Male involvement on women and children healthcare
Bibliographic record
Abstract
Title: Male involvement on women and children healthcare Authors: Idrissa Beogo*, Jean Ramdé*, Jean Pierre Ndiamy Aim: the aims of this study are: 1. to identify the barriers to men’s involvement in women and children’s healthcare and to learn how to facilitate these concerns moving forward. 2. To highlight the best practices of men’s involvement in women and children’s healthcare. In accordance with this objective, we target the other side to describe how men carry out their strategies and finally show how these strategies impact women and children’s healthcare. Background: Maternal and children’s healthcare is among the most important public health issue of a country. It helps with avoiding high rates of death among pregnant women and their children, which can negatively impact the development of a country. Being among affected countries in West Africa with 134,6 per 100 000 of maternal deaths, Burkina Faso has implemented some strategies to cope with this serious situation. Today the scoping studies are considered more often among the approaches primarily used to review health research matters. Therefore, using this approach to see male involvement on women and children’s healthcare, knowing otherwise that male engagement can help reduce maternal and infantile mortality, enables us to deal with a grave question and may help us highlight parts of the problem which would probably be deeply useful for Burkina Faso in terms of reducing the rate of death in mothers and children death throughout the country. Inclusion criteria Inclusion and exclusion criteria will be based on the Population, Interventions, Comparators and designs, Outcomes (PICO) Population (P): This scoping review will consider studies on male engaging in maternal and children healthcare. So being considered as one the key factors of research, population will be of a great importance in the inquiry. It will furthermore contribute to the establishment of a suitable search strategy. Intervention (I) As there is no exhaustive list of male involvement, every kind being useful for women and children’s healthcare for instance: - Involvement in antenatal care - Involvement in prescription purchasing - Participation in birth preparedness - Attendance at deliveries - Communication and decision sharing Outcomes (O): This scoping review will target the following outcomes. The outcomes targeted in this review will be: Primary outcomes - children and mother’s healthcare outcomes -Services uptake (e.g., number of assisted deliveries, number of post-natal, prenatal) Funding: Social Sciences and Humanities Research Council of Canada (890-2020-0106)
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.002 |
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".