Longitudinal studies like ALSPAC usually suffer from missing data arising through non-response. This issue can be partly addressed by linking to routine data sources, since individuals who are missing from the study data will be present in such datasets. Measures created using routine data could be used in place of the missing study outcomes or used to impute the missing values. However, in order for them be used in this way, it is important to know how outcomes recorded in these datasets relate to outcomes recorded in the longitudinal studies. To our knowledge, no studies to date have validated measures for defining ADHD or conduct disorder within routine electronic primary care data.

The Strength and Difficulties Questionnaire (SDQ) has been widely used to measure child psychopathology both in research studies and in clinical practice. It has been shown to be a valid tool for identifying children with attention deficit hyperactivity disorder (ADHD) and conduct disorder (Goodman et al, 2000a). The Development and Well-being Assessment (DAWBA) is a tool that can be used to ascertain whether an individual meets DSM IV (American Psychiatric Association, 1994) diagnostic criteria for a range of psychiatric disorders, including ADHD and conduct disorder (Goodman et al, 2000b)

SDQ data have been collected in both ALSPAC and the Millennium Cohort Study (MCS). ALSPAC has also collected DAWBA data. Both studies have also linked to primary care data on a subset of participants. As such, these two studies provide a unique opportunity to validate measures of ADHD and conduct disorder derived using electronic primary care data against previously validated measures.