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Tensorial Principal Component Analysis in Detecting Temporal Trajectories of Purchase Patterns in Loyalty Card Data: Retrospective Cohort Study

Tensorial Principal Component Analysis in Detecting Temporal Trajectories of Purchase Patterns in Loyalty Card Data: Retrospective Cohort Study

However, when the data are arranged by time of purchase, they are longitudinal, and the third dimension is time, including information on, for example, time trends, seasonality, or change points. Therefore, loyalty card data are longitudinal data, having dimensions in both time and product groups, and can be seen as a tensor. Tensorial data are multidimensional array data.

Reija Autio, Joni Virta, Klaus Nordhausen, Mikael Fogelholm, Maijaliisa Erkkola, Jaakko Nevalainen

J Med Internet Res 2023;25:e44599

Seasonality of Hashimoto Thyroiditis: Infodemiology Study of Google Trends Data

Seasonality of Hashimoto Thyroiditis: Infodemiology Study of Google Trends Data

Our study examined the seasonality of HT Google-related searches in Europe using GT data, with the goal to explore whether there was a seasonal characteristics of Google searches regarding HT, examine the potential impact of the countries’ geographic location on the potential seasonality, and identify possible modifiable risk factors for HT, thereby inspiring future research on the topic.

Robert Marcec, Josip Stjepanovic, Robert Likic

JMIR Bioinform Biotech 2022;3(1):e38976

Confounding Effect of Undergraduate Semester–Driven “Academic" Internet Searches on the Ability to Detect True Disease Seasonality in Google Trends Data: Fourier Filter Method Development and Demonstration

Confounding Effect of Undergraduate Semester–Driven “Academic" Internet Searches on the Ability to Detect True Disease Seasonality in Google Trends Data: Fourier Filter Method Development and Demonstration

Recognizing and trying to understand the driving forces behind disease seasonality helps deliver insights that might lead to more effective prevention or treatment of seasonally modulated conditions. Google Trends has become a popular tool for investigation of disease seasonality. An early use in this area was rapid real-time surveillance of influenza-like illness [15], something that continues to be worked on to augment conventional public health surveillance measures [16].

Timber Gillis, Scott Garrison

JMIR Infodemiology 2022;2(2):e34464

Sustained Reductions in Online Search Interest for Communicable Eye and Other Conditions During the COVID-19 Pandemic: Infodemiology Study

Sustained Reductions in Online Search Interest for Communicable Eye and Other Conditions During the COVID-19 Pandemic: Infodemiology Study

Online searches and social media reflect the clinical seasonality and epidemics of conjunctivitis [37-40]. Previously, we found evidence that during the start of the COVID-19 pandemic (through April 2020), some ocular-related terms (in multiple languages on a worldwide level) showed an increased search trend. These terms included “burning,” “sore,” and “red” eyes [5].

Michael S Deiner, Gerami D Seitzman, Gurbani Kaur, Stephen D McLeod, James Chodosh, Thomas M Lietman, Travis C Porco

JMIR Infodemiology 2022;2(1):e31732

Importance of Getting Enough Sleep and Daily Activity Data to Assess Variability: Longitudinal Observational Study

Importance of Getting Enough Sleep and Daily Activity Data to Assess Variability: Longitudinal Observational Study

Our secondary goals are to investigate whether there is a relationship between sleep quality, physical activity, and heart rate and whether individuals who exhibit similar activity and sleep patterns in general and in relation to seasonality can be clustered together. We address the secondary goals through the following three research questions: Is there a relationship between sleep quality, physical activity, and heart rate?

María Óskarsdóttir, Anna Sigridur Islind, Elias August, Erna Sif Arnardóttir, François Patou, Anja M Maier

JMIR Form Res 2022;6(2):e31807

Global Public Interests and Dynamic Trends in Osteoporosis From 2004 to 2019: Infodemiology Study

Global Public Interests and Dynamic Trends in Osteoporosis From 2004 to 2019: Infodemiology Study

Cosinor analysis was utilized to investigate the seasonal patterns of RSV for “osteoporosis,” where the RSV was regressed onto a sine and a cosine term of transformations of the time variable and represented as a sine curve that could be applied to test the seasonality [26,27]. A time-series plot was used to demonstrate the consistency in seasonal patterns.

Peng Wang, Qing Xu, Rong-Rong Cao, Fei-Yan Deng, Shu-Feng Lei

J Med Internet Res 2021;23(7):e25422

Seasonality Patterns of Internet Searches on Mental Health: Exploratory Infodemiology Study

Seasonality Patterns of Internet Searches on Mental Health: Exploratory Infodemiology Study

In addition, studies have reported seasonality patterns for anxiety disorders [10], obsessive-compulsive disorder (OCD) [10], and psychotic disorders [11]. Most recently, evidence showed that seasonality patterns are similar across different climate zones [1]. Until recently, the sampling of populations for information on mental health was mostly conducted using epidemiological surveys, which have been widely used to study evidence on the level of disorders in the general population [12,13].

Noam Soreni, Duncan H Cameron, David L Streiner, Karen Rowa, Randi E McCabe

JMIR Ment Health 2019;6(4):e12974