Challenges that surveys are facing are increasing data collection costs and declining budgets. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done into the effect on quality and costs of reducing the use of interviewers in mixed-mode surveys starting with internet observation, followed by telephone or face-to-face observation of internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. Currently, adaptive survey design is an option in redesigns of social surveys at Statistics Netherlands. In 2018 it has been implemented in the Health Survey and the Public Opinion Survey, in 2019 in the Life Style Monitor and the Leisure Omnibus, in 2021 in the Labour Force Survey, and in 2022 it is planned for the Social Coherence Survey. This paper elaborates on the development of the adaptive survey design for the Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and the six-month parallel design with corresponding response results.
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The aim of the current study is twofold. First, it investigates the influencing factors of runners' sports apparel value at a running event. Second, the potential value of observational data in the socioeconomic field is investigated, as this study combines data retrieved by a survey and by visually scanning pictures of event runners. The results demonstrate that visual data gathering methods contribute to explaining sports apparel usage and consumption. For example, it is found that runners who wear a shirt of the running event spent less money on their running shoes and overall sports apparel. From a methodological point of view, it is shown that observation leads to no nonresponse and thus corrects for selection bias. Other advantages (e.g., less selection bias, less recall bias, time-efficiency for research subject, potential automatic computer analysis in future) and disadvantages (e.g., technical, labor intensiveness for researcher, privacy) of visual data are discussed.
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This study (re)tests the relationship between planning and transfer success. Previous studies show that planning increases satisfaction, but find no or only weak relations to transfer effectiveness. 76 Dutch SME business owners, who succeeded in the transfer, were surveyed. To improve on previous studies reliable scales were constructed and results were tested for common method bias, social desirable answering and nonresponse. Multi regression analyses indicate that planning and preparation does relate to satisfaction but has no relation with performance. To predict effectiveness of SME transfers both the market and entrepreneurial abilities of the buyer seem more appealing.
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The purpose of the research was the development of a questionnaire that can measure the behaviour of groups of students (for instance departments' cohorts) in Personal Information Management (PIM). Variables for the questionnaire were derived from the international literature on PIM. The questionnaire has been tested out on 79 students (last year before graduation) from four different departments of the Academy of ICT&Media at The Hague University of Applied Sciences. The students' responses were checked on consistency, item non response, desirability bias and information value of the results. All these criteria indicated that the questionnaire is an adequate tool for the assessment of PIM at an institutional level. The results that have been found for the four departments have not yet been discussed with the managers of the Academy and those of the individual departments. [De hier gepubliceerde versie is het 'accepted paper' van het origineel dat is gepubliceerd op www.springerlink.com . De officiële publicatie kan worden gedownload op http://www.springerlink.com/content/n0h3k71u85024xnt/]
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Adaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is a standard option in redesigns of person and household surveys at Statistics Netherlands and it has been implemented for the Dutch Health survey in 2018. In this article, the implementation of static adaptive survey designs is described and motivated with a focus on practical feasibility.
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Rationale, aims and objective: Primary Care Plus (PC+) focuses on the substitution of hospital-based medical care to the primary care setting without moving hospital facilities. The aim of this study was to examine whether population health and experience of care in PC+ could be maintained. Therefore, health-related quality of life (HRQoL) and experienced quality of care from a patient perspective were compared between patients referred to PC+ and to hospital-based outpatient care (HBOC). Methods: This cohort study included patients from a Dutch region, visiting PC+ or HBOC between December 2014 and April 2018. With patient questionnaires (T0, T1 and T2), the HRQoL and experience of care were measured. One-to-two nearest neighbour calliper propensity score matching (PSM) was used to control for potential selection bias. Outcomes were compared using marginal linear models and Pearson chi-square tests. Results: One thousand one hundred thirteen PC+ patients were matched to 606 HBOC patients with well-balanced baseline characteristics (SMDs <0.1). Regarding HRQoL outcomes, no significant interaction terms between time and group were found (P > .05), indicating no difference in HRQoL development between the groups over time. Regarding experienced quality of care, no differences were found between PC+ and HBOC patients. Only travel time was significantly shorter in the HBOC group (P ≤ .001). Conclusion: Results show equal effects on HRQoL outcomes over time between the groups. Regarding experienced quality of care, only differences in travel time were found. Taken as a whole, population health and quality of care were maintained with PC+ and future research should focus more on cost-related outcomes.
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This study examines completion rate for a self-assessment survey designed to assess employees' digital skills levels in the workplace. The aim is to improve data quality by investigating completion of the survey. The study reviews the theoretical background related to self-assessment surveys and completion rate, and explores the influence of survey length and format in survey design on completion rate. The research design and data analysis are described in detail, with a focus on identifying factors that may influence completion rate. Results suggest that survey designers should consider using Likert scales to optimize completion rate and completion time. However, this study did not find a significant increase in completion rate as a result of motivation, which was claimed from the literature. The study concludes with implications for the design and implementation of self-assessment surveys in the workplace, including the importance of reducing length and complexity of survey items and questions.
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Although governments are investing heavily in big data analytics, reports show mixed results in terms of performance. Whilst big data analytics capability provided a valuable lens in business and seems useful for the public sector, there is little knowledge of its relationship with governmental performance. This study aims to explain how big data analytics capability led to governmental performance. Using a survey research methodology, an integrated conceptual model is proposed highlighting a comprehensive set of big data analytics resources influencing governmental performance. The conceptual model was developed based on prior literature. Using a PLS-SEM approach, the results strongly support the posited hypotheses. Big data analytics capability has a strong impact on governmental efficiency, effectiveness, and fairness. The findings of this paper confirmed the imperative role of big data analytics capability in governmental performance in the public sector, which earlier studies found in the private sector. This study also validated measures of governmental performance.
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Like many countries, the COVID-19 pandemic has forced Statistics Netherlands to make changes in its fieldwork strategy. Since mid-March 2020, there have been limited opportunities to conduct face-to-face interviews. Therefore, from September 2020, CAPI sampled people are offered the opportunity to respond by telephone. For this purpose, face-to-face interviewers are instructed to persuade the potential respondent at the doorway. When people refuse a face-to-face interview, interviewers ask for a telephone number and try to make an appointment to conduct the interview by telephone. The aim of our study was to investigate the effects of conducting the interview by telephone instead of face-to-face on important survey outcome variables. We were particularly interested in whether differences are due to selection effects or caused by mode-specific measurement errors. Because we did not have the time or capacity to set up a controlled experiment, we performed regression analyses to decompensate the differences between selection effects and mode-specific measurement errors. We used data of the Labour Force Survey (LFS) and the Housing Survey (WoON). Our analysis showed that there were differences in important target variables, for both LFS and WoON. These differences were, however, mainly caused by selection effects – which can be taken into account for during weighting – and were less likely to be caused by mode specific measurement errors. Although there are important limitations and caveats, these findings are supportive to further implement this field strategy.
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Purpose: Providing an overview of studies on family participation in physiotherapy-related tasks of critically ill patients, addressing two research questions (RQ): 1) What are the perceptions of patients, relatives, and staff about family participation in physiotherapy-related tasks? and 2) What are the effects of interventions of family participation in physiotherapy-related tasks? Material and methods: Qualitative, quantitative and mixed-methods articles were identified using PubMed, Embase and CINAHL. Studies reporting on family participation in physiotherapy-related tasks of adult critically ill patients were included. A convergent segregated approach for mixed-methods reviews was used. Results: Eighteen articles were included; 13 for RQ1, and 5 for RQ2. The included studies were quantitative, qualitative and mixed-method, including between 8 and 452 participants. The descriptive studies exhibit a general appreciation for involvement of relatives in physiotherapy-related tasks, although most of the studies reported on family involvement in general care and incorporated diverse physiotherapy-related tasks. One study explored the effectiveness of family participation on a rehabilitation outcome and showed that the percentage of patients mobilizing three times a day increased. Conclusion: Positive attitudes were observed among patients, their relatives and staff towards family participation in physiotherapy-related tasks of critically ill patients. However, limited research has been done into the effect of interventions containing family participation in physiotherapy-related tasks.
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