2022
DOI: 10.31234/osf.io/avj92
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A jsPsych plugin for visual analogue scales

Abstract: Visual analogue scales (VASs) allow survey respondents to specify their answers with a high degree of precision, unlike Likert-type scales in which only a few categorical responses are available. In web-based research, HTML sliders (in which the respondent drags and drops a marker) are sometimes used as a substitute for VASs, but sliders produce data of a lower quality than true point-and-click VASs. Here, I introduce a plugin for jsPsych that enables survey responses using a true VAS, enabling researchers to … Show more

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Cited by 8 publications
(7 citation statements)
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“…Thus, it may be that the visual metaphor employed by IOS-type scales is particularly effective at measuring a form of self-continuity that relates more closely to temporal discounting. Recently-developed web-based implementations of measures like this (Kinley and van Vugt, 2023;Beranek and Castillo, 2022) could enable future research to explore this possibility.…”
Section: Discussionmentioning
confidence: 99%
“…Thus, it may be that the visual metaphor employed by IOS-type scales is particularly effective at measuring a form of self-continuity that relates more closely to temporal discounting. Recently-developed web-based implementations of measures like this (Kinley and van Vugt, 2023;Beranek and Castillo, 2022) could enable future research to explore this possibility.…”
Section: Discussionmentioning
confidence: 99%
“…This flexibility of abstraction is a key feature of jsPsych, and part of what makes it a particularly powerful way of declaratively creating experiments. jsPsych v7.2 includes 50 plugins, and many more plugins have been developed by the research community (e.g., Callaway et al, 2017;Rajananda, Lau, & Odegaard, 2018;Kuroki, 2021;Galang et al, 2021;Strittmatter, Spitzer, & Kiesel, 2021;Cousineau, 2021;Gibeau, 2021;Donhauser & Klein, 2021;Kinley, 2022).…”
Section: Methodsmentioning
confidence: 99%
“…This flexibility of abstraction is a key feature of jsPsych, and part of what makes it a particularly powerful way of declaratively creating experiments. jsPsych v7.2 includes 50 plugins, and many more plugins have been developed by the research community (e.g., Callaway et al, 2017;Rajananda, Lau, & Odegaard, 2018;Kuroki, 2021;Galang et al, 2021;Strittmatter, Spitzer, & Kiesel, 2021;Cousineau, 2021;Gibeau, 2021;Donhauser & Klein, 2021;Kinley, 2022).…”
Section: Methodsmentioning
confidence: 99%