Acceptability of Delivering and Accessing Health Information Through Text Messaging Among Community Health Advisors
Bibliographic record
Abstract
BACKGROUND: Communication technologies can play a significant role in decreasing communication inequalities and cancer disparities by promoting cancer control and enhancing population and individual health. Studies have shown that technology, such as the mobile phone short message service (SMS) or text messaging, can be an effective health communication strategy that influences individuals' health-related decisions, behaviors, and outcomes. OBJECTIVE: The purpose of this study was to explore usage of communication technologies, assess the acceptability of mobile technology for delivery and access of health information, and identify cancer and health information needs among Deep South Network for Cancer Control trained Community Health Advisors as Research Partners (CHARPs). METHODS: A mixed-method design was used, and a triangulation protocol was followed to combine quantitative and qualitative data. Focus groups (4 focus groups; n=37) and self-administered surveys (n=77) were conducted to determine CHARPs mobile phone and text message usage. The objective was to include identification of barriers and facilitators to a mobile phone intervention. RESULTS: All participants were African American (37/37, 100%), 11/37 (89%) were women, and the mean age was 53.4 (SD 13.9; focus groups) and 59.9 (SD 8.7; survey). Nearly all (33/37, 89%) of focus group participants reported owning a mobile phone. Of those, 8/33 (24%) owned a smartphone, 22/33 (67%) had a text messaging plan, and 18/33 (55%) and 11/33 (33%) received and sent text messages several times a week or day, respectively. Similar responses were seen among the survey participants, with 75/77 (97%) reporting owning a mobile phone, and of those, 22/75 (30%) owned a smartphone, 39/75 (53%) had a text messaging plan, and 37/75 (50%) received and 27/75 (37%) sent text messages several times a week or day. The benefits of a text messaging system mentioned by focus group participants included alternative form of communication, quick method for disseminating information, and privacy of communication. The main barriers reported by both groups to using mobile technology to receive health information were cost and not knowing how to text message. Ways to overcome barriers were explored with focus group participants, and education was the most proposed solution. Majority of CHARPs were in favor of receiving a weekly text message that would provide cancer/health information. CONCLUSIONS: The findings from this study indicate that CHARPs are receptive to receiving text messages focusing on cancer/health information and would be likely to engage in mobile health research. These findings represent the first step in the development of an interactive mobile health program designed to provide cancer/health information and a support network for the Deep South Network Community Health Advisors as Research Partners (DSN CHARPs).
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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 | 0.011 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".