Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2019 Aug 6.
Published in final edited form as: Asia Pac J Soc Work Dev. 2019 Feb 27;29(1):59–69. doi: 10.1080/02185385.2019.1575271

Assessing the impact of an asset-based intervention on educational outcomes of orphaned children and adolescents: findings from a randomised experiment in Uganda

Nabunya Proscovia a,b, Namatovu Phionah b, Damulira Christopher b, Kivumbi Apollo b, William Byansi a,b, Mukasa Miriam b, Nattabi Jennifer b, Ssewamala M Fred a,b
PMCID: PMC6684351  NIHMSID: NIHMS1015386  PMID: 31388222

Abstract

This paper examines the effect of an asset-based intervention on academic performance and school transition among orphaned and vulnerable children in Uganda. Participants were randomly assigned to either the control arm or two treatment arms receiving an asset-based intervention. Participants in the treatment arms scored better grades; and had higher odds of transitioning to post-primary education relative to the control arm. Programmes which target financial insecurity may have a positive impact on the educational achievement and progression of orphaned children. There is a need to consider incorporating asset-based interventions within the development of educational policy, especially in low-income countries.

Keywords: Academic performance, school transition, Bridges to the future, orphaned children

Introduction

Approximately 50 million children in sub-Saharan Africa (SSA) are orphans, i.e. have lost one or both biological parents; more than 15 million of these have lost their parent(s) to HIV/AIDS (UNICEF, 2016). In Uganda, one of the SSA countries hardest hit by the epidemic, more than 1.2 million children are orphaned as a direct result of the disease (UNICEF, 2016). Children orphaned as a result of HIV/AIDS are at a greater risk of poor schooling and educational outcomes compared to non-orphans and children orphaned due to other causes (Bicego, Rutstein, & Johnson, 2003; Case, Paxton, & Ableidinger, 2004). They are more likely to have poor educational outcomes, including lower school enrolment and attendance rates, less likely to be at a proper education level and are more likely to drop out of school completely (Case et al., 2004; Evan & Miguel, 2004; Kasirye & Hisali, 2010; Monasch & Boerma, 2004).

Given the aforementioned risks, educational opportunities are a key component of the current safety net programmes for orphaned and vulnerable children (OVCs) in communities heavily affected by HIV/AIDS (Hunter & Williamson, 2000). Indeed, OVCs are widely considered a subset of the population targeted by Education for All – a Dakar Framework for Action global commitment that obligates countries to ensure that all children (especially girls, children in difficult circumstances and ethnic minorities) have access to and complete, free and compulsory primary education of good quality (UNESCO, 2000).

Uganda is one of the countries that embraced the Education for All movement. In 1997, Universal Primary Education (UPE), was instituted as one of the United Nations Millennium Development Goals, wherein each child of school-going age is allowed to attend primary school without paying tuition. The abolition of school fees improved entry into primary schooling, incentivised school enrolment and reduced dropout, particularly for girls and for children in rural areas (Deininger, 2003; Grogan, 2009). Between 2000 and 2015, access to primary school increased by 27.7%, and net enrollment at primary school level increased from 83% to 96% (MoES, 2015). However, the completion rates (i.e. the percentage of students of official graduation age who complete primary school) remains lower than the 100% target (Uganda Ministry of Education and Sports [MoES], 2015). The 2016/2017 statistics from MoES indicate that the survival rate to primary seven (i.e. the percentage of a cohort of students enrolled in a given year who reach primary seven) was only 32%, and out of these only 62% were able to complete primary education (i.e. sit for their Primary Leaving Examinations [PLE]) (MoES, 2017).

Despite progress in school access and enrolment, Uganda still faces challenges in ensuring that OVCs participate in and complete primary schooling. The challenges include lack of infrastructure (e.g. classrooms and sanitation facilities given high enrolment rates), high dropout rates (especially among girls), teacher absenteeism and high attrition rates, and the HIV/AIDS epidemic that affect both the supply of qualified teachers and school participation of OVCs (MoES, 2015). These challenges, combined with poor schooling and educational outcomes associated with HIV orphanhood (Bicego, et al., 2003; Case et al., 2004), further limit the opportunities of OVCs from benefiting from the education policy of education for all.

Improving household economic security and providing psychosocial support to affected children and their caregivers is one strategy to address the needs of OVCs. There has been a growing interest in asset-building interventions to enable individuals with limited financial and economic resources or opportunities to acquire and accumulate long-term productive assets (Ssewamala, 2015). Asset-based interventions are modelled on asset theory (Sherraden, 1990, 1991), which posits that assets (e.g. savings, educational opportunities, economic opportunities, including microenterprise activities) have important social, economic and psychological benefits for individuals and families. In addition, Sherraden theorises that holding even minor financial or material assets affects individuals’ behaviours, attitudes and hopes for the future. The acquisition of assets creates a sense of financial security, which in turn improves self-confidence, responsibility and hope for the future. This is what Schreiner and Sherraden (2007) refer to as asset effects.

Several studies both in the developed and developing world have demonstrated positive outcomes, ranging from improved health and psychosocial outcomes, financial outcomes and social outcomes, including educational outcomes (Adato & Bassett, 2009; Cheatham & Elliott, 2013; Curley, Ssewamala, & Han, 2010; Elliott, 2009; Han, Ssewamala, & Wang, 2013; Kim & Sherraden, 2011; Ssewamala, Han, Neilands, Ismayilova, & Sperber, 2010; Ssewamala & Ismayilova, 2009; Ssewamala, Neilands, Waldfogel, & Ismayilova, 2012). For example, previous studies among OVCs in Uganda found that participating in asset-based interventions, specifically those that use matched savings accounts, was associated with positive changes in adolescents’ future educational planning, higher levels of confidence in the future, better school grades and school attendance (Curley et al., 2010; Ssewamala & Ismayilova, 2009). Therefore, asset-based interventions have the potential to increase household economic resources and reduce economic stressors associated with paying non-tuition requirements, thereby reducing student’s absenteeism and improving their performance in school.

Although the aforementioned studies documented positive school outcomes and educational planning among OVCs in Uganda, they have all been tested using relatively small samples, with relatively short intervention and follow-up periods. In addition, none examined participants’ transition rates and progression from primary school to post-primary education. Yet, post-primary education is equally important in defining children’s career paths and preparing them for futures that contribute to a country’s economic, political and social development. This paper, therefore, examines the impact of an asset-based intervention on academic performance and school transition among a relatively large sample of OVCs, using longitudinal data collected over 5 years, and comparing three study groups. In implementing UPE, this specific focus is important to researchers developing strategies to address the challenges associated with educational outcomes of OVCs in SSA countries heavily affected by HIV/AIDS.

Methods

Study sample and design

This paper uses data from the Bridges to the Future study (hereafter Bridges study), a 5-year (2011–2016) randomised controlled trial funded by the National Institute of Child Health and Human Development (NICHD Grant #1R01 HD070727–01, PI: Fred Ssewamala, PhD).

The Bridges study evaluated the impact of a family asset-based intervention that use Child Development Accounts (CDAs) on the developmental outcomes of OVCs in Southern Uganda. Forty-eight primary schools were randomly assigned to either the control arm (n = 16 schools, 496 participants) or one of the two treatment arms: Bridges arm (n = 16 schools, 402 participants) or Bridges Plus arm (n = 16 schools, 512 participants). Eligible participants had lost one or both biological parents to HIV/AIDS, lived within a family and not an institution, and were in grades 5 or 6 of a public primary school. Participants in the control condition received ‘usual care’ services offered to OVCs in the region, including food aid and scholastic materials. Participants in the two treatment arms (Bridges and Bridges Plus) received usual care services plus the following intervention components: A matched savings account in a form of a CDA with a matching rate of 1:1 for the Bridges arm or a 2:1 match ratio for the Bridges Plus arm; microenterprise workshops for participants and their caregivers; and a one-hour monthly mentorship programme for participants. Additional information on the Suubi and Bridges mentorship programme has been published elsewhere (Nabunya, Ssewamala, Mukasa, Byansi, & Nattabi, 2015; Ssewamala, Nabunya, Mukasa, Ilic, & Nattabi, 2014).

Measures

Data for the Bridges study were collected at baseline, 12, 24, 36, and 48 months post baseline. Each study participant responded to a 90-min survey administered by trained Ugandan interviewers. The primary outcomes for this analysis were OVCs’ academic performance and school transition, collected between 24- and 48-months follow-ups.

Academic performance was measured using official scores from PLE, a national standardised examination administered by the MoES to all students completing primary school in Uganda. All students intending to enroll in post-primary education including vocational institutions must complete and pass the PLE. Participants in the Bridges study were recruited within their last 3 years of primary schooling; therefore, their PLE scores were collected between 24 and 48 months follow-ups. PLE scores are measured in aggregates, ranging from 4 (best) to 36 (worst). To illustrate, a total aggregate of 4 means that a child received Distinction 1 (also presented at D1, the best grade one could get in any given subject) for each of the four subjects on which each student is tested (i.e. English Mathematics, Social Studies, Science). Likewise, if a child gets a total aggregate of 36, it means that he/ she got Failure 9 (also presented as F9, the worst grade one could get) for each of the four subjects outlined above.

School transition was measured by participants’ enrollment into post-primary education, (i.e. secondary/high school or vocational institutions). This data was collected between 24- and 48-months follow-up. Responses were coded as ‘1’ for those who had transitioned to post-primary education and ‘0’ for those who had not transitioned.

The independent variable was participation in the Bridges intervention. Participants’ demographic and household characteristics included as control variables were age, gender, orphanhood status (single or double orphan), the child’s primary caregiver, household size, family cohesion, availability of personal savings and household assets. A household asset index was created, measuring the amount of assets (ranging from 0 to 20 items) reported by participants in the form of home ownership, land or rental property, means of transportation, gardens and livestock, and any ownership of a family microenterprise business.

Data analysis

Baseline sample characteristics were analysed and compared between the three study arms (i.e. the control arm, Bridges arm, Bridges Plus arm). Specifically, chi-square tests of independence and analysis of variance (ANOVA) were conducted. A descriptive analysis of school outcomes (i.e. PLE performance and school transition to post-primary education) was conducted. In addition, ordinary least squares regression analysis was conducted to examine the effect of the intervention on academic performance (PLE scores). Binary logistic regression analysis was conducted to examine the effect of the intervention on school transition. In both regression models, we controlled for participants’ demographics and household characteristics.

Results

Characteristics of the study sample

Baseline sample characteristics are summarised in Table 1. The average age of participants was 12.7 years. The majority of participants were female (56%). Across all three study arms, participants reported statistically different distribution on orphanhood status, with a higher likelihood of being paternal orphans (i.e. had lost a biological father) (χ2 = 10.27, p ≤ .05). Participants lived in households with an average of six members, with three children under the age of 18 years. About 39% of participants reported a surviving biological parent as their primary caregiver and 37% reported their grandparents. The average score of family cohesion was 23.5 (SD = 5.13), indicating a moderate level of family closeness. In terms of household assets, the average asset ownership reported was 9.73 items out of the possible 20, indicating moderate levels of household asset ownership. The majority of participants (69%) reported no personal savings.

Table 1.

Baseline sample characteristics: n (%).

Variable Total sample
(N = 1410)		 Bridges Plus arm
(n = 512)		 Bridges arm
(n = 402)		 Control arm
(n = 496)		 F-value
or χ2
Participants’ characteristics
Age (mean, SD) 12.70 (1.26) 12.71 (1.24) 12.56 (1.31) 12.75 (1.23) 2.74
Gender 0.28
 Female 789 (55.96) 288 (56.25) 228 (56.72) 273 (55.04)
 Male 621 (44.04) 224 (43.75) 174 (43.28) 223 (44.96)
Orphan-hood status 10.57*
 Double orphan 297 (21.06) 104 (20.31) 70 (17.41) 123 (24.80)
 Maternal orphan 302 (21.42) 113 (22.07) 79 (19.65) 110 (22.18)
 Paternal orphan 811 (57.52) 295 (57.62) 253 (62.94) 263 (53.02)
Household characteristics
Number of people in the household (mean, SD) 6.35 (2.79) 6.32 (2.73) 6.26 (2.62) 6.47 (2.97) 0.67
Number of children in the household (mean, SD) 3.18 (2.20) 3.22 (2.17) 3.11 (2.09) 3.20 (2.32) 0.34
Family assets (mean, SD) 9.73 (3.22) 9.79 (3.29) 9.52 (3.26) 9.83 (3.12) 1.16
Family cohesion (mean, SD) 23.50 (5.13) 23.39 (5.06) 23.27 (5.02) 23.80 (5.27) 1.40
Availability of personal savings 3.35
 Yes 433 (30.71) 172 (33.59) 120 (29.85) 141 (28.43)
 No 977 (69.26) 340 (66.41) 282 (70.15) 355 (71.57)
Caregiver type 6.59
 Biological parent 552 (39.15) 216 (42.19) 160 (39.80) 176 (35.48)
 Grandparent(s) 516 (36.60) 182 (35.55) 137 (34.08) 197 (39.72)
 Other relatives (i.e. aunt, uncle, siblings, in-laws) 342 (24.26) 114 (22.27) 105 (26.12) 123 (24.80)
Open in a new tab

PLE performance and school transition

Descriptive analysis results of school outcomes are provided in Table 2. Of the total sample, about 61% completed their PLE, meaning that they completed their primary education. Participants in both treatment arms completed PLE at similar rates, higher than those in the control arm. The average PLE aggregate score was 24.57, with participants in the Bridges arm (mean score = 22.6) performing better compared to their counterparts in the Bridges Plus arm (mean score = 24.33) and the control arm (mean score = 26.74). In terms of school transition, about 46% of the total sample (representing about 67% of those who completed PLE) transitioned to post-primary school. About half of participants in both Bridges and Bridges Plus arms transitioned to post-primary education, compared to only 36% of participants in the control arm. Overall, participants who completed PLE had a high likelihood of transitioning to post-primary education.

Table 2.

Descriptive analysis of PLE performance and school transition: n (%).

Variables Total
(N = 1410)		 Bridges Plus arm
(n = 512)		 Bridges arm
(n = 402)		 Control arm
(n = 496)
Completed PLE
Yes 856 (60.71) 319 (62.30) 264 (65.67) 273 (55.04)
No 554 (39.29) 193 (37.70) 138 (34.33) 223 (44.96)
PLE scores (mean, SD) 24.57 (6.98) 24.33 (6.24) 22.62 (7.78) 26.74 (6.39)
Transitioned to post-primary
% of the sample 571 (45.86) 224 (50.56) 187 (51.80) 160 (36.28)
% of those who completed PLE 571 (66.7) 224 (70.2) 187 (70.8) 160 (71.7)
Dropped out of school 633 (44.9) 204 (39.8) 162 (40.3) 267 (53.8)
Repeated a grade/still in primary school 41 (2.9) 15 (2.9) 12 (3.0) 14 (2.8)
Lost to follow-up 165 (11.7) 18 (3.5) 12 (3.0) 55 (11.1)
Open in a new tab

Finally, at 48-months follow-up, 59% (n = 839) of participants had not transitioned to post-primary education. They had either dropped out of school before or after completing primary school (44.9%), had not completed primary school at the time of interviews (2.9%), or lost to follow up (11.7%). Results from regression analyses are presented in the next section.

Effect of the bridges intervention on academic performance and school transition

Table 3 illustrates the effect of the Bridges intervention on participants’ PLE scores and school transition. Results indicate that participating in an asset-based intervention (Bridges or Bridges Plus) was associated with better PLE grades (lower scores indicate better performance) and transitioning to post-primary education. Specifically, controlling for participants’ demographic and household characteristics (model 1), participants in the Bridges arm (b = −3.78, 95% confidence interval [CI] = −4.92, −2.64, p ≤ 0.001) and Bridges Plus arm (b = −2.23, 95% CI = −3.32, −1.13, p ≤ 0.001), were more likely to report better PLE scores compared to participants in the control condition. Between the intervention groups, participants in the Bridges arm, receiving the 1:1 match rate, scored 1.55-point higher than those in the Bridges Plus arm receiving 1:2 match rate. Participants’ gender (b = 1.25, 95% CI = 0.29, 2.22, p ≤ 0.01), participants’ age (b = 0.98, 95% CI = 0.59, 1.36, p ≤ 0.001) and family assets (b = 0.28, 95% CI = 0.14, 0.43, p ≤ 0.001) were inversely associated with PLE grades.

Table 3.

Regression models on PLE scores and school transition.

Variables Model 1: PLE scores: b (95% Cl) Model 2: School transition: OR (95% Cl)
Intervention (control)
Bridges −3.78 (−4.92, −2.64)*** 1.69 (1.27, 2.25)***
Bridges Plus −2.23 (−3.32, −1.13)*** 1.66 (1.28, 2.18)***
Participants’ characteristics
Age 0.98 (0.59, 1.36)*** 0.64 (0.58, 0.71)***
Gender (female) 1.25 (0.29, 2.22)** 1.04 (0.82, 1.32)
Orphan hood (double orphan)
Maternal orphan −0.46 (−1.93, 1.02) 1.41 (0.98, 2.04)
Paternal orphan 0.12 (−1.19, 1.43) 1.42 (1.02, 1.98)*
Household characteristics
Number of people in the household 0.004 (−0.33, 0.34) 1.09 (1.01, 1.19)*
Number of children in the household −0.009 (−0.43, 0.42) 0.92 (0.78, 1.29)
Family assets 0.28 (0.14, 0.43)*** 1.00 (0.96, 1.04)
Family cohesion 0.03 (−0.06, 0.12) 1.00 (0.98, 1.03)
Availability of personal savings 0.48 (−0.54, 1.49) 1.01 (0.78, 1.29)
Caregiver (others)
Biological parent −0.89 (−2.15, 0.38) 1.09 (0.79, 1.52)
Grandparent −0.23 (−1.43, 0.96) 0.86 (0.63, 1.16)
F or χ2 7.64*** 131.23***
df 13 13
Adjusted R2 0.09 0.07
N 856 1375
Open in a new tab
*

p ≤ .05

**

p ≤ .01

***

p ≤ .001.

Similarly, participants receiving the intervention exhibited higher odds of transitioning to post-primary education (model 2). Specifically, the odds of transitioning to post-primary education were 1.69 times higher for Bridges arm participants (odds ratio [OR] = 1.69, 95% CI = 1.27, 2.25, p ≤ 0.001) and 1.66 times higher for Bridges Plus arm participants (OR = 1.66, 95% CI = 1.28, 2.18, p ≤ 0.001), relative to the control condition. In addition, participants who identified as paternal orphans (OR = 1.42, 95% CI = 1.02, 1.98, p ≤ 0.05), and those reporting more individuals living in the household (OR = 1.09, 95% CI = 1.01, 1.19, p ≤ 0.05) had higher odds of transitioning to post-primary education. However, older adolescents had lower odds of transitioning to post-primary education compared to younger adolescents (OR = 0.64, 95% CI = 0.58, 0.71, p ≤ 0.001).

Discussion

This paper examines the effects of participating in an asset-based intervention on educational outcomes (i.e. academic performance and school transition from primary to post-primary education) of OVCs in Uganda. Over the 5-year assessment period, the Bridges intervention, which combines CDAs, a mentorship programme and financial planning and microenterprise development workshops, indicate positive outcomes for OVCs. Results show that OVCs receiving the intervention (i.e. Bridges and Bridges Plus arms) performed significantly better on the PLE and had higher odds of transitioning to secondary/high school or vocational institutions than their counterparts in the control arm. Because OVCs receiving the intervention (and their families) did not have to worry about paying the entirety of an expensive post-primary education, it could be that they were more likely to think beyond primary school education and concentrate on their studies to qualify and enrol in post-primary education. Moreover, given that participants receiving the intervention met with peer mentors throughout the intervention period to discuss academic planning, setting realistic academic and career goals, financial planning and asset accumulation, it is possible that adolescents were able to integrate the knowledge and skills acquired during their mentorship sessions into their schooling, leading to better performance.

The findings of this study support the premise of asset theory that guides the design and implementation of this work. In particular, promoting and increasing the economic assets and opportunities of vulnerable youth, such as OVCs, encourages more positive beliefs and attitudes about the future (Schreiner & Sherraden, 2007; Sherraden, 1991, 1990). In this case, the multicomponent intervention provided a sense of economic security through the provision of matched savings, provided OVCs with a sense of hope to complete primary school without economic constraints, enabling them to envision a more tangible and realistic future, as well as personal responsibility of paying attention in class and working harder to achieve better grades. These findings are also consistent with previous findings that documented positive impacts on academic participation in terms of attendance, academic planning and performance in Uganda (Curley, Ssewamala, Nabunya, Ilic, & Keun, 2014; Ssewamala & Curley, 2006; Ssewamala & Ismayilova, 2009).

In addition, though study participants were recruited during their last 2–3 years of primary schooling, a large number of participants had either dropped out of school completely or were still in primary school 5 years later. Among those who had dropped out, more than half (53.8%) were participants in the control condition. This finding is consistent with those reported by Kasirye and Hisali (2010), wherein orphans from poor families affected by HIV/AIDS were more likely to fall 3 years behind their appropriate grade level compared to non-orphans. This situation may be attributed to several factors beyond the intervention, such as family responsibilities, grade repetition/ falling behind, and change of residences, which are common among OVCs, as well as stigma and discrimination associated with HIV/AIDS and orphanhood. Specifically, issues of family responsibilities that force OVCs to take on additional household responsibilities in lieu of schooling remains a major challenge to educational participation and achievement in Uganda, and many parts of SSA (Nabunya & Ssewamala, 2014). Low levels of school attendance and participation inhibit children’s performance in school and ultimately lead to grade repetition and school dropout. In addition, OVCs are more likely to bounce from one extended family to another, especially when the current family is overwhelmed with a large number of orphaned children and poverty. In such cases, children are often forced to change schools, which results in setbacks in schooling and performance.

Furthermore, though participants were enrolled in UPE with no school fees required, schools continue to experience inadequate supplies and infrastructures, including instructional materials, classrooms, gender-specific bathrooms and teachers. Schools often shift the burden of paying for these infrastructures to parents and caregivers in the form of ‘building fees.’ This often becomes the basis for sending children back home for lack of payments, leading to missed schooling, poor performance and eventually dropping out. All these situations combined might help explain why a number of participants in our study had not transitioned from primary school.

Study limitations

Given that the intervention was provided as a bundle of services that included matched savings, mentorship, financial planning and microenterprise development, it is not possible to measure the unique contribution of each individual component on educational outcomes. Future research should consider testing the effectiveness of each of the intervention components on OVC outcomes. Also, the lack of a true control condition may have implications for findings. Researchers should consider designs, wherein non-intervention participants do not receive support services from the study to ascertain the net effect of the intervention. The sample was limited to rural school/participants. Findings could be different among schools and participants in an urban school setting.

Implications and conclusion

Even with these limitations, the findings indicate that participating in an economic intervention has the potential to improve OVCs’ academic performance and reduce their economic barriers to transition from primary education to secondary school or vocational education. The small differences observed between the two intervention groups have implications for programming and policy. Specifically, programmes intending to incorporate matched saving interventions within the social protection efforts for OVCs may not need to select a higher match rate to see positive results. Even small financial contributions can offset the possible negative outcomes for OVCs, especially those orphaned as a result of HIV/AIDS. Finally, outcomes of national policies such as UPE could be improved and strengthened by incorporating economic strengthening components to help address poverty issues for poor families, especially those caring for OVCs to offset their human capital outcomes, including educational achievement.

Acknowledgments

Funding

This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development [1R01 HD070727-01].

Footnotes

Disclosure statement

No potential conflict of interest was reported by the authors.

References

  1. Adato M, & Bassett L (2009). Social protection to support vulnerable children and families: The potential of cash transfers to protect education, health and nutrition. AIDS Care, 21(S1), 60–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bicego G, Rutstein S, & Johnson K (2003). Dimensions of the emerging orphan crisis in sub-Saharan Africa. Social Science & Medicine, 56(6), 1235–1247. [DOI] [PubMed] [Google Scholar]
  3. Case A, Paxton C, & Ableidinger J (2004). Orphans in Africa: Parental death, poverty, and school enrollment. Demography, 41, 483–508. [DOI] [PubMed] [Google Scholar]
  4. Cheatham GA, & Elliott W (2013). The effects of family college savings on postsecondary school enrollment rates of students with disabilities. Economics of Education Review, 33, 95–111. [Google Scholar]
  5. Curley J, Ssewamala F, & Han C (2010). Assets and educational outcomes: Child Development Accounts (CDAs) for orphaned children in Uganda. Children and Youth Services Review, 32(11), 1585–1590. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Curley J, Ssewamala FM, Nabunya P, Ilic V, & Keun HC (2014). Child Development Accounts (CDAs): An asset building strategy to empower girls in Uganda. International Social Work doi: 10.1177/0020872813508569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Deininger K (2003). Does cost of schooling affect enrollment by the poor? Universal primary education in Uganda. Economics of Education Review, 22(3), 291–305. [Google Scholar]
  8. Elliott W (2009). Children’s college aspirations and expectations: The potential role of children’s development accounts (CDAs). Children and Youth Services Review, 31, 274–283. [Google Scholar]
  9. Evan D, & Miguel E (2004). Orphans and schooling in Africa: A longitudinal analysis. Demography, 44(1), 33–57. [DOI] [PubMed] [Google Scholar]
  10. Grogan L (2009). Universal primary education and school entry in Uganda. Journal of African Economies, 18(2), 183–211. [Google Scholar]
  11. Han C-K, Ssewamala FM, & Wang JS-H (2013). Family economic empowerment and mental health among AIDS-affected children living in AIDS-impacted communities: Evidence from a randomized evaluation in Southwestern Uganda. Journal of Epidemiology and Community Health, 67(3), 225–230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hunter S, & Williamson J (2000). Children on the brink: Strategies to support a generation isolated by HIV/AIDS Washington, DC: USAID. [Google Scholar]
  13. Kasirye I, & Hisali E (2010). The socioeconomic impact of HIV/AIDS on education outcomes in Uganda: School enrolment and the schooling gap in 2002/2003. International Journal of Educational Development, 30, 12–22. [Google Scholar]
  14. Kim Y, & Sherraden M (2011). Do parental assets matter for children’s educational? Attainment? Evidence from mediation tests. Children and Youth Services Review, 33, 969–979. [Google Scholar]
  15. Monasch R, & Boerma JT (2004). Orphanhood and childcare patterns in sub-Saharan Africa: An analysis of national surveys from 40 countries. AIDS, 18, S55–S65. [DOI] [PubMed] [Google Scholar]
  16. Nabunya P, & Ssewamala FM (2014). The effects of parental loss on the psychosocial wellbeing of AIDS-orphaned children living in AIDS-impacted communities: Does gender matter? Children and Youth Services Review, 43, 131–137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Nabunya P, Ssewamala FM, Mukasa MN, Byansi W, & Nattabi J (2015). Peer mentorship program on HIV/AIDS knowledge, beliefs, and prevention attitudes among orphaned adolescents: An evidence based practice. Vulnerable Children and Youth Studies, 10(4), 345–356. [PMC free article] [PubMed] [Google Scholar]
  18. Schreiner M, & Sherraden M (2007). Can the poor save? Saving & asset building in individual development accounts Piscataway, NJ: Transaction Publishers. [Google Scholar]
  19. Sherraden M (1990). Stakeholding: Notes in a theory of welfare based on assets. Social Service Review, 64(4), 580–601. [Google Scholar]
  20. Sherraden M (1991). Assets and the poor: A new American welfare policy New York, NY: M. E. Sharpe. [Google Scholar]
  21. Ssewamala F, Nabunya P, Mukasa NM, Ilic V, & Nattabi J (2014). Integrating a mentorship component in programming for care and support of AIDS-orphaned and vulnerable children: Lessons from the suubi and bridges programs in sub-Saharan Africa. Global Social Welfare, 1(1), 9–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Ssewamala FM (2015). Optimizing the “demographic dividend” in young developing countries: The role of contractual savings and insurance for financing education. International Journal of Social Welfare, 24(3), 248–262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Ssewamala FM, & Curley J (2006). Asset ownership and school attendance of orphaned children in sub-Saharan Africa. Social Development Issues, 28(2), 84–105. [Google Scholar]
  24. Ssewamala FM, Han C-K, Neilands TB, Ismayilova L, & Sperber E (2010). Effect of economic assets on sexual risk taking intentions among orphaned adolescents in Uganda. American Journal of Public Health, 100(3), 483–488. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Ssewamala FM, & Ismayilova L (2009). Integrating children savings accounts in the care and support of orphaned adolescents in rural Uganda. Social Service Review, 83(3), 453–472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ssewamala FM, Neilands TB, Waldfogel J, & Ismayilova L (2012). The impact of a comprehensive microfinance intervention on depression levels of AIDS-orphaned children in Uganda. Journal of Adolescent Health, 50(4), 346–352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Uganda Ministry of Education and Sports [MoES]. (2015). Education for all 2015 national review Retrieved from http://unesdoc.unesco.org/images/0023/002317/231727e.pdf
  28. Uganda Ministry of Education and Sports [MoES]. (2017). The education and sports sector annual performance report. Financial Year 2016/17 Retrieved from http://www.education.go.ug/files/downloads/ESSAPR%20%202016-17.pdf
  29. UNESCO. (2000). The Dakar Framework for Action. Education for All: Meeting our collective commitment Retrieved from http://unesdoc.unesco.org/images/0012/001211/121147e.pdf
  30. UNICEF. (2016). The State of the World’s Children 2016: A fair chance for every child Retrieved from http://www.unicef.org/publications/files/UNICEF_SOWC_2016.pdf

RESOURCES