# data[].attributes.attachment_link.readable_text
The Definition of Cancer

Cancer is a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body.

Cancer can start almost anywhere in the human body, which is made up of trillions of cells. Normally, human cells grow and multiply (through a process called cell division) to form new cells as the body needs them. When cells grow old or become damaged, they die, and new cells take their place.

Sometimes this orderly process breaks down, and abnormal or damaged cells grow and multiply when they shouldn't. These cells may form tumors, which are lumps of tissue. Tumors can be cancerous or not cancerous ( benign).

Cancerous tumors spread into, or invade, nearby tissues and can travel to distant places in the body to form new tumors (a process called metastasis). Cancerous tumors may also be called malignant tumors. Many cancers form solid tumors, but cancers of the blood, such as leukemias, generally do not.

Benign tumors do not spread into, or invade, nearby tissues. When removed, benign tumors usually don't grow back, whereas cancerous tumors sometimes do. Benign tumors can sometimes be quite large, however. Some can cause serious symptoms or be life threatening, such as benign tumors in the brain.

Differences between Cancer Cells and Normal Cells

Cancer cells differ from normal cells in many ways. For instance, cancer cells:

grow in the absence of signals telling them to grow. Normal cells only grow when they receive such signals.

ignore signals that normally tell cells to stop dividing or to die (a process known as programmed cell death, or apoptosis).

invade into nearby areas and spread to other areas of the body. Normal cells stop growing when they encounter other cells, and most normal cells do not move around the body.

tell blood vessels to grow toward tumors. These blood vessels supply tumors with oxygen and nutrients and remove waste products from tumors.

hide from the immune system. The immune system normally eliminates damaged or abnormal cells.

trick the immune system into helping cancer cells stay alive and grow. For instance, some cancer cells convince immune cells to protect the tumor instead of attacking it.

accumulate multiple changes in their chromosomes, such as duplications and deletions of chromosome parts. Some cancer cells have double the normal number of chromosomes.

rely on different kinds of nutrients than normal cells. In addition, some cancer cells make energy from nutrients in a different way than most normal cells. This lets cancer cells grow more quickly.

Many times, cancer cells rely so heavily on these abnormal behaviors that they can't survive without them. Researchers have taken advantage of this fact, developing therapies that target the abnormal features of cancer cells. For example, some cancer therapies prevent blood vessels from growing toward tumors, essentially starving the tumor of needed nutrients.

How Does Cancer Develop?

Cancer is a genetic disease-that is, it is caused by changes to genes that control the way our cells function, especially how they grow and divide.

Genetic changes that cause cancer can happen because:

of errors that occur as cells divide.

of damage to DNA caused by harmful substances in the environment, such as the chemicals in tobacco smoke and ultraviolet rays from the sun. (Our Cancer Causes and Prevention section has more information.)

they were inherited from our parents.

The body normally eliminates cells with damaged DNA before they turn cancerous. But the body's ability to do so goes down as we age. This is part of the reason why there is a higher risk of cancer later in life.

Each person's cancer has a unique combination of genetic changes. As the cancer continues to grow, additional changes will occur. Even within the same tumor, different cells may have different genetic changes.

When Cancer Spreads

A cancer that has spread from the place where it first formed to another place in the body is called metastatic cancer. The process by which cancer cells spread to other parts of the body is called metastasis.

Metastatic cancer has the same name and the same type of cancer cells as the original, or primary, cancer. For example, breast cancer that forms a metastatic tumor in the lung is metastatic breast cancer, not lung cancer.

Under a microscope, metastatic cancer cells generally look the same as cells of the original cancer. Moreover, metastatic cancer cells and cells of the original cancer usually have some molecular features in common, such as the presence of specific chromosome changes.

In some cases, treatment may help prolong the lives of people with metastatic cancer. In other cases, the primary goal of treatment for metastatic cancer is to control the growth of the cancer or to relieve symptoms it is causing. Metastatic tumors can cause severe damage to how the body functions, and most people who die of cancer die of metastatic disease.

Types of Cancer

There are more than 100 types of cancer. Types of cancer are usually named for the organs or tissues where the cancers form. For example, lung cancer starts in the lung, and brain cancer starts in the brain. Cancers also may be described by the type of cell that formed them, such as an epithelial cell or a squamous cell.

You can search NCI's website for information on specific types of cancer based on the cancer's location in the body or by using our A to Z List of Cancers. We also have information on childhood cancers and cancers in adolescents and young adults.

Here are some categories of cancers that begin in specific types of cells:

Carcinoma

Carcinomas are the most common type of cancer. They are formed by epithelial cells, which are the cells that cover the inside and outside surfaces of the body. There are many types of epithelial cells, which often have a column-like shape when viewed under a microscope.

Carcinomas that begin in different epithelial cell types have specific names:

Adenocarcinoma is a cancer that forms in epithelial cells that produce fluids or mucus. Tissues with this type of epithelial cell are sometimes called glandular tissues. Most cancers of the breast, colon, and prostate are adenocarcinomas.

Basal cell carcinoma is a cancer that begins in the lower or basal (base) layer of the epidermis, which is a person's outer layer of skin.

Squamous cell carcinoma is a cancer that forms in squamous cells, which are epithelial cells that lie just beneath the outer surface of the skin. Squamous cells also line many other organs, including the stomach, intestines, lungs, bladder, and kidneys. Squamous cells look flat, like fish scales, when viewed under a microscope. Squamous cell carcinomas are sometimes called epidermoid carcinomas.

Transitional cell carcinoma is a cancer that forms in a type of epithelial tissue called transitional epithelium, or urothelium. This tissue, which is made up of many layers of epithelial cells that can get bigger and smaller, is found in the linings of the bladder, ureters, and part of the kidneys (renal pelvis), and a few other organs. Some cancers of the bladder, ureters, and kidneys are transitional cell carcinomas.

Sarcoma

Sarcomas are cancers that form in bone and soft tissues, including muscle, fat, blood vessels, lymph vessels, and fibrous tissue (such as tendons and ligaments).

Osteosarcoma is the most common cancer of bone. The most common types of soft tissue sarcoma are leiomyosarcoma, Kaposi sarcoma, malignant fibrous histiocytoma, liposarcoma, and dermatofibrosarcoma protuberans.

Our page on soft tissue sarcoma has more information.

Leukemia

Cancers that begin in the blood-forming tissue of the bone marrow are called leukemias. These cancers do not form solid tumors. Instead, large numbers of abnormal white blood cells (leukemia cells and leukemic blast cells) build up in the blood and bone marrow, crowding out normal blood cells. The low level of normal blood cells can make it harder for the body to get oxygen to its tissues, control bleeding, or fight infections.

There are four common types of leukemia, which are grouped based on how quickly the disease gets worse (acute or chronic) and on the type of blood cell the cancer starts in (lymphoblastic or myeloid). Acute forms of leukemia grow quickly and chronic forms grow more slowly.

Our page on leukemia has more information.

Lymphoma

Lymphoma is cancer that begins in lymphocytes (T cells or B cells). These are disease-fighting white blood cells that are part of the immune system. In lymphoma, abnormal lymphocytes build up in lymph nodes and lymph vessels, as well as in other organs of the body.

There are two main types of lymphoma:

Hodgkin lymphoma - People with this disease have abnormal lymphocytes that are called Reed-Sternberg cells. These cells usually form from B cells.

Non-Hodgkin lymphoma - This is a large group of cancers that start in lymphocytes. The cancers can grow quickly or slowly and can form from B cells or T cells.

Our page on lymphoma has more information.

Multiple Myeloma

Multiple myeloma is cancer that begins in plasma cells, another type of immune cell. The abnormal plasma cells, called myeloma cells, build up in the bone marrow and form tumors in bones all through the body. Multiple myeloma is also called plasma cell myeloma and Kahler disease.

Our page on multiple myeloma and other plasma cell neoplasms has more information.

Melanoma

Melanoma is cancer that begins in cells that become melanocytes, which are specialized cells that make melanin (the pigment that gives skin its color). Most melanomas form on the skin, but melanomas can also form in other pigmented tissues, such as the eye.

Our pages on skin cancer and intraocular melanoma have more information.

Brain and Spinal Cord Tumors

There are different types of brain and spinal cord tumors. These tumors are named based on the type of cell in which they formed and where the tumor first formed in the central nervous system. For example, an astrocytic tumor begins in star-shaped brain cells called astrocytes, which help keep nerve cells healthy. Brain tumors can be benign (not cancer) or malignant (cancer).

Our page on brain and spinal cord tumors has more information.

Other Types of Tumors

Germ Cell Tumors

Germ cell tumors are a type of tumor that begins in the cells that give rise to sperm or eggs. These tumors can occur almost anywhere in the body and can be either benign or malignant.

Our page of cancers by body location/system includes a list of germ cell tumors with links to more information.

Neuroendocrine Tumors

Neuroendocrine tumors form from cells that release hormones into the blood in response to a signal from the nervous system. These tumors, which may make higher-than-normal amounts of hormones, can cause many different symptoms. Neuroendocrine tumors may be benign or malignant.

Our definition of neuroendocrine tumors has more information.

Carcinoid Tumors

Carcinoid tumors are a type of neuroendocrine tumor. They are slow-growing tumors that are usually found in the gastrointestinal system (most often in the rectum and small intestine). Carcinoid tumors may spread to the liver or other sites in the body, and they may secrete substances such as serotonin or prostaglandins, causing carcinoid syndrome.

Our page on gastrointestinal neuroendocrine tumors has more information.

# data[].attributes.attachment_link.description
Explanations about what cancer is, how cancer cells differ from normal cells, and genetic changes that cause cancer to grow and spread.

# data[].attributes.attachment_link.title
Lifetime Risk of Developing or Dying From Cancer

# data[].attributes.attachment_link.description
Learn about the chance each person has of being diagnosed with or dying from different types of cancer during his or her lifetime.

# data[].attributes.attachment_link.readable_text
Advancing age is the most important risk factor for cancer overall and for many individual cancer types. The incidence rates for cancer overall climb steadily as age increases, from fewer than 25 cases per 100,000 people in age groups under age 20, to about 350 per 100,000 people among those aged 45-49, to more than 1,000 per 100,000 people in age groups 60 years and older.

According to the most recent statistical data from NCI's Surveillance, Epidemiology, and End Results (SEER) Program, the median age of a cancer diagnosis is 66 years. This means that half of cancer cases occur in people below this age and half in people above this age. A similar pattern is seen for many common cancer types. For example, the median age at diagnosis is 62 years for breast cancer, 67 years for colorectal cancer, 71 years for lung cancer, and 66 years for prostate cancer.

But cancer can be diagnosed at any age. For example, bone cancer is most frequently diagnosed in children and adolescents (people under age 20), with about one-fourth of cases occurring in this age group. And 12% of brain and other nervous system cancers are diagnosed in children and adolescents, whereas only 1% of cancer overall is diagnosed in this age group.

# data[].attributes.attachment_link.description
Advancing age is the most important risk factor for cancer overall and for many individual cancer types. The incidence rates for cancer overall climb steadily as age increases, from fewer than 25 cases per 100,000 people in age groups under age 20, to about 350 per 100,000 people among those aged 45-49, to more than 1,000 per 100,000 people in age groups 60 years and older.

# data[].attributes.attachment_link.title
Why are cancer rates increasing? - Cancer Research UK - Cancer news

# data[].attributes.attachment_link.description
Half of us in the UK will hear the words “you have cancer” at some point in our lives. But why? We look at why rates are on the up, and what can be done.

# data[].attributes.attachment_link.readable_text
Christmas 2022: Don't Believe the Hype

Sonia Paytubi, postdoctoral researcher, ¹ Yolanda Benavente, senior statistician, 1 ,² Alexandra Montoliu, mathematician, ¹ Gemma Binefa, medical epidemiologist, 2 ,³ Maria Brotons, medical epidemiologist, 1 ,² Raquel Ibáñez, postdoctoral researcher, 1 ,² Cristian Ochoa, psychooncologist, 4 ,⁵ Paula Peremiquel-Trillas, medical epidemiologist, 1 ,² Beatriz Serrano, medical epidemiologist, 1 ,² Noémie Travier, statistician, ³ Laia Alemany, medical epidemiologist, 1 ,² and Laura Costas, medical epidemiologist 1 ,²

Abstract

Objective

To evaluate, using an online non-probability sample, the beliefs about and attitudes towards cancer prevention of people professing vaccination scepticism or conspiracy theories.

Design

Cross sectional survey.

Setting

Data collected mainly from ForoCoches (a well known Spanish forum) and other platforms, including Reddit (English), 4Chan (English), HispaChan (Spanish), and a Spanish language website for cancer prevention (mejorsincancer.org) from January to March 2022.

Participants

Among 1494 responders, 209 were unvaccinated against covid-19, 112 preferred alternative rather than conventional medicine, and 62 reported flat earth or reptilian beliefs.

Main outcome measures

Cancer beliefs assessed using the Cancer Awareness Measure (CAM) and Cancer Awareness Measure Mythical Causes Scale (CAM-MYCS) (both validated tools).

Results

Awareness of the actual causes of cancer was greater (median CAM score 63.6%) than that of mythical causes (41.7%). The most endorsed mythical causes of cancer were eating food containing additives or sweeteners, feeling stressed, and eating genetically modified food. Awareness of the actual and mythical causes of cancer among the unvaccinated, alternative medicine, and conspiracy groups was lower than among their counterparts. A median of 54.5% of the actual causes was accurately identified among each of the unvaccinated, alternative medicine, and conspiracy groups, and a median of 63.6% was identified in each of the three corresponding counterparts (P=0.13, 0.04, and 0.003, respectively). For mythical causes, medians of 25.0%, 16.7%, and 16.7% were accurately identified in the unvaccinated, alternative medicine, and conspiracy groups, respectively; a median of 41.7% was identified in each of the three corresponding counterparts (P<0.001 in adjusted models for all comparisons). In total, 673 (45.0%) participants agreed with the statement "It seems like everything causes cancer." No significant differences were observed among the unvaccinated (44.0%), conspiracist (41.9%), or alternative medicine groups (35.7%), compared with their counterparts (45.2%, 45.7%, and 45.8%, respectively).

Conclusions

Almost half of the participants agreed that "It seems like everything causes cancer," which highlights the difficulty that society encounters in differentiating actual and mythical causes owing to mass information. People who believed in conspiracies, rejected the covid-19 vaccine, or preferred alternative medicine were more likely to endorse the mythical causes of cancer than their counterparts but were less likely to endorse the actual causes of cancer. These results suggest a direct connection between digital misinformation and consequent erroneous health decisions, which may represent a further preventable fraction of cancer.

Introduction

Cancer is a leading cause of mortality worldwide, accounting for nearly 10 million deaths in 2020.1 Between 30% and 50% of diagnosed cancer is preventable through lifestyle changes and existing evidence based prevention strategies,2 such as maintaining a healthy weight, partaking in physical activity, eating fruits and vegetables, limiting consumption of alcohol and red and processed meat, avoiding excess sun exposure and active and passive smoking, and participating in vaccination programmes against human papillomavirus and hepatitis.3 4 Adherence to recommendations on cancer prevention is directly related to beliefs about cancer. Therefore, identifying these beliefs and their underlying factors can help to inform prevention efforts.5

Although communication technologies and social media provide new opportunities to access health information, they also have a pervasive effect. They open a direct avenue of misinformation (false information that is spread, regardless of intent to mislead) and disinformation (misinformation that is circulated intentionally for secondary gains-namely, money, reputation, or power), posing health concerns.6 7 Conspiracy beliefs are the extreme results of misinformation and widespread suspicions of the real world. These include the beliefs that the earth is flat, that humanoids take reptilian forms to manipulate human societies, or that condensation trails from planes are "chemtrails" comprising agents sprayed for evil purposes.8 9 Some myths also relate to Santa Claus-some people think that Santa is an anagram of Satan and brings corruption and greed during Christmas, whereas others believe that Santa Claus is a giant lie that was started by the Illuminati for mind control.10 The covid-19 pandemic also caused multiple conspiracies, mainly related to its origin and vaccines, undermining preventive health responses and leading some people to undertake risky alternative treatments.11

Increasing misinformation on the internet and its dissemination patterns have promoted narratives that affect real world health outcomes. Misinformation about cancer can lead to increased disease burden because of people's refusal to adopt effective preventive health measures (for instance, making cancer promoting lifestyle choices or rejecting human papillomavirus vaccines). It can also lead to delays in seeking effective oncological treatment and, consequently, worsen the outcomes in patients with cancer. Misinformation is also associated with avoidable social suffering. For instance, conspiracy theories may produce intense fear related to malevolent reptilians, mortal side effects of vaccines, or inhalation of ubiquitous toxins. People can also encounter social stigma when they endorse conspiracy theories.12 Social media algorithms promote the aggregation of users, who may share a broader health related magical world view. Health world views that dismiss scientific knowledge in support of magical thinking were previously associated with vaccination scepticism.13 However, no data exist on endorsement of conspiracies or vaccination scepticism in relation to individuals' beliefs about and attitudes to cancer prevention. We did this study to evaluate beliefs about and attitudes to cancer prevention based on health preferences and conspiracy beliefs.

Methods

Study design

We collected data anonymously using a cross sectional design, with an online survey distributed on several platforms. Data mainly came from ForoCoches ( https://forocoches.com/), a well known and influential Spanish forum.14 15 The administrators of ForoCoches granted us access to publish a post on their website for this research. We also posted the survey on other websites such as Reddit and 4Chan. Reddit ( https://www.reddit.com/) is an English language discussion website on which registered members submit content that is upvoted or downvoted by other members. Reddit works with a reputation system that provides better visibility when the member has more points (called "karma") based on the voting system. 4Chan ( https://www.4chan.org/) is a registration-free English language platform on which users typically post anonymously. We also posted the survey on HispaChan ( https://www.hispachan.org/), which is equivalent to 4Chan in Spanish, and other influential forums according to Alexa ranking site (used as a metric to determine the popularity of a site), including MediaVida ( https://www.mediavida.com/), Burbuja Info ( https://www.burbuja.info/), and Taringa ( https://www.taringa.net/), which are similar to ForoCoches but with smaller audiences. The survey was also posted in certain Telegram groups with titles including words such as "anti-vaxxers," "reptilians," and "flat earth." Finally, the survey was distributed on the website Mejor Sin Cáncer ("Better Without Cancer" in Spanish; https://mejorsincancer.org/), a Spanish language website on cancer prevention created in 2015 that we manage; it receives approximately 300 daily visits, mainly via search engines (98% of visits). We created a pop-up advertisement to invite visitors to participate in this survey. We applied no exclusion criteria. We collected the study data by using REDCap electronic data capture tools hosted at the Catalan Institute of Oncology.16 17

Measures

Sociodemographics, health behaviours, and conspiracy beliefs

A copy of the survey is provided in the supplementary material. We asked the participants to provide information on their age, sex, country of birth, country of residence, education level, and whether their occupation was related to the medical field. Questions on health habits and behaviours included a preference for conventional or alternative medicines, administration of any covid-19 vaccine, the reason for not undergoing vaccination, smoking status, alcohol consumption, weight and height, and personal history of cancer.

We asked the participants if they considered the Earth to be round or flat, with four response options (I have always considered the Earth to be round (spherical or similar); I always thought that the Earth was round (spherical or similar) but recently I have had doubts; I had always thought the Earth was flat, but recently I have had doubts; I have always considered the Earth to be flat). We included two questions to assess reptilian conspiracy beliefs, using the statements "there are many shape shifting lizards taking human forms or turning into reptilian humanoids" and "presidents of most countries are reptilian humanoids." The response options were based on a five point Likert-type scale (strongly disagree, disagree, unsure, agree, and strongly agree). We included participants in the "conspiracy group" if they marked options other than "I have always considered the Earth to be round (spherical or similar)," or if they agreed or strongly agreed with either of the two questions on reptilians.

Cancer beliefs

To assess their beliefs about actual and mythical (non-established) causes of cancer, we presented the participants with the closed risk factor questions on the validated scales-the Cancer Awareness Measure (CAM) and CAM-Mythical Causes Scale (CAM-MYCS).18 19 The closed risk factor questions on the CAM assesses cancer risk perceptions of 11 established risk factors for cancer: smoking actively or passively, consuming alcohol, low levels of physical activity, consuming red or processed meat, getting sunburnt as a child, family history of cancer, human papillomavirus infection, being overweight, age ≥70 years, and low vegetable and fruit consumption. These items are causally associated with at least one cancer site and (except for non-modifiable risk factors) included in the European Code Against Cancer, an initiative of the European Commission to inform society of actions that can be undertaken to reduce the risk of cancer. The CAM-MYCS measure includes 12 questions on risk perceptions of mythical causes of cancer-non-established causes that are commonly believed to cause cancer without supporting scientific evidence. Accordingly, mythical causes are not classified as group 1 carcinogens (that is, carcinogenic to humans) by the International Agency for Research on Cancer and are not included in the European Code Against Cancer or the World Cancer Research Fund recommendations. These items include drinking from plastic bottles; eating food containing artificial sweeteners or additives and genetically modified food; the use of microwave ovens, aerosol containers, mobile phones, and cleaning products; living near power lines; feeling stressed; experiencing physical trauma; and being exposed to electromagnetic frequencies/non-ionising radiation, such as wi-fi networks, radio, and television. Responses to both measures are recorded on a five point Likert-type scale ranging from "strongly disagree" to "strongly agree."

To adapt the CAM and CAM-MYCS scales to the Spanish speaking population, we followed a methodological approach described in the guideline of Sousa et al: "Translation, adaptation, and validation of instruments or scales for use in cross-cultural health care research: a clear and user-friendly guideline."20 In brief, two interpreters (one of whom was a specialist in cancer) translated the survey into Spanish. A third researcher resolved ambiguities and discrepancies through consensus. Two native translators (one of whom was a specialist in cancer) blindly back translated the consensus translated survey into English. We compared the two back translations and the original survey to evaluate the similarity among the instructions, items, and response format regarding wording and meaning. Discrepancies were resolved through consensus reached by the five translators involved, and we also obtained feedback from the developers of the original survey.

Finally, we asked the participants about other perceived cancer risks, using the statements "it seems like everything causes cancer," "there's not much you can do to lower your chances of getting cancer," and "cancer worries me a lot," and the question "compared with other people of your age, how likely are you to get cancer in your lifetime?" The possible responses were strongly disagree, disagree, unsure, agree, and strongly agree for the three statements and very likely, likely, neither unlikely nor likely, unlikely, and very unlikely for the question. We piloted the questionnaire (n=15) to test for any technical problems and estimate the time for completion.

Participants

We collected data from January to March 2022 and obtained 1754 responses. We identified that 14 responses had the same values for all 23 CAM items and therefore considered them to be low quality surveys and excluded them from analyses. We excluded partial responses to covid-19 vaccination and CAM items. Nine responses had missing information on covid-19 vaccination, and 232 participants filled only the first page of the survey so that information on cancer beliefs (CAM items) was missing. Five more participants did not respond to all the cancer belief items and were excluded from analyses. Conspiracy belief items were on the last page of the survey, and 57 participants did not complete this information. Considering that the participants had given information on cancer beliefs and covid-19 vaccination, we retained these data in analyses. We reclassified four responses on conspiracy questions as "not conspiracists," as the participants reported in open comments that they believed in conspiracies "just for fun." This yielded a final sample size of 1494 responses. Descriptive characteristics of full and partial responders are provided in supplementary table A.

Statistical analysis

We did basic descriptive analyses of the responses to the questions on sociodemographics, health behaviours, and conspiracy beliefs. We dichotomised CAM and CAM-MYCS responses into "correct" (strongly agree/agree on CAM, strongly disagree/disagree on CAM-MYCS) and "incorrect" (unsure/disagree/strongly disagree on CAM, unsure/agree/strongly agree on CAM-MYCS) responses, which resulted in a total score of 0-11 for CAM and 0-12 for CAM-MYCS (1 point for each correct answer). We also added the dichotomised "correct"' CAM and CAM-MYCS responses together, resulting in a 0-23 CAM-total score. We converted the scores to a "percentage correct" (0-100) score, using the percentage of maximum possible method. We classified responses on whether screening was recommended for certain types of cancer as correct if they were marked "yes" for breast, colorectal, and cervical cancers, according to current recommendations by the European Code of Cancer, and incorrect if they were marked "yes" for lung, ovarian, and prostate cancers.

We did multivariable analyses of CAM, CAM-MYCS, and CAM-total by using quantile regression. We used unconditional logistic regression to do multivariable analyses of binary variables. We introduced missing values into the models as independent categories. We treated ordinal variables as continuous variables to test linear trends. Models were adjusted for covid-19 vaccination (unvaccinated versus one dose or more), conspiracy beliefs (yes, no), preference for medicine (alternative, conventional), age (<25, 25-34, 35-44, and ≥45 years), sex (male, female, and non-binary), education level (below college level, at least college level), region (Europe, others), medical occupation (no, yes), body mass index (body mass index <25, 25-29.9, and ≥30), regular alcohol intake (no, yes), smoking (never, ever), personal history of cancer (no, yes), and source of the survey (ForoCoches, cancer blog, 4Chan/Reddit/Hispachan/others). All tests were two tailed, with a significance level of 0.05. We used Stata version 16.0 for all analyses and generated graphs by using R version 4.1.2. We obtained consent to participate by using the following sentence: "I understand the purpose of this study, and I grant consent to the use of my responses for the purposes of this study (Yes/No)." In total, 46 participants explicitly denied their consent to participate by clicking "No." We calculated the sample size by using the previous CAM-total of Shahab et al.21 Assuming a one to four ratio, we needed at least 290 (58:232) participants to detect a 15% two sided difference in the CAM-total score with 80% power and 650 (130:520) participants to detect a 10% difference between the two groups.

Sensitivity analyses

Given that 80% of the sample was collected from Spain, we did restricted analyses among respondents residing in Spain to weigh responses for the representative distribution of sex, age, and education, considering national data from the Spanish National Statistics Institute.22 In particular, we rebalanced responses from 1068 participants in ForoCoches who reported residence in Spain by age (18-34/35-59 years), sex (male/female), and education (below college level, at least college level). We used data from the Continuous Household Survey (2020), which represents more than 99% of the total population residing in Spain, to obtain the proportion of each of the six groups of our demographic profile in the target population.22 We obtained the weights by dividing the proportion of the group in the target population by the proportion of the group in the survey population. Next, we did analyses similar to those described above using weighted data.

Patient and public involvement

An anonymous person who professed reptilian conspiracy theory helped to design the questionnaire. We maintained interesting chats in forums with other people who held conspiracy beliefs and who provided useful insights. The survey also contained an open response option for general comments. We did no formal qualitative analysis as it was beyond the scope of the project but selected 11 responses for illustrative purposes ( table 1 ).

Table 1

Source

Comment

4Chan

It's really about the shapeshifting lizards, isn't it

4Chan

You might want to post this on reddit for a more realistic sample, you are going to get a LOT of antivaxx schizos posting here

4Chan

I'd only know if I got a plane and chased the sun, anything else is something somebody told me. Agnostic earthers rise!

Reddit

This is hilarious. Why did you ask about flat earth

ForoCoches

This survey gives cancer*

ForoCoches

Well, according to many "experts," EVERYTHING causes cancer. We can't even breathe*

ForoCoches

Being born between June 21 - July 22. If not, you are from another (horoscope) sign. I hope I helped you*

Survey (open question)

Stupid questions. no one can prove the earth is round or flat and or that lizard people do or do not exist. anyone who says it's definitely either way is stupid

Survey (open question)

I am a reptilian experiencer. I believe in reptilians because I have seen them, not because I heard somebody else believes in them

Survey (open question)

Everyone knows that the Bellatricians died out eons ago, and Pleiadians are those among us, and they are much more dangerous*

Survey (open question)

I believe in lots of reptilians and them being capable of appearing human, but I don't think they are many presidents. They are in other positions

Results

Characteristics of the sample are listed in table 2 and supplementary table A. Full responders were more likely to be aged 25-44 years, come from Europe, have a higher education level, and originate from ForoCoches (supplementary table A) than the partial responders. Among the full responders, 209 (14.0%) did not receive any covid-19 vaccination and 62 (4.1%) reported that they believed that the Earth was flat or that shapeshifting lizards existed ( table 2 ). Additionally, 112 (7.5%) participants reported that they preferred alternative medicine to conventional medicine. Figure 1 shows a Venn diagram in which 15 responders were simultaneously classified as unvaccinated against covid-19, believed in conspiracies, and preferred alternative medicine.

Table 2

Characteristics

Covid-19 vaccination

Believes in flat earth or shapeshifting lizards

Preferred type of medicine

One dose or more (n=1285)

Unvaccinated (n=209)

P value*

No (n=1375)

Yes (n=62)

P value*

Conventional (n=1367)

Alternative (n=112)

P value*

Among all participants, awareness of the actual causes of cancer (median CAM score 63.6%, interquartile range 45.5-81.8%) was greater than awareness of the mythical causes of cancer (41.7%, 16.7-58.3%) ( fig 2 and fig 3 ). Overall, the most endorsed actual causes of cancer were active smoking (97.4%; n=1455), passive smoking (85.1%; n=1271), family history of cancer (77.6%; n=1160), and being overweight (71.4%; n=1066). By contrast, less than 25% (n=369) of the participants correctly identified low intake of fruits and vegetables as a cause of cancer. The most endorsed mythical causes of cancer were eating food containing additives (63.9%; n=954) or sweeteners (50.7%; n=758), feeling stressed (59.7%; n=892), and eating genetically modified foods (38.4%; n=573) (supplementary figure A).

Awareness of the actual and mythical causes of cancer in the unvaccinated and conspiracy groups (those who believed that the Earth was flat or that shapeshifting lizards existed) was lower than in their counterparts. Specifically, the unvaccinated and conspiracy groups accurately identified a median of 54.5% (45.5-72.7%) and 54.5% (36.4-72.7%) of the actual causes, respectively; by contrast, the respective counterparts identified a median of 63.6% (45.5-81.8%) and 63.6% (45.5-81.8%) of the actual causes of cancer (P=0.13 and P=0.003 in adjusted models, respectively). Moreover, a median of 25.0% (8.3-50.0%) and 16.7% (8.3-41.7%) of the mythical causes were correctly identified in the unvaccinated and conspiracy groups; by contrast, 41.7% (16.7-58.3%) and 41.7% (16.7-58.3%) of the mythical causes were correctly identified by their counterparts (P<0.001 in adjusted models for both comparisons) ( fig 3 ). The preference for alternative medicine was also associated with lower CAM and CAM-MYCS scores. Specifically, a median of 63.6% (45.5-81.8%) of the actual causes were accurately identified among those who preferred conventional medicine or were unsure; by contrast, 54.5% (36.4-72.7%) of the actual causes were identified among those who preferred alternative medicine (adjusted P=0.04). Furthermore, 41.7% (16.7-58.3%) and 16.7% (8.3-33.3%) of mythical causes were identified by those who preferred conventional and alternative medicine, respectively (adjusted P<0.001) ( fig 3 ). Male sex, higher education, and medical occupation survey profile were positively associated with higher CAM-total, CAM, and/or CAM-MYCS scores (supplementary table B). Generally, a risk factor for cancer was inversely associated with the endorsement of that specific risk factor as a cause of cancer. For instance, we observed an inverse trend between age and the belief that being >70 years old was a risk factor for cancer (supplementary table C). We observed similar patterns for obesity, passive smoking, and alcohol consumption.

Overall, 673 (45.0%) participants agreed or strongly agreed with the statement "It seems like everything causes cancer." We observed no significant differences according to vaccination status (44% (n=92) among the unvaccinated; adjusted P=0.96), conspiracy group (42% (n=26); adjusted P=0.91), or alternative medicine preference (36% (n=40); adjusted P=0.15) compared with their counterparts (45.2% (n=581); 45.7% (n=628); and 45.8% (n=626), respectively) ( table 3 ). This belief was significantly associated with alcohol consumption (P<0.001) and was inversely associated with age (adjusted P for trend <0.001) and male sex (P<0.001) (supplementary table D). Overall, 305 (20.4%) participants agreed or strongly agreed with the statement "There's not much I can do to reduce the chances of getting cancer" (data not shown). Of the participants, 86.9% (95% confidence interval 85.1% to 88.6%; n=1256) accurately identified that screening programmes are established in the general population for the detection of breast cancer, 69.3% (66.9% to 71.7%; n=1002) did so for colorectal cancer, and 50.0% (47.4% to 52.6%; n=723) for cervical cancer. In addition, 73.6% (71.2% to 75.8%; n=1063) of participants accurately identified that screening programmes are not established in the general population for lung cancer, 66.0% (63.5% to 68.5%; n=954) did so for ovarian cancer, and 27.9% (25.6% to 30.3%; n=403) for prostate cancer (supplementary table E). We observed no significant differences according to vaccination status, conspiracy group, or type of medicine preference, except for a lower awareness of the available colorectal screening programmes in the conspiracy group (51.6%, 38.6% to 64.5%; n=32; adjusted P=0.05, compared with the non-conspiracy group).

Table 3

Group

Strongly disagree, disagree, or not sure

Agree or strongly agree

Odds ratio (95% CI)

P value

Sensitivity analyses in Spanish respondents weighting for sex, age, and education using data from the Spanish National Statistics Institute yielded similar results for awareness of actual causes of cancer (median CAM score 63.6%, interquartile range 45.5-81.8%) but lower estimates of mythical cancer causes (33.3%, 8.3-50.0%) than in the non-weighted analyses (supplementary table F). Weighted sensitivity analyses did not yield significant associations, except for a lower median CAM score among conspiracy believers (45.5%, 45.5-72.7%) than among non-believers (63.6%, 45.5-81.8).

Discussion

Almost half of the participants agreed with the statement "It seems like everything causes cancer." This highlights the difficulty that society encounters in distinguishing the actual causes of cancer from mythical causes owing to the mass information on the news and social media platforms. Overall, awareness of the actual and mythical causes of cancer was low. Only a median of approximately two thirds of the actual causes of cancer and approximately 40% of the mythical causes were correctly identified. We provided first time data on beliefs about a range of actual and mythical causes of cancer according to conspiracy beliefs and health preferences. In adjusted models, people who believed in conspiracies, rejected the covid-19 vaccine, or preferred alternative medicine were more likely to endorse mythical causes of cancer than their counterparts but were less likely to endorse actual causes of cancer.

We evaluated beliefs about cancer among flat earthers and reptilian conspiracy theorists, although associations with other existing conspiracies could be shown in future studies. Beliefs about cancer may differ substantially among chemtrail believers, global warming deniers, those who believe that the moon landings were staged by NASA in a film studio, those who peddle the "Santa is an Illuminati weapon" conspiracy, or even those who believe that birds are drones operated by the United States government to spy on citizens.23 24 The sample in this study may not represent the general population; however, the administration of at least one dose of the covid-19 vaccine (87.3% in the Spanish sample) is comparable to population estimates (88.0%).25 We could not estimate whether the prevalence of flat earthers or reptilian conspiracy believers in our sample is comparable to that in the Spanish population because, to our knowledge, no estimates are available for comparison. Assuming that a lower knowledge of risk factors for cancer is associated with non-response because of a social desirability bias, this would result in lower CAM scores in the general population than in our sample, which reinforces our conclusion that awareness of the actual and mythical causes of cancer was poor.

Comparison with previous studies

A cognitive paradox has been observed among people who reject covid-19 vaccines-they generally believe less in a wide range of well established facts and more in fake statements than do vaccine supporters26; this is consistent with our results. Our results on the overall endorsement of causes of cancer are mostly in agreement with the previous literature (supplementary figure A).21 27 28 29 30 Awareness of physical inactivity, human papillomavirus infection, and poor diet as risk factors for cancer is reported to be low.21 27 28 29 However, our estimates were lower for certain items, such as sunburn and low intake of fruits and vegetables, than for the CAM benchmark data.30 In line with our results, the most endorsed mythical causes of cancer in a representative English population were exposure to stress and food additives.21

Digital misinformation is abundant on the internet. False information spreads further and deeper than true information.31 32 Social media algorithms promote the use of a similar language that facilitates the aggregation of users. This results in many people believing in ideas, including conspiracies, that are clearly against the current scientific knowledge. Non-experts tend to justify the rejection of scientific evidence by questioning the motivation of experts and therefore resolving any cognitive dissonance.33 Conspiracists and people with a preference for alternative medicine may share a similar magical world view. Interestingly, those who preferred alternative medicine were more prone to endorse mythical causes of cancer than were the rest of the participants. In patients with cancer, the fear of death and serious side effects from standard treatments may drive people to seek alternative treatments, which can become a source of hope and empowerment but are associated with increased mortality.34 Thus, these patients are especially vulnerable to misinformation that could lead to delays in treatment, the toxicity of alternative therapies, or adverse interactions with standard care.6

Some organisations have taken initial steps to reduce the increasing amount of misinformation on healthcare. Examples include fact checking approaches, such as the website Rumor Control by the US Food and Drug Administration,35 and "inoculation" approaches that include tutorials informing people of fake news to help them to make better choices about what to share online.36 Additionally, interventions to rate or reflect the accuracy of online content are effective in distinguishing between true and false content.36 Crowd sourced accuracy ratings are proposed to improve online ranking algorithms.36 Accordingly, the US National Academies of Sciences, Engineering, and Medicine proposed new communication strategies, including the reconfiguration of platform features that promote misinformation.37 They also proposed partnering with trusted social media, cultivating scientific literacy, and monitoring content that spreads misinformation.37 Other authors have suggested that persuasive messages reflecting different world views of the population (tailored health communication) could be more effective than fact based campaigns.13 38

Strengths and limitations of study

This study is the first to show the possible patterns of beliefs about cancer among conspiracy believers. Our sample size was relatively large but limited among conspiracy groups because we obtained a reduced number of responses from certain platforms. Particularly, we had low "karma" on Reddit, which limited the distribution of our survey, and we were banned from several platforms (including 4Chan), which highlighted the perceptions of institutional organisations as untrustworthy. The main limitation is that we used an anonymous online cross sectional survey, which may be associated with response and sampling biases. We had conversations with an individual who believed in the reptilian conspiracy and learnt about the presence of potentially paranoid features in this group: they may feel spied on by reptilians and would never answer the survey if it was not completely anonymous. This background knowledge implied the unfeasibility of sampling using telephone numbers and/or postal addresses; thus, we used a non-probability sampling approach wherein response rates and potential duplicate responses could not be evaluated. Representative probability sampling is effective, but it incurs considerable monetary, personal, and time costs. Additionally, its benefits have diminished owing to the decline in response rates over the years, and random digit dialling sampling is less feasible for young adults because of its low response rate.39 By contrast, non-probability sampling may be more prone to bias, although it is more feasible and cost effective. This bias can be controlled by weighting and statistical adjustments.40 We applied a weighting approach to the Spanish population, which showed mostly similar results and was significant for the association between CAM estimates and conspiracy beliefs, supporting our conclusions. Other observational designs, such as case-control or cohort studies, were not relevant to our research question and may also be subject to selection and response bias when the response is associated with the outcome of interest.41 42

Risk factors classified as mythical or non-established on the basis of current evidence may be reclassified in future as established risk factors, as the evaluation of causes of cancer is a dynamic process and will progress as new evidence becomes available. Our responses to conspiracy beliefs may be affected by "troll" or fake responses. Responses among those who preferred alternative medicine rather than conventional medicine were less prone to this misclassification bias by fake responses. This group endorsed mythical cancer causes the most and the actual causes the least. Another internationally validated instrument in English was developed to measure awareness and beliefs about cancer (ABC measure)43; however, no internationally validated instrument exists for mythical causes. Therefore, we used the CAM and CAM-MYCS measures, previously validated in the UK, which have a similar structure (with five possible responses rather than the four option ABC measure).18 19 Owing to the online administration of the survey, only people with internet access could respond to it, which raises the possibility of selection bias. However, in 2021, an estimated 94% of the Spanish population used the internet within the previous three months,44 so we expected a low impact of this bias.

A strategic multidisciplinary research agenda to evaluate the effect of misinformation on health is crucial. Different methods will be needed to answer the questions raised while creating this roadmap. For instance, interviewing one conspiracy believer gave relevant insights; formal qualitative studies may offer further information that can help to define enrolment strategies and increase participation rates. Innovative designs using alternative methods (using social media or even gaming platforms45) could help to approach a larger potentially misinformed audience and, combined with conventional designs, understand the burden of misinformation. Furthermore, a detailed characterisation of the wide range of non-scientific beliefs, ideally using existing scales on conspiracy and magical beliefs,46 47 48 49 50 will help to increase understanding of the effect of the different participant profiles on health.

Conclusion and implications

We evaluated the patterns of beliefs about cancer among people who believed in conspiracies, rejected the covid-19 vaccine, or preferred alternative medicine. We observed that the participants who belonged to these groups were more likely to endorse mythical causes of cancer than were their counterparts but were less likely to endorse the actual causes of cancer. Almost half of the participants, whether conspiracists or not, agreed with the statement "It seems like everything causes cancer," which highlights the difficulty that society encounters in differentiating actual causes of cancer from mythical causes owing to mass (veridical or not) information. This suggests a direct connection between digital misinformation and consequent potential erroneous health decisions, which may represent a further preventable fraction of cancer. Cultivating oriented medical education and scientific literacy, improving online ranking algorithms, building trust, and using effective health communication and social marketing campaigns may be possible ways to tackle this complex public health threat.

What is already known on this topic

Knowing the established risk factors for cancer is the first step in ensuring adherence to cancer prevention recommendations

Difficulties in differentiating the actual causes of cancer from mythical causes are caused by mass information, some of which is not based on scientific results

No data exist on vaccination scepticism or conspiracy beliefs-for example, reptilians or flat earth-in relation to beliefs about and attitudes to cancer prevention

What this study adds

Awareness of causes of cancer was poor, especially among people who rejected the covid-19 vaccine, preferred alternative medicine, or endorsed flat earth or reptilian conspiracies

This suggests a direct connection between digital misinformation and consequent potential erroneous health decisions, which may represent a further preventable fraction of cancer

Acknowledgments

We thank Edu Martin-Prieto, Eric Duell, Jordi Edo, Javi Sanz, Manu Jiménez, Emilio López, Aline Bosle, Javier Aparicio, Christopher Ray Thompson, Marisa Mena, Nati Patón, Beatriz Pelegrina, and Sonya Farrell for their invaluable contributions. We also thank all participants for participating in the survey. We are deeply grateful to the anonymous individual who believed in the reptilian conspiracy theory for helping to design the survey. Through interactions, we could better understand the suffering that misinformation is causing to cancer patients, conspiracy believers, and the entire society.

Web extra.

Extra material supplied by authors

Web appendix: Online survey

Web appendix: Supplementary materials

Notes

Contributors: LC conceived the study. All the authors participated in designing the study and interpreting the data. All the authors critically revised the manuscript for important intellectual content. LC and SP did the literature review and wrote the first draft of the manuscript. LC and YB analysed the data. LC is the guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: No external funding.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; LC has received speakers' honorariums from Roche outside this work; PPT has received honorariums from Werfen outside this work; IDIBELL has signed a contract with Roche to collaborate in the development of the bioinformatics pipeline of a research project to detect endometrial cancer; the Cancer Epidemiology Research Program, to which SP, YB, AM, MB, RI, PPT, BS, LA, and LC are affiliated, has received unrestricted grants from Merck Sharp and Dohme, human papillomavirus test kits free of charge from Roche, reagents from Integrated DNA Technologies and Roche Diagnostics at a 50% discount, and Colli-Pee devices from Novosanis free of charge for research purposes; no other relationships or activities that could appear to have influenced the submitted work.

The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; no important aspects of the study have been omitted; any discrepancies from the study as originally planned (and, if relevant, registered) have been explained.

Dissemination to participants and related patient and public communities: The authors will prepare a post for the blog https://mejorsincancer.org/ summarising the results of the study. This post will be further distributed in the forums in which participants were invited, including ForoCoches, Reddit, and others. The institutions to which the authors are affiliated (Catalan Institute of Oncology and IDIBELL) will prepare a press release to be distributed to journalists.

Provenance and peer review: Not commissioned; externally peer reviewed.

Ethics statements

Ethical approval

The study protocol was approved by the Ethics Committee for Clinical Research of Bellvitge University Hospital (reference PR294/21). All research participants gave written informed consent.

Data availability statement

Data are available from the corresponding author (lcostas@iconcologia.net) on reasonable request.

References

2. Wild C, Weiderpass E, Stewart B, eds. World Cancer Report: Cancer research for cancer prevention. World Health Organization, 2020. [ Google Scholar]

8. Golbeck J. Social media and shared reality Off the Edge: flat earthers, conspiracy culture, and why people will believe anything [ Kelly Weill Algonquin Books, 2022. 256 pp. Science 2022;375:624. 10.1126/science.abn6017 [ PubMed] [ CrossRef] Google Scholar]

10. Dery M. The Vast Santanic Conspiracy. In: I must not think bad thoughts: drive-by essays on American dread, American dreams. University of Minnesota Press, 2012. 10.5749/minnesota/9780816677733.003.0024. [[ CrossRef] Google Scholar]

12. Lantian A, Muller D, Nurra C, et al.. Stigmatized beliefs: Conspiracy theories, anticipated negative evaluation of the self, and fear of social exclusion. Eur J Soc Psychol 2018;48:939-54 10.1002/ejsp.2498. [[ CrossRef] Google Scholar]

14. Miro CJ, Toff B. How right-wing populists engage with cross-cutting news on online message boards: the case of ForoCoches and Vox in Spain. Int J Press, 2022. [ Google Scholar]

15. Willem C, Tortajada I. Gender, voice and online space: expressions of feminism on social media in Spain. Media Commun 2021;9:62-71 10.17645/mac.v9i2.3851. [[ CrossRef] Google Scholar]

18. Stubbings S, Robb K, Waller J, et al.. Development of a measurement tool to assess public awareness of cancer. Br J Cancer 2009;101(Suppl 2):S13-7. 10.1038/sj.bjc.6605385 [[ PubMed] [ CrossRef] PMC free article] [ Google Scholar]

37. National Academies of Sciences, Engineering, and Medicine. Health and Medicine Division. Board on Population Health and Public Health Practice. Roundtable on Health Literacy . Addressing Health Misinformation with Health Literacy Strategies: Proceedings of a Workshop-in Brief. National Academies Press, 2020. [[ PubMed] Google Scholar]

40. Valliant R, Dever JA. Survey weights: a step-by-step guide to calculation. Stata Press, 2018. [ Google Scholar]

45. Wang W, Rothschild D, Goel S, et al.. Forecasting elections with non-representative polls. Int J Forecast 2015;31:980-91 10.1016/j.ijforecast.2014.06.001. [[ CrossRef] Google Scholar]

Articles from The BMJ are provided here courtesy of BMJ Publishing Group

# data[].attributes.attachment_link.title
Christmas 2022: Don't Believe the Hype: Everything causes cancer? Beliefs and attitudes towards cancer prevention among anti-vaxxers, flat earthers, and reptilian conspiracists: online cross sectional survey

# data[].attributes.attachment_link.description
To evaluate, using an online non-probability sample, the beliefs about and attitudes towards cancer prevention of people professing vaccination scepticism or conspiracy theories.Cross sectional survey.Data collected mainly from ForoCoches (a well known ...

# data[].attributes.attachment_link.readable_text
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health.
Learn more: PMC Disclaimer | PMC Copyright Notice

Silvia Russel, 1, ² Gerben Westerhof, ³ Michael Scherer-Rath, ⁴ Fabiola Camuti, ⁵ Sabrina Kamstra, ⁶ Zarah M Bood, 1, ² Niels van Poecke, 1, ² Jeroen Lutters, ⁵ and Hanneke WM van Laarhoven 1, ²

Background

A diagnosis of advanced cancer can be described as an unexpected disruption of someone's life story, an experience of contingency. 1 To address an experience of contingency, a new sense of direction and coherence in life needs to be found. One's story of life needs to be rewritten, which requires creative thinking. This process may be supported by a specific art-perception method: Art-Based Learning. Art-Based Learning is a step-wise process of observing an artwork, creating a new narrative related to this artwork, and connecting this narrative to the personal situation. 2 Art-Based Learning is designed to stimulate creative thinking through four steps: 1. Formulation of a personal question. 2. Observation of details of an artwork. 3. Imagination of a story based on the artwork. 4. Sharing the art-perception experience and reflection on the link with the personal question with a fellow participant. We aimed to explore how persons with advanced cancer could benefit from Art-Based Learning to deal with contingency experiences and stimulate meaning-making.

Methods

To enable patients to view art works, an art-exhibition was curated by three art curators. To increase accessibility for the participating patients, the art-exhibition was located in the hospital where the patients were treated. The exhibition, entitled "Light," consisted of 21 artworks; photos ( n = 15), paintings ( n = 2), and prints ( n  = 4) in a mix of landscape, portrait, black/white, colored, and abstract works. The Art-Based Learning session lasted 1 h and all participating patients were individually guided through all steps by an art-guide. The study was exempted from ethical approval by the Amsterdam University Medical Centre Ethics Board, METC (Date: 03.12.2020, ref. number W20_089 # 20.116).

Participants with non-curable cancer in a good health condition (WHO 0 or 1) were invited consecutively, after being informed by a member of staff, by telephone by SR (female, social scientist, and more than 10 year experience as a professional performative artist), who explained the purpose and procedures of the study. As a first step, four patients were invited to participate and assess feasibility of the Art-Based Learning approach in within an hour. Next, an additional three patients were invited to participate. From these three patients, extensive data was collected by SR, viz. verbatim transcripts of expressions during Art-Based Learning, field notes on visual behavior, and short (max 10 min) feedback interviews. For participant characteristics, see Table 1 .

Table 1.

Bart

Cornelia

Angelique

Preparing for dead and eternal life

Creating meaning in life

Moving away from darkness

Beauty in life and in eternity

Creating past, present and future

Beauty and eternity

Active response

Active response

Active response

No Transformation

Transformation

Transformation

The collected data was analyzed by SR using both an inductive, as well as a deductive approach. As an inductive approach we chose Holistic Content Analysis (HCA). 3 In HCA, reading and re-reading the data usually results in three to four individual main themes. HCA is particularly suitable for doing justice to patients' stories as a whole. We also used a deductive approach to see how we could describe art-perception relations in Art-Based Learning from a theoretical framework about relating to the world. We found Resonance theory particularly useful as it describes the possibility of a transformation in the world relation. 4 Resonance theory takes emotions, cognition, and bodily actions into account. Resonance relations are characterized by moments of: (1) Contact (being affected by something in the world), (2) an active response, (3) Adaptive Transformation (emergence of a new personal perspective), and (4) Uncontrollability (the resonant relation may or may not occur and the type of transformation is unpredictable). In Resonance Theory, art relations are described as resonant relations par excellence.

Findings

All patients were found to be able to create a personal narrative within the projected time frame and indicated that this was meaningful for them.

Using Holistic Content Analysis we identified three individual themes for each of the participants, as indicated in Table 1 and illustrated with quotes. These themes were found to relate to the participants' experiences of contingency as formulated in their personal question. In the art-perception processes, we were also able to identify all four resonance characteristics: contact, active response, transformation, and uncontrollability (cf. Table 1 for illustrating quotes).

Discussion and conclusion

This is the first study which indicated that Art-Based Learning can facilitate cancer patients in the palliative phase to express an experience of contingency and to create new meaning in relation to an artwork. This could be achieved within a 1 h session, underscoring the feasibility of this approach in a palliative care context. Future research with larger groups of patients should indicate whether the Art-Based Learning approach provides long term benefit for patients in terms of meaning making. Specific research questions include the influence of the specific theme and artworks chosen for the exhibition, the effect of providing multiple sessions to patients rather than one, and the potential of a digital exhibition with a digital home-based Art-Based Learning session. As such, Art-Based Learning has potential to support meaning making in patients with advanced cancer.

Footnotes

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was financially supported by the Regieorgaan SIAKIEM-hbo (grant number KIEM.VRIJ.04.134).

ORCID iDs: Silvia Russel https://orcid.org/0000-0002-7375-5872

Hanneke WM van Laarhoven https://orcid.org/0000-0003-3546-9709

References

1. Hartog I, Scherer-Rath M, Kruizinga R, et al. Narrative meaning making and integration: toward a better understanding of the way falling ill influences quality of life. J Health Psychol 2020; 25: 738-754. [[ PubMed] PMC free article] [ Google Scholar]

2. Lutters J. In the shadow of the artwork, art-based learning in practice. Amsterdam: Valiz, 2019, pp.15-28. [ Google Scholar]

3. Lieblich A, Tuval-Mashiach R, Zilber T. The holistic-content perspective. In: Narrative research: reading, analysis, and interpretation. London: Sage, 1998, pp.62-87. [ Google Scholar]

4. Rosa H. Resonance: A sociology to our relation to the world. Cambridge: Polity Press, 2019, pp.286-301. [ Google Scholar]

Articles from Palliative Medicine are provided here courtesy of SAGE Publications

# data[].attributes.attachment_link.title
Art-Based Learning in the last stage of life: An exploratory study on how cancer patients create meaning in relation to artworks

# data[].attributes.attachment_link.description
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health.

# data[].attributes.attachment_link.title
Ethical Issues in Cancer Genetics - Holland-Frei Cancer Medicine - NCBI Bookshelf

# data[].attributes.attachment_link.description
The heritable cancer predispositions, such as the Li-Fraumeni and familial breast/ovarian cancer syndromes, require that oncologists consider the ethical issues regarding the clinical and research use of genetic tests.177 These issues include (1) the appropriate use of genetic tests in high- and average-risk persons; (2) the genetic testing of children; (3) the familial implications of genetic information; (4) the protection of genetic privacy; and (5) the problems raised by genetic research.

# data[].attributes.attachment_link.title
Cancer: A Historic Perspective | SEER Training

# data[].attributes.attachment_link.description
Since the earliest medical records were kept, cancer as a disease has been described in the history of medicine. The earliest known descriptions of cancer appear in seven papyri, discovered and deciphered late in the 19th century. They provided the first direct knowledge of Egyptian medical practice. Two of them, known as the “Edwin Smith” and “George Ebers” papyri, contain descriptions of cancer written around 1600 B.C., and are believed to date from sources as early as 2500 B.C. The Smith papyrus describes surgery, while the Ebers’ papyrus outlines pharmacological, mechanical, and magical treatments.

# data[].attributes.attachment_link.description
This page answers questions like, is cancer genetic? Can cancer run in families? How do genetic changes cause cancer? Should I get genetic testing for cancer risk?

# data[].attributes.attachment_link.title
2024 Cancer Facts & Figures Cancer | 2024--First Year the US Expects More than 2M New Cases of Cancer

# data[].attributes.attachment_link.description
The American Cancer Society reports lower overall cancer death rates, yet incidence is increasing for many common cancers, including 6 of the top 10.

# data[].attributes.body
https://research.ebsco.com/c/rr6pft/viewer/pdf/uz2lkv5gc5

# data[].attributes.attachment_link.readable_text
The air throughout south-east Louisiana's "Cancer Alley" is probably being poisoned with a highly carcinogenic gas at levels much higher than previously thought, new research reveals.

Using cutting-edge equipment that more accurately checks for the gas, ethylene oxide, which is primarily used in plastic production, researchers found levels more than 1,000 times above previous measurements, and about 10 times higher on average than regulators' modeling.

The levels pose a "worrisome" risk to residents and workers in the region, especially children, said Pete DeCarlo, a Johns Hopkins University researcher and senior author of the paper. Residents in the region are majority lower-income and African American.

"I don't think there's any census tract in the area that wasn't at higher risk for cancer than we would deem acceptable," DeCarlo said. "We expected to see ethylene oxide in this area. But we didn't expect the levels that we saw, and they certainly were much, much higher than EPA's estimated levels."

Ethylene oxide is linked at low levels of exposure to multiple cancers, DNA damage, lung injury and other serious health issues. It's used in the production of other chemicals for plastic and in a fumigation process for sterilizing surgical equipment and food canisters. Though ethylene oxide is emitted from industrial plants around the nation, it's most widely used in Louisiana because of the high number of chemical facilities.

The most common exposure route is inhalation. The EPA found a cancer risk in air samples at 11 parts per trillion, an exceptionally low level compared with many other common air pollutants, like ozone.

"This is a really, really, really small amount," DeCarlo said, which is why getting an accurate reading on the levels is essential, he added.

The Environmental Protection Agency collects air samples in and around facilities that emit the gas and takes them to labs for measurement. But the gas quickly changes once in a sampling container and its true volume becomes difficult to measure.

Researchers spent a month during winter 2023 repeatedly driving a heavily industrialized route along the Mississippi River between New Orleans and Baton Rouge, collecting air and testing it in real time as they drove past large industrial facilities and nearby residential areas.

The equipment detected plumes that were up to seven miles long coming from some facilities, showing that the gas is concentrated enough at that distance to still present a health threat. East Ascension high school in Gonzales, Louisiana, is about five miles from one of the identified ethylene oxide hotspots.

It's unclear whether the chemicals are being released from stacks or as fugitive emissions that escape through piping or equipment throughout the plants.

The EPA in 2018 established lower cancer risk levels for the chemical, DeCarlo said, noting that industry disagrees with the agency's assessment. It is classified as a hazardous air pollutant, so the government aims to allow zero emissions, but polluters are given permits to emit some of the substance each year.

Using an EPA tool that weighs a chemical's total hazard in the region, researchers found ethylene oxide comprised 68% of the threat for hazardous air pollutants in Cancer Alley.

skip past newsletter promotion
Get the most important US headlines and highlights emailed direct to you every morning
Privacy Notice: Newsletters may contain info about charities, online ads, and content funded by outside parties. For more information see our Privacy Policy. We use Google reCaptcha to protect our website and the Google Privacy Policy and Terms of Service apply.
after newsletter promotion

Though the tool paints a broad picture, "the fact that so much of the environmental risk in this area seems to come from a single chemical is remarkable", the authors wrote in the study.

DeCarlo said researchers focused on ethylene oxide because it is so carcinogenic and very little data exists, but he noted it's only one of countless chemicals that people in the area are exposed to.

"The reality is people aren't just breathing ethylene oxide, they are breathing a whole soup of chemicals," he said. "When you start to add everything up, it becomes a much more problematic picture."

The Louisiana Chemical Association (LCA) disputed the findings, calling into question the study's methodology.

"The Louisiana Chemical Association's industry partners are constantly working towards lowering all emissions," said Greg Bowser, president and CEO of the LCA.

"According to the EPA, from 2013 to 2022, releases of ethylene oxide into the air have decreased by 43%. We all live and work here. Our goal is to better our state and our community while continuing to manufacture the materials vital to our medical and agricultural products.'"

# data[].attributes.attachment_link.title
Air in Louisiana's 'Cancer Alley' likely more toxic than previously thought

# data[].attributes.attachment_link.description
New research reveals levels of ethylene oxide more than 1,000 times above previous measurements