Adult Willingness to Use Email and Social Media for Peer-to-Peer Cancer Screening Communication: Quantitative Interview Study
Bibliographic record
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. OBJECTIVE: The objective of our study was to assess current practices and attitudes toward use of email and other e-communication for peer-to-peer dialogues on cancer screening. METHODS: We conducted in-person interviews with 438 insured adults ages 42-73 in Georgia, Hawaii, and Massachusetts. Participants reported on use of email and other e-communication including social media to discuss with peers routine health topics including breast and colorectal cancer (CRC). We ascertained willingness to share personal CRC screening experiences via conversation, postcard, email, or other e-communication. Health literacy scores were measured. RESULTS: Email had been used by one-third (33.8%, 148/438) to discuss routine health topics, by 14.6% (64/438) to discuss breast cancer screening, and by 12.6% (55/438) to discuss CRC screening. Other e-communication was used to discuss routine health topics (11.6%, 51/438), screening for breast cancer (3.9%, 17/438), and CRC (2.3%, 10/438). In the preceding week, 84.5% (370/438) of participants had used email, 55.9% (245/438) had used e-communication of some type; 44.3% (194/438) text, 32.9% (144/438) Facebook, 12.3% (54/438) instant message, 7.1% (31/438) video chat, and 4.8% (21/438) Twitter. Many participants were willing to share their CRC screening experiences via email (32.4%, 142/438 might be willing; 36.3%, 159/438 very willing) and via other e-communication (15.8%, 69/438 might be willing; 14.4%, 63/438 very willing). Individuals willing to send CRC screening emails scored significantly higher on tests of health literacy compared to those willing to send only postcards (P<.001). CONCLUSIONS: Many adults are willing to use email and e-communication to promote cancer screening to peers. Optimal approaches for encouraging peer-to-peer transmission of accurate and appropriate cancer screening messages must be studied.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".