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OPEN ACCESS Top-Quality Science
Peer Reviewed
Open Peer Reviewed
Review of Communication Research
2023, Vol.11
ISSN: 2255-4165
Editor: Camiel J. Beukeboom (Vrije Universiteit Amsterdam, The Netherlands).
Reviewers who accepted to sign their review: The reviewers prefer to stay blind.
Received: January 11, 2022 Open peer reviewed: November 30, 2022 Accepted: December 21, 2022 Published: May 10, 2023
Images Published by Cancer Patients in Social Media and
Their Reception: A Systematic Review
Abstract
This paper presents a systematic review of the discourses that emerge from the study of cancer images posted by patients and
caregivers on Instagram, Imgur, Pinterest, Twitter and Facebook. It presents the types of images that posters use to visualise
cancer and how they are perceived by viewers. Results indicate that three factors affect visibility and engagement: (a) the
framing, (b) the purpose, and (c) the emotions portrayed. They also show that viewers prefer images that (a) show the patient
improving their condition through treatment, (b) tell a personal story and (c) take on an optimistic tone. This type of image
reflects the common idea of the cancer patient as a survivor, which is particularly visible in breast cancer posts. For patients
faced with uncertainty, fear or frustration, the standardisation of survivorship images may challenge identity-formation and
create a sense of isolation. However, we also find that patients who use photographs to express negative emotions (such as
sadness or frustration) are met with emotional support from viewers. Our findings show that, beyond virality and standardised
discourses, visual social media and photography can provide a positive venue for the communication of more diverse cancer
experiences from patients and caregivers.
Highlights
• Social media-cancer is a rich field, but little attention has been given to the specific role of images.
• Current studies are divided between the biomedical and social approaches, making it challenging to establish
a conversation.
• Few of the published papers use images to communicate their results, despite studying visual communications.
• Images that show cancer as a journey are met with positive reactions in most social media.
• Images that provide general information about cancer perform best on Twitter and Pinterest.
• Social media favours positive emotions, but negative emotions also find home and support.
• Mixed methods can help predict the (algorithmic) performance of images while also accounting for their
individual perception.
• Situating social media images of cancer in three discursive lines may help predict their impact.
Suggested citation: Varela-Rodriguez, M., & Vicente-Mariño, M. (2023). Images Published by Cancer Patients in Social
Media and Their Reception: A Systematic Review. Review of Communication Research, 11, 33–64. https://doi.org/10.5680/
RCR.V11.2
Keywords: Visual sociology; Health Communication; Cancer Photography; Public understanding of science; Discourse analysis
Miguel Varela-Rodríguez
Department of Sociology and Social Work,
University of Valladolid,
Valladolid, Spain
miguel.varela@uva.es
Miguel Vicente-Mariño
Department of Sociology and Social Work,
University of Valladolid,
Valladolid, Spain
miguel.vicente@uva.es
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Varela-Rodríguez and Vicente-Mariño
Content
INTRODUCTION ......................................................................................................... 35
PROBLEM STATEMENT AND GOALS....................................................................... 36
Approaching Images in Social Media ........................................................................... 37
METHODOLOGY ........................................................................................................ 39
Understanding of “Photographic Images” .................................................................... 39
Understanding of “Social Media” ................................................................................ 39
Research Questions ..................................................................................................... 39
Search Strategy ............................................................................................................ 39
Research dates .....................................................................................................................39
Paper sources .......................................................................................................................40
Platforms Considered .................................................................................................. 40
Search Queries ............................................................................................................ 40
Exclusion criteria, high level (before full-text reading) ..............................................................40
Exclusion criteria, low level (after full-text reading) .................................................................40
Data Management and Analysis .................................................................................. 41
Search Results ............................................................................................................. 41
Figure 1. Papers removed after full-text reading and the criteria that motivated
their exclusion ............................................................................................................. 42
Figure 2. PRISMA Flowchart ...................................................................................... 43
Methodologies used and cancer sites represented ......................................................................44
Visual analysis and image aesthetics ......................................................................................44
Extracting common discourses ...............................................................................................44
RESULTS ...................................................................................................................... 45
Representation of Cancer Sites .................................................................................... 45
Methodological Approaches ........................................................................................ 45
Figure 3. The coding process to obtain the “Positive Emotions” hierarchy .................... 45
Visual Analysis and Image Aesthetics ........................................................................... 46
Three Discursive Lines ................................................................................................ 47
First Discursive Line, Framing: Cancer as a Personal Story or a General Theme ............ 47
A personal story (episodic framing): tracking progress on treatment
and visualising the journey ...................................................................................................47
A general theme (thematic framing): communicating facts and calling for action .......................49
Second Discursive Line, Emotion: An Affective Line between Optimism and Fear ........ 50
Positive emotions: celebrating milestones and the hope for restitution. .......................................50
Negative emotions: expressing fear and uncertainty .................................................................51
Third Discursive Line, Purpose: Addressing the Self (“Me”) or the Other (“You”)
in Cancer Images ......................................................................................................... 52
“Me”: defending and reassessing identity and normalising cancer ............................................52
“You”: education and activism ..............................................................................................53
DISCUSSION ................................................................................................................ 54
On the Representation of Cancer Sites ......................................................................... 54
On Method ................................................................................................................. 54
35 2023, 11, 33–64
Cancer Images Social Media
Introduction
With World Breast Cancer Awareness month in October
and the Movember movement in November, the last quar-
ter of the year sees scores of cancer-related news and posts
in social media. Users publish messages and images to
support patients, share experiences of treatment, or partic-
ipate in fund-raising campaigns for cancer research. During
these months, thousands of images mention breast cancer,
a site that achieves high levels of engagement on Twitter,
Instagram and Facebook (Vraga et al., 2018), as well as on
Imgur (Hale et al., 2020). Other cancer sites, such as skin
cancer, also receive attention (Banerjee et al., 2018).
The study of social media as a space for cancer com-
munication has grown in recent years. Post metadata, their
features, the level of engagement with them, and the dis-
courses they create have been subject to numerous studies.
Systematic reviews in this area have analysed the psychoso-
cial impact of social media (Skrabal Ross et al., 2020), their
usefulness for clinical trials (Reuter et al., 2018), or their
measurable effects on health outcomes (Chou et al., 2020).
Overall, research shows that social media help communicate
cancer prevention and screening measures, support patients
during treatment, and provide psychosocial and informa-
tional support to patients and caregivers (Attai et al., 2015;
Chou et al., 2020).
This paper taps into an emerging area in the literature:
the use of photographic images in social media to commu-
nicate cancer. The systematic review covers three databases
(PUBMED, SCOPUS and Web of Science) and 17 years of
publications (from 2004 to 2021). Papers are assessed first
on six criteria, related to language, access and whether the
paper attempts an analysis of images related to cancer in
social media. Papers that pass these first criteria are then
reviewed in-depth to determine whether they focus on still
images, whether they address social media and content
analysis of said images, whether they evaluate cancer dis-
courses as generated by patients, and whether they put for-
ward a clear method for their analysis. The final sample
consists of 16 papers that have been found to study photo-
graphic and visual representations of cancer on Instagram,
Twitter, Facebook, Pinterest and Imgur. All of them make
their methods explicit and analyse the discourses that result
from the images studied, their captions, and the comments
they receive.
A review of the 16 papers reveals that cancer images in
social media move along three discursive lines. The first line
is drawn between images that present their poster’s journey
through cancer (episodic framing) and images that discuss
cancer information generally (thematic framing). The second
line is drawn between images that visualise positive emotions
(hope, joy) and those that present negative emotions (fear,
uncertainty). Lastly, the third line reviews whether images
take on a “me” framing (focusing on the poster’s experience
of cancer and how they perceive it) and those that take a
“you” framing (calling the viewer to action, highlighting
the consequences of cancer, or advocating for change in the
public health system). These three lines highlight the chal-
lenges and opportunities for both health communicators,
practitioners, and patients in using photographs to discuss
cancer in social media. They also carry implications for pre-
vention and screening efforts.
The review is divided into four general sections. It first
presents the problem addressed, previous research done on
the topic, and the goals of the paper. The Methodology sec-
tion outlines the search queries, the search and inclusion
criteria, and the process to store and analyse the papers
obtained. The Results section presents the findings: number
of papers filtered and selected, their characteristics, and how
the three discursive lines appear in the sample. This section
also discusses the engagement that the different discourses
lead to, where available. Lastly, the Discussion reviews the
Three Discursive Lines ................................................................................................ 54
Figure 4. The three discursive lines for images of cancer in social media
that emerge from a meta-synthesis of the 16 papers studied ........................................... 55
An Image of Cancer in Social Media… without Images? .............................................. 56
Implications for Further Research and Future Developments ........................................ 57
Limitations .................................................................................................................. 58
CONCLUSIONS ............................................................................................................ 58
REFERENCES ...............................................................................................................58
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Varela-Rodríguez and Vicente-Mariño
implications of the results obtained, as well as options for
future research.
Problem Statement and Goals
Since the 1970s, the study of public discourses of cancer has
been a fruitful field. Susan Sontag discussed cancer as “the
master illness” (Sontag, 1978). Along with the work of fem-
inist writers like Audre Lorde (1980), Sontag’s critique of
the discourse of restitution gave shape to a new understand-
ing of this group of illnesses. At the time, researchers and
activists questioned the usefulness of referring to patients as
“fighters”, challenged the use of visual tropes such as the
pink ribbon, and highlighted the risks of using cancer aware-
ness campaigns for commercial purposes (King, 2008).
Media representations of breast cancer have received
great academic attention in the past decades, which has
crossed over to other cancer sites. Today, an enhanced under-
standing of the informational and support needs of cancer
patients has enabled advances in psychosocial attention.
It has also impacted the way cancer is communicated and
increased the uptake of screening and prevention messages.
In the early 2000s, the rise of social media platforms came
with new opportunities and challenges for cancer communi-
cation. While social media have enhanced patients’ agency
to discuss their illness, they also appear to favour carefully
curated contents (Tifentale & Manovich, 2018), which may
force users into adopting aesthetic and cultural patterns that
do not always conform with the reality of cancer. Further,
while the hashtag-based design of platforms like Instagram
makes browsing and categorising posts easier, they have also
made some cancer sites (such as breast cancer) and discourses
(such as survivorship) more visible than others (Bell, 2014).
Importantly, social media posts discussing health have
been found to contain significant volumes of misinforma-
tion. Wang et al. (2019) illustrate how posts discussing health
often contain fake or inaccurate facts, especially around
infectious diseases and cancer prevention. Suárez-Lledo &
Álvarez-Gálvez (2021) note that cancer-related topics such
as the HPV vaccine are particularly affected, as misinforma-
tion is liked and shared more than accurate medical informa-
tion. Extant research also suggest that social media amplifies
the search for unproven, alternative treatment, unsupervised
advice, and false promises on prevention (Delgado-López &
Corrales-García, 2018; Wilner & Holton, 2018). Wang et al.
explain that viewers need certainty and reassurance, which
misinformation sometimes provides.
Despite their limitations, social media have also been
shown to play a positive role in cancer survivorship, preven-
tion, and screening. In 2007, a study of online communities
(blogs and forums at the time) found that these platforms
help increase social interaction, interpersonal trust, and
social support for patients (Beaudoin & Tao, 2007). Since
then, numerous studies have approached social media and
its role in cancer support.
From the perspective of patients, Instagram, Facebook,
or Twitter enhance the relationship with health practitioners
(Gentile et al., 2018). They also facilitate the understanding
and management of symptoms (Bender et al., 2013), provide
clarity and support through the different phases of treatment
(Attai et al., 2015; Banerjee et al., 2018), support the build-
ing of communities of exchange (Zade et al., 2017), and
alleviate the feeling of loneliness during and after treatment
(Hale et al., 2020; Skrabal Ross et al., 2020).
From the perspective of practitioners, mobile health tech-
nologies and social media can be sued to engage participants
in clinical trials (Gentile et al., 2018), to increase participation
in cancer screening (Ruco et al., 2021), and to support aware-
ness-raising on preventive measures (Brinker et al., 2017).
Systematic reviews in this area reveal a divide between the
biomedical sciences and the social/communication sciences,
however. Biomedical research often looks at the impact that
the use of social media has on health, from a quantitative
approach. Meanwhile, the social and communication sci-
ences lean on qualitative methods to explore the affordances
of social media and how they affect the psychosocial needs
of patients, as well as the impact of visual elements in pre-
vention campaigns.
Thus, reviews in the biomedical fields often take issue
with the lack of hard evidence in the social sciences. An
example is the review by McAlpine et al.: while they affirm
that social media appear to have a “mildly positive effect” on
cancer patients, they also highlight how “the vast majority
[of papers studied] report only simple qualitative analysis”.
This is found to limit their capacity to lead to measurable
health outcomes (McAlpine et al., 2015, p. 293). Similar
concerns are raised in Koskan et al. (2014) and can be seen
in systematic reviews across different cancer sites, be it breast
cancer (Falisi et al., 2017), colorectal cancer (Pellino et al.,
2017) or prostate cancer (Pyle et al., 2021). Despite the chal-
lenges in establishing a clear correlation between health
37 2023, 11, 33–64
Cancer Images Social Media
improvements and social media usage, it has been observed
that social media does increase the uptake of preventive
measures (Han et al., 2018) and the likelihood of screening
(Döbrössy et al., 2020).
On the other side of the spectrum, social scientists high-
light how biomedical studies neglect the non-medical aspects
of treatment, “leaving survivorship to the wayside” (Cherian
et al., 2020, p. 16). Through qualitative approaches, their work
addresses the effects of misinformation on patients (Delgado-
López & Corrales-García, 2018; Wilner & Holton, 2020), the
adoption of social discourses on illness and how they relate
to user agency (Stage, 2019a, 2019b), and how social media
can increase the participation of underrepresented groups
(Pailler et al., 2020; Rivera et al., 2021). In sum, they find
that social media “can create a space to share, comment and
discuss health information” (Moorhead et al., 2013, p. 9).
The finding comes with a warning, however: social media
is useful when research goes beyond commonly studied plat-
forms, when it includes the perspectives of underprivileged
groups, and when it expands the reach of study to cancer
sites that are less present in public communications (Grant
& Hundley, 2008; Hale et al., 2020; Macdonald et al., 2018).
Despite the advancements in the study of the cancer-
social media nexus, a gap remains in knowledge when it
comes to where images fit in that discussion. This paper
aims to obtain a picture of the topic, drawing the number
of academic papers that have been dedicated to it and their
main conclusions to facilitate discussion across fields.
Approaching Images in Social Media
The emergence of patient-produced photographs of cancer
around the 1980s provided a new layer of information and
meaning-creation for patients, one that commercial and
medical representations did not enable (Pardo, 2019). Where
the latter presented images of patients that were often stig-
matising (íbid.), visual auto-pathographies (Hawkins, 1999)
enhanced the self-expression and self-tracking of patients
and raised public awareness on the consequences of cancer.
The photographic camera has allowed patients to see them-
selves, negotiate their identity, and understand their emo-
tional responses to the illness (Capewell et al., 2020). It
has also served as a tool for activism. While Audre Lorde’s
Cancer Journals used text to challenge cancer stereotypes, Jo
Spence, Matuschka, or Hannah Wilke used their cameras to
the same end (Gómez-Arrieta & Silva-Salazar, 2017).
Cancer photographs taken by patients and caregivers
reflect the “here and now”, an instant in the journey of ill-
ness as seen by those who live through it. As Sontag put it,
photographs are a “way of dealing with the present” (2008,
p.130). For people that live with cancer, dealing with the
present may entail showing the effects of chemotherapy,
expressing hope for restitution through a thumbs up, show-
ing gratefulness to their caregivers as they embrace them, or
showing the physical and emotional toll when they simply do
not have the strength to get out of bed. Through the camera,
patients “deploy normality”, coexist with their illness, reflect
on what they may have left behind, and normalise life with
illness in the eyes of the viewer (Plage, 2021).
By 2010, the arrival of visual social media (such as
Instagram or the now-extinct Vine) added new elements to
this function of self-presentation. While platforms launched
in the early 2000s like SmugMug, PhotoBucket, or Flickr
prioritised storage and artistic expression, these new appli-
cations focused on the immediacy of smartphone pho-
tography. Instagram’s launch in 2010 was a milestone in
this regard (Leaver et al., 2020). It enabled people with an
iPhone (later, with an Android smartphone too) to capture
the world around them and to share it instantaneously with a
global audience. Eventually, it would become one of the fast-
est growing social media (Pew Research Center, 2019), and
other networks would incorporate its approach to photogra-
phy to their design. Today, posts that are accompanied by an
image are known to achieve higher levels of engagement in
all the major platforms (Miller et al., 2019), and images have
become ubiquitous in social media.
Photographs do not exist in isolation in these platforms,
however, not even in visual social media. They coexist with
audio, video, text, polls, and other interactive elements.
Users add text (both to the captions and to the image itself),
hashtags, filters and enhancements to guide the perception
of their post, deploying the anchorage function that Barthes
outlined already in the 1970s (Barthes, 1977, p.40). Further,
the grid layout and the infinite feeds of Instagram, Pinterest
or 9Gag perform a relay function (Barthes, 1977), engag-
ing the viewer in a continuous visual discourse that tells a
story and propagates a message. Applied to cancer, these
two functions (anchorage and relay), along with Instagram’s
algorithms that prioritise the best-performing posts, lead to
the creation of social discourses of cancer (Stage, 2019b,
p. 272): images that are socially recognised as representative
of this group of illnesses.
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Varela-Rodríguez and Vicente-Mariño
Admittedly, visual social media cannot be taken as “photo-
graphic truth” in cancer communication. For one, Instagram
users are selective in what they share, as they seek to conform
to aesthetic and cultural expectations (Leaver et al., 2020,
p. 44). Typically, this leads to curated photographs. Benefiting
from the stillness of photography, users may take tens of dif-
ferent versions of any given image before they finally share
their preferred version. Some apps and smartphones can even
facilitate that process with algorithms that choose the “best”
of the roll. Meanwhile, filters, captions, and text overlays not
only anchor the images, but serve to shape their aesthetics
and motivate responses (Manovich, 2017).
For researchers, visual social media provide a unique
opportunity, as images posted there are accompanied by ele-
ments that facilitate their use as data. Likes, comments and
shares can be incorporated into content analysis to evalu-
ate the perception of certain elements or discourses. With
cancer images in social media, researchers can conduct both
quantitative and qualitative analysis (Stage, 2018, p. 16),
addressing not only the visual elements but also their accom-
panying text and the reaction from viewers.
When it comes to their interpretation, Barthes (1977)
provides a fitting framework for visual analysis with the dis-
tinction between denotation and connotation. Overall, deno-
tation refers to identifying what is in the picture, with little
to no interpretation, and with no reference to supporting
documents such as captions. Individuals, objects, and envi-
ronments are part of this level. A denotative analysis indi-
cates there is a person, a building, or an animal in the frame,
without identifying them by name.
Connotation goes a step further by interpreting and
naming each of those denotative elements and situations,
sometimes helped by captions or comments: a person
becomes a specific celebrity or a cancer patient; a building
becomes a museum, a library, or the city council, for instance.
These two levels of visual study, denotation and conno-
tation, are expanded with Panofsky’s (1991) framework for
iconology. Panofsky spoke of the primary subject (the ele-
ments in the image; equivalent to denotation), the secondary
subject (what the elements in the image are meant to rep-
resent; equivalent to connotation) and the intrinsic mean-
ing. Some authors refer to this latter level as “ideological”
1 Banerjee’s and Hay’s work on skin cancer and social media, although it does not fit within the specific scope of this review, is one of the
more revealing accounts of how social media can affect patients by imposing normative discourses of survivorship.
analysis (Rodríguez & Dimitrova, 2011). It evaluates the
social messages of an image and what it can tell us about its
context. Engaging in this level of analysis helps understand
the context that has led to the production of an image, the
ideas that it portrays, and what their producers try to tell us
about the world. For instance, through ideological analysis
we can identify that a pink ribbon is a symbolic represen-
tation of support to cancer patients. Descriptions, captions
and comments are common resources to support this task.
Lastly, there are other components of image semiotics,
mainly those relating to modality and framing. At this level,
framing is understood as the position and composition of
elements in the image: assessing the relationship between the
subjects pictured and how they are presented to the viewer,
whether there are elements in the image that are more
salient than others, or whether the photographer uses visual
devices to highlight the subject. Issues related to thematic
and episodic framing (which are explained in detail in fur-
ther sections) may also be explored here. Meanwhile, image
modality refers to visual devices that regulate the “realness”
of an image: the use of black and white, extreme saturation,
filters or strong lighting, for instance, are elements that make
images appear stylised and thus further from reality (see
Kress & van Leeuwen, 2010).
Applying visual analysis should enable a deeper under-
standing of images in social media. To our purpose, it can
reveal patterns in our social imagination of cancer. While
previous research has highlighted the scarcity of this type
of analysis in visual social media (Highfield & Leaver,
2016), the social media-cancer nexus has seen some prog-
ress. Kearney et al. (2019) reviewed the representation of
the HPV vaccine on Instagram and how viewers reacted
to different images; Ketonen & Malik (2020) implemented
a machine-learning method to identify and characterise
vaping posts on Instagram; Banerjee1 et al. look at represen-
tations of tanning on Pinterest (2019) and how they affect
the perception of skin cancer. For cancer screening and
health messaging, images have been shown to increase recall
and information uptake (Houts et al., 2006). However, our
review has found few papers that engage in a discussion of
visual representations of cancer as produced by patients or
caregivers. Thus, there is a gap in understanding how people
39 2023, 11, 33–64
Cancer Images Social Media
who live through cancer imagine the illness and their life
with it. To our knowledge, no systematic review has been
conducted on this topic before, either.
We believe that a systematic review has the potential to
identify key papers and open new venues of research into
cancer narratives, strengthening future work. It may dis-
cover patterns of image creation and engagement that could
explain if (or why) social media favours certain cancer sites
and discourses, evaluate the functions of images in social
media for cancer patients, or expand the discussion from
cancer sites more typically studied (such as breast cancer) to
other cancer sites.
Methodology
This systematic review combines existing approaches for
qualitative and quantitative systematic reviews (Pardal-
Refoyo & Pardal-Peláez, 2020; Petticrew & Roberts, 2006).
From question formulation to report write-up, each step in
the process is detailed below.
The Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRISMA) statement (Moher et al.,
2009; Page et al., 2021) is followed to report on the total
number of papers considered for review and the selection
process. The PRISMA flowchart can be found in the Results
section for a quick picture of the process followed.
Understanding of “Photographic Images”
“Photographic images” are understood as still images that
may or may not include text, drawings, or other visual ele-
ments outside of traditional photography. This allows for the
inclusion of memes, informational posters, and infograph-
ics, all of which are widely used online. This review does
not include video or other moving image formats, since these
contain narrative elements that are unique to them and out-
side the scope of this work.
Understanding of “Social Media”
This review uses Sloan and Quan-Haase’s definition of
social media:
“web-based services that allow individuals, communities,
and organizations to collaborate, connect, interact, and
build a community by enabling them to create, co-create,
modify, share, and engage with user-generated content
that is easily accessible.” (Sloan & Quan-Haase, 2016,
p. 23)
Mentions to broader online communities (such as forums
or blogs) are also considered, to avoid missing papers that
consider the visual discourses in patient-generated images of
cancer online. Conversely, the broader discussion of cancer
photography, outside social media, informs the aim of the
paper but is not considered for the results, as the research is
interested in the nexus that exists between social media and
photography.
Research Questions
An overall question was formulated:
How do peer-reviewed papers address the use of
patient-generated photographic images in social
media to discuss cancer?
The overall question would later be expanded to include
images posted by caregivers, too, given their central role in
cancer care and support.
In addition, several questions are considered to guide the
systematic review of results:
1. What are the methodological approaches applied?
2. What use do patients make of photographic
images in social media?
3. Which types of engagement do the photographs
posted achieve?
4. What are the common discourses and conse-
quences that emerge from the papers?
Search Strategy
Research dates
To be considered for this review, papers must be published
between 1 January 2004 and 11 November 2022. 2004 was
selected as the start date since it was the year Facebook
was launched. Searches were conducted on 11 November
2022.
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Varela-Rodríguez and Vicente-Mariño
Paper sources
Three databases were searched: SCOPUS, Web of Science
and PUBMED. Only papers published in peer-reviewed
journals were considered for review. Other sources, such as
books, inform the research but fall outside the scope of the
review—future work may look to these sources to expand
the validity of this work.
Platforms Considered
Initially, only Facebook, Instagram, and Twitter, as the three
largest social media platforms, were considered for research.
After a first round of searches, several platforms stood out as
potentially relevant and were included in the study: Pinterest,
Imgur, 9Gag, Reddit, TikTok and SnapChat.
Search Queries
Two groups of search queries were defined for each data-
base. Wildcards were used to allow for more results.
1. General searches that combine social media,
visual elements, and cancer:
a. PUBMED: ((“Social media”) AND ((Photogra*)
OR (imag*) OR (visual*)) AND ((cancer)
OR (tumor))) AND ((“2004/01/01”[Date -
Publication] : “2022/11/11”[Date - Publication]))
b. SCOPUS: (TITLE-ABS-KEY (“social media”)
AND TITLE-ABS-KEY (cancer OR tumor) AND
TITLE-ABS-KEY (photogra* OR imag* OR
visual*)) AND PUBYEAR
>
2003
c. Web of Science (with manual selection
of dates: 01/01/2004 to 11/11/2022):
ALL
=
(“social media”) AND ALL
=
(photogra* OR
visual* OR imag*) AND ALL
=
(cancer OR tumor)
2. Platform-specific searches, substituting the
term “social media” for either “Instagram”,
“Facebook” or “Twitter”.
a. In a second round, additional searches were
conducted for the terms “selfie” and “health
communication”, as well as for additional
platforms (Pinterest, Imgur, Reddit, 9Gag,
Tiktok and Snapchat)
To expand the reach of the search queries, papers were
added to the sample through a snowball approach by
reviewing the reference lists of papers selected for full-text
reading. Snowballing has been shown to be an efficient
way to achieve relevant results that may escape automated
searches (Greenhalgh & Peacock, 2005).
Exclusion criteria, high level (before full-text
reading)
Papers were first considered on an abstract and title level.
Titles that suggested a review of social media, photogra-
phy and cancer advanced to the next round. For those that
passed this initial review, six sequential exclusion criteria
were defined, where passing one criterion allowed the paper
to be considered for the next one:
1. Language: only papers in Spanish, English or
Portuguese were considered.
2. Accessibility: only papers that could be accessed
through the library services available to the
authors were considered.
3. Social media: only papers that explicitly discuss
social media.
4. Health: only papers that explicitly address
health-related topics.
5. Cancer: only papers that explicitly address cancer.
6. Images: only papers that explicitly discuss images.
All papers that passed these six criteria were downloaded and
stored for full-text reading. This included 62 papers in total,
deemed to be representative of the nexus social media-can-
cer-image nexus.
Exclusion criteria, low level
(after full-text reading)
For papers that passed the high-level criteria, an additional
round of exclusion was implemented. This is a more detailed
round, where papers are excluded if:
1. Images are only partially discussed. Images are
not discussed as a core part of the study. Instead,
papers commonly utilise a quantitative approach
that solely mentions that an image is present in a
post. Thus, images are considered in the results,
but researchers do not engage with the contents
of said images nor their effect.
41 2023, 11, 33–64
Cancer Images Social Media
2. Focuses on video, not still, photographic images.
These are mainly papers that focus on YouTube or
TikTok, and typically deal with audio transcripts.
Moving images include elements of rhythm and
montage that merit their own analysis.
3. Social media is not the object of the study but
used as a tool to connect with patients. This
includes clinical trials that are disseminated via
social media, or which use photographic appli-
cations to simulate changes in the user’s body
if they do not engage in preventive behaviour.
These papers are relevant for cancer prevention
and screening, but do not focus on patient- or
caregiver- generated discourses of cancer.
4. The paper analyses text, not images. The paper
uses text analysis as its primary method. While
images may be mentioned, they are not analysed
individually nor collectively.
5. Cancer is not the focus. The paper might men-
tion elements related to cancer or analyse envi-
ronmental factors such as smoking or tanning,
but cancer is not its primary focus, which means a
discourse of cancer cannot be extracted.
6. Social media discourse as generated by patients
is not analysed. These papers typically look at
images posted by health practitioners or organ-
isations, analysing their quality, or instead dis-
cuss image-analysis methods to diagnose cancer.
Sometimes they engage in a review of an organ-
isation’s campaign. While relevant, these papers
fall outside the scope of our review as they do
not address patient-generated visual discourses
of cancer. Where papers were found to focus on
cancer discourses as generated by caregivers, they
were considered for full analysis.
7. Method is unclear. These are often abstracts
without an accompanying paper, conference pre-
sentations, or papers that have unclear sources.
Figure 1 shows the papers that were removed from the review
according to these criteria, a total of 46 papers.
Data Management and Analysis
References were downloaded from each database into the
free and open-source library management software Zotero,
using its version 6.0.0. For those that passed a title review,
abstracts were exported to an Excel file, where each paper
was reviewed for the six high-level criteria. Papers that
passed said criteria were then downloaded in full (in PDF
format) into Atlas.Ti Qualitative Data Analysis (version 22),
a commercial software that allows for the qualitative analy-
sis of textual and visual documents and helps finding con-
nections between them. The PDF files were read in detail
and coded in Atlas.Ti, where they were also reviewed for the
seven low-level criteria.
Search Results
The search queries implemented returned a total of 1247
papers. We removed 528 duplicates, and 24 additional
records were added through snowballing, making for a total
of 743 records for title and abstract review. The PRISMA
flowchart in Figure 2 visualises the different steps.
Most of the papers rejected (435) do not study social
media, despite being returned by the queries. Of those that
do address social media, many either do not focus on cancer
(117) or do not study images (114). We found 20 papers in
the sample that do not mention social media in their title or
abstract but refer to “blogs” or forums”. None of them were
found to conduct a visual discourse analysis or image content
analysis. It thus appears that, despite social media-cancer
being a rich field of study, visual representations of the ill-
ness by patients or caregivers remain an area to be explored.
All records identified were either in Spanish, English,
or Portuguese, and only two records could not be accessed
through the university library services by the authors. The
two of them were messages from the editors of a journal and
were thus not pursued further.
Finally, 62 papers passed all initial exclusion criteria
and were downloaded for full-text reading. Of these, 58
were in English and 4 in Spanish; none were in Portuguese.
While the 62 were relevant for the broader approach of this
review, only 16 of them passed the low-level exclusion cri-
teria. We find that the criteria established for this review
are a rare occurrence in the literature. Where they address
cancer and social media, papers tend to treat images as a
sidenote, mentioning that an image is present in the post but
not performing image content or discourse analysis. In some
cases, the papers analyse the texts that accompany an image
(be it captions or comments), but do not conduct visual
content analysis. We understand that the lack of a deeper
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Varela-Rodríguez and Vicente-Mariño
Figure 1. Papers removed after full-text reading and the criteria that motivated their exclusion
43 2023, 11, 33–64
Cancer Images Social Media
Figure 2. PRISMA Flowchart
engagement with the images might be due to the complexity
of image analysis as a technique, something that is explored
later in this review.
Therefore, the final sample for review is made of
16 papers, which are found to be representative of the study
of visual discourses of cancer in visual social media as
generated by patients and caregivers. All of them are evalu-
ated on the method they use and the cancer sites they repre-
sent, how they approach visual analysis, and the discourses
that emerge from them.
A table is provided in annexes that details the 16
papers, the number of images they review, their methods
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Varela-Rodríguez and Vicente-Mariño
to obtain images and to code them, and the cancer sites
they focus on.
Methodologies used and cancer sites represented
The method implemented in each paper is assessed on a
qualitative-quantitative continuum, annotated on Atlas.Ti,
along with the tools used and their coding process. Similarly,
the cancer sites they address are also noted in the table in
annexes.
Visual analysis and image aesthetics
Information is collected on whether the papers attempt to
conduct a visual analysis as per Barthes’s (1977), Panofsky’s
(1991), Kress & van Leeuwen’s (2010) or Rodriguez &
Dimitrova’s (2011) frameworks. These four models aim to
evaluate the process of meaning-making in photographs
through the use of distinct subjects, light sources, and com-
position, as well as external elements like text. Papers may
adapt these frameworks or apply them indirectly.
Extracting common discourses
The extraction of common discourses was developed
through meta-ethnographic synthesis (Noblit & Hare, 1999;
Sandelowski & Barroso, 2007; Thorne et al., 2004), follow-
ing three distinct phases of coding.
First, each paper was thematically coded (Thomas &
Harden, 2008) using Atlas.Ti. This method entails the
in-depth reading of each paper and the verbatim coding of
their findings and core ideas. The result is a number of quo-
tations from each paper.
Second, each of these quotations was re-read and reinter-
preted by both authors, who then summarised and clustered
them into general statements. Statements take the shape of a
single phrase that seeks to encapsulate the findings expressed
in the larger quotations. This allowed the authors to analyse
and compare different statements.
Thirdly, statements were compared and clustered into
analytical hierarchies, which were compared with one
another. Each paper’s context was considered for this, with
several rounds of review conducted.
Given the diversity in methods and approaches present in
the papers, a certain degree of “translation” (Britten et al.,
2002) had to be performed to draw codes adequate both for
qualitative and quantitative research. Some of the hierar-
chies, such as “cancer as a journey” were already present in
the literature, while others were developed inductively based
on our findings. Similar approaches have been followed in
previous research to categorise the experiences of cancer
patients and relatives participating in psychosocial interven-
tions (Hoeck et al., 2017) and to evaluate the sources of can-
cer-related fear (Vrinten et al., 2017).
Take the following three quotations as an example:
“[
…
] posts that explicitly pushed back against conventional
notions of health and beauty were not nearly as promi-
nent, let alone popular, as those that focus on a return to a
pre-cancer state [
…
]” (Cherian et al., 2020, p. 12)
“The smooth overlap between the happiness and loving
optimism expressed and produced through sharing treat-
ment metrics is based on a general cultural prioritization of
restitution narratives [
…
]” (Stage, 2019a, p. 90)
“[
…
] posters who positively reappraised their situation
increased their likelihood of receiving informational sup-
port.” (Hale et al., 2020, p. 10)
Through context, the three of them could be traced to the
narrative of restitution, whereby a cancer patient expresses
their hope to regain health. Jointly, the quotations appear
to reflect a cultural tendency to prioritise this narrative in
social media. In consequence, the following statement was
formulated:
“Restitution is culturally prioritised as a cancer discourse in
social media.”
Deeper reading reveals that, apart from being linked to the
use of episodic framing (where cancer is described as a jour-
ney), this prioritisation appears linked to at least two facts.
First, viewers empathise more easily with positivity. Second,
posters appear more approachable when they express opti-
mism. Through clustering, the authors traced this and other
statements to the broader hierarchy of positive emotions, as
visualised in Figure 3.
This form of coding relies on the interpretation and
reflexivity of the researcher. To limit the risk of bias, both
reviewers discussed each code to ensure they were inter-
preted the same way and that the text included was indeed a
good match for the code.
45 2023, 11, 33–64
Cancer Images Social Media
Results
Representation of Cancer Sites
The representation of cancer sites in the sample echoes some
of the trends observed in the literature. Most papers (10)
focus on breast cancer. Coincidentally, these include some
of the most qualitative studies, which engage deeply with the
images and the discourses that they create. Two papers study
skin cancer, specifically melanoma, and engage with the rep-
resentation of the actual cancer in the images. One paper
discusses ovarian cancer through the qualitative analysis of
a single profile, while the rest address cancer more generally.
Methodological Approaches
Most of the papers in the final sample (15) are in
English; one is in Spanish. Papers focus on Instagram (6),
Pinterest (4), Facebook (2), Imgur (1), a combination of
Facebook, Instagram and Twitter (1), and a combina-
tion of Twitter and Instagram (1). Methodologically, two
of them engaged participants in a survey and interview
or performed keyword-based searches with them; four
observed specific profiles over an extended period; and the
rest (10) conducted hashtag or keyword-based searches to
identify images mentioning different cancer sites or can-
cer-related phrases.
The papers can be divided in two groups depending on
their approach to image coding and discourse analysis. On
the one hand, four papers (Gupta, 2022; Stage, 2019a, 2019b;
Tetteh, 2021) implement an in-depth, qualitative study of
Instagram profiles. This results in a thorough analysis of
discursive practices in the images and the reactions that they
prompt. Three of these, Gupta’s and both of Stage’s, show
some of the images studied within the paper and engage in an
analysis of their content, facilitated by the informed consent
Figure 3. The coding process to obtain the “Positive Emotions” hierarchy
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Varela-Rodríguez and Vicente-Mariño
of the research subjects. Images and text are weaved together,
creating a conversation between visual and textual exposition.
On the other hand, seven papers (Cho et al., 2018;
Henderson et al., 2021; Ma & Yang, 2022; Miller et al.,
2019, 2020; Park et al., 2019; Varela-Rodríguez & Vicente-
Mariño, 2021b) deploy a methodology that leans on quan-
titative approaches. They conduct content analysis to
measure the presence of certain elements in the images and
how they affect engagement metrics. Of these, only Varela-
Rodríguez & Vicente-Mariño include images in their papers
(either non-identifiable or posted by a public organisation
or business), while most do not offer visual support to the
text.
Somewhere in between are Cherian et al. (2020), Gürtler
et al. (2022), Hale et al. (2020), Rivera et al. (2021), and
Wilner & Holton (2020). These five papers implement what
could be characterised as a mixed-methods approach: they
perform content analysis, measure engagement, and provide
a review of discursive practices in the photographs. Rivera
et al. and Wilner & Holton use some images to communi-
cate their results.
It should be noted that, despite quantitative approaches
being more common in the sample, most if not all the papers
incorporate notions of qualitative analysis. They do so by
reviewing the presence of narrative resources or models, like
the Health Beliefs Model, and by making use of traditionally
qualitative methods such as Grounded Theory to code the
images manually.
One of the papers, by Varela-Rodríguez & Vicente-
Mariño, makes use of automated image-analysis, and it does
so only to extract their leading colours using scripts on the
open-source image analysis software ImageJ.
Visual Analysis and Image Aesthetics
All papers conduct visual analysis, adapting elements of dif-
ferent frameworks such as Barthes’s image rhetoric (1977),
Kress & van Leeuwen’s visual grammar (2010), Panofsky’s
iconological analysis (1991) or Rodríguez & Dimitrova’s
visual framing (2011). Gürtler et al. (2022) adapt a frame-
work developed by Acal-Díaz (2015). While none of the
other papers make their visual analysis method explicit, they
all address at least at one of four levels: denotation, connota-
tion, ideology or image semiotics.
When it comes to denotation, all papers discuss the items
contained in the images: specific colours, the presence of
people or nature, or the picturing of medical equipment, for
instance. Six papers provide a full list of the items they anal-
yse, although they do not differentiate between denotative
and connotative elements. Cherian et al. (2020) note the pres-
ence of individuals and nature while they also distinguish
patients, friends and doctors. Miller et al. (2020) indicate
the presence of adults and their demographic characteristics
(such as their apparent gender or the colour of their skin).
Henderson et al. (2021) note the “individual profile race” as
well as elements that reveal cancer treatment (chemotherapy
equipment, scars, or surgeries). Park et al. (2019) annotate
the picturing of male, female, white and non-white individu-
als. Rivera et al. (2021) identify whether the image discusses
food/diet, alcohol, obesity or tobacco, as well as specific
cancer sites. Cho et al. (2018) collect the emotions portrayed
in the images.
Across the 16 papers, denotative elements are extended
into connotation: selfies are discussed as patient represen-
tations; groups of people are interpreted as support groups,
celebrities are named; pink ribbons are interpreted as aware-
ness ribbons, images of medical equipment are transformed
into chemotherapy sessions, and smiles are coded as positive
emotions. Papers also use connotative analysis, often sup-
ported by image captions and comments, to categorise and
cluster posts.
Other semiotic elements are considered through a discus-
sion of framing, mainly, both in terms of episodic-thematic
framing and in terms of where each element in the image is
located (Henderson et al., 2021; Miller et al., 2020). While
not widely addressed, image modality is discussed in two
of the papers, which consider the use of colour and black
and white to convey emotions (Park et al., 2019; Varela-
Rodríguez & Vicente-Mariño, 2021). Filters, lighting or sub-
ject distance are not present, however, while composition is
discussed in Stage (2019a; 2019b) and Tetteh (2021).
Lastly, ideological analysis is presented through ele-
ments of the health beliefs model (Cho et al., 2018; Park
et al., 2019), misinformation (Rivera et al., 2021; Wilner &
Holton, 2020); different types of social support (Hale et al.,
2020); or different social cancer discourses (Cho et al., 2018;
Varela-Rodríguez & Vicente-Mariño, 2021). Qualitative
papers (Gupta, 2022; Stage, 2019a, 2019b; Tetteh, 2021) put
emphasis on this level, engaging in a discursive analysis of
what social media images can do for cancer discourse and
for patients’ identities.
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Cancer Images Social Media
Three Discursive Lines
The perception and impact of cancer images is found to
depend on their framing, on the emotions they portray, and
on their purpose. All papers engage in the discussion of at
least one of these three factors, which allows us to draw
three distinct discursive lines.
First discursive line, framing: episodic vs thematic.
This line situates images between the poles of episodic and
thematic framing. While episodic images visualise cancer as
a journey through (and after) diagnosis and treatment, the-
matic framing refers to images that contain general informa-
tion about cancer (Hale et al., 2020; Henderson et al., 2021,
p. 2; Miller et al., 2019). These two poles, common in com-
munication studies (Reese et al., 2001) receive various names
in the papers studied: for instance, Stage includes “self-mea-
surement” images as episodic (Stage, 2019a), Cherian et al.
(2020) and Tetteh (2021) speak of “cancer journeys”, while
Ma & Yang (2022) do not explicitly refer to episodic fram-
ing but speak of narrative and exemplars in both text and
images.
Second discursive line, emotion: positive vs negative.
This line is drawn to locate images between the poles of pos-
itive and negative emotions. Images that visualise positive
emotions, such as hope, generate different responses from
viewers than those that visualise negative emotions, such as
fear (Cherian et al., 2020; Hale et al., 2020; Henderson et al.,
2021; Stage, 2019a). Drawing a line between these two poles
highlights the importance of emotions in social media pho-
tographs of cancer. The line appears more clearly in papers
that study episodic images, while it does not appear to be as
relevant for more neutral, thematic images.
Third discursive line, purpose: addressing the self or
the other. As an extension of the episodic-thematic con-
tinuum, this third line situates images between two poles
that we have called “me” and “you” messaging. It emerges
from papers that pay closer attention to educational images
(Hale et al., 2020; Park et al., 2019; Rivera et al., 2021), but
is also present in qualitative inquiries into patient identities
(Gupta, 2022; Stage 2019a; 2019b). This discursive line dis-
tinguishes two types of images: those that aim to visualise
the posters’ experience of cancer, and those that explicitly
intend to change the viewers’ attitude towards cancer. “Me”
images thus tell the poster’s story: through them, patients
and caregivers maintain a visual diary, share a moment in
treatment, or represent the changes they observed in their
bodies. In other words: “this is my cancer”, “this is how I
have changed” or “this is who I am”. “Me” images engage
the viewer in the experience of cancer through the eyes of
the poster.
Conversely, “you” images are explicitly directed towards
the viewer. They aim to educate viewers about cancer,
whether it is through the discussion of healthy diets, by
reminding them to get checked by a doctor, or by advocat-
ing for more research. Thus, “this is what you should do”
. “You” images seek an attitudinal change with regards to
cancer in the viewer and sometimes contain cues to action.
While this and the first line are sometimes equivalent, they
are distinctly identifiable in the sample, as episodic images
can be both “me” and “you” framed.
Table 1 illustrates the angles and poles visible in each
paper, which are discussed in detail in the following pages.
First Discursive Line, Framing: Cancer as a
Personal Story or a General Theme
A personal story (episodic framing): tracking prog-
ress on treatment and visualising the journey
In the papers reviewed, some patients use images to keep a
“diary” of their cancer experience. Their photographs log
their progress, celebrate milestones, or count down to their
next chemotherapy session. Others present the evolution of
a loved one or a relative through treatment. Authors describe
this type of image as one with an episodic framing, where
posters “present an issue by offering a specific example or
experience (e.g., a firsthand narrative about one’s cancer
journey) […]” (Miller et al. 2019, p. 51).
The use of episodic framing is common in social media,
where “the lay public decides what to express and share
about their cancer experiences” (Cho et al., 2018, p. 8).
On Instagram, this type of image helps patients engage
in “self-measurement” (Stage, 2019a). They use visual
resources to point to an upcoming treatment session and to
track their progress on the road to recovery:
The term ‘self-measurement’ refers both to measurements
initiated by the poster (e.g. by posting a picture of hair mea-
surement) and processes of measurement initiated by others
(e.g. the medical system) that are articulated or visualized
by the patient on the profile. (Stage, 2019a, p. 78)
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Varela-Rodríguez and Vicente-Mariño
Stage (2019a, p. 88) illustrates this framing with an image
posted by one of his informants. In the image, the patient,
with a shaved head, is shown in hospital. With a broad
smile, her fingers signal the number nine, an allusion to the
ninth session of chemotherapy they are pictured at. The
caption, accompanied by a smiling emoji, mentions they
are looking forward to finishing treatment, with three more
sessions to go.
Patients appear to post this type of image regularly,
often including quantifiable elements to indicate progress:
hair (and its loss), medical equipment, fingers forming a
number that indicates how many chemotherapy sessions are
left… Together, they build the “journey” of cancer (Cherian
et al., 2020), a collection of “small stories” (Stage, 2019b)
that are presented by a single user but given meaning to in
cooperation with commenters, likers, and followers. Episodic
framing also appears to serve a therapeutic function:
Describing cancer as a journey [
…
] has been argued to min-
imize feelings of guilt or failure that are implicitly felt by
those who conceptualized themselves as ‘fighters’ or ‘war-
riors’ if treatment is ineffective. (Cherian et al., 2020, p. 9)
On Facebook, Ma & Yang (2022) describe the use of
exemplification, which can be linked to episodic framing.
Exemplars in images present relatable, personal stories and
specific events that resonate with viewers. They find that this
type of image intensifies emotional responses and motivates
behavioural intentions (íbid., p. 132).
Typically, and across the platforms studied, reac-
tions to episodic framing take on a positive tone, whereby
Table 1. Discursive lines that can be inferred from each paper
Framing: Cancer as a gen-
eral theme or as a personal
story
Emotion: An affective line
between optimism and
fear
Purpose: Addressing
the self or the other
Thematic Episodic Negative Positive “Me” “You”
Cherian et al. (2020) YES YES YES YES YES NO
Cho et al. (2018) NO YES YES YES YES YES
Gupta (2022) NO YES YES YES YES NO
Gürtler et al. (2022) YES NO YES YES NO YES
Hale et al. (2020) YES YES YES YES NO YES
Henderson et al. (2021) YES YES YES NO YES YES
Ma & Yang (2022) YES YES YES YES NO YES
Miller et al. (2019) YES YES NO NO NO YES
Miller et al. (2020) YES YES NO NO YES YES
Park et al. (2019) YES NO NO NO NO YES
Rivera et al. (2021) YES NO NO NO YES YES
Stage (2019a) NO YES YES YES YES NO
Stage (2019b) NO NO YES YES YES NO
Tetteh (2021) NO YES YES YES NO NO
Varela-Rodríguez & Vicente-Mariño (2021) NO YES NO NO YES NO
Wilner & Holton (2020) YES NO NO NO NO YES
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Cancer Images Social Media
commenters encourage the poster to “keep going” and show
their appreciation. This is particularly so when the post
shows signs of progress and a return to “normality” after
cancer. Stage calls this an “affective tailwind”: a feedback
loop whereby images aligned with the survivorship discourse
generate positive reinforcement that, in turn, motivates users
to continue deploying said discourse (Stage, 2019a, p. 89).
The tailwind extends to caregivers, family members, and
generally any user who shares the cancer story of their loved
ones (Hale et al., 2020).
Episodic images in the shape of journeys are most
common and most successful on Instagram (Cherian et al.,
2020; Henderson et al., 2021; Tetteh, 2021), where a closer
relationship between posters and viewers is common. On
this platform, episodic framing also appears to lead to higher
levels of engagement (Henderson et al., 2021, p. 5). This
type of image is not as common on Twitter or Pinterest,
where posters favour images rich in information and with a
thematic framing (Cherian et al, 2020; Miller et al., 2019).
Interestingly, the use of episodic images on Imgur con-
tains traits that are not reported for other platforms. Here,
photographs that discuss the cancer of another person or
of their pets are more common than self-referential images
(Hale et al., 2020, p. 6). In fact, when patients post their
own stories of cancer on Imgur, they receive less supportive
comments than when they post those of a loved one (human
or otherwise). Regardless, episodic images appear to retain
their affective tailwind against thematic publications (Hale
et al., 2020, p. 7).
Hale et al. discuss whether this effect may just reflect
viewers’ familiarity with the situation pictured. Those who
have not experienced cancer themselves may still empathise
with the emotional toll that it takes to have someone close
to you undergo cancer treatment or being ill. Further, the
design of Imgur around pseudonymity is appears to favour
anonymous stories of cancer, which may further limit the
use episodic framing. Lastly, Imgur is geared around “posts
[that] are generally brief and humorous” and the fact that
users tend to it for distraction does not favour the use this
framing (Hale et al., 2020, p. 10).
A general theme (thematic framing): communicating
facts and calling for action
On the opposite pole of this line are images that do not visu-
alise cancer as an individual’s journey, but instead present
information specific to a cancer site, its treatment, its preven-
tion, or its symptoms:
[
…
] a thematic pin may provide a summary of mammog-
raphy screening guidelines. (Miller et al. 2019, p. 53)
This thematic framing seems more common on Twitter
(Cherian et al., 2020) and on Pinterest (Miller et al., 2019;
2020). Thematic images lean on factual content, make inten-
sive use of text, and provide rich, often external information
to viewers. A common example are the guidelines and gen-
eral recommendations given in breast cancer images (Gürtler
et al., 2022; Miller et al., 2019).
The risk of misinformation hovers over thematic
images, as they often contain inaccurate information and
exaggerated claims (Gürtler et al., 2022, p. 157; Wilner
& Holton, 2020, p. 303). This risk is compounded by the
fact that thematic images on Instagram, Pinterest and
Facebook are often posted by individuals, and not by
health organisations (Henderson et al., 2021; Miller et al.,
2019; Rivera et al., 2021). For Miller et al. (2019) this is an
opportunity for more, better cancer communication and
education:
[
…
] the breast cancer conversation currently present on
Pinterest contains more than just superficial content and
inspirational images, and provides support for Pinterest as
a possible channel for promulgating health education and
promotion. (Miller et al., 2019, p. 565)
When it comes to the reception of thematic images, results
seem inconclusive. Information-heavy posts achieve higher
shares on Pinterest, where they are perceived positively
(Miller et al., 2019, 2020; Park et al., 2019). It also seems
that the inclusion of text within the image facilitates their
uptake on Facebook (Ma & Yang, 2022).
However, thematic framing on Instagram leads to lower
engagement (Henderson et al., 2021; Stage, 2019a). In fact,
images that visualise cancer or which discuss its negative
effects (both of which are described as important elements
of the Health Beliefs Model) seem to decrease the number
of likes on this platform (Cho et al., 2018).
This difference in perception is seen to be related to the
different affordances of these applications. While Instagram
is used to build deeper connections with others, Pinterest
appears as a resource to obtain and organise information.
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Varela-Rodríguez and Vicente-Mariño
On Facebook, users react positively to thematic images
posted by sources they trust. That is regardless of whether
they consider the source knowledgeable or simply because
they feel close to them, culturally or socially (Rivera et al.,
2021). Viewer-engagement on Facebook is also facilitated
by narrative and exemplar elements, such as personal sto-
ries that highlight the risks of cancer-related behaviours like
drinking alcohol (Ma & Yang, 2022). Thus, episodic and the-
matic framings work together.
Meanwhile, on Imgur factual information appears to
decrease engagement and support, especially when it is not
accompanied by identifiable people in the image (Hale et al.,
2020). Again, exemplars and personal messages appear to
support the social impact of thematic images.
The thematic frame is highlighted by papers that study
prevention and screening campaigns, and by those that
review the presence of the Health Beliefs Model, such as
Cho et al. (2018) or Miller et al. (2019; 2020). They find
that thematic images do not always come accompanied by
a cue to action, an important component to motivate pre-
ventive behaviour. Instead, fear-invoking images of the con-
sequences of cancer or miracle-diets may be presented, both
of which are often ignored by viewers (Miller et al., 2019, p.
56) and limit the impact of this framing.
Second Discursive Line, Emotion: An Affective
Line between Optimism and Fear
Positive emotions: celebrating milestones and the
hope for restitution.
Positive emotions are a staple of the cancer survivorship
discourse, where the patient is shown as hopeful, strong,
and willing to “fight”. In social media, they often take the
shape of hope, strength, joy and bravery (Cho et al., 2018;
Henderson et al., 2021).
In the sample, optimism is visually contrasted with signs
of treatment and cancer symptoms. In a picture shown by
Stage (2019b, p. 278), an Instagram user who has undergone
a double mastectomy sunbathes with a lush lawn behind her.
Her smile and her skin, lit and tanned by the sun, contrast
with the visible scars left by the intervention. The patient
reflects on this contrast in the caption while she reaffirms
her identity and highlights the positive aspects of no longer
having breasts. Stage discusses the impact of this optimistic
framing, and notes that 7 out of the 10 most-liked posts in
this patient’s feed were images showing her “bare-chested,
with one or two breasts removed, while smiling” (2019b,
p. 278).
Visualising restitution is arguably one of the functions of
social media most visible across the sample. Gupta (2022),
Stage (2019a, 2019b) and Cherian et al. (2020) describe how
cancer patients picture themselves as hopeful and optimistic
in their fight towards regaining the normality that cancer has
taken away from them. Bodies become the canvas for such
a struggle, contrasting the impact of cancer with smiles, gri-
mace and other elements that reveal posttraumatic growth
(Cherian et al., 2020) or even renewal through cancer (Stage,
2019a). When posters stay hopeful, some viewers appreciate
it with their likes.
Positive images are thus often intertwined with episodic
framing and are used to celebrate milestones in treatment
and share moments of joy. Patients invite their followers to
join in celebration and accompany their hope for a return to
life as it was before cancer. This type of framing is reminis-
cent of the survivorship discourse, which presents patients
as brave and positive fighters. This discourse is salient on
key dates such as World Breast Cancer Day (Cherian et al.,
2020). It is sometimes found to promote a normative dis-
course on femininity, using the female body to get attention
and showing highly stylised images of young and healthy
women (Gürtler et al. 2022, p. 157-158).
The results of positive framing vary depending on the
platform. Conducting a large-scale study, Cho et al. (2018,
p. 9) find that it does not increase the number of likes on
Instagram, while Stage’s (2019b) study of a patient’s feed sig-
nals that positivity does seem to increase likes. On Instagram
and Twitter, Cherian et al. (2020) find that positive fram-
ing performs best when it challenges dominant discourses,
showing that cancer patients can also be happy and self-ful-
filled despite their illness.
Once again, Imgur is in stark contrast with the other plat-
forms: despite taking on a positive attitude to coexist with
cancer or regain normality, patients who share optimism on
this platform are met with fewer and less supportive com-
ments than those sharing negative emotions. Hale et al.
speculate that this difference may be due to the fact that
audiences on Imgur are often unfamiliar with the poster, and
thus do not feel attached to their story (Hale et al., 2020):
Agentive problem solving and positive reappraisal indicate
a positive or healthy transformation in the poster’s mindset
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Cancer Images Social Media
(e.g.,”I have decided to take charge and try something new”;
“I have now developed a new outlook on life”) and thus
could have more impact for familiar and intimate audi-
ences, which are more likely to provide empathic support
[
…
]. Hale et al. 2021, p. 10
The key seems to lie not on the specific emotion visual-
ised, but on whether the image presents a positive outlook
towards being cured and whether it highlights the positive
outcomes and learnings from cancer (Cho et al., 2018; Hale
et al., 2020). Why? Perhaps because viewers believe that post-
ers who share these perspectives are more open to feedback
and support, or because such attitudes are culturally more
acceptable and a better fit to the economy of social media:
The ability to transgress the hardships of illness and insist
that the present and future is a space for self-cultivation and
struggle aligns more effectively with the attention economy
of social media, where affective clicking motivates further
visibility. (Stage, 2019a, p. 96)
Regardless of their effect on viewers, positive framing is dis-
cussed in the papers as therapeutic for posters, as long as
they are not forced to fit a discourse that is not aligned with
their own experience and they feel like they have the space
to share negative emotions, too (Cherian et al., 2020; Tetteh,
2021).
Negative emotions: expressing fear and uncertainty
The visualisation of cancer inevitably carries negative emo-
tions, either because patients and caregivers need to express
their fear, anger and frustration or because these may be used
as a device to deter consumers from engaging in cancer-re-
lated behaviours. The papers studied consider negative emo-
tions through the depiction of fear, anger and sadness (Cho
et al., 2018, p. 4), as well as through the sharing of fear-in-
voking images. They also discuss images that explicitly men-
tion the possibility of death and the fragility of life.
In some cases, negative emotions result in comments
that show compassion and empathic support, strengthen-
ing the use of social media for community-building. This is
particularly so for Imgur, where negative images seem to be
expressed more often than in other platforms (Hale et al.,
2020, p. 10).
On Instagram, images with negative emotions achieve
fewer likes but unlock conversations. Especially when they
have a close relationship with the poster, viewers respond to
this type of image with more comments (Cho et al., 2018,
p. 9):
While the ‘most liked’ list primarily consists of posts that
present news of progression that can be supported, the
‘most commented’ list also consists of posts that present
news of progress being threatened or stalled. (Stage, 2019b,
p. 280)
The role of negative emotions challenges dominant dis-
courses, particularly the discourse of survivorship. Patients
turn to crude images to establish visual contrast with com-
mercial images that show them as heroic, beautiful and opti-
mistic (Gupta, 2022; Gürtler, 2022). While they may limit
the reach of the image, negative emotions help patients feel
accompanied and validated. The experience of celebrities
and influencers is particularly impactful here. Reviewing
Elly Mayday’s images of ovarian cancer, Tetteh reflects on
how her images in the hospital, bruised and with multiple
syringes connected to her body, brought the restitution nar-
rative to question:
Given such a cultural context, it is particularly imperative
that Elly did not hide some of these personal details about
her ovarian cancer experience and by that, forced society to
make space for and consider these not-too-pleasant experi-
ences as legitimate part of the ovarian cancer experience.
(Tetteh, 2021, p. 10)
When faced with this type of image, more graphic and less
positive in nature, viewers on Instagram may take one of two
routes. Some may look away, or even unfollow the poster,
as was the experience of Mayday; others offer what Stage
defines as “supportive disalignment”, helping the poster
re-focus their attention on the positive and giving them hope
for the future:
If posts divert from the desired narrative over a period of
time, it can be argued that the poster is forced to engage in
acts that reposition the overall story he or she hopes to tell in
the future. (Stage, 2019b, p. 281)
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Varela-Rodríguez and Vicente-Mariño
On Twitter, patients choose to “emphasize the difficulties
[…] that are often glossed over” (Cherian, 2020, p. 11) in
cancer communications. On Pinterest, where thematic
images are more common, negative emotions are expressed
through fear images, meant to motivate behavioural change.
Overall, papers argue that enabling the expression of
negative emotions is important to ensure a more inclusive
representation of cancer online (Cherian et al., 2020, p. 12;
Varela-Rodríguez & Vicente-Mariño, 2021b, p. 15), espe-
cially for cancer sites that have been subject to gendered
and romanticised representations in popular media, such
as breast cancer (Gupta, 2022; Gürtler, 2022; Tetteh, 2021).
However, the use of these emotions comes at a cost, typically
with lower engagement and, consequently, visibility:
[T]he women who post about [triple negative breast cancer]
may be aware of the lower engagement with posts that may
appear negative, therefore opting to potentially mask their
real feelings by posting content that provides a silver lining
in a negative post. (Henderson, 2020, p. 6).
Third Discursive Line, Purpose: Addressing the
Self (“Me”) or the Other (“You”) in Cancer
Images
“Me”: defending and reassessing identity and nor-
malising cancer
Across the papers, photography is understood as a tool for
self-expression, which patients use not only to communicate
with others but to better understand themselves. Cancer is
a profoundly life-altering illness, which entails a change in
identity for patients (Gupta, 2022, p. 222). Social media
images allow them to express themselves, visualise their rela-
tionship with cancer, and perform their persona. The “me-
you” discursive line evaluates this function by reviewing the
purpose and the ‘addressee’ of the image: is the image meant
to express my experience and represent me, as the poster,
or is it meant to inspire a change in attitude from you, the
viewer? It is often the case that the answer lies somewhere in
between both poles.
When it comes to forming and affirming the self (“me”),
posting a photograph on social media can help regaining a
sense of certainty and challenge the aggression of cancer
(Gupta, 2022, p. 218). Stage (2019a) outlines two functions
for Instagram pictures in this regard. The first is that of
self-tracking: episodic images, typically in sequence, that help
patients keep a visual diary and monitor their own progress.
The second function is simply for patients to see how
their body changes, without necessarily establishing a con-
versation with other images. Stage refers to this as “self-ex-
perimentation” (Stage, 2019a, p. 78); Gupta speaks of
performed patienthood, a form of self-negotiation that often
involves a disconnection between the self and the body.
Cancer is an invasive illness that affects patients’ perception
of themselves: the loss of hair and weight, and they transfor-
mation of their capacities is a traumatic process. The photo-
graphic camera and the reactions from viewers help patients
regain agency and control over their own image (Gupta,
2022, p. 222; Cherian et al, 2020, p. 8). Posting images to
social media also lets them reflect on their personal relation-
ships (Tetteh, 2021, p. 11) and create their own definition of
cancer (Cho et al., 2018, p. 2).
Across the spectrum, “me” images see patients taking
the lead in shaping their own understanding of what being
a patient means. While these photographs may have an
implicit function to inform others, they are self-expressing at
their core. Cho et al. (2018, p. 9) find that this is particularly
true for images with positive emotions on Instagram, which
help modify the posters’ beliefs and keep them in high spirits.
Similar findings are made by Cherian et al.:
[T]he most popular posts represented the line between treat-
ment and survivorship as a return to previous appearance
and functional status, with many posts emphasizing “#thi-
sisme”. (Cherian et al., 2020, p. 10)
On Imgur, “me” images present the poster through agentive
problem-solving or positive re-appraisal, expressing a change
in attitude or a new outlook on life (Hale et al., 2020, p. 10).
Through this line, posters establish a visual conversation
with leading social discourses, and evaluate how these fit
into their own experience. Sometimes, they adopt the survi-
vor or warrior identity. Other times, they reject that identity
and present themselves as vulnerable and afraid, accepting
that cancer is a life-long illness (Gupta, 2022, p. 225). Often,
positive emotions help counter the visual impact of cancer
symptoms and consequences, allowing the poster to be more
than a patient:
[P]osts contrast scarring and hair loss, which are convention-
ally depicted as tragic, with smiles and hopeful expressions
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Cancer Images Social Media
that call into question the experience of cancer treatment as
unremittingly negative. (Cherian et al., 2020, p. 11)
The embodiment of cancer is another crucial part of self-ne-
gotiation in “me” images. Typically, auto-pathographies
visualise identity through aesthetic or bodily changes over
time. It is common for patients to use “dramatic before-
and-after images contrasting the aesthetics of treatment and
post-treatment” (Cherian et al., 2020, p. 12). But patients
also use these images to dissociate and abstract themselves
from the illness:
Hair becomes the most visible platform for this contestation
where the affective tensions between the I (the embodied
self) and the It (the physiology of cancer, its own life force)
becomes most pronounced. (Gupta, 2022, p. 222)
“Me” images are thus a constant negotiation between the
poster’s desired identity, the actual content of the image, and
how followers react to them, which in turn further reinforces
or challenges the poster’s desired identity (Stage, 2019b, p.
276).
Engagement with this type of image appears to be high on
Imgur, especially when there are people in the frame (Hale
et al., 2020), and on Instagram (Cho et al., 2018; Tetteh,
2021). When posted by trusted community leaders, “me”
images are also effective on Facebook (Rivera et al., 2021).
For posters who transform their social media into a
visual diary of cancer, “me” images come with costs, too.
When treatment is complete, they may experience what
Stage (2019b) calls a “crisis of tellability”: should I continue
posting images? How will my identity change now that I
am cured? What is my relationship with my followers after
treatment?
We have not found specific mentions to “me” framing on
papers dedicated to Pinterest. However, given that thematic
images are more common there than episodic photographs,
and given the use of Pinterest for “visual curation” (Park
et al., 2019, p. 9), we may speculate that “me” images are not
common on this platform.
“You”: education and activism
Opposite to self-expressive photographs are images that
focus on the viewer and contain cues to action. Admittedly,
this could appear as just another term for thematic framing,
yet episodically framed images may also fit within this cat-
egory. A selfie showing progress in treatment and explicitly
asking the viewer to get checked by a doctor would be epi-
sodic and “you” framed.
“You” images call others to action, raise awareness on
prevention, and try to motivate screening. Typically, they
also contain information about the negative consequences
of cancer. These are, for instance, posters and infographics,
or images that make a personal appeal to viewer’s responsi-
bility and self-care (often in captions). In the sample, they
are discussed in relation to the Health Beliefs Model and to
misinformation on cancer prevention.
“You” images are important to increase the perception
of self-efficacy amongst viewers (Gürtler et al., 2022; Ma &
Yang, 2022; Miller et al., 2019, p. 56) and to motivate pre-
ventive behaviours. In their review of breast cancer commu-
nications on Pinterest, Miller et al. (2019) find that thematic
images rarely contain such cues. Park et al. (2019, p. 7) find
that, on Pinterest, “you” messaging works best when it con-
tains people in frame, explanatory texts, and rich informa-
tion. Meanwhile, images that discuss cancer as a threat are
often ignored on this platform:
Messages that contain primarily perceived threat compo-
nents (i.e., severity and susceptibility) are more likely to
result in people ignoring the message and not adhering to
the recommendation. (Miller et al., 2019, p. 56).
Rivera et al. (2021) find that, on Facebook, viewers do
engage with this type of content if they are connected to
the person or group who posted it, or when shared by a
respected figure, suggesting that personal ties lead to higher
trust in the content posted. On Imgur, calls for check-ups
or screening led to lower support and engagement, as they
are perceived as an intrusion into a moment of browsing
that should be fun and relaxed (Hale et al., 2020, p. 10). On
Instagram, “you” images are not often accompanied by con-
structs of the Health Belief Model (Henderson et al., 2021);
when they are, they reduce the likelihood for engagement
(Cho et al., 2018). It thus appears that “you” images face
resistance across the platforms studied.
The framing of “you” messages is also affected by the
high prevalence of misinformation in cancer images online.
Wilner & Holton (2020) find that more than half of the
posts on Pinterest that contained information about breast
cancer also contained misinformation, typically through
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Varela-Rodríguez and Vicente-Mariño
exaggeration, which may further limit the impact of this
type of image. This risk is only higher given the absence of
health organisations from platforms like Pinterest (Miller,
2019; 2020) or Facebook (Rivera et al., 2021), and given the
misalignment of cancer prevention contents with medical
recommendations (Gürtler et al., 2022).
Discussion
The study of social media images that visualise cancer
remains a field in development. While many papers deal
with text and even video transcript in social media, few—
to the author’s knowledge, as few as 16—attempt an image
content or discourse analysis. Yet relevant results can be
extracted from them.
On the Representation of Cancer Sites
The fact that breast cancer has more presence in the sample is
explained by the great amount of work done since the 1970s
to raise public attention on its prevalence and the importance
of research and prevention. While they are no strangers to
criticism (see, for instance, Bell, 2014; Sweeney & Killoran-
McKibbin, 2016), breast cancer awareness campaigns have
activated multiple mechanisms for attention in popular
media, developed a clear visual identity, built successful
messages of resilience and survivorship, and achieved the
support of large businesses. Breast cancer has thus been put
at the centre of public awareness on cancer generally and,
consequently, users today are relatively comfortable sharing
contents that mention this site. As a result, images of breast
cancer are commonplace in social media, especially in the
month of October.
In addition, breast cancer has been subject to numer-
ous studies on representation, and special attention has
been given to the importance of communities of patients.
While similar studies have been conducted for other sites,
the volume of papers remains low in comparison (Koskan
et al., 2014). The sheer number of breast cancer images in
social media dwarves other cancer sites (Varela-Rodríguez
& Vicente-Mariño, 2021b), while the widespread use of
visual tropes that are easy to identify (such as pink ribbons)
may further compound its higher visibility. In addition,
cancer sites that affect primarily women appear to be more
visible in social media overall, which Cherian et al. interpret
as a consequence of “the norms surrounding masculinity
that deter disclosure, even in private” (Cherian et al., 2020,
p. 11).
On Method
The difference between qualitative and quantitative
approaches leads to different results in the analysis.
Quantitative studies provide an answer to a question of
“what”: what do posters share to visualise cancer, and what
is the engagement with such posts? In contrast, qualitative
studies provide answers to “how”: how do patients present
themselves and their illness, and how does that affect others?
Where the former fall short in capturing the experiences of
individual patients, the latter tend to look at common sus-
pects and achieve results with limited significance for other
sites. Bridging the two approaches can help facilitate a com-
munication of cancer that is impactful and inclusive.
Inspiration may be sought in existing work on cancer pre-
vention, where visual communication of smoking, vaping,
tanning or the HPV vaccine have received more attention.
These are fields where even machine learning algorithms
have been used in conjunction with qualitative methods.
Admittedly, detecting a cigarette or a syringe in an image
may be easier than detecting a visual representation of
cancer, which is a general term that is compounded by mul-
tiple illnesses, emotions, and life experiences.
Further developing the three discursive lines identified
in this meta-synthesis may serve as a starting point. At the
very least, they could guide the design of cancer communi-
cations by helping to predict some of the impact that images
may have on viewers, and on the patients and relatives who
posted them, too.
Three Discursive Lines
Figure 4 condenses the three discursive lines that emerged
in this paper. They translate into a three-dimensional plot
where images could be located—not without some difficulty.
Images may be more episodic, “me” framed and positive, or
the complete opposite.
The first line, episodic vs thematic framing, can be used to
understand patient messaging and psychosocial needs. Their
use and impact seem to be tied to platform affordances: the-
matic framing is well-received in social media that are not
based on interpersonal connections but rather on browsing
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Cancer Images Social Media
Figure 4. The three discursive lines for images of cancer in social media that emerge from a meta-synthesis of the 16 papers studied
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Varela-Rodríguez and Vicente-Mariño
and collecting content (such as Pinterest and Imgur). They
are also received positively on Facebook when the poster is
a trusted organisation or a closer acquaintance. Conversely,
episodic framing has a measurable impact on Instagram,
where viewers follow the experience of their friends or of
the people they admire (celebrities, influencers), and where
they are actively encouraged to comment and like.
The second discursive line, between positive and nega-
tive emotions, returns inspiring results. Part of the litera-
ture is critical of the social media economy, arguing that it
puts pressure on patients to share a specific discourse (that
of survivorship) that favours positive images (Stage, 2019a;
Henderson et al., 2021). Images where patients count down
to life as it was before cancer, show a thumbs up from their
chemotherapy session, or appear in frame with scars and a
smile do reflect a push towards restitution. Indeed, positive
emotions are more often expressed across all social media
studied. The design of social media platforms is also shown
to favour unobtrusive cancer sites that permit visually-
appealing images, sites that are well-known, and privileged
groups, with higher technological competencies or gen-
erally more representation in social media (Miller et al.,
2019; Park et al., 2019; Rivera et al., 2021; Stage, 2019b).
Symptomatic of this, argues Stage (2019a), is how viewers
react to posts outside dominant discourses on Instagram.
When a post shows fear or uncertainty, commenters redi-
rect them to a socially desirable narrative of cancer: they
reassure posters and encourage them to stay hopeful. Tetteh
(2021) echoes these observations, while Varela-Rodríguez &
Vicente-Mariño (2021b) provide some quantitative support
by visualising the unequal distribution of cancer sites on
Instagram.
However, results also show that social media can offer a
positive space for the broader spectrum of emotions associ-
ated with cancer (Cho et al., 2018; Hale et al., 2020; Park
et al., 2019). On Instagram, Pinterest and Imgur, negative
emotions and even the discussion of mortality have a space,
and images that make use of them are met with supportive,
reassuring, and compassionate comments. Cho et al. (2018)
demonstrate that negative emotions are better at generating
comments (thus conversation), while Hale et al. (2020) show
how commenters offer compassion to posters who are shar-
ing their anxiety over treatment. For patients, this means
that, even if they do not align with survivorship or if they
struggle with the social imperative to remain optimistic, and
even if their images may not reach the influential status of
more positive ones, they can find support in social media.
Importantly, however, this may be true for well-represented
groups, while underrepresented peoples continue to swim
against the tide (Rivera et al., 2021).
This second discursive line (positive vs negative emo-
tions) is important to achieve a more inclusive representation
of cancer. It may facilitate the inclusion of underprivileged
groups and give visibility to lesser-known cancer sites, while
speaking to patients beyond standardised discourses.
For cancer screening and prevention, the use of negative
emotions should be approached carefully. By favouring images
that insist on the physical and emotional consequences of
cancer, such as fear-invoking photographs, campaigns could
run the risk of falling into shock advertisement. They may
also stigmatise patients. An example may be found in anti-to-
bacco campaigns: while the use of shock images may have
deterred consumption, it may have also contributed to plac-
ing blame on lung cancer patients (Riley et al., 2017).
It is also important to note that discourses by patients
who feel represented in scars and other bodily manifesta-
tions of cancer are not representative of all cancer experi-
ences. Popular imagery, especially around breast cancer,
made a positive move towards the 1990s by incorporating
more diverse groups and reducing the blame on patients
(Andsager et al., 2001). Building a more representative
image of cancer does not entail going back to images where
cancer is only visible as scars or trauma, but instead creating
a space that allows for the representation of the broad spec-
trum of cancer experiences, whether those imply visualising
hope or fear, or both.
Lastly, the third discursive line (“me” vs “you”) estab-
lishes that posts framed through “me” messaging (sharing
personal experience) are effective on Instagram and Imgur.
They are amplified when posted by celebrities who are vocal
about their cancer, which can create an image of cancer that
is closer to the broader reality of the illness. Meanwhile,
“you” messages remain ever-important for screening and
prevention, as well as for informational support to patients.
They are most impactful on Pinterest or Twitter, while they
struggle to become visible on Instagram or Imgur.
An Image of Cancer in Social Media… without
Images?
A final consideration, one that is striking to us as authors,
is how images are absent from the majority of the 16 papers
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Cancer Images Social Media
studied. Only 6 of them use images from their samples to
communicate results.
Most of the papers point to ethical challenges to explain
the absence of images. Social media studies undertake an
analysis of data that is often disjointed and great in scale,
which makes it complex to obtain consent. Further, the
images studied are, after all, deeply personal, and there are
few mechanisms to deidentify them as one could do with
quotations from an interview. One method is used by Varela-
Rodríguez and Vicente-Mariño, who collapse together the
images in their study so that they are virtually impossible
to identify but retain some information (mainly colour).
Stage, on the other hand, uses sample images that are per-
fectly identifiable, having obtained informed consent from
his research subjects to do so.
There are also technical challenges to obtaining images,
as social media platforms limit access for researchers. In
addition, reproducing social media images, although public
in the sense that they are available to public viewers, leads
to a legal dead-end that is yet to be resolved. This is a recur-
ring challenge in social media studies, and it is even more
pressing for the obtention, storing and study of images (see
Varela-Rodríguez & Vicente-Mariño, 2021a).
That said, all the papers studied engage in a generous,
in-depth analysis of images, either quantitatively or quali-
tatively. Yet we cannot help but wonder if accompanying
said analysis with sample images could strengthen their
results.
Implications for Further Research and Future
Developments
The implications of this research are several. Firstly, we
have established that images in social media are an import-
ant vehicle for sense-making, identity-formation, and
community- building for cancer patients. Researchers will
find a fruitful field here. Before that, however, more work is
needed to develop methods for social media image analysis.
In particular, the automation of some of this work (both in
terms of image-download and image-processing) can help
(see Varela-Rodríguez & Vicente-Mariño, 2021a). There are
important technical and ethical considerations to bear in
mind, including the constant changes in the Terms of Use
of social media platforms, the grey area that is social media
data ownership and access by researchers, and the challenges
in obtaining informed consent when conducting large-scale
studies.
Secondly, challenging the divide between qualitative and
quantitative methods and relying on mixed approaches have
been shown to be productive. Social media are particularly
ripe for this type of work. Future work could explore the use
of automated searches that can then be analysed in-depth
through interviews and focus groups, similar to the method
used by Rivera et al. (2021; 2022). Likewise, reviewing quan-
titative findings with posters and viewers can provide richer
information on user-intention and impact. Social media
research thus appears to be a potentially fruitful field to con-
nect the biomedical and social sciences.
Thirdly, multi-platform studies may risk obtaining a
biased picture if they neglect the affordances of said plat-
forms. The different expectations users have for each plat-
form may explain the disparities observed on Instagram,
Pinterest and Imgur. Future work may look to conduct
cross-platform research while being mindful of each plat-
form’s audience and functionalities.
Fourthly, researchers studying visual communications
should be well-positioned to strengthen their own use of
images to reinforce textual narratives. If our object of inter-
est are images, it appears reasonable to use them as part of
our communication.
Lastly, the three-dimensional grid we have developed
with the three discursive lines may help analyse social media
images of cancer qualitatively, while offering some value
towards predicting their engagement. Future work may look
to validate, modify, or improve these three lines, developing
specific criteria for each line and contrasting the engagement
for each type of image.
As visual social media continue to grow, it seems reason-
able to expect them to continue playing a key role in the com-
munication of cancer. Given their rapid development, it is
likely that new papers dealing with the topic are published in
the next few years. Future research may also consider works
developed in other formats, such as communication cam-
paigns run by cancer organisations, or lager-format books.
Academic works like Carsten Stage’s Networked Cancer are
outside the scope of this paper but are an important source of
knowledge. Similarly, the work of Stephanie Plage, although
not focused on social media, offers great insight into visual
cancer discourses by a variety of patients (Plage, 2021).
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Limitations
This research is limited by the small number of papers avail-
able in this field, or, at least, the number of papers we could
identify with the queries defined and the resources available.
Some relevant documents known to the authors were left
out as they were not part of the search or had a format that
was not included—most notably Carsten Stage’s exploration
of the topic in the book Networked Cancer (Stage, 2018).
By narrowing the search to very exclusive criteria (journal
papers AND images AND cancer AND social media) we
have made it possible to undertake a deeper analysis but had
to leave out works that we hope to return to in the future.
In addition, the lack of previous systematic reviews on
this topic does not allow to build on existing knowledge, but
instead generate new ideas that will be tested by time and,
surely, need to be updated.
Conclusions
This review presented an in-depth analysis of 16 papers that
address the use of images in social media to communicate
cancer.
Overall, the papers study at least three discursive lines
that are followed by the images in their studies. The first line,
between episodic and thematic framing, considers the differ-
ent impact that images have depending on whether they pres-
ent cancer as a journey or as an individual topic. Episodic
image are individual, personal images, where patients show
progress. Thematic images contain text and present general
information about cancer or its prevention. Thematic images
are more successful on Pinterest or Twitter, while Instagram
favours episodic images. Imgur returns interesting results
as episodic images often present cancer stories from other
people, instead of the poster’s.
The second line considers the different impact that pos-
itive and negative emotions have on viewers on the differ-
ent platforms. Positive emotions are found to receive more
likes on sites like Instagram, and to be generally more
“agreeable” as they align better with dominant discourses.
However, negative emotions still have a place in social
media, and are met with empathic support and compas-
sionate comments on Imgur or Facebook and are reshared
on Pinterest.
Lastly, the third line considers the primary purpose of
the images, whether it is to present the poster’s experience
(“me” images) or to motivate action from the viewer (“you”
images). The former seem to perform better on most of the
platforms, whereas “you” images are often perceived as
intrusive.
References
Acal Díaz, I. (2015). Metodologías para el análisis de la imagen fija en los documentos publicitarios: Revisión y aplicaciones.
Revista General de Información y Documentación, 25(2), 425–446. https://doi.org/10.5209/rev_RGID.2015.v25.n2.51243
Andsager, J. L., Hust, S. J. T., & Powers, A. (2001). Patient-Blaming and Representation of Risk Factors in Breast Cancer
Images. Women & Health, 31(2–3), 57–79. https://doi.org/10.1300/J013v31n02_03
Attai, D. J., Cowher, M. S., Al-Hamadani, M., Schoger, J. M., Staley, A. C., & Landercasper, J. (2015). Twitter Social Media
is an Effective Tool for Breast Cancer Patient Education and Support: Patient-Reported Outcomes by Survey. Journal of
Medical Internet Research, 17(7), e4721. https://doi.org/10.2196/jmir.4721
Banerjee, S. C., D’Agostino, T. A., Gordon, M. L., & Hay, J. L. (2018). “It’s Not JUST Skin Cancer”: Understanding
Their Cancer Experience From Melanoma Survivor Narratives Shared Online. Health Communication, 33(2), 188–201.
https://doi.org/10.1080/10410236.2016.1250707
Banerjee, S. C., Rodríguez, V. M., Greene, K., & Hay, J. L. (2019). Trending on Pinterest: An examination of pins about skin
tanning. Translational Behavioral Medicine, 9(4), 737–748. https://doi.org/10.1093/tbm/iby036
Barthes, R. (1977). Rhetoric of the Image. In R. Barthes & S. Heath (Eds.), Image, music, text: Essays (13. [Dr.]). Fontana.
Beaudoin, C. E., & Tao, C.-C. (2007). Benefiting from social capital in online support groups: An empirical study of cancer
patients. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 10(4),
587–590. https://doi.org/10.1089/cpb.2007.9986
59 2023, 11, 33–64
Cancer Images Social Media
Bell, K. (2014). The breast-cancer-ization of cancer survivorship: Implications for experiences of the disease. Social Science &
Medicine, 110, 56–63. https://doi.org/10.1016/j.socscimed.2014.03.031
Bender, J. L., Katz, J., Ferris, L. E., & Jadad, A. R. (2013). What is the role of online support from the perspective of facil-
itators of face-to-face support groups? A multi-method study of the use of breast cancer online communities. Patient
Education and Counseling, 93(3), 472–479. https://doi.org/10.1016/j.pec.2013.07.009
Brinker, T. J., Schadendorf, D., Klode, J., Cosgarea, I., Rösch, A., Jansen, P., Stoffels, I., & Izar, B. (2017). Photoaging
Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study. JMIR MHealth and UHealth, 5(7), e101.
https://doi.org/10.2196/mhealth.8231
Britten, N., Campbell, R., Pope, C., Donovan, J., Morgan, M., & Pill, R. (2002). Using meta ethnography to synthesise
qualitative research: A worked example. Journal of Health Services Research & Policy, 7(4), 209–215. https://doi.org/
10.1258/135581902320432732
Capewell, C., Ralph, S., & Symonds, M. (2020). Listening to women’s voices: Using an adapted photovoice methodology to
access their emotional responses to diagnosis and treatment of breast cancer. Journal of Patient Experience. https://doi.org/
10.1177/2374373520930463
Cherian, R., Le, G., Whall, J., Gomez, S., & Sarkar, U. (2020). Content shared on social media for national cancer survivors
day 2018. PLoS ONE, 15(1). https://doi.org/10.1371/journal.pone.0226194
Cho, H., Silver, N., Na, K., Adams, D., Luong, K. T., & Song, C. (2018). Visual Cancer Communication on Social Media:
An Examination of Content and Effects of #Melanomasucks. Journal of Medical Internet Research, 20(9), e10501.
https://doi.org/10.2196/10501
Chou, W.-Y. S., Trivedi, N., Peterson, E., Gaysynsky, A., Krakow, M., & Vraga, E. (2020). How do social media users pro-
cess cancer prevention messages on Facebook? An eye-tracking study. Patient Education and Counseling, 103(6), 1161–1167.
https://doi.org/10.1016/j.pec.2020.01.013
Delgado-López, P. D., & Corrales-García, E. M. (2018). Influence of internet and social media in the promotion of alterna-
tive oncology, cancer quackery, and the predatory publishing phenomenon. In Curēus (Vol. 10, Issue 5). CUREUS INC.
https://doi.org/10.7759/cureus.2617
Döbrössy, B., Girasek, E., Susánszky, A., Koncz, Z., Győrffy, Z., & Bognár, V. K. (2020). “Clicks, likes, shares and comments”
a systematic review of breast cancer screening discourse in social media. PloS One, 15(4), e0231422. https://doi.org/
10.1371/journal.pone.0231422
Falisi, A. L., Wiseman, K. P., Gaysynsky, A., Scheideler, J. K., Ramin, D. A., & Chou, W.-Y. S. (2017). Social media for
breast cancer survivors: A literature review. Journal of Cancer Survivorship, 11(6), 808–821. https://doi.org/10.1007/
s11764-017-0620-5
Gentile, D., Markham, M. J., & Eaton, T. (2018). Patients With Cancer and Social Media: Harness Benefits, Avoid Drawbacks.
Journal of Oncology Practice. https://doi.org/10.1200/JOP.18.00367
Gómez-Arrieta, N. R., & Silva-Salazar, Y. N. (2017). La fotografía terapéutica como forma de re-significación del cuerpo con
mastectomía. Kepes, 14(15), 141–172. https://doi.org/10.17151/kepes.2017.14.15.6
Gupta, N. (2022). The afterlife of breast cancer: Exploring the digital performativity of post-treatment patienthood. Journal
of Creative Communications, 17(2), 216–230. https://doi.org/10.1177/09732586211048243
Gürtler, S. V., Rodríguez-Tablado, M., Weisbrot, M. A., Ruiz-Yanzi, M. V., Kopitowski, K. S., & Terrasa, S. A. (2022).
Análisis cuantitativo y cualitativo de las campañas argentinas de prevención de cáncer de mama difundidas mediante
imágenes fijas en redes sociales durante octubre del 2019. Revista Peruana de Medicina Experimental y Salud Pública, 39(2),
152–160. https://doi.org/10.17843/rpmesp.2022.392.11019
Grant, J. A., & Hundley, H. (2008). Fighting the Battle or Running the Race? Visual Communication Quarterly, 15(3), 180–195.
https://doi.org/10.1080/15551390802235578
Greenhalgh, T., & Peacock, R. (2005). Effectiveness and efficiency of search methods in systematic reviews of complex
evidence: Audit of primary sources. BMJ (Clinical Research Ed.), 331(7524), 1064–1065. https://doi.org/10.1136/
bmj.38636.593461.68
60
www.rcommunicationr.org
Varela-Rodríguez and Vicente-Mariño
Hale, B. J., Collins, R., & Kilgo, D. K. (2020). Posting about cancer: Predicting social support in imgur comments. Social Media
and Society, 6(4). https://doi.org/10.1177/2056305120965209
Han, C. J., Lee, Y. J., & Demiris, G. (2018). Interventions Using Social Media for Cancer Prevention and Management: A
Systematic Review. Cancer Nursing, 41(6), E19–E31. https://doi.org/10.1097/NCC.0000000000000534
Hawkins, A. H. (1999). Reconstructing illness: Studies in pathography (2nd ed). Purdue University Press.
Highfield, T., & Leaver, T. (2016). Instagrammatics and digital methods: Studying visual social media, from selfies and GIFs
to memes and emoji. Communication Research and Practice, 2(1), 47–62. https://doi.org/10.1080/22041451.2016.1155332
Henderson, A., Miller, C. A., Sutton, A. L., & Guidry, J. P. D. (2021). #TripleNegativeBreastCancer on Instagram. Health
Education & Behavior : The Official Publication of the Society for Public Health Education, 48(5), 567–574. https://doi.org/
10.1177/1090198120985450
Hoeck, B., Ledderer, L., & Ploug Hansen, H. (2017). Dealing with cancer: A meta-synthesis of patients’ and relatives’ expe-
riences of participating in psychosocial interventions. European Journal of Cancer Care, 26(6), e12652. https://doi.org/
10.1111/ecc.12652
Houts, P. S., Doak, C. C., Doak, L. G., & Loscalzo, M. J. (2006). The role of pictures in improving health communication:
A review of research on attention, comprehension, recall, and adherence. Patient Education and Counseling, 61(2), 173–190.
https://doi.org/10.1016/j.pec.2005.05.004
Kearney, M. D., Selvan, P., Hauer, M. K., Leader, A. E., & Massey, P. M. (2019). Characterizing HPV Vaccine Sentiments
and Content on Instagram. Health Education & Behavior : The Official Publication of the Society for Public Health Education,
46(2_suppl), 37–48. https://doi.org/10.1177/1090198119859412
Ketonen, V., & Malik, A. (2020). Characterizing vaping posts on instagram by using unsupervised machine learning.
International Journal of Medical Informatics, 141, 104223. https://doi.org/10.1016/j.ijmedinf.2020.104223
Kress, G. R., & Leeuwen, T. van. (2010). Reading images: The grammar of visual design (2. ed., reprinted). Routledge.
King, S. (2008). Pink ribbons, Inc.: Breast cancer and the politics of philanthropy. University of Minnesota Press. https://amzn.
com/dp/B00IK7WS4G
Koskan, A., Klasko, L., Davis, S. N., Gwede, C. K., Wells, K. J., Kumar, A., Lopez, N., & Meade, C. D. (2014). Use and tax-
onomy of social media in cancer-related research: A systematic review. American Journal of Public Health, 104(7), e20–37.
https://doi.org/10.2105/AJPH.2014.301980
Leaver, T., Highfield, T., & Abidin, C. (2020). Instagram: Visual social media cultures. Polity.
Lorde, A. (1980). The cancer journals. Spinsters/Aunt Lute.
Ma, Z., & Yang, G. (2022). Show Me a Photo of the Character: Exploring the Interaction between Text and Visuals in
Narrative Persuasion. Journal of Health Communication, 27(2), 125–133. https://doi.org/10.1080/10810730.2022.2065387
Macdonald, S., Cunningham, Y., Patterson, C., Robb, K., Macleod, U., Anker, T., & Hilton, S. (2018). Mass media and
risk factors for cancer: The under-representation of age. BMC Public Health, 18(1), 490. https://doi.org/10.1186/
s12889-018-5341-9
Manovich, L. (2017). Instagram and Contemporary Image.
McAlpine, H., Joubert, L., Martin-Sanchez, F., Merolli, M., & Drummond, K. J. (2015). A systematic review of types and
efficacy of online interventions for cancer patients. Patient Education and Counseling, 98(3), 283–295. https://doi.org/
10.1016/j.pec.2014.11.002
Miller, C. A., Guidry, J. P. D., & Fuemmeler, B. F. (2019). Breast Cancer Voices on Pinterest: Raising Awareness or Just
an Inspirational Image? Health Education & Behavior : The Official Publication of the Society for Public Health Education,
46(2_suppl), 49–58. https://doi.org/10.1177/1090198119863774
Miller, C. A., Henderson, A. N., Guidry, J. P. D., McGuire, K. P., & Fuemmeler, B. F. (2020). Pinning Pink: Messages About
Hereditary Breast Cancer Risk on Pinterest. Journal of Cancer Education : The Official Journal of the American Association for
Cancer Education. https://doi.org/10.1007/s13187-020-01842-x
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-
analyses: The PRISMA Statement. Open Medicine. https://doi.org/null
61 2023, 11, 33–64
Cancer Images Social Media
Moorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013). A New Dimension of Health
Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication. Journal of
Medical Internet Research, 15(4), e85. https://doi.org/10.2196/jmir.1933
Noblit, G. W., & Hare, R. D. (1999). Chapter 5: Meta-Ethnography: Synthesizing Qualitative Studies. Counterpoints, 44,
93–123. JSTOR.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M.,
Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W.,
Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting
systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pailler, M. E., Beaupin, L. K., Brewer-Spritzer, E., Grant, P. C., Depner, R. M., Levy, K., & Tenzek, K. E. (2020). Reaching
Adolescent and Young Adult Cancer Patients Through Social Media: Impact of the Photographs of Meaning Program.
Journal of Adolescent and Young Adult Oncology, 9(4), 508–513. https://doi.org/10.1089/jayao.2019.0140
Panofsky, E. (1991). Studies in iconology: Humanistic themes in the art of the Renaissance (14. [pr.]). Harper & Row.
Pardal-Refoyo, J. L., & Pardal-Peláez, B. (2020). Anotaciones para estructurar una revisión sistemática. Revista ORL, 11(2),
155–160. https://doi.org/10.14201/orl.22882
Pardo, R. (2019). Fotografía y enfermedad: Iconografías en transformación. In La imagen desvelada: Prácticas fotográfi-
cas en la enfermedad, la muerte y el duelo (pp. 19–60). Sans Soleil Ediciones. https://www.sanssoleil.es/tienda/
la-imagen-desvelada-practicas-fotograficas-en-la-enfermedad-la-muerte-y-el-duelo-montse-morcate-y-rebeca-pardo-ed/
Park, S.-E., Tang, L., Bie, B., & Zhi, D. (2019). All pins are not created equal: Communicating skin cancer visually on
Pinterest. Translational Behavioral Medicine, 9(2), 336–346. https://doi.org/10.1093/tbm/iby044
Pellino, G., Simillis, C., Qiu, S., Rasheed, S., Mills, S., Warren, O., Kontovounisios, C., & Tekkis, P. P. (2017). Social media
and colorectal cancer: A systematic review of available resources. PloS One, 12(8), e0183031. https://doi.org/10.1371/
journal.pone.0183031
Petticrew, M., & Roberts, H. (Eds.). (2006). Systematic Reviews in the Social Sciences. Blackwell Publishing Ltd. https://doi.org/
10.1002/9780470754887
Pew Research Center. (2019, June 12). Demographics of Social Media Users and Adoption in the United States. Pew Research
Center: Internet, Science & Tech. https://www.pewresearch.org/internet/fact-sheet/social-media/
Plage, S. (2021). Deploying Normality: Cancer Survivor Identity and Authenticity in Ritual-like Practice. Medical Anthropology,
40(5), 473–489. https://doi.org/10.1080/01459740.2021.1909582
Pyle, D., Perry, A., Lamont-Mills, A., Tehan, G., & Chambers, S. K. (2021). A scoping review of the characteristics and ben-
efits of online prostate cancer communities. Psycho-Oncology, 30(5), 659–668. https://doi.org/10.1002/pon.5618
Reese, S. D., Gandy, Jr., & Grant, A. E. (Eds.). (2001). Prologue—Framing Public Life: A Bridging Model for Media Research.
In Framing Public Life (0 ed., pp. 23–48). Routledge. https://doi.org/10.4324/9781410605689-7
Reuter, K., Angyan, P., Le, N., MacLennan, A., Cole, S., Bluthenthal, R. N., Lane, C. J., El-Khoueiry, A. B., & Buchanan, T. A.
(2018). Monitoring Twitter conversations for targeted recruitment in cancer trials in Los Angeles county: Protocol for a
mixed-methods pilot study. JMIR Research Protocols, 7(9). https://doi.org/10.2196/resprot.9762
Riley, K. E., Ulrich, M. R., Hamann, H. A., & Ostroff, J. S. (2017). Decreasing Smoking but Increasing Stigma? Anti-
tobacco Campaigns, Public Health, and Cancer Care. AMA Journal of Ethics, 19(5), 475–485. https://doi.org/10.1001/
journalofethics.2017.19.5.msoc1-1705
Rivera, Y. M., Moran, M. B., Thrul, J., Joshu, C., & Smith, K. C. (2021). When Engagement Leads to Action: Understanding
the Impact of Cancer (Mis)information among Latino/a Facebook Users. Health Communication, 1–13. https://doi.org/
10.1080/10410236.2021.1950442
Rivera, Y. M., Moran, M. B., Thrul, J., Joshu, C., & Smith, K. C. (2022). Contextualizing Engagement With Health
Information on Facebook: Using the Social Media Content and Context Elicitation Method. Journal of Medical Internet
Research, 24(3), e25243. https://doi.org/10.2196/25243
62
www.rcommunicationr.org
Varela-Rodríguez and Vicente-Mariño
Rodriguez, L., & Dimitrova, D. V. (2011). The levels of visual framing. Journal of Visual Literacy, 30(1), 48–65. https://doi.org/
10.1080/23796529.2011.11674684
Ruco, A., Dossa, F., Tinmouth, J., Llovet, D., Jacobson, J., Kishibe, T., & Baxter, N. (2021). Social media and mhealth technol-
ogy for cancer screening: Systematic review and meta-analysis. Journal of Medical Internet Research, 23(7). https://doi.org/
10.2196/26759
Sandelowski, M., & Barroso, J. (2007). Handbook for synthesizing qualitative research. Springer Publishing Company.
Skrabal Ross, X., Gunn, K. M., Olver, I., Willems, R. A., Lechner, L., Mesters, I., & Bolman, C. A. W. (2020). Online psy-
chosocial interventions for posttreatment cancer survivors: An international evidence review and update. Current Opinion
in Supportive and Palliative Care, 14(1), 40–50. https://doi.org/10.1097/SPC.0000000000000478
Sloan, L., & Quan-Haase, A. (2016). The SAGE Handbook of Social Media Research Methods. SAGE Publications Ltd.
https://doi.org/10.4135/9781473983847
Sontag, S. (1978). Illness As Metaphor (1st edition). Farrar, Straus and Giroux.
Sontag, S. (2008). On Photography. Penguin UK.
Stage, C. (2018). Networked Cancer: Affect, narrative and measurement. Palgrave Macmillan.
Stage, C. (2019a). Affective measures: Self-measurement and gridding in female cancer patients’ storytelling practices on
Instagram. Distinktion: Journal of Social Theory, 20(1), 77–100. https://doi.org/10.1080/1600910X.2019.1580594
Stage, C. (2019b). Cancer narratives on social media as ‘small stories’: An investigation of positioning, supportive
(dis)alignment and tellability crises in cancer storytelling on Instagram. Tidsskrift for Forskning i Sygdom Og Samfund, 16(31),
Article 31. https://doi.org/10.7146/tfss.v16i31.116969
Suárez-Lledo, V., & Álvarez-Gálvez, J. (2021). Prevalence of Health Misinformation on Social Media: Systematic Review.
Journal of Medical Internet Research, 23(1), e17187. https://doi.org/10.2196/17187
Sweeney, E., & Killoran-McKibbin, S. (2016). Selling Pink: Feminizing the Non-Profit Industrial Complex from Ribbons to
Lemonaid. Women’s Studies, 45(5), 457–474. https://doi.org/10.1080/00497878.2016.1186492
Tetteh, D. A. (2021). “I just re-evaluated what was beautiful when I went through treatment:” an analysis of Elly Mayday’s
ovarian cancer narrative. Feminist Media Studies. https://doi.org/10.1080/14680777.2021.1922482
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC
Medical Research Methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45
Thorne, S., Jensen, L., Kearney, M. H., Noblit, G., & Sandelowski, M. (2004). Qualitative metasynthesis: Reflections on
methodological orientation and ideological agenda. Qualitative Health Research, 14(10), 1342–1365. https://doi.org/
10.1177/1049732304269888
Tifentale, A., & Manovich, L. (2018). Competitive Photography and the Presentation of the Self. In J. Eckel, J. Ruchatz, &
S. Wirth (Eds.), Exploring the Selfie: Historical, Theoretical, and Analytical Approaches to Digital Self-Photography (pp. 167–187).
Springer International Publishing. https://doi.org/10.1007/978-3-319-57949-8_8
Varela-Rodríguez, M., & Vicente-Mariño, M. (2021a). Imágenes desgarradas: El uso de scrapers en investigación social en
Instagram sobre cáncer. Cuadernos.Info, 49, 72–97. https://doi.org/10.7764/cdi.49.27809
Varela-Rodríguez, M., & Vicente-Mariño, M. (2021b). Whose cancer? Visualising the distribution of mentions to cancer sites
on instagram. Journal of Visual Communication in Medicine, 1–17. https://doi.org/10.1080/17453054.2021.1964356
Vraga, E. K., Stefanidis, A., Lamprianidis, G., Croitoru, A., Crooks, A. T., Delamater, P. L., Pfoser, D., Radzikowski, J. R.,
& Jacobsen, K. H. (2018). Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and
Other Reproductive Cancers on Twitter and Instagram. Journal of Health Communication, 23(2), 181–189. https://doi.org/
10.1080/10810730.2017.1421730
Vrinten, C., McGregor, L. M., Heinrich, M., von Wagner, C., Waller, J., Wardle, J., & Black, G. B. (2017). What do people
fear about cancer? A systematic review and meta-synthesis of cancer fears in the general population. Psycho-Oncology,
26(8), 1070–1079. https://doi.org/10.1002/pon.4287
63 2023, 11, 33–64
Cancer Images Social Media
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic Literature Review on the Spread of Health-
related Misinformation on Social Media. Social Science & Medicine (1982), 240, 112552. https://doi.org/10.1016/j.
socscimed.2019.112552
Wilner, T., & Holton, A. (2020). Breast cancer prevention and treatment: Misinformation on pinterest, 2018. American Journal
of Public Health, 110, S300–S304. https://doi.org/10.2105/AJPH.2020.305812
Zade, H. A., Habibi, L., Arabtani, T. R., Sarani, E. M., & Farpour, H. R. (2017). Functions of Social Networks in a Community
of Cancer Patients: The Case of Instagram. International Journal of Networks and Communications, 7(4), 71–78.
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