Designing Robust Models for Behaviour Prediction Using Sparse Data from Mobile Sensing

2021 ◽  
Vol 2 (4) ◽  
pp. 1-33
Author(s):  
Seyma Kucukozer-Cavdar ◽  
Tugba Taskaya-Temizel ◽  
Abhinav Mehrotra ◽  
Mirco Musolesi ◽  
Peter Tino
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Impact ◽  
Contextual Information ◽  
Working Hours ◽  
Office Workers ◽  
Estimation Model ◽  
Work Related ◽  
Generalised Linear Mixed Model ◽  
Rest Breaks

Understanding in which circumstances office workers take rest breaks is important for delivering effective mobile notifications and make inferences about their daily lifestyle, e.g., whether they are active and/or have a sedentary life. Previous studies designed for office workers show the effectiveness of rest breaks for preventing work-related conditions. In this article, we propose a hybrid personalised model involving a kernel density estimation model and a generalised linear mixed model to model office workers’ available moments for rest breaks during working hours. We adopt the experience-based sampling method through which we collected office workers’ responses regarding their availability through a mobile application with contextual information extracted by means of the mobile phone sensors. The experiment lasted 10 workdays and involved 19 office workers with a total of 528 responses. Our results show that time, location, ringer mode, and activity are effective features for predicting office workers’ availability. Our method can address sparse sample issues for building individual predictive behavioural models based on limited and unbalanced data. In particular, the proposed method can be considered as a potential solution to the “cold-start problem,” i.e., the negative impact of the lack of individual data when a new application is installed.

scholarly journals Burnout syndrome among psychiatric trainees in 22 countries: Risk increased by long working hours, lack of supervision, and psychiatry not being first career choice

2016 ◽  
Vol 32 ◽  
pp. 34-41 ◽  
Author(s):  
N. Jovanović ◽  
A. Podlesek ◽  
U. Volpe ◽  
E. Barrett ◽  
S. Ferrari ◽  
...  
Keyword(s):  
Career Choice ◽  
Online Survey ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Working Hours ◽  
Maslach Burnout Inventory ◽  
Burnout Syndrome ◽  
Related Factors ◽  
Long Working Hours ◽  
Work Related

AbstractBackgroundPostgraduate medical trainees experience high rates of burnout, but evidence regarding psychiatric trainees is missing. We aim to determine burnout rates among psychiatric trainees, and identify individual, educational and work-related factors associated with severe burnout.MethodsIn an online survey psychiatric trainees from 22 countries were asked to complete the Maslach Burnout Inventory (MBI-GS) and provide information on individual, educational and work-related parameters. Linear mixed models were used to predict the MBI-GS scores, and a generalized linear mixed model to predict severe burnout.ResultsThis is the largest study on burnout and training conditions among psychiatric trainees to date. Complete data were obtained from 1980 out of 7625 approached trainees (26%; range 17.8–65.6%). Participants were 31.9 (SD 5.3) years old with 2.8 (SD 1.9) years of training. Severe burnout was found in 726 (36.7%) trainees. The risk was higher for trainees who were younger (P < 0.001), without children (P = 0.010), and had not opted for psychiatry as a first career choice (P = 0.043). After adjustment for socio-demographic characteristics, years in training and country differences in burnout, severe burnout remained associated with long working hours (P < 0.001), lack of supervision (P < 0.001), and not having regular time to rest (P = 0.001). Main findings were replicated in a sensitivity analysis with countries with response rate above 50%.ConclusionsBesides previously described risk factors such as working hours and younger age, this is the first evidence of negative influence of lack of supervision and not opting for psychiatry as a first career choice on trainees’ burnout.

scholarly journals Socioeconomic Conditions and Landowners’ Perception Affect the Intention to Restore Polylepis Forests in the Central Andes of Peru

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 118
Author(s):  
Lunel Joseph ◽  
Raúl Marino Yaranga Cano ◽  
Marco Arizapana-Almonacid ◽  
Marcela Venelli Pyles ◽  
Flávia Freire de Siqueira ◽  
...  
Keyword(s):  
Rural Communities ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Impact ◽  
Positive Impact ◽  
Central Andes ◽  
Socioeconomic Conditions ◽  
Native Flora ◽  
The Family ◽  
Andes Region

Research Highlights: Families more dependent on crops as the main source of income of properties have a greater intention of restoring Polylepis forest areas. However, this intention reduces with the increase of family dependence on subsistence products supplied by Polylepis forests. Properties where the chances of restoration of Polylepis forests are greater are those where the educational and technical level is better. Objectives: We aimed to comprehend which socioeconomic factors of rural properties and families’ perception were determinant for the intention to restore Polylepis forests in the Central Andes region of Peru. Material and Methods: We collected data through visits and the application of questionnaires. We selected 13 rural communities in the Tulumayo River Basin. We randomly sampled 10 to 20 families in each community, depending on its size, totaling 200 families. We used generalized linear mixed model (GLMM) to test which variables affect the intention to restore the forest. Results: When crops are the main source of income in the property, the families have more intention to restore Polylepis areas, on the other hand, when Polylepis forests are an important source of products for the family subsistence, the intention to restore forests reduces, indicating that higher technological status has a positive impact on restoration. The perception that Polylepis forests are important for the existence of water sources had a positive impact on the families’ intention to restore the areas. However, the perception that Polylepis forests are important for native flora persistence had a negative impact on the intention to restore their areas. Conclusions: Our results showed that investment in improving the productivity of the properties and in the education of their landowners should increase the success of eventual programs for restoration of Polylepis forests.

scholarly journals 103 Periodontal Health and Sarcopenia: Cross-Sectional Evidence From A Cohort of 2040 Twin Volunteers

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
M B Zazzara ◽  
P M Wells ◽  
R C E Bowyer ◽  
M N Lochlainn ◽  
E J Thompson ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Frailty Index ◽  
Muscle Quality ◽  
Low Grade ◽  
Periodontal Health ◽  
Cross Sectional ◽  
Age Related ◽  
European Working ◽  
Generalised Linear Mixed Model

Abstract Introduction Periodontitis is a chronic inflammatory disease affecting the periodontium, ultimately leading to looseness and/or loss of teeth. Sarcopenia refers to age-related reduction in muscle mass and strength. Similar to periodontitis, chronic low-grade inflammation is thought to play a key role in its development. In addition, both increase in prevalence with advancing age. Despite known associations with other diseases involving a dysregulated inflammatory response, for example rheumatoid arthritis,, the relationship between periodontitis and sarcopenia, and whether they could be driven by similar processes, remains uncertain. The aim of this study was to explore the association between periodontitis and sarcopenia. Methods Observational study of 2040 adult volunteers [age 67.18 (12.17)] enrolled in the TwinsUK cohort study. Presence of tooth mobility and number of teeth lost were used to assess periodontal health. A binary variable was created to define periodontitis. Measurements of muscle strength, muscle quality/quantity and physical performance were used to assess sarcopenia. A categorical variable was created according to the European Working Group on Sarcopenia in Older People (EWGSOP2) consensus, to define sarcopenia (1: probable; 2: positive; 3: severe). Generalised linear mixed model analysis used on complete cases and age-matched (n = 1,288) samples to ascertain associations between periodontitis and sarcopenia. Results No significant association was found between periodontitis and sarcopenia in both the complete cases analysis and age-matched analysis. Results were consistent when analysis was adjusted for potential confounders including body mass index, frailty index, Mini Mental State Examination smoking, nutritional status and educational level. Conclusions This study found no significant association between periodontitis and sarcopenia in a cohort of 2040 adults. Although both periodontitis and sarcopenia have been linked to a dysregulated immune response and demonstrate an increase in prevalence with increasing age, our work is inconclusive due to the plethora of possible aetiopathogenetic pathways.

Factors influencing the occurrence of high ultimate pH in three muscles of lamb carcasses in Australia

2014 ◽  
Vol 54 (10) ◽  
pp. 1853 ◽  
Author(s):  
N. G. McPhail ◽  
J. L. Stark ◽  
A. J. Ball ◽  
R. D. Warner
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Rectus Femoris ◽  
Carcass Weight ◽  
Mixed Model Analysis ◽  
Factors Influencing ◽  
South Wales ◽  
Generalised Linear Mixed Model ◽  
Processing Plants ◽  
Few Data

Chilled lamb meat exported from Australia has, on occasions, been rejected by importing countries due to greening, after only 6 weeks of storage time. Greening is known to be more prevalent in high ultimate pH (pHu) beef meat (>5.9). There are few data available for lamb carcasses in Australia on the occurrence of high pHu meat, which may have an impact on the understanding and control of quality and greening during storage. The aim of this project was to determine the prevalence of, and influencing factors for, high pHu meat in a range of muscle types in lamb carcasses in Australia. Muscle pHu data were collected from a total of 1614 carcasses from 78 lots at four lamb processing plants in Victoria and New South Wales in autumn and spring of 2013. The pHu of the knuckle (rectus femoris), rack (longissimus) and blade (infraspinatus) was measured and data on carcass and lot characteristics were recorded. Data were subjected to restricted maximum likelihood and generalised linear mixed model analysis. The mean pHu of the knuckle, rack and shoulder were 6.06, 5.79 and 6.12 respectively, and the main factors influencing muscle pHu and occurrence of dark-cutting were breed, season, electrical stimulation and carcass weight. Merino lambs had a higher pHu in the blade and knuckle than did other breeds (P < 0.05, P < 0.01 respectively). Lambs processed in autumn had a higher predicted pHu in the blade and knuckle and a higher percentage dark-cutting (DC; pHu >6.0) for those muscles, than did those processed in spring (P < 0.05). Carcasses that had been electrically stimulated had a higher %DC and a higher pHu in all three muscles (P < 0.05). Carcass weight had a significant effect on the pHu of all three muscles (P < 0.001), with heavier carcasses having a lower pHu and lower %DC. The pHu of the rack was not a reliable predictor for the pHu in other muscles of the lamb carcass. In conclusion, the high occurrence of DC in the muscles, particularly the blade and knuckle, suggests that these muscles may be at risk for producing greening in the vacuum bag during storage.

scholarly journals Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review

2018 ◽  
Vol 147 ◽  
Author(s):  
A. Aswi ◽  
S. M. Cramb ◽  
P. Moraga ◽  
K. Mengersen
Keyword(s):  
Dengue Fever ◽  
Random Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Assessment Tool ◽  
Temporal Dynamics ◽  
Random Effect ◽  
Temperature And Precipitation ◽  
Generalised Linear Mixed Model ◽  
Spatio Temporal

AbstractDengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.

scholarly journals Thalamic white matter macrostructure and subnuclei volumes in Parkinson’s disease depression

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
R. Bhome ◽  
A. Zarkali ◽  
G. E. C. Thomas ◽  
J. E. Iglesias ◽  
J. H. Cole ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Neural Structure ◽  
Generalised Linear Mixed Model ◽  
Antidepressant Use ◽  
The Relationship

AbstractDepression is a common non-motor feature of Parkinson’s disease (PD) which confers significant morbidity and is challenging to treat. The thalamus is a key component in the basal ganglia-thalamocortical network critical to the pathogenesis of PD and depression but the precise thalamic subnuclei involved in PD depression have not been identified. We performed structural and diffusion-weighted imaging (DWI) on 76 participants with PD to evaluate the relationship between PD depression and grey and white matter thalamic subnuclear changes. We used a thalamic segmentation method to divide the thalamus into its 50 constituent subnuclei (25 each hemisphere). Fixel-based analysis was used to calculate mean fibre cross-section (FC) for white matter tracts connected to each subnucleus. We assessed volume and FC at baseline and 14–20 months follow-up. A generalised linear mixed model was used to evaluate the relationship between depression, subnuclei volume and mean FC for each thalamic subnucleus. We found that depression scores in PD were associated with lower right pulvinar anterior (PuA) subnucleus volume. Antidepressant use was associated with higher right PuA volume suggesting a possible protective effect of treatment. After follow-up, depression scores were associated with reduced white matter tract macrostructure across almost all tracts connected to thalamic subnuclei. In conclusion, our work implicates the right PuA as a relevant neural structure in PD depression and future work should evaluate its potential as a therapeutic target for PD depression.

scholarly journals The SARS-CoV-2 Alpha variant is associated with increased clinical severity of disease

2021 ◽  
Author(s):  
David J Pascall ◽  
Guy Mollett ◽  
Rachel Blacow ◽  
Naomi Bulteel ◽  
Robyn Campbell ◽  
...  
Keyword(s):  
Growth Rate ◽  
Cohort Study ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Transmission Rate ◽  
Severe Disease ◽  
Positive Association ◽  
Clinical Severity ◽  
Generalised Linear Mixed Model ◽  
The Impact

Background The Alpha (B.1.1.7) SARS-CoV-2 variant of concern has been associated with increased transmission and increased 28-day mortality. We aimed to investigate the impact of infection on clinical severity of illness, including the need for oxygen or ventilation in a national cohort study. Methods In this prospective clinical cohort study, 1475 SARS-CoV-2 sequences were obtained from patients infected in Scotland, UK between the 1st November 2020 and 30th January 2021 and matched to clinical outcomes as the lineage became dominant in Scotland. We modelled the association between B.1.1.7 infection and severe disease using a cumulative generalised linear mixed model employing a 4-point scale of maximum severity based on requirement of respiratory support at 28 days. We also estimated the growth rate of B.1.1.7-associated infections as it emerged in Scotland using a phylogenetic exponential growth rate population model. Results The B.1.1.7 lineage was responsible for a third wave of SARS-CoV-2 infection in Scotland in association with a transmission rate 5-fold higher than the preceding second wave B.1.177 lineage. Of 1475 patients, 364 were infected with B.1.1.7, 1030 with B.1.177 and 81 with other lineages. Our analysis found a positive association between increased clinical severity and lineage (B.1.1.7 versus non-B.1.1.7; cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93). Viral load was higher in B.1.1.7 samples than in non-B.1.1.7 samples, as measured by cycle threshold (Ct) value (mean Ct change: -2.46, 95% CI: -4.22, -0.70). Conclusions The B.1.1.7 lineage was associated with more severe clinical disease in Scottish patients than co-circulating lineages.

Symptomatic Relief is Related to Serum Free Triiodothyronine Concentrations during Follow-up in Levothyroxine-Treated Patients with Differentiated Thyroid Cancer

2018 ◽  
Vol 126 (09) ◽  
pp. 546-552 ◽  
Author(s):  
Rolf Larisch ◽  
John Midgley ◽  
Johannes Dietrich ◽  
Rudolf Hoermann
Keyword(s):  
Mixed Model ◽  
Clinical Decision Making ◽  
Linear Mixed Model ◽  
Reference Range ◽  
Symptomatic Relief ◽  
Symptom Relief ◽  
Multivariable Analysis ◽  
Free Triiodothyronine ◽  
Generalised Linear Mixed Model

Abstract Aim Patients on levothyroxine-treatment frequently have complaints although TSH is within the reference range. Moreover, FT3 is often low in these patients. The clinical significance of this disequilibrium is studied here. Patients, methods We conducted a retrospective longitudinal study including 319 patients with differentiated thyroid carcinoma on LT4-medication (1.8 [1.6,2.1] µg/kg body weight). Patients were followed at 2309 visits for at median 63 [46,81] months. Association of reported complaints during follow-up with changes in thyroid parameters were analysed using a generalised linear mixed model accounting for within-variability and intra-subject correlations. Results 26% of patients expressed hypothyroid and 9.7% hyperthyroid complaints at any one visit, rates per visit being 6.5% and 2%, respectively. During follow-up, median changes in spans were as follows, LT4-dose 0.49 [IQR 0.29,0.72] µg/kg, FT3 1.77 [1.25,2.32] pmol/l, FT4 9.80 [6.70,12.8] pmol/l and TSH 1.25 [0.42,2.36] mIU/l. While rates of both hypothyroid or hyperthyroid symptoms were significantly related to all three thyroid parameters, the relationship of hypothyroid symptoms with FT3 extended to a below reference TSH range. Hypothyroid symptom relief was associated with both a T4 dose giving TSH-suppression below the lower reference limit and FT3 elevated further into the upper half of its reference range. In multivariable analysis, relationships between complaints and FT3 concentrations remained significant after adjusting for gender, age and BMI. Conclusion Residual hypothyroid complaints in LT4-treated patients are specifically related to low FT3 concentrations. This supports an important role of FT3 for clinical decision making on dose adequacy, particularly in symptomatic athyreotic patients.

scholarly journals Comparison of approaches to interpolating climate observations in steep terrain with low-density gauging networks

2019 ◽  
Vol 23 (11) ◽  
pp. 4763-4781 ◽  
Author(s):  
Juan Ossa-Moreno ◽  
Greg Keir ◽  
Neil McIntyre ◽  
Michela Cameletti ◽  
Diego Rivera
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Mean Squared Error ◽  
Performance Criterion ◽  
Probability Of Detection ◽  
Monthly Precipitation ◽  
Low Density ◽  
Temperature And Precipitation ◽  
Generalised Linear Mixed Model ◽  
Approximate Bayesian

Abstract. The accuracy of hydrological assessments in mountain regions is often hindered by the low density of gauges coupled with complex spatial variations in climate. Increasingly, spatial datasets (i.e. satellite and other products) and new computational tools are merged with ground observations to address this problem. This paper presents a comparison of approaches of different complexities to spatially interpolate monthly precipitation and daily temperature time series in the upper Aconcagua catchment in central Chile. A generalised linear mixed model (GLMM) whose parameters are estimated through approximate Bayesian inference is compared with simpler alternatives: inverse distance weighting (IDW), lapse rates (LRs), and two methods that analyse the residuals between observations and WorldClim (WC) data or Climate Hazards Group Infrared Precipitation with Station data (CHIRPS). The assessment is based on a leave-one-out cross validation (LOOCV), with the root-mean-squared error (RMSE) being the primary performance criterion for both climate variables, while the probability of detection (POD) and false-alarm ratio (FAR) are also used for precipitation. Results show that for spatial interpolation of temperature and precipitation, the approaches based on the WorldClim or CHIRPS residuals may be recommended as being more accurate, easy to apply and relatively robust to tested reductions in the number of estimation gauges. The GLMM has comparable performance when all gauges were included and is better for estimating occurrence of precipitation but is more sensitive to the reduction in the number of gauges used for estimation, which is a constraint in sparsely monitored catchments.

scholarly journals The importance of genetic factors for the development of arthropathy: a longitudinal study of children and adolescents with haemophilia A

2017 ◽  
Vol 117 (02) ◽  
pp. 277-285 ◽  
Author(s):  
Edward D. Gomperts ◽  
John Schwarz ◽  
Sharyne M. Donfield ◽  
Alice E. Lail ◽  
Jan Astermark ◽  
...  
Keyword(s):  
Children And Adolescents ◽  
Genetic Factors ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Snp Markers ◽  
Haemophilia A ◽  
Full Model ◽  
Logistic Regression Models ◽  
Haemophilic Arthropathy ◽  
Generalised Linear Mixed Model

SummaryHaemophilia A is a congenital bleeding disorder characterised by recurrent haemorrhages into the major joints. Haemophilic arthropathy is a well-established outcome of recurrent joint bleeding; however, it is clear that multiple factors determine the extent and severity of its occurrence. We sought to identify genetic factors related to abnormalities in range of motion (ROM) in the knees, ankles and elbows in a cohort of children and adolescents with haemophilia A not treated primarily with regular prophylaxis. Using data from the Haemophilia Growth and Development Study, we examined associations between 13,342 genetic markers and ROM scores measured at six-month intervals for up to seven years. As a first step, ordered logistic regression models were fit for each joint separately. A subset of SNP markers showing significant effects (p<0.01) on the right and left sides for at least two joints were included in a full model fit using a multivariate generalised linear mixed model assuming an ordinal response. The models contained all ROM scores obtained at all visits. Twenty-five markers analysed in the full model showed either increased or decreased risk of ROM abnormalities at the p<0.001 level. Several genes identified at either the first or second stage of the analysis have been associated with arthritis in a variety of large studies. Our results support the likelihood that risk for haemophilic arthropathy is associated with genetic factors, the identification of which holds promise for further advancing the individualisation of treatment.

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