| The rise of consumer health wearables: promises and barriers L Piwek, DA Ellis, S Andrews, A Joinson PLoS Medicine, 2016 | 1197 | 2016 |
| 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 | 506 | 2015 |
| Do smartphone usage scales predict behaviour DA Ellis, BI Davidson, H Shaw, K Geyer International Journal of Human-Computer Studies, 2019 | 320 | 2019 |
| 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 | 201 | 2021 |
| Are smartphones really that bad? Improving the psychological measurement of technology-related behaviors DA Ellis Computers in Human Behavior 97, 60-66, 2019 | 198 | 2019 |
| 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 | 198 | 2017 |
| 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 | 194 | 2020 |
| 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 | 167 | 2017 |
| 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 | 154 | 2015 |
| 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 | 139 | 2018 |
| 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 | 138 | 2019 |
| 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 | 130 | 2018 |
| Digital detox: The effect of smartphone abstinence on mood, anxiety, and craving TDW Wilcockson, AM Osborne, DA Ellis Addictive behaviors 99, 106013, 2019 | 107 | 2019 |
| 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 | 87 | 2016 |
| Weekday affects attendance rate for medical appointments: large-scale data analysis and implications DA Ellis, R Jenkins PloS one 7 (12), e51365, 2012 | 71 | 2012 |
| 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 | 70 | 2017 |
| 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 | 47 | 2016 |
| 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 | 45 | 2013 |
| 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 | 44 | 2021 |
Heather ShawLecturer at Lancaster University在 lancaster.ac.uk 的电子邮件经过验证
