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Conducting thematic analysis on brief texts: The structured tabular approach



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.
Conducting thematic analysis on brief texts: The structured tabular approach
Dr Oliver C. Robinson
University of Greenwich
Dreadnought Building, London, SE10 9LS
Tel: +44 208 331 9630
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
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
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,
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
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
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),
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
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
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’
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
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,
tables and a figure based on a study on how perceptions of parenting relate to authenticity in
young adults (Ayoola & Robinson, 2017).
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.
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.
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).
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
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
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).
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.
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
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).
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
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
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
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
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.
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.
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Table 1. Analytical phases for deductive, inductive and hybrid research studies
Phase A: A-priori theme
Phase A: A-priori theme
Phase B: Deep immersion in
the data
Phase B: Deep immersion in
the data
Phase B: Deep immersion in
the data
Phase C Developing revised
codes and themes in context
of, and influenced by, a-priori
Phase C Generating codes
and themes (as uninfluenced
by existing theory as is
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
Phase F Exploring Theme
Phase F Exploring Theme
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
Table 2: Spreadsheet format for Phase 1 with illustrative textual data from parenting
authenticity study
Qualitative data segment
Initial notes
Initial codes
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.
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.
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.
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
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
Qualitative data segment
Subtheme 1
Cultural /
Subtheme 2
Parents as
role models
Subtheme 3
Criticism or
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.
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.
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.
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.
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.
NB. Cases selected for this table represent main theme of perceived negative effects of
parenting on authenticity
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
avoidance of self-
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
sense of security
Authenticity as a
young adult
Perceived negative effect of
parenting on authenticity
Perceived positive effect of
parenting on authenticity
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
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.
... The study employed Structured Tabular Thematic Analysis (ST-TA) to analyze the data [40]. This form of thematic analysis is designed specifically to analyze brief texts such as those ...
... For the current study, given the relatively uncharted nature of the domain under study, particularly from a qualitative perspective, we chose to conduct an inductive analysis. The phases for inductive analysis in ST-TA are as follows: 1. Deep Immersion in the Data; 2. Generating Initial Codes and Themes; 3. Tabulating Themes Against Data Segments; 4. Checking Inter-analyst Agreement; 5. Exploring Theme Frequencies, 6. Developing thematic maps and diagrams, and 7. Producing the report [40]. ...
... A process within ST-TA that supports this is for the agreement-reaching process. Part of the this is calculating agreement levels via two analysts independently analyzing a subsample of texts, and aiming for 80% [40]. Using random samples of responses and analyst pairs, it took three iterations of agreement check to reach 80%, between which there were continued revisions of themes and sub-themes to boost clarity and cogency. ...
Full-text available
Long-term adverse experiences following psychedelic use can persist for weeks, months, or even years, and are relatively unexplored in psychedelic research. Our convergent mixed-method study gained quantitative and qualitative data from 608 participants who reported extended difficulties following psychedelic experiences. Data was gathered on the context of use, the nature and duration of the challenges they experienced (including a written description of these), plus a range of possible risk factors and perceived causes. The most common forms of extended difficulty were feelings of anxiety and fear, existential struggle, social disconnection, depersonalization and derealization. For approximately one-third of the participants, problems persisted for over a year, and for a sixth, they endured for more than three years. It was found that a shorter duration of difficulties was predicted by knowledge of dose, drug type and lower levels of difficulty reported during the psychoactive experience, while a narrower range of difficulties was predicted by taking the drug in a guided setting. Implications for psychedelic harm reduction are discussed.
... Qualitative data were analysed using the procedures using the guidelines of Robinson, Larkin et al., and Miles et al., [20,21,22]. The open-ended narrative data was downloaded from the online Qualtrics portal into Microsoft Excel. ...
... The open-ended narrative data was downloaded from the online Qualtrics portal into Microsoft Excel. A structured tabular analysis was carried out within Excel following Robinson's widely used framework specifically developed to analyse open-ended qualitative survey questions [20]. Robertson's method for data coding begins by gaining a thorough understanding of the survey data. ...
... In this research, the themes represent the types of concerns people have around family members providing DNA to police in LTMP cases. Each theme identified is then titled and the data is coded in a tabular approach within Excel [20]. The qualitative approach used to develop the themes was a sequential idiographic thematic content analysis, where all short answer responses are read in full in sequence and themes are developed in the data as they arise [21]. ...
... Furthermore, the Scale-CVIs were calculated for the themes. These were calculated by dividing the sum score of all roles in a theme (i.e., sum of Item-CVI scores in a theme) by the total number of ratings [23]. For a minimum Scale-CVI the score should be at least 0.90 [21]. ...
... For a minimum Scale-CVI the score should be at least 0.90 [21]. The open questions were analysed using structured tabular thematic analysis [23]. Reniers ...
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Background Pets play very important roles for older adults. However, whether the same roles apply to pets of care clients receiving long-term care at home (LTCH) is unclear. This study aimed primarily to explore whether the roles of pets for LTCH-clients who own pets are comparable to the roles of pets for older adults in the general population. Furthermore, we explored potential pet-related problems that might be encountered in LTCH in practice, and the potential influences of pet ownership on caregiving relationships. These insights may help improve long-term care services in LTCH. Methods This project started with a study using the Consensual Qualitative Research method (CQR). We conducted semi-structured interviews based on themes from our previous review (e.g., Relational Aspects, Emotional Aspects, and Social Aspects). Secondly, an online survey was used to confirm the findings from the CQR study by calculating Content Validity Index scores (in SPSS 26) regarding contents, relevance, and clarity. The survey also included open-ended questions on potential pet-related problems and their impact on caregiving relationships for LTCH-clients, family caregivers, and professional caregivers. Results The CQR study found that the roles pets play for LTCH-clients (N = 8), family caregivers (N = 10), and professional caregivers (N = 10) were similar to the roles pets play for older adults in the general population. The online survey confirmed most of the CQR findings. In the survey, LTCH-clients (N = 4), family caregivers (N = 8), professional caregivers (N = 8), and researchers in human-animal studies and in geriatric care (N = 5) reported various potential problems that could arise from pet ownership by LTCH-clients, such as clients with deteriorating health being forced to part with their pets. Participants also reported potential positive and negative effects of pet ownership on caregiving relationships, such as pets being a nice topic of conversation, or, conversely, a source of disagreement in the LTCH context. Conclusions The roles pets play for LTCH-clients seem comparable to the roles pets play for older adults in the general population. In addition, LTCH-clients might experience pet-related problems specific to the LTCH context. Pets may influence caregiving relationships, either positively or negatively. Therefore, instruments and guidelines are needed to account for pets in LTCH.
... Основная задача интервью состояла в том, чтобы получить целостное представление о феномене аутентичности (Neuendorf, 2018). Для анализа данных мы выбрали структурированный табличный тематический анализ, подходящий для работы с краткими текстами на больших выборках (Boyatzis, 1998;Robinson, 2022). В этом виде анализа в ответах респондентов выделяются смысловые паттерны и темы. ...
... В процессе анализа мы следовали плану анализа О. Робинсона (Robinson, 2022), который согласуется с планом рефлективного тематического анализа, разработанного В. Браун и В. Кларк: знакомство с данными, генерация исходных кодов, поиск тем, пересмотр тем, формулирование названий тем и составление отчeта (Braun, Clarke, 2006). Процесс кодирования был итеративным и рефлексивным, данные многократно перечитывались, коды пересматривались, темы укрупнялись (Fereday, Muir-Cochrane, 2006). ...
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Authenticity is a personality trait, which implies loyalty to one's true self, correspondence to the personality, spatio-temporal life circumstances, and vocation. Three main paradigms of the interpretation of authenticity are compared - person-centered, existential, and agent paradigms. To study the dynamics of everyday experience of authenticity, an exploratory study was conducted on the respondents of three ages: primary school children (7–12 years old, SDage = 1.12), adolescents (12–17 years old, SDage = 1.62), and youth (18–23 years old, SDage = 0.92). Each group included 150 people and was balanced by gender. The main method was a research interview followed by a structured tabular thematic analysis. The interview included five thematic blocks covering the main manifestations of authenticity - authentic living, accepting external influence, self-alienation, behavior, and balance of social/individual. The results demonstrate the greater relevance of the existential and agent paradigms for describing the respondents’ authenticity. In all ages, authenticity was described as an initially social feature, stimulated by interaction with other people and manifested in it. The influence of other people was not considered by respondents as a source of self-alienation, regardless of age. The descriptions of authenticity become richer and more differentiated with age. In primary school children, authenticity is reflected weaker, and the state of self-alienation is recognized with difficulty. Finally, manifestations of authenticity are age-specific and closely related to the content of the developmental tasks of each of the considered stages. The results obtained can be used in further research and applied programs. Аутентичность — черта личности, означающая верность своему истинному Я, соответствие природе индивидуальности, пространственно-временному контексту жизни и предназначению. Сопоставляются три основные парадигмы толкования аутентичности — личностно-ориентированная, экзистенциальная и субъектная парадигмы. Для изучения динамики повседневных представлений об аутентичности проведено эксплораторное исследование представителей трех возрастных групп: младших школьников (7–12 лет, SDвозраст = 1.12), подростков (12–17 лет, SDвозраст = 1.62) и юношей и девушек (18–23 года, SDвозраст = 0.92). Каждая группа включала по 150 человек и была сбалансирована по полу. В качестве метода сбора данных использовалось исследовательское интервью. Полученные тексты были проанализированы с помощью структурированного табличного тематического анализа. Интервью включало пять тематических блоков, охватывающих ос нов ные проявления аутентичности: аутентичную жизнь, принятие внешнего влияния, самоотчуждение, поведение и баланс социального/ инди видуального. Результаты демонстрируют боль шую релевантность экзистенциальной и субъектной парадигм для описания аутентичности респондентов указанного возраста. Во всех воз растных группах аутентичность описывается как изначально социальное качество, стимулируемое взаимодействием с другими людьми и проявляющееся в нем. Влияние других людей не рассматривалось респондентами как источник самоотчуждения, независимо от возраста. По мере взросления описания аутентичности становятся более богатыми и дифференцированными. В младшем школьном возрасте аутентичность рефлексируется слабее, а состояние самоотчуждения распознается с трудом. Все изученные проявления аутентичности возрастно специфичны и тесно связаны с содержанием задач развития каждой из рассмотренных стадий. Полученные результаты могут быть использованы в дальнейших исследованиях и психоразвивающих программах.
... Responses to these open-ended questions constituted narrative records written during or immediately after each interaction. Records were organized by two independent raters into themes [84] if a majority of the instructors mentioned them. In response to these open-ended questions, all instructors described themselves as adopting a student-centered pedagogical approach. ...
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This study examined whether differences exist in the emotional state of students whose approach to undergraduate courses is either preferentially learning-oriented or grade-oriented. It focused on an understudied population of female college students of Saudi Arabian descent who were enrolled in a challenging writing course. Their emotional state was assessed both globally, through the appraisal of their degree of happiness, and locally, through the appraisal of their writing anxiety (a task-specific emotional state). The study contributed to the extant literature by examining whether the association between goal orientation and emotional state, which is predicted by goal orientation theory, could be found in the selected understudied student population. Results illustrate differences between STEM and non-STEM learners. For STEM students, a grade orientation was associated with declining self-reported happiness and increasing writing anxiety. In contrast, for both STEM and non-STEM students, a learning orientation was associated with increasing happiness and declining writing anxiety. Differences existed in the particular type of writing anxiety that was experienced by STEM and non-STEM students. These findings suggest that interventions for students who are struggling academically may need to address personal dispositions if such interventions are to foster subjective well-being (including positive emotions).
... The open question delivered together with SUS was analysed using structured tabular thematic analysis [22]. The answers to the open question were imported into spreadsheet software (Microsoft Excel). ...
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Background Early mobilisation is strongly recommended following abdominal cancer surgery, but evidence on how to structure early mobilisation to improve outcomes and support patient adherence is lacking. Pedatim® (Phystec) is a novel digital tool designed to support mobilisation in hospital settings using prescribed activities and goals on a tablet. The aim of this study was to evaluate the feasibility of the Pedatim tablet to enhance mobilisation following abdominal cancer surgery. Methods In a non-randomised feasibility trial design, participants were recruited between January and May 2022 at Karolinska University Hospital, Sweden. Participants used a Pedatim tablet from postoperative day 1 (POD 1) until hospital discharge. The primary objective was to evaluate process feasibility, regarding recruitment, compliance, and acceptability. Recruitment was measured by percentage of available patients included, eligibility criteria sufficiency, and number of dropouts. Compliance was measured by number of patients using versus not using the board. Acceptability was measured using the System Usability Scale. The secondary objective was to evaluate scientific feasibility, defined as an indication of treatment effects where physical activity was assessed using an activPAL accelerometer. Unforeseen events relating to the tablet were also registered. Results Based on predetermined feasibility criteria, the overall study design was determined to be feasible regarding recruitment as 69% accepted participation ( n = 20), compliance was 95%, and the acceptability mean score was high (77/100). Eligibility criteria were not feasible as 79% ( n = 108) of available patients were excluded. The intervention was determined to be scientifically feasible, mean steps per day increased from 623 (SD 766) to 1823 (SD 1446), and mean sit-to-stand transitions per day increased from 11 (SD 8) to 29 (SD 12) POD 1–4. Technical issues emerged, highlighting the need for available technical support and “user champions” among healthcare professionals on the ward. Conclusions Using the Pedatim tablet to enhance mobilisation following abdominal cancer surgery was deemed feasible, but a randomised controlled trial is needed to determine the tool’s effectiveness. The study process was determined to be feasible with revisions of the eligibility criteria needed before a future trial. Involving healthcare professionals and providing available technical support are important for future implementation.
... (3) these transcripts contained information about at least one of the AM functions of the model (e.g., Lehdonvirta, 2018;Möhlmann et al., 2021;Rahman, 2021;Wood et al., 2019). The papers were coded with six codes corresponding to each AM function and thematic analysis was performed (Robinson, 2022). ...
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There is an increasing body of research on algorithmic management (AM), but the field lacks measurement tools to capture workers' experiences of this phenomenon. Based on existing literature, we developed and validated the algorithmic management questionnaire (AMQ) to measure the perceptions of workers regarding their level of exposure to AM. Across three samples (overall n = 1332 gig workers), we show the content, factorial, discriminant, convergent, and predictive validity of the scale. The final 20‐item scale assesses workers' perceived level of exposure to algorithmic: monitoring, goal setting, scheduling, performance rating, and compensation. These dimensions formed a higher order construct assessing overall exposure to algorithmic management, which was found to be, as expected, negatively related to the work characteristics of job autonomy and job complexity and, indirectly, to work engagement. Supplementary analyses revealed that perceptions of exposure to AM reflect the objective presence of AM dimensions beyond individual variations in exposure. Overall, the results suggest the suitability of the AMQ to assess workers' perceived exposure to algorithmic management, which paves the way for further research on the impacts of these rapidly accelerating systems.
Introduction Adolescent delinquency has been suggested to evolve from a normative motivation to establish independence and identity. However, few studies have examined this in detail, especially in young women. The aim was, therefore, to investigate identity formation in adolescent females with limited delinquency by focusing on identity status and identity processes in narratives about committing crimes and being convicted. Methods Interviews with 10 females, 15–18 years old, sentenced to youth service in three Swedish cities were conducted on Zoom. Results The results showed an equal distribution of all identity statuses within the group. Thematic analysis of their stories about crime and conviction showed that delinquency was described in terms of exploration and commitment, although commitment appeared more clearly. Social relations, in particular peers, played an important role in both committing as well as desisting from delinquency. In terms of narrative processes, the stories contained elements of agency, although diminishing of one's own capability and/or responsibility was common, and meaning making, mostly lesson learning, usually pertained to behaviors, interactional rules, or norms. Conclusion These findings point to the importance of viewing delinquency among young women in a social and developmental context, where delinquency may be a part of the process of identity formation. Interventions focusing on expressing needs of belonging as well as finding oneself in more adaptive ways are warranted, where supporting pro‐social relations and contexts is a suggested focus.
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There is a frequently cited epistemological link made in contemporary qualitative psychology between quantitative methods and positivism. In fact, quantitative methods are based on a pluralist hybrid of philosophies, none of which are positivist. This eclectic philosophical mix provides a more fertile soil for hybridisation with qualitative techniques within mixed methods research than is commonly appreciated.
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Narratives can be considered as a way for presenting and representing reality, going beyond time, space, aesthetic form, and medium of conveyance. From Aristotelian classical principles, to structuralist rules, to post-structuralist plurality, the aesthetics of narrative representation is constantly put into discussion. Narratives are composed by both constant structures and figures, which determines whether an object can be identified as a narrative, and variables which determine the way in which it is conveyed on different media. In this paper, we concentrate on contemporary narratives on social media. After declaring what are the main characteristics of the medium in terms of affordances, content, and role of the users, we analyse two existing case studies using the concepts of remediation and narrativity. The paper aims at bringing a contribution to the discussion about contemporary aesthetics in media design, considering narratives as a matter of design, and investigating on the role of the designer.
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This study explores the changing relationship in the digital era between celebrities and fans by examining a group of emerging celebrities and their followers on Twitter. Seven crime authors were chosen as a case sample, each of which published their first work after 2010 and might therefore be regarded as ‘social media natives’. The authors’ followers were categorised according to their self-descriptions into various professional and non-professional groups (e.g. ‘publishing industry professionals’, ‘fellow crime authors’). In some of these groups, notably ‘aspiring authors’ and ‘book fans/bloggers’, the performance of fandom was not always found to be uni-directional. Microanalysis of authors’ interactions with followers suggested that traditional media audience categories such as ‘fan’ have become looser in social media where all users are ‘followers’ and perform multiple identities. In particular, book bloggers seem to have carved out an important role as legitimising agents within the crime fiction field.
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This article sets out to establish the naturalistic study of online social communication as a substantive topic in social psychology and to discuss the challenges of developing methods for a formal analysis of the structural and interactional features of message threads on discussion forums. I begin by outlining the essential features of online communication and specifically discussion forum data, and the important ways in which they depart from spoken conversation. I describe the handful of attempts to devise systematic analytic techniques for adapting methods such as conversation and discourse analysis to the study of online discussion. I then present a case study of a thread from the popular UK parenting forum Mumsnet which presents a number of challenges for existing methods, and examine some of the interactive phenomena typical of forums. Finally, I consider ways in which membership categorization analysis and social identity theory can complement one another in the exploration of both group processes and the rhetorical deployment of identities as dynamic phenomena in online discussion.
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This paper introduces the work of the MOOD (Microanalysis Of Online Data) network, an interdisciplinary association of academic researchers exploring ways of conducting close qualitative analyses of online interaction. Despite the fact that much online interaction meets the criteria for ‘conversation’, conversation analysis (CA) has only recently begun to grow and flourish as a methodology for analysing the overwhelming quantity of material that in many cases sits in archive form, visible to millions, on the Internet. We discuss the development of methods that are inherently suited for subjecting online interaction to the kind of rigorous analysis that conversation analysts have applied to talk of all kinds for several decades. We go on to explore the fundamental challenges that online data pose for CA, the value of many CA techniques for online analysis, and the possibilities of developing bespoke modes of analysis that are crafted for use with specific forms of online data (e.g. ‘tweets’ on Twitter).
The MODI model is a dialectical way of comprehending the complementary relationship between science and spirituality. The model is founded on the notion that science and spirituality are domains of enquiry that both exemplify the values of modernity: open and embodied enquiry; the questioning of authority; and empowerment of the individual. The model captures the difference between science and spirituality by way of seven conceptual polarities: outer-inner; impersonal-personal; thinking-feeling; empirical-transcendental; mechanistic-purposive; verbal-ineffable; and explanation-contemplation. At the point where these dialectics overlap, the MODI model proposes an ‘interface space’ where science and spirituality overlap and combine. I further suggest that these seven polarities capture aspects of a fundamental ‘head-heart’ duality in human knowing, which is represented in a range of existing theories across philosophical, psychological and neurological levels. The model has predictive power and can help frame the growing interaction between science and spirituality that is a central feature of the contemporary world.
How does confiding secrets relate to well-being? The current work presents the first empirical examination of mechanisms by which confiding diverse real-world secrets to known others predicts well-being. We examined over 800 participants with more than 10,000 secrets in total, finding that confiding a secret does not predict reduced instances of concealment. Rather, confiding a secret predicts higher well-being through perceived coping efficacy. Correlational and experimental studies find that through confiding a secret, people feel they obtain social support and are more capable in coping with the secret. Additionally, through perceived coping efficacy, confiding a secret predicts less frequent mind wandering to the secret. Confiding predicts higher well-being through changing the way and how often people think about their secret.
Sharing the moment live, a built-in logic of many social networking sites, is, I claim, an invitation for creating plots, which has led to systematic practices. I single out taking a narrative stance on Facebook as such a practice and show the interplay between key-norms and evolving media affordances for pre-selection of story ingredients, localization, visualization of the experience, and audience selection. These contribute to showing the moment as opposed to telling it, with selected friends serving as knowing co-narrators and with story-linking allowing for allusive, transmedia links. I review these practices in the context of increased story facilities that notably bring together several social media apps. I argue that although this curation promises a move beyond the moment, it ultimately serves to consolidate sharing-lives-in-the-moment. I reflect on the implications of this for the direction of travel in relation to stories on many social media platforms.
In this article, I employ small stories research as a micro-perspective for the scrutiny of any crisis-related positionings of `Greece' and `the Greeks' that accompany the circulation of news stories from Greece in social media. My claim is that such positionings cannot be fully understood without reference to what stories get circulated, where, by whom, for/with whom and how. To substantiate this, I draw on a particular incident involving the assault of two female MPs by a male MP on a Greek TV breakfast show (June 2012). My analysis will show that the ways in which the Greek crisis is invoked or disregarded and erased in the social media transpositions of the incident are intimately linked with two key-narrative processes, which I call narrative stancetaking and resemiotizations (i.e. video-based or text-based) that involve a rescripting of the initial incident. In both cases, I will show how processes of story making are important for what is signalled as relevant and for how the context of the Greek crisis is made sense of, critiqued and ultimately backgrounded or erased in favour of more personalized and localized interpretations, grounded in the original and the transposed tales and tellings.