The ‘right time’ – negotiating the timing of interviews with vulnerable young people

Participant retention is a key factor in determining the success of longitudinal research. Challenges in re-locating and retaining participants over the long term are major issues for researchers working with young people who face adversity and experience frequent changes in circumstances. This article reports on a study of vulnerable young people and their transition into adulthood. Rather than the more conventional schedule-based approach to locating and re-interviewing young people, a relational process, the ‘right time’ framework, was used to facilitate young people's involvement in the study. Embedded in the ‘right time’ framework is recognition of the diverse and fluctuating circumstances that shape young people's availability for interviews. Several case examples are considered which amplify the way that the ‘right time’ framework allowed the research to navigate around these circumstances. The case examples highlight the value young people attached to being involved in the research, the influence on the ‘right time’ of wider relational tensions for young people and the need to negotiate researcher status as a different sort of adult. The ‘right time’ framework contributed to a high retention rate in the study generating a more representative sample and enhancing the subsequent data analysis by providing valuable insights into the lives of these vulnerable young people.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

The Story of Belle, Minnie, Louise and the Sovjets: throwing light on the dark side of an institution

Our post-modernist story is composed as a narrative analysis of the lived experiences of Belle and Louise--two women with 'learning difficulties'--and our ethnographic field notes while doing narrative inquiry. The narratives mirror a shared construction of meaning and broaden our understanding--throwing light on the dark side of an institution. The narrative analysis points out a clear illustration of power dynamics and discourses in their lives, and shows how the women boast of resilience and offer (hidden) resistance. This paper particularly illuminates the individual, personal and even private celebration of activism and self-empowerment of Belle and Louise. Their vivid stories take us on an enthralling journey, getting to know their world through their eyes.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Entering a New Peer Group in Ethnically and Linguistically Diverse Childcare Classrooms

This short‐term longitudinal study examined changes over time in social competence with peers as a function of child and classroom characteristics. One hundred and seventy ethnically diverse low‐income children, all new to their peer groups, entered childcare classrooms with heterogeneous entry policies and ethnic/racial compositions. We observed them with their teachers and peers at entry and again six months later. Observers rated aggressive, anxious/withdrawn, and prosocial behavior with peers and observed complexity of peer play. Children who lacked peers with a shared ethnic heritage and children who spoke a different language at home than the language most often used in the classrooms appeared to be struggling with peer interaction six months after entry into the peer group. Children who had a peer who shared their ethnic heritage and entered the most ethnically diverse classrooms increased their complex peer play more than other children.     

The efficacy of using judgmental versus quantitative forecasting methods in practice

In an era where forecasts drive entire supply chains forecasting is seen as an increasingly critical organizational capability. However, business forecasting continues to rely on judgmental methods despite large advancements in information technology and quantitative method capability, prompting calls for research to help understand the reasons behind this practice. Our study is designed to contribute to this knowledge by profiling differences between firms identified as primary users of either judgmental or quantitative forecasting methods. Relying on survey data from 240 firms we statistically analyzed differences between these categories of users based on a range of organizational and forecasting issues. Our study finds large differences in forecast error rates between the two groups, with users of quantitative methods significantly outperforming users of judgmental methods. The former are found to be equally prevalent regardless of industry, firm size, and product positioning strategy, documenting the benefits of quantitative method use in a variety of settings. By contrast, the latter are found to have significantly lower access to quantifiable data and to use information and technology to a lesser degree.     

‘Democracy always comes first’: adolescents’ views on decision-making in everyday life and political democracy

Research shows adolescents to be positively oriented towards democracy, but little is known about what it actually means to them and what their views are on decision-making in both everyday situations and political democracy. To gain insight into these aspects of adolescents’ democratic views, we have interviewed 40 Dutch adolescents from second grade of different types of high school. Potential conflict between various democratic principles prevalent in everyday life situations was discussed and compared to how they view decision-making in political democracy. The results of our qualitative study showed that adolescents’ views on issues concerning collective decision-making in everyday situations are quite rich and reflect different models of democracy (majoritarian, consensual, and deliberative). Moreover, how adolescents deal with tensions between democratic principles in everyday life situations varies. While some adolescents combine several principles (for instance, majority rule as a last resort after trying to find broader consensus), other adolescents tend to strictly focus on only one of these principles. Adolescents’ views on political democracy, however, are rather limited and one-dimensional. Those adolescents who seemed to have a more explicit picture of political democracy often preferred a strict focus on majority rule, neglecting minority interests.