| Literature DB >> 24287495 |
Sarah L Cutrona1, Douglas W Roblin, Joann L Wagner, Bridget Gaglio, Andrew E Williams, Rosalie Torres Stone, Terry S Field, Kathleen M Mazor.
Abstract
BACKGROUND: Adults over age 40 are increasing their use of email and social media, raising interest in use of peer-to-peer Internet-based messaging to promote cancer screening.Entities:
Keywords: Internet; breast neoplasms; colorectal neoplasms; communication; early detection of cancer; electronic mail; health promotion; peer group; social media; social support
Year: 2013 PMID: 24287495 PMCID: PMC3868965 DOI: 10.2196/resprot.2886
Source DB: PubMed Journal: JMIR Res Protoc ISSN: 1929-0748
Figure 1Colorectal cancer screening message template with edits (example).
Figure 2Health communication network tool. Study participants were provided with blank worksheets and asked: “Please mark one stick figure for each person you can think of that you communicate with about routine health topics…these are people you would communicate with about routine health topics like cancer screening, vaccine shots, diet, or exercise.” The worksheet was used to facilitate the estimation of the number of emails or postcards promoting colorectal cancer screening that they would send to members of their social network.
Participant characteristics. χ2 used to derive P values shown for age, gender, race/ethnicity, education, marital status, ever had friends/family diagnosed with CRC, and ever had a colonoscopy. Analysis of variance–ANOVA used to derive P values for health literacy scores, numeracy, and self-efficacy.
| Characteristic | n | % | |
| Study sample |
| 438 | 100.0 |
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| Georgia | 130 | 29.7 |
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| Hawaii | 105 | 24.0 |
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| Massachusetts | 203 | 46.3 |
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| Black/African-American | 65 | 14.8 |
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| Asian/Pacific Islander | 45 | 10.3 |
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| White/Caucasian | 286 | 65.3 |
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| Other or not reported | 42 | 9.6 |
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| English | 419 | 95.7 |
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| English and other | 9 | 2.1 |
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| Other | 7 | 1.6 |
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| High School degree or less (includes technical school) | 104 | 23.7 |
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| At least some college | 331 | 75.6 |
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| 40-49 | 52 | 11.9 |
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| 50-59 | 157 | 35.8 |
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| 60-73 | 229 | 52.3 |
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| Male | 191 | 43.6 |
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| Female | 247 | 56.4 |
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| Married | 282 | 64.4 |
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| Unmarried | 153 | 34.9 |
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| Working for pay | 260 | 59.4 |
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| Retired | 126 | 28.8 |
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| Disabled | 17 | 3.9 |
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| Other | 35 | 8.0 |
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| Excellent/very good | 240 | 54.8 |
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| Good/fair/poor | 197 | 45.0 |
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| 0/1 | 336 | 76.7 |
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| 2+ | 99 | 22.6 |
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| Current smoker | 27 | 6.2 |
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| Current nonsmoker | 410 | 93.6 |
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| Yes | 385 | 87.9 |
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| No | 48 | 11.0 |
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| Yes | 382 | 87.2 |
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| No | 50 | 11.4 |
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| Yes | 318 | 72.6 |
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| No | 114 | 26.0 |
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| Verbal health literacy (CMLT-Listening) | 79.9 | (14.1) | |
| Print health literacy (CMLT-Reading) | 84.8 | (14.6) | |
| Numeracy | 78.5 | (21.9) | |
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| Self-efficacy (PEPPI) | 8.1 | (1.3) |
Use of email and social media to discuss health-related topics and to discuss cancer screening.
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| Total sample | Age 40-49 | Age 50-59 | Age 60-73 |
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| n | % | n | % | n | % | n | % |
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| Ever | 387 | 88.4 | 49 | 94.2 | 144 | 91.7 | 194 | 85.5 | .067 |
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| In past week | 370 | 84.5 | 47 | 90.4 | 135 | 86.0 | 188 | 82.8 | .345 |
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| For 5-7 days in past week | 303 | 69.2 | 39 | 75.0 | 120 | 76.4 | 144 | 63.4 | .016 |
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| To discuss routine health topics | 148 | 33.8 | 14 | 26.9 | 62 | 39.5 | 72 | 31.4 | .180 |
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| To discuss CRC screeninga | 55 | 12.6 | 6 | 11.5 | 24 | 15.3 | 25 | 10.9 | .683 |
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| To discuss breast cancer screeninga | 64 | 14.6 | 9 | 17.3 | 26 | 16.6 | 29 | 12.7 | .176 |
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| Ever | 247 | 56.4 | 43 | 82.7 | 107 | 68.2 | 97 | 42.4 | <.001 |
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| In past week | 245 | 55.9 | 43 | 82.7 | 105 | 67.7 | 97 | 42.4 | <.001 |
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| For 5-7 days in past week | 148 | 33.8 | 30 | 57.7 | 70 | 45.2 | 48 | 21.0 | <.001 |
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| Texting | 194 | 44.3 | 41 | 78.8 | 88 | 56.1 | 65 | 28.4 | <.001 |
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| 144 | 32.9 | 24 | 46.2 | 59 | 37.6 | 61 | 26.6 | .008 | |
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| Instant messaging/Internet-based chatting | 54 | 12.3 | 10 | 19.2 | 28 | 17.8 | 16 | 7.0 | .002 |
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| Video chatting | 31 | 7.1 | 5 | 9.6 | 16 | 10.2 | 10 | 4.4 | .068 |
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| 21 | 4.8 | 4 | 7.7 | 13 | 8.3 | 4 | 1.7 | .007 | |
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| 3 | 0.6 | 0 | 0.0 | 3 | 1.9 | 0 | 0.0 | .067 | |
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| Other | 3 | 0.7 | 1 | 1.9 | 1 | 0.6 | 1 | 0.4 | .500 |
| Used other e-communication to discuss routine health topics | 51 | 11.6 | 16 | 30.8 | 25 | 15.9 | 10 | 4.4 | .000 | |
| Used other e-communication to discuss CRC screeningc | 10 | 2.3 | 3 | 5.8 | 7 | 4.5 | 0 | 0.0 | .168 | |
| Used other e-communication to discuss breast cancer screeningc | 17 | 3.9 | 7 | 13.5 | 9 | 5.7 | 1 | 0.4 | .244 | |
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| Texting | 31 | 7.1 | 11 | 21.2 | 16 | 10.2 | 4 | 1.7 | .000 |
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| 21 | 4.8 | 5 | 9.6 | 10 | 6.4 | 6 | 2.6 | .053 | |
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| Instant messaging/ Internet-based chatting | 6 | 1.4 | 3 | 5.8 | 2 | 1.3 | 1 | 0.4 | .011 |
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| Video chatting | 3 | 0.7 | 0 | 0.0 | 2 | 1.3 | 1 | 0.4 | .505 |
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| 1 | 0.2 | 0 | 0.0 | 1 | 0.6 | 0 | 0.0 | .408 | |
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| Other | 2 | 0.5 | 1 | 1.9 | 1 | 0.6 | 0 | 0.0 | .163 |
| Uses cell phone to access Internet | 122 | 27.9 | 23 | 44.2 | 55 | 35.3 | 44 | 19.2 | .000 | |
aOnly asked of those who use email to discuss routine health topics.
bIncludes texting, Facebook, instant messaging, Internet-based or video chatting, Twitter, LinkedIn or other.
cOnly asked of those who use e-communication to discuss routine health topics.
Willingness to share personal CRC screening experience with friends and family and preferred mode.
| Mode by which CRC screening experience would be shared | Total sample | Age 40-49 | Age 50-59 | Age 60-73 |
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| n=433 | % | n=52 | % | n=156 | % | n=225 | % |
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| .620 | |||||||||||
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| Not willing | 10 | 2.3 | 0 | 0.0 | 4 | 2.6 | 6 | 2.7 |
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| Might be willing | 102 | 23.6 | 13 | 25.0 | 32 | 20.5 | 57 | 25.3 |
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| Very willing | 321 | 74.1 | 39 | 75.0 | 120 | 76.9 | 162 | 72.0 |
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| .393 | |||||||||||
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| Not willing | 84 | 21.8 | 8 | 16.3 | 30 | 21.1 | 46 | 23.7 |
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| Might be willing | 142 | 36.9 | 18 | 36.7 | 47 | 33.1 | 77 | 39.7 |
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| Very willing | 159 | 41.3 | 23 | 46.9 | 65 | 45.8 | 71 | 36.6 |
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| .029 | |||||||||||
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| Not willing | 119 | 47.4 | 13 | 30.2 | 48 | 45.3 | 58 | 56.9 |
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| Might be willing | 69 | 27.5 | 18 | 41.9 | 27 | 25.5 | 24 | 23.5 |
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| Very willing | 63 | 25.1 | 12 | 27.9 | 31 | 29.2 | 20 | 19.6 |
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Characteristics of respondents who are willing to pass along self-edited email or postcard messages sharing CRC screening experience (n=432).
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| Emaila | Postcard only | Would not send |
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| n=300 | % | n=74 | % | n=58 | % |
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| .010 | |||||||||||||||||
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| 40-49 | 42 | 82.4 | 5 | 9.8 | 4 | 7.8 |
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| 50-59 | 118 | 76.1 | 20 | 12.9 | 17 | 11.0 |
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| 60-73 | 140 | 61.9 | 49 | 21.7 | 37 | 16.4 |
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| .010 | |||||||||||||||||
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| Male | 117 | 62.2 | 37 | 19.7 | 34 | 18.1 |
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| Female | 183 | 75.0 | 37 | 15.2 | 24 | 9.8 |
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| .365 | |||||||||||||||||
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| Black/African-American | 46 | 70.8 | 15 | 23.1 | 4 | 6.2 |
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| Asian/Pacific Islander | 35 | 77.8 | 5 | 11.1 | 5 | 11.1 |
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| White/Caucasian | 192 | 68.3 | 47 | 16.7 | 42 | 14.9 |
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| Other or not reported | 27 | 65.9 | 7 | 17.1 | 7 | 17.1 |
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| <.001 | |||||||||||||||||
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| High School degree or less (includes technical school) | 55 | 53.9 | 33 | 32.4 | 14 | 13.7 |
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| At least some college | 243 | 74.3 | 41 | 12.5 | 43 | 13.1 |
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| .561 | |||||||||||||||||
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| Married | 198 | 71.2 | 45 | 16.2 | 35 | 12.6 |
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| Unmarried | 100 | 66.2 | 29 | 19.2 | 22 | 14.6 |
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| .063 | |||||||||||||||||
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| Yes | 103 | 76.9 | 19 | 14.2 | 12 | 9.0 |
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| No | 196 | 66.0 | 55 | 18.5 | 46 | 15.5 |
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| .039 | |||||||||||||||||
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| Yes | 221 | 70.4 | 58 | 18.5 | 35 | 11.1 |
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| No | 73 | 65.2 | 16 | 14.3 | 23 | 20.5 |
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| Verbal health literacy “CMLT-Listening”, mean (SD) | 81.24 (13.50) | 73.96 (15.11) | 81.26 (13.46) | <.001 | ||||||||||||||
| Print health literacy “CMLT-Reading”, mean (SD) | 86.23 (13.72) | 78.51 (15.60) | 85.39 (15.85) | <.001 | ||||||||||||||
| Numeracy, mean (SD) | 79.72 (20.18) | 71.62 (27.63) | 80.82 (21.99) | .012 | ||||||||||||||
| Self-efficacy “PEPPI”, mean (SD) | 8.18 (1.21) | 8.22 (1.51) | 7.56 (1.67) | .004 | ||||||||||||||
aThose indicated in the email column would send out either only emails or would send a mix of emails and postcards.
Willingness to send messages sharing CRC screening experience with peers.
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| Model 1a | Model 2b | ||||
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| Odds of being an email sender | Odds of being a postcard sender | Odds of sending either email or postcard | |||
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| OR | 95% CI | OR | 95% CI | OR | 95% CI |
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| 40-49 | 2.21 | 0.73-6.73 | 0.77 | 0.19-3.22 | 1.83 | 0.61-5.53 |
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| 50-59 | 1.72 | 0.89-3.29 | 1.06 | 0.47-2.41 | 1.57 | 0.83-2.97 |
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| 60 and upc | - | - | - | - | - | - |
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| Male | 0.50 | 0.27-0.90 | 0.80 | 0.38-1.67 | 0.55 | 0.31-0.99 |
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| Femalec |
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| - | - |
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| Black/African American | 2.55 | 0.70-9.26 | 2.70 | 0.66-11.07 | 2.50 | 0.70-8.92 |
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| Asian/Pacific Islander | 1.19 | 0.46-3.12 | 0.59 | 0.15-2.32 | 1.05 | 0.41-2.72 |
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| Other or not reported | 0.85 | 0.31-2.30 | 0.93 | 0.28-3.14 | 0.84 | 0.32-2.20 |
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| White/Caucasianc | - | - | - | - | - | - |
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| High School degree or less (includes technical school) | 0.88 | 0.42-1.88 | 2.39 | 1.02-5.59 | 1.17 | 0.56-2.45 | |
| At least some collegec | - | - |
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| - | - | |
| Print health literacy scored (CMLT-Reading) | 1.01 | 0.99-1.03 | 0.99 | 0.96-1.01 | 1.00 | 0.98-1.03 | |
| Self-efficacy (PEPPI)d | 1.25 | 1.03-1.53 | 1.35 | 1.04-1.74 | 1.28 | 1.06-1.55 | |
aModel 1–Odds of being an email sender or a postcard sender as compared to being a nonsender.
bModel 2–Odds of being a sender, either email or postcard, as compared to being a nonsender.
creference
dper unit increase in score