Qualitative Evidence Synthesis on Self-Collection for Human Papillomavirus–Based Cervical Screening: Protocol for Systematic Review
Bibliographic record
Abstract
BACKGROUND: Cervical cancer is the fourth most common cancer affecting women worldwide. In the 1980s, it was found that the sexually transmitted disease human papillomavirus causes over 90% of all cervical cancer cases. Since that discovery, diagnostic technologies have been developed for the detection of human papillomavirus DNA in cervical samples. However, significant sociocultural and structural barriers remain. Considerable strides have taken place in recent years to address these barriers, such as the self-collection for human papillomavirus-based cervical screening method. OBJECTIVE: The purpose of this review is to synthesize qualitative evidence around the self-collection method and identify strategies to increase acceptability and feasibility in different settings. This qualitative synthesis will be used to better understand how to conceptualize and implement more effective, accessible, and socially and culturally acceptable cervical screening programs and policies globally. METHODS: A systematic search will be conducted in Global Health, Cochrane, CINAHL (Cumulative Index to Nursing and Allied Health Literature), ProQuest, ScienceDirect, EMBASE, EMCARE, Medline (OVID), Scopus, and Web of Science. Published and peer-reviewed articles will be included. Two reviewers will independently screen and assess the studies. The data will be coded and analyzed using a thematic synthesis process. The socioecological model will be used to organize emergent themes at the micro and macro levels. The results will be presented in narrative and tabular form. RESULTS: The article search and data extraction were completed in May 2020. The data were analyzed in June 2020. The review will be submitted for publication in Fall 2020. CONCLUSIONS: This review will present the global evidence of the perspectives and experiences of various key stakeholders and how these perspectives and experiences impact their decision-making process to perform or accept self-collection for human papillomavirus-based cervical screening. The review will provide guidance to implementation researchers as well as implications for future research. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42019109073; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=109073. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21093.
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 | 0.127 | 0.156 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.067 | 0.008 |
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".