Identifying Barriers and Facilitators towards Implementing Guidelines to Reduce Caesarean Section Rates in Quebec/Identification Des Elements Empachant Ou Facilitant la Mise En Oeuvre Des Directives Visant a Reduire Les Taux D'accouchement Par Cesarienne Au Quebec/Identificacion De Los Factores Que Impiden O Favorecen la Aplicacion De Protocolos Orientados a Reducir Las Tasas De Cesarea En Quebec
Bibliographic record
Abstract
Background The World Health Organization recommends that the caesarean section rate should not be higher than 10% to 15%. (1) The caesarean delivery rate in Canada increased steadily from 17.5% of deliveries in 1994-1995 to 23.7% in 2002-2003. (2,3) Moreover, caesarean delivery was associated with high maternal and neonatal complication rates and increased healthcare costs. (4-9) According to the Society of Obstetricians and Gynaecologists of Canada (SOGC), vaginal delivery represents the safest route for the fetus and newborn in the first and subsequent pregnancies. (10) SOGC clinical practices guidelines contribute to the promotion of evidence-based practice and represent an appropriate means for reducing caesarean section rates in Canada. The challenge lies in implementing these guidelines. (11-15) Each clinical environment presents organizational, professional, maternal and cultural particularities. The identification of specific barriers and facilitators represents a new approach for identifying the determinants of guidelines use by health professionals. (7,15-18) This study's premise is that strategies to implement guidelines and reduce caesarean section rates should take into account physicians' perceptions in order to identify different forces and variables influencing their behaviour. Consequently, we carried out an exploratory study to investigate obstetricians' perceptions of SOGC guidelines, and to identify barriers to, facilitators of and obstetricians' solutions for their implementation. Methods We used a qualitative study design to explore and describe obstetricians' perceptions in three Montreal hospitals (one primary-level, one secondary-level and one tertiary-level), (19) with annual deliveries [less than or equal to] 1000, caesarean section rates [greater than or equal to] 20%, and where 75% of obstetricians agreed to participate. Data was obtained from two focus group sessions, with obstetricians from each of the three hospitals, dealing with induction of labour at term and fetal health surveillance in labour guidelines, and operative vaginal birth and vaginal birth after previous caesarean birth guidelines. For secondary-level and tertiary-level hospitals, with more than 10 clinicians, focus groups were divided into two sessions; thus there were four focus groups in each hospital. All obstetricians were approached to participate in the study. Data sources and collection A focus group gathers people from similar backgrounds or experiences to discuss a specific topic of interest. (19) Focus groups conducted at each unit were scheduled at the convenience of participants. Semi-structured interviews were conducted with clinicians who were notable to take part in the focus groups. The focus groups and personal interviews lasted approximately 90 minutes. A moderator, also referred to as an interviewer, conducted each focus group in the presence of an observer, but only the moderator conducted the semi-structured interviews. The moderator was in control of the session and was responsible for the direction taken by the focus group. The main tasks of the observer were to take notes, including non-verbal observations, to record and observe the session. All focus groups and interviews were audio-taped and transcribed verbatim. The interviewer and observer reconstructed detailed notes of each interview immediately after the session. An interview guide was used for all focus groups and interviews (Annex 1, available at http://www.who.int/bulletin/volumes/85/10/06-039289/en/index.html). Focus groups and interviews about SOGC guidelines were structured in the following manner: respondents were asked to describe their perceptions about the adoption of recommendations, barriers and challenges encountered when following the recommendations, and factors and interventions they believed important for facilitating and supporting use of the recommendations. …
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".