Improving sexual and reproductive health knowledge and practice in Mozambican families with media campaign and volunteer family health champions
Bibliographic record
Abstract
OBJECTIVE: To increase knowledge, attitudes and practice of sexual and reproductive health and family planning and to reduce maternal and neonatal mortality rates in Mozambique. DESIGN: An implementation research project's intermediate evaluation, applying two cross-sectional surveys. The surveys were planned for 316 subjects before and after interventions. SETTING: Research performed in Natikiri district of Nampula province in northern Mozambique, targeting a suburban and rural populations in their homes. PARTICIPANTS: 452 people were surveyed (91 before, 361 after), all belonging to the Macua ethnic group. INTERVENTIONS: A media campaign (2 weekly radio spots, bimonthly theatre performances) was performed for 8 months (2017 to 2018) and family health champions' teachings (monthly home visits) performed for 3 months, on sexual and reproductive health and family planning. Outcome measures planned and measured were adolescent's and adult's knowledge, attitudes and practice about those. Data were analysed by gender, age group and frequencies, using a CI of 95% (p<0.5 statistically significant). RESULTS: Radio spots, community theatre and volunteer champions increased population's knowledge about sexual and reproductive health and led to a more positive attitude toward family planning. Concerning attitude, results show differences between adults' proportions before and after: (1) did you hear about sexual and reproductive health (p=0.0425); (2) knows project key messages (p<0.001); (3) knows prenatal visits importance (p=0.0301); (4) access to contraceptives was easy (p<0.001). Adolescents showed statistically significant differences before and after: (1) knows project key messages (p<0.001); (2) access to contraceptives was easy (p=0.0361). Family planning practice did not increase in both groups. CONCLUSION: A health education intervention, using a media campaign and local volunteers, is useful to promote mother and child health. There is an unmet need for family planning and the use of modern contraception is below desired practice, needing further research about cultural barriers. Communication for behaviour change activities will pursue and impact will be assessed to document family planning practice improvement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".