Response Latency Methodology for Survey Research: Measurement and Modeling Strategies

Mulligan, Kenneth; Grant, J. Tobin; Mockabee, Stephen T.; Monson, J. Quin

doi:10.1093/pan/mpg004

Cited by 53 publications

(57 citation statements)

References 23 publications

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“…Nevertheless, interviewers accounted for only 3.2 percent of the variance in response times, a magnitude in line with Couper and Kreuter's findings in a face-to-face survey. Finally, the response time measures collected by paradata are from "latent timers" (Mulligan et al 2003), measuring the time from which a question appeared on an interviewer's screen to the time that they advanced to the next question. Thus, we cannot disentangle whether a longer time spent on a question is due to the interviewer taking more time to administer a question, the respondent requiring more time to respond, or deviations from a question-answer-neutral feedback sequence (Maynard and Schaeffer 2002).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…This is a "latent" timer; the interviewer does not directly interact with the timing device (Mulligan et al 2003). Most of the early work on response times used active timers that were triggered by interviewers (e.g., Bassili 1996), with a focus on the time that it takes the respondent to answer a question after the interviewer stopped reading it.…”

Section: Measuring Response Timementioning

confidence: 99%

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The Effect of CATI Questions, Respondents, and Interviewers on Response Time

Olson¹,

Smyth²

2015

J Surv Stat Methodol

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In this paper, we evaluate the joint effects of question, respondent, and interviewer characteristics on response time in a telephone survey. We include question features traditionally examined, such as the length of the question and format of response options, and features that have yet to be examined that are related to the layout and format of intervieweradministered questions. We examine how these question features affect the time to ask and answer survey questions and how different interviewers vary in their administration of these questions. This paper uses paradata from the Work and Leisure Today survey and uses cross-classified random effects models. Overall, most of the variation in response time is due to question characteristics, rather than respondent or interviewer attributes. Additionally, we find that question characteristics related to necessary survey design features and respondent confusion are the primary predictors of response time, with little effect of visual design features of the question.We also find modest differences in the effects of question characteristics by interviewer experience.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Measuring Response Timementioning

confidence: 99%

The Effect of CATI Questions, Respondents, and Interviewers on Response Time

Olson¹,

Smyth²

2015

J Surv Stat Methodol

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“…The IAT can be used as a predictor of consumer behaviour, which can be correlated with explicit attitudes [24] and has been shown to relate to behavioural orientations [22]. The IAT uses response latency to reveal attitudes [25] and can be administered on paper or via computer. Response latency in health research is used to determine how accessible an attitude is to consciousness ('attitude accessibility'), by determining how quickly it comes to mind [25].…”

Section: The Implicit Association Testmentioning

confidence: 99%

“…The IAT uses response latency to reveal attitudes [25] and can be administered on paper or via computer. Response latency in health research is used to determine how accessible an attitude is to consciousness ('attitude accessibility'), by determining how quickly it comes to mind [25].…”

Section: The Implicit Association Testmentioning

confidence: 99%

What I say isn’t always what I do: Investigating differences in children’s reported and actual snack food preferences

Jones

Kervin

Reis

et al. 2012

Int. J. Child Health Nutr.

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The current study sought to explore discrepancies between children's stated snack food motivations and actual food choices, using the Implicit Association Test (IAT) as a measure of implicit attitudes towards 'healthy' and 'unhealthy' foods. Participants were children aged 6-12 years (n=118), from two primary schools on the South Coast of NSW, Australia -a public school in a semi-rural suburb south of a sea-side city and a public school in a largely residential northern suburb of the same city. The children completed a questionnaire about motivations for snack choices, participated in an activity, completed two further questionnaires, selected snack foods from an in-class store, and participated in two rounds of an IAT 'game' pairing pictures of snack foods with positive and negative words. As hypothesized, the majority of children reported 'healthiness' as their primary motivator for snack food choice, but when faced with an actual purchase decision predominantly chose unhealthy snacks. It appears that children may have internalized the 'moral' values attributed to healthy and unhealthy foods and that this process influences both their explicit and implicit attitudes. However, their actual food choices are likely to be influenced by other factors, and thus more complex to understand and influence.Keywords investigating, food, differences, actual, children, reported, preferences, snack, i, say, isn, t, always, do Abstract: The current study sought to explore discrepancies between children's stated snack food motivations and actual food choices, using the Implicit Association Test (IAT) as a measure of implicit attitudes towards 'healthy' and 'unhealthy' foods. Participants were children aged 6-12 years (n=118), from two primary schools on the South Coast of NSW, Australia -a public school in a semi-rural suburb south of a sea-side city and a public school in a largely residential northern suburb of the same city. The children completed a questionnaire about motivations for snack choices, participated in an activity, completed two further questionnaires, selected snack foods from an in-class store, and participated in two rounds of an IAT 'game' pairing pictures of snack foods with positive and negative words. As hypothesized, the majority of children reported 'healthiness' as their primary motivator for snack food choice, but when faced with an actual purchase decision predominantly chose unhealthy snacks. It appears that children may have internalized the 'moral' values attributed to healthy and unhealthy foods and that this process influences both their explicit and implicit attitudes. However, their actual food choices are likely to be influenced by other factors, and thus more complex to understand and influence.

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“…So, if respondents take longer to answer a question about the frequency of a behaviour that took place various times in the last year, and take less time to answer a question about a behaviour that only happened occasionally a short time ago, one could infer that the answer to the first question took longer because it took more effort or more mental steps were needed to retrieve it from Long Term Memory (e.g. Bassili, 1996;Mulligan, Grant, Mockabee, & Monson, 2003; see also Yan & Tourangeau, 2007, for a recent example). On the other hand, very short reaction times can indicate that no cognitive effort took place at all, and strong satisficing 2 took place (Krosnick, 1991).…”

Section: The Toolbox Of Cognitive Survey Researchmentioning

confidence: 99%

Getting from neuron to checkmark: models and methods in cognitive survey research

Holleman

Murre

2007

Applied Cognitive Psychology

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Since the 1980s much work has been done in the field of Cognitive Survey Research. In an interdisciplinary endeavour, survey methodologists and cognitive psychologists (as well as social psychologists and linguists) have worked to unravel the cognitive processes underlying survey responses: to improve survey measurement, but also to obtain fundamental insight into the process of question answering, the nature of attitudes, the functioning of human memory, etc. Yet, despite the amount of work that has been done, less progress has been made than was deemed possible. This paper suggests ways in which to develop cognitive theories that may help to obtain an integrated understanding of question answering in surveys. One way to build better theories is to focus on model construction. Different types of cognitive models are discussed that can be used to model question answering. Second, a larger variety of methods from the cognitive toolbox can be used to further develop and test these models. An overview is given of the various tools available to researchers of cognitive aspects of survey research, with a special focus on newer methods from cognitive neuroscience. To connect different tools and methods into an integrative theory of question answering, the idea of hierarchical modelling is proposed.

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Response Latency Methodology for Survey Research: Measurement and Modeling Strategies

Cited by 53 publications

References 23 publications

The Effect of CATI Questions, Respondents, and Interviewers on Response Time

The Effect of CATI Questions, Respondents, and Interviewers on Response Time

What I say isn’t always what I do: Investigating differences in children’s reported and actual snack food preferences

Getting from neuron to checkmark: models and methods in cognitive survey research

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