Investigating the healthcare-seeking behaviors of mobile phone users in rural Uganda
Bibliographic record
Abstract
ABSTRACT Cervical cancer is the leading cause of cancer in low- and middle-income countries, despite being a preventable disease. Uganda, which lacks an effective screening program, has one of the highest cervical cancer incidence rates in the world. Mobile health (mHealth) technology has the potential to improve healthcare-seeking behaviors and access to cervical cancer screening. This study aims to describe the connection between mobile phone access and healthcare-seeking behaviors in rural Uganda. This cross-sectional study recruited participants from January 23 to August 24, 2023. Women were eligible if they had no prior screening or treatment for cervical cancer in the past 5 years, were aged 30 to 49 years old, and were residents of the South Busoga Forest reserve. Each participant completed a 43-item survey which included questions on demographics, previous health service usage, and opinions on cervical cancer prevention. All data was analyzed using descriptive statistics and chi-square tests. Of the 1434 participants included in the analysis, 91.4% reported having access to a mobile phone. Most respondents were aged 30-40 years, were married or in a relationship, had ≤ primary education, and were farmers. Participants with access to a mobile phone were significantly more likely to report attending a healthcare outreach visit (access = 87.3%, no access = 72.6%, p<0.001) or visiting a health centre (access = 96.9%, no access = 93.5%, p<0.001). Participants in both groups had largely positive attitudes around and good knowledge of cervical cancer screening. While attendance to healthcare outreach visits or health centres was high amongst participants, those with mobile phone access were more likely to seek healthcare services. Further inquiry into this association between mobile phone access and healthcare-seeking behaviour is needed to optimize the improvements to cervical cancer screening when implementing interventions such as mHealth technology. AUTHOR SUMMARY Cervical cancer is the leading cause of cancer in low- and middle-income countries, despite being a preventable disease. This can be partially attributed to the lack of widespread screening programs. In Uganda, the development of a comprehensive screening program has been slow despite having one of the highest rates of cervical cancer. However, mobile health might have the capacity to help improve cervical cancer screening rates in resource-limited settings such as Uganda. Our study explored the existing relationships between access to a mobile phone and healthcare-seeking behaviour in rural Uganda. We found that access to a mobile phone was associated with higher use of healthcare services and a more positive attitude towards and knowledge of cervical cancer prevention. It is important to study these existing relationships to find the best use of mobile health and to allow for the assessment of a digital health intervention once implemented. Future studies can build on our findings by investigating the impact of digital health interventions on the use of cervical cancer screening services in rural settings, which will contribute to the elimination of this devastating disease in Uganda, and in other resource-limited settings.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".