Reported evidence on the effectiveness of mass media interventions in increasing knowledge and use of family planning in low and middle-income countries: a systematic mixed methods review
Bibliographic record
Abstract
BACKGROUND: An estimated 200 million women and girls in low and middle-income countries (LMICs) wish to delay, space or avoid becoming pregnant, yet are not using contraceptives. This study seeks to investigate the effectiveness of mass media interventions for increasing knowledge and use of contraceptives, and to identify barriers to program implementation. METHODS: Using a mixed-methods systematic approach, we searched five electronic databases using pre-determined search strategies and hand-searching of articles of any study design published from 1994 to 2017 of mass media interventions for family planning education. Two reviewers independently applied clearly defined eligibility criteria to the search results, quality appraisal, data extraction from published reports, and data analysis (using meta-analysis and thematic analysis) following PRISMA guidelines. RESULTS: We identified 59 eligible studies. Although the majority of studies suggest a positive association between media interventions and family planning outcomes, the pooled results are still consistent with possibly null intervention effects. The reported prevalence ratios (PR) for media interventions association with increased contraceptive knowledge range from 0.97 to 1.41, while the PRs for contraceptive use range from 0.54 to 3.23. The qualitative analysis indicates that there are barriers to contraceptive uptake at the level of individual knowledge (including demographic factors and preconceived notions), access (including issues relating to mobility and financing), and programming (including lack of participatory approaches). CONCLUSIONS: There is a need for rigorous impact evaluation, including randomised controlled trials, of mass media interventions on knowledge and uptake of family planning in LMIC settings. Interventions should be better tailored to cultural and socio-demographic characteristics of the target populations, while access to resources should continue to remain a priority and be improved, where possible.
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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 | 0.060 | 0.199 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".