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David A. Ellis
David A. Ellis
Professor of Behavioural Science, University of Bath
Verified email at bath.ac.uk - Homepage
Title
Cited by
Cited by
Year
The rise of consumer health wearables: promises and barriers
L Piwek, DA Ellis, S Andrews, A Joinson
PLoS Medicine, 2016
12142016
Beyond self-report: Tools to compare estimated and real-world smartphone use
S Andrews, DA Ellis, H Shaw, L Piwek
PloS one 10 (10), e0139004, 2015
5082015
Do smartphone usage scales predict behaviour
DA Ellis, BI Davidson, H Shaw, K Geyer
International Journal of Human-Computer Studies, 2019
3212019
An agenda for open science in communication
T Dienlin, N Johannes, ND Bowman, PK Masur, S Engesser, AS Kümpel, ...
Journal of Communication 71 (1), 1-26, 2021
2032021
Are smartphones really that bad? Improving the psychological measurement of technology-related behaviors
DA Ellis
Computers in Human Behavior 97, 60-66, 2019
2002019
Stress detection using wearable physiological and sociometric sensors
O Martinez Mozos, V Sandulescu, S Andrews, D Ellis, N Bellotto, ...
International Journal of Neural Systems 27 (2), 2017
1992017
The conceptual and methodological mayhem of “screen time”
L K. Kaye, A Orben, D A. Ellis, S C. Hunter, S Houghton
International Journal of Environmental Research and Public Health 17 (10), 3661, 2020
1952020
Demographic and practice factors predicting repeated non-attendance in primary care: a national retrospective cohort analysis
DA Ellis, R McQueenie, A McConnachie, P Wilson, AE Williamson
The Lancet Public Health 2 (12), e551-e559, 2017
1702017
Stress detection using wearable physiological sensors
V Sandulescu, S Andrews, D Ellis, N Bellotto, OM Mozos
Artificial Computation in Biology and Medicine: International Work …, 2015
1552015
Determining typical smartphone usage: What data do we need?
TDW Wilcockson, DA Ellis, H Shaw
Cyberpsychology, Behavior, and Social Networking 21 (6), 395-398, 2018
1432018
Morbidity, mortality and missed appointments in healthcare: a national retrospective data linkage study
R McQueenie, DA Ellis, A McConnachie, P Wilson, AE Williamson
BMC medicine 17, 1-9, 2019
1412019
The Technology Integration Model (TIM). Predicting the continued use of technology
H Shaw, DA Ellis, FV Ziegler
Computers in Human Behavior 83, 204-214, 2018
1312018
Digital detox: The effect of smartphone abstinence on mood, anxiety, and craving
TDW Wilcockson, AM Osborne, DA Ellis
Addictive behaviors 99, 106013, 2019
1082019
Predicting smartphone operating system from personality and individual differences.
H Shaw, D Ellis, LR Kendrick, F Ziegler, R Wiseman
Cyberpsychology, Behavior, and Social Networking, 2016
872016
Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
A Williamson, DA Ellis, P Wilson, R McQueenie, A McConnachie
BMJ Open, 2017
712017
Weekday affects attendance rate for medical appointments: large-scale data analysis and implications
DA Ellis, R Jenkins
PloS one 7 (12), e51365, 2012
712012
Quantifying smartphone “use”: Choice of measurement impacts relationships between “usage” and health
H Shaw, DA Ellis, K Geyer, BI Davidson, FV Ziegler, A Smith
Technology, Mind, and Behavior 1 (2), 2020
67*2020
Can programming frameworks bring smartphones into the mainstream of psychological science?
L Piwek, DA Ellis, S Andrews
Frontiers in Psychology 7, 2016
472016
Rich contexts do not always enrich the accuracy of personality judgments
HJ Wall, PJ Taylor, J Dixon, SM Conchie, DA Ellis
Journal of Experimental Social Psychology 49 (6), 1190-1195, 2013
452013
Opening Pandora’s Box: Peeking inside Psychology’s data sharing practices, and seven recommendations for change
JN Towse, DA Ellis, AS Towse
Behavior Research Methods 53, 1455-1468, 2021
442021
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