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.

Self-report dominates research that considers the impact of technology on people and society. However, errors of measurement may obscure any genuine associations between technology use and mental health. We explored how different ways of measuring technology use, through psychometric scales, subjective estimates and objective logs leads to highly distorted associations between screen-time and health. Across two pre-registered designs, including: iPhone (n=199) and Android (n=46), we observed that measuring smartphone use via self-reports inflates any effect size between smartphone use and mental health symptomology (depression, anxiety, and stress). The size of the relationship was fourfold in study one, and nearly threefold in study two when employing a smartphone addiction scale in comparison to objective logs. Consequently, and beyond smartphones, any research which administers self-reports as a measure of problematic behaviors is likely to have findings which exaggerate any associations with mental health.

Psychological science has spent many years attempting to understand the impact of new technology on people and society. However, the frequent use of self-report methods to quantify patterns of usage remain limited when attempting to capture subtle nuances of human-computer interaction. This has become particularly problematic for devices like smartphones that are used frequently and for a variety of purposes. While commercial apps can provide an element of objectivity, these are ‘closed’ and cannot be adapted to deliver a researcher-focused ‘open’ platform that allows for straightforward replication. Therefore, we have developed a freely available android app, which provides accurate, highly detailed, and customisable accounts of smartphone usage without compromising participants privacy. Further recommendations and code are provided in order to assist with data analysis.

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.