| Literature DB >> 26931572 |
Karen Austrian1, Eunice Muthengi2, Joyce Mumah3, Erica Soler-Hampejsek4, Caroline W Kabiru5, Benta Abuya6, John A Maluccio7.
Abstract
BACKGROUND: Many adolescent girls in Kenya and elsewhere face considerable risks and vulnerabilities that affect their well-being and hinder a safe, healthy, and productive transition into early adulthood. Early adolescence provides a critical window of opportunity to intervene at a time when girls are experiencing many challenges, but before those challenges have resulted in deleterious outcomes that may be irreversible. The Adolescent Girls Initiative-Kenya (AGI-K) is built on these insights and designed to address these risks for young adolescent girls. The long-term goal of AGI-K is to delay childbearing for adolescent girls by improving their well-being. INTERVENTION: AGI-K comprises nested combinations of different single-sector interventions (violence prevention, education, health, and wealth creation). It will deliver interventions to over 6000 girls between the ages of 11 and 14 years in two marginalized areas of Kenya: 1) Kibera in Nairobi and 2) Wajir County in Northeastern Kenya. The program will use a combination of girl-, household- and community-level interventions. The violence prevention intervention will use community conversations and planning focused on enhancing the value of girls in the community. The educational intervention includes a cash transfer to the household conditioned on school enrollment and attendance. The health intervention is culturally relevant, age-appropriate sexual and reproductive health education delivered in a group setting once a week over the course of 2 years. Lastly, the wealth creation intervention provides savings and financial education, as well as start-up savings. METHODS/Entities:
Mesh:
Year: 2016 PMID: 26931572 PMCID: PMC4774031 DOI: 10.1186/s12889-016-2888-1
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Fig. 1AGI-K theory of change
Key indicators for primary and secondary outcomes
| Outcome domain | Indicator 1 | Indicator 2 | Indicator 3 |
|---|---|---|---|
| Primary outcome | |||
| Well-being | Age at first birth (+) | Age at first sex (+) | Age at marriage (+) |
| Secondary outcomes | |||
| Violence | Experience of gender-based violence (−) | Positive gender norms related to violence (+) | |
| Education | Mean grade of schooling (+) | Rate of primary school completion (+) | |
| Health | Knowledge on sexual and reproductive health (+) | Decision-making skills (+) | Contraceptive use (+) |
| Wealth | Knowledge on financial education (+) | Saving (+) | Participation in income generating activities (+) |
Fig. 2AGI-K causal mechanisms
Minimum detectable differences for sample estimates
| Site | Sample estimate | Minimum detectable differences |
|---|---|---|
| Kibera | 600 girls per arm at follow-up (2019) | Percent of girls who have given birth: Assuming that 15.4 % of girls in the violence prevention only arm would have given birth by follow-up, can detect a statistically significant difference of 5.4 percentage points between the violence prevention only arm and each of the other three arms |
| Grades of schooling: Assuming a correlation coefficient of 0.33, can detect a statistically significant difference of 0.49 grades of schooling between any two arms | ||
| 480 girls per arm at follow-up (2019) | Assuming that 15.4 % of girls in the violence prevention only arm would have given birth by follow-up, can detect a statistically significant difference of 6.3 percentage points between the violence prevention only arm and each of the other three arms | |
| Assuming a correlation coefficient of 0.33, can detect a statistically significant difference of 0.55 grades of schooling between any two arms | ||
| Wajir | 20 clusters per arm, 32 girls at follow-up (2019) | Assuming that 17.6 % of girls in the violence prevention only arm would have given birth by follow-up, can detect a statistically significant difference of 5.9 percentage points between the violence prevention only arm and each of the other three arms |
| Assuming a correlation coefficient of 0.26, can detect a statistically significant difference of 0.48 grades of schooling between any two arms | ||
| 20 clusters per arm, 22 girls at follow-up (2019) | Assuming that 17.6 % of girls in the violence prevention only arm would have given birth by follow-up, can detect a statistically significant difference of 6.9 percentage points between the violence prevention only arm and each of the other three arms | |
| Assuming a correlation coefficient of 0.26, can detect a statistically significant difference of 0.49 grades of schooling between any two arms |
Respondents interviewed
| Site | Initial sample from household listing | Eligible | Interviewed (% of eligible) |
|---|---|---|---|
| Kibera | 3296 | 2606 (79 %) | 2402 (92 %) |
| Huruma/Mathare | 895 | 730 (82 %) | 666 (91 %) |
| Wajir | 2923 | 2297 (79 %) | 2150 (93 %) |