models: Theory and application. In H.H. Bock (Ed.), Classification and related methods of data an... more models: Theory and application. In H.H. Bock (Ed.), Classification and related methods of data analysis (pp. 421-430). Amsterdam: North-Holland.
BackgroundStudies demonstrated that adolescent e-cigarette use is associated with subsequent toba... more BackgroundStudies demonstrated that adolescent e-cigarette use is associated with subsequent tobacco smoking, commonly referred to as thegateway effect. However, most studies only investigated gateways from e-cigarettes to tobacco smoking. This study replicates a cornerstone study revealing a positive association between both adolescent e-cigarette use and subsequent tobacco use; and tobacco and subsequent e-cigarette use in the Netherlands and Flanders.DesignThe longitudinal design included baseline (n=2839) and 6-month (n=1276) and 12-month (n=1025) follow-up surveys among a school-based cohort (mean age: 13.62). Ten high schools were recruited as a convenience sample. The analyses involved (1) associations of baseline e-cigarette use and subsequent tobacco smoking among never smokers; (2) associations of e-cigarette use frequency at baseline and tobacco smoking frequency at follow-up; and (3) the association of baseline tobacco smoking and subsequent e-cigarette use among non-use...
Computational and Mathematical Methods in Medicine, 2018
If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B)... more If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B) and extended parallel (AA/BB) group designs. This study extends these results in that (a) optimal instead of equal treatment allocation is examined, (b) allowance for treatment-dependent outcome variances is made, and (c) next to treatment effects, also treatment by period interaction effects are examined. Starting from a linear mixed model analysis, the optimal allocation requires knowledge on intraclass correlations in A and B, which typically is rather vague. To solve this, maximin versions of the designs are derived, which guarantee a power level across plausible ranges of the intraclass correlations at the lowest research costs. For the treatment effect, an extensive numerical evaluation shows that if the treatment costs of A and B are equal, or if the sum of the costs of one treatment and measurement per person is less than the remaining subject-specific costs (e.g., recruitment c...
Introduction Financial incentives effectively increase smoking cessation rates, but it is unclear... more Introduction Financial incentives effectively increase smoking cessation rates, but it is unclear via which psychological mechanisms incentives influence quit behavior. The current study examines how receiving financial incentives for smoking cessation leads to quitting smoking and investigates several mediators and moderators of that relationship. Aims and Methods The study sample consisted of 604 tobacco-smoking employees from 61 companies in the Netherlands who completed a baseline and follow-up questionnaire. The current study is a secondary analysis from a cluster randomized trial where employees received smoking cessation group counseling at the workplace. Participants in the intervention group additionally received financial incentives of €350 in total for 12-month continuous smoking abstinence. We used a two-level path analysis to test a model that assesses the effects of financial incentives through smoking cessation program evaluation, medication use, nicotine replacement ...
In multilevel populations, there are two types of population means of an outcome variable ie, the... more In multilevel populations, there are two types of population means of an outcome variable ie, the average of all individual outcomes ignoring cluster membership and the average of cluster‐specific means. To estimate the first mean, individuals can be sampled directly with simple random sampling or with two‐stage sampling (TSS), that is, sampling clusters first, and then individuals within the sampled clusters. When cluster size varies in the population, three TSS schemes can be considered, ie, sampling clusters with probability proportional to cluster size and then sampling the same number of individuals per cluster; sampling clusters with equal probability and then sampling the same percentage of individuals per cluster; and sampling clusters with equal probability and then sampling the same number of individuals per cluster. Unbiased estimation of the average of all individual outcomes is discussed under each sampling scheme assuming cluster size to be informative. Furthermore, th...
Background: Organ donation registration rates remain low, especially among people with lower educ... more Background: Organ donation registration rates remain low, especially among people with lower educational levels. An interactive educational intervention was developed to prepare lower-educated students in the Netherlands for making a well-informed decision about organ donation. This article reports on the effects of this intervention on the intention to register (i.e. the primary outcome in the study at hand) and beliefs regarding organ donation.Methods: The effectiveness was investigated in a post-test only cluster randomized controlled trial, in which the intervention was offered to the experimental group and after measurement also to the control group. Randomization to the experimental and control groups took place at a class level. Teachers of schools for intermediate vocational education who taught a course on Citizenship delivered three intervention elements (i.e. video fragments and discussion, quizzes with tailored feedback and exercise filling out a registration form) to th...
To estimate the mean of a quantitative variable in a hierarchical population, it is logistically ... more To estimate the mean of a quantitative variable in a hierarchical population, it is logistically convenient to sample in two stages (two-stage sampling), i.e. selecting first clusters, and then individuals from the sampled clusters. Allowing cluster size to vary in the population and to be related to the mean of the outcome variable of interest (informative cluster size), the following competing sampling designs are considered: sampling clusters with probability proportional to cluster size, and then the same number of individuals per cluster; drawing clusters with equal probability, and then the same percentage of individuals per cluster; and selecting clusters with equal probability, and then the same number of individuals per cluster. For each design, optimal sample sizes are derived under a budget constraint. The three optimal two-stage sampling designs are compared, in terms of efficiency, with each other and with simple random sampling of individuals. Sampling clusters with pr...
Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, w... more Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment‐dependent costs and treatment‐dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment‐to‐control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment‐dependent costs (cost‐considered design). The results show that the balanced design is the MMD if...
The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) ... more The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level costeffectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program SamP2CeT in R to perform these sample size calculations. SamP2CeT provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters, SamP2CeT also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy. SamP2CeT can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a userspecified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in SamP2CeT. This program is user-friendly, as illustrated for two published cost-effectiveness trials.
Repairing the efficiency loss due to varying cluster sizes in two-level two-armed randomized tria... more Repairing the efficiency loss due to varying cluster sizes in two-level two-armed randomized trials with heterogeneous clustering.
International Journal of Environmental Research and Public Health, 2019
In 2016, the Netherlands was required to introduce new European Union (EU)’s (pictorial) tobacco ... more In 2016, the Netherlands was required to introduce new European Union (EU)’s (pictorial) tobacco health warnings. Our objective was to describe the pathways through which the new EU tobacco health warnings may influence quit attempts and smoking cessation among Dutch smokers. Longitudinal data from 2016 and 2017 from the International Tobacco Control (ITC) Netherlands Survey were used. Smokers who participated in both surveys were included (N = 1017). Structural equation modeling was applied to examine the hypothesized pathways. Health warning salience was positively associated with more health worries (β = 0.301, p < 0.001) and a more positive attitude towards quitting (β = 0.180, p < 0.001), which, in turn, were associated with a stronger quit intention (health worries: β = 0.304, p < 0.001; attitude: β = 0.340, p < 0.001). Quit intention was a strong predictor of quit attempts (β = 0.336, p = 0.001). Health warning salience was also associated with stronger perceived ...
Previously, a Dutch randomized controlled trial evaluating an intervention aimed at changing adol... more Previously, a Dutch randomized controlled trial evaluating an intervention aimed at changing adolescents' cannabis use, called Moti-4, has shown its efficacy. A secondary analysis of the Moti-4 data investigated the process of change specified by the Stage of Change (SOC) model in cannabis use during the trial. Seventy-one Moti-4 participants and 60 controls were recruited for the study with a pre-test, post-test (T1), and six-month follow-up (T2). All participants showed signs of problematic cannabis use. No contribution of the Moti-4 intervention to a change in SOC between T1 and T2 was found. Although motivation for treatment and motivation for change can be conceived as independent predictors of treatment outcome, the SOC a person is in does not mediate the effect of the intervention on change in cannabis use. However, a reduction in cannabis use was associated with a positive change in "action willingness," in line with the SOC model. In contrast to model expectat...
Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, Jan 3, 2017
The aim of the study was to compare the construct validity and the predictive validity of three i... more The aim of the study was to compare the construct validity and the predictive validity of three instruments to measure intention to quit smoking: a Stages of Change measure, the Motivation To Stop Scale (MTSS) and a Likert scale. We used the Theory of Planned Behaviour as theoretical framework. We used data from the International Tobacco Control (ITC) Netherlands Survey. We included smokers who participated in three consecutive survey waves (n=980). We measured attitude, subjective norm, and perceived behavioural control in 2012, intention to quit with three instruments in 2013, and having made a quit attempt in the last year in 2014. We conducted Structural Equation Modelling with three models for the instruments of intention separately, and with one model that included the three instruments simultaneously. All three instruments of intention were significantly and positively related to attitude and perceived behavioural control but none was related to subjective norm. All three ins...
When national pharmacoeconomic guidelines are compared, different recommendations are identified ... more When national pharmacoeconomic guidelines are compared, different recommendations are identified on how to identify, measure and value lost productivity, leading to difficulties when comparing lost productivity estimates across countries. From a transferability point of view, the question arises of whether differences between countries regarding lost productivity are the result of using different calculation methods (methodological differences) or of other between-country differences. When lost productivity data differ significantly across countries, the transferability of lost productivity data across countries is hindered. The objective of this study was to investigate whether country of residence has a significant influence on the quantity of lost productivity among patients with rheumatic disorders. Confounding factors that might differ between countries were corrected for, while the methodology used to identify and measure lost productivity was kept the same. This question was investigated by means of an online questionnaire filled out by 200 respondents with a rheumatic disorder per country in four European countries, namely the Netherlands, the UK, Germany and France. In addition to those regarding lost productivity, the questionnaire contained questions about patient characteristics, disability insurance, disease characteristics, quality of life and job characteristics as these variables are expected to influence lost productivity in terms of absenteeism and presenteeism. The data were analysed by regression analyses, in which different components - being absent in last 3 months, number of days absent and presenteeism - of lost productivity were the main outcome measures and other variables, such as gender, impact of disease, shift work, job control, partial disability and overall general health, were corrected for. The results showed that country sometimes has a significant influence on lost productivity and that other variables such as, for example, age, disease severity, number of contract hours, decision latitude, experienced health (as reported on the visual analogue scale) and partial disability, also influence lost productivity. A significant influence of country of residence was found on the variables &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;being absent in the last three months&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;, &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;number of days absent&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;quality of work on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;. However, country did not influence &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;quantity of work on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;overall presenteeism on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;. It can be concluded that country has a significant influence on lost productivity among patients with rheumatic disorders, when corrected for other variables that have an influence on absenteeism and presenteeism. Transferring lost productivity data across countries without adaptation is hindered by the significant differences between countries in this patient group. As a result, transferring lost productivity data, being either monetary values or volumes of productivity losses, between countries can give wrong estimations of the cost effectiveness of treatments.
models: Theory and application. In H.H. Bock (Ed.), Classification and related methods of data an... more models: Theory and application. In H.H. Bock (Ed.), Classification and related methods of data analysis (pp. 421-430). Amsterdam: North-Holland.
BackgroundStudies demonstrated that adolescent e-cigarette use is associated with subsequent toba... more BackgroundStudies demonstrated that adolescent e-cigarette use is associated with subsequent tobacco smoking, commonly referred to as thegateway effect. However, most studies only investigated gateways from e-cigarettes to tobacco smoking. This study replicates a cornerstone study revealing a positive association between both adolescent e-cigarette use and subsequent tobacco use; and tobacco and subsequent e-cigarette use in the Netherlands and Flanders.DesignThe longitudinal design included baseline (n=2839) and 6-month (n=1276) and 12-month (n=1025) follow-up surveys among a school-based cohort (mean age: 13.62). Ten high schools were recruited as a convenience sample. The analyses involved (1) associations of baseline e-cigarette use and subsequent tobacco smoking among never smokers; (2) associations of e-cigarette use frequency at baseline and tobacco smoking frequency at follow-up; and (3) the association of baseline tobacco smoking and subsequent e-cigarette use among non-use...
Computational and Mathematical Methods in Medicine, 2018
If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B)... more If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B) and extended parallel (AA/BB) group designs. This study extends these results in that (a) optimal instead of equal treatment allocation is examined, (b) allowance for treatment-dependent outcome variances is made, and (c) next to treatment effects, also treatment by period interaction effects are examined. Starting from a linear mixed model analysis, the optimal allocation requires knowledge on intraclass correlations in A and B, which typically is rather vague. To solve this, maximin versions of the designs are derived, which guarantee a power level across plausible ranges of the intraclass correlations at the lowest research costs. For the treatment effect, an extensive numerical evaluation shows that if the treatment costs of A and B are equal, or if the sum of the costs of one treatment and measurement per person is less than the remaining subject-specific costs (e.g., recruitment c...
Introduction Financial incentives effectively increase smoking cessation rates, but it is unclear... more Introduction Financial incentives effectively increase smoking cessation rates, but it is unclear via which psychological mechanisms incentives influence quit behavior. The current study examines how receiving financial incentives for smoking cessation leads to quitting smoking and investigates several mediators and moderators of that relationship. Aims and Methods The study sample consisted of 604 tobacco-smoking employees from 61 companies in the Netherlands who completed a baseline and follow-up questionnaire. The current study is a secondary analysis from a cluster randomized trial where employees received smoking cessation group counseling at the workplace. Participants in the intervention group additionally received financial incentives of €350 in total for 12-month continuous smoking abstinence. We used a two-level path analysis to test a model that assesses the effects of financial incentives through smoking cessation program evaluation, medication use, nicotine replacement ...
In multilevel populations, there are two types of population means of an outcome variable ie, the... more In multilevel populations, there are two types of population means of an outcome variable ie, the average of all individual outcomes ignoring cluster membership and the average of cluster‐specific means. To estimate the first mean, individuals can be sampled directly with simple random sampling or with two‐stage sampling (TSS), that is, sampling clusters first, and then individuals within the sampled clusters. When cluster size varies in the population, three TSS schemes can be considered, ie, sampling clusters with probability proportional to cluster size and then sampling the same number of individuals per cluster; sampling clusters with equal probability and then sampling the same percentage of individuals per cluster; and sampling clusters with equal probability and then sampling the same number of individuals per cluster. Unbiased estimation of the average of all individual outcomes is discussed under each sampling scheme assuming cluster size to be informative. Furthermore, th...
Background: Organ donation registration rates remain low, especially among people with lower educ... more Background: Organ donation registration rates remain low, especially among people with lower educational levels. An interactive educational intervention was developed to prepare lower-educated students in the Netherlands for making a well-informed decision about organ donation. This article reports on the effects of this intervention on the intention to register (i.e. the primary outcome in the study at hand) and beliefs regarding organ donation.Methods: The effectiveness was investigated in a post-test only cluster randomized controlled trial, in which the intervention was offered to the experimental group and after measurement also to the control group. Randomization to the experimental and control groups took place at a class level. Teachers of schools for intermediate vocational education who taught a course on Citizenship delivered three intervention elements (i.e. video fragments and discussion, quizzes with tailored feedback and exercise filling out a registration form) to th...
To estimate the mean of a quantitative variable in a hierarchical population, it is logistically ... more To estimate the mean of a quantitative variable in a hierarchical population, it is logistically convenient to sample in two stages (two-stage sampling), i.e. selecting first clusters, and then individuals from the sampled clusters. Allowing cluster size to vary in the population and to be related to the mean of the outcome variable of interest (informative cluster size), the following competing sampling designs are considered: sampling clusters with probability proportional to cluster size, and then the same number of individuals per cluster; drawing clusters with equal probability, and then the same percentage of individuals per cluster; and selecting clusters with equal probability, and then the same number of individuals per cluster. For each design, optimal sample sizes are derived under a budget constraint. The three optimal two-stage sampling designs are compared, in terms of efficiency, with each other and with simple random sampling of individuals. Sampling clusters with pr...
Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, w... more Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment‐dependent costs and treatment‐dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment‐to‐control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment‐dependent costs (cost‐considered design). The results show that the balanced design is the MMD if...
The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) ... more The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level costeffectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program SamP2CeT in R to perform these sample size calculations. SamP2CeT provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters, SamP2CeT also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy. SamP2CeT can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a userspecified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in SamP2CeT. This program is user-friendly, as illustrated for two published cost-effectiveness trials.
Repairing the efficiency loss due to varying cluster sizes in two-level two-armed randomized tria... more Repairing the efficiency loss due to varying cluster sizes in two-level two-armed randomized trials with heterogeneous clustering.
International Journal of Environmental Research and Public Health, 2019
In 2016, the Netherlands was required to introduce new European Union (EU)’s (pictorial) tobacco ... more In 2016, the Netherlands was required to introduce new European Union (EU)’s (pictorial) tobacco health warnings. Our objective was to describe the pathways through which the new EU tobacco health warnings may influence quit attempts and smoking cessation among Dutch smokers. Longitudinal data from 2016 and 2017 from the International Tobacco Control (ITC) Netherlands Survey were used. Smokers who participated in both surveys were included (N = 1017). Structural equation modeling was applied to examine the hypothesized pathways. Health warning salience was positively associated with more health worries (β = 0.301, p < 0.001) and a more positive attitude towards quitting (β = 0.180, p < 0.001), which, in turn, were associated with a stronger quit intention (health worries: β = 0.304, p < 0.001; attitude: β = 0.340, p < 0.001). Quit intention was a strong predictor of quit attempts (β = 0.336, p = 0.001). Health warning salience was also associated with stronger perceived ...
Previously, a Dutch randomized controlled trial evaluating an intervention aimed at changing adol... more Previously, a Dutch randomized controlled trial evaluating an intervention aimed at changing adolescents' cannabis use, called Moti-4, has shown its efficacy. A secondary analysis of the Moti-4 data investigated the process of change specified by the Stage of Change (SOC) model in cannabis use during the trial. Seventy-one Moti-4 participants and 60 controls were recruited for the study with a pre-test, post-test (T1), and six-month follow-up (T2). All participants showed signs of problematic cannabis use. No contribution of the Moti-4 intervention to a change in SOC between T1 and T2 was found. Although motivation for treatment and motivation for change can be conceived as independent predictors of treatment outcome, the SOC a person is in does not mediate the effect of the intervention on change in cannabis use. However, a reduction in cannabis use was associated with a positive change in "action willingness," in line with the SOC model. In contrast to model expectat...
Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, Jan 3, 2017
The aim of the study was to compare the construct validity and the predictive validity of three i... more The aim of the study was to compare the construct validity and the predictive validity of three instruments to measure intention to quit smoking: a Stages of Change measure, the Motivation To Stop Scale (MTSS) and a Likert scale. We used the Theory of Planned Behaviour as theoretical framework. We used data from the International Tobacco Control (ITC) Netherlands Survey. We included smokers who participated in three consecutive survey waves (n=980). We measured attitude, subjective norm, and perceived behavioural control in 2012, intention to quit with three instruments in 2013, and having made a quit attempt in the last year in 2014. We conducted Structural Equation Modelling with three models for the instruments of intention separately, and with one model that included the three instruments simultaneously. All three instruments of intention were significantly and positively related to attitude and perceived behavioural control but none was related to subjective norm. All three ins...
When national pharmacoeconomic guidelines are compared, different recommendations are identified ... more When national pharmacoeconomic guidelines are compared, different recommendations are identified on how to identify, measure and value lost productivity, leading to difficulties when comparing lost productivity estimates across countries. From a transferability point of view, the question arises of whether differences between countries regarding lost productivity are the result of using different calculation methods (methodological differences) or of other between-country differences. When lost productivity data differ significantly across countries, the transferability of lost productivity data across countries is hindered. The objective of this study was to investigate whether country of residence has a significant influence on the quantity of lost productivity among patients with rheumatic disorders. Confounding factors that might differ between countries were corrected for, while the methodology used to identify and measure lost productivity was kept the same. This question was investigated by means of an online questionnaire filled out by 200 respondents with a rheumatic disorder per country in four European countries, namely the Netherlands, the UK, Germany and France. In addition to those regarding lost productivity, the questionnaire contained questions about patient characteristics, disability insurance, disease characteristics, quality of life and job characteristics as these variables are expected to influence lost productivity in terms of absenteeism and presenteeism. The data were analysed by regression analyses, in which different components - being absent in last 3 months, number of days absent and presenteeism - of lost productivity were the main outcome measures and other variables, such as gender, impact of disease, shift work, job control, partial disability and overall general health, were corrected for. The results showed that country sometimes has a significant influence on lost productivity and that other variables such as, for example, age, disease severity, number of contract hours, decision latitude, experienced health (as reported on the visual analogue scale) and partial disability, also influence lost productivity. A significant influence of country of residence was found on the variables &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;being absent in the last three months&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;, &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;number of days absent&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;quality of work on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;. However, country did not influence &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;quantity of work on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;overall presenteeism on the last working day&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;. It can be concluded that country has a significant influence on lost productivity among patients with rheumatic disorders, when corrected for other variables that have an influence on absenteeism and presenteeism. Transferring lost productivity data across countries without adaptation is hindered by the significant differences between countries in this patient group. As a result, transferring lost productivity data, being either monetary values or volumes of productivity losses, between countries can give wrong estimations of the cost effectiveness of treatments.
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