UK Device Use and Associations (DUaA)

Published: 19-10-2020| Version 1 | DOI: 10.17632/pyxhjd58d9.1
Contributors:
Madeleine Steeds,
Sarah Clinch,
Caroline Jay

Description

This research aimed to investigate how adults in the UK use four everyday devices, the associations they make with the devices, and whether there is an interaction between how they are used and perceived. The data was collected via an online survey advertised on prolific.ac, and participants who were under 18, non-native English speakers, or did not complete the survey were excluded. Participants were asked to provide demographic information, how many of each device they use frequently and the make and model. They were asked about their confidence using the device and to complete a free association task and multiple choice association task about smartphones and desktops. Participants then rated the four devices as hedonic and utilitarian (Batra and Ahtola, 1991), and to rate the devices within the Stereotype Content Model as per experiment 2 of Schwind et al. (2019). Participants were asked how long they spent on activities on their devices and what activities they undertake. The data was analysed using ANOVAs, MANOVAs, correlations, and regressions. In some cases the data was non-parametric so equivalent tests or z-score transformations were applied. The data here is the raw data, before the exclusion criteria was applied. The full questionnaire is included with the data. In the free association data, if no words or more than one word were saved to a row, this was not included in the analysis. Activities data was analysed by scoring hedonic activities as 1, utilitarian activities as -1 and neutral activities as 0 (Utilitarian activities: emailing; meetings; reading for work; making notes; banking; reading/watching the news; report writing; spreadsheets; presentations. Hedonic activities: social media; messaging; gaming; shopping; writing for pleasure; reading for pleasure; watching television; listening to music/podcasts; browsing; online dating; taking/viewing photos). Data for "Useful", "valuable" and "pleasant" in the 'opinion' CSVs needs to be counterbalanced (e.g. 5=1).

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