Assessment of non-directed computer-use behaviours in the home can indicate early cognitive impairment: A proof of principle longitudinal study.

OBJECTIVES: Computer-use behaviours can provide useful information about an individual's cognitive and functional abilities. However, little research has evaluated unaided and non-directed home computer-use. In this proof of principle study, we explored whether computer-use behaviours recorded during routine home computer-use i) could discriminate between individuals with subjective cognitive decline (SCD) and individuals with mild cognitive impairment (MCI); ii) were associated with cognitive and functional scores; and iii) changed over time. METHODS: Thirty-two participants with SCD (n = 18) or MCI (n = 14) (mean age = 72.53 years; female n = 19) participated in a longitudinal study in which their in-home computer-use behaviour was passively recorded over 7-9 months. Cognitive and functional assessments were completed at three time points: baseline; mid-point (4.5 months); and end point (month 7 to 9). RESULTS: Individuals with MCI had significantly slower keystroke speed and spent less time on the computer than individuals with SCD. More time spent on the computer was associated with better task switching abilities. Faster keystroke speed was associated with better visual attention, recall, recognition, task inhibition, and task switching. No significant change in computer-use behaviour was detected over the study period. CONCLUSION: Passive monitoring of computer-use behaviour shows potential as an indicator of cognitive abilities, and can differentiate between people with SCD and MCI. Future studies should attempt to monitor computer-use behaviours over a longer time period to capture the onset of cognitive decline, and thus could inform timely therapeutic interventions.Supplemental data for this article can be accessed online at http://dx.doi.org/10.1080/13607863.2022.2036946.

Quantification of structural changes in the corpus callosumin children with profound hypoxic-ischaemic brain injury.

BACKGROUND: Birth-related acute profound hypoxic-ischaemic brain injury has specific patterns of damage including the paracentral lobules. OBJECTIVE: To test the hypothesis that there is anatomically coherent regional volume loss of the corpus callosum as a result of this hemispheric abnormality. MATERIALS AND METHODS: Study subjects included 13 children with proven acute profound hypoxic-ischaemic brain injury and 13 children with developmental delay but no brain abnormalities. A computerised system divided the corpus callosum into 100 segments, measuring each width. Principal component analysis grouped the widths into contiguous anatomical regions. We conducted analysis of variance of corpus callosum widths as well as support vector machine stratification into patient groups. RESULTS: There was statistically significant narrowing of the mid-posterior body and genu of the corpus callosum in children with hypoxic-ischaemic brain injury. Support vector machine analysis yielded over 95% accuracy in patient group stratification using the corpus callosum centile widths. CONCLUSION: Focal volume loss is seen in the corpus callosum of children with hypoxic-ischaemic brain injury secondary to loss of commissural fibres arising in the paracentral lobules. Support vector machine stratification into the hypoxic-ischaemic brain injury group or the control group on the basis of corpus callosum width is highly accurate and points towards rapid clinical translation of this technique as a potential biomarker of hypoxic-ischaemic brain injury.

A comparison of experience sampled hay fever symptom severity across rural and urban areas of the UK.

Hay fever affects people differently and can change over a lifetime, but data is lacking on how environmental factors may influence this. This study is the first to combine atmospheric sensor data with real-time, geo-positioned hay fever symptom reports to examine the relationship between symptom severity and air quality, weather and land use. We study 36145 symptom reports submitted over 5 years by over 700 UK residents using a mobile application. Scores were recorded for nose, eyes and breathing. Symptom reports are labelled as urban or rural using land-use data from the UK's Office for National Statistics. Reports are compared with AURN network pollution measurements and pollen and meteorological data taken from the UK Met Office. Our analysis suggests urban areas record significantly higher symptom severity for all years except 2017. Rural areas do not record significantly higher symptom severity in any year. Additionally, symptom severity correlates with more air quality markers in urban areas than rural areas, indicating that differences in allergy symptoms may be due to variations in the levels of pollutants, pollen counts and seasonality across land-use types. The results suggest that a relationship exists between urban surroundings and hay fever symptoms.

UK daily meteorology, air quality, and pollen measurements for 2016-2019, with estimates for missing data.

In recent years, quantifying the impacts of detrimental air quality has become a global priority for researchers and policy makers. At present, the systems and methodologies supporting the collection and manipulation of this data are difficult to access. To support studies quantifying the interplay between common gaseous and particulate pollutants with meteorology and biological particles, this paper presents a comprehensive data-set containing daily air quality readings from the Automatic Urban and Rural Network, and pollen and weather data from Met Office monitoring stations, in the years 2016 to 2019 inclusive, for the United Kingdom. We describe (1) the sources from which the data were collected, (2) the methods used for the data cleaning process and (3) how issues related to missing values and sparse regional coverage were addressed. The resulting data-set is designed to be used 'as is' by those using air quality data for research; we also describe and provide open access to the methods used for curating the data to allow modification of or addition to the data-set.

Which computer-use behaviours are most indicative of cognitive decline? Insights from an expert reference group.

Computer use is becoming ubiquitous among older adults. As computer use depends on complex cognitive functions, measuring individuals' computer-use behaviours over time may provide a way to detect changes in their cognitive functioning. However, it is uncertain which computer-use behaviour changes are most likely to be associated with declines of particular cognitive functions. To address this, we convened six experts from clinical and cognitive neurosciences to take part in two workshops and a follow-up survey to gain consensus on which computer-use behaviours would likely be the strongest indicators of cognitive decline. This resulted in a list of 21 computer-use behaviours that the majority of experts agreed would offer a 'strong indication' of decline in a specific cognitive function, across Memory, Executive function, Language and Perception and Action domains. This list enables a hypothesis-driven approach to analysing computer-use behaviours predicted to be markers of cognitive decline.