Preferences of Underserved Chilean Women on a Mobile Technology Intervention for Cervical Cancer Screening: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: In Chile and Latin America, cervical cancer disproportionately affects women of low socioeconomic status. Mobile technology (mobile health, mHealth) may be able to address this disparity by targeting women in underserved populations. However, there is a lack of information regarding barriers to the implementation of mHealth interventions in underserved populations. OBJECTIVE: The objective of this study was to investigate the use of cell phones and text messaging (short message service, SMS) in Latina women from disadvantaged communities to design an mHealth intervention for improving cervical cancer screening rates. METHODS: We conducted 9 focus groups among women aged 25-64 years to better understand the implementation barriers and perceptions of a text message (SMS)-based intervention designed to improve cervical cancer screening rates. We used the PRECEDE-PROCEED model to categorize identified themes using template analysis. RESULTS: Focus group results indicated that older women use mobile phones to receive calls from family and friends but seldom send text messages. Furthermore, they prefer personal contact with their health care providers regarding Papanicolaou (Pap) testing. Younger women, on the other hand, find text messaging easy to use and frequently send texts to family and friends. Importantly, women of all ages mentioned they would like to receive text messages about Pap tests. Factors that facilitate the uptake of the intervention include ease of access to Pap testing, inclusion of family members, and reminder messaging. Potential barriers include cost and the impersonal nature of messaging. Health team members support an mHealth intervention even though they acknowledge the potential barriers to this strategy. Overall, these results support the implementation of an mHealth intervention to increase cervical cancer screening rates. CONCLUSIONS: This study describes the opinions of women nonadherent to Pap testing on the potential use of mobile technologies for cervical cancer screening. Although the overall acceptance was positive, older women prefer personal contact and phone calls over text messaging. Information surrounding these preferences will aid in the implementation of effective strategies to improve cancer screening in underserved populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".