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Parenting programs are effective for children with externalizing problems, but not always easily accessible for parents. In order to facilitate accessibility, we developed a self-help parenting program, consisting of a manual and online part. The efficacy of the program in reducing children's externalizing problems was compared to waitlist in a randomized controlled trial. In addition, two versions of the program were exploratively compared, one with and one without biweekly telephonic support. Candidate moderators (child and parent factors) and parental satisfaction were also examined. We randomly assigned 110 families to one of the following three conditions: the support condition, the no support condition, or the waitlist condition. Intervention duration was 15 weeks. Outcomes were collected at baseline (T0), 8 weeks (T1), 15 weeks (T2), and 28 weeks (T3) and included daily telephonic measurements of parent-rated externalizing behavior and the Intensity scale of the parent-rated Eyberg Child Behavior Inventory (ECBI). Main analyses compared outcomes at T2, using longitudinal regressions with T0 as fixed factor. Results showed that children improved significantly more on both outcomes in the intervention condition compared to waitlist, with small to medium effect sizes. Parental satisfaction was high. Neither differences in efficacy nor in parental satisfaction were found between the support and no support condition. No moderators were detected. The newly developed self-help parenting program is effective in reducing children's externalizing behavior problems and may help improve access to evidence-based care. [ABSTRACT FROM AUTHOR]

Background: Confounding is a common issue in epidemiological research. Commonly used confounder-adjustment methods include multivariable regression analysis and propensity score methods. Although it is common practice to assess the linearity assumption for the exposure-outcome effect, most researchers do not assess linearity of the relationship between the confounder and the exposure and between the confounder and the outcome before adjusting for the confounder in the analysis. Failing to take the true non-linear functional form of the confounder-exposure and confounder-outcome associations into account may result in an under- or overestimation of the true exposure effect. Therefore, this paper aims to demonstrate the importance of assessing the linearity assumption for confounder-exposure and confounder-outcome associations and the importance of correctly specifying these associations when the linearity assumption is violated. Methods: A Monte Carlo simulation study was used to assess and compare the performance of confounder-adjustment methods when the functional form of the confounder-exposure and confounder-outcome associations were misspecified (i.e., linearity was wrongly assumed) and correctly specified (i.e., linearity was rightly assumed) under multiple sample sizes. An empirical data example was used to illustrate that the misspecification of confounder-exposure and confounder-outcome associations leads to bias. Results: The simulation study illustrated that the exposure effect estimate will be biased when for propensity score (PS) methods the confounder-exposure association is misspecified. For methods in which the outcome is regressed on the confounder or the PS, the exposure effect estimate will be biased if the confounder-outcome association is misspecified. In the empirical data example, correct specification of the confounder-exposure and confounder-outcome associations resulted in smaller exposure effect estimates. Conclusion: When attempting to remove bias by adjusting for confounding, misspecification of the confounder-exposure and confounder-outcome associations might actually introduce bias. It is therefore important that researchers not only assess the linearity of the exposure-outcome effect, but also of the confounder-exposure or confounder-outcome associations depending on the confounder-adjustment method used. [ABSTRACT FROM AUTHOR]

Background: Confounding bias is a common concern in epidemiological research. Its presence is often determined by comparing exposure effects between univariable- and multivariable regression models, using an arbitrary threshold of a 10% difference to indicate confounding bias. However, many clinical researchers are not aware that the use of this change-in-estimate criterion may lead to wrong conclusions when applied to logistic regression coefficients. This is due to a statistical phenomenon called noncollapsibility, which manifests itself in logistic regression models. This paper aims to clarify the role of noncollapsibility in logistic regression and to provide guidance in determining the presence of confounding bias.Methods: A Monte Carlo simulation study was designed to uncover patterns of confounding bias and noncollapsibility effects in logistic regression. An empirical data example was used to illustrate the inability of the change-in-estimate criterion to distinguish confounding bias from noncollapsibility effects.Results: The simulation study showed that, depending on the sign and magnitude of the confounding bias and the noncollapsibility effect, the difference between the effect estimates from univariable- and multivariable regression models may underestimate or overestimate the magnitude of the confounding bias. Because of the noncollapsibility effect, multivariable regression analysis and inverse probability weighting provided different but valid estimates of the confounder-adjusted exposure effect. In our data example, confounding bias was underestimated by the change in estimate due to the presence of a noncollapsibility effect.Conclusion: In logistic regression, the difference between the univariable- and multivariable effect estimate might not only reflect confounding bias but also a noncollapsibility effect. Ideally, the set of confounders is determined at the study design phase and based on subject matter knowledge. To quantify confounding bias, one could compare the unadjusted exposure effect estimate and the estimate from an inverse probability weighted model. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effects of Shared Decision-Making (SDM) using Routine Outcome Monitoring (ROM) primary on patients' perception of Decisional Conflict (DC), which measures patients' engagement in and satisfaction with clinical decisions, and secondary on working alliance and treatment outcomes.Method: Multi-centre two-arm matched-paired cluster randomised-controlled trial in Dutch specialist mental health care. SDM using ROM (SDMR) was compared with Decision-Making As Usual (DMAU). Outcomes were measured at baseline (T0) and 6 months (T1). Multilevel regression and intention-to-treat analyses were used. Post hoc analyses were performed on influence of subgroups and application of SDMR on DC.Results: Seven teams were randomised to each arm. T0 was completed by 186 patients (51% intervention; 49% control) and T1 by 158 patients (51% intervention, 49% control). DC, working alliance, and treatment outcomes reported by patients did not differ significantly between two arms. Post hoc analyses revealed that SDMR led to less DC among depressed patients (p = 0.047, d =- 0.69). If SDMR was applied well, patients reported less DC (SDM: p = 0.000, d = - 0.45; ROM: p = 0.021, d = - 0.32), which was associated with better treatment outcomes.Conclusion: Except for patients with mood disorders, we found no difference between the arms for patient-reported DC. This might be explained by the less than optimal uptake of this generic intervention, which did not support patients directly. Regarding the positive influence of a higher level of applying SDM and ROM on less DC and better treatment outcomes, the results are encouraging for further investments in patient-oriented development and implementation of SDMR. [ABSTRACT FROM AUTHOR]

Previous studies showed that missing data in multi-item scales can best be handled by multiple imputation of item scores. However, when many scales are used, the number of items will become too large for the imputation model to reliably estimate imputations. A solution is to use passive imputation or a parcel summary score that combine and consequently reduce the number of variables in the imputation model. The performance of these methods was evaluated in a simulation study and illustrated in an example. Passive imputation, which updated scale scores from imputed items, and parcel summary scores that use the average over available item scores were compared to using all items simultaneously, imputing total scores of scales and complete-case analysis. Scale scores and coefficient estimates from linear regression were compared to "true" parameters on bias and precision. Passive imputation and using parcel summaries showed smaller bias and more precision than imputing total scores and complete-case analyses. Passive imputation or using parcel summary scores are valid missing data solutions in studies that include many multi-item scales. [ABSTRACT FROM AUTHOR]

This study intended to investigate the capability of the 4 test items “sprint”, “agility”, “speed while dribbling” and “throwing a ball” of the Dutch perceptuo-motor skills assessment used at the age of 7–10 years to predict table tennis performance (U13, U15 and U18) in an observational study. Data of 1191 young table tennis players, collected from 1998 to 2013, were analysed in univariable and multivariable logistic and linear regression models. The test items “sprint” and “throwing a ball” showed to be significant predictors for table tennis performance outcomes in boys (P < 0.05). For girls, besides these test items also “speed while dribbling” had a significant contribution (P < 0.05). Since the accuracies of the models were low, it is advised to include other determinants to enhance the predictive value of a model for table tennis performance. Nevertheless, it can be concluded that a perceptuo-motor skills assessment might improve the effectiveness of talent programmes in table tennis as an additional method to objectively estimate a youth players’ potential. Future research focusing on the inclusion of test items specifically assessing eye hand coordination and other domains, for example, the psychological and the environmental domain, related to table tennis performance are recommended. [ABSTRACT FROM AUTHOR]

Purpose:In this manuscript, we evaluated the effectiveness of an intervention programme consisting of integrated care and a participatory workplace intervention on supervisor support, work instability and at-work productivity after 6 months of follow-up among workers with rheumatoid arthritis (RA). Methods:We conducted a randomized controlled trial; we compared the intervention programme to usual care. Eligible patients were diagnosed with RA, had a paid job (> 8 h per week) and who experienced, at least, minor difficulties in work functioning. Supervisor support was measured with a subscale of the Job Content Questionnaire, work instability with the Work Instability Scale for RA, and at-work productivity with the Work Limitations Questionnaire. Data were analyzed using linear regression analyses. Results:A beneficial effect of the intervention programme was found on supervisor support among 150 patients. Analyses revealed no effects on work instability and at-work productivity. Conclusion:We found a small positive effect of the intervention on supervisor support, but did not find any effects on work instability and at-work productivity loss. Future research should establish whether this significant but small increase in supervisor support leads to improved work functioning in the long run. This study shows clinicians that patients with RA are in need of efforts to support them in their work functioning.Implications for RehabilitationRheumatoid arthritis (RA) is a chronic inflammatory disease with a severe impact on work functioning, even when a patient is still working.It is important to involve the workplace when an intervention is put in place to support RA patients in their work participation.Supervisor support influences health outcomes of workers, and it is possible to improve supervisor support by an intervention which involves the workplace and supervisor. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to examine the association of birth weight and infant growth with childhood autonomic nervous system (ANS) activity and to assess whether ANS activity mediates the associations of birth weight and infant growth with energy-balance-related behaviours, including energy intake, satiety response, physical activity and screen time.Methods: In 2089 children, we prospectively collected birth weight, infant growth defined as conditional weight and height gain between birth and 12 months and-at 5 years-indices of cardiac ANS activity and parent-reported energy-balance-related behaviours. A mediation analysis was conducted, based on MacKinnon's multivariate extension of the product-of-coefficients strategy.Results: Birth weight and infant height gain were inversely associated with sympathetic, but not parasympathetic, activity at age 5. Infant weight gain was not associated with childhood ANS activity. Infant weight gain was predictive of increased childhood screen time and infant height gain of diminished childhood energy intake, but sympathetic activity did not mediate these associations.Conclusions: Low-birth-weight children have higher sympathetic activity, which is considered a risk factor for cardiovascular disease. Height gain in infancy seems to be beneficial for childhood sympathetic activity. However, sympathetic activity was no mediator of the associations of infant growth with childhood energy-balance-related behaviours. As individual differences in ANS activity predict increased risk of cardiovascular disease, these differences may offer insight into the early-life origins of chronic diseases and provide further basis for public health strategies to optimize birth weight and infant growth. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to examine the longitudinal associations of person-related factors with physical activity (PA) behavior in young adults. Methods: We analyzed longitudinal self-reported time spent in moderate-intensity PA (MPA; 4-7 METs) and vigorous-intensity PA (VPA; >7 METs) from 499 young adults (49% male) who participated in the Amsterdam Growth and Health Longitudinal Study at the age of 21, 27, 32, and 36 yr. Sociodemographic factors (i.e., marital and employment status), physical factors (i.e., skinfolds, aerobic fitness, neuromotor fitness, back problems, and general health status), psychological factors (i.e., problem and emotion focused coping, mild health complaints, and personality), and behavioral factors (i.e., alcohol consumption, smoking, and energy intake) were assessed at each time point. We performed sex-specific univariable and multivariable generalized estimating equations. Results: Men and women with higher aerobic fitness were more moderately and vigorously active. Not having paid work was associated with more MPA in both men and women. Men with part-time paid work, lower scores on dominance, higher scores on hostility, and above moderate alcohol consumption (i.e., ≥140 g of alcohol per week) were more moderately active. Divorced women and those with better physical flexibility spent more time in MPA. Men having full-time paid work, with a good general health status and nonsmokers, were more vigorously active. Women being married/living together, who had better physical flexibility, lower scores on inadequacy, higher scores on dominance, and low caloric intake (around 2000 kcal•d-1) were more vigorously active. Conclusion: Several sociodemographic, physical, psychological, and behavioral factors were associated with PA in Dutch young adults. Determinants were different for MPA and VPA and for men and women. [ABSTRACT FROM AUTHOR]

Background: Within longitudinal epidemiological research, 'count' outcome variables with an excess of zeros frequently occur. Although these outcomes are frequently analysed with a linear mixed model, or a Poisson mixed model, a two-part mixed model would be better in analysing outcome variables with an excess of zeros. Therefore, objective of this paper was to introduce the relatively 'new' method of two-part joint regression modelling in longitudinal data analysis for outcome variables with an excess of zeros, and to compare the performance of this method to current approaches. Methods: Within an observational longitudinal dataset, we compared three techniques; two 'standard' approaches (a linear mixed model, and a Poisson mixed model), and a two-part joint mixed model (a binomial/Poisson mixed distribution model), including random intercepts and random slopes. Model fit indicators, and differences between predicted and observed values were used for comparisons. The analyses were performed with STATA using the GLLAMM procedure. Results: Regarding the random intercept models, the two-part joint mixed model (binomial/Poisson) performed best. Adding random slopes for time to the models changed the sign of the regression coefficient for both the Poisson mixed model and the two-part joint mixed model (binomial/Poisson) and resulted into a much better fit. Conclusion: This paper showed that a two-part joint mixed model is a more appropriate method to analyse longitudinal data with an excess of zeros compared to a linear mixed model and a Poisson mixed model. However, in a model with random slopes for time a Poisson mixed model also performed remarkably well. [ABSTRACT FROM AUTHOR]

Background: The essential amino acid methionine can be used for protein synthesis but also serves as a precursor for homocysteine and cysteine. Objective: The objective of this study was to determine the minimal obligatory methionine requirement of infants in the presence of excess cysteine (91 mg · kg-1 · d -1) by using the indicator amino acid oxidation (IAAO) method with L-[1 -13C]phenylalanine as the indicator. Design: Fully enterally fed term infants < 1 mo of age were randomly assigned to methionine intakes that ranged from 3 to 59 mg • kg-1 · d-1 as part of an elemental formula. After 1 d of adaptation to the test diet, [l3C]bicarbonate and L-[1-13C]phenylalanine tracers were given enterally. Breath samples were collected at baseline and during isotopic plateaus. The mean methionine requirement was determined by using biphasic linear regression crossover analysis on the fraction of 13CO2 recovery from L-[1-13C]phenylalanine oxidation (F13CO2). Data are presented as means ± SDs. Results: Thirty-three neonates (gestational age: 39 ± 1 wk) were studied at 13 ± 6 d. With increasing methionine intakes, F13CO2 decreased until a methionine intake of 38 mg • kg~' · d-1; additional increases in methionine intake did not affect FI3CO2. The mean methionine requirement was determined at 38 mg • kg-1 • d-1, and the upper and lower CIs were 48 and 27 mg • kg-1 • d-1, respectively (P < 0.0001, r = 0.59). Conclusions: Although the current recommended methionine intake of 28 mg • kg-1 • d-1 is within the CIs of our study, the estimated mean requirement is substantially higher. However, most of the infant formulas provide a methionine intake of 49-80 mg · kg-1 • d-1, which is above the upper CI of our study. This trial was registered at www.trialregister.nl as NTR1610. [ABSTRACT FROM AUTHOR]

Musculoskeletal complaints (MSC) are common among children, often persist into adolescence, and increase the risk of MSC in adulthood. Knowledge regarding determinants of MSC among children is limited. The aim of this study was to determine the prevalence of MSC at age 11 years and to examine associations with sociodemographic factors, growth and development factors, mental health, tiredness, and lifestyle. Data from a Netherlands birth cohort study, the Prevention and Incidence of Asthma and Mite Allergy (PIAMA) Study (n = 2,638), were used (1996–2009). MSC were defined as complaints about the back, an upper extremity, a lower extremity, or any of these sites. Logistic regression analyses using a forward stepwise procedure were performed on multiply imputed data. The 1-year period prevalences of back, upper extremity, and lower extremity complaints that lasted at least 1 month were 2.8%, 4.8%, and 10.9%, respectively. Only poorer mental health was consistently associated with all 3 types of complaints. Poorer mental health, daytime tiredness, early pubertal development, being physically active at age 11 years, and weight-for-height z score were associated with having any MSC. This study showed that MSC, especially lower extremity complaints, are common among 11-year old-children and that only poorer mental health status is associated with MSC at all anatomic sites. [ABSTRACT FROM PUBLISHER]

Objectives. To examine the relationships between exposure to the air disaster in Amsterdam and multiple physical symptoms among firefighters and police officers, and to explore the role of post-traumatic stress symptoms (PTSS) herein. Design. Historic cohort study. Methods. On average 8.5 years post-disaster, exposed professional firefighters (N = 334) and police officers (N = 834) and their nonexposed colleagues (N = 194 and N = 634, respectively) completed questionnaires on disaster exposure and current symptoms. Logistic regression with adjustment for background characteristics was used to compare exposed and nonexposed workers. PTSS were added to these models, as was the interaction between exposure and PTSS, to explore potential mediating and modifying effects, respectively. Results. Exposed workers reported multiple physical symptoms significantly more often. Multiple physical symptoms seemed to have particularly affected the exposed firefighters who rescued people, and the exposed police officers who supported injured victims and workers, who were involved in the identification of or search for victims and human remains, who witnessed the immediate disaster scene or had a close one affected by the disaster. These exposure effects were essentially independent of PTSS, and no significant interactions between exposure and PTSS were found. Conclusions. In conclusion, the excess in post-disaster multiple physical symptoms in exposed workers could not be attributed to PTSS. [ABSTRACT FROM AUTHOR]

Objectives: Regardless of the proportion of missing values, complete-case analysis is most frequently applied, although advanced techniques such as multiple imputation (MI) are available. The objective of this study was to explore the performance of simple and more advanced methods for handling missing data in cases when some, many, or all item scores are missing in a multi-item instrument. Study Design and Setting: Real-life missing data situations were simulated in a multi-item variable used as a covariate in a linear regression model. Various missing data mechanisms were simulated with an increasing percentage of missing data. Subsequently, several techniques to handle missing data were applied to decide on the most optimal technique for each scenario. Fitted regression coefficients were compared using the bias and coverage as performance parameters Results: Mean imputation caused biased estimates in every missing data scenario when data are missing for more than 10% of the subjects. Furthermore, when a large percentage of subjects had missing items (>25%), MI methods applied to the items outperformed methods applied to the total score. Conclusion: We recommend applying MI to the item scores to get the most accurate regression model estimates. Moreover, we advise not to use any form of mean imputation to handle missing data. [ABSTRACT FROM AUTHOR]