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.
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]
Table 1. STROBE Statement—checklist of items that should be included in reports of observational studies. |
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1 |
(a) Indicate the study’s design with a commonly used term in the title or the abstract |
269 |
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(b) Provide in the abstract an informative and balanced summary of what was done and what was found |
269 |
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Background/rationale |
2 |
Explain the scientific background and rationale for the investigation being reported |
269-270 |
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3 |
State specific objectives, including any prespecified hypotheses |
269-270 |
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4 |
Present key elements of study design early in the paper |
270 |
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5 |
Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection |
270 |
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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 |
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(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 |
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7 |
Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable |
270 |
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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 |
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9 |
Describe any efforts to address potential sources of bias |
270 |
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10 |
Explain how the study size was arrived at |
270 |
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11 |
Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why |
270 |
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Statistical methods |
12 |
(a) Describe all statistical methods, including those used to control for confounding |
270 |
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(b) Describe any methods used to examine subgroups and interactions |
270 |
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(c) Explain how missing data were addressed |
270 |
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(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 |
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(e) Describe any sensitivity analyses |
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Results |
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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 |
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(b) Give reasons for non-participation at each stage |
270-274 |
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(c) Consider use of a flow diagram |
270-274 |
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Descriptive data |
14* |
(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders |
270 |
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(b) Indicate number of participants with missing data for each variable of interest |
270-274 |
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(c) Cohort study—Summarise follow-up time (eg, average and total amount) |
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15* |
Cohort study—Report numbers of outcome events or summary measures over time |
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Case-control study—Report numbers in each exposure category, or summary measures of exposure |
270-274 |
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Cross-sectional study—Report numbers of outcome events or summary measures |
270-274 |
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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 |
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(b) Report category boundaries when continuous variables were categorized |
270-274 |
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(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period |
270-274 |
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17 |
Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses |
270-274 |
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18 |
Summarise key results with reference to study objectives |
270-274 |
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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 |
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20 |
Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence |
270-274 |
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21 |
Discuss the generalisability (external validity) of the study results |
270-274 |
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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 |
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*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.
Participants were civilian, noninstitutionalized, aged 18 and over, living adults in the United States who participated in the HINTS survey conducted by the NCI.
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.
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.
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 approval and participant consent were not required as this study involved publicly available de-identified data.
Table 2. Results Regarding the Demographic Information of the Participants |
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Variables |
n |
% of Total |
|
Gender |
Missing Data |
410 |
6.6 % |
Male |
2307 |
36.9 % |
|
Female |
3535 |
56.5 % |
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Work Full Time |
Missing Data |
412 |
6.6 % |
Yes |
2778 |
44.4 % |
|
No |
3062 |
49.0 % |
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Occupation |
Missing Data |
390 |
6.2% |
Employed only |
2761 |
44.16% |
|
Homemaker only |
221 |
3.5% |
|
Student only |
63 |
1.0% |
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Retired only |
1725 |
27.6% |
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Disabled only |
326 |
5.2% |
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Multiple Occupation statuses selected |
473 |
7.6% |
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Unemployed for one year or more only |
148 |
2.4% |
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Unemployed for less than one year only |
101 |
1.6% |
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Other OccupationOccupation only |
44 |
0.7% |
|
Marital Status |
Missing Data |
415 |
6.6% |
Married |
2624 |
42.0 % |
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Living as married or living with a romantic partner |
373 |
6.0 % |
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Divorced |
939 |
15.0 % |
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Widowed |
646 |
10.3 % |
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Separated |
136 |
2.2 % |
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Single, never been married |
1119 |
17.9 % |
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Education |
Missing Data |
404 |
6.5% |
Less than eight years |
116 |
1.9 % |
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8 through 11 years |
271 |
4.3 % |
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12 years or completed high school |
1068 |
17.1 % |
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Post-high school training other than college (vocational or |
433 |
6.9 % |
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Some college |
1239 |
19.8 % |
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College Graduate |
1613 |
25.8 % |
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Postgraduate |
1108 |
17.7 % |
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Ethnicities |
Missing Data |
644 |
10.3% |
Not Hispanic only |
4607 |
73.7 % |
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Mexican only |
477 |
7.6 % |
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Puerto Rican only |
111 |
1.8 % |
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Cuban only |
41 |
0.7 % |
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Other Hispanic only |
331 |
5.3 % |
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Multiple Hispanic ethnicities selected |
41 |
0.7 % |
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Income Ranges |
Missing Data |
732 |
11.7% |
$0 to $9,999 |
389 |
6.2 % |
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$10,000 to $14,999 |
304 |
4.9 % |
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$15,000 to $19,999 |
266 |
4.3 % |
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$20,000 to $34,999 |
729 |
11.7 % |
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$35,000 to $49,999 |
732 |
11.7 % |
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$50,000 to $74,999 |
937 |
15.0 % |
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$75,000 to $99,999 |
694 |
11.1 % |
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$100,000 to $199,999 |
1012 |
16.2 % |
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$200,000 or more |
457 |
7.3 % |
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Income Feelings |
Missing Data |
485 |
7.8% |
Living comfortably on present income |
2518 |
40.3 % |
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Getting by on present income |
2140 |
34.2 % |
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Finding it difficult on present income |
763 |
12.2 % |
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Finding it very difficult on present income |
346 |
5.5 % |
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Frequencies Go, Provider, |
Missing Data |
117 |
1.9% |
None |
698 |
11.2 % |
|
One time |
862 |
13.8 % |
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Two times |
1165 |
18.6 % |
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Three times |
973 |
15.6 % |
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Four times |
881 |
14.1 % |
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5-9 times |
962 |
15.4 % |
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Ten or more times |
594 |
9.5 % |
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General Health Statues |
Missing Data |
234 |
3.7% |
Excellent |
600 |
9.6 % |
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Very good |
2081 |
33.3 % |
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Good |
2249 |
36.0 % |
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Fair |
932 |
14.9 % |
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Poor |
156 |
2.5 % |
Table 3. Participants Results Regarding Cancer Screening and Awareness Levels |
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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 % |
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Yes |
261 |
4.2 % |
|
No |
3955 |
63.3 % |
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Do not know |
239 |
3.8 % |
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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 % |
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A year ago or less |
1148 |
18.4 % |
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More than 1, up to 2 years ago |
605 |
9.7 % |
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More than 2, up to 3 years ago |
424 |
6.8 % |
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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 % |
Table 4. Relationship Between Cancer Screening, Awareness and Cancer Beliefs (n=6552) |
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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 % |
Table 5. Mean and Standard Deviation Values for Continuous Variables for Participants |
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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 |
Table 6. Relationship Between Cancer Screening, Awareness and Cancer Beliefs (n=6552) |
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Interested Ca Screening |
FreqWorryCancer |
P3_Total |
P4_Total |
P5_Total |
P6_Total |
General Health |
InterestedCaScreening |
Pearson's r |
1 |
|
|
|
|
|
|
p-value |
|
|
|
|
|
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FreqWorryCancer |
Pearson's r |
0.707*** |
1 |
|
|
|
|
|
p-value |
< .001 |
|
|
|
|
|
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P3_Total |
Pearson's r |
0.688*** |
0.741*** |
1 |
|
|
|
|
p-value |
< .001 |
< .001 |
|
|
|
|
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P4_Total |
Pearson's r |
0.626*** |
0.665*** |
0.776*** |
1 |
|
|
|
p-value |
< .001 |
< .001 |
< .001 |
|
|
|
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P5_Total |
Pearson's r |
0.648*** |
0.686*** |
0.802*** |
0.875*** |
1 |
|
|
p-value |
< .001 |
< .001 |
< .001 |
< .001 |
|
|
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P6_Total |
Pearson's r |
0.608*** |
0.665*** |
0.738*** |
0.777*** |
0.838*** |
1 |
|
p-value |
< .001 |
< .001 |
< .001 |
< .001 |
< .001 |
|
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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 |
Implementing these recommendations can help improve community health behaviors and make significant strides in the fight against cancer by increasing cancer screening and awareness.
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