Enhancing Understanding of Digital Traces

“How did Galileo demonstrate the veracity of the copernican view of the sun centred universe? Well, the main advances were incremental in their ability to refine glass into lenses, not very sexy, except he could use that to make his own telescopes and see the moons of Jupiter.” - Dr Steven Hyman. (Cahalan, 2019, p 283) Technological advances have repeatedly provided new tools for psychologists to conduct scientific inquiry. Theories regarding cognition, perception and behaviour have been more rigorously falsified or at least tested thanks to computers, electroencephalographs and associated big data sets. Smartphones are among the latest technologies being used for psychological research. Portable devices like these could provide unparalleled access into peoples’real-world behaviour via highly ecologically valid data. However, there are significant obstacles for psychologists to overcome before the potential of smartphones can be fully realised. Part one of this thesis documents multiple newmethodsthat concern the development of smartphone apps for psychological research and provides guidance to ensure subsequent research is compliant with open science practices while maintaining participant privacy.In part two, developed apps are used in research designsthat reveal inconsistencies between objective and self-report assessments ofsmartphone usage. Specifically, objective methodsof measuring smartphone usage reduce the associations to almost zero between ‘screen time’ and health when compared with subjective estimates. Thisfurther demonstrates how the interdisciplinary application ofsmartphone technology can transform applied psychology or at least increase the methodological rigor

Do smartphone usage scales predict behavior?

Understanding how people use technology remains important, particularly when measuring the impact this might have on individuals and society. However, despite a growing body of resources that can quantify smartphone use, research within psychology and social science overwhelmingly relies on self-reported assessments. These have yet to convincingly demonstrate an ability to predict objective behavior. Here, and for the first time, we compare a variety of smartphone use and ‘addiction’ scales with objective behaviors derived from Apple’s Screen Time application. While correlations between psychometric scales and objective behavior are generally poor, single estimates and measures that attempt to frame technology use as habitual rather than ‘addictive’ correlate more favorably with subsequent behavior. We conclude that existing self-report instruments are unlikely to be sensitive enough to accurately predict basic technology use related behaviors. As a result, conclusions regarding the psychological impact of technology are unreliable when relying solely on these measures to quantify typical usage

A simple location-tracking app for psychological research

Location data gathered from a variety of sources is particularly valuable when it comes to understanding individuals and groups. However, much of this work relies on participants’ active engagement to regularly report their location. More recently, smartphones have been used to assist with this process, but while commercial smartphone applications are available, these are often expensive and not designed with researchers in mind. In order to overcome these and other related issues, we have developed a freely available Android application that logs location accurately, stores data securely, and ensures participants can provide consent or withdraw from a study at any time. Further recommendations and R code are provided to assist with subsequent data analysis

Quantifying Smartphone “Use”: Choice of Measurement Impacts Relationships Between “Usage” and Health

Problematic smartphone scales and duration estimates of use dominate research that considers the impact of smartphones on people and society. However, issues with conceptualization and subsequent measurement can obscure genuine associations between technology use and health. Here, we consider whether different ways of measuring “smartphone use,” notably through problematic smartphone use (PSU) scales, subjective estimates, or objective logs, lead to contrasting associations between mental and physical health. Across two samples including iPhone (n = 199) and Android (n = 46) users, we observed that measuring smartphone interactions with PSU scales produced larger associations between mental health when compared with subjective estimates or objective logs. Notably, the size of the relationship was fourfold in Study 1, and almost three times as large in Study 2, when relying on a PSU scale that measured smartphone “addiction” instead of objective use. Further, in regression models, only smartphone “addiction” scores predicted mental health outcomes, whereas objective logs or estimates were not significant predictors. We conclude that addressing people’s appraisals including worries about their technology usage is likely to have greater mental health benefits than reducing their overall smartphone use. Reducing general smartphone use should therefore not be a priority for public health interventions at this time

Development of the Reporting Information about Networks and Groups (RING) task: a method for eliciting information from memory about associates, groups, and networks

Purpose Eliciting detailed and comprehensive information about the structure, organisation and relationships between individuals involved in organised crime gangs, terrorist cells and networks is a challenge in investigations and debriefings. Drawing on memory theory, the purpose of this paper is to develop and test the Reporting Information about Networks and Groups (RING) task, using an innovative piece of information elicitation software. Design/methodology/approach Using an experimental methodology analogous to an intelligence gathering context, participants (n=124) were asked to generate a visual representation of the “network” of individuals attending a recent family event using the RING task. Findings All participants successfully generated visual representations of the relationships between people attending a remembered social event. The groups or networks represented in the RING task output diagrams also reflected effective use of the software functionality with respect to “describing” the nature of the relationships between individuals. Practical implications The authors succeeded in establishing the usability of the RING task software for reporting detailed information about groups of individuals and the relationships between those individuals in a visual format. A number of important limitations and issues for future research to consider are examined. Originality/value The RING task is an innovative development to support the elicitation of targeted information about networks of people and the relationships between them. Given the importance of understanding human networks in order to disrupt criminal activity, the RING task may contribute to intelligence gathering and the investigation of organised crime gangs and terrorist cells and networks