The University of Southampton
University of Southampton Institutional Repository

Dataset supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease" Empirical paper I "Induction of spatial anxiety in a virtual navigation environment"

Dataset supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease" Empirical paper I "Induction of spatial anxiety in a virtual navigation environment"
Dataset supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease" Empirical paper I "Induction of spatial anxiety in a virtual navigation environment"
This dataset is supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease". This dataset supports Empirical paper I, "Induction of Spatial Anxiety in a Virtual Navigation Environment." The spatial anxiety induction procedure is available for free use. The software package and instruction manual can be downloaded on the following site, https://doi.org/10.17605/OSF.IO/UQ4V7 When using the route-learning task, please cite: Oliver. A., Wildschut, T., Parker, M. O., Wood, A. P., & Redhead, E. (2022). Induction of Spatial Anxiety in a Virtual Navigation Environment. Behavior Research Methods. https://doi.org/10.3758/s13428-022-01979-1
University of Southampton
Oliver, Alice
18dffa2e-f895-4a54-8b40-4b1bc62cc09d
Wildschut, Tim
4452a61d-1649-4c4a-bb1d-154ec446ff81
Redhead, Edward
d2342759-2c77-45ef-ac0f-9f70aa5db0df
Oliver, Alice
18dffa2e-f895-4a54-8b40-4b1bc62cc09d
Wildschut, Tim
4452a61d-1649-4c4a-bb1d-154ec446ff81
Redhead, Edward
d2342759-2c77-45ef-ac0f-9f70aa5db0df

Oliver, Alice (2024) Dataset supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease" Empirical paper I "Induction of spatial anxiety in a virtual navigation environment". University of Southampton doi:10.17605/OSF.IO/UQ4V7 [Dataset]

Record type: Dataset

Abstract

This dataset is supporting the University of Southampton Doctoral Thesis "The benefits of nostalgia within spatial environments for people with and without Alzheimer’s disease". This dataset supports Empirical paper I, "Induction of Spatial Anxiety in a Virtual Navigation Environment." The spatial anxiety induction procedure is available for free use. The software package and instruction manual can be downloaded on the following site, https://doi.org/10.17605/OSF.IO/UQ4V7 When using the route-learning task, please cite: Oliver. A., Wildschut, T., Parker, M. O., Wood, A. P., & Redhead, E. (2022). Induction of Spatial Anxiety in a Virtual Navigation Environment. Behavior Research Methods. https://doi.org/10.3758/s13428-022-01979-1

Other
spatial_anxiety_spss.sav - Dataset
Available under License Creative Commons Attribution.
Download (11kB)

More information

Published date: 16 February 2024
Related URLs:

Identifiers

Local EPrints ID: 487327
URI: http://eprints.soton.ac.uk/id/eprint/487327
PURE UUID: c0cdbf27-169a-41d5-8411-ab0b155f0fe6
ORCID for Alice Oliver: ORCID iD orcid.org/0000-0001-8812-315X
ORCID for Tim Wildschut: ORCID iD orcid.org/0000-0002-6499-5487
ORCID for Edward Redhead: ORCID iD orcid.org/0000-0002-7771-1228

Catalogue record

Date deposited: 19 Feb 2024 16:17
Last modified: 21 Feb 2024 03:00

Export record

Altmetrics

Contributors

Creator: Alice Oliver ORCID iD
Research team head: Tim Wildschut ORCID iD
Research team head: Edward Redhead ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×