International challenges in patient-centred care in fertility clinics offering assisted reproductive technology: providers' gaps and attitudes towards addressing the patients' psychological needs
Bibliographic record
Abstract
Introduction. Psychosocial care provided to patients undergoing fertility treatment has focused on a small proportion of patients with major psychosocial problems, leaving the remaining patients impacted by psychosocial stressors without follow-up. Factors that could influence the ability or willingness of physicians treating infertility to assess and address patients’ psychosocial needs have not been investigated. This study aimed to identify the practice gaps and educational needs of physicians treating and managing patients with infertility, with the aim of informing future educational interventions. Methods. A cross-sectional, exploratory, mixed-methods study incorporating semi-structured qualitative telephone interviews and a quantitative online survey was designed and deployed to actively practising physicians treating infertile couples from 15 countries across the Americas, Europe, Asia, and the Middle East Region. Triangulation of qualitative and quantitative data was used to increase trustworthiness of findings. Results. Forty-five participants completed a qualitative interview and 271 participants completed the quantitative online survey (response rates were 4 and 9%, respectively). A majority (74%) of respondents reported needing improvement in their psychological assessment skill, which was considered essential to the provision of optimal care by less than half (41%) of respondents. A need for improvement in their skill to assess patients’ parenting skills was reported in 72% of respondents, and this skill was considered as essential by 32% of participants. Similarly, 72% reported needing improvement in their ability to identify the needs of patients for psychological and emotional support, and this ability was considered essential by 45%. Statistical differences were observed between countries (p<0.05). Conclusion. Addressing the gaps highlighted in this study, through educational or performance improvement activities, could optimise the clinical performance of physicians treating infertility and, thus, increase patient satisfaction and outcomes.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".