Literature DB >> 35444340

Matched and Fully Private? A New Self-Generated Identification Code for School-Based Cohort Studies to Increase Perceived Anonymity.

Maria Calatrava1,2, Jokin de Irala1,2, Alfonso Osorio1,2,3, Edgar Benítez1,4, Cristina Lopez-Del Burgo1,2.   

Abstract

Anonymous questionnaires are frequently used in research with adolescents in order to obtain sincere answers about sensitive topics. Most longitudinal studies include self-generated identification codes (SGICs) to match information. Typical elements include a combination of letters and digits from personal data. However, these data may make the participant feel that their answers are not truly anonymous, and some studies using these types of SGICs have been perceived as not entirely anonymous by some participants. Furthermore, data protection laws could place limits on research carried out with these codes. The objective of our article is to test an SGIC with a higher degree of anonymity. We conducted two studies. In Study 1, we tested the perceived anonymity of this new SGIC code. Adolescents aged 12 to 18 years (N = 601) completed an anonymous questionnaire about lifestyles and risk behaviors, which also included the SGIC. Adolescents with and without risk behaviors were compared regarding whether or not they answered to the SGIC questions. We did not find any differences to suggest that participants felt identifiable. In Study 2, we assessed the efficiency of the new SGIC. At baseline, 123 students from two high schools (eighth grade) filled in questionnaires consisting of the new SGIC and their full names. Two years later, these same students (then in the 10th grade) were invited to fill in the same information again (116 students responded to this second call). A total of 97 students were present in both waves. The SGIC showed a moderate performance, with good enough indices of recall and precision. Evidence suggests that the new SGIC is a suitable tool for the anonymous matching of adolescents in follow-ups of school cohorts.
© The Author(s) 2021.

Entities:  

Keywords:  adolescents; cohort studies; linking; matching; risk behaviors; self-generated identification codes

Year:  2021        PMID: 35444340      PMCID: PMC9014735          DOI: 10.1177/00131644211035436

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   3.088


  15 in total

1.  Matching anonymous pre-posttests using subject-generated information.

Authors:  J McGloin; S Holcomb; D S Main
Journal:  Eval Rev       Date:  1996-12

2.  Self-generated identification codes for anonymous collection of longitudinal questionnaire data.

Authors:  K A Kearney; R H Hopkins; A L Mauss; R A Weisheit
Journal:  Public Opin Q       Date:  1984

3.  Improving the use of self-generated identification codes.

Authors:  Rainer Schnell; Tobias Bachteler; Jörg Reiher
Journal:  Eval Rev       Date:  2010-10

4.  Testing anonymous link procedures for follow-up of adolescents in a school-based trial: the EU-DAP pilot study.

Authors:  M Rosaria Galanti; Roberta Siliquini; Luca Cuomo; Juan Carlos Melero; Massimiliano Panella; Fabrizio Faggiano
Journal:  Prev Med       Date:  2006-09-18       Impact factor: 4.018

5.  The use of self-generated identification codes in longitudinal research.

Authors:  Leo A Yurek; Joseph Vasey; Donna Sullivan Havens
Journal:  Eval Rev       Date:  2008-05-13

6.  Matching anonymous participants in longitudinal research on sensitive topics: Challenges and recommendations.

Authors:  Jane E Palmer; Samantha C Winter; Sarah McMahon
Journal:  Eval Program Plann       Date:  2020-02-25

7.  A Successful Strategy for Linking Anonymous Data from Students' and Parents' Questionnaires Using Self-Generated Identification Codes.

Authors:  Jaroslav Vacek; Hana Vonkova; Roman Gabrhelík
Journal:  Prev Sci       Date:  2017-05

8.  An evaluation of a self-generated identification code.

Authors:  C DiIorio; J E Soet; D Van Marter; T M Woodring; W N Dudley
Journal:  Res Nurs Health       Date:  2000-04       Impact factor: 2.228

9.  Developing and Validating a Novel Anonymous Method for Matching Longitudinal School-Based Data.

Authors:  Jon Agley; David Tidd; Mikyoung Jun; Lori Eldridge; Yunyu Xiao; Steve Sussman; Wasantha Jayawardene; Daniel Agley; Ruth Gassman; Stephanie L Dickinson
Journal:  Educ Psychol Meas       Date:  2020-07-08       Impact factor: 2.821

Review 10.  Project YOURLIFE (What Young People Think and Feel about Relationships, Love, Sexuality, and Related Risk Behavior): Cross-sectional and Longitudinal Protocol.

Authors:  Silvia Carlos; Alfonso Osorio; María Calatrava; Cristina Lopez-Del Burgo; Miguel Ruiz-Canela; Jokin de Irala
Journal:  Front Public Health       Date:  2016-02-22
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