.
2019; Terry & Braun, 2017). The approach synthesizes injunctions from two approaches to
thematic analysis and adds in a range of processes for working with brief texts, including the
practical advantages of using a spreadsheet when dealing with a larger sample and a tabulated
form of analysis that provides opportunities for frequency and agreement calculation. It
requires no specialist analysis software, thus is widely accessible and user-friendly for
researchers at any level. The protocols and processes I have described above are flexible
guidelines, and I encourage the reader to adapt them to their needs and to innovate further as
and when appropriate. Brief texts remain an important frontier for qualitative psychology and
I hope this method will act as encouragement for researchers to explore the full potential of
this type of data.
19
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Table 1. Analytical phases for deductive, inductive and hybrid research studies
Deductive
Hybrid
Inductive
Phase A: A-priori theme
development
Phase A: A-priori theme
development
SKIP PHASE A
Phase B: Deep immersion in
the data
Phase B: Deep immersion in
the data
Phase B: Deep immersion in
the data
SKIP PHASE C
Phase C Developing revised
codes and themes in context
of, and influenced by, a-priori
themes.
Phase C Generating codes
and themes (as uninfluenced
by existing theory as is
possible)
Phase D Tabulating themes
against data chunks
Phase D Tabulating themes
against data chunks
Phase D Tabulating themes
against data chunks
Phase E: Checking agreement
Phase E: Checking agreement
Phase E: Checking agreement
Phase F Exploring Theme
Frequencies
Phase F Exploring Theme
Frequencies
Phase F Exploring Theme
Frequencies
Phase G: Thematic maps
Phase G: Thematic maps
Phase G: Thematic maps
Phase H - Producing the report
Phase H - Producing the report
Phase H - Producing the report
25
Table 2: Spreadsheet format for Phase 1 with illustrative textual data from parenting
authenticity study
No.
Gender
Qualitative data segment
Initial notes
Initial codes
1
Male
Yeah. I think so. My parents were honest with
me and about themselves and I think it fostered
that in me, too... So, I try to stay true to myself
as much as I can.
9
Female
My mum made it very easy to be whoever I
wanted to be and I saw how she accepted all my
friends growing up in spite of anything that
could make them different/stand out. She took
an interest in me and who I was and so I had a
strong sense of self from an early age.
27
Female
I believe that it helped a lot. My mum always
encouraged me to be myself and it was fun to
sometimes shock my dad with who I am. So, I
have learnt to know myself and to be myself.
33
Male
The love my parents have for me show that I
don't need to pretend to be someone else as they
love me just the way I am.
NB. Cases selected for this table represent main theme of perceived positive effects of
parenting on authenticity
26
Table 3: Spreadsheet format for Phase 4 illustrative five cases, one main theme with three
subthemes shown
Main theme: Perceived negative effect of
parenting on authenticity
No.
Gender
Qualitative data segment
Subtheme 1
Cultural /
generational
disconnect
Subtheme 2
Parents as
negative
role models
Subtheme 3
Criticism or
disapproval
of
characteristics
10
Male
I feel I am true to myself, but there are some
parts of who I am I feel I have dismissed or
choose to hide from my parents as I feel that
they would disapprove or not fit the image
that they have of me.
1
15
Female
I think they gave me a foundation. However,
I've come to being my own adult sometimes
in disagreement with my parents. I think it's
because they were born and raised in Africa
and I in London.
1
35
Female
Being criticised for my personality by my
family has caused me to feel insecure as an
adult. If I was ever feeling upset about
something that my parents didn't believe to
be a big deal, they would brush it off,
leaving me to feel like I was too sensitive.
1
41
Male
My parents are very particular people and so
the parts of myself that do not match their
picture of me have to be hidden. I try to be
as authentic as possible but it is not always
possible, but only in some aspects of life.
1
48
Female
Seeing how much my father neglected his
own emotions and needs completely, I feel
obligated not to make the same mistakes and
live a life being as authentic as possible but
find it difficult as I feel the impression my
father gave has stuck with me and is
difficult to counterbalance.
1
SUBTHEME FREQUENCY
1
1
3
NB. Cases selected for this table represent main theme of perceived negative effects of
parenting on authenticity
27
Figure 1. A map of themes developed in a study of how parents are perceived to influence
adult authenticity in young adults
Criticism or disapproval
of characteristics
Perceived lack of
importance to parents
Parents as negative role
models
Cultural/generational
disconnect
Self-concealment,
insecurity,
avoidance of self-
disclosure
Support for choices
and decisions made
Parents positive role
models; honest & open
Acceptance of
personality & friends
Unconditional love
and care
Confidence to
self-assert or
self-disclose,
sense of security
Authenticity as a
young adult
undermine
facilitate
Perceived negative effect of
parenting on authenticity
Perceived positive effect of
parenting on authenticity
28
Appendix A. The epistemologies underlying quantitative research: A complex picture
the assertion that quantitative research is positivist is discrepant with historical facts.
The history of psychology clearly shows that quantitative research is based on a plurality of
epistemologies, with positivism being a minority player at best. The first of these paradigms
is Popper’s hypothetico-deductive approach to science (Popper, 2002). Popper was explicitly
critical of positivism; whilst positivism conceives of science as eliciting solid facts and
objective truths, Popper’s approach sees science as eliciting tentative and provisional
hypotheses that are never actually true but can be only said to be not yet proved false. The
second influential paradigm in quantitative methods is the pragmatism of William James
(1907). James supported the use of qualitative and quantitative data. He based this on the
reasoning that all research should primarily be directed towards some productive end, and
thus have an instrumental benefit. We should use whatever kind of empirical information can
help solve that problem, and not determine a priori if that evidence should be verbal or
numerical. A third paradigmatic foundation is the introspectionism of Wundt and his
followers, which formatively influenced the development of psychometrics (Otto, 2018). This
paradigm provides a justification for self-observation and hence for self-report
questionnaires, and this in turn supports the edifice of quantitative psychometric methods.
Self-report questionnaires are not only reliant on the validity of self-observation and
introspection, they also require substantial interpretation on the part of the participant. The
individual completing a questionnaire must read a series of written statements or questions
and then judge which number on the scale accords best to their character or experience in
relation to the statements. This process is clearly a deeply subjective and hermeneutic one,
albeit one that is not frequently recognised as such (Robinson, 2014).
While positivism has had little influence on psychology, where it has had some
influence is in sociology, and crucially, positivists in sociology dismiss attempts at self-
observation or self-report (Comte, 1842). This in turn means the rejection of the countless
quantitative studies based on self-report, which are the foundation of much of neuroscience as
well as psychology.
In sum, there is no neat allegiance between quantitative methods and positivism. Such
an assertion appears to be an over-simplistic and distorting reinterpretation of history. The
binary distinction of ‘qualitative-quantitative’ hides a raft of commonalities and complexities.
Rather than two islands with their own separate methodological ethos, qualitative and
quantitative research are more like two intersecting paths through the same forest of
29
evidence-based sense-making. Hence, I contend that a method such as ST-TA, which
intentionally combines qualitative research with limited quantification, is epistemologically
justifiable and coherent.
... • Tabulating themes against data segments The first column included a student identifier, and the second column included each student's response in a separate cell. I repeatedly read the data carefully and slowly, colour-coding certain words and expressions in responses for possible codes and added other initial ideas in a third column that was named initial notes (Robinson 2021). This step was completed through ensuring immersing reading of the entire dataset until I felt I was strongly familiar with all the data and patterns started to appear. ...
... Tabulating themes against data segments-in this step, I attached data segments to themes in a tabulated form. According to Robinson (2021), this step provides foundation for agreementchecking and enables frequency calculation processes. ...
Thesis
The modern translation industry is using machine translation post-editing (MTPE) widely, and the translation industry in the Arab World is following the global lead. However, while MTPE training is offered in many language pairs around the world, MTPE training in English-Arabic is still not officially offered in translation training programmes in the Arab World. The aim of this study is to evaluate the effectiveness of MTPE training in a female undergraduate translation programme in Saudi Arabia by examining students’ opinions about MTPE and comparing its productivity and quality with an established practice in the translation classroom, i.e., human translation (HT). To achieve its aim, this study used a mixed-method design of the ‘Kirkpatrick Model of Learning Evaluation’. Focus group discussions and retrospective pre-test surveys were used to examine students’ opinions as well as a pre-post experiment which involved two groups of students (29 in the control group and 31 in the experimental group) that was used to compare the productivity of students and the quality of translated texts when using MTPE as compared with HT. Students’ opinions that were revealed through the pre-intervention focus group discussions were generally mixed with a preference shown in favour of HT, except for translation speed as most of the students thought that MTPE was the faster method of translation. As for the survey, students’ pre-intervention responses supported those opinions revealed in the focus group discussions. However, post-intervention responses revealed a statistically significant shift towards more acceptance of MTPE training and use, indicating that the more students learned about the features of MT and MTPE skills and practiced them, the more positive their opinions became. Statistical results from comparing students’ productivity showed a medium effect size which indicates that MTPE cannot be ignored as a method to increase productivity in translation. The effectiveness of MTPE in translation quality was evaluated by measuring error count and error type. Error count analysis indicated that students who used MTPE have increased scores in a similar manner to those who used HT but not more. The analysis of error type showed that while MTPE helped students avoid deletion and technical errors, the number of errors relating to accuracy, comprehension and grammar were more frequent in Arabic MTPE translated texts.
... In a final step, in order to enhance the understanding from the qualitative analyses, frequencies of themes were calculated and related to identity centrality (RQ3). In the following we describe these steps in more detail: For the qualitative part of the study, addressing RQ1 about what types of family-related stories people wrote, a thematic analysis (Braun & Clarke, 2006) was conducted with a structured tabular approach (Robinson, 2022). The structured tabular approach to thematic analysis is very similar in procedure to the procedure described by Braun and Clarke (2006) but includes the use of spreadsheet software when coding the data, which is well-suited for larger samples of brief texts, and the approach allows for both qualitative interpretation as well as frequency and reliability calculations (Robinson, 2021). ...
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This study examines the content of family identity among people in Sweden, a country often portrayed as relatively free from traditional family norms. More specifically, we investigated the types of family-related narratives that individuals shared, narratives of deviation from the master narrative of what was expected and accepted in Swedish society. In addition, the identity centrality of the themes was investigated. The data covered 462 participants, 170 of whom – 139 women, 30 men, and one non-binary (Mage = 20.11, SD = 4.85) – had family-related narratives. We identified six themes of deviating narratives, of which the family-related narratives had significantly higher identity centrality than did the non-family-related narratives. Not only do the present findings emphasize the importance of family for people’s identities, but they also illustrate the complex and multilayered aspects of family identity. The master narrative discernable in the participants’ narratives of deviation portrays ideals of the happy, white, secular, middle-class, heteronormative nuclear family, even though this does not always correspond to the actual lived situations of families in contemporary Sweden.
... Two independent coders coded the answer to each of the two interview questions applying a coding scheme developed by Shachnai and Daniel (2020). Following a hybrid ST-TA model approach (Robinson, 2021), we developed the criterion using both theory-driven and data-driven methods. In the first step, the two coders immersed themselves in a sample of the data, searching for the categories developed by Shachnai and Daniel (2020) for abstraction coding, and fine-tuning the coding based on the answers of the participants. ...
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The study aimed to clarify the recent claim that at age five, children rank meaningful values, despite known limitations in their abstract thinking skills. We thus investigated how children develop in their understanding of values between six and eight years of age, as well as associations between this development and cognitive gains. N =299 children ( M ageT1 = 7 .24, SD =.62; T2, 8-13 months later) were asked what they valued and why. Interviews were coded as describing values concretely or abstractly. Working memory (WM) and concept formation (CF) were measured. As hypothesized, older children understood their values more abstractly than younger ones. Mediation analyses established that WM was directly associated with value abstraction at T1 and indirectly associated with value abstraction, via CF, at T2. The results suggest children increasingly understand values as abstract concepts, and this advancement may be tied to progress in both basic and complex cognitive processes.
... Deductive thematic analysis [56] was conducted to test students' responses to the online open-ended question on the existing student engagement framework (behavioural, affective and cognitive engagement), as discussed in the Introduction part. Microsoft Excel was used for conducting a structured tabular thematic analysis [57]. Overall, 178 out of 446 students from both departments left their qualitative responses in this final part of the questionnaire (online open-ended question) and Table 7 provides a breakdown of the number of students who left a qualitative reply per department and year. ...
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This study compared student learning engagement from two UK departments exploring their participation in face-to-face and synchronous online learning environments. Overall, 446 undergraduate students from Psychology (soft/non-Science, Technology, Engineering, and Mathematics (STEM) discipline) and Electrical Engineering and Electronics (EEE) (hard/STEM discipline) completed an online questionnaire over the second semester of the 2020–2021 academic year, where the teaching was mainly online. The questionnaire included validated scales regarding teaching and students’ characteristics and an open-ended question regarding the role of learning environments. There was a significant difference between the two learning environments in both departments, with most of the students believing that they were better engaged with their learning process in face-to-face environments (quantitative analysis). Additionally, the thematic analysis of student qualitative responses revealed that online student engagement was influenced by (1) Behaviour, (2) Affective, and (3) Cognitive challenges (i.e., additional workload, lack of communication and distractions in the home environment) and opportunities (i.e., the effective use of study time and online content through interactive learning environments). This study could assist academics, university policymakers, and researchers to understand student engagement alongside learning environments, reconsidering the opportunities and challenges that were gained from online learning due to the COVID-19 pandemic.
... To validate the results of the quantitative data, part two of the mixed-method questionnaire was intended to collect students' curriculum modification suggestions in view of further improving their career adaptability. Content analysis, a research method for the subjective interpretation of textual data through systematic coding and theme identification (Hsieh and Shannon, 2005;Mayring, 2021;Robinson, 2022), was applied. The coding categories and themes in this study emerged from a thematic examination of the data, rather than being determined beforehand. ...
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The issue of employability has already become a well-delineated topic of study among interpreting educators. However, the current literature still lacks descriptive research on interpreting students' employability development and ignores the developmental effects of interpreter competences in this process. Moreover, the advantage of using career adaptability for measurement is also under-researched. This exploratory case study aims at taking an initial step forward, surveying interpreting students' career adaptability development and the developmental effects of different interpreter competences on major adaptability resources, and ultimately diagnosing curriculum problems and making modifications accordingly. Thirty grade 2019 interpreting students from three Chinese universities contributed to data collection, through six questionnaires in a two-wave survey. The results highlight that, throughout the Chinese MTI program, interpreting students could become more concerned and well prepared for their future (concern), more curious to explore themselves and their surroundings (curiosity), and more capable of solving problems (confidence). The results also indicate that students' knowledge and language competence serve as the major facilitators in this process, and that other interpreter competences, such as psychological competence, transfer competence, professionalism, and cross-cultural competence, are also instrumental. In order to further boost their adaptability constructs, the results suggest that students' language and knowledge competence, professionalism, and cross-cultural and mental agility still need to be improved. Five suggestions for curriculum revision have been raised accordingly. As an initial effort, the current study will hopefully inspire further studies on interpreting students' career adaptability and add more knowledge to the curriculum design from this viewpoint.
... Bivariate associations between age/sexual orientation and individual GAP items were also assessed using a Pearson's r test/point biserial correlation. An inductive structured tabular thematic analysis was conducted to develop and determine the frequency of themes from the open-ended question examining the most important things service providers can do to provide culturally competent services to sexual minorities (Robinson, 2021). ...
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Objectives: Sexual minorities experience higher rates of psychological distress than heterosexual people, likely due to minority stress. While rates of help-seeking by sexual minorities are high, sexual minorities report greater dissatisfaction with mental health service providers. This dissatisfaction may result from poor cultural competence practices. Our study sought to determine the importance of service provider cultural competence practices to a community sample of sexual minority people. Methods: Participants (n = 274) were sexual minority Australians recruited from affirming Facebook groups, organizations, and research-based organizations. To measure the importance of cultural competence practices, participants completed a modified online version of the Gay Affirming Practices Scale (GAP) and responded to open-ended questions. Results: Between 80% and 99% of participants endorsed each item on the GAP, indicating the importance of service providers demonstrating an array of culturally affirming practices. No significant associations were found between overall GAP score and age or sexual orientation, though further analyses revealed individual items on the GAP showed associations with age. A structured tabular thematic analysis, of open-ended participant responses, found positive attitudes, knowledge, and affirming practices were the three most important characteristics for service providers seeking to demonstrate culturally competent practices, mirroring the tripartite model (attitudes, knowledge, and skills) of cultural competence. Conclusion: Recommendations for service providers to demonstrate cultural competence include: utilizing affirming practices such as inclusive language, increasing knowledge about sexual minorities, and utilizing education resources such as cultural competence workshops, lived experience stories, and seeking mentorship from service providers with expertise in working with sexual minorities.
... Hybrid designs of deductive and inductive analysis approaches are appropriate when there is qualitative literature on the topic of the study but the existing knowledge is partial. Thus, a purely inductive approach might omit existing knowledge or theories, while a purely deductive approach will not contribute to the continued development of thematic frameworks and theories (Robinson, 2022). ...
... These opportunities to discuss thoughts and experiences in detail were included to provide depth to the dataset and determine additional understanding and meaning. Thematic analysis, based on an inductive approach within the work of Braun and Clarke [17], was employed to provide unforeseen insights adding further richness to the dataset [18]. ...
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Purpose To establish UK Physiotherapy lecturers’ perceptions of online learning during the COVID-19 pandemic. Materials and methods A cross-sectional mixed methods electronic survey of UK higher education lecturers, actively teaching pre-registration undergraduate or postgraduate physiotherapy degrees, was conducted between October 2020 and February 2021. Data was converted into proportions with a 95% confidence interval. Likert scale questions were treated as numeric variables with the mean and standard deviation calculated for combined responses. The thematic analysis reported patterns of data extracted from open-ended questions. Results 96 respondents completed the survey, reporting some positive attributes attached to online learning. 81% (n = 78, 95% CI 72–88) agreed that students developed their digital skills and were able to learn conveniently at their own pace (n = 75, 78%, 95% CI 69–85). However, 62.5% (n = 60, 95% CI 23–72) of respondents felt that students were overall disadvantaged with online learning, with 72% (n = 69, 95% CI 62–80) reporting that online learning was not comparable to face-to-face to teaching. The reasons for perceived student disadvantage were categorised into three themes; 1) a lack of ability in sessions to practice handling techniques, 2) the inability to gauge student understanding and check practical skill competence and 3) the lack of student self-directed practice time. UK physiotherapy lecturers did indicate they would continue to incorporate online learning in the future (n = 84, 87.5%, 95% CI 79–93). Such responses were based on two key themes; an improved work-life balance and the perception that online learning was no more challenging than traditional on-campus delivery. Conclusions UK physiotherapy lecturers reported that students were disadvantaged with online learning delivery compared to face-to-face teaching. Lecturers indicated a willingness to continue with aspects of online learning across the curriculum, despite suggesting it had a negative impact on students subject understanding.
... This was employed using thematic analysis within the work of Braun and Clarke [27]. This method, based on an inductive approach, can reveal unanticipated insights which may provide further richness to the dataset [28]. ...
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Background As a result of the COVID-19 pandemic a rapid transformation from face-to-face curriculum delivery to an online teaching and learning environment, was adopted in a number of higher education institutions globally. Allied Health Profession courses such as physiotherapy, traditionally utilising an in person teaching model to prepare students for practice, needed to swiftly adopt new methods of delivery, involving both synchronous and asynchronous approaches. Understanding physiotherapy student perceptions of this transition is important to allow faculty to develop their delivery of online teaching and provide an evidence base for future course curricula. Methods Cross-sectional survey of UK higher education students studying either an undergraduate or post-graduate pre-registration degree in physiotherapy was conducted between October 2020 and February 2021. The survey investigated the student’s perception of the transition to either an online or hybrid model of learning during the COVID-19 pandemic. A mixed method approach was adopted allowing respondents to share their experiences and facilitate the exploration of questions which required in-depth thought. Results Two hundred thirty-six respondents completed the questionnaire. Online learning was perceived to be a flexible (49%, n =116,CI 95% 43 to 55) and convenient (49, 116, 43 to 55) method of learning. Despite this, 79% of the students surveyed felt that the online learning experience had a negative impact on their understanding of the subject and were disadvantaged compared to traditional face-to-face teaching provision (mean 4.14 ± SD 1.06). Online physiotherapy delivery produced low student satisfaction, leaving respondents feeling disadvantaged. Decreased levels of engagement and the lack of ability to practice ‘hands-on’ skills were detrimental aspects of the online approach, with 55% ( n =106) reporting they did not perceive the academic staff had the necessary skills to deliver effective online content. Conclusions The majority of UK physiotherapy students surveyed were dissatisfied and lacked engagement with an online learning approach within the curricula, compared with the traditional face-to-face delivery. Although several positives of both a synchronous and asynchronous delivery were highlighted, faculty must consider how they best deliver online learning content, making use of pedagogical strategies that will create as many learning and engagement opportunities as possible.
... A postpositivist paradigm holds that multiple realities exist, yet these realities can never be fully understood and therefore only approximated (Ponterotto, 2005). The structured tabular approach by Robinson (2021) was employed. An excel file was created for each demographic of interest, such that there were All Participants, Cis Men, Cis Women, Trans/ Genderqueer, Heterosexual, and LGBQ spreadsheets. ...
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