Towards a global framework for assessing male involvement in maternal health: results of an international Delphi study
Bibliographic record
Abstract
PURPOSE: Currently, no standard instrument exists for assessing the concept of male involvement in maternal health, hampering comparison of results and interpretation of the literature. The aim of this study was to construct the key elements of a global multidimensional male involvement framework, based on the latest evidence and input of experts in the field. METHODS: For this purpose, a Delphi study, including an international panel of 26 experts, was carried out. The study consisted of three rounds, with 92% of respondents completing all three surveys. Experts were asked to rate indicators within six categories in terms of validity, feasibility, sensitivity, specificity and context robustness. Furthermore, they were encouraged to clarify their rating with open text responses. Indicators were excluded or adapted according to experts' feedback before inclusion. A 85% agreement was used as threshold for consensus. RESULTS: A general consensus was reached for a global framework for assessing male involvement in maternal health, consisting of five categories: involvement in communication, involvement in decision-making, practical involvement, physical involvement and emotional involvement. CONCLUSIONS: Using the male involvement framework as a tool to assess the concept of male involvement in maternal health at local, national, and international levels could allow improved assessment and comparison of study findings. Further research is needed for refining the indicators according to context and exploring how shared decision-making, gender equality and women's empowerment can be assessed and facilitated within male involvement programmes.
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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 | 0.180 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| 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".