Methodological Issues With Coding Participants in Anonymous Psychological Longitudinal Studies

Abstract

Longitudinal studies are commonly used in the social and behavioral sciences to answer a wide variety of research questions. Longitudinal researchers often collect data anonymously from participants when studying sensitive topics to ensure that accurate information is provided. One difficulty gathering longitudinal anonymous data is that of correctly matching participants across waves of data collection. A number of methods have been proposed for using nonidentifying codes to match anonymous participants; however, currently there is no consensus on the most effective method. This article reviews and analyzes the literature on nonidentifying codes and provides recommendations for researchers interested in using these types of codes in conducting anonymous longitudinal studies.

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

“…Conceptually, there were also other factors that likely improved our rate, and some that likely suppressed our rate. As Audette et al (2020) demonstrated, matching rates tend to decline over time, and so our relatively short time frame likely improved our rate by limiting data loss due to failed recall. At the same time, our computation of matching rate was conservative in how it handled missing data elements; we required all matching elements to be missing (e.g., a fully blank survey) to remove a survey from the denominator, meaning that mostly blank instruments that were ''functionally'' unmatchable were included in our computation and lowered our matching success rate.…”

“…It is, however, difficult to determine where this match rate falls within the spectrum of published SGIC match rates in terms of efficacy, as we outline subsequently. Audette et al (2020) found that a substantive portion of the literature on SGIC matching cannot be mined effectively because insufficient details are available. That research team identified a wide range of ''one-off'' matching rates for different numbers of elements; the rates for seven and eight elements (the numbers used in this study) in that review were 84.2% and 75.7%, respectively.…”

“…When analyzing longitudinal data, it is important to be able to match responses across data collection points, as each instance of a failed match contributes to attrition rate, and there are meaningful reductions in statistical power when treating repeated measurement of the same subjects as data from independent samples (e.g., Fradette et al, 2003). However, many longitudinal studies are designed to be anonymous (Audette et al, 2020), increasing the difficulty of successfully matching data from the same participant between data collection points. For the purposes of this study, we conceptualized anonymous data as being data that cannot be traced back to an individual participant (Coffelt, 2017), though this standard can be interpreted differentially.…”

“…SGICs have been used for matching anonymous responses for decades with varying levels of success (Yurek et al, 2008). However, most of the commonly used elements in SGICs draw personalized components from the respondents' birthday, own name, and mother and/or father's name (Audette et al, 2020). While Audette et al's (2020) review identified these methods as anonymous, the mere fact that they reference personal information-even though only limited elements are being used-may raise privacy concerns in a school-based data collection setting.…”

“…At least one study has raised the possibility that some students will assume that research projects are being sponsored and conducted by the school and that the school may have an interest in using data punitively, producing heightened apprehension about anonymity and concomitant reluctance to participate (Gassman et al, 2016). Furthermore, even though there appears to be a consensus that using individual letters or numbers from personal elements makes reidentification of participants highly unlikely (Audette et al, 2020), parents or students may react to the mere mention of middle initials or birthdays on a survey that is labeled anonymous and assume a breach of trust, or even malfeasance (Gassman et al, 2019). The consequences of such assumptions for public health initiatives and projects can be striking.…”