We are embarking on a longitudinal research project which will involve children from 9 to 18 years old. We were hoping to develop an SGIC for the children to maintain anonymity for participants, but haven't nailed a code which will work over the longer term. A literature doesn't reveal much advice or work in this area at all, so wondering if anyone else has experience on this topic?
When children are involved as participants, this task is more difficult than with adults, as there is a need:
· For children to remember and accurately self-report over time (selecting data which does not change over time)
· For researchers to ensure that participants remain unidentifiable (confidence in the anonymity of data)
· For researchers to develop simple and clear instructions to obtain unambiguous code responses (This will reduce data loss through mismatch or duplication over time)
· For researchers to develop a choice of codes which are achievable by all (e.g. Does everyone have a father/mobile phone?)
Sorry I didn't even know the term SGIC because I study a small pool of participants (max 100 subjects) and one off data collection, not longitudinal. So I simply use running numbers. As I was reading the application of SGIC just now, I came across these, not sure if they would be of any value to you:
Article A Successful Strategy for Linking Anonymous Data from Studen...
Design and Application of Self-Generated Identification Codes (SGICs) for Matching Longitudinal Data:
http://sefibenvwh.cluster023.hosting.ovh.net/wp-content/uploads/2017/09/direnga-design-and-application-of-self-generated-identification-codes-172_a.pdf
USING SELF-GENERATED IDENTIFICATION CODES TO MATCH QUESTIONNAIRES IN PANEL STUDIES OF ADOLESCENT
https://core.ac.uk/download/pdf/34711537.pdf
Thanks Yvonne - I hadn't seen the Direnga article so thanks for that. In case you're also interested in this area, the best I've found so far are recent articles from Agley et al 2020 and Audette et al 2020. The latter Audette article is a more general discussion of methodological issues relating to coding for longitudinal studies (rather than specifically applying to young people), but it is a very good meta-analysis. The Agley article focuses on young people. Cheers Janet
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