A review of factors affecting patient fertility preservation discussions & decision-making from the perspectives of patients and providers
Bibliographic record
Abstract
Women undergoing cancer treatments and their healthcare providers encounter challenges in fertility preservation (FP) discussions and decision-making. A systematic review of qualitative research was conducted to gain in-depth understanding of factors influencing FP discussions and decision-making. Major bibliographic databases and grey literature in English from 1994 to 2016 were searched for qualitative research exploring patient/provider perspectives on barriers and facilitators to FP decision-making. Two researchers screened article titles, abstracts and full-texts. Verbatim data on research questions, study methodology, participants, findings and discussions of findings were extracted. Quality assessment and thematic analysis were conducted. The search yielded 74 studies dating from 2007 onwards; 29 met the inclusion criteria. Analysis revealed three types of barriers: (a) FP knowledge, skills and information deficits contributed to discomfort for providers and discontent for patients; (b) psychosocial factors and clinical issues influenced providers' practices around FP discussions and patients' decision-making; and (c) material, social and structural factors (e.g., lack of resources and accessibility) posed challenges to FP discussions. Potential facilitators to FP discussions and decision-making were also identified. A discussion of ways to improve physician's knowledge and facilitate women's decision-making and access to FP is presented, along with areas for policy development and further research.
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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".