European Journal of Cultural Studies2015, Vol. 18(4-5) 395 –

European Journal of Cultural Studies
2015, Vol. 18(4-5) 395 –412
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DOI: 10.1177/1367549415577392
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e u r o p e a n j o u r n a l o f
Algorithmic culture
Ted Striphas
Indiana University, USA
Abstract
Over the last 30 years or so, human beings have been delegating
the work of culture
– the sorting, classifying and hierarchizing of people, places,
objects and ideas –
increasingly to computational processes. Such a shift
significantly alters how the
category culture has long been practiced, experienced and
understood, giving rise to
what, following Alexander Galloway, I am calling ‘algorithmic
culture’. The purpose
of this essay is to trace some of the conceptual conditions out of
which algorithmic
culture has emerged and, in doing so, to offer a preliminary

treatment on what it is.
In the vein of Raymond Williams’ Keywords, I single out three
terms whose bearing
on the meaning of the word culture seems to have been
unusually strong during the
period in question: information, crowd and algorithm. My claim
is that the offloading
of cultural work onto computers, databases and other types of
digital technologies
has prompted a reshuffling of some of the words most closely
associated with
culture, giving rise to new senses of the term that may be
experientially available
but have yet to be well named, documented or recorded. This
essay, though largely
historical, concludes by connecting the dots critically to the
present day. What is at
stake in algorithmic culture is the gradual abandonment of
culture’s publicness and
the emergence of a strange new breed of elite culture purporting
to be its opposite.
Keywords
Algorism, algorithm, algorithmic culture, big data, crowd,
culture, information,
keywords, Raymond Williams
Easter 2009 might well be remembered for Amazon.com’s
having outshined Jesus Christ.
That much was true on Twitter, at any rate, where, during that
long weekend in April, a
sudden influx of short missives about the online retailer
propelled it to the Number 1 spot
Corresponding author:
Ted Striphas, Department of Communication and Culture,

Indiana University, Classroom
Office Building, 800 E. 3rd Street, Indiana University,
Bloomington IN 47405, USA.
Email: [email protected]; Twitter: @striphas
577392ECS0010.1177/1367549415577392European Journal of
Cultural StudiesStriphas
research-article2015
Article
mailto:[email protected]
Twitter: @striphas
http://crossmark.crossref.org/dialog/?doi=10.1177%2F13675494
15577392&domain=pdf&date_stamp=2015-06-16
396 European Journal of Cultural Studies 18(4-5)
on Twitter’s trending topics list, unseating the Prince of Peace
along the way (James,
2009b). As the Beatles learned back in 1966, however, ‘more
popular than Jesus’ (as
John Lennon had claimed of the band) is not necessarily an
enviable position in which to
find oneself. The hashtag to which the Twitterati directed tens
of thousands of messages
– #AmazonFail – indicated that something had gone terribly
wrong with company. Why,
they wondered, had Amazon apparently begun excluding gay
and lesbian–themed books
from its sales rankings, searches and bestseller lists?
Author Mark R Probst first brought the issue to widespread
attention when, on Good
Friday, he noticed that several gay romance books had lost their

Amazon sales rankings,
including his own novel, The Filly. Hoping the matter was a
simple mistake, he wrote to
Amazon customer service. The agent who emailed Probst
explained that Amazon had a
policy of filtering ‘adult’ material out of most product listings.
Incensed, Probst (2009)
posted an account of the incident on his blog in the wee hours
of Easter Sunday morning,
pointing out inconsistencies in the retailer’s policy. The story
was subsequently picked
up by major news outlets, who traced incidences of gay and
lesbian titles disappearing
from Amazon’s main product list back to February 2009
(Lavallee, 2009; see also Kellog,
2009; Rich, 2009).
In a press release issued on Monday afternoon, a spokesperson
for Amazon attributed
the fiasco to ‘an embarrassing and ham-fisted cataloging error’.
More than 57,000 books
had been affected in all, including not only those with gay and
lesbian themes but also
titles appearing under the headings ‘Health, Mind, Body,
Reproductive and Sexual
Medicine, and Erotica’ (quoted in James, 2009a; see also Rich,
2009). An Amazon techni-
cian working in France reportedly altered the value of a single
database attribute – ‘adult’
– from false to true. The change then spread globally throughout
the retailer’s network of
online product catalogs, de-listing any books that had been
tagged with the corresponding
metadata (James, 2009b). This was not homophobia, Amazon
insisted, but a slip-up
resulting from human error amplified by the affordances of a

technical system.
In the wake of the controversy, author and lesbian, gay,
bisexual and transgender
(LGBT) activist Larry Kramer observed: ‘We have to now keep
a more diligent eye on
Amazon and how they handle the world’s cultural heritage’
(quoted in Rich, 2009).
Indeed, Amazon may have started as a retailer, but it has grown
into an exemplar of the
many ways human beings have been delegating the work of
culture – the sorting, clas-
sifying and hierarchizing of people, places, objects and ideas –
to data-intensive compu-
tational processes.1 Amazon’s back-end data infrastructure is so
vast, in fact, that in 2006
it began selling excess capacity to clients under the name
Amazon Web Services. It also
collects sensitive data about how people read through its Kindle
e-book devices – which
is to say nothing of how it profiles and then markets products to
customers based on their
browsing and purchasing patterns (Striphas, 2010). What one
sees in Amazon, and in its
kin Google, Facebook, Twitter, Netflix and many others, is the
enfolding of human
thought, conduct, organization and expression into the logic of
big data and large-scale
computation, a move that alters how the category culture has
long been practiced, expe-
rienced and understood. This is the phenomenon I am calling,
following Alexander R
Galloway (2006), ‘algorithmic culture’.2
The purpose of this essay is to trace one set of conditions out of
which a data-driven

algorithmic culture has developed and, in doing so, to offer a
preliminary sense of what
Striphas 397
‘it’ is. The overarching impulse here is historico-definitional,
though there are many ways
to execute such a project. One could focus on the propagation of
‘truthful’ statements (i.e.
discourses) pertaining to algorithmic culture (Foucault, 1972),
or map the sociological
circuitry through which the concept has made its way through
the world (Mannheim,
1955). Or instead, one could take an etymological tack in
attempting to trace the origins
of particular words, or adopt a philological thrust in trying to
apprehend definitive usages
of words in history.
While this essay combines elements of these approaches, it is
inspired primarily by
Raymond Williams’ (1983) work on keywords. This piece
emphasizes moments of cat-
achresis – instances of lexical ‘misuse’ that help concretize an
alternative semantics for
particular words and word clusters. These moments enable new
or at least different ways
of figuring reality through language, for example, in drawing
what was long taken to be
the conceptual sine qua non of qualitative human experience –
culture – into the orbit of
computational data processing (see, e.g. Kittler, 2006). It is a
contention of this essay that
the semantic dimensions of algorithmic culture (and also then of

the related phenomena
of big data, data mining and analytics, the themes of this special
issue of European
Journal of Cultural Studies) are at least as important as the
technological ones, the latter,
for perhaps obvious reasons, tending to command the spotlight.
But as Williams (1983)
noted, ‘some important social and historical processes occur
within language’, giving
rise to new existential territories that only later come to be
populated by technical arti-
facts (p. 22; see also Striphas, 2014).
Moreover, a keywords approach is useful in apprehending
latencies of sense and
meaning that persist, insist and subsist in contemporary usage
as ‘traces without … an
inventory’ (Gramsci, 1971: 324; see also Seigworth, 2000: 237).
Logging that inventory,
as it were, allows one to not only situate algorithmic culture
within a longer durée but
also reflect on claims to objectivity and egalitarianism that are
now made in its name.
Beyond semantics, what is at stake in algorithmic culture is the
gradual abandonment of
culture’s publicness and thus the emergence of a new breed of
elite culture purporting to
be its opposite.
Keywords today
Gary Hall (2002) opens the final section of Culture in Bits with
the line, ‘what if Richard
Hoggart had had email?’ (p. 126). This is tantamount to asking,
‘what would the work of
cultural studies’ canonical figures look like were it composed

today, a time of ubiquitous
digital computational technologies?’ Imagine, say, Raymond
Williams (1958) were writ-
ing Culture and Society having to confront the #AmazonFail
episode. How might he
make sense of the entwining of culture, which he posited as a
‘court of human appeal’
(Williams, 1958: viii), and computational decision-making (see
also Hallinan and
Striphas, 2014)?
Williams’ (1983) original project was to show how culture, once
a relatively obscure
word in English-language usage, became ‘one of the two or
three most complicated words’
by the start of the 20th century (p. 87). He did so by tracing
semantic shifts across a net-
work of terms, many of which formed the basis for his
compendium, Keywords (Williams,
1976, 1983). The introduction to Culture and Society offers a
more succinct version of the
story, focusing on five words whose history and interconnection
uniquely embodied ‘a
general change in our characteristic ways of thinking about our
common life’: industry,
democracy, class, art and culture (Williams, 1958: xiii). With
the first four, Williams estab-
lished a set of semantic coordinates, which he then used to chart
culture’s shifting meaning
and importance: from a pre-modern understanding grounded in
husbandry to a more capa-

cious, modern view – ‘a thing in itself’, encompassing not only
‘the general body of the
arts’ but also ‘a whole way of life, material, intellectual, and
spiritual’ (p. xvi).
Spanning the years 1780–1950, Culture and Society is
bookended by two major his-
torical events, namely, the industrial revolution and the end of
the Second World War.
The latter helped precipitate another great transformation
referred to variously as the
computer revolution, the communications revolution, the
cybernetics revolution and so
on (Beniger, 1986: 4–5). Prescient as he was, it is doubtful
Williams grasped the full
significance of his endpoint. More likely, he chose 1950
because the date marked mid-
century, the moment in which the symbolics of history and
futurity mingle more or less
freely. Still, one can see Williams (1958) grasping to
understand new technological con-
texts in his reflections on communication appearing in the
conclusion to Culture and
Society (pp. 296, 300–304, 313–319). It was not until the
publication of The Sociology of
Culture, however, that Williams (1981) broached the
relationship between culture, infor-
mation and digital technologies – but then only in passing, in
the work’s conclusion (pp.
231–232).3 He may not have been able to work out a fully
revised theory of culture per
se, but he managed to lay important groundwork for assessing
how the semantic – and
hence practical and experiential – coordinates of culture had
shifted since 1950.

We are still living in the midst of this shift, although the
nascent trends and tendencies
Williams tried to make sense of in the early 1980s are more
coherent today. The
#AmazonFail episode illustrates this point, underscoring the
degree to which shopping,
merchandizing and a host of other everyday cultural activities
are now data-driven activ-
ities subject to machine-based information processing (Striphas,
2009: 81–110). Indeed,
the incident would not have been intelligible, much less
possible, without a reshuffling
of the terms surrounding the word, culture. Those that Williams
(1958) identified in
Culture and Society remain important, to be sure, but in recent
decades a host of others
have emerged. An extended list might include analog,
application, cloud, code, control,
convergence, copy, data, design, digital, format, free, friend,
game, graph, hack, human,
identity, machine, message, mobile, network, noise, peer,
platform, protocol, search,
security, server, share, social, status, web and many more.4
Like Williams, however, I
want to single out a small group of terms whose semantic twists
and turns tell us some-
thing about senses and meanings of the word culture that are
available today, and also
then about the politics of big data, data mining and analytics.
Williams identified the first
one – information; the other two – crowd and algorithm – are
my own.5
Information
If culture’s usage is unusually ‘complicated’, then information’s

is equally contradictory.
John Durham Peters (1988) describes its etymology as ‘a history
full of inversions and
compromises’ (p. 10). Like a moody teenager, it swings from
specificity to generality,
and from the empirical to the abstract. Yet, this range is also
what makes information
Striphas 399
intriguing from the standpoint of algorithmic culture, which
channels an older sense of
the word that the Oxford English Dictionary or OED describes
as, ‘now rare’
(‘Information’, n., n.d.; see also Peters, 1988: 11; Gleick,
2011).
When information enters the English language sometime around
the 12th or 13th
century CE, chiefly from Latin, the tension at the heart of the
word is already becoming
manifest. At this early stage, it operates in two main semantic
registers: religion and law.
The use that the OED claims is ‘now rare’ is the religious one,
although it might be more
apt to describe it as spiritual, even deific. Here, information
denotes ‘the giving of form
or essential character to something; the act of imbuing with a
particular quality; anima-
tion’ (‘Information’, n., n.d.). This definition posits an
irreducible connection between
the shaping of something and the endowment with character,
substance or life.

Information’s juridical definition derives from the codes of
ancient Roman legal pro-
cedure. Broadly, it refers to ‘the imparting of incriminating
knowledge’, and more specifi-
cally, in US law, to ‘an accusation or criminal charge brought
before a judge without a
grand jury indictment’ (‘Information’, n., n.d.). Although
information here depends on
and passes among incarnate human agents, this definition
differs from the more recent
understanding, ‘knowledge communicated concerning some
particular fact, subject, or
event’ (‘Information’, n., n.d.). In the legal sense, one does not
refer to information per se
but to something narrower in scope – ‘an information’, or even
‘information’. The corre-
sponding verb form, ‘laying of information’, is a special type of
communication – a
speech act – whose outcome is to transform the innocent into
the accused and to set forth
social rituals intended to restore order in the wake of some
disturbance. Here the defini-
tion comes closest to the religious sense of character- or
quality-giving, although now the
information ‘source’ is secular interaction.
The influence of early modern empiricism and idealism on the
word information must
not be underestimated. The definition to which I referred in
passing, ‘knowledge com-
municated concerning some particular fact, subject, or event’, is
indicative of the term’s
encounter with these crosscurrents of early modern thought, for
it posits information not
as intrinsic quality or character but as extrinsic sense data. This
bit of semantic drift is

significant, underscoring how far the locus of information has
shifted from pre-modern
through early modern times and beyond. Although it continued
to refer to a kind of exis-
tential work, divine or worldly, gradually, a more object-
oriented definition sidelined this
sense of the word.
The passive voice construction ‘knowledge communicated’ is
important to dwell on,
moreover, because it indicates that information – now conceived
as a thing – always
emanates from some source external to one’s self. In the
framework of Immanuel Kant,
it belongs to the noumenon, or the realm of unmediated sense
data. This marks a signifi-
cant departure from the spiritual and legal definitions, both of
which locate information
in the body vis-a-vis its incarnations, godly or performative.
The object-oriented defini-
tion, on the other hand, inaugurates a process of abstracting
information from the body;
instead of being vested there, information becomes a separate
raw material that must be
given order vis-a-vis our cognitive faculties (‘Information’, n.,
n.d.).
The 20th century information theorist Norbert Wiener famously
quipped that the nat-
ural world consists of ‘a myriad of To Whom It May Concern
messages’ (quoted in
Rheingold, 1985: 113), drawing a line back to the work of his
early-modern forebears.

They similarly imagined a world bombarding us with sensory
input. This was a broken,
not a direct line, however, resulting in an even more diffuse
meaning for the word. If
information were akin to a ‘To Whom It May Concern
Message’, then it need not be
directed to anyone in particular. More to the point, in Wiener’s
formulation, it need not
be directed to anyone at all.
Apropos, the stars of Wiener’s two major books on cybernetics
and information are
neither the brain nor the cognitive structures that purportedl y
allow people to make our
way in the world. They are, instead, photoelectric cells and
antiaircraft guns, and more
utilitarian things like automatic door openers and thermostats
(Wiener, 1954, 1961). In
contrast to wind-up clocks and other simple mechanical devices,
which function in a
manner more or less unattuned to environmental conditions,
these machines ‘must be en
rapport with the world by sense organs’ and adjust their
behavior according to the infor-
mation they receive (Wiener, 1954: 33; see also pp. 21–22). In
1944, the physicist Erwin
Schrödinger (1967 [1944]) argued that life ‘feeds on negative
entropy’, meaning that life
is nothing more and nothing less than a small pocket of order
within a world abuzz with
information (p. 70). Four years later, Wiener told a similar story
but threw in a major plot
twist. If machines possessed an appetite for information, then
apparently information

was not particular to human beings.
From the Second World War on, then, machines begin being
seen not merely as useful
things but as custodians of orderliness. Critical to their work
was information, which
Gregory Bateson (2000 [1971]) defined as ‘a difference which
makes a difference’ (p.
315). Bateson, like Wiener, identified as a cyberneticist, so in
one sense it should not
surprise to find him defining information in terms of bits, or
simple yes–no decisions.
But in another sense, his definition may surprise. Bateson was a
trained anthropologist
and spouse of Margaret Mead, to whom he was married for 14
years. They had one child
together, Mary Catherine, who also became a noted
anthropologist. In a family so thick
with interest in people and culture, it is telling that Bateson
never bothered with the ques-
tion ‘to whom?’ when he called informatio n ‘a difference which
makes a difference’. By
the early 1970s, information was only residually the process by
which people and things
were endowed with substance, trait or character – in-formed, as
it were. It had become,
instead, a counter-anthropological leveler, smoothing over
longstanding differences
between humans and machines: Inform-uniform. James Gleick
(2011) puts the matter
succinctly: ‘it’s all one problem’ (p. 280).
In 1966, Michel Foucault concluded The Order of Things (1971
[1970]) by claiming
that ‘man is an invention of recent date … [a]nd one perhaps
nearing its end’ (p. 387).

Six years later, Gilles Deleuze and Félix Guattari (1983) opened
Anti-Oedipus by pro-
claiming that ‘everything is a machine’ – plant life, animal life,
mechanical devices,
electronic goods, economic activities, celestial bodies and more
(p. 2). Sandwiched
between them was Bateson, the an-anthropic anthropologist for
whom cultural life
becomes one type of information processing task among many.
One can also see emerg-
ing the sense of cultural objects, practices and preferences as
comprising a corpus of data
(from the Latin, ‘something given’), albeit data that exceed the
traditional view of the
human sciences in the agnosticism toward the intended
recipient. No longer would
human beings hold exclusive rights as cultural producers,
arbiters, curators or interpret-
ers – a welcome development, perhaps, given the shame,
disrespect and brutality elites
Striphas 401
have long exacted in the name of cultural difference. But what
if the apparent uniformity
between people and machines resulted in cultural practices and
decision-making that
were no better in-formed?
Crowd
The etymology of the word crowd is, like that of information, a
study in polarity reversal.
It entered the English language around the 15th century CE as

an adaptation of verbs
extant in Dutch, German and Frisian denoting pressuring or
pushing. The English verb
form ‘to crowd’ preserves this early meaning of the word,
although in some contexts the
element of physical force may be figurative rather than literal.
The OED mentions that
crowd was ‘comparatively rare down to 1600’, which means its
rise roughly coincides
with early modernity (‘Crowd’, n.d.). The noun form of the
word has often been used
interchangeably with mass, mob, multitude and throng to refer
to large gatherings of
people, generally in public, especially in urban settings.
Frequently, it denotes imped-
ance, inefficiency and frustration, as in the expressions
‘fighting the crowds’ and ‘three’s
a crowd’. It also conveys individual anonymity and engaged
inaction, as in the phrase, ‘a
crowd of onlookers’.6 For these reasons crowd has, until
recently, harbored almost exclu-
sively pejorative connotations.
Semantically, crowd comes fully into its own in the 19th
century, becoming a mainstay
of journalistic and scholarly attention.7 Charles Mackay’s
Extraordinary Popular Delusions
and the Madness of Crowds, first published in Britain in 1841,
is a key text in this regard.
The book chronicles incidents in which, as Mackay (2001
[1841]) puts it, ‘whole commu-
nities suddenly fix their minds upon one object, and go mad in
pursuit of it’ (p. ix). The list
ranges from stock bubbles to hairstyles, catch phrases, slow
poisoning, dueling, occult
practices and the mania for tulips in 17th century Holland. It is

a capacious book, yet one
that offers surprising little in the way of explicit insight into
crowds – at least beyond their
guilt by association with practices and events that, for Mackay,
evidenced the collective
abandonment of reason. Instead, he seems to play to the
conventional wisdom of the time:
‘Men, it has been well said, think in herds; it will be seen that
they go mad in herds, while
they only recover their senses slowly, and one by one’ (Mackay,
2001 [1841]: x).
But Mackay does not only play to the conventional wisdom – he
also plays upon it.
Preceding his statement about ‘thinking in herds’ is a passing
reference to an analogous
concept: the ‘popular mind’ (Mackay, 2001 [1841]: x).
Terminologically, it is a small
difference, but semantically it is a bait-and-switch. The verb
phrase ‘thinking in herds’
would seem to designate an active, living process, albeit one in
which any individual
contribution registers diffusely. The noun form ‘popular mind’
largely elides that pro-
cess, positing some overarching thing referring to everyone in
general and no one in
particular. And in this way, crowd’s etymology closely parallels
that of information,
which follows the term’s divestiture from the human body, its
transformation into an
immaterial object and its dispersal into the world.
This way of conceiving of crowds culminates in Gustave Le
Bon’s (2002 [1895]) The
Crowd: A Study of the Popular Mind. Le Bon offers something
like the explanatory

framework absent in Mackay. Le Bon’s book is occasioned by
‘the entry of the popular
classes into political life’, whom he paints a vicious, unthinking
horde: ‘History tells us
that from the moment when the moral forces on which a
civilisation rested have lost their
strength, its final dissolution is brought about by those
unconscious and brutal crowds
known, justifiably enough, as barbarians’ (Le Bon, 2002 [1895]:
xii–xiii; see also Arnold,
1993 [1869]).
Le Bon’s book has been read, understandably, as an attack on
crowds (see, for exam-
ple, Milgram and Toch, 2010; Surowiecki, 2004). It is one, to
be sure, and an elegy for
the decline of privileged minority rule akin to Edmund Burke’s
(1999 [1790]) Reflections
on the Revolution in France. Yet, there is a tone of resignation
evident in Le Bon’s prose,
suggesting a kind of begrudging acceptance of the emerging
political realities of the
time: ‘The age we are about to enter will in truth be the era of
crowds’, he states (Le
Bon, 2002 [1895]: x; emphasis in original). This may help to
explain why The Crowd
also contains a handful of passages in which Le Bon offers a
more equivocal view, such
as this one: ‘What, for instance, can be more complicated, more
logical, more marvelous
than a language? Yet whence can this admirably organised

production have arisen, except
it be the outcome of the unconscious genius of crowds’ (Le Bon,
2002 [1895]: v)?
Whether by default or by design, Le Bon was drawing on a
subterranean line of think-
ing about crowds. This line developed in the overlap of
Classical Liberalism and the
Scottish Enlightenment and received its most enduring
expression in the work of Adam
Smith. It was Smith (1977 [1776]) who, in An Inquiry into the
Causes of the Wealth of
Nations, struggled to make sense of apparently spontaneous
economic activities whose
outcome was – in Le Bon’s words – ‘admirably organised
production’. Yet, the figure of
the crowd is noticeably absent from Smith. In fact, the word
crowd appears only four
times in his 375,000 word magnum opus, and only then in verb
form. His figure is a dif-
ferent one, and of a different kind, although it performs
rhetorical work comparable to Le
Bon’s ‘genius’ crowd. This is the famous ‘invisible hand’,
which, in Smith’s (1977
[1776]) view, aligns the interests of individual economic actors
with the needs of a soci-
ety as a whole (p. 477).
Mysterious, ghostlike, the ‘invisible hand’ is essentiall y a deus
ex machina of eco-
nomic activity, and in this regard it is not too far removed from
the spiritual sense of
information mentioned earlier. In the 20th century, Friedrich A
Hayek would make the
link more explicit, helping to bolster the more affirmative view
of crowds nascent in both

Smith and Le Bon. The key work here is Hayek’s (2007 [1944])
Road to Serfdom, pub-
lished in 1944, arguably the strong state’s high-water mark in
both Europe and the United
States. Hayek believed there ought to be some force to which
was assigned the task of
holding the state in check; for him, that force was the economic
sphere. Hence, his desire
to strip the state of the responsibility of economic planning and
to leave the task of coor-
dinating economic activities up to individual actors dispersed
far and wide (Hayek, 2007
[1944]: 232). Instead of positing that coordination resulted from
the arcane workings of
an invisible hand, Hayek stressed the crucial role that
information – his word – played in
choreographing this intricate group dance, particularly through
the price system (Hayek,
2007 [1944]: 95).
Like Smith, Hayek had little to say about crowds per se. His
understanding of the indi-
vidual, however, harkened back to the earliest English-language
sense of crowd as the
exertion of force on others. And with this, he helped to usher
the idea of the intelligent,
constructive crowd more fully into view. He was not alone in
this endeavor. In 1965, the
Striphas 403
economist Mancur Olson (1971), a friend of Hayek, refuted the
claim that groups were
intrinsically stupid and irrational by describing the hidden

‘logic’ underlying collective
action.8 So, too, with sociologist Stanley Milgram, whose early
work on obedience to
authority was given subtlety and dimension in his later work on
crowds, where he disman-
tled the view that crowds caused otherwise mindful people to
become deluded (Milgram,
2010; Milgram and Toch, 2010). Finally, inasmuch as he was
Hayek’s ideological oppo-
site, we must nonetheless reckon with the contributions
Raymond Williams made to the
redemption of crowds. The conclusion to Culture and Society is
an extended critique of
the notion of masses-as-mob, culminating in the insight, ‘there
are in fact no masses; there
are only ways of seeing people as masses’ (Williams, 1958:
300). The alternatives
Williams proposes – ‘community’ or ‘common culture’ – bear
an uncanny resemblance to
the sense of crowd I have been tracing here: a ‘complex
organization, requiring continual
adjustment and redrawing’; denying the individual the
possibility of ‘full participation’,
while still granting her or him a modicum of effect or influence;
and incapable of being
‘fully conscious of itself’ (Williams, 1958: 333–334).
It is this set of positive connotations that crystallizes into
contemporary terms like
‘crowdsourcing’, ‘crowd wisdom’ and a host of cognates, all of
which have entered
popular usage over the last two decades or so: ‘hive mind’,
‘collective intelligence’,
‘smart mobs’, ‘group genius’ and more (see, for example,
Howe, 2008; Jenkins, 2006;
Kelly, 1995; Levy, 1999; Rheingold, 2002; Sawyer, 2007;

Shirky, 2008; Surowiecki,
2004; Tapscott and Williams, 2006). The translation between
then and now is hardly
perfect, owing to the diverse traditions out of which this vision
of crowds has emerged,
which is to say nothing of the technological transformations that
have occurred over the
last century. Indeed, when Williams (1958) wrote about the
‘solidarity’ necessary to sus-
tain a ‘common culture’ (pp. 332–338), could he have
anticipated the degree to which,
today, that solidarity would be forged computationally? And
what then to make of the
redemption of crowds, when proprietary computer platforms
have become the major
hubs for interaction online?9
Algorithm
Compared to information and crowd, algorithm is a less obvious
keyword by means of
which to make sense of culture today. If the former two terms
could be considered domi-
nant, or prevalent, as judged by their popular usage, then the
latter would best be
described as emergent, or restricted, though tending in the
direction of conventionality.
Yet, as James Gleick (2011) puts it in The Information, ‘[t]he
twentieth century gave
algorithms a central role’ (p. 206).10
Algorithm comes to modern English from Arabic by way of
Greek, medieval Latin,
Old French and Middle English. Historically, it has maintained
close ties to the Greek
word for number, arithmós (αριθμός), from which the English

form arithmetic is derived.
Algorithm’s most common contemporary meaning – a formal
process or set of step-by-
step procedures, often expressed mathematically – flows from
this connection, although
the OED insists it is a point of etymological ‘perversion’
(‘Algorism’, n., n.d.). In fact,
the word is a ‘mangled transliteration’ of the surname of a 9th
century mathematician,
Abū Jafar Muḥammad ibn Mūsā al-Khwārizmī, who lived much
of his life in Persia
(‘Algorithm’, n., n.d.). Algorithm is recorded in English for the
first time at the beginning
of the 13th century CE as augrim, in Chaucer’s Canterbury
Tales, whereupon it under-
goes a long series of orthographic transformations before
settling into what, from the
early 18th century until the early 20th century, becomes its
conventional spelling, algo-
rism (Karpinski, 1914: 708). The present-day rendering of the
word, algorithm, likewise
appears around the start of the 18th century, but it does not
become the standard orthog-
raphy until almost 1940.
The confusion stems mainly from two key mathematics texts
attributed to al-Khwārizmī
from which his name, and eventually two different though
related senses of the word
algorithm wind their way into English. The first manuscript, Al -
Kitāb al-Mukhtaṣar fī

ḥisāb al-jabr wa-al-Muqābala (The Compendious Book of
Calculation by Restoration
and Balancing), introduced many of the fundamental methods
and operations of algebra.
It is the primary work through which the word algebra itself,
adapted from the Arabic
al-jabr, diffused through Moorish Spain into the languages of
Western Europe (Crossley
and Henry, 1990: 106; Smith and Karpinski, 1911: 4–5; see also
Karpinski, 1915).
Incidentally, the word appearing just before al-jabr in the
Arabic version of the title,
ḥisāb, though translated as calculation, also denotes arithmetic.
Algorithm, arithmetic:
conceptually, they have been a stone’s throw away from one
another since the 9th cen-
tury. Consequently, it is hardly the case that one corrupted the
other. It is more accurate
to say that, until the second quarter of the 20th century, the
arithmetic sense of the word
algorithm was not dominant or preferred.
The other key work is al-Khwārizmī’s untitled text on Hindu- or
Indo-Arabic num-
bers, or what today many Westerners simply refer to as ‘Arabic’
numerals. It is widely
believed that this untitled manuscript of al-Khwārizmī’s played
a major part in introduc-
ing Europeans to Arabic numerals in the middle ages (Crossley
and Henry, 1990: 104).
Just as Al-Khwārizmī’s name became synonymous with
arithmetic through the algebra
book, so too did it become synonymous with the Arabic system
of numeration itself. The
form of the word algorithm that has today fallen out of favor,
algorism, is a legacy of this

association. Until the early 20th century, Arabic numerals were
commonly referred to as
‘the numbers of algorism’ (‘Algorism’, n., n.d.)
Still, this is not the only or most interesting sense of the term.
Algorism’s semantic
context includes a range of secondary meanings that are key to
making sense of algorith-
mic culture. Among the most important is its close association
with zero (Smith and
Karpinski, 1911: 58). The word zero comes from śūnya,
Sanskrit for ‘void’, which
migrates into Arabic as ṣifr, meaning ‘empty’, the root from
which the modern English
language form cypher derives (Smith and Karpinski, 1911: 56–
57). Thus, it is no coinci-
dence that the phrase ‘cypher in algorism’ was long used
interchangeably with the word
zero; sometimes cypher would be used to designate any of the
Arabic numerals, making
it synonymous with algorism (‘Algorism’, n., n.d., ‘Cipher,
Cypher’, n., n.d.). Moreover,
until the middle of the 19th century, cypher, like zero, could
refer to a placeholder – often
in a derogatory sense, indicating a ‘worthless’ person (‘Cipher,
Cypher’, n., n.d.). This
was alongside what has emerged today as cypher’s more
commonplace definition,
namely, a secret code or the key by means of which to crack it.
So, on the one hand, we have algorithms – a set of mathematical
procedures whose
purpose is to expose some truth or tendency about the world. On
the other hand, we have

Striphas 405
algorisms – coding systems that might reveal, but that are
equally if not more likely to
conceal. The one boasts of providing access to the real; the
other, like an understudy,
holds its place. Why in the early 20th century did algorithm
become preferred over algo-
rism, so much so that the latter form is now all but an archaism?
In a word, information. The touchstones in this regard are two
landmark papers, both
written by engineers who worked at Bell Laboratories in the
United States. The first,
Ralph Hartley’s ‘Transmission of Information’, appeared in
1928. The second, Claude E
Shannon’s ‘Mathematical Theory of Communication’, appeared
in 1948. Hartley’s paper
was noteworthy for many reasons, chiefly technical, but perhaps
his most audacious
move was to subsume communication under the rubric of
information. He states, ‘In any
given communication the sender mentally selects a particular
symbol … As the selec-
tions proceed more and more possible symbol sequences are
eliminated, and we say that
the information becomes more precise’ (Hartley, 1928: 536).
Hartley thus conceived of
communication as a procedural activity – a game of chance in
which the stake was infor-
mation, or the likelihood of achieving identity of message
within and across a specific
context of interaction. He was followed in his work by Shannon,
who raised the stakes
on Hartley’s theory.

One of the differences between Hartley and Shannon’s papers
was that Shannon
placed significantly less faith in the process of communication.
For Hartley, it was a rela-
tively placid affair in which the revelation of symbol s led to
understanding and order. For
Shannon, communication was a tumultuous affair consisting of
such a complex ensem-
ble of determinations, both past and present, that disorder was
the state to which it natu-
rally tended. Communication thus occurred within a context rife
with uncertainty, or in
the language of information theory, entropy; order could not be
taken for granted but
instead needed to be engineered. Shannon’s problem was thus to
figure out how to parse
signal and noise, and thereby increase the odds that the system
would achieve a sufficient
degree of order. Hence, he needed to devise a set of procedures
– an algorithm, if you
will, although he did not use the term specifically – capable of
dealing with the cascade
of determinations that governed communicative encounters.
Shannon may have believed
he was developing a ‘Mathematical Theory of Communication’,
but in fact he produced
among the first algorithmic theories of information.
It is worth mentioning that Shannon was not just a talented
electrical engineer, he was
also a world-class cryptographer, having worked on several
government-sponsored
‘secrecy’ projects at Bell Labs throughout the Second World
War. During that time, he
produced a lesser-known paper, originally classified, entitled ‘A

Mathematical Theory of
Cryptography’ (Shannon, 1945). Shannon operated, in other
words, at the junction point
of algorithms and algorisms. Or, as he described his work on
communication and cryp-
tography many years later, ‘they were so close together you
couldn’t separate them’
(quoted in Kahn, 1967: 744; see also Gleick, 2011: 216–218).
Indeed for Shannon, com-
munication in the ordinary sense of the term was nothing other
than a special, simpler
case of cryptography, or of ciphering and deciphering. Both in
his view consisted of
signals and noise stuck in a dizzying, entropic dance, along with
telling redundancies
that, if exploited using the right mathematics, could mitigate
much of the turmoil and
thereby point the way toward order (Rheingold, 1985: 119).
What Shannon was essen-
tially proposing in his work, then, was the use of algorithms to
attenuate algorisms.
Conclusion
I have tried my best to connect as many of the dots between the
words information,
crowd and algorithm as possible. I realize, of course, that there
are a great many dots left
to be connected – something that is inevitable in a synoptic
piece such as this, which
marshals a version of what Franco Moretti (2005) has called a
method of ‘distant read-

ing’ (p. 1). I am well aware of the prejudices of this research,
moreover, particularly the
privileging of the work and experiences mostly of White men of
European descent. The
purpose in doing so is not to exalt them. Instead, I am trying to
tell a story about word-
worlds or ‘universes of reference’ they helped call into being by
using specific terms
unconventionally (Guattari, 1995: 9). Having said that, I want
to say a few more words
about how the conceptual history I have presented here connects
up with culture, and
also then big data, data mining and analytics.
Matthew Arnold’s (1993 [1869]) Culture and Anarchy is
infamous for having defined
culture in elite terms, as ‘the best which has been thought and
said’ (p. 190). Elsewhere
in the book Arnold refers to culture as ‘sweetness and light’,
thereby defining a model
disposition for the small group of apostles whom he imagined
would, like him, spread
the gospel of culture. Yet, there is a third sense of culture
present in the book which,
while hardly overlooked, is overshadowed by these two more
quotable definitions. He
refers to culture as ‘a principle of authority, to counteract the
tendency to anarchy which
seems to be threatening us’ (Arnold, 1993 [1869]: 89). For
Arnold, culture as authorita-
tive principle meant a selective tradition of national –
specifically English – art and lit-
erature that would, in his view, create a basis for national unity
and moral uplift at a time
when heightening class antagonism was threatening English
society.

This latter definition – culture as authoritative principle – is the
one that is chiefly
operative in and around algorithmic culture. Today, however, it
is not culture per se that is
a ‘principle of authority’ but increasingly the algorithms to
which are delegated the task of
driving out entropy, or in Arnold’s language, ‘anarchy’. You
might even say that culture is
fast becoming – in domains ranging from retail to rental, search
to social networking, and
well beyond – the positive remainder resulting from specific
information processing tasks,
especially as they relate to the informatics of crowds. And in
this sense, algorithms have
significantly taken on what, at least since Arnold, has been one
of culture’s chief respon-
sibilities, namely, the task of ‘reassembling the social’, as
Bruno Latour (2005) puts it –
here, though, using an array of analytical tools to discover
statistical correlations within
sprawling corpuses of data, correlations that would appear to
unite otherwise disparate
and dispersed aggregates of people (see, e.g., Hallinan and
Striphas, 2014).
I suggested at the outset of this article and at points along the
way that part of what is
at stake in algorithmic culture is the privatization of process:
that is, the forms of decision-
making and contestation that comprise the ongoing struggle to
determine the values, prac-
tices and artifacts – the culture, as it were – of specific social
groups. Tarleton Gillespie
(2011) has explored this issue in relationship to Twitter’s
trending topics, noting how the

company’s black box approach creates all sorts of
mystifications about how it adduces
topical importance. ‘The interesting question is not whether
Twitter is censoring its Trends
list’, he writes. ‘The interesting question is, what do we think
the Trends list is … that we
can presume to hold it accountable when we think it is “wrong”’
(Gillespie, 2011). His
Striphas 407
point is that Twitter and its kin bandy about in what one might
call the algorithmic real,
where placeholders for trending topics and the like are
presented as if they were faithful
renderings of reality. But the issue is even more complex than
this. Gillespie (2011) adds
that ‘[w]e don’t have a sufficient vocabulary for assessing the
algorithmic intervention in
a tool like Trends’, an observation that underscores just how
deeply entangled are ques-
tions of language, technology, big data, analytics and political
economy. This is all the
more reason to broach the issue of the privatization of cultural
decision-making only after
having explored the semantic context, or keywords, that frame
the issue in the first place.
In brief, consider the product recommendations one sees on
Amazon. These, says the
retailer, are the result of one’s browsing and purchasing
histories, which are correlated
with those of Amazon’s millions of other customers – a crowd –
to determine whose buy-

ing patterns are similar to one’s own. You, too, might like what
this select group has
bought, and vice-versa – a process Amazon calls, ‘collaborative
filtering’. Google report-
edly works in a similar way. Although the company has moved
far beyond its original
‘PageRank’ algorithm, which measured the number of links
incoming to a website to
determine its relative importance, it still leverages crowd
wisdom to determine what is
significant on the web. As Wired magazine explained in 2010,
PageRank has been celebrated as instituting a measure of
populism into search engines: the
democracy of millions of people deciding what to link to on the
Web. But Google’s engineers
… are exploiting another democracy – the hundreds of millions
who search on Google, using
this huge mass of collected data to bolster its algorithm. (Levy,
2010: 99–100)
All this makes algorithmic culture sound as if it were the
ultimate achievement of
democratic public culture. Now anyone with an Internet
connection gets to have a role in
determining ‘the best that has been thought and said’! I am
tempted to follow here by
saying, ‘much to the chagrin of Matthew Arnold’, but I am not
convinced that algorith-
mic culture is all that far removed – in spirit, if not execution –
from a kind of Arnoldian
project. Despite the populist rhetoric, I believe we are returning
to something like his
apostolic vision for culture. The Wired magazine story from
which I just quoted also says
this: ‘You may think [Google’s] algorithm is little more than a

search engine, but wait
until you get under the hood and see what this baby can do’
(Levy, 2010: 98). The prob-
lem is, thanks to trade secret law, nondisclosure agreements and
noncompete clauses,
virtually none of us will ever know what is ‘under the hood’ at
Amazon, Google,
Facebook or any number of other leading tech firms. As
Gillespie (2007) is fond of say-
ing, you cannot look under a hood that has been ‘welded shut’
(p. 222).
All this harkens back to the oldest sense of information – where
some mysterious
entity is responsible for imbuing people and objects with shape,
quality or character. I do
not mean to downplay the role that crowds play in generating
raw data. Yet, it seems to
me that ‘crowd wisdom’ is largely just a stand-in – a
placeholder, an algorism – for algo-
rithmic data processing, which is increasingly becoming a
private, exclusive and indeed
profitable affair. This is why, in our time, I believe that
algorithms are becoming deci-
sive, and why companies like Amazon, Google and Facebook
are fast becoming, despite
their populist rhetoric, the new apostles of culture.
Funding
This research received no specific grant from any funding
agency in the public, commercial or

not-for-profit sectors.
Notes
1. This is not to suggest algorithmic culture is somehow strictly
computational and therefore
exclusive of human beings. As Tarleton Gillespie (2014) has
noted, and as the preceding
example suggests, algorithms are best conceived as ‘socio-
technical assemblages’ joining
together the human and the nonhuman, the cultural and the
computational. Having said that,
a key stake in algorithmic culture is the automation of cultural
decision-making processes,
taking the latter significantly out of people’s hands (Flusser,
2011: 117).
2. Galloway does not offer a specific definition of ‘algorithmic
culture’, nor does he provide any
type of genealogy for the term. His having largely taken this
suggestive idea for granted is a
primary motivation for this essay.
3. Outside the United States, the book is simply titled, Culture.
4. Several of these terms appear in Fuller (2008), although the
project does not adhere closely
to a Williamsonian keywords approach. The Williams-inspired
New Keywords (Bennett
et al., 2005) contains only a handful of them. Ben Peters’ (ed.)
forthcoming Digital Keywords
project is the most compelling project to have developed in this
vein to date (Welcome, n.d.;
see also Striphas, 2014).
5. Beyond Williams’ passing interest in information, I can offer

no strong empirical basis for the
selection of these terms beyond my own intuition, or a desire to
engage in a thought experiment
that would attempt to see what new understandings of culture
might emerge from having placed
the word alongside information, crowd and algorithm. That sai d,
one should not dismiss ‘intui-
tive’ methods as lacking in scholarly rigor. Henri Bergson
(1992), for one, pioneered the project
of recovering intuition from the Kantian doctrine of the
faculties, seeing it as a way of relating
to the world that was less categorical and therefore better
attuned to duration (pp. 126–129).
More recently, Lauren Berlant (2011) has made a strong case
for the relationship of intuition,
the somatic and the affective (pp. 52–53). Gregory J Seigworth
(2006) also gets at the point in
arguing for the relationship between intuition and what
Williams has called the ‘pre-emergent’,
which is to say a category of experience exceeding the realm of
the visible and the articulable.
It is also not a coincidence that Seigworth draws attention to the
etymological links between the
words experience, experiment and empiricism (Seigworth, 2006:
107–126; Williams, 1977: 132).
6. The exception here would be the word’s usage in the phrase
‘the usual crowd’, which indi-
cates familiarity with those who have assembled.
7. Williams (1983) notes that, prior to this time, the word
multitude tended to predominate in
English. It is the 18th and 19th centuries that see the rise of
mass and, evidently, crowd as well
(p. 192).

8. On Olson’s friendship with Hayek, see p. viii.
9. For a critique of the politics of platforms, see Gillespie,
2010.
10. Although hardly a prevalent term in the English language,
the word algorithm’s usage shows
a dramatic upsurge from about 1960 on. Before that year, it
barely registered, but between
1970 and 2000 its usage increased by about 350 percent,
approaching levels comparable to
crowd (‘Algorithm’, n.d.).
References
‘Algorism’, n. (n.d.) OED Online. Oxford University Press.
Available at: http://www.oed.com
(accessed 18 October 2010).
http://www.oed.com
Striphas 409
‘Algorithm’, n. (n.d.) Dictionary.com. Available at:
http://dictionary.reference.com/browse/
algorithm?s=t (accessed 8 February 2011).
‘Algorithm’ (n.d.) Google Books Ngram Viewer. Available at:
https://books.google.com/ngrams/
graph?content=algorithm&year_start=1800&year_end=2000&co
rpus=15&smoothing=3&
share=&direct_url=t1%3B%2Calgorithm%3B%2Cc0 (accessed 5
May 2014).
Arnold M (1993 [1869]) Culture and Anarchy and Other
Writings (ed S Collini). Cambridge; New

York: Cambridge University Press.
Bateson G (2000 [1971]) Steps to an Ecology of Mind:
Collected Essays in Anthropology,
Psychiatry, Evolution, and Epistemology. Chicago, IL:
University of Chicago Press.
Beniger JR (1986) The Control Revolution: Technological and
Economic Origins of the
Information Society. Cambridge, MA: Harvard University Press.
Bennett T, Grossberg L and Morris M (eds) (2005) New
Keywords: A Revised Vocabulary of
Culture and Society. Malden, MA: Blackwell Publishing.
Bergson H (1992) The Creative Mind: An Introduction to
Metaphysics (trans. M Andison). New
York: Citadel Press.
Berlant L (2011) Cruel Optimism. Durham, NC: Duke
University Press.
Burke E (1999 [1790]) Reflections on the Revolution in France
(ed LG Mitchell). Oxford; New
York: Oxford University Press.
‘Cipher, Cypher’, n. (n.d.) OED Online. Oxford University
Press. Available at: http://www.oed.
com (accessed 18 October 2010).
Crossley JN and Henry AS (1990) Thus spake al-Khwārizmī: A
Translation of the Text of
Cambridge University Library Ms. Ii.vi.5. Historia Mathematica
17(2): 103–131.
‘Crowd’ (n.d.) Google Books Ngram Viewer. Available at:
https://books.google.com/ngrams/

graph?content=crowd&year_start=1800&year_end=2000&corpu
s=15&smoothing=3&share
=&direct_url=t1%3B%2Ccrowd%3B%2Cc0 (accessed 5 May
2014).
Deleuze G and Guattari F (1983) Anti-Oedipus: Capitalism and
Schizophrenia (trans. R Hurley, M
Seem and HR Lane). Minneapolis, MN: University of Minnesota
Press.
Flusser V (2011) Into the Universe of Technical Images (trans.
NA Roth). Minneapolis, MN:
University of Minnesota Press.
Foucault M (1971 [1970]) The Order of Things: An
Archaeology of the Human Sciences. New
York: Vintage Books.
Foucault M (1972) The Archaeology of Knowledge (trans. AM
Sheridan). New York: Pantheon
Books.
Fuller M (ed.) (2008) Software Studies: A Lexicon. Cambridge,
MA: The MIT Press.
Galloway AR (2006) Gaming: Essays on Algorithmic Culture.
Minneapolis, MN: University of
Minnesota Press.
Gillespie T (2007) Wired Shut: Copyright and the Shape of
Digital Culture. Cambridge, MA: The
MIT Press.
Gillespie T (2010) The politics of ‘platforms’. New Media &
Society 12(3): 347–364.
Gillespie T (2011) Our misplaced faith in Twitter Trends.

Salon. Available at: http://www.salon.
com/2011/10/19/our_misplaced_faith_in_twitter_trends/
(accessed 12 May 2014).
Gillespie T (2014) Algorithm (Digital Keywords). Available at:
http://culturedigitally.org/2014/06/
algorithm-draft-digitalkeyword/ (accessed 6 November 2014).
Gleick J (2011) The Information: A History, A Theory, A
Flood. New York: Pantheon Books.
Gramsci A (1971) Selections from the Prison Notebooks.
Reprint ed. (eds Q Hoare and GN Smith).
New York: International Publishers Co.
Guattari F (1995) Chaosmosis: An Ethico-Aesthetic Paradigm.
Bloomington, IL: Indiana
University Press.
Hall G (2002) Culture in Bits: The Monstrous Future of Theory.
London; New York: Continuum.
http://dictionary.reference.com/browse/algorithm?s=t
http://dictionary.reference.com/browse/algorithm?s=t
https://books.google.com/ngrams/graph?content=algorithm&yea
r_start=1800&year_end=2000&corpus=15&smoothing=3&share
=&direct_url=t1%3B%2Calgorithm%3B%2Cc0
http://www.oed.com
http://www.oed.com
https://books.google.com/ngrams/graph?content=crowd&year_st
art=1800&year_end=2000&corpus=15&smoothing=3&share=&d

irect_url=t1%3B%2Ccrowd%3B%2Cc0
art=1800&year_end=2000&corpus=15&smoothing=3&shar e=&d
art=1800&year_end=2000&corpus=15&smoothing=3&share=&d
http://www.salon.com/2011/10/19/our_misplaced_faith_in_twitt
er_trends/
http://www.salon.com/2011/10/19/our_misplaced_faith_in_twitt
er_trends/
http://culturedigitally.org/2014/06/algorithm-draft-
digitalkeyword/
http://culturedigitally.org/2014/06/algorithm-draft-
digitalkeyword/
Hallinan B and Striphas T (2014) Recommend for you: The
Netflix Prize and the production
of algorithmic culture. New Media & Society. Epub ahead of
print 23 June 2014. DOI:
10.1177/1461444814538646.
Hartley RVL (1928) Transmission of Information. Bell System
Technical Journal 7(3): 535–563.
Hayek FA (2007 [1944]) The Road to Serfdom: Text and
Documents – Definitive Edition (ed
Caldwell B). Chicago, IL: University Of Chicago Press.
Howe J (2008) Crowdsourcing: Why the Power of the Crowd Is
Driving the Future of Business
(1st edn). New York: Crown Business.
‘Information’, n. (n.d.) OED Online. Oxford University Press.

Available at: http://www.oed.com
James A (2009a) Amazon calls mistake ‘embarrassing and ham-
fisted’. In: Seattle Post
Intelligencer Blog. Available at:
http://blog.seattlepi.com/amazon/2009/04/13/amazon-calls-
mistake-embarrassing-and-ham-fisted/ (accessed 25 October
2010).
James A (2009b) AmazonFail: An inside look at what happened.
Seattle Post Intelligencer Blog.
Available at:
http://blog.seattlepi.com/amazon/2009/04/13/amazonfail -an-
inside-look-at-
what-happened/ (accessed 25 October 2010).
Jenkins H (2006) Convergence Culture: Where Old and New
Media Collide. New York: New
York University Press.
Kahn D (1967) The Codebreakers: The Story of Secret Writing.
New York: The Macmillan
Company.
Karpinski LC (1914) The algorism of John Killingworth.
English Historical Review 29(116):
707–717.
Karpinski LC (1915) Introduction. In: Karpinski LC (ed.)
Robert of Chester’s Latin Translation of
the Algebra of Al-Khowarizmi. New York: The Macmillan
Company.
Kellog C (2009) Amazon de-ranks so-called adult books,

including National Book Award win-
ner. In: LA Times Blogs – Jacket Copy. Available at:
http://latimesblogs.latimes.com/jacket-
copy/2009/04/amazon-deranks-gayfriendly-books-the-
twitterverse-notices.html (accessed 25
October 2010).
Kelly K (1995) Out of Control: The New Biology of Machines,
Social Systems, & the Economic
World. Reading, MA: Basic Books.
Kittler F (2006) Thinking colour and/or machines. Theory,
Culture, & Society 23(7–8): 39–50.
Latour B (2005) Reassembling the Social: An Introduction to
Actor-Network Theory. Oxford; New
York: Oxford University Press.
Lavallee A (2009) Blogs and Twitter coin ‘AmazonFail’. Wall
Street Journal – Digits. Available
at: http://blogs.wsj.com/digits/2009/04/13/blogs-and-twitter-
coin-amazonfail/ (accessed 25
October 2010).
Le Bon G (2002 [1895]) The Crowd: A Study of the Popular
Mind (Reprint edition). Mineola, NY:
Dover Publications.
Levy P (1999) Collective Intelligence: Mankind’s Emerging
World in Cyberspace (trans. R
Bononno). Cambridge, MA: Basic Books.
Levy S (2010) How Google’s algorithm rules the web. Wired.
Available at: http://www.wired.
com/magazine/2010/02/ff_google_algorithm/ (accessed 17
September 2012).

Mackay C (2001 [1841]) Extraordinary Popular Delusions: And
the Madness of Crowds. Amherst,
NY: Prometheus Books.
Mannheim K (1955) Ideology and Utopia: An Introduction to
the Sociology of Knowledge (Reprint
edn). San Diego, CA: Harcourt.
Milgram S (2010) Some conditions on obedience and
disobedience to authority (3rd edn). In: Blass
T (ed.) The Individual in a Social World: Essays and
Experiments. London: Pinter & Martin
Ltd, pp.128–150.
http://www.oed.com
mistake-embarrassing-and-ham-fisted/
mistake-embarrassing-and-ham-fisted/
http://blog.seattlepi.com/amazon/2009/04/13/amazonfail-an-
inside-look-at-what-happened/
http://blog.seattlepi.com/amazon/2009/04/13/amazonfail -an-
inside-look-at-what-happened/
http://latimesblogs.latimes.com/jacketcopy/2009/04/amazon-
deranks-gayfriendly-books-the-twitterverse-notices.html
http://latimesblogs.latimes.com/jacketcopy/2009/04/amazon-
deranks-gayfriendly-books-the-twitterverse-notices.html
http://blogs.wsj.com/digits/2009/04/13/blogs-and-twitter-coin-
amazonfail/
http://www.wired.com/magazine/2010/02/ff_google_algorithm/
http://www.wired.com/magazine/2010/02/ff_google_algorithm/
Striphas 411

Milgram S and Toch H (2010) Crowds. In: Blass T (ed.) The
Individual in a Social World: Essays
and Experiments (3rd edn). London: Pinter & Martin Ltd,
pp.237–305.
Moretti F (2005) Graphs, Maps, Trees: Abstract Models for a
Literary History. London; New
York: Verso.
Olson M (1971) The Logic of Collective Action: Public Goods
and the Theory of Groups (Revised
edn). Cambridge, MA: Harvard University Press.
Peters JD (1988) Information: Notes toward a critical history.
Journal of Communication Inquiry
12(2): 9–23.
Probst M (2009) Ramblings from a Literature Lover and
Sometimes Writer. Amazon Follies.
Available at: http://markprobst.livejournal.com/15293.html
Rheingold H (1985) Tools for Thought: The History and Future
of Mind-Expanding Technology.
Cambridge, MA: The MIT Press.
Rheingold H (2002) Smart Mobs: The Next Social Revolution.
Cambridge, MA: Basic Books.
Rich M (2009) Amazon says error removed listings. The New
York Times, 14 April. Available
at:
http://www.nytimes.com/2009/04/14/technology/internet/14ama
zon.html (accessed 25
October 2010).

Sawyer K (2007) Group Genius: The Creative Power of
Collaboration. New York: Basic Books.
Schrödinger E (1967 [1944]) What is Life? The Physical Aspect
of the Living Cell. Cambridge;
New York: Cambridge University Press.
Seigworth G (2000) Banality for cultural studies. Cultural
Studies 14(2): 227–268.
Seigworth G (2006) Cultural studies and Gilles Deleuze. In:
Birchall C and Hall G (eds) New
Cultural Studies: Adventures in Theory. Athens: University of
Georgia Press, pp.107–126.
Shannon C (1945) A Mathematical Theory of Cryptography.
Murray Hill, NJ: Bell Labs. Available
at: http://www.cs.bell-
labs.com/who/dmr/pdfs/shannoncryptshrt.pdf (accessed 27 June
2014).
Shirky C (2008) Here Comes Everybody: The Power of
Organizing Without Organizations. New
York: Penguin Press.
Smith A (1977 [1776]) An Inquiry into the Nature and Causes
of the Wealth of Nations (ed E Cannan).
Chicago, IL: University of Chicago Press.
Smith DE and Karpinski LC (1911) The Hindu-Arabic
Numerals. Boston, MA; London: Ginn and
Co.
Striphas T (2009) The Late Age of Print: Everyday Book
Culture from Consumerism to Control.
New York: Columbia University Press.
Striphas T (2010) The abuses of literacy: Amazon Kindle and

the right to read. Communication
and Critical/Cultural Studies 7(3): 297–317.
Striphas T (2014) The Internet of words. The Chronicle of
Higher Education. Available at: http://
chronicle.com/article/The-Internet-of-Words/148179/ (accessed
15 August 2014).
Surowiecki J (2004) The Wisdom of Crowds: Why the Many
Are Smarter Than the Few and
How Collective Wisdom Shapes Business, Economies, Societies
and Nations. New York:
Doubleday.
Tapscott D and Williams AD (2006) Wikinomics: How Mass
Collaboration Changes Everything.
New York: Portfolio Hardcover.
Welcome (n.d.) Digital Keywords: A Scholarly Workshop at the
University of Tulsa. Available at:
http://orgs.utulsa.edu/dkw/ (accessed 5 May 2014).
Wiener N (1954) The Human Use of Human Beings:
Cybernetics and Society (Revised edn).
Cambridge, MA: Da Capo Press.
Wiener N (1961) Cybernetics or, Control and Communication in
the Animal and the Machine.
New York: The MIT Press.
Williams R (1958) Culture and Society, 1780–1950. New York:
Columbia University Press.
http://markprobst.livejournal.com/15293.html
http://www.nytimes.com/2009/04/14/technology/internet/14ama

zon.html
http://www.cs.bell-labs.com/who/dmr/pdfs/shannoncryptshrt.pdf
http://chronicle.com/article/The-Internet-of-Words/148179/
http://chronicle.com/article/The-Internet-of-Words/148179/
http://orgs.utulsa.edu/dkw/
Williams R (1976) Keywords: A Vocabulary of Culture and
Society (1st edn). New York: Oxford
University Press.
Williams R (1977) Marxism and Literature. Oxford: Oxford
University Press (English).
Williams R (1981) The Sociology of Culture. Chicago, IL:
University of Chicago Press.
Williams R (1983) Keywords: A Vocabulary of Culture and
Society (Revised edn). New York:
Oxford University Press.
Biographical note
Ted Striphas is Associate Professor in the Department of
Communication and Culture, Indiana
University, USA. He is the author of The Late Age of Print:
Everyday Book Culture from
Consumerism to Control (Columbia University Press, 2009) and
is currently at work on his next
book, Algorithmic Culture. Twitter: @striphas.

An Investigation into the Feasibility of Intensive Cognitive
Behavioural Therapy
A thesis submitted to The University of Manchester for the
degree of Doctor of Clinical Psychology
in the Faculty of Biology, Medicine and Health
2019
Lauren Hampson
School of Health Sciences
Division of Psychology and Mental Health

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2
Table of Contents
Figures and Tables
...............................................................................................
..... 5
Table of Appendices
...............................................................................................
.. 6
Word Counts
...............................................................................................
.............. 8
Overall Abstract
...............................................................................................
........ 9
Declaration
...............................................................................................
.............. 10

Copyright Statement
...............................................................................................
10
Acknowledgments
...............................................................................................
... 11
Dedication
...............................................................................................
............... 12
Introduction to Paper I
........................................................................................ 13
Paper I Systematic Review
.................................................................................. 14
1. Abstract
...............................................................................................
............... 15
2. Introduction
...............................................................................................
......... 16
2.1 Mental Health and Psychological Distress
....................................................... 16
2.2 Cognitive Behavioural Therapy
....................................................................... 17

2.3 Components of Cognitive Behavioural Therapy
.............................................. 18
2.4 Clinical Guidelines for Delivery of CBT
......................................................... 19
2.5 Intensive CBT
...............................................................................................
.... 21
2.6 Review Aims
...............................................................................................
..... 22
3. Method
...............................................................................................
................. 23
3.1 Review Protocol
...............................................................................................
23
3.2 Search strategy
...............................................................................................
.. 23
3.3 Inclusion Criteria
..............................................................................................
25
3.4 Quality Assessment
.......................................................................................... 25
3.5 Analysis of Studies
...........................................................................................
26

4. Results
...............................................................................................
................. 28
4.1 Description of Papers
....................................................................................... 28
4.2 Quality of Studies
.............................................................................................
34
4.3 Participants
...............................................................................................
........ 36
4.4 Characteristics of Intensive CBT
..................................................................... 36
4.5 Effects of Intensive CBT
.................................................................................. 37
4.6 Long Term Follow Up
...................................................................................... 43
4.7 Acceptability
...............................................................................................
..... 43
3
5. Discussion
...............................................................................................

........... 45
5.1 Summary of Evidence
...................................................................................... 45
5.2 Strengths and Limitations
................................................................................. 48
5.3 Clinical Implications and Future Directions
.................................................... 50
5.4 Conclusions
...............................................................................................
....... 52
6. References
...............................................................................................
........... 53
Introduction to Paper II
....................................................................................... 62
Paper II Research Study
...................................................................................... 63
1. Abstract
...............................................................................................
............... 64
2. Introduction
...............................................................................................
......... 65

3. Method
...............................................................................................
................. 69
3.1 Study Design
...............................................................................................
..... 69
3.2 Participant Sample
............................................................................................
69
3.3 Inclusion Criteria
..............................................................................................
69
3.4 Recruitment
...............................................................................................
....... 70
3.5 Procedure
...............................................................................................
........... 72
3.6 Measures
...............................................................................................
............ 72
3.7 Intervention
...............................................................................................
....... 75
3.8 Data Analysis
...............................................................................................
.... 77

3.9 Ethical Approval
...............................................................................................
78
4. Results
...............................................................................................
................. 80
4.1 Demographic and Clinical Characteristics
....................................................... 80
4.2 Feasibility Outcome Measures (Hypothesis One)
............................................ 80
4.3 Clinical Outcome Measures (Hypothesis Two)
............................................... 84
5. Discussion
...............................................................................................
........... 87
5.1 Acceptability and Feasibility
............................................................................ 87
5.2 Clinical Outcome
..............................................................................................
90
5.3 Strengths and Limitations
................................................................................. 92
5.4 Further Clinical and Research Considerations
................................................. 93
6. References

...............................................................................................
........... 95
4
Introduction to Paper III
................................................................................... 102
Paper 3: Critical Reflection Paper
.................................................................... 103
Overview
...............................................................................................
................. 104
1. Paper I: Systematic Review
.............................................................................. 105
1.1 Rationale for the Review
................................................................................ 105
1.2 Scoping and Database
Searching.................................................................... 106
1.3 Quality Appraisal
...........................................................................................
107

1.4 Synthesising Results
....................................................................................... 108
1.5 Limitations
...............................................................................................
....... 108
1.6 Clinical Implications and Future Directions
.................................................. 109
1.7 Conclusions
...............................................................................................
..... 110
2. Paper II: Empirical Study
................................................................................. 111
2.1 Study Aims and Rationale
.............................................................................. 111
2.2 Development Stage
.........................................................................................
111
2.3 Recruitment Considerations
........................................................................... 112
2.4 Conducting Research in Prison
...................................................................... 114
2.5 The Role of Clinical Psychology in Prison
.................................................... 117
2.6 Delivering Psychological Intervention in Prison
............................................ 118

2.7 System-level Considerations
.......................................................................... 120
2.8 Final Considerations
....................................................................................... 121
3. References
...............................................................................................
......... 123
Appendices
...............................................................................................
........... 128
1. Paper I: Systematic Review
.............................................................................. 128
2. Paper II: Empirical Study
................................................................................. 144
3. Paper III: Critical Review
Paper....................................................................... 229
5

Figures and Tables
Paper I: Systematic Review
Figure 1: A PRISMA Chart to Outline Screening and Eligibilty
Procedures ........ 24
Table 1: Characteristics of Studies
................................................................... 29-33
Table 2: Component and Global Quality Ratings using the
EPHPP ...................... 35
Table 3: Changes to Mean Scores and Calculated Effect Sizes
for Psychological
Distress Associated with Mental Health
............................................................... 39
for Pain .............. 41
for Distress
following Trauma
...............................................................................................
.... 42

Paper II: Empirical Paper
Figure 1: Consort Diagram of Recruitment and Study Retention
.......................... 71
Figure 2: A Box Plot to Demonstrate Therapists Rating of
Adherance to Therapy
...............................................................................................
................................. 83
Figure 3: Suicide Ideation as Rated by Participants and
Therapists, across all Five
Sessions
...............................................................................................
................... 86
Table 1: An Overview of the Therapeutic Modules Delivered
During the
Programme
...............................................................................................
............. 82
Table 2: CSQ Mean Scores and Overall Satisfaction Score
.................................. 84
Table 3. Mean Scores and Effect Sizes at Baseline and Follow

Up....................... 84
6
Table of Appendices
Appendix 1: Clinical Psychology Review Guidance for
Authors .................... 129
Appendix 2: EPHPP Quality Tool
.................................................................... 140
Appendix 3: Archives of Suicide Research Guidance for
Authors ..................... 145
Appendix 4: University of Manchester Ethical Approval
.................................... 147
Appendix 5: Health Research Authority Ethical Approval
.................................. 149

Appendix 6: Favourable Research and Ethics Committee Letter
........................ 152
Appendix 7: HMPSS Ethical Approval
................................................................ 157
Appendix 8: Clinical Trial Registration
............................................................... 159
Appendix 9: Participant Information Sheet
.......................................................... 161
Appendix 10: Summary Participant Information Sheet
....................................... 166
Appendix 11: Informed Consent Form
................................................................ 168
Appendix 12: Prison GP Letter
............................................................................ 171
Appendix 13: The InSPire Programme: What to Expect
..................................... 173
Appendix 14: Participant Debriefing Sheet
.......................................................... 176
Appendix 15: Certificate of Completion
.............................................................. 178
Appendix 16: Demographics Questionnaire
........................................................ 180
Appendix 17: Additional Study Metrics
.............................................................. 185

Appendix 18: Therapist Session Summary Sheet
................................................ 187
Appendix 19: Therapist Rating Scale
................................................................... 190
Appendix 20: Client Satisfaction Questionnaire
.................................................. 192
Appendix 21: Discharge Summary Sheet
............................................................ 196
Appendix 22: Beck Suicide Scale
........................................................................ 198
Appendix 23: The Difficulties in Regulating Emotions Scale
............................. 201
Appendix 24: Social Problem Solving Inventory
................................................. 207
Appendix 25: Multi-dimensional Scale of Percieved Social
Support .................. 209
Appendix 26: Participant Sessional Measure
....................................................... 211
Appendix 27: Therapist Sessional Measure
......................................................... 213
Appendix 28: Qualitative Interview Topic Guide
................................................ 215
Appendix 29: CBSP Therapy Modules
................................................................ 219

7
Appendix 30: Distress Protocol
............................................................................ 221
Appendix 31: Safe Working Practices and Risk Management
Protocol .............. 223
Paper III: Critical Review
Appendix 32: EPHPP Dictionary
......................................................................... 230
Appendix 33: InSPire Appointment Slips
............................................................ 235
8
Word Counts

(excluding abstracts, references, tables, figures and appendices)
Papers
Paper III: Critical Reflection
Total word count
Word Counts
8456
8275
5966
22, 697

9
Overall Abstract
Background
Paper I: Intensive Cognitive Behavioural Therapy (CBT) is an
emerging intervention
for psychological distress and mental health. There is no known
review in this area
in an adult population. Paper II: The InSPire programme was
developed to deliver
intensive cognitive behavioural suicide prevention (CBSP)
therapy within a prison,
to address barriers to long term engagement in previous
psychological intervention
studies (i.e. attrition).
Aims
Paper I systematically reviewed studies which have delivered
intensive CBT within
an adult population experiencing psychological distress. Paper
II aimed to
determine the feasibility of intensive CBSP in a prison, with
individuals experiencing
suicidal thoughts and behaviours.
Methods
Paper I was a systematic review of 17 studies delivering

intensive CBT across
populations experiencing psychological distress associated with
mental health,
addiction, chronic pain and following a traumatic incident.
Paper II was a feasibility
case series with single baseline and single follow up. Thirteen
individuals consented
to the InSPire programme, delivering an intensive CBSP
intervention within a three
week period (five two-hourly sessions were offered). Outcome
measures assessed
suicidality (including thoughts of self-harm) and client
satisfaction. Psychological
mechanisms associated with suicide were measured, including
perceived social
support, emotional regulation and problem solving.
Results
Paper I found promising results in the efficacy and feasibility of
intensive CBT,
particularly in the population experiencing distress associated
with mental health
difficulties. The review unearthed a number of
recommendations for further
research in this field. Paper II found the InSPire programme to
be feasible, as
determined by successful recruitment and retention across the
study, including
high participant satisfaction. The programme appeared to have
an efficacious
benefit for those who took part across all outcomes measured.
Conclusions
Paper I highlights the promising feasibility and efficacy of
intensive CBT, yet more
rigorously designed studies (i.e. RCTs) must be conducted

before firm conclusions
can be drawn and prior to a future repeat review. Paper II
highlighted the potential
benefit of conducting intensive CBSP in prison. Given the
limited generalisability of
this study, a larger scale feasibility trial would now be
warranted to determine more
conclusive evidence.
Paper III was a critical review paper appraising papers I and II.
This included
consideration of the methodological process, strengths and
limitations, and
considerations alongside further literature.
10
Declaration
No portion of the work referred to in the thesis has been
submitted in support of an
application for another degree or qualification of this or any
other university or
other institute of learning.
Copyright Statement
i. The author of this thesis (including any appendices and/or
schedules to this
thesis) owns certain copyright or related rights in it (the

“Copyright”) and s/he has
given The University of Manchester certain rights to use such
Copyright, including
for administrative purposes.
ii. Copies of this thesis, either in full or in extracts and whether
in hard or electronic
copy, may be made only in accordance with the Copyright,
Designs and Patents Act
1988 (as amended) and regulations issued under it or, where
appropriate, in
accordance with licensing agreements which the University has
from time to time.
This page must form part of any such copies made. iii. The
ownership of certain
Copyright, patents, designs, trademarks and other intellectual
property (the
“Intellectual Property”) and any reproductions of copyright
works in the thesis, for
example graphs and tables (“Reproductions”), which may be
described in this
thesis, may not be owned by the author and may be owned by
third parties. Such
Intellectual Property and Reproductions cannot and must not be
made available for
use without the prior written permission of the owner(s) of the
relevant Intellectual
Property and/or Reproductions. iv. Further information on the
conditions under
which disclosure, publication and commercialisation of this
thesis, the Copyright
and any Intellectual Property and/or Reproductions described in
it may take place is
available in the University IP Policy (see
http://documents.manchester.ac.uk/ DocuInfo.aspx?DocID=2442
0), in any relevant
Thesis restriction declarations deposited in the University

Library, The University
Library’s regulations (see
http://www.library.manchester.ac.uk/about/regulations/)
and in The University’s policy on Presentation of Theses
11
Acknowledgments
I would like to thank the participants for taking part in the
InSPire programme.
Involvement has allowed us to further our understanding of
psychological therapy
in prison for those experiencing suicidal thoughts and
behaviours. Thank you to all
prison and NHS staff who worked alongside us to make this
programme possible.
Thank you to Dr Daniel Pratt, for this incredible opportunity,
and for the ongoing
inspiration, patience and guidance throughout. Thank you to Dr
Charlotte Lennox
for research support and guidance throughout.

Thank you to Minjae Kim for data entry. Thank you to Claire
Steele and Megan
McKenna for support with inter-rater reliability. Thank you to
Jemma Gaskell,
Martin Parrington and Claire Oakes for support with proof
reading.
Thank you to Jessica Killilea, for being my ‘wingman’ on this
project, for always
having a listening ear and encouraging voice.
Thank you to the incredible cohort that I have been so lucky to
have been a part of
during the three years.
Finally, thank you to Gareth Moore, without whom none of this
would be possible.
Thank you for being you.
12
Dedication

To those who have lost their lives to suicide.
To families and friends who have been affected by suicide.
To the individuals who continue to fight every day.
13
Introduction to Paper I
Paper I is a systematic review written in accordance with the

author guidance for
submission to the journal Clinical Psychology Review
(Appendix 1). The authorship
for this paper will be as follows: Hampson, L., Killilea, J.,
Lennox, C., & Pratt, D.
(2019).
Previous years have seen the emergence of innovative and
adapted formats in the
delivery of Cognitive Behavioural Therapy (CBT), across all
clinical populations. The
NHS adapts and shapes services based upon clinical need and
cost-effectiveness.
Intensive CBT is one method of therapeutic delivery which has
attracted research
interest over the past decade. Although there is one published
review in this field
that investigates intensive CBT with children with anxiety
disorders, there are no
known equivalent reviews which investigate intensive CBT in
an adult population.
This review takes a broader approach into investigating the use
of intensive CBT
across clinical populations experiencing psychological distress.
This review seeks to

understand more about how intensive CBT has been delivered
so far, and the
efficacy of its delivery. This review will be relevant for
clinicians delivering CBT, in
highlighting the importance of patient choice in the delivery of
services, as well as
providing recommendations in terms of overall service delivery.
First and foremost,
this review will provide a foundation for future, larger scale,
reviews of this type.
Paper I explores the components of an intensive delivery of
CBT, as was delivered in
the research study of Paper II. This gave the author a broader
understanding of
what intensive CBT is and the areas in which it has been
delivered to date.
14

Paper I Systematic Review
Intensive Cognitive Behavioural Therapy for Psychological
Distress: A Systematic Review
Written in preparation for submission to
Clinical Psychology Review
Word count: 8456 (excluding abstract, tables, figures and
references)

15
1. Abstract
Delivery of Cognitive Behavioural Therapy (CBT) has adapted
over time in response
to the need for more streamlined services. This systematic
review aims to examine
existing literature to understand the primary characteristics and
efficacy of
‘intensive’ CBT across clinical populations experiencing
psychological distress.
Intensive CBT offers a quicker intervention which is completed
in a much shorter
time than the traditional weekly delivery.
Seventeen papers were included in this review. Four categories
of clinical
population were defined, including psychological distress
associated with mental
health, chronic pain, addiction and following a traumatic
incident. Delivery of
intensive CBT differed across the studies. An average of 17
hours of therapy was

received per participant. Studies delivered a variety of different
components of
CBT, most often being cognitive restructuring. Effect sizes
were promising at post-
intervention and longer term follow-up, particularly within
studies investigating
mental health difficulties.
This review has collated information on the delivery of
intensive CBT and highlights
the promising results in the efficacy of intensive CBT.
However, most studies were
exploratory in design, with small sample sizes and weak
methodological quality.
Recommendations are given for larger scale trials of intensive
CBT to be conducted
in order to establish a more reliable evidence base.
Key words: Systematic, Review, Intensive, Cognitive
Behavioural Therapy.

16
2. Introduction
2.1 Mental Health and Psychological Distress
It is widely reported that one in four people in the UK will
experience a mental
health difficulty during their lifespan (Ginn & Horder, 2012),
with one in six
reporting symptoms of anxiety or depression within the past
week (McManus,
Bebbington, Jenkins, & Brugha, 2016). Mental health retains a
significant focus in
the government’s political agenda, as it holds considerable
bearing upon rates of
employment, housing, debt and poverty (Mental Health
Foundation, 2016). There
are financial consequences both on an individual and societal
level. Costs to the UK
economy are substantial and taking into account the associated
reduced quality of
life, the cost in England alone in 2010 reached £105.2 billion
(Centre for Mental

Health, 2010). Both nationally and globally the investment into
resources for
prevention and treatment is outweighed by the cost. Despite
this, mental health
remains a political focus, as outlined in many Government
initiatives, emphasising
the importance of effective service provision and investment
into both physical and
mental health (Department of Health [DH], 2011; Mental Health
Taskforce, 2016).
Whilst mental health difficulties are generally captured within a
diagnostic
framework, (American Psychiatric Association [APA], 2013),
‘psychological distress’
is a broader term used throughout the literature. Mirowsky
(2007) offers an
understanding of ‘distress’ as being beyond concepts or
diagnoses, which
essentially captures the emotional suffering experienced by the
individual. Ridner
(2004) suggested that psychological distress is most often,
although not exclusively,
pre-empted by a stressor for which coping is ineffective. Ridner
(2004) defines

psychological distress as the “unique discomforting, emotional
state experienced by
an individual in response to a specific stressor or demand that
results in harm, either
temporary or permanent, to the person” (p. 539). The
description by Ridner (2004)
was the working definition of psychological distress for the
current review.
Psychological distress is commonly measured using the General
Health
Questionnaire [GHQ] (Goldberg, 1972) or Kessler
Psychological Distress Scale [K10]
(Kessler et al., 2002). According to these measures, prevalence
of psychological
distress has been shown to vary greatly from 7% to 33% in
general populations
17
across the world (Australia: Chittleborough, Winefield, Gill,
Koster, & Taylor, 2011;
Phongsavan, Chey, Bauman, Brooks, & Silove, 2006; Spain:
Gispert, Rajmil,
Schiaffino, & Herdman, 2003; Japan: Kuriyama et al., 2009).

There are further
variations within particular population groups. Using the GHQ,
Gispert et al. (2003)
found psychological distress was reported by 15.4% of females,
compared to 9.2%
of males within a Catalan community. Using the K10,
Phongsavan et al. (2006)
reported even higher rates of distress within the Australian
population, with up to
35.5% in females compared to 29.9% in males. Furthermore,
chronic physical health
conditions or severe ill health were found to greatly increase
prevalence of
psychological distress (Arvidsdotter, Marklund, Kylén, Taft, &
Ekman, 2016;
Drapeau, Marchand, & Beaulieu-Prévost, 2012). Chittleborough
et al. (2011)
reported a prevalence of 15.8% in a population with chronic
health conditions.
Further social factors were found to increase psychological
distress: being young or
old age; being a smoker or drinker; having a low or high BMI;
having lower social
capital or education levels; unemployment; restricted or reduced

daily physical
activity; and a lack of social support or integration within a
community
(Arvidsdotter et al., 2016; Drapeau et al., 2012; Kuriyama et al.,
2009; Gispert et al.,
2003; Phongsavan et al., 2006).
2.2 Cognitive Behavioural Therapy
Cognitive Behavioural Therapy (CBT) has been identified as the
primary
psychological intervention in many disorders of psychological
distress, with
particular effectiveness noted in disorders of anxiety (Stewart &
Chambless, 2009;
Hofmann & Smits, 2008) and depression (Butler, Chapman,
Forman, & Beck, 2006).
CBT is recommended as first-line treatment before
pharmacological intervention
for anxiety disorders (National Institute for Health and Care
Excellence [NICE],
2014). Specific anxiety disorders and other disorders (i.e.
depression; NICE, 2011)
have individual quality standards recommending the appropriate
level of

psychological input.
Beyond anxiety and depression, a number of meta-analyses
highlight the efficacy of
CBT across populations with psychological distress:
behavioural parent training
(BPT) for antisocial behaviour in young people (post-treatment
ES = 0.35; follow up
18
ES = 0.31) (McCart, Priester, Davies, & Azen, 2006); male
offenders experiencing
anger management issues, with treatment aimed to reduce
recidivism (ES = 0.77)
(Henwood, Chou, & Browne, 2015); difficulties with insomnia
(medium to large
effects; Okajima, Komada, & Inoue, 2011); chronic pain,
improvements noted in
mood (standardised mean difference [SMD] = -0.24; p = 0.004)
and pain coping
(SMD = 0.85; p = 0.006; Bernardy, Füber, Köllner, & Häuser,
2010); and problem
gambling (large effect sizes at post treatment and follow up;
Gooding & Tarrier,

2009). Finally, a Cochrane Review demonstrated the
effectiveness of a CBT-based
intervention (i.e. cognitive reframing) in supporting carers of
people with dementia,
with associated anxiety (SMD = -0.21), depression (SMD = -
0.66) and subjective
stress (SMD = -0.23; Vernooij‐ Dassen, Draskovic, McCleery,
& Downs, 2011).
The studies above are important for highlighting the broad
scope of CBT and its
efficacy beyond psychiatric disorders and into issues of
psychological distress. CBT
has an established evidence base across a number of
psychological disorders (Epp &
Dobson, 2010). More specifically, The Department of Health
published a document
for the Improving Access to Psychological Therapies (IAPT)
Programme (2007)
outlining the most evidence based CBT models for a number of
psychological
disorders, including social phobia (Heimberg, 1995; Clark &
Wells, 1995); panic
disorder (Clark, 1994; Barlow, Craske, Cerny & Klosko, 1989);
obsessive compulsive

disorder (OCD) (Steketee, 1993; Kozak & Foa, 1997);
generalised anxiety disorder
(GAD) (Borkovec & Ruscio, 2001; Dugas, Gagnon, Ladouceur
& Freeston, 1998;
Zinbarg, Barlow, Brown & Hertz, 1992; Craske, 1999); post-
traumatic stress disorder
(PTSD) (Foa & Rothbaum, 1998; Ehlers & Clark, 2000; Resick,
2000) and depression
(Beck, 1979; Jacobson, Martell & Dimidijan, 2001). CBT is
therefore recommended
by the National Institute for Health and Care Excellence (NICE)
for a number of
psychological disorders.
2.3 Components of Cognitive Behavioural Therapy
CBT is essentially focussed upon our thoughts, feelings and
behaviours and the
interactions between them (Beck, 1979). It highlights unhelpful
thinking and
behavioural patterns that emerge and maintain distress (British
Association for
Behavioural and Cognitive Psychotherapies, [BABCP], 2019).
The Department of

19
Health (DoH) published a document for the Improving Access
to Psychological
Therapies (IAPT) Programme (2007), which provides detail of
therapeutic standards
and competencies which are important for practitioners to
deliver CBT to an
appropriate level according to good practice. In addition, there
are variations across
the literature as to which therapeutic components make up a
CBT intervention. The
Association for Behavioural and Cognitive Therapies (ABCT)
condenses CBT to three
main components, each with specific therapeutic techniques.
These components
are case conceptualisation, behavioural components (self-
monitoring, behavioural
activation, exposure) and cognitive components (eliciting and
modifying thinking)
(ABCT, 2019). Tolin (2010) determined six categories which
were used as a checklist
within a meta-analysis investigating the effectiveness of CBT.

European Journal of Cultural Studies2015, Vol. 18(4-5) 395 –

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