OWLET: An automated, open-source method for infant gaze tracking using smartphone and webcam recordings

Groundbreaking insights into the origins of the human mind have been garnered through the study of eye movements in preverbal subjects who are unable to explain their thought processes. Developmental research has largely relied on in-lab testing with trained experimenters. This constraint provides a narrow window into infant cognition and impedes large-scale data collection in families from diverse socioeconomic, geographic, and cultural backgrounds. Here we introduce a new open-source methodology for automatically analyzing infant eye-tracking data collected on personal devices in the home. Using algorithms from computer vision, machine learning, and ecological psychology, we develop an online webcam-linked eye tracker (OWLET) that provides robust estimation of infants' point of gaze from smartphone and webcam recordings of infant assessments in the home. We validate OWLET in a large sample of 7-month-old infants (N = 127) tested remotely, using an established visual attention task. We show that this new method reliably estimates infants' point-of-gaze across a variety of contexts, including testing on both computers and mobile devices, and exhibits excellent external validity with parental-report measures of attention. Our platform fills a significant gap in current tools available for rapid online data collection and large-scale assessments of cognitive processes in infants. Remote assessment addresses the need for greater diversity and accessibility in human studies and may support the ecological validity of behavioral experiments. This constitutes a critical and timely advance in a core domain of developmental research and in psychological science more broadly.

The validation of online webcam-based eye-tracking: The replication of the cascade effect, the novelty preference, and the visual world paradigm

The many benefits of online research and the recent emergence of open-source eye-tracking libraries have sparked an interest in transferring time-consuming and expensive eye-tracking studies from the lab to the web. In the current study, we validate online webcam-based eye-tracking by conceptually replicating three robust eye-tracking studies (the cascade effect, n = 134, the novelty preference, n = 45, and the visual world paradigm, n = 32) online using the participant's webcam as eye-tracker with the WebGazer.js library. We successfully replicated all three effects, although the effect sizes of all three studies shrank by 20-27%. The visual world paradigm was conducted both online and in the lab, using the same participants and a standard laboratory eye-tracker. The results showed that replication per se could not fully account for the effect size shrinkage, but that the shrinkage was also due to the use of online webcam-based eye-tracking, which is noisier. In conclusion, we argue that eye-tracking studies with relatively large effects that do not require extremely high precision (e.g., studies with four or fewer large regions of interest) can be done online using the participant's webcam. We also make recommendations for how the quality of online webcam-based eye-tracking could be improved.

e-Babylab: An open-source browser-based tool for unmoderated online developmental studies

The COVID-19 pandemic massively changed the context and feasibility of developmental research. This new reality, as well as considerations about sample diversity and naturalistic settings for developmental research, highlights the need for solutions for online studies. In this article, we present e-Babylab, an open-source browser-based tool for unmoderated online studies targeted for young children and babies. e-Babylab offers an intuitive graphical user interface for study creation and management of studies, users, participant data, and stimulus material, with no programming skills required. Various kinds of audiovisual media can be presented as stimuli, and possible measures include webcam recordings, audio recordings, key presses, mouse-click/touch coordinates, and reaction times. An additional feature of e-Babylab is the possibility to administer short adaptive versions of MacArthur-Bates Communicative Development Inventories (Chai et al. Journal of Speech, Language, and Hearing Research, 63, 3488-3500, 2020). Information pages, consent forms, and participant forms are customizable. e-Babylab has been used with a variety of measures and paradigms in over 12 studies with children aged 12 months to 8 years (n = 1516). We briefly summarize some results of these studies to demonstrate that data quality, participant engagement, and overall results are comparable between laboratory and online settings. Finally, we discuss helpful tips for using e-Babylab and present plans for upgrades.

Autistic traits are associated with individual differences in finger tapping: an online study

In a novel online study, we explored whether finger tapping differences are evident in people with autistic traits in the general population. We hypothesised that those with higher autistic traits would show more impairment in finger tapping, and that age would moderate tapping output. The study included a non-diagnosed population of 159 participants aged 18-78 who completed an online measure of autistic traits (the AQ-10) and a measure of finger tapping (the FTT). Results showed those with higher AQ-10 scores recorded lower tapping scores in both hands. Moderation analysis showed younger participants with more autistic traits recorded lower tapping scores for the dominant hand. This suggests motor differences seen in autism studies are evident in the general population.

Stress research during the COVID-19 pandemic and beyond

The COVID-19 pandemic confronts stress researchers in psychology and neuroscience with unique challenges. Widely used experimental paradigms such as the Trier Social Stress Test feature physical social encounters to induce stress by means of social-evaluative threat. As lockdowns and contact restrictions currently prevent in-person meetings, established stress induction paradigms are often difficult to use. Despite these challenges, stress research is of pivotal importance as the pandemic will likely increase the prevalence of stress-related mental disorders. Therefore, we review recent research trends like virtual reality, pre-recordings and online adaptations regarding their usefulness for established stress induction paradigms. Such approaches are not only crucial for stress research during COVID-19 but will likely stimulate the field far beyond the pandemic. They may facilitate research in new contexts and in homebound or movement-restricted participant groups. Moreover, they allow for new experimental variations that may advance procedures as well as the conceptualization of stress itself. While posing challenges for stress researchers undeniably, the COVID-19 pandemic may evolve into a driving force for progress eventually.

Using Security Questions to Link Participants in Longitudinal Data Collection

Anonymous data collection systems are often necessary when assessing sensitive behaviors but can pose challenges to researchers seeking to link participants over time. To assist researchers in anonymously linking participants, we outlined and tested a novel security question linking (security question linking; SEEK) method. The SEEK method includes four steps: (1) data management and standardization, (2) many-to-many matching, (3) fuzzy matching, and (4) rematching and verification. The method is demonstrated in SAS with two samples from a longitudinal study of adolescent dating violence. After an initial assessment during a laboratory visit, participants were asked to complete an online assessment either (a) once, 3 months later (Sample 1, n = 60), or (b) three times at 1-month intervals (Sample 2, n = 140). Demographics, eye color, and responses to nine security questions were used as key variables to link responses from the laboratory and online follow-up assessments. The rates of matched cases were 100% in Sample 1 and from 94.3 to 98.3% in Sample 2. To quantify the confidence in the data quality of successfully matched pairs, we reported the means and standard deviations of the number of matched security questions. In addition, we reported the rank order and counts of the mismatched components in key variables. Results indicate that the SEEK method provides a feasible and reliable solution to link responses in longitudinal studies with sensitive questions.

A thousand studies for the price of one: Accelerating psychological science with Pushkin

Half of the world's population has internet access. In principle, researchers are no longer limited to subjects they can recruit into the laboratory. Any study that can be run on a computer or mobile device can be run with nearly any demographic anywhere in the world, and in large numbers. This has allowed scientists to effectively run hundreds of experiments at once. Despite their transformative power, such studies remain rare for practical reasons: the need for sophisticated software, the difficulty of recruiting so many subjects, and a lack of research paradigms that make effective use of their large amounts of data, due to such realities as that they require sophisticated software in order to run effectively. We present Pushkin: an open-source platform for designing and conducting massive experiments over the internet. Pushkin allows for a wide range of behavioral paradigms, through integration with the intuitive and flexible jsPsych experiment engine. It also addresses the basic technical challenges associated with massive, worldwide studies, including auto-scaling, extensibility, machine-assisted experimental design, multisession studies, and data security.