2021
DOI: 10.1038/s41598-021-86388-8
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Reliability assessment of temporal discounting measures in virtual reality environments

Abstract: In recent years the emergence of high-performance virtual reality (VR) technology has opened up new possibilities for the examination of context effects in psychological studies. The opportunity to create ecologically valid stimulation in a highly controlled lab environment is especially relevant for studies of psychiatric disorders, where it can be problematic to confront participants with certain stimuli in real life. However, before VR can be confidently applied widely it is important to establish that comm… Show more

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Cited by 23 publications
(30 citation statements)
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References 84 publications
(90 reference statements)
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“…Model comparison revealed that the DDM S (DDM including a sigmoidal drift rate modulation) accounted for the data best (Table 4), replicating previous findings [39,46,48,51] . Further analyses focused on the DDM S .…”
Section: Resultssupporting
confidence: 85%
See 3 more Smart Citations
“…Model comparison revealed that the DDM S (DDM including a sigmoidal drift rate modulation) accounted for the data best (Table 4), replicating previous findings [39,46,48,51] . Further analyses focused on the DDM S .…”
Section: Resultssupporting
confidence: 85%
“…comparing F5 vs. S1) in either group for any physiological measure. Instead, in both groups, the tonic skin conductance level (SCL) increased substantially upon VR immersion in both groups (effect size r between .66 and .81 in both groups and both sessions) and remained elevated until the end of the experiment, an effect we have observed previously in non-gambling controls [39] . No corresponding effects were observed for heart rate or the number of spontaneous skin conductance responses.…”
Section: Discussionmentioning
confidence: 64%
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“…Alterations in TD are associated with a range of psychiatric conditions and problematic behaviors, including addiction, substance abuse and attention-deficit hyperactivity disorder (Amlung et al, 2019; Bickel et al, 2019; Jackson & McKillop, 2016; Wiehler & Peters, 2015). TD exhibits stability over weeks ( r = .91; Simpson & Vuchinich, 2000), months ( r = .77-.80; Arfer & Luhmann, 2017) and even one year ( r = .71; Kirby, 2009), and across different testing environments (Bruder et al, 2021; Odum, 2011). Temporal discounting is therefore regarded as a trait-like characteristic (Smith & Hantula, 2008).…”
Section: Introductionmentioning
confidence: 99%