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Mode effects and survey context Introduction
This section discusses survey mode and timing as well as the impact of the wider context in which surveys are conducted - such as incidental day-to-day events that might affect responses. It essentially concerns the extent to which subjective well-being data collected under different circumstances using different methods can still be considered comparable. It also examines the question of whether there is an “optimal” method for subjective well-being data collection, in terms of data quality.
There are a variety of different survey methods available for the collection of subjective well-being data. These include:
The central issue with regard to survey mode is whether data collected in different modes can be considered comparable. In general, survey mode effects can take the form of: 1) coverage error, i.e. certain modes excluding or failing to reach certain segments of the population; 2) non-response bias, i.e. different respondents having preferences for different modes; and 3) measurement error (Jackle, Roberts and Lynn, 2006). The current chapter is
Box 2.2. Experience Sampling and the Day Reconstruction method
Some measures of subjective well-being, particularly affective measures, require respondents to retrospectively recall their previous experiences over a given time frame. A frequent concern is that various self-report biases (including those linked to certain personality traits) can influence this recall process. In terms of minimising the memory burden and the risk of recall biases, Experience Sampling Methodologies (ESM - Csikszentmihalyi and Larson, 1992; Hormuth, 1986; Larson and Delespaul, 1992), also known as Ecological Momentary Assessments (EMA - Schwartz and Stone, 1998; Smyth and Stone, 2003; Stone et al., 1998) represent the “gold standard”. In these methods, respondents provide “real-time” reports throughout the study-period, and the memory burden is either very small (e.g. summing experiences over the past few hours) or nonexistent (e.g. requiring respondents to report how they are feeling right now). Studies typically involve between two and twelve recordings per day (Scollon et al., 2003) and may last one or two weeks. To ensure compliance among respondents (for example, to detect and prevent the “hoarding” of responses until the end of the day, which can be a significant problem with paper diaries), it is advisable to use electronic diaries, such as palm-top computers pre-programmed with questions and with an internal clock that can both remind respondents when entries are due and record the timing of responses (Stone et al., 2002).
Whilst experience sampling methods have some significant advantages in data quality, the study design is burdensome for both respondents and research resources. A less intrusive and burdensome alternative is offered by the Day Reconstruction Method or DRM (Kahneman et al., 2004). This technique is designed to assist respondents in systematically reconstructing their day in order to minimise recall biases. It builds on evidence suggesting that end-of-day mood reports may be more accurate than previously supposed (Parkinson et al., 1995), and that retrospective accounts of mood may be reasonably valid for periods of up to 24 hours (Stone, 1995). The DRM represents a more pragmatic alternative to the ESM but still requires detailed survey modules, which can for example take respondents between 45 and 75 minutes to complete (Kahneman et al., 2004).
particularly concerned with the third of these issues, and although discussion of sampling issues is covered in Chapter 3, the first and second issues also have consequences that potentially interact with mode effects and problems with data quality - for example, where mode effects are more likely among certain groups of respondents.
A further crucial consideration is the extent to which identical question wording and response formats can be used across different survey modes. As noted in Sections 1 and 2 of this chapter, question wording and response formats can have non-trivial impacts on responses. If questions designed for pen-and-paper questionnaires or face-to-face interviews need to be modified for presentation over the telephone, for example, this may reduce the comparability of the data collected.
Techniques for the measurement of subjective well-being can vary substantially on a wide range of dimensions that may be of relevance to measurement error, such as:
There are various ways in which the above features of survey mode can influence data quality - for example, through influencing respondent motivation, question comprehension and the likelihood of satisficing and response biases. Interviewer interaction and audience effects are also expected to influence the extent to which self-presentational effects and socially desirable responding are likely to occur, such as presenting oneself in a positive light, or conforming to social norms. In the case of subjective well-being measures, self-presentational biases, if present, would be expected to increase reports of positive evaluations and emotions and decrease reports of negative ones. Although self-presentation effects are quite a wide-reaching issue for data quality, discussion of them is generally limited to this section of the chapter, because the main practical implications in terms of survey methodology concern the impact of survey mode.
Different survey methods have different advantages, and steps taken to reduce one risk to data quality (such as social desirability) may have consequences for other risks (such as other forms of response bias). Furthermore, where mode differences are detected, this does not in itself tell you which mode is producing the more accurate data. Much of the discussion that follows therefore describes the extent to which survey mode appears to influence subjective well-being data and the extent to which data collected in different modes can be compared with confidence.
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