About our work
The first 1000 days of human life cover the period between conception and the second birthday. Proper development during this period contributes to future health, happiness, and productivity, so it is essential to track the child’s progress during infancy and early childhood. But did you know that more than 150 instruments exist that quantify child development? And are you aware that many of these tools produce not just one, but many scores? Such an overwhelming choice may seem a luxury until you realise that we cannot compare their ratings. Of course, we could settle on just one instrument …., but that’s never going to happen.
Our work on the D-score explores an alternative strategy—modern data science methods aid in connecting instruments through shared milestones. We present a unified framework that places children and milestones from different tools onto the same scale. As a result, we can measure child development by just one number, the D-score. Separating the scale from the instrument is a revolutionary concept. Application of the D-score enables comparisons in child development across populations, groups and individuals, even when we measure by different tools.
The new “unit for child development” has exciting implications. We may:
- Track child development over time, as in growth charts;
- Construct age-related references for healthy development;
- Adjust the D-score for age;
- Select an instrument that is precise enough for the setting at hand;
- Compare developmental trajectories between children;
- Compare child development between countries;
- Derive concise tools by picking only well-targeted milestones;
- Study the impact of interventions on child development;
- Predict future health from the current D-score.
Our ongoing work addresses conceptual aspects of the D-score, discusses practical issues, and introduces a dedicated set of R packages.
We aim for three audiences:
Professionals in child development who wish to familiarise themselves with a new approach to measure child development in early childhood. Separating the tools from the scales allows the professional to select the means most suited for a particular setting. These chapters give professionals the conceptual background of the D-score.
Policymakers in international settings who need to weigh the effect of interventions on child development. The existence of different instruments severely hampers their ability to obtain insight into the results of these interventions. The ability to place measurements onto the same scale allows for a more accurate understanding of policy effects, thus supporting the setting of priority levels.
Data scientists who can transform a vector of milestone data into a one-number summary with an unambiguous unit. The techniques have a solid psychometric backing, and also apply to other types of problems. These chapters explain this conversion process in detail, thereby opening up the way for the application of precise analytic techniques in many different settings.
Additionally, parents are always eager to follow every step of their child. While we do not target this work to parents, our methodology may spark the interest of authors, app writers, and instrument creators that do address the interests and needs of parents. Hence, the publication of these chapters may have additional societal impact.