Examining Actor-Level Change and Contribution Pathways in a Multisectoral WASH–SRH Programme Using an Integrated Implementation Mapping–Outcome Mapping–Outcome Harvesting Framework

In the world of public health, a common challenge is figuring out how to get life-saving programs to work when they involve many different groups of people. Imagine trying to improve water, sanitation, and reproductive health in a community. This is not just about handing out supplies; it requires doctors, local leaders, market sellers, banks, and families to all change how they act and work together. For a long time, researchers have tried to measure success by looking at simple cause-and-effect chains: if we do X, then Y happens. But real life is rarely that straight. It is more like a complex web where everyone influences everyone else, and changes often appear unexpectedly. To understand these messy, real-world situations, scientists need new ways of looking at the picture, moving beyond simple checklists to see how different people and organizations actually shift their behavior over time.

This is exactly what a team of researchers set out to do in Ethiopia. They studied a large program designed to improve water, sanitation, and sexual health across two very different regions: the farming-heavy Jimma zone and the more nomadic, pastoral Borena zone. Instead of just counting how many toilets were built or how many people attended a meeting, the researchers wanted to understand the story of how the program actually unfolded. They asked a different question: how did the various people involved—from community health workers to government officials and local money lenders—change their daily habits and relationships to make the program work? To answer this, they used a special three-part method. First, they mapped out what they hoped would happen and who they expected to change. Second, they watched closely to see who actually changed their behavior. Third, they gathered evidence to prove those changes were real and linked them back to the program's activities. This approach allowed them to see the program not as a machine with gears, but as a living system where progress depended on many moving parts aligning.

The researchers followed the program from 2022 to 2025, collecting stories and data from routine reports, supervision visits, and meetings with local stakeholders. They started with 48 potential examples of change, or "outcomes," and carefully filtered them down to 35 that were well-supported by evidence. These 35 stories fell into five main categories. The largest group involved changes in how different government offices and community groups coordinated with each other. Another group showed how people learned new skills and changed their daily work habits. A third category captured how families and businesses found new ways to pay for improvements, such as taking out loans or using savings. The remaining stories focused on better record-keeping and the actual delivery of services and infrastructure.

What the team found was that success did not come from any single activity working in isolation. It was not enough to simply tell people they needed better sanitation, or to build a latrine without ensuring someone could afford it. The program only moved forward when different pieces of the system clicked into place at the same time. For instance, community health workers successfully encouraged families to want better sanitation, but this demand only turned into action when local artisans were ready to build, when banks offered loans, and when government offices coordinated their oversight. In one specific instance, health workers began systematically tracking referrals to local builders, creating a reliable link between a family's request and the person who could fulfill it. In another, families stopped waiting for free aid and started combining savings, loans, and help from neighbors to finance their own improvements.

The study also highlighted that progress looked different depending on the setting. In the more settled farming areas, the changes often involved strengthening existing service networks. In the more mobile pastoral communities, the focus shifted to making sure services could reach people who moved frequently. Across both regions, the researchers observed that when one part of the system lagged behind, the whole effort slowed down. If families wanted sanitation but could not get a loan, the demand remained unmet. If artisans were ready to build but had no clear direction from health workers, they had no work. The most successful moments occurred when demand creation, service readiness, access to money, and government support all reinforced each other.

The evidence for these changes was robust. More than half of the 35 documented outcomes were backed by multiple independent sources, such as official records, financial documents, and confirmation from the people involved. The researchers noted that over 12,000 households constructed improved sanitation facilities during the study period, and families invested more than 119 million Ethiopian birr into these improvements. While these numbers show the scale of the effort, the researchers emphasized that the true value lay in understanding the human behaviors behind the numbers. They saw families shifting from passive interest to active investment, and local businesses adapting their services to meet new needs.

This research suggests that fixing complex health and development problems requires a shift in how we think about implementation. It is not enough to design a perfect plan and hope it works. Instead, programs must be flexible enough to adapt as different groups of people change their behaviors. The researchers concluded that the key to success in these multisectoral efforts is alignment. When the people who create demand, the people who provide services, the people who provide money, and the people who oversee the system all move in the same direction, real progress happens. By using a method that tracks these interactions over time, the study offers a clearer way to understand how complex programs succeed or fail in the real world, providing a roadmap for future efforts that rely on the cooperation of many different actors.