Mobile Web App Intervention to Promote Breast Cancer Screening Among American Indian Women in the Northern Plains: Feasibility and Efficacy Study
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the most common cancer in the United States and the second leading cause of death for American Indian women. American Indian women have lower rates of breast cancer screening than other racial groups, and disparities in breast cancer mortality and survival rates persist among them. To address this critical need, a culturally appropriate, accessible, and personalized intervention is necessary to promote breast cancer screening among American Indian women. This study used mobile health principles to develop a mobile web app-based mammogram intervention (wMammogram) for American Indian women in a remote, rural community in the Northern Plains. OBJECTIVE: This study aimed to assess the feasibility and efficacy of the wMammogram intervention, which was designed to motivate American Indian women to undergo breast cancer screening, as compared with the control group, who received an educational brochure. METHODS: Using community-based participatory research (CBPR) principles and a multipronged recruitment strategy in a randomized controlled trial design, we developed the wMammogram intervention. This study involved 122 American Indian women aged between 40 and 70 years, who were randomly assigned to either the intervention group (n=62) or the control group (n=60). Those in the intervention group received personalized and culturally appropriate messages through a mobile web app, while those in the control group received an educational brochure. We measured outcomes such as mammogram receipt, intention to receive breast cancer screening after the intervention, and participants' satisfaction with and acceptance of the intervention. RESULTS: =-3.61; P<.001). Moreover, compared with the brochure group, the intervention group expressed greater intention to receive a mammogram in the future when it is due (62/62, 100% vs 51/60, 85%) and were more willing to recommend the intervention they received to their friends (61/62, 98.4% vs 54/60, 90%) with statistically significant differences. CONCLUSIONS: This study shows the feasibility and efficacy of the wMammogram intervention to promote breast cancer screening for American Indian women in a remote, rural community-based setting. Findings suggest that, with advancements in technology and the ubiquity of mobile devices, mobile web apps could serve as a valuable health intervention tool that builds upon low-cost technology and enhances accessibility and sustainability of preventive care to help reduce breast health disparities experienced in hard-to-reach American Indian populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT05530603; https://clinicaltrials.gov/ct2/show/NCT05530603.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".