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An official publication of the Middle-Eastern Association for Cancer Research
Clinical Cancer Investigation Journal
ISSN Print: 2278-1668, Online: 2278-0513
ARTICLE
Year: 2024   |   Volume: 13   |   Issue: 2   |   Page: 26-33     View issue

The Relationship Between Cancer Screening, Cancer Awareness, and Cancer Beliefs: The Case of American Population


, , ,
  1. Faculty of Economics and Administrative Sciences, Dicle University, Diyarbakir, Turkey.
  2. Department of Nursing, Istanbul Nisantasi University, Istanbul, Turkey.
Abstract

Although cancer is a global public health problem, it is at the forefront of the disease burden ranking of countries. It tried to examine the relationship between screening, awareness, and belief variables for cancer, which is a significant health problem. The Health Information National Trends Survey (HINTS 6) data was used. The association between cancer screening, awareness, and belief was evaluated using Pearson's r Correlation Coefficient with data from 6252 American adults. Moderate and high correlations were found between the variables analyzed within the scope of the study. There was a strong positive correlation between interest in cancer screening and concern about getting cancer (r=0.707; p<0.001) and a strong positive correlation between cancer prevention and cancer treatments, cancer screenings (r=0.608; p<0.001) and general health status (r=0.491; p<0.001). It is thought that studies to increase cancer screening and awareness may positively affect individuals' health behaviors. Therefore, it is recommended that strategies be developed that can help improve public health behaviors and make significant progress in the fight against cancer by increasing cancer screening and awareness.

Keywords: Cancer screening, Cancer awareness, Cancer beliefs, Health behaviors, American population

Introduction

Cancer is recognized as an essential health problem worldwide and is the second leading cause of death in the United States of America.[1] The burden of cancer continues to increase globally, putting significant physical, emotional, and financial pressure on individuals, families, communities, and health systems. In countries with robust health systems, survival rates for many types of cancer can be increased through accessible early diagnosis, quality treatment, and survivorship care.[2] In order to achieve early diagnosis and thus prolong the life span of patients, it is necessary to increase the level of awareness, consciousness, and knowledge of society about cancer and screening programs. In a study conducted on awareness levels, poor cancer awareness was shown to be an essential reason for lower survival and higher mortality rates, especially among the black American population. It has been stated that low awareness leads to worse outcomes because people present to the medical care system when they are in the advanced stage of cancer.[3] Therefore, to increase awareness, practices that may lead to an increase in the belief levels of society towards cancer should be put forward, and the groups at risk should be directed to screening programs by raising awareness of society by health authorities. However, it is also possible to come across studies indicating various barriers to participation in cancer screening programs. Studies are showing that cultural factors such as knowledge, beliefs, and attitudes about cancer disease or screening process, lack of health insurance, communication problems, distrust in the health system, and fatalistic beliefs may prevent participation in cancer screening programs.[4] As a result of the literature review, it is possible to find studies showing that studies' beliefs about cancer are more directive and may affect patients' cancer awareness and participation in screening programs. For example, in a study conducted with 108 patients, participants' cognitive and emotional beliefs about lung cancer were evaluated. Self-reporting served to gauge the intention to undergo lung cancer screening with a CT scan. Fatalistic beliefs, fear of radiation exposure, and anxiety about CT scans were found to be significantly associated with decreased intention to screen. It was found that
 

 

differences were observed in the beliefs of minority and non-minority participants about lung cancer and screening.[5]

It is known that various cognitive, emotional, and cultural factors affect belief. Considering that there is a close relationship between belief and action, the relationship between beliefs about cancer, awareness, and screening programs was addressed within the scope of the study. The relationship between these variables was tried to be explicitly revealed for cancer patients.

Materials and Methods

The materials and methods used within the scope of the research are to be explained in the form of sub-headings. Such a way was followed due to the complexity of the method used.

Study setting and timing

This study was conducted from March 7 – November 8, 2022, to obtain 7,000 completed questionnaires in the United States of America by the National Cancer Institute (NCI). The population of this study is Americans who participated in the Health Information National Trends Survey (HINTS) conducted by the NCI.[6]

Study design

This study was conducted using a descriptive cross-sectional type. The model of the study is the relational screening model, a causal comparison subtype of quantitative research methods. The study complied with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement’s guidelines for reporting cross-sectional studies (Table 1).

 

 

Table 1. STROBE Statement—checklist of items that should be included in reports of observational studies.

 

Item No.

Recommendation

Page
No.

Relevant text from manuscript

Title and abstract

1

(a) Indicate the study’s design with a commonly used term in the title or the abstract

269

 

(b) Provide in the abstract an informative and balanced summary of what was done and what was found

269

 

Introduction

 

Background/rationale

2

Explain the scientific background and rationale for the investigation being reported

269-270

 

Objectives

3

State specific objectives, including any prespecified hypotheses

269-270

 

Methods

 

Study design

4

Present key elements of study design early in the paper

270

 

Setting

5

Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection

270

 

Participants

6

(a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls.

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

270

 

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case

270

 

Variables

7

Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable

270

 

Data sources/ measurement

8*

For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group

270

 

Bias

9

Describe any efforts to address potential sources of bias

270

 

Study size

10

Explain how the study size was arrived at

270

 

Quantitative variables

11

Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why

270

 

Statistical methods

12

(a) Describe all statistical methods, including those used to control for confounding

270

 

(b) Describe any methods used to examine subgroups and interactions

270

 

(c) Explain how missing data were addressed

270

 

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed

Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

 

 

(e) Describe any sensitivity analyses

 

 

Results

 

Participants

13*

(a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed

270-274

 

(b) Give reasons for non-participation at each stage

270-274

 

(c) Consider use of a flow diagram

270-274

 

Descriptive data

14*

(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders

270

 

(b) Indicate number of participants with missing data for each variable of interest

270-274

 

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

 

 

Outcome data

15*

Cohort study—Report numbers of outcome events or summary measures over time

 

 

Case-control study—Report numbers in each exposure category, or summary measures of exposure

270-274

 

Cross-sectional study—Report numbers of outcome events or summary measures

270-274

 

Main results

16

(a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included

270-274

 

(b) Report category boundaries when continuous variables were categorized

270-274

 

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period

270-274

 

Other analyses

17

Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses

270-274

 

Discussion

 

Key results

18

Summarise key results with reference to study objectives

270-274

 

Limitations

19

Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias

270-274

 

Interpretation

20

Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence

270-274

 

Generalisability

21

Discuss the generalisability (external validity) of the study results

270-274

 

Other information

 

Funding

22

Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based

270-274

 

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org

 

Participants

Participants were civilian, noninstitutionalized, aged 18 and over, living adults in the United States who participated in the HINTS survey conducted by the NCI.

Sample size and sampling

The sampling strategy for the HINTS 6 survey consisted of a two-stage design. In the first stage, a stratified sample of addresses was selected from a file of residential addresses. In the second stage, one adult was selected within each sampled household. With this two-stage sampling, the sample size of 6252 people was determined.

Data collection tools

The data were collected with the HINTS 6 survey by NCI, published in 2023. Questions in the HINTS 6 survey, such as gender, age, full-time employment status, occupation, marital status, education level, ethnicity, income range, perceived income level, frequency of going to health institutions, and general health status, were used to collect findings regarding the demographic information of the participants. Questions such as lung cancer, cervical cancer, colorectal cancer, and HPV knowledge were used to collect findings regarding the participants' cancer screening and awareness levels. In addition, findings regarding the participants' beliefs about cancer were reported regarding the question of the possibility of getting cancer.

Data analysis

Frequency and percentage values were used to report demographic and other discrete variables. Pearson Correlation Coefficient was used for correlation analysis. All analyses employed a two-sided p-value < 0.05 at a 95% confidence level. All analyses were performed with Jamovi Version 2.4 computer software.[7, 8]

Ethical consideration and responsibilities

Ethical approval and participant consent were not required as this study involved publicly available de-identified data.

Results and Discussion

 

 

Table 2. Results Regarding the Demographic Information of the Participants

Variables

n

% of Total

Gender

Missing Data

410

6.6 %

Male

2307

36.9 %

Female

3535

56.5 %

Work Full Time

Missing Data

412

6.6 %

Yes

2778

44.4 %

No

3062

49.0 %

Occupation

Missing Data

390

6.2%

Employed only

2761

44.16%

Homemaker only

221

3.5%

Student only

63

1.0%

Retired only

1725

27.6%

Disabled only

326

5.2%

Multiple Occupation statuses selected

473

7.6%

Unemployed for one year or more only

148

2.4%

Unemployed for less than one year only

101

1.6%

Other OccupationOccupation only

44

0.7%

Marital Status

Missing Data

415

6.6%

Married

2624

42.0 %

Living as married or living with a romantic partner

373

6.0 %

Divorced

939

15.0 %

Widowed

646

10.3 %

Separated

136

2.2 %

Single, never been married

1119

17.9 %

Education

Missing Data

404

6.5%

Less than eight years

116

1.9 %

8 through 11 years

271

4.3 %

12 years or completed high school

1068

17.1 %

Post-high school training other than college (vocational or

433

6.9 %

Some college

1239

19.8 %

College Graduate

1613

25.8 %

Postgraduate

1108

17.7 %

Ethnicities

Missing Data

644

10.3%

Not Hispanic only

4607

73.7 %

Mexican only

477

7.6 %

Puerto Rican only

111

1.8 %

Cuban only

41

0.7 %

Other Hispanic only

331

5.3 %

Multiple Hispanic ethnicities selected

41

0.7 %

Income Ranges

Missing Data

732

11.7%

$0 to $9,999

389

6.2 %

$10,000 to $14,999

304

4.9 %

$15,000 to $19,999

266

4.3 %

$20,000 to $34,999

729

11.7 %

$35,000 to $49,999

732

11.7 %

$50,000 to $74,999

937

15.0 %

$75,000 to $99,999

694

11.1 %

$100,000 to $199,999

1012

16.2 %

$200,000 or more

457

7.3 %

Income Feelings

Missing Data

485

7.8%

Living comfortably on present income

2518

40.3 %

Getting by on present income

2140

34.2 %

Finding it difficult on present income

763

12.2 %

Finding it very difficult on present income

346

5.5 %

Frequencies Go, Provider,

Missing Data

117

1.9%

None

698

11.2 %

One time

862

13.8 %

Two times

1165

18.6 %

Three times

973

15.6 %

Four times

881

14.1 %

5-9 times

962

15.4 %

Ten or more times

594

9.5 %

General Health Statues

Missing Data

234

3.7%

Excellent

600

9.6 %

Very good

2081

33.3 %

Good

2249

36.0 %

Fair

932

14.9 %

Poor

156

2.5 %

 

 

The majority of the participants were women; the number of people working full time was less than those who were not working; the majority of them were working and retired, the majority of them were married, college graduates, and not only Hispanic; the majority of them had an annual income between 100 thousand and 200 thousand dollars and live comfortably with their current income. It was determined that the majority of them receive service from health institutions at least twice a year. Their general health condition is good or excellent (Table 2).

 

 

 

Table 3. Participants Results Regarding Cancer Screening and Awareness Levels

Variables

n

% of Total

Has a healthcare professional talked to you about checking for lung cancer?

Missing Data

389

6.2 %

I have never heard of this test

1408

22.5 %

Yes

261

4.2 %

No

3955

63.3 %

Do not know

239

3.8 %

How long ago did you have your most recent Pap test to check for cervical cancer?

Missing Data

549

9.9%

Inapplicable, coded 1 in BirthGender

1069

17.1 %

A year ago or less

1148

18.4 %

More than 1, up to 2 years ago

605

9.7 %

More than 2, up to 3 years ago

424

6.8 %

More than 3, up to 5 years ago

287

4.6 %

More than five years ago

829

13.3 %

I have never had a Pap test

169

2.7 %

I am male (Web only)

1172

18.7 %

Has a doctor or other health professional ever told you there are a few different tests to detect colorectal cancer?

Missing Data

454

7.3%

Yes

3011

48.2 %

No

1379

22.1 %

I have never discussed these tests with a doctor, or other he

1408

22.5 %

Have you ever heard of HPV?

Missing Data

 

 

Yes

3942

63.1 %

No

1945

31.1 %

Do you think HPV can cause cervical cancer?

Misising Data

585

9.4%

Inapplicable, coded 2 in HeardHPV

1753

28.0 %

Yes

2468

39.5 %

No

63

1.0 %

Not sure

1383

22.1 %

Before today, have you ever heard of the cervical cancer vaccine or HPV shot?

Missing Data

417

6.7%

Yes

3730

59.7 %

No

2105

33.7 %

 

 

 

A large portion of participants reported not speaking to a healthcare professional to check for lung cancer. On the other hand, 18.4 percent of female participants reported having had a Pap test for cervical cancer in the last year or more recently. Most participants stated that a physician or healthcare professional informed them that several tests were available to detect colorectal cancer. The majority of the participants stated that they had heard of HPV and thought that it caused cervical cancer and that they also had information about the cervical cancer vaccine or HPV shot (Table 3).

 

 

Table 4. Relationship Between Cancer Screening, Awareness and Cancer Beliefs (n=6552)

Variables

n

% of Total

Compared to other people your age, how likely do you think you are to get cancer in your lifetime?

Missing Data

91

1.5 %

I already had cancer

562

9.0 %

Very unlikely

482

7.7 %

Unlikely

678

10.8 %

Neither likely nor unlikely

1636

26.2 %

Likely

905

14.5 %

Very likely

287

4.6 %

I do not know

1304

20.9 %

 

Most of the participants marked "neither likely nor unlikely" for their risk of getting cancer compared to their peers (Table 4).

 

 

Table 5. Mean and Standard Deviation Values for Continuous Variables for Participants

 

InterestedCaScreening

FreqWorryCancer

P3_Total

P4_Total

P5_Total

P6_Total

General Health

Age

n

6252

6252

6252

6252

6252

6252

6252

6252

Mean

2.40

2.04

7.07

3.49

7.95

3.61

2.28

54.6

Standard deviation

2.82

2.75

10.4

5.41

12.8

5.52

2.14

19.1

InterestedCaScreening: Interested in having a cancer screening test in the next year; FreqWorryCancer: Worried about getting cancer; P3_Total: Everything causes cancer, prevention not possible, too many recommendations, cancer fatal; P4_Total: Increase cancer soda sugar, Increase cancer alcohol; P5_Total: Increase cancer too much-processed meat, Increase cancer too much red meat, Increase cancer too much fast food, Not eating enough fruits and vegetables, Not getting enough sleep; P6_Total: Cancer progress prevention, cancer progress cures.

 

It seemed that very few of the participants had cancer, and almost one in two were interested in cancer screening tests. Very few of the participants are worried about getting cancer. It was determined that the majority of the participants believe that everything causes cancer, that it is unpreventable, that there are many recommendations for cancer, and that cancer is a fatal disease. Many participants stated that soda, sugar, alcohol use, too much processed meat, too much red meat, too much fast food, not eating enough fruits and vegetables, and not getting enough sleep increased cancer (Table 5).

 

Table 6. Relationship Between Cancer Screening, Awareness and Cancer Beliefs (n=6552)

 

 

Interested Ca Screening

FreqWorryCancer

P3_Total

P4_Total

P5_Total

P6_Total

General Health

InterestedCaScreening

Pearson's r

1

 

 

 

 

 

 

p-value

 

 

 

 

 

 

FreqWorryCancer

Pearson's r

0.707***

1

 

 

 

 

 

p-value

< .001

 

 

 

 

 

P3_Total

Pearson's r

0.688***

0.741***

1

 

 

 

 

p-value

< .001

< .001

 

 

 

 

P4_Total

Pearson's r

0.626***

0.665***

0.776***

1

 

 

 

p-value

< .001

< .001

< .001

 

 

 

P5_Total

Pearson's r

0.648***

0.686***

0.802***

0.875***

1

 

 

p-value

< .001

< .001

< .001

< .001

 

 

P6_Total

Pearson's r

0.608***

0.665***

0.738***

0.777***

0.838***

1

 

p-value

< .001

< .001

< .001

< .001

< .001

 

general health

Pearson's r

0.491***

0.505***

0.487***

0.490***

0.510***

0.488***

1

p-value

< .001

< .001

< .001

< .001

< .001

< .001

* p<0.05; **p<0.01; ***p<0.001; InterestedCaScreening: Interested in having a cancer screening test in the next year; FreqWorryCancer: Worried about getting cancer; P3_Total: Everything cause cancer, prevent not possible, too many recommendations, cancer fatal; P4_Total: Increase cancer soda sugar, Increase cancer alcohol; P5_Total: Increase cancer too much-processed meat, Increase cancer too much red meat, Increase cancer too much fast food, Not eating enough fruits and vegetables, Not getting enough sleep; P6_Total: Cancer progress prevention, cancer progress cures.

 

A strong positive relationship was detected between interest in cancer screening and concern about getting cancer (r=0.707; p<0.001). A strong positive relationship was found between the variable consisting of the combined variables that everything causes cancer, that it is not possible to protect from cancer, that there are many recommendations for cancer, and that cancer is fatal, and being interested in cancer screening (r = 0.688; p < 0.001). A statistically significant positive relationship was detected between a composite variable indicating that cancer increases with soda, sugar, and alcohol and interest in cancer screening (r=626; p<0.001). A positive relationship was detected between cancer and the composite variable of high consumption of processed meat, red meat consumption, fast food consumption, low fruit and vegetable consumption, and inadequate sleep (r = 648; p < 0.001). Finally, it was determined that there was a strong positive relationship between cancer prevention and cancer treatments, cancer screening (r=0.608; p<0.001), and general health status (r=0.491; p<0.001) (Table 6).

Within the scope of this study, the relationship between the data obtained from 6252 American adults and the level of cancer screening, cancer awareness, and beliefs about cancer of these individuals was examined. When the literature was examined, it was seen that there are different studies on this subject. However, the fact that the studies found in the literature generally focus on specific cancer patients and conducted research on smaller populations distinguishes this study from other studies. For example, in a study conducted by Tarı Selçuk et al. (2020), the study sample consists of women over 40, and it is seen that it is directed towards a more specific group.[9] This study used a data set representing American society in general.

The findings obtained within the scope of the study are generally in line with the findings of the studies in the literature. This study found a strong positive correlation between willingness to undergo cancer screening and concern about getting cancer (r=0.707; p<0.001). A medium- and high-level relationship between cancer screening and other variables was found. In addition, a strong positive relationship was found between cancer prevention and cancer treatments, cancer screenings (r=0.608; p<0.001), and general health status (r=0.491; p<0.001). In the study conducted by Maladze et al. (2023), positive attitudes toward cancer prevention and cancer screening were reported.[10] However, adverse reports were made about the effectiveness of treatments. In a study conducted by Özdemir et al. (2023), it was determined that prostate cancer men who participated in the study had low levels of knowledge about cancer screening, medium levels of sensitivity, seriousness, and barrier perceptions, and high levels of health motivation and benefit perceptions.[11] In another study by Lin et al. (2023), age and socioeconomic status were associated with more positive cancer attitudes and beliefs and more knowledge about cancer screening.[12]

A strong positive relationship was found between interest in cancer screening and concern about getting cancer (r=0.707; p<0.001). A study by Kong et al. (2022) found a positive relationship between concerns about getting cancer and participation behaviors in cancer screening.[13] It has been reported that lack of participation in screenings due to the concerns above and failure to detect cancer at an early stage will cause negative situations. In a study conducted by Katherine et al. (2018), individuals with a low perception of cancer screening are more likely to report information overload, fatalistic attitudes toward cancer, a lack of knowledge about cancer prevention, and frequent concerns about cancer.[14]

Within the scope of the study, it is also possible to come across studies that examine issues such as cancer screening and attitudes towards cancer at the level of different cultures and different societies. For example, in a study by Kam et al. (2016), Chinese culture strongly influences beliefs and attitudes towards cancer.[15] In another study conducted by Lesley et al. (2015), it is stated that the inclusion of a narrative brochure can positively affect beliefs about cancer screening.[16] With the findings obtained in this study, it can be stated that the levels of cancer awareness, cancer screening, and beliefs about cancer in American society in general may be high and interrelated factors.

Conclusion

This study examined the relationships between cancer screening, cancer awareness, and cancer beliefs in the American population. The study included data from 6252 American adults. The findings showed a strong positive relationship between cancer prevention and treatment, cancer screenings, and general health status. On the other hand, according to the cancer beliefs examined in the study, it was revealed that many participants believed that everything causes cancer, cancer is not preventable, and there are too many suggestions.

It was determined that individuals interested in cancer screening were more concerned about cancer risks and cared more about their general health status. Therefore, it is thought that efforts to increase cancer screening and awareness may positively affect individuals' health behaviors. According to the results obtained within the scope of this study, the following recommendations may be appropriate;

  • Campaigns and trainings for cancer screening and raising awareness should be accessible to citizens.
  • Awareness-raising activities should be carried out to correct false beliefs about cancer and the importance of early diagnosis. 
  • Health policies realized in the context of public health should focus on strategies to increase cancer screening and awareness.
  • Efforts to increase cancer screening and awareness should be planned and implemented, considering ethnic and socioeconomic differences.

Implementing these recommendations can help improve community health behaviors and make significant strides in the fight against cancer by increasing cancer screening and awareness.

Acknowledgments

None.

Conflict of interest

None.

Financial support

None.

Ethics statement

None.

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Cite this article
Vancouver
Cakmak C, Cinar F, Çapar H, Cakmak MA. The Relationship Between Cancer Screening, Cancer Awareness, and Cancer Beliefs: The Case of American Population. Clin Cancer Investig J. 2024;13(2):26-33. https://doi.org/10.51847/GKdrnoOVBT
APA
Cakmak, C., Cinar, F., Çapar, H., & Cakmak, M. A. (2024). The Relationship Between Cancer Screening, Cancer Awareness, and Cancer Beliefs: The Case of American Population. Clinical Cancer Investigation Journal, 13(2), 26-33. https://doi.org/10.51847/GKdrnoOVBT

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