Antenatal counselling for congenital anomaly tests: An exploratory video-observational study about client–midwife communication
Bibliographic record
Abstract
OBJECTIVE: antenatal counselling for congenital anomaly tests is conceptualised as having both Health Education (HE) and Decision-Making Support (DMS) functions. Building and maintaining a client-midwife relation (CMR) is seen as a necessary condition for enabling these two counselling functions. However, little is known about how these functions are fulfilled in daily practice. This study aims to describe the relative expression of the antenatal counselling functions; to describe the ratio of client versus midwife conversational contribution and to get insight into clients' characteristics, which are associated with midwives' expressions of the functions of antenatal counselling. DESIGN: exploratory video-observational study. PARTICIPANTS AND SETTING: 269 videotaped antenatal counselling sessions for congenital anomaly tests provided by 20 midwives within six Dutch practices. MEASUREMENTS: we used an adapted version of the Roter Interaction Analysis System to code the client-midwife communication. Multilevel linear regression analyses were used to analyse associations between clients' characteristics and midwives' expressions of antenatal counselling in practice. FINDINGS: most utterances made during counselling were coded as HE (41%); a quarter as DMS (23%) and 36% as CMR. Midwives contributed the most to the HE compared to clients or their partners (91% versus 9%) and less to the DMS function of counselling (61% versus 39%). Multilevel analyses showed an independent association between parity and shorter duration of antenatal counselling; (β=-3.01; p<0.001). The amount of utterances concerning HE and DMS during counselling of multipara was less compared to nulliparous. KEY CONCLUSIONS: antenatal counselling for congenital anomaly tests by midwives is focused on giving HE compared to DMS. The relatively low contribution of clients during DMS might indicate poor DMS given by midwives. Counselling of multipara was significantly shorter than counselling of nulliparous; multiparae received less HE as well as DMS compared to nulliparous women. IMPLICATIONS FOR PRACTICE: our findings should encourage midwives to reflect on the process of antenatal counselling they offer with regards to the way they address the three antenatal counselling functions during counselling of nulliparous women compared to multiparae.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".