An important interest in mixture modeling is the investigation of what types of individuals belong to each latent class by relating classes to covariates, concurrent outcomes and distal outcomes, also known as auxiliary variables. This article presents results from real data examples and simulations to show how various factors, such as the degree to which people are classified correctly into latent classes and sample size, can impact the estimates and standard errors of auxiliary variable effects and testing mean equality across classes. Based on the results of the examples and simulations, suggestions are made about how to select auxiliary variables for a latent class analysis.
Introduction Response rates in health research are declining, and low response rates could result in biased outcomes when population characteristics of participants systematically differ from the non-respondents. Few studies have examined key factors of non-response beyond demographic characteristics, such as behavioral and psychological factors. The aim of the current study was to identify predictors of non-response and loss to follow-up in a longitudinal sexual health study. Materials and methods A longitudinal cohort study (iMPaCT) was conducted from November 2016 to July 2018 among heterosexual STI clinic visitors aged 18–24 years. At four different time points in one year, data was collected on sexual behavior, psychological determinants and chlamydia infections. The national STI surveillance database provided data on demographic, behavioral and sexual health-related characteristics for non-respondents. Predictors of non-response at baseline and of loss to follow-up were identified using multivariable logistic regression analyses. Results In total, 13,658 STI clinic visitors were eligible to participate, of which 1,063 (8%) participated. Male gender, low/medium education level, young age (≤ 20 years) and having a non-Dutch migration background were significant predictors of non-response at baseline. Furthermore, non-respondents at baseline were more likely to report STI-related symptoms, to have been notified by a partner, to have had condomless sex, and to have had ≤ 2 partners in the past six months, compared to participants. Psychological predictors of loss to follow-up differed between STI clinic regions, but low perceived importance of health at baseline was associated with loss to follow-up in all regions. The baseline chlamydia positivity rate was significantly higher in the non-respondents (17%) compared to the participants (14%), but was not a predictor of loss to follow-up. Discussion Targeted recruitment aimed at underrepresented groups in the population based on demographic, behavioral and psychological characteristics, might be necessary to decrease loss to follow-up, and to prevent non-response bias in health research.
BackgroundChlamydia trachomatis (chlamydia), the most commonly reported sexually transmitted infection (STI) in the Netherlands, can lead to severe reproductive complications. Reasons for the sustained chlamydia prevalence in young individuals, even in countries with chlamydia screening programs, might be the asymptomatic nature of chlamydia infections, and high reinfection rates after treatment. When individuals are unaware of their infection, preventive behaviour or health-care seeking behaviour mostly depends on psychological determinants, such as risk perception. Furthermore, behaviour change after a diagnosis might be vital to reduce reinfection rates. This makes the incorporation of psychological determinants and behaviour change in mathematical models estimating the impact of interventions on chlamydia transmission especially important. Therefore, quantitative real-life data to inform these models is needed.MethodsA longitudinal cohort study will be conducted to explore the link between psychological and behavioural determinants and chlamydia (re)infection among heterosexual STI clinic visitors aged 18–24 years. Participants will be recruited at the STI clinics of the public health services of Amsterdam, Hollands Noorden, Kennemerland, and Twente. Participants are enrolled for a year, and questionnaires are administrated at four time points: baseline (before an STI consultation), three-week, six-month and at one-year follow-up. To be able to link psychological and behavioural determinants to (re)infections, participants will be tested for chlamydia at enrolment and at six-month follow-up. Data from the longitudinal cohort study will be used to develop mathematical models for curable STI incorporating these determinants to be able to better estimate the impact of interventions.DiscussionThis study will provide insights into the link between psychological and behavioural determinants, including short-term and long-term changes after diagnosis, and chlamydia (re)infections. Our mathematical model, informed by data from the longitudinal cohort study, will be able to estimate the impact of interventions on chlamydia prevalence, and identify and prioritise successful interventions for the future. These interventions could be implemented at STI clinics tailored to psychological and behavioural characteristics of individuals.Trial registrationDutch Trial Register NTR-6307. Retrospectively registered 11-nov-2016.
Prevention of infectious diseases depends on health-related behavior, which is often influenced by psychological characteristics. However, few studies assessing health-related behavior have examined psychological characteristics to identify risk groups, and this multidimensional approach might improve disease risk assessment. We aimed to characterize subgroups based on psychological characteristics and examine their influence on behavior and disease risk, using chlamydia as a case study. Selected participants (heterosexuals aged 18–24 years and females aged 18–24 years who had sex with both men and women) in a Dutch longitudinal cohort study (the Mathematical Models Incorporating Psychological Determinants: Control of Chlamydia Transmission (iMPaCT) Study) filled out a questionnaire and were tested for chlamydia (2016–2017). Latent class analysis was performed to identify risk classes using psychological predictors of chlamydia diagnosis. Two classes were identified: class 1 (n = 488; 9% chlamydia diagnosis) and class 2 (n = 325; 13% chlamydia diagnosis). The proportion of participants with high shame, high impulsiveness, and lower perceived importance of health was higher in class 2 than in class 1. Furthermore, persons in class 2 were more likely to be male and to report condomless sex compared with class 1, but the number of recent partners was comparable. Thus, risk classes might be distinguished from each other by psychological characteristics beyond sexual behavior. Therefore, the impact of the same intervention could differ, and tailoring interventions based on psychological characteristics might be necessary to reduce chlamydia prevalence most effectively.
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