Mean corrected generalized estimating equations for longitudinal binary outcomes with report bias

Cocaine addiction is an important public health problem worldwide. Cognitive-behavioral therapy is a counseling intervention for supporting cocaine-dependent individuals through recovery and relapse prevention. It may reduce patients’ cocaine uses by improving their motivations and enabling them to recognize risky situations. To study the effect of cognitive behavioral therapy on cocaine dependence, the self-reported cocaine use with urine test data were collected at the Primary Care Center of Yale-New Haven Hospital. Its outcomes are binary, including both the daily self-reported drug uses and weekly urine test results. To date, the generalized estimating equations are widely used to analyze binary data with repeated measures. However, due to the existence of significant self-report bias in the self-reported cocaine use with urine test data, a direct application of the generalized estimating equations approach may not be valid. In this paper, we proposed a novel mean corrected generalized estimating equations approach for analyzing longitudinal binary outcomes subject to reporting bias. The mean corrected generalized estimating equations can provide consistently and asymptotically normally distributed estimators under true contamination probabilities. In the self-reported cocaine use with urine test study, accurate weekly urine test results are used to detect contamination. The superior performances of the proposed method are illustrated by both simulation studies and real data analysis.

Validity and bias on the online active Australia survey: activity level and participant factors associated with self-report bias

Background This study examined the criterion validity of the online Active Australia Survey, using accelerometry as the criterion, and whether self-report bias was related to level of activity, age, sex, education, body mass index and health-related quality of life. Methods The online Active Australia Survey was validated against the GENEActiv accelerometer as a direct measure of activity. Participants (n = 344) wore an accelerometer for 7 days, completed the Active Australia Survey, and reported their health and demographic characteristics. A Spearman’s rank coefficient examined the association between minutes of moderate-to-vigorous physical activity recorded on the Active Australia Survey and GENEActiv accelerometer. A Bland-Altman plot illustrated self-report bias (the difference between methods). Linear mixed effects modelling was used to examine whether participant factors predicted self-report bias. Results The association between moderate-to-vigorous physical activity reported on the online Active Australia Survey and accelerometer was significant (rs = .27, p < .001). Participants reported 4 fewer minutes per day on the Active Australia Survey than was recorded by accelerometry (95% limits of agreement −104 – 96 min) but the difference was not significant (t(343) = −1.40, p = .16). Self-report bias was negatively associated with minutes of accelerometer-recorded moderate-to-vigorous physical activity and positively associated with mental health-related quality of life. Conclusions The online Active Australia Survey showed limited criterion validity against accelerometry. Self-report bias was related to activity level and mental health-related quality of life. Caution is recommended when interpreting studies using the online Active Australia Survey.

Longitudinal Change in Adolescent Bedtimes Measured by Self-Report and Actigraphy

Introduction: Sleep is often quantified using self-report or actigraphy. Self-report is practical and less technically challenging, but prone to bias. We sought to determine whether these methods have comparable sensitivity to measure longitudinal changes in adolescent bedtimes. Methods: We measured one week of free-living sleep with wrist actigraphy and usual bedtime on school nights and non-school nights with self-report questionnaire in 144 students at 15 y and 17 y. Results: Self-reported and actigraphy-measured bedtimes were correlated with one another at 15 y and 17 y (p < .001), but reported bedtime was consistently earlier (>30 minutes, p < .001) and with wide inter-method confidence intervals (> ±106 minutes). Mean inter-method discrepancy did not differ on school nights at 15 y and 17 y but was greater at 17 y on non-school nights (p = .002). Inter-method discrepancy at 15 y was not correlated to that at 17 y. Mean change in self-reported school night bedtime from 15 y to 17 y did not differ from that by actigraphy, but self-reported bedtime changed less on non-school nights (p = .002). Two-year changes in self-reported bedtime did not correlate with changes measured by actigraphy. Conclusions: Although methods were correlated, consistently earlier self-reported bedtime suggests report-bias. More varied non-school night bedtimes challenge the accuracy of self-report and actigraphy, reducing sensitivity to change. On school nights, the methods did not differ in group-level sensitivity to changes in bedtime. However, lack of correlation between bedtime changes by each method suggests sensitivity to individual-level change was different. Methodological differences in sensitivity to individual- and group-level change should be considered in longitudinal studies of adolescent sleep patterns.

A Picture of Bias Crime in New South Wales

Bias Crime is crime where the victim is targeted because of an aspect of their identity, including race, ethnicity, religion or sexuality. It is an extreme manifestation of cultural tension and conflict. Bias crime remains under-researched in Australia. While there has been some investigation into different types of bias crime, such as racist and homophobic offences, there is little analysis of the nature and extent of bias crime across these categories. For the first time, this article presents the results of a study into official records of bias crime held by the New South Wales Police Force. The study shows that crimes motivated by bias based on the victim’s race/ethnicity and religion are by far the most common types of bias crime reported in NSW. People from Asian, Indian/Pakistani and Muslim backgrounds are the most likely victims to report bias crime. The study also shows that there is much work to be done to encourage bias crime reporting amongst marginalised communities and improve the capacity of police to identify and accurately record bias crime. We argue that civil society has an important role to play in building partnerships with police to achieve positive change in the policing of bias crime.