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Objectives: Longitudinal mediation effects can be estimated with mixed effects models. Mixed effects models are versatile, as they accommodate the estimation of contemporaneous, lagged, time-independent, and time-dependent effects. However, the inclusion of time lags and time interactions in mixed effects models for longitudinal mediation analysis has received little attention. This article demonstrates how time lags and time interactions in mixed effects models affect the interpretation of longitudinal mediation effect estimates. Study Design and Setting: We used a data example from the Amsterdam Growth and Health Longitudinal Study to illustrate how the inclusion of time lags and time interactions in mixed effects models may affect the size and interpretation of longitudinal mediation effect estimates. Results: The chosen time lags between the determinant, mediator, and outcome influenced the size and interpretation of the mediation effect estimates. Furthermore, time interactions can be used to model linear or nonlinear development of the mediation effects over time. Conclusion: The inclusion of time lags and time interactions should be considered when estimating longitudinal mediation effects based on mixed effects models, as this enables the estimation of lagged and time-dependent effects.

Additional file 1.

Additional file 6. Observer OPTIONMCC scores with and without use of patient preparatory tool (intervention group).

Additional file 4. Baseline characteristics informal caregivers.

Additional file 4.

Additional file 7. Observer OPTIONMCC scores for geriatricians, patients and informal caregivers (subgroup analysis of eight geriatricians).

Additional file 3. Adapted control preference scale.

Additional file 1. Patient preparatory tool.

Additional file 5. Evaluation of use of the patient preparatory tool in the intervention group (n = 108).

Additional file 3.

Additional file 5.

Additional file 2.

Because missing data are present in almost every study, it is important to handle missing data properly. First of all, the missing data mechanism should be considered. Missing data can be either completely at random (MCAR), at random (MAR), or not at random (MNAR). When missing data are MCAR, a complete case analysis can be valid. Also when missing data are MAR, in some situations a complete case analysis leads to valid results. However, in most situations, missing data imputation should be used. Regarding imputation methods, it is highly advised to use multiple imputations because multiple imputations lead to valid estimates including the uncertainty about the imputed values. When missing data are MNAR, also multiple imputations do not lead to valid results. A complication hereby is that it not possible to distinguish whether missing data are MAR or MNAR. Finally, it should be realized that preventing to have missing data is always better than the treatment of missing data.

Supplemental material, sj-docx-4-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Additional file 1. Hypothetical data example to illustrate the noncollapsibility effect.

Supplemental material, sj-docx-1-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Supplemental material, sj-docx-1-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Supplemental material, sj-docx-3-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Additional file 3: Supplementary appendix 3. List of papers included in the scoping review.

Supplemental material, sj-docx-3-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Supplemental material, sj-docx-2-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Supplemental material, sj-docx-4-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Additional file 1: Supplementary appendix 1. PRISMA-ScR checklist.

Supplemental material, sj-docx-2-heb-10.1177_10901981211046533 for How to Evaluate the Effectiveness of Health Promotion Actions Developed Through Youth-Centered Participatory Action Research by Manou Anselma, Teatske M. Altenburg, Jos W. R. Twisk, dr. Xinhui Wang and Mai J. M. Chinapaw in Health Education & Behavior

Supplemental material, Supplementary_Material for Is Resting-State EEG Longitudinally Associated With Recovery of Clinical Neurological Impairments Early Poststroke? A Prospective Cohort Study by Mique Saes, Sarah B. Zandvliet, Aukje S. Andringa, Andreas Daffertshofer, Jos W. R. Twisk, Carel G. M. Meskers, Erwin E. H. van Wegen and Gert Kwakkel in Neurorehabilitation and Neural Repair

Additional file 1. Cognitive Failure Questionnaire (CFQ).

Aim This study aimed to determine the developmental trajectories of social participation, by level of gross motor function and intellectual disability, in a Dutch population of individuals with cerebral palsy (CP) aged 1 to 24 years. Method As part of the Pediatric Rehabilitation Research in the Netherlands (PERRIN+), 424 individuals with CP (261 males, 163 females; mean age [SD] 9y 6mo [6y 2mo]; Gross Motor Function Classification [GMFCS] levels I–V [50% level I]; 87% with spastic CP; 26% with intellectual disability) were longitudinally followed for up to 4 years between 2002 and 2007. Social participation was assessed with the Vineland Adaptive Behavior Scales survey. Effects of age, GMFCS level and intellectual disability were analysed using multilevel modelling. Results The developmental trajectories for individuals in GMFCS levels I to IV did not significantly differ from each other. For individuals without intellectual disability, the degree of social participation increased with age and stabilized at about 18 years. These individuals reached social participation levels similar to typically developing individuals. The trajectories were significantly less favourable for individuals in GMFCS level V and individuals with intellectual disability. Interpretation Intellectual disability is more distinctive for the development of social participation than GMFCS level. The developmental trajectories will support individuals with CP and their families in setting realistic goals and professionals in optimizing the choice of interventions at an early age.

The Amsterdam Growth and Health Longitudinal Study (AGHLS) is a unique, multidisciplinary cohortstudy that was initially set up to examine growth and health among teenagers. Throughout the years, the AGHLS has aimed to answer research questions dealing with the relationships between the (natural) development of anthropometry, lifestyle and health from adolescence into adulthood. The AGHLS specifically focuses on anthropometrics, physical activity and fitness, cardiovascular disease risk, lifestyle, musculoskeletal health, psychological health and well-being. Besides this, many methodological issues related to the analysis of longitudinal data were also explored within the framework of the AGHLS. In 1976, students from two secondary schools from the greater Amsterdam area were included in the study. Between 1976 and 2006, 10 rounds of measurement were performed covering an age range between 13 and 43 years. The huge database collected so far has been primarily used to answer relevant research questions regarding the longitudinal relationship between lifestyle and health. Further informationabout the study can be obtained from the principal investigator Jos Twisk (jwr.twisk@vumc.nl), and up-to-date information on AGHLS can be found by visiting the website www.aggo.nl. © The Author 2012; all rights reserved.