Abstract
Introduction
Initial download and use of sleep tracking is very high, but prolonged use is very low. Poor prolonged use may be attributable to several factors such as engagement, ...functionality, aesthetics, information, and recommendation. We appraised these five factors in 16 consumer- and research/medical- grade digital sleep devices.
Methods
Three reviewers independently assessed 16 consumer- and medical-grade sleep digital devices using the Mobile Application Rating Scale (MARS) App quality ratings, which measures engagement (engagement, entertainment, interest, customization, interactivity, target group), functionality (functionality, performance, ease of use, navigation, gestural design), aesthetics (layout, graphics, visual appeal), information (Accuracy. Goals, Quality of information, Quantity of information, Visual information, Credibility, and Evidence base) and recommended on a Likert scale, with 1- Inadequate to 5 Excellent. Each subcategory is rated on a 1-5 Likert scale which is summed for each category: engagement (30), functionality (25), aesthetics (15), information (35) and recommended (yes or no).
Results
Devices that had the highest engagement score were Fitbit (27), Apple Watch (27), Garmin (27), and Dreem 2 headband (25.5). Apple Watch (30) had highest score; while Fitbit (13), Apple Watch (13), Garmin (13), Samsung Gear (13) had highest aesthetic score. While for information, ActiGraph (35), SOMNOwatch plus (35), CleveMed SleepView Monitor (35), CleveMed Sapphire PSG (35), SOMNOscreen plus (35), Nox T3 Sleep Monitor (35) and Nox A1 PSG System (35) had the highest ratings. The Dreem 2 headband has the potential induce prolong use among users with and without sleep disorders, based on high scores on engagement (25.5), Functionality (20.5), and Information (26.5).
Conclusion
Consumer- and research-grade digital devices that measure sleep have varying levels of engagement, functionality, aesthetics, information and recommendations to facilitate prolong use. Consumer grade devices had higher engagement, functionality and aesthetics scores, while research grade devices had higher information and recommendation scores. If consumer- and research-grade devices are to have prolonged use, standardization is needed across the five MARS components.
Support
K01HL135452, R01MD007716, R01HL142066, and K07AG052685
People with COVID-19 might have sustained postinfection sequelae. Known by a variety of names, including long COVID or long-haul COVID, and listed in the ICD-10 classification as post-COVID-19 ...condition since September, 2020, this occurrence is variable in its expression and its impact. The absence of a globally standardised and agreed-upon definition hampers progress in characterisation of its epidemiology and the development of candidate treatments. In a WHO-led Delphi process, we engaged with an international panel of 265 patients, clinicians, researchers, and WHO staff to develop a consensus definition for this condition. 14 domains and 45 items were evaluated in two rounds of the Delphi process to create a final consensus definition for adults: post-COVID-19 condition occurs in individuals with a history of probable or confirmed SARS-CoV-2 infection, usually 3 months from the onset, with symptoms that last for at least 2 months and cannot be explained by an alternative diagnosis. Common symptoms include, but are not limited to, fatigue, shortness of breath, and cognitive dysfunction, and generally have an impact on everyday functioning. Symptoms might be new onset following initial recovery from an acute COVID-19 episode or persist from the initial illness. Symptoms might also fluctuate or relapse over time. A separate definition might be applicable for children. Although the consensus definition is likely to change as knowledge increases, this common framework provides a foundation for ongoing and future studies of epidemiology, risk factors, clinical characteristics, and therapy.
Likert scales are useful for collecting data on attitudes and perceptions from large samples of people. In particular, they have become a well-established tool in soundscape studies for conducting
...surveys to determine how people experience urban public spaces. However, it is still unclear whether the metrics of the scales are consistently interpreted during a typical assessment task. The current work aims at identifying some general trends in the interpretation of Likert scale metrics and introducing a procedure for the derivation of metric corrections by analyzing a case study dataset of 984 soundscape assessments across 11 urban locations in London. According to ISO/TS 12913-2:2018, soundscapes can be assessed through the scaling of 8 dimensions: pleasant, annoying, vibrant, monotonous, eventful, uneventful, calm, and chaotic. The hypothesis underlying this study is that a link exists between correlations across the percentage of assessments falling in each Likert scale category and a dilation/compression factor affecting the interpretation of the scales metric. The outcome of this metric correction value derivation is introduced for soundscape, and a new projection of the London soundscapes according to the corrected circumplex space is compared with the initial ISO circumplex space. The overall results show a general non-equidistant interpretation of the scales, particularly on the vibrant-monotonous direction. The implications of this correction have been demonstrated through a Linear Ridge Classifier task for predicting the London soundscape responses using objective acoustic parameters, which shows significant improvement when applied to the corrected data. The results suggest that the corrected values account for the non-equidistant interpretation of the Likert metrics, thereby allowing mathematical operations to be viable when applied to the data.
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