Understanding accelerators to improve SDG-related outcomes for adolescents-An investigation into the nature and quantum of additive effects of protective factors to guide policy making

Abstract

Recent evidence has shown support for the United Nations Development Programme (UNDP) accelerator concept, which highlights the need to identify interventions or programmatic areas that can affect multiple sustainable development goals (SDGs) at once to boost their achievement. These data have also clearly shown enhanced effects when interventions are used in combination, above and beyond the effect of single interventions. However, detailed knowledge is now required on optimum combinations and relative gain in order to derive policy guidance. Which accelerators work for which outcomes, what combinations are optimum, and how many combinations are needed to maximise effect? The current study utilised pooled data from the Young Carers (n = 1402) and Child Community Care (n = 446) studies. Data were collected at baseline (n = 1848) and at a 1 to 1.5- year follow-up (n = 1740) from children and young adolescents aged 9-13 years, living in South Africa. Measures in common between the two databases were used to generate five accelerators (caregiver praise, caregiver monitoring, food security, living in a safe community, and access to community-based organizations) and to investigate their additive effects on 14 SDG-related outcomes. Predicted probabilities and predicted probability differences were calculated for each SDG outcome under the presence of none to five accelerators to determine optimal combinations. Results show that various accelerator combinations are effective, though different combinations are needed for different outcomes. Some accelerators ramified across multiple outcomes. Overall, the presence of up to three accelerators was associated with marked improvements over multiple outcomes. The benefit of targeting access to additional accelerators, with additional costs, needs to be weighed against the relative gains to be achieved with high quality but focused interventions. In conclusion, the current data show the detailed impact of various protective factors and provides implementation guidance for policy makers in targeting and distributing interventions to maximise effect and expenditure. Future work should investigate multiplicative effects and synergistic interactions between accelerators.

Fig 1. Accelerator combinations leading to the strongest changes in adjusted probabilities for each mental health outcome.

Figure scales adjusted based on range of outcome values. Presence of all conditions based on symptom not clinical cut-offs (13). Good mental health: composite measure of the other three conditions. CBO = Access to community-based organisations, SC = Living in a Safe Community, CP = Caregiver Praise, FS = Food security, CM = Caregiver Monitoring. 95% confidence intervals included.

Fig 2. Accelerator combinations leading to the strongest changes in adjusted probabilities for each behavioural outcome.

Figure scales adjusted based on range of outcome values. CBO = Access to community-based organisations, SC = Living in a Safe Community, CP = Caregiver Praise, FS = Food security, CM = Caregiver Monitoring. 95% confidence intervals included.

Fig 3. Accelerator combinations leading to the strongest changes in adjusted probabilities for each school outcome.

Figure scales adjusted based on range of outcome values. CBO = Access to community-based organisations, SC = Living in a Safe Community, CP = Caregiver Praise, FS = Food security, CM = Caregiver Monitoring. 95% confidence intervals included.

Fig 4. Accelerator combinations leading to the strongest changes in adjusted probabilities for each violence-related outcome.

Figure scales adjusted based on range of outcome values. CBO = Access to community-based organisations, SC = Living in a Safe Community, CP = Caregiver Praise, FS = Food security, CM = Caregiver Monitoring. 95% confidence intervals included.

Fig 5. Accelerator combinations leading to the strongest changes in adjusted probabilities for SDG outcomes.

This figure depicts the predicted probabilities for an adaptive outcome for all 13 indicators, under the presence of no accelerator, the single most effective accelerator, the most effective combinations of two, three and four accelerators, and all five accelerators.