A Counseling Mobile App to Reduce the Psychosocial Impact of Human Papillomavirus Testing: Formative Research Using a User-Centered Design Approach in a Low-Middle-Income Setting in Argentina
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV) testing detects sexually transmitted infections with oncogenic types of HPV. For many HPV-positive women, this result has negative connotations. It produces anxiety, fear of cancer or death, and disease denial. Face-to-face counseling could present many difficulties in its implementation, but a counseling mobile app could be practical and may help HPV-positive women reduce the psychosocial impact of the result, improve their knowledge of HPV and cervical cancer, and increase adherence to follow-up. OBJECTIVE: This study aims to understand HPV-tested women's perceptions about an app as a tool to receive information and support to reduce the emotional impact of HPV-positive results. We investigated their preferences regarding app design, content, and framing. METHODS: We conducted formative research based on a user-centered design approach. We carried out 29 individual online interviews with HPV-positive women aged 30 years and over and 4 focus groups (FGs) with women through a virtual platform (n=19). We shared a draft of the app's potential screens with a provisional label of the possible content, options menus, draft illustrations, and wording. This allowed us to give women understandable triggers to debate the concepts involved on each screen. The draft content and labels were developed drawing from the health belief model (HBM) and integrative behavioral model (IBM) variables and findings of mobile health literature. We used an FG guide to generate data for the information architecture (ie, how to organize contents into features). We carried out thematic analysis using constructs from the HBM and IBM to identify content preferences and turn them into app features. We used the RQDA package of R software for data processing. RESULTS: We found that participants required more information regarding the procedures they had received, what HPV-positive means, what the causes of HPV are, and its consequences on their sexuality. The women mentioned fear of the disease and stated they had concerns and misconceptions, such as believing that an HPV-positive result is a synonym for cancer. They accepted the app as a tool to obtain information and to reduce fears related to HPV-positive results. They would use a mobile app under doctor or health authority recommendation. The women did not agree with the draft organization of screens and contents. They believed the app should first offer information about HPV and then provide customized content according to the users' needs. The app should provide information via videos with experts and testimonies of other HPV-positive women, and they suggested a medical appointment reminder feature. The app should also offer information through illustrations, or infographics, but not pictures or solely text. CONCLUSIONS: Providing information that meets women's needs and counseling could be a method to reduce fears. A mobile app seems to be an acceptable and suitable tool to help HPV-positive women.
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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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".