ObjectiveThere has been widespread concern that so-called lockdown measures, including social distancing and school closures, could negatively impact children’s mental health. However, there has been little direct evidence of any association due to the paucity of longitudinal studies reporting mental health before and during the lockdown. This present study provides the first longitudinal examination of changes in childhood mental health, a key component of an urgently needed evidence base that can inform policy and practice surrounding the continuing response to the COVID-19 pandemic.MethodsMental health assessments on 168 children (aged 7.6–11.6 years) were taken before and during the UK lockdown (April–June 2020). Assessments included self-reports, caregiver reports, and teacher reports. Mean mental health scores before and during the UK lockdown were compared using mixed linear models.ResultsA significant increase in depression symptoms during the UK lockdown was observed, as measured by the Revised Child Anxiety and Depression Scale (RCADS) short form. CIs suggest a medium-to-large effect size. There were no significant changes in the RCADS anxiety subscale and Strengths and Difficulties Questionnaire emotional problems subscale.ConclusionsDuring the UK lockdown, children’s depression symptoms have increased substantially, relative to before lockdown. The scale of this effect has direct relevance for the continuation of different elements of lockdown policy, such as complete or partial school closures. This early evidence for the direct impact of lockdown must now be combined with larger scale epidemiological studies that establish which children are most at risk and tracks their future recovery.
The PyGaze toolbox is an open-source software package for Python, a high-level programming language. It is designed for creating eyetracking experiments in Python syntax with the least possible effort, and it offers programming ease and script readability without constraining functionality and flexibility. PyGaze can be used for visual and auditory stimulus presentation; for response collection via keyboard, mouse, joystick, and other external hardware; and for the online detection of eye movements using a custom algorithm. A wide range of eyetrackers of different brands (EyeLink, SMI, and Tobii systems) are supported. The novelty of PyGaze lies in providing an easy-to-use layer on top of the many different software libraries that are required for implementing eyetracking experiments. Essentially, PyGaze is a software bridge for eyetracking research.
Due to increasing ease of use and ability to quickly collect large samples, online behavioural research is currently booming. With this popularity, it is important that researchers are aware of who online participants are, and what devices and software they use to access experiments. While it is somewhat obvious that these factors can impact data quality, the magnitude of the problem remains unclear. To understand how these characteristics impact experiment presentation and data quality, we performed a battery of automated tests on a number of realistic set-ups. We investigated how different web-building platforms (Gorilla v.20190828, jsPsych v6.0.5, Lab.js v19.1.0, and psychoJS/PsychoPy3 v3.1.5), browsers (Chrome, Edge, Firefox, and Safari), and operating systems (macOS and Windows 10) impact display time across 30 different frame durations for each software combination. We then employed a robot actuator in realistic set-ups to measure response recording across the aforementioned platforms, and between different keyboard types (desktop and integrated laptop). Finally, we analysed data from over 200,000 participants on their demographics, technology, and software to provide context to our findings. We found that modern web platforms provide reasonable accuracy and precision for display duration and manual response time, and that no single platform stands out as the best in all features and conditions. In addition, our online participant analysis shows what equipment they are likely to use.
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