Early Language in Victoria Study (ELVS)
The Early Language in Victoria Study (ELVS) has been following the speech and language development of a large group of children (>1900) born in the surrounds of Melbourne, Victoria (Australia) since they were 8 months of age. ELVS continues to follow this same group of children as they transition from middle childhood to adolescence. There are a number of ELVS sub-studies investigating different areas of communication development including: stuttering, autism and bilingual language development.
|Study name||Early Language in Victoria Study|
|Current principal investigator/s||
|Current project manager||
The University of Melbourne - UoM
Murdoch Children’s Research Institute - MCRI
La Trobe University
|Major funding source/s||
National Health and Medical Research Council - NHMRC
|Key reference for study||Reilly, S., Cook, F., Bavin, E.L., Bretherton, L., Cahir, P., Eadie, P., Gold, L., Mensah, F., Papadopoullos, S. and Wake, M. (2017). Cohort Profile: The Early Language in Victoria Study (ELVS). International Journal of Epidemiology. doi: 10.1093/ije/dyx079dyx079-dyx079.|
How language develops from infancy (8 months) to adolescence. Sub-studies include investigations in to stuttering, autism, and bilingual language development.
Maternal and Child Health Nurses approached all parents of babies aged 8-10 months of age, within six Local Government Areas of Melbourne, Australia.
|Primary study type||Longitudinal cohort|
|Is this study ongoing?||Yes - the study is ongoing|
|Sample size (N)||
|Survey data available?||Yes|
|Imaging data available?||No|
|Linkage to administrative dataset/s?||No, no consent to link to administrative dataset(s) obtained|
|Are data available to others outside study team, with appropriate safeguards and structures in line with the cohort’s ethics and governance processes?||Yes|
|Are there any costs associated with data/sample access for approved requests?||There may be costs associated with access, evaluated on a case by case basis|
|Broadest type of participant consent available||
Extended consent (can be used for future ethically approved research related to this project)
Gasparini L, Shepherd DA, Bavin EL, Eadie P, Reilly S, Morgan AT, Wake M. (2023). Using machine‐learning methods to identify early‐life predictors of 11‐year language outcome Journal of Child Psychology and Psychiatry, 64(8), 1242 - 1252. DOI: 10.1111/jcpp.13733