The Smartphone Psychology Manifesto

By Geoffrey F. Miller. Perspectives on Psychological Science, 2012

604 citations recorded by the source corpus.

Subfields: Applied Psychology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/a8a2b4efad3b0f5f64c46421a9786a9c2df9bd36

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In Applied Psychology

In Human-Computer Interaction

Citations in the corpus

Lab And/Or Field? Measuring Personality Processes and Their Social Consequences (2015, background): “At the same time, the future likely holds the biggest scientific leaps forward in this domain given the surge in technical progress in smartphone and wearable sensing technologies (Chittaranjan, Blom, & Gatica-Perez, 2013; Lathia et al., 2013; Miller, 2012; Raento et al., 2009).”
UvA-DARE ( Digital Academic Repository ) Simpson ' s paradox in psychological science : a practical guide (2017, background): “For instance, the advent of smartphone technology opens up a variety of means to relatively non-invasively collect psychological data outside of the lab within the same individual over time (cf. Miller, 2012).”
Measuring Large-Scale Social Networks with High Resolution (2014, background): “They allow for automatic collection of sensor data including GPS, WiFi, Bluetooth, calls, SMS, battery, and application usage [19].”
Twitter Analysis: Studying US Weekly Trends in Work Stress and Emotion (2016, background): “Historically, innovative data collection methods have held promise for advancing psychological research paradigms and meaningfully improving our knowledge of human beings (Miller, 2012).”
Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study (2013, background): “Previous research on the views of healthy adults as well as at-risk and chronically ill participants also suggested that monitoring and tracking features are acceptable and valuable [1,3,4,9].”
Choosing prediction over explanation in psychology: Lessons from machine learning (2017, background): “One might suppose that having access to enormous data-sets would make it much easier to build highly predictive models, thereby enabling researchers to solve with ease problems that used to be nigh impossible in the days before smartphone sensors, Amazon Mechanical Turk, and Twitter (Miller, 2012; Y”
Using Smartphones to Collect Behavioral Data in Psychological Science: Opportunities, Practical Considerations, and Challenges (2016, positive): “Together, these features mean that smart-phones have the potential to revolutionize how behavioral data are collected in psychological science (Gosling & Mason, 2015; Miller, 2012).”
Putting the ‘app’ in Happiness: A Randomised Controlled Trial of a Smartphone-Based Mindfulness Intervention to Enhance Wellbeing (2016, background): “Miller (2012) claims the formidability of smartphones is enough to ‘‘transform psychology even more profoundly than PCs and brain imaging’’ (p. 221).”
From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices (2016, background): “The collection of data related to the physical activity performed is very relevant to analyse the lifestyle and physiological characteristics of people [98].”
Using multi-item psychometric scales for research and practice in human resource management (2018, background): “Increasingly, electronic questionnaires are being administered on handheld digital devices such as PDAs, smartphones, and tablets, and this approach has great research potential (Miller, 2012).”
The generalizability crisis (2019, background): “…routines that we carry with us for large swathes of the day—that psychologists are utilizing to predict a variety of outcomes, from social interaction, personality, mood, to general health (Davidson, 2020; Ellis, 2020; Miller, 2012; Piwek et al., 2016; Harari et al., 2019; Stachl et al., 2020).”
Beyond Self-Report: Tools to Compare Estimated and Real-World Smartphone Use (2015, background): “Trull and Ebner-Priemer [9] and Miller [10] argue that smartphone data have a great deal to offer as a research tool in psychology, yet comparatively little research utilises objective smartphone data.”
Ambulatory Assessment: New adventures in characterizing dynamic processes (2016, neutral): “Research that incorporates such devices is still rare, and largely conducted in engineering and computer science fields (e.g., see Glenn & Monteith, 2014; Miller, 2012).”
"Just Another Tool for Online Studies” (JATOS): An Easy Solution for Setup and Management of Web Servers Supporting Online Studies (2015, background): “It is especially useful in cases where laboratory-based data collection is too expensive or simply not feasible, like studies of particularly large or diverse populations [3] or of micro-longitudinal data [1,4].”