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Weighting methods are commonly used in situations of unit nonresponse with linked register data. However, several arguments in terms of valid inference and practical usability can be made against the use of weighting methods in these situations. Imputation methods such as sample and mass imputation may be suitable alternatives, as they lead to valid inference in situations of item nonresponse and have some practical advantages. In a simulation study, sample and mass imputation were compared to traditional weighting when dealing with unit nonresponse in linked register data. Methods were compared on their bias and coverage in different scenarios. Both, sample and mass imputation, had better coverage than traditional weighting in all scenarios. Imputation methods can therefore be recommended over weighting as they also have practical advantages, such as that estimates outside the observed data distribution can be created and that many auxiliary variables can be taken into account. The use of sample or mass imputation depends on the specific data structure.

Item does not contain fulltext Previous research has shown limited efficacy of nicotine replacement therapy (NRT) among adolescents and generally low compliance rates. As higher compliance rates are associated with improved abstinence rates, the present study examined predictors of NRT compliance. This study aims to test whether different NRT compliance trajectories can be distinguished among adolescents, to test whether these trajectories can be predicted by demographic, smoking-related, and personality factors, and to examine abstinence rates for each trajectory. Data were used from a randomized controlled trial that tested the efficacy of nicotine patches versus placebo patches among 265 Dutch adolescents. During NRT treatment, adolescents filled out six online questionnaires in which they reported on the number of days they used the patches. Predictors (i.e., demographic and smoking-related factors and personality characteristics) and end-of-treatment abstinence were also administered through these self-reports. Latent class growth analysis (LCGA) was used to analyze compliance data by classifying individuals into similar growth trajectories. Three compliance trajectories were found (i.e., "compliers" (n = 89), "moderate decreasers" (n = 41), and "strong decreasers" (n = 127)). The compliers can be characterized by higher levels of conscientiousness and agreeableness and lower levels of extraversion compared with the strong decreasers, and by higher levels of conscientiousness and education compared with the moderate decreasers. Among the compliers, a substantially higher percentage of adolescents achieved abstinence at end-of-treatment (10 %) compared with the moderate decreasers (3 %) and the strong decreasers (6 %). These findings could be the starting point for person-tailored interventions that aim to enhance NRT compliance rates among adolescents. 10 p.

ObjectivesThe use of stakeholders in systematic reviews is increasingly valued, but their influence on the systematicity of the review is often unclear. The aim of this study was to describe some of the processes of involvement of stakeholders and to demonstrate a Tool for Recording and Accounting for Stakeholder Involvement (TRASI).MethodsWe demonstrate the TRASI in two worked examples. In one project, the reviewers collaborated with the end-user and an expert during the literature search. In the other project, experts were consulted to generate keywords before searching the literature.ResultsIn the first project, disagreements about keywords to identify studies for the research topic were solved by informal discussion. In the second project, difficulties arose in reaching agreement between experts and reviewers about the core construct and the meaningful keywords associated with it.DiscussionThe TRASI aids researchers to systematically and transparently account for the decisions taken. The TRASI supports information specialists and librarians to shape the search strategy to match the objectives of the review.ConclusionsWe propose the TRASI as a first step in resolving the challenges of detecting and reconstructing stakeholder influences. Potential new applications of the TRASI are discussed.

This article reports from a pilot study that was conducted in a probability-based online panel in the Netherlands. Two parallel surveys were conducted: one in the traditional questionnaire layout of the panel and the other optimized for mobile completion with new software that uses a responsive design (optimizes the layout for the device chosen). The latter questionnaire was optimized for mobile completion, and respondents could choose whether they wanted to complete the survey on their mobile phone or on a regular desktop. Results show that a substantive number of respondents (57%) used their mobile phone for survey completion. No differences were found between mobile and desktop users with regard to break offs, item nonresponse, time to complete the survey, or response effects such as length of answers to an open-ended question and the number of responses in a check-all-that-apply question. A considerable number of respondents gave permission to record their GPS coordinates, which are helpful in defining where the survey was taken. Income, household size, and household composition were found to predict mobile completion. In addition, younger respondents, who typically form a hard-to-reach group, show higher mobile completion rates.

The effects of an intervention designed to prevent onset of weekly drinking in non drinking students (PAS) were investigated in the group of students that was already drinking at baseline. A cluster randomized trial was used including 3,490 Dutch early adolescents (M age=12.66, SD =0.49) randomized over four conditions; 1) parent intervention, 2) student intervention, 3) combined intervention and 4) control group. Outcome measures were amount and growth of weekly alcohol drinking measured 10, 22 and 34months after baseline. The combined intervention significantly curbed the growth of drinking among both non-drinkers (the target group of the intervention) and drinkers at baseline. Overall, less strong increases of drinking over time are found among non-drinkers compared to drinkers at baseline. Thus, the combined PAS intervention is also effective in curbing adolescents' drinking behaviour in those who already were drinking at baseline. Broad implementation of the combined parent–student intervention is recommended.

Low public acceptance hinders the successful introduction of biotechnological innovations, such as genetically modified foods or vaccinations against infectious diseases. Earlier studies indicated that a lack of knowledge is not a key barrier to acceptance. This was confirmed in the current study, which examined an integrated theoretical model tested among 579 participants from the Dutch public. The results suggest that communication strategies should instead target attitudes, social norms, and risk perceptions, and appeal to people's tendency (or lack thereof) to be innovative.

Purpose To provide an overview of factors influencing the acceptance of electronic technologies that support aging in place by community-dwelling older adults. Since technology acceptance factors fluctuate over time, a distinction was made between factors in the pre-implementation stage and factors in the post-implementation stage. Methods A systematic review of mixed studies. Seven major scientific databases (including MEDLINE, Scopus and CINAHL) were searched. Inclusion criteria were as follows: (1) original and peer-reviewed research, (2) qualitative, quantitative or mixed methods research, (3) research in which participants are community-dwelling older adults aged 60 years or older, and (4) research aimed at investigating factors that influence the intention to use or the actual use of electronic technology for aging in place. Three researchers each read the articles and extracted factors. Results Sixteen out of 2841 articles were included. Most articles investigated acceptance of technology that enhances safety or provides social interaction. The majority of data was based on qualitative research investigating factors in the pre-implementation stage. Acceptance in this stage is influenced by 27 factors, divided into six themes: concerns regarding technology (e.g., high cost, privacy implications and usability factors); expected benefits of technology (e.g., increased safety and perceived usefulness); need for technology (e.g., perceived need and subjective health status); alternatives to technology (e.g., help by family or spouse), social influence (e.g., influence of family, friends and professional caregivers); and characteristics of older adults (e.g., desire to age in place). When comparing these results to qualitative results on post-implementation acceptance, our analysis showed that some factors are persistent while new factors also emerge. Quantitative results showed that a small number of variables have a significant influence in the pre-implementation stage. Fourteen out of the sixteen included articles did not use an existing technology acceptance framework or model. Conclusions Acceptance of technology in the pre-implementation stage is influenced by multiple factors. However, post-implementation research on technology acceptance by community-dwelling older adults is scarce and most of the factors in this review have not been tested by using quantitative methods. Further research is needed to determine if and how the factors in this review are interrelated, and how they relate to existing models of technology acceptance. Keywords: Independent living, Aged, Technology, Review, Behavior, Assistive technology, eHealth