Vera Toepoel

Ageing, Leisure, and Social Connectedness: How could Leisure Help Reduce Social Isolation of Older People?

This study investigates the relation between leisure activities and the social status of the elderly based on a heterogeneous sample of the Dutch population. Close relationships are also analyzed to identify which people could serve as successful stimulators of leisure participation. The social profile confirms that older people have fewer social contacts and often feel lonely. This study shows that leisure activities explain a significant part of older people’s social connectedness. Voluntary work, cultural activities, holiday, sports, reading books, hobbies and shopping are found to be successful predictors for social connectedness of older people. Watching TV, listening to the radio, and spending time behind the computer (passive activities) were not associated with social connectedness. Friends correlate positively to participation in leisure activities. Partners play a role in participation in cultural activities and sports; parents play a role in participation in voluntary work and holidays; siblings play a role in voluntary work and sports; and children play a role in cultural activities, reading books, and shopping. Local communities can use these close relationships and develop special programs to increase social connectedness and hence improve quality of life for older adults.

What Happens if You Offer a Mobile Option to Your Web Panel? Evidence From a Probability-Based Panel of Internet Users

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.

Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys

Over the past decades there has been an increasing use of panel surveys at the household or individual level. Panel data have important advantages compared to independent cross sections, but also two potential drawbacks: attrition bias and panel conditioning effects. Attrition bias arises if dropping out of the panel is correlated with a variable of interest. Panel conditioning arises if responses are influenced by participation in the previous wave(s); the experience of the previous interview(s) may affect the answers to questions on the same topic, such that these answers differ systematically from those of respondents interviewed for the first time. In this study the authors discuss how to disentangle attrition and panel conditioning effects and develop tests for panel conditioning allowing for nonrandom attrition. First, the authors consider a nonparametric approach with assumptions on the sample design only, leading to interval identification of the measures for the attrition and panel conditioning effects. Second, the authors introduce additional assumptions concerning the attrition process, which lead to point estimates and standard errors for both the attrition bias and the panel conditioning effect. The authors illustrate their method on a variety of repeated questions in two household panels. The authors find significant panel conditioning effects in knowledge questions, but not in other types of questions. The examples show that the bounds can be informative if the attrition rate is not too high. In most but not all of the examples, point estimates of the panel conditioning effect are similar for different additional assumptions on the attrition process.

The Use of PCs, Smartphones, and Tablets in a Probability-Based Panel Survey

Respondents in an Internet panel survey can often choose which device they use to complete questionnaires: a traditional PC, laptop, tablet computer, or a smartphone. Because all these devices have different screen sizes and modes of data entry, measurement errors may differ between devices. Using data from the Dutch Longitudinal Internet Study for the Social sciences panel, we evaluate which devices respondents use over time. We study the measurement error associated with each device and show that measurement errors are larger on tablets and smartphone than on PCs. To gain insight into the causes of these differences, we study changes in measurement error over time, associated with a switch of devices over two consecutive waves of the panel. We show that within individuals, measurement errors do not change with a switch in device. Therefore, we conclude that the higher measurement error in tablets and smartphones is associated with self-selection of the sample into using a particular device.

Non-probability Sampling

A sample is a subset of a population and we survey the units from the sample with the aim to learn about the entire population. However, the sampling theory was basically developed for probability sampling, where all units in the population have known and positive probabilities of inclusion. This definition implicitly involves randomization, which is a process resembling lottery drawing, where the units are selected according to their inclusion probabilities. In probability sampling the randomized selection is used instead of arbitrary or purposive sample selection of the researcher, or, instead of various self-selection processes run by respondents. Within this context, the notion of non-probability sampling denotes the absence of probability sampling mechanism.

Words, Numbers, and Visual Heuristics in Web Surveys: Is There a Hierarchy of Importance?

Respondents follow simple heuristics in interpreting the visual features of questions. The authors carried out two experiments in two panels to investigate how the effect of visual heuristics affects the answers to survey questions. In the first experiment, the authors varied the distance between scale points in a 5-point scale to investigate whether respondents use the conceptual or visual midpoint of a scale. In the second experiment, the authors used different end point labels of a 5-point scale, by adding different shadings of color and numbers that differed both in sign and value (2 to -2), to study whether options that are similar of appearance are considered conceptually closer than when they are dissimilar in appearance. The authors predicted that there is a hierarchy of features that respondents attend to, with verbal labels taking precedence over numerical labels, and numerical labels taking precedence over visual cues. The results confirmed the hypothesis: the effect of spacing of response options and different end points was only apparent in polar point scales and not in fully labeled scales. In addition, this study on two panels, with one consisting of extremely trained respondents and the other of relatively fresh respondents, shows that trained respondents are affected by the distance between response options whereas relatively new respondents are not. To reduce the effect of visual cues, taking into account the robustness of results, the authors suggest it is better to use fully labeled 5-point scales in survey questions.

Design of Web Questionnaires : An Information Processing Perspective for the Effect of Response Categories

In this article, an information-processing perspective is used to explore the impact of response categories on the answers respondents provide in Web surveys. Response categories have a significant effect on response formulation in questions that are difficult to process, whereas in easier questions (where responses are based on direct recall) the response scales have a smaller effect. In general, people with less cognitive sophistication are more affected by contextual cues. The Need for Cognition and the Need to Evaluate indexes for motivation account for a significant part of the variance in survey responding. Interactions of ability to process information and motivation combine in regulating responses for questions that are more difficult to process. The results hint at a substantial role of satisficing in Web surveys.

Effects of Incentives in Surveys

Nonresponse is an important indicator of TSE, and incentives are widely used to increase response rates. This chapter discusses the theories behind incentive effects, discusses the possible forms of incentives and related effects, estimates the optimal amount of incentives, handles different modes of data collection, the relation between incentives and data quality, and ends with best practices and a view toward the future in order to help survey researchers in identifying if, how and how much incentives should be used in their surveys.

Online Coping After Negative Life Events

This article explores how individuals use online coping strategies after experiencing a negative life event. Many studies have shown that online coping is of rising importance. However, these studies have not provided all pieces of the puzzle because they tend to focus on one particular online venue (e.g., an online support group or social network site [SNS]) and on a limited number of coping strategies. This article aims to provide a more complete picture, by simultaneously examining multiple online and off-line coping strategies, using a survey administered to a representative sample of the 16+ population of the Netherlands. Furthermore, we analyze what kind of Internet activities are related to online coping and whether online coping is associated with well-being. Some 57% of our sample mentioned some form of online coping. Using the Internet for mental disengagement, active coping and planning were the most reported online coping strategies, whereas strategies aimed at emotional coping were reported less frequently. Online coping encompassed several activities: online gaming, which was associated with mental disengagement; searching for information, which was associated with problem-focused coping; and SNS and online support groups, which were associated with mental disengagement, problem-focused coping, and socioemotional coping. Finally, we examined the correlations between online coping and well-being. Controlling for off-line coping, we found online mental disengagement and online socioemotional coping to be inversely related to life satisfaction, self-esteem, and optimism, whereas correlations between online problem-focused coping and well-being were nonsignificant. The implications of these findings are discussed.

Conceptualisation and Operationalisation of Event and Festival Experiences: Creation of an Event Experience Scale

Abstract Experiences are becoming increasingly important in events and festivals, which are prime manifestations of the experience economy. However, research on event experiences has generally been concerned with economic impacts and visitor motivations [Gursoy, D., Kim, K., & Uysal, M. (2004). Perceived impacts of festivals and special events by organizers: An extension and validation. Tourism Management, 25(2), 171–181. doi:10.1016/s0261-5177(03)00092-x]. Few studies have attempted to operationalise and quantitatively analyse experiences, and there is no consensual definition regarding the essence of experiences [Walls, A. R., Okumus, F., Wang, Y., & Kwun, D. J.-W. (2011). An epistemological view of consumer experiences. International Journal of Hospitality Management, 30(1), 10–21. doi:10.1016/j.ijhm.2010.03.008]. This article develops an Event Experience Scale (EES) for event experiences. In this exploratory study the item generation and selection for this scale are presented in three phases: specifying the domain of construct and generation of items, item selection, and scale purification. An 18-item scale, comprising four dimensions – affective engagement, cognitive engagement, physical engagement, and experiencing newness – with satisfactory values for Cronbachs alphas (.83, .86, .86, and .87), emerged. Implications for theoretical and practical research are discussed.